Artificial Intelligence

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Korean conglomerate SK leads $600M round for Chinese chipmaker Horizon Robotics

Horizon Robotics, a three-year-old Chinese startup backed by Intel Capital, just raised a mega-round of fundings from domestic and overseas backers as it competes for global supremacy in developing AI solutions and chips aimed at autonomous vehicles, smart retail stores, surveillance equipment and other devices for everyday scenarios.

The Beijing-based company announced Wednesday in a statement that it’s hauled in $600 million in a Series B funding round led by SK China, the China subsidiary of South Korean conglomerate SK Group; SK Hynix, SK’s semiconductor unit; and a number of undisclosed Chinese automakers along with their funds.

The fresh capital drove Horizon’s valuation to at least $3 billion, the company claims. The Financial Times previously reported that the chipmaker was raising up to $1 billion in a funding round that could value it at as much as $4 billion. Such a price tag could perhaps be justified by the vast amount of resources China has poured into the red-hot sector as part of a national push to shed dependency on imported chips and work towards what analysts call “semiconductor sovereignty.”

Horizon did not specify how the proceeds will be used. The company could not be immediately reached for comments.

In 2015, Yu Kai left Baidu as the Chinese search engine giant’s deep learning executive and founded Horizon to make the “brains” for a broad spectrum of connected devices. In doing so Yu essentially set himself up for a race against industry veterans like Intel and Nvidia. To date, the startup has managed to make a dent by securing government contracts, which provide a stable source of income for China’s AI upstarts including SenseTime, and several big-name clients like SK’s telecommunication unit, which is already leveraging Horizon’s algorithms to develop smart retail solutions. Like many of its peers who are at the forefront of the AI race, Horizon has set up an office in Silicon Valley and hiring local talents for its lab.

Other investors who joined the round included several of Horizon’s returning investors such as Hillhouse Capital and Morningside Venture Capital . There were also some heavyweight new backers, such as a fund run by conglomerate China Oceanwide Holdings as well as the CSOBOR Fund, a private equity entity set up by China’s state-owned CITIC to back projects pertaining to China’s ambitious “One Belt, One Road” modern Silk Road initiative.

Musiio raises $1M to let digital music services use AI for curation

Musiio, a Singapore-based startup that uses AI to help digital music companies with discovery and creation, has pulled in a $1 million seed round.

The capital comes from Singapore’s Wavemaker Partners, U.S. investor Exponential Creativity Ventures and undisclosed angels. The deal represents the first outside round for Musiio, which was founded at the Entrepreneur First program in Singapore where CEO Hazel Savage, a former streaming exec, met CEO Aron Pettersson. It also makes Musiio the first venture capital-backed music AI startup in Southeast Asia and one of the most notable EF graduates from its Asian cohorts.

We first wrote about Musiio last April when it had raised SG$75,000 ($57,000) as part of its involvement in EF, the London-based accelerator that has big ambitions in Asia. Since then, it has increased its team to seven full-time staff.

The company is focused on reducing inefficiencies for music curation using artificial intelligence by augmenting the important work of human curators. In short, it aims to give those without the spending power of Spotify the opportunity to automate or partially automate a lot of the heavy lifting when it comes to scouring through music.

“Musiio won’t replace the need to have people listening to music,” Savage told TechCrunch last year. “But we can delete the inefficiencies.”

The Musiio team at its office in Singapore

The company’s first public client is Free Music Archive (FMA), a Creative Commons-like free music site developed by independent U.S. radio station WFMU. Musiio developed a curated playlist which raised the profile of a number of songs that had become ‘lost’ in the catalog. In particular, it helped one track double the number of plays it had received over eight years within just two days.

The FMA deal was really a proof of concept for Musiio, and Savage said that the company is getting close to announcing deals.

“Over the next month or two, there will be two or three commercial announcements,” Savage said this week. “We’re working with streaming companies and sync companies.”

Apple’s long-time Siri leader reportedly no longer in charge

The man who has headed up Siri at Apple since 2012 is no longer at the helm, according to The Information. Bill Stasior remains at the company in a different role, the report states.

We’ve reached out to Apple for comment.

Stasior joined Apple to take over Siri in 2012 after being poached from Amazon’s A9 retail search team. At this in time, most of the original Siri co-founders had already left Apple and Stasior was tasked with taking on the mantle of deciding where the digital assistant should move next.

Siri has had a troubled history at Apple. Though the voice assistant arrived with a big splash, the company’s inability to iterate the product quickly left its competitors ample opportunity to leapfrog its capabilities. Something that both Amazon and Google clearly have with their Alexa and Google Assistant platforms.

This past April, Apple hired Google’s John Giannandrea to lead AI and machine learning efforts at the company, a division that includes Siri and CoreML. Giannandrea is expected to be leading the search for a new leader for the Siri team, the report says.

VCs give us their predictions for startups and tech in Southeast Asia in 2019

The new year is well underway and, before January is out, we polled VCs in Southeast Asia to get their thoughts on what to expect in 2019.

The number of VCs in the region has increased massively in recent years, in no small part due to forecasts of growth in the tech space as internet access continues to shoot up among Southeast Asia’s cumulative population of more than 600 million consumers.

There are other factors, including economic growth and emerging middle classes, but with more than 3.8 million people becoming first-time internet users each month — thanks to smartphones — Southeast Asia’s ‘digital economy’ is tipped to more than triple to reach $240 billion by 2025. That leaves plenty of opportunity for tech and online businesses and, by extension, venture capitalists.

With a VC corpus that now numbers dozens of investment firms, TechCrunch asked the people who write the checks what is on the horizon for 2019.

The only rule was no more than three predictions — below, in no particular order, is what they told us.


Albert Shyy, Burda

Funds will continue to invest aggressively in Southeast Asia in the first half of this year but capital will tighten up by Q4 as funds and companies prepare for a possible recession. I think we will see a lot of companies opportunistically go out to fundraise in Q1/Q2 to take advantage of a bull market.

We will see two to three newly-minted unicorns from the region this year, after a relative lull last year.

This will (finally) be the year that we start to see some consolidation in the e-commerce scene


Dmitry Levit, Cento

A significant portion of capital returned by upcoming U.S. IPOs to institutional investors will be directed to growth markets outside of China, with India and Southeast Asia being the likeliest beneficiaries. Alternative assets such as venture and subsets of private equity in emerging markets will enter their golden age.

The withdrawal of Chinese strategic players held back by weakened domestic economy, prudent M&A by local strategics and ongoing caution among Japanese, Korean and global corporates, combined with ongoing valuations exuberance by late-stage investors allocating funds to Southeast Asia, will continue holding back large liquidity events. Save perhaps for a roll-up of a local champion or two into a global IPO. Fundraising will get more troublesome for some of Southeast Asia’s larger unprofitable market leaders. Lack of marquee liquidity events and curtailed access to late-stage capital for some will lead to a few visible failures (our money is on the subsidy-heavy wallets!) and a temporary burst of short-term skepticism around Southeast Asia as an investment destination towards the end of 2019.

The trend towards the emergence of value-chain specific funds and fund managers will continue, as digitalization is reaching ever further into numerous industry sectors and as Southeast Asia hosts an increasing portion of global supply chains. We foresee at least dozen new venture firms and vehicles emerging in 2019 with clear sector-led investment thesis around the place of Southeast Asian economies in the global value chains of fashion industry, agriculture and food; labour, healthcare services; manufacturing, construction tech and so on, with investment teams that have the necessary expertise to unravel this increasing complexity.


Willson Cuaca, East Ventures

Jakarta becomes Southeast Asia’s startup capital surpassing Singapore in terms of the number of deals and investment amount.

As Indonesia’s startup scene heats up, regional seed and series A funds move away from Indonesia and target Vietnam, Malaysia, Thailand and the Philippines (in market priority order).

Southeast gets two new unicorns.


Rachel Lau, RHL Ventures

North Asian companies will provide well-needed liquidity as they withdraw capital from developed American and European markets due to the Federal Reserve’s actions. The FED raised interest rates and reduced the size of its balance sheet (by not replacing the bonds that were maturing at a rate of $50 billion a month). This has been seen in the recent fundraising exercise by Southeast Asian unicorns. Grab has recently seen an impressive list of North Asian investors such as Mirae, Toyota and Yamaha . A recent stat stated that 85 percent of the funding of Southeast Asia startups have gone to billion dollar unicorn such as Grab and Gojek, bypassing the early stage startups that are more in need for funding, this trend is expected to continue. Therefore, we will see early-stage companies and venture capitalists becoming more focused on generating cash flow from operating operations instead as fundraising activities become more difficult.

A growth in urbanization in Southeast will create new job opportunities in small/medium businesses, as evident in China. Currently, only 12 percent of Asia’s urban population live in megacities, while four percent live in towns of fewer than 300,000 inhabitants. New companies will see the blurred lines between brick and mortar businesses vs pure online businesses. In the past year or so, we have seen more and more offline businesses going online and more online businesses going offline.

Fertility rates in the Philippines, Laos, Cambodia, Indonesia and Vietnam exceed 2.1 births per woman — the level that sustains a population — but rates below 1.5 in Singapore and Thailand mean their populations will decline without immigration. As we see more startup activities coming to Southeast Asian countries, we expect to see more qualified foreign talent moving to the region vs staying in low growth American and European countries.


Kay-Mok Ku, Gobi Ventures

First Chinese “Seaward” Unicorn in Southeast Asia. In recent years, a growing number of Chinese startups are targeting overseas markets from the get go (known as Chuhai 出海 or “Seaward”). These Chinese entrepreneurs typically bring with them best practices in consumer marketing and product development honed by a hyper-competitive home market, supported by strong, dedicated technical team based out of China and increasingly capitalized by Chinese VCs which have raised billion-dollar funds.

Consolidation among ASEAN Unicorns. While ASEAN now boasts 10 unicorns, they are duplicative in the sense that more than one exists in a particular category, which is unsustainable for winner-takes-all markets. For example, in the ASEAN ride-hailing space, while one unicorn is busy with regional geographic expansion, the other simply co-exists by staying focused on scope expansion within its home market. This will never happen in a single country market like China but now that the ASEAN ride hailing unicorns are finally locking horns, the stage may be set for a Didi-Kuadi like scenario to unfold.

ASEAN jumps on Chinese 5G bandwagon. The tech world in the future will likely bifurcate into American and Chinese-led platforms. As it is, emerging markets are adopting Chinese business models based on bite-sized payment and have embraced Chinese mobile apps often bundled with cheap Chinese smartphones. Looking ahead, 5G will be a game changer as its impact goes beyond smartphones to generic IoT devices, having strategic implications for industries such as autonomous driving. As a result, the US-China Trade War will likely evolve into a Tech War and ASEAN will be forced to choose side.


Daren Tan, Golden Equator Capital

We are excited by growth in the AI and deep tech sectors. The focus has generally been on consumer-focused tech in Southeast Asia as an emerging market, but we are starting to see proprietary solutions emerge for industries such as medtech and fintech. AI also has great applicability across a wide range of consumer sectors in reducing reliance on manpower and creating cost savings.

Data analytics to uncover organizational efficiencies and customer trends will continue to be even more widely used, but there will also be greater emphasis on securing such data especially confidential information in light of multiple high-profile data breaches in 2018. Tools enabling the collection, storage, safe-keeping and analysis of data will be essential.

We are seeing the emergence of more institutional funds from North Asia. So far it has predominantly been Chinese tech giants like Tencent and Alibaba, now we are starting to see Korean and Japanese institutions placing greater emphasis on investment in the Southeast Asian region.


Vinnie Lauria, Golden Gate Ventures

Even more capital flowing from U.S. and China into Southeast Asia, with VCs from both locations soon to open offices in the region

A fresh wave of Series A investments into Vietnam.

Ten exits over $100 million.

 


Amit Anand, Jungle Ventures

The emergence of a financial services super app, think the Meituan or WeChat but only for financial services: The Southeast Asian millennial is one of the most underserved customer from a financial services perspective whether it is payments, consumer goods loans, personal loans, personal finance management, investments or other financial services. We will see the emergence of digital platforms that will aggregate all these related services and provide a one stop financial services shop for this digitally native consumer.

Digitisation of SMEs will be new fintech: Southeast Asia is home to over 100 million SMEs that are at the cusp of digital transformation. Generational change in ownership, local governments push for digitization and increased globalization have created a perfect storm for these SMEs to adopt cloud and other digital technologies at neck-breaking pace. Startups focussing on this segment will get mainstream attention from the venture community over the next few years as they look for new industries that are getting enabled or disrupted by technology.


Kuo-Yi Lim and Peng Ong, Monk’s Hill Ventures

Lyft and Uber go public and show the path to profitability for other rideshare businesses. This has positive effect for the regional rideshare players but also puts pressure on them to demonstrate the same economics in ridesharing. Regional rideshare players double down on super-app positioning instead, to demonstrate value in other ways as rideshare business alone may not reach profitability — ever.

The trade war between China and the US reaches a truce, but a general sense of uncertainty lingers. This is now the new norm — things are less certain and companies have to plan for more adverse scenarios. In the short term, Southeast Asia benefits. Companies — Chinese, American etc — see Southeast Asia as the neutral ground. Investment pours in, creating jobs across industries. Acquisition of local champions intensifies as foreign players jostle for the lead positions.

“Solve the problem” – tech companies will become more prominent… tech companies that are real-estate brokers, recruiters, healthcare providers, food suppliers, logistics… why: many industries are very inefficient.


Hian Goh, Openspace Ventures

Fight to quality will happen. Fundraising across all stages from seed to Series C and beyond will be challenging if you don’t have the metrics. Investors will want to see a path to profitability, or an ability to turn profitable if the environment becomes worse. This will mean Saas companies with stable cash flows, vertical e-commerce with strong metrics will be attractive investment opportunities.

Investor selection will become critical, as investors take a wait and see approach. Existing or new investors into companies will be judged upon their dry powder in their funds and their ability to fund further rounds

The regulatory risk for fintech lenders will be higher this year, rising compliance cost and uncertainty on licensing, which would lead to consolidation in the market.


Heang Chhor, Qualgro

Southeast Asia: an intensifying battlefield for tech investments

There has never been so much VC money in Southeast Asia chasing interesting startups, at all life cycle stages. The 10 most active local and regional VCs have raised their second or third funds recently, amassing at least two times more money than a few years ago, probably reaching a total amount close to $1 billion. In addition, international VCs have also doubled down on their allocation into the region, while top Chinese VCs have visibly stated their intent not to miss the dynamic momentum. Several growth funds have recently built a local presence in order to target Southeast Asia tech companies at Series C and beyond. Not counting the amount going to the unicorns, there might be now more than $3-4 billion available for seed to growth stages, which may be 3-4 times the amount of three years ago. There are, of course, many more good startups coming up to invest into. But the most promising startups will be in a very favorable position to negotiate higher valuation and better terms. However, they should not forget that, eventually, what creates value is how they make a difference with their tech capabilities or their business model, how they acquire and retain the best talent, with the funds raised, not only how much money they will be able to raise. Most local and regional corporate VCs are likely to lose in this more intense investment game.

Significant VC money investing into so-called ‘AI-based startups’, but are there really much (deep) Artificial Intelligence capabilities around?

A good portion of the SEA startups claim they have ‘something-AI’. Investors are overwhelmed, if not confused, by the ‘AI claim’ that they find in most startup pitches. While there is no doubt that Southeast Asia will grow its own strong AI-competence pool in the future, unfortunately today most ‘AI-based’ business models from the region would still be just ‘good algorithms or machine learning’ that can process some amount of data to come up with good-enough outcomes, that do not always generate substantial business value to users/customers. The significant budget that some of the very-well-funded Southeast Asia unicorns are putting into their ‘AI-based apps’ or ‘AI platform’ is unlikely to make a real difference for the consumers, for lack of deep AI competences in the region. 2019 may be another year of AI-promise, not realized. Hopefully, public and private research labs, universities and startups will continue to be (much more) strongly supported (especially by governments) to significantly build bigger AI talent pool, which means growing and attracting AI talent into the region.

Bigger Series A and Series B rounds to fuel more convincing growth trajectory, towards growth-stage fundraising.

Although situations vary a lot: typical Series A in Southeast Asia used to be around $5 million, and Series B around $10-15 million. Investors tended to accept that normally companies would raise money after 18 months or so, between A and B, and between B and C. There has been an increasing number of larger raises at A and B recently, and very likely this trend will accelerate. The fact that VCs now have much more money to deploy into each investment will contribute to this trend. However, the required milestones for raising Series C have become much more around: minimum scale and very solid growth (and profit) drivers. Therefore, entrepreneurs will have to look for getting as much funding reserve as possible, irrespective of time between raises, to build growth engines that take their companies past the milestones of the next Series, be it B or C. In the future, we will see more Series A of $10 million and more Series B of well-above $20 million. Compelling businesses will not have too much difficulties for doing so, but most Southeast Asia entrepreneurs would be wise to learn to more effectively master fundraising skills for capturing much bigger amounts than in the past. Of course, this assumes that their businesses are compelling enough in the eyes of investors.


Vicknesh R Pillay, TNB Aura

Out-sized valuations will be less commonplace in 2019 as Southeast Asian investors learn from experience and become more sophisticated. Therefore, we do see opportunities at Series A/B for undervalued deals due to lack of early-stage funding while we expect to continue to see the trend of the majority of venture capital investments going into later stage companies (Series C and beyond) due to lower risk appetite and ‘herd’ mentality.

2018 has also seen the rapid emergence of many corporate venture capital funds and innovation programs. But, 2019 will see large corporations cutting back on their allocation towards startup investing which would be the easiest option for them in case of adverse news to the jittery public markets in 2019.

With the growth of AI, the need for API connections and increased thought leadership to embrace tech, Southeast Asia is going to see an upsurge in SaaS startups and existing startups moving to a Saas business model. Hence, we expect increased investments into Saas companies focused on IoT and cybersecurity as hardware data and software are moved onto the cloud.


Chua Kee Lock, Vertex Ventures

Southeast Asia VC investment pace has grown steadily and significantly since 2010 where it started from less than $100 million in VC investment in the region. For the first eight months of 2018, the region’s VC investment was over $5.4 billion. For the whole of 2018, it will likely end around $8 billion. For 2019, we expect the VC investment pace to surpass 2018 level and record between $9-10 billion. Southeast Asia will continue to attract more VC investments because:

(1) Governments in Southeast Asia, especially ASEAN, continue their support policy to encourage startups.

(2) young demographics and the fast technology adoption in Southeast Asia give rise to more innovative and disruptive ideas.

(3) global investors looking for a better return and will naturally focus on growing emerging market like Southeast Asia.

The trend towards gig economy will begin to have an impact in the region. In developed economies like the U.S, gig economy is expected to reach over 40 percent by 2020. The young population will look for more freelance opportunities as a way to increase income levels while still maintaining flexibility. This will include white-collar work like computer programming, accounting, customer service, etc. and also blue-collar work like delivery services, ride-sharing, home services, etc. We believe that the gig economy will grow to over 15 percent in Southeast Asia by 2019.

AI-heavy or -driven startups will begin to make inroads into Southeast Asia.


Victor Chua, Vynn Capital

The BIG convergence — there will more integration between industries and sectors. Traveloka went into car rental, Blibli went into travel business and these are only some examples. There is a lot of synergistic value between travel startups and food startups or between property startups and automotive startups. Imagine a future where you travel to a city where you stay in an apartment you rented through a marketplace (like Travelio, my portfolio company), and when you need to book a restaurant you can make the reservation through a platform that is integrated with the property manager, and when you need to move around you go down to the car park to drive a car you rent from an automotive marketplace. There is clear synergy between selective industries and this leads to an overall convergence between companies, between industries.

More channels to raise Series B/C, early-stage companies find fundraising more challenging — We have seen a number of VC funds raising or already raised growth funds, this means that there are now more channels for Series A or B companies to raise growth rounds. As the market matures, there will be more competition for investments amongst growth funds as there is considerably more growth in the number of growth funds than companies that are raising at growth-stage. On the flip side, the feel is that there is a consistent growth in the number of early-stage companies, yet the amount of capital in early-stage funds is not growing as much as more VCs prefer bigger and later stages, due to the maturity of their existing portfolio companies.

Newcomers gaining weight — there will be at least 10 companies that will hit a valuation of at least $100 million. These valuations will not be based on a single market exposure. Companies that raise larger rounds will need to show that they are regional.


Thanks to all the VCs who took part, I certainly felt like the class teacher collecting assignments.

GBatteries let you charge your car as quickly as visiting the pump

A YC startup called GBatteries has come out of stealth with a bold claim: they can recharge an electric car as quickly as it takes to full up a tank of gas.

Created by aerospace engineer Kostya Khomutov, electrical engineers Alex Tkachenko and Nick Sherstyuk, and CCO Tim Sherstyuk, the company is funded by the likes of Airbus Ventures, Initialized Capital, Plug and Play, and SV Angel.

The system uses AI to optimize the charging systems in electric cars.

“Most companies are focused on developing new chemistries or materials (ex. Enevate, Storedot) to improve charging speed of batteries. Developing new materials is difficult, and scaling up production to the needs of automotive companies requires billions of $,” said Khomutov. “Our technology is a combination of software algorithms (AI) and electronics, that works with off-the-shelf Li-ion batteries that have already been validated, tested, and produced by battery manufacturers. Nothing else needs to change.”

The team makes some bold claims. The product allows users to charge a 60kWh EV battery pack with 119 miles of range in 15 minutes as compared to 15 miles in 15 minutes today. “The technology works with off-the-shelf lithium ion batteries and existing fast charge infrastructure by integrating via a patented self-contained adapter on a car charge port,” writes the team. They demonstrated their product at CES this year.

Most charging systems depend on fairly primitive systems for topping up batteries. Various factors – including temperature – can slow down or stop a charge. GBatteries manages this by setting a very specific charging model that “slows down” and “speeds up” the charge as necessary. This allows the charge to go much faster under the right conditions.

The company bloomed out of frustration.

“We’ve always tinkered with stuff together since before I was even a teenager, and over time had created a burgeoning hardware lab in our basement,” said Sherstyuk. “While I was studying Chemistry at Carleton University in Ottawa, we’d often debate and discuss why batteries in our phones got so bad so rapidly – you’d buy a phone, and a year later it would almost be unusable because the battery degraded so badly.”

“This sparked us to see if we can solve the problem by somehow extending the cycle life of batteries and achieve better performance, so that we’d have something that lasts. We spent a few weeks in our basement lab wiring together a simple control system along with an algorithm to charge a few battery cells, and after 6 months of testing and iterations we started seeing a noticeable difference between batteries charged conventionally, and ones using our algorithm. A year and a half later of constant iterations and development, we applied and were accepted in 2014 into YC.”

While it’s not clear when this technology will hit commercial vehicles, it could be the breakthrough we all need to start replacing our gas cars with something a little more environmentally-friendly.

Wandelbots raises $6.8M to make programming a robot as easy as putting on a jacket

Industrial robotics is on track to be worth around $20 billion by 2020, but while it may something in common with other categories of cutting-edge tech — innovative use of artificial intelligence, pushing the boundaries of autonomous machines that are disrupting pre-existing technology — there is one key area where it differs: each robotics firm uses its own proprietary software and operating systems to run its machines, making programming the robots complicated, time-consuming and expensive.

A startup out of Germany called Wandelbots (a portmanteau of “change” and “robots” in German) has come up with an innovative way to skirt around that challenge: it has built a bridge that connects the operating systems of the 12 most popular industrial robotics makers with what a business wants them to do, and now they can be trained by a person wearing a jacket kitted with dozens of sensors.

“We are providing a universal language to teach those robots in the same way, independent of the technology stack,” said CEO Christian Piechnick said in an interview. Essentially reverse engineering the process of how a lot of software is built, Wandelbots is creating what is a Linux-like underpinning to all of it.

With some very big deals under its belt with the likes of Volkwagen, Infineon and Midea, the startup out of Dresden has now raised €6 million ($6.8 million), a Series A to take it to its next level of growth and specifically to open an office in China. The funding comes from Paua VenturesEQT Ventures and other unnamed previous investors. (It had previously raised a seed round around the time it was a finalist in our Disrupt Battlefield last year, pre-launch.)

Notably, Paua has a bit of a history of backing transformational software companies (it also invests in Stripe), and EQT, being connected to a private equity firm, is treating this as a strategic investment that might be deployed across its own assets.

Piechnick — who co-founded Wandelbots with Georg Püschel, Maria Piechnick, Sebastian Werner, Jan Falkenberg and Giang Nguyen on the back of research they did at university — said that typical programming of industrial robots to perform a task could have in the past taken three months, the employment of specialist systems integrators, and of course an extra cost on top of the machines themselves.

Someone with no technical knowledge, wearing one of Wandelbots’ jackets, can bring that process down to 10 minutes, with costs reduced by a factor of ten.

“In order to offer competitive products in the face of the rapid changes within the automotive industry, we need more cost savings and greater speed in the areas of production and automation of manufacturing processes,” said Marco Weiß, Head of New Mobility & Innovations at Volkswagen Sachsen GmbH, in a statement. “Wandelbots’ technology opens up significant opportunities for automation. Using Wandelbots offering, the installation and setup of robotic solutions can be implemented incredibly quickly by teams with limited programming skills.”

Wandelbots’ focus at the moment is on programming robotic arms rather than the mobile machines that you may have seen Amazon and others using to move goods around warehouses. For now, this means that there is not a strong crossover in terms of competition between these two branches of enterprise robotics.

However, Amazon has been expanding and working on new areas beyond warehouse movements: it has, for example, been working ways of using computer vision and robotic arms to identify and pick out the most optimal fruits and vegetables out of boxes to put into grocery orders.

Innovations like that from Amazon and others could see more pressure for innovation among robotics makers, although Piechnick notes that up to now we’ve seen very little in the way of movement, and there may never be (creating more opportunity for companies like his that build more usability).

“Attempts to build robotics operating systems have been tried over and over again, and each time it’s failed,” he said. “But robotics has completely different requirements, such as real time computing, safety issues and many other different factors. A robot in operation is much more complicated than a phone.” He also added that Wandelbots itself has a number of innovations of its own currently going through the patent process, which will widen its own functionality too in terms of what and how its software can train a robot to do. (This may see more than jackets enter the mix.)

As with companies in the area of robotic process automation — which uses AI to take over more mundane back-office features — Piechnick maintains that what he has built, and the rise of robotics overall, is not going to replace workers, but put them on to other roles, while allowing businesses to expand the scope of what they can do that a human might never have been able to execute.

“No company we work with has ever replaced a human worker with a robot,” he said, explaining that generally the upgrade is from machine to better machine. “It makes you more efficient and cost reductive, and it allows you to put your good people on more complicated tasks.”

Currently, Wandelbots is working with large-scale enterprises, although ultimately, it’s smaller businesses that are its target customer, he said.

“Previously the ROI on robots was too difficult for SMEs,” he said. “With our tech this changes.”

“Wandelbots will be one of the key companies enabling the mass-adoption of industrial robotics by revolutionizing how robots are trained and used,” said Georg Stockinger, Partner at Paua Ventures, in a statement. “Over the last few years, we’ve seen a steep decline in robotic hardware costs. Now, Wandelbots’ resolves the remaining hurdle to disruptive growth in industrial automation – the ease and speed of implementation and teaching. Both factors together will create a perfect storm, driving the next wave of industrial revolution.”

 

 

Korean AI startup Skelter Labs lands strategic investment to expand to Southeast Asia

Korean AI startup Skelter Labs is expanding to Southeast Asia after it pulled in undisclosed funding from Singapore-based VC firm Golden Gate Ventures.

Skelter Labs was founded in 2015 by founded by Ted Cho, the former engineering site director at Google Korea. It started out developing apps and services that made use of AI but then it pivoted to focus fully on AI tech, which it licenses out to companies and corporations that it works with. Now it is eying opportunities in  Japan and parts of Southeast Asia — which has a cumulative population of over 600 million — with Vietnam, Thailand and Malaysia specifically mentioned.

The startup raised a $9 million seed round earlier this year, and Golden Gate has added an additional check to that round which came from KakaoBrain — the AI unit of Korean messaging giant Kakao — Kakao’s K-Cute venture arm, Stonebridge Ventures and Lotte Homeshopping, the TV and internet shopping business owned by multi-billion dollar retail giant Lotte.

More specifically, Seoul-based Skelter Labs works on AI in the context of vision and speech, conversation, and context recognition, while it goes after customers in areas that include manufacturing, customer operations, device interaction, and consumer marketing.

The startup doesn’t disclose customers, but it previously told TechCrunch that its vision is to bring its machine learning technology to daily life and schedules. Possible examples of that might be could include “intelligent virtual assistant technology that can be widely applied to various areas including smart speakers, smartphones, home appliances, automobiles and wearable devices.”

Golden Gate is one of Southeast Asia’s longest running tech VC firms. This deal is part of its recently announced third fund, which is $100 million in size.

In a statement, Skelter Labs CEO Cho paid tribute to the VC’s strong footprint in Southeast Asia that he said could open doors for the company. Startups in Golden Gate’s portfolio that might be of particular interest could include mobile listings startup Carousell, auto portal Carro, fashion commerce site Grana and online furnishings seller Hipvan.

Note: The original version of this article has been corrected. Skelter Labs has announced an extension to its previous round not a new round. Apologies for any confusion caused.

Facial recognition startup Kairos founder continues to fight attempted takeover

There’s some turmoil brewing over at Miami-based facial recognition startup Kairos . Late last month, New World Angels President and Kairos board chairperson Steve O’Hara sent a letter to Kairos founder Brian Brackeen notifying him of his termination from the role of chief executive officer. The termination letter cited willful misconduct as the cause for Brackeen’s termination. Specifically, O’Hara said Brackeen misled shareholders and potential investors, misappropriated corporate funds, did not report to the board of directors and created a divisive atmosphere.

Kairos is trying to tackle the society-wide problem of discrimination in artificial intelligence. While that’s not the company’s explicit mission — it’s to provide authentication tools to businesses — algorithmic bias has long been a topic the company, especially Brackeen, has addressed.

Brackeen’s purported termination was followed by a lawsuit, on behalf of Kairos, against Brackeen, alleging theft, a breach of fiduciary duties — among other things. Brackeen, in an open letter sent a couple of days ago to shareholders — and one he shared with TechCrunch — about the “poorly constructed coup,” denies the allegations and details his side of the story. He hopes that the lawsuit will be dismissed and that he will officially be reinstated as CEO, he told TechCrunch. As it stands today, Melissa Doval who became CFO of Kairos in July, is acting as interim CEO.

“The Kairos team is amazing and resilient and has blown me away with their commitment to the brand,” Doval told TechCrunch. “I’m humbled by how everybody has just kind of stuck around in light of everything that has transpired.”

The lawsuit, filed on October 10 in Miami-Dade and spearheaded by Kairos COO Mary Wolff, alleges Brackeen “used his position as CEO and founder to further his own agenda of gaining personal notoriety, press, and a reputation in the global technology community” to the detriment of Kairos. The lawsuit describes how Brackeen spent less than 30 percent of his time in the company’s headquarters, “even though the Company was struggling financially.”

Other allegations detail how Brackeen used the company credit card to pay for personal expenses and had the company pay for a car he bought for his then-girlfriend. Kairos alleges Brackeen owes the company at least $60,000.

In his open letter, Brackeen says, “Steve, Melissa and Mary, as cause for my termination and their lawsuit against me, have accused me of stealing 60k from Kairos, comprised of non-work related travel, non-work related expenses, a laptop, and a beach club membership,” Brackeen wrote in a letter to shareholders. “Let’s talk about this. While I immediately found these accusations absurd, I had to consider that, to people on the outside of  ‘startup founder’ life— their claims could appear to be salacious, if not illegal.”

Brackeen goes on to say that none of the listed expenses — ranging from trips, meals, rides to iTunes purchases — were not “directly correlated to the business of selling Kairos to customers and investors, and growing Kairos to exit,” he wrote in the open letter. Though, he does note that there may be between $3,500 to $4,500 worth of charges that falls into a “grey area.”

“Conversely, I’ve personally invested, donated, or simply didn’t pay myself in order to make payroll for the rest of the team, to the tune of over $325,000 dollars,” he wrote. “That’s real money from my accounts.”

Regarding forcing Kairos to pay for his then-girlfriend’s car payments, Brackeen explains:

On my making Kairos ‘liable to make my girlfriend’s car payment’— in order to offset the cost of Uber rides to and from work, to meetings, the airport, etc, I determined it would be more cost effective to lease a car. Unfortunately, after having completely extended my personal credit to start and keep Kairos operating, it was necessary that the bank note on the car be obtained through her credit. The board approved the $700 per month per diem arrangement, which ended when I stopped driving the vehicle. Like their entire case— its not very sensational, when truthfully explained.

The company also claims Brackeen has interfered with the company and its affairs since his termination. Throughout his open letter, Brackeen refers to this as an “attempted termination” because, as advised by his lawyers, he has not been legally terminated. He also explains how, in the days leading up to his ouster, Brackeen was seeking to raise additional funding because in August, “we found ourselves in the position of running low on capital.” While he was presenting to potential investors in Singapore, Brackeen said that’s “when access to my email and documents was cut.”

He added, “I traveled to the other side of the world to work with my team on IP development and meet with the people who would commit to millions in investment— and was fired via voicemail the day after I returned.”

Despite the “termination” and lawsuit, O’Hara told TechCrunch via email that “in the interest of peaceful coexistence, we are open to reaching an agreement to allow Brian to remain part of the family as Founder, but not as CEO and with very limited responsibilities and no line authority.”

O’Hara also noted the company’s financials showed there was $44,000 in cash remaining at the end of September. He added, “Then reconcile it with the fact that Brian raised $6MM in 2018 and ask yourself, how does a company go through that kind of money in under 9 months.”

Within the next twelve days, there will be a shareholder vote to remove the board, as well as a vote to reinstate Brackeen as CEO, he told me. After that, Brackeen said he intends to countersue Doval, O’Hara and Wolff.

In addition to New World Angels, Kairos counts Kapor Capital, Backstage Capital and others as investors. At least one investor, Arlan Hamilton of Backstage Capital, has publicly come out in support of Brackeen.

I’m proud of @BrianBrackeen. I’m honored to be his friend. He has handled recent events with his company with grace and patience, and has every right to be screaming inside. I’ve got his back. And he & I only want the best for @LoveKairos.

Certain distractions will be fleeting.

— Arlan 👊🏾 (@ArlanWasHere) October 25, 2018

As previously mentioned, Brackeen has been pretty outspoken about the ethical concerns of facial recognition technologies. In the case of law enforcement, no matter how accurate and unbiased these algorithms are, facial recognition software has no business in law enforcement, Brackeen said at TechCrunch Disrupt in early September. That’s because of the potential for unlawful, excessive surveillance of citizens.

Given the government already has our passport photos and identification photos, “they could put a camera on Main Street and know every single person driving by,” Brackeen said.

And that’s a real possibility. In the last couple of months, Brackeen said Kairos turned down a government request from Homeland Security, seeking facial recognition software for people behind moving cars.

“For us, that’s completely unacceptable,” Brackeen said.

Whether that’s entirely unacceptable for Doval, the interim CEO of Kairos, is not clear. In an interview with TechCrunch, Doval said, “we’re committed to being a responsible and ethical vendor” and that “we’re going to continue to champion the elimination of algorithmic bias in artificial intelligence.” While that’s not a horrific thing to say, it’s much vaguer than saying, “No, we will not ever sell to law enforcement.”

Selling to law enforcement could be lucrative, but that comes with ethical risks and concerns. But if the company is struggling financially, maybe the pros could outweigh the cons.

Oracle acquires DataFox, a developer of ‘predictive intelligence as a service’ across millions of company records

Oracle today announced that it has made another acquisition, this time to enhance both the kind of data that it can provide to its business customers, and its artificial intelligence capabilities: it is buying DataFox, a startup that has amassed a huge company database — currently covering 2.8 million public and private businesses, adding 1.2 million each year — and uses AI to analyse that to make larger business predictions. The business intelligence resulting from that service can in turn be used for a range of CRM-related services: prioritising sales accounts, finding leads, and so on.

“The combination of Oracle and DataFox will enhance Oracle Cloud Applications with an extensive set of AI-derived company-level data and signals, enabling customers to reach even better decisions and business outcomes,” noted Steve Miranda, EVP of applications development at Oracle, in a note to DataFox customers announcing the deal. He said that DataFox will sit among Oracle’s existing portfolio of business planning services like ERP, CX, HCM and SCM. “Together, Oracle and DataFox will enrich cloud applications with AI-driven company-level data, powering recommendations to elevate business performance across the enterprise.”

Terms of the deal do not appear to have been disclosed but we are trying to find out. DataFox — which launched in 2014 as a contender in the TC Battlefield at Disrupt — had raised just under $19 million and was last valued at $33 million back in January 2017, according to PitchBook. Investors in the company included Slack, GV, Howard Linzon, and strategic investor Goldman Sachs among others.

Oracle said that it is not committing to a specific product roadmap for DataFox longer term, but for now it will be keeping the product going as is for those who are already customers. The startup counted Goldman Sachs, Bain & Company and Twilio among those using its services. 

The deal is interesting for a couple of reasons. First, it shows that larger platform providers are on the hunt for more AI-driven tools to provide an increasingly sophisticated level of service to customers. Second, in this case, it’s a sign of how content remains a compelling proposition, when it is presented and able to be manipulated for specific ends. Many customer databases can get old and out of date, so the idea of constantly trawling information sources in order to create the most accurate record of businesses possible is a very compelling idea to anyone who has faced the alternative, and that goes even more so in sales environments when people are trying to look their sharpest.

It also shows that, although both companies have evolved quite a lot, and there are many other alternatives on the market, Oracle remains in hot competition with Salesforce for customers and are hoping to woo and keep more of them with the better, integrated innovations. That also points to Oracle potentially cross and up-selling people who come to them by way of DataFox, which is an SaaS that pitches itself very much as something anyone can subscribe to online.

Not hog dog? PixFood lets you shoot and identify food

What happens when you add AI to food? Surprisingly, you don’t get a hungry robot. Instead you get something like PixFood. PixFood lets you take pictures of food, identify available ingredients, and, at this stage, find out recipes you can make from your larder.

It is privately funded.

“There are tons of recipe apps out there, but all they give you is, well, recipes,” said Tonnesson. “On the other hand, PixFood has the ability to help users get the right recipe for them at that particular moment. There are apps that cover some of the mentioned, but it’s still an exhausting process – since you have to fill in a 50-question quiz so it can understand what you like.”

They launched in August and currently have 3,000 monthly active users from 10,000 downloads. They’re working on perfecting the system for their first users.

“PixFood is AI-driven food app with advanced photo recognition. The user experience is quite simple: it all starts with users taking a photo of any ingredient they would like to cook with, in the kitchen or in the supermarket,” said Tonnesson. “Why did we do it like this? Because it’s personalized. After you take a photo, the app instantly sends you tailored recipe suggestions! At first, they are more or le

ss the same for everyone, but as you continue using it, it starts to learn what you precisely like, by connecting patterns and taking into consideration different behaviors.”

In my rudimentary tests the AI worked acceptably well and did not encourage me to eat a monkey. While the app begs the obvious question – why not just type in “corn?” – it’s an interesting use of vision technology that is definitely a step in the right direction.

 

Tonnesson expects the AI to start connecting you with other players in the food space, allowing you to order corn (but not a monkey) from a number of providers.

“Users should also expect partnerships with restaurants, grocery, meal-kit, and other food delivery services will be part of the future experiences,” he said.

Robotics-as-a-service is on the way and inVia Robotics is leading the charge

The team at inVia Robotics didn’t start out looking to build a business that would create a new kind of model for selling robotics to the masses, but that may be exactly what they’ve done.

After their graduation from the University of Southern California’s robotics program, Lior Alazary, Dan Parks, and Randolph Voorhies, were casting around for ideas that could get traction quickly.

“Our goal was to get something up and running that could make economic sense immediately,’ Voorhies, the company’s chief technology officer, said in an interview.

The key was to learn from the lessons of what the team had seen as the missteps of past robotics manufacturers.

Despite the early success of iRobot, consumer facing or collaborative robots that could operate alongside people had yet to gain traction in wider markets.

Willow Garage, the legendary company formed by some of the top names in the robotics industry had shuttered just as Voorhies and his compatriots were graduating, and Boston Dynamics, another of the biggest names in robotics research, was bought by Google around the same time — capping an six-month buying spree that saw the search giant acquire eight robotics companies.

In the midst of all this we were looking around and we said, ‘God there were a lot of failed robotics companies!’ and we asked ourselves why did that happen?” Voorhies recalled. “A lot of the hardware companies that we’d seen, their plan was: step one build a really cool robot and step three: an app ecosystem will evolve and people will write apps and the robot will sell like crazy. And nobody had realized how to do step 2, which was commercialize the robot.”

So the three co-founders looked for ideas they could take to market quickly.

The thought was building a robot that could help with mobility and reaching for objects. “We built a six-degree-of-freedom arm with a mobile base,” Voorhies said.

However, the arm was tricky to build, components were expensive and there were too many variables in the environment for things to go wrong with the robot’s operations. Ultimately the team at inVia realized that the big successes in robotics were happening in controlled environments. 

“We very quickly realized that the environment is too unpredictable and there were too many different kinds of things that we needed to do,” he said. 

Parks then put together a white paper analyzing the different controlled environments where collaborative robots could be most easily deployed. The warehouse was the obvious choice.

Back in March of 2012 Amazon had come to the same conclusion and acquired Kiva Systems in a $775 million deal that brought Kiva’s army of robots to Amazon warehouses and distribution centers around the world.

“Dan put a white paper together for Lior and I,” Voorhies said, “and the thing really stuck out was eCommerce logistics. Floors tend to be concrete slabs; they’re very flat with very little grade, and in general people are picking things off a shelf and putting them somewhere else.”

With the idea in place, the team, which included technologists Voorhies and Parks, and Lazary, a serial entrepreneur who had already exited from two businesses, just needed to get a working prototype together.

Most warehouses and shipping facilities that weren’t Amazon were using automated storage and retrieval systems, Voorhies said. These big, automated systems that looked and worked like massive vending machines. But those systems, he said, involved a lot of sunk costs, and weren’t flexible or adaptable.

And those old systems weren’t built for random access patterns and multi-use orders which comprise most of the shipping and packing that are done as eCommerce takes off.

With those sunk costs though, warehouses are reluctant to change the model. The innovation that Voorhies and his team came up with, was that the logistics providers wouldn’t have to.

“We didn’t like the upfront investment, not just to install one but just to start a company to build those things,” said Voorhies. “We wanted something we could bootstrap ourselves and grow very organically and just see wins very very quickly. So we looked at those ASRS systems and said why don’t we build mobile robots to do this.”

In the beginning, the team at inVia played with different ways to build the robot.l first there was a robot that could carry several different objects and another that would be responsible for picking.

The form factor that the company eventually decided on was a movable puck shaped base with a scissor lift that can move a platform up and down. Attached to the back of the platform is a robotic arm that can extend forward and backward and has a suction pump attached to its end. The suction pump drags boxes onto a platform that are then taken to a pick and pack employee.

We were originally going to grab individual product.s. Once we started talking to real warehouses more and more we realized that everyone stores everything in these boxes anyway,” said Voorhies. “And we said why don’t we make our lives way easier, why don’t we just grab those totes?” 

Since bootstrapping that initial robot, inVia has gone on to raise $29 million in financing to support its vision. Most recently with a $20 million round which closed in July.

“E-commerce industry growth is driving the need for more warehouse automation to fulfill demand, and AI-driven robots can deliver that automation with the flexibility to scale across varied workflows. Our investment in inVia Robotics reflects our conviction in AI as a key enabler for the supply chain industry,” said Daniel Gwak, Co-Head, AI Investments at Point72 Ventures, the early stage investment firm formed by the famed hedge fund manager, Steven Cohen.

Given the pressures on shipping and logistics companies, it’s no surprise that the robotics and automation are becoming critically important strategic investments, or that venture capital is flooding int the market. In the past two months alone, robotics companies targeting warehouse and retail automation have raised nearly $70 million in new financing. They include the recent raised $17.7 million for the French startup Exotec Solutions and Bossa Nova’s $29 million round for its grocery store robots.

Then there are warehouse-focused robotics companies like Fetch Robotics, which traces its lineage back to Willow Garage and Locus Robotics, which is linked to the logistics services company Quiet Logistics.

“Funding in robotics has been incredible over the past several years, and for good reason,” said John Santagate, Research Director for Commercial Service Robotics at Research and Analysis Firm IDC, in a statement. “The growth in funding is a function of a market that has become accepting of the technology, a technology area that has matured to meet market demands, and vision of the future that must include flexible automation technology. Products must move faster and more efficiently through the warehouse today to keep up with consumer demand and autonomous mobile robots offer a cost-effective way to deploy automation to enable speed, efficiency, and flexibility.”

The team at inVia realized it wasn’t enough to sell the robots. To give warehouses a full sense of the potential cost savings they could have with inVia’s robots, they’d need to take a page from the software playbook. Rather than selling the equipment, they’d sell the work the robots were doing as a service.

“Customers will ask us how much the robots cost and that’s sort of irrelevant,” says Voorhies. “We don’t want customers to think about those things at all.”

Contracts between inVia and logistics companies are based on the unit of work done, Voorhies said. “We charge on the order line,” says Voorhies. “An order line is a single [stock keeping unit] that somebody would order regardless of quantity… We’re essentially charging them every time a robot has to bring a tote and present it in front of a person. The faster we’re able to do that and the less robots we can use to present an item the better our margins are.”

It may not sound like a huge change, but those kinds of efficiencies matter in warehouses, Voorhies said. “If you’re a person pushing a cart in a warehouse that cart can have 35 pallets on it. With us, that person is standing still, and they’re really not limited to a single cart. They are able to fill 70 orders at the same time rather than 55,” he said.

At Rakuten logistics, the deployment of inVia’s robots are already yielding returns, according to Michael Manzione, the chief executive officer of Rakuten Super Logistics.

“Really [robotics] being used in a fulfillment center is pretty new,” said Manzione in an interview. “We started looking at the product in late February and went live in late March.”

For Manzione, the big selling point was scaling the robots quickly, with no upfront cost. “The bottom line is ging to be effective when we see planning around the holiday season,” said Manzione. “We’re not planning on bringing in additional people, versus last year when we doubled our labor.”

As Voorhies notes, training a team to work effectively in a warehouse environment isn’t easy.

The big problem is that it’s really hard to hire extra people to do this. In a warehouse there’s a dedicated core team that really kicks ass and they’re really happy with those pickers and they will be happy with what they get from whatever those people can sweat out in a shift,” Voorhies said. “Once you need to push your throughput beyond what your core team can do it’s hard to find people who can do that job well.” 

SessionM customer loyalty data aggregator snags $23.8 M investment

SessionM announced a $23.8 million Series E investment led by Salesforce Ventures. A bushel of existing investors including Causeway Media Partners, CRV, General Atlantic, Highland Capital and Kleiner Perkins Caufield & Byers also contributed to the round. The company has now raised over $97 million.

At its core, SessionM aggregates loyalty data for brands to help them understand their customer better, says company co-founder and CEO Lars Albright. “We are a customer data and engagement platform that helps companies build more loyal and profitable relationships with their consumers,” he explained.

Essentially that means, they are pulling data from a variety of sources and helping brands offer customers more targeted incentives, offers and product recommendations “We give [our users] a holistic view of that customer and what motivates them,” he said.

Screenshot: SessionM (cropped)

To achieve this, SessionM takes advantage of machine learning to analyze the data stream and integrates with partner platforms like Salesforce, Adobe and others. This certainly fits in with Adobe’s goal to build a customer service experience system of record and Salesforce’s acquisition of Mulesoft in March to integrate data from across an organization, all in the interest of better understanding the customer.

When it comes to using data like this, especially with the advent of GDPR in the EU in May, Albright recognizes that companies need to be more careful with data, and that it has really enhanced the sensitivity around stewardship for all data-driven businesses like his.

“We’ve been at the forefront of adopting the right product requirements and features that allow our clients and businesses to give their consumers the necessary control to be sure we’re complying with all the GDPR regulations,” he explained.

The company was not discussing valuation or revenue. Their most recent round prior to today’s announcement, was a Series D in 2016 for $35 million also led by Salesforce Ventures.

SessionM, which was founded in 2011, has around 200 employees with headquarters in downtown Boston. Customers include Coca-Cola, L’Oreal and Barney’s.

Cogito scores $37M as AI-driven sentiment analysis biz grows

Cogito announced a $37 million Series C investment today led by Goldman Sachs Growth Equity. Previous investors Salesforce Ventures and OpenView also chipped in. Mark Midle of Goldman Sachs’ Merchant Banking Division, has joined Cogito’s Board of Directors

The company has raised over $64 million since it emerged from the MIT Human Dynamics Lab back in 2007 trying to use the artificial intelligence technology available at the time to understand sentiment and apply it in a business context.

While it took some time for the technology to catch up with the vision, and find the right use case, company CEO and founder Joshua Feast says today they are helping customer service representatives understand the sentiment and emotional context of the person on the line and give them behavioral cues on how to proceed.

“We sell software to very large software, premium brands with many thousands of people in contact centers. The purpose of our solution is to help provide a really wonderful service experience in moments of truth,” he explained. Anyone who deals with a large company’s customer service has likely felt there is sometimes a disconnect between the person on the phone and their ability to understand your predicament and solve your problem.

Cogito in action giving customer service reps real-time feedback.

He says using his company’s solution, which analyzes the contents of the call in real time, and provides relevant feedback, the goal is to not just complete the service call, but to leave the customer feeling good about the brand and the experience. Certainly a bad experience can have the opposite effect.

He wants to use technology to make the experience a more human interaction and he recognizes that as an organization grows, layers of business process make it harder for the customer service representative to convey that humanity. Feast believes that technology has helped create this problem and it can help solve it too.

While the company is not talking about valuation or specific revenue at this point, Feast reports that revenue has grown 3X over the last year. Among their customers are Humana and Metlife, two large insurance companies, each with thousands of customer service agents.

Cogito is based in downtown Boston with 117 employees at last count, and of course they hope to use the money to add on to that number and help scale this vision further.

“This is about scaling our organization to meet client’s needs. It’s also about deepening what we do. In a lot of ways, we are only scratching the surface [of the underlying technology] in terms of how we can use AI to support emotional connections and help organizations be more human,” Feast said.

AnyVision AI startup locks in $28M for its body and facial recognition tech

As image recognition advances continue to accelerate, startups with a mind towards security applications are seeing some major interest to turn surveillance systems more intelligent.

AnyVision is working on face, body and object recognition tech and the underlying system infrastructure to help companies deploy smart cameras for various purposes. The tech works when deployed on most types of camera and does not require highly sophisticated sensors to operate, the company says

“It’s not just how accurate the system is, it’s also how much it scales,” Etshtein tells TechCrunch. “You can put more than 20 concurrent full HD camera streams on a single GPU.”

The Tel Aviv-based AI startup announced today that it has closed a $28 million Series A funding round led by Bosch. The quickly growing company already has 130 employees and has plans to open up three new offices by the year’s end.

Right now, AnyVision is working on products in a few different verticals. Its security product called “Better Tomorrow” has been a key focus for the company.

Even as tech giants in the U.S. like Amazon and Google are scrutinized for contracts with government orgs that involve facial recognition tech, Etshtein believes that their company’s solution will be an improvement over existing video surveillance technologies in terms of protecting the public’s privacy.

“Today, the video management systems basically record everything and you can see individuals faces, you can see everything.”Etshtein says. “Once our system is installed it pixelates all the faces in the stream automatically, even the operator in the control center cannot see your face because the mathematical models just represent the persons of interest.”

The company also recently released a product called FaceKey that leverages the company’s facial recognition tech for verification purposes, allowing customers with phones that are not just the iPhone X to use their face as a two-factor authentication method in things like banking apps. Now, there have certainly been a lot of issues with maintaining the needed accuracy which is exactly what has made FaceID so novel, but AnyVision CEO Eylon Etshtein claims to have “cracked the problem.”

Other products AnyVision is working on include some new efforts in the sports and entertainment spaces as well as a retail analytics platform that they’re hoping to release later this summer.

Machine learning boosts Swiss startup’s shot at human-powered land speed record

The current world speed record for riding a bike down a straight, flat road was set in 2012 by a Dutch team, but the Swiss have a plan to topple their rivals — with a little help from machine learning. An algorithm trained on aerodynamics could streamline their bike, perhaps cutting air resistance by enough to set a new record.

Currently the record is held by Sebastiaan Bowier, who in 2012 set a record of 133.78 km/h, or just over 83 mph. It’s hard to imagine how his bike, which looked more like a tiny landbound rocket than any kind of bicycle, could be significantly improved on.

But every little bit counts when records are measured down a hundredth of a unit, and anyway, who knows but that some strange new shape might totally change the game?

To pursue this, researchers at the École Polytechnique Fédérale de Lausanne’s Computer Vision Laboratory developed a machine learning algorithm that, trained on 3D shapes and their aerodynamic qualities, “learns to develop an intuition about the laws of physics,” as the university’s Pierre Baqué said.

“The standard machine learning algorithms we use to work with in our lab take images as input,” he explained in an EPFL video. “An image is a very well-structured signal that is very easy to handle by a machine-learning algorithm. However, for engineers working in this domain, they use what we call a mesh. A mesh is a very large graph with a lot of nodes that is not very convenient to handle.”

Nevertheless, the team managed to design a convolutional neural network that can sort through countless shapes and automatically determine which should (in theory) provide the very best aerodynamic profile.

“Our program results in designs that are sometimes 5-20 percent more aerodynamic than conventional methods,” Baqué said. “But even more importantly, it can be used in certain situations that conventional methods can’t. The shapes used in training the program can be very different from the standard shapes for a given object. That gives it a great deal of flexibility.”

That means that the algorithm isn’t just limited to slight variations on established designs, but it also is flexible enough to take on other fluid dynamics problems like wing shapes, windmill blades or cars.

The tech has been spun out into a separate company, Neural Concept, of which Baqué is the CEO. It was presented today at the International Conference on Machine Learning in Stockholm.

A team from the Annecy University Institute of Technology will attempt to apply the computer-honed model in person at the World Human Powered Speed Challenge in Nevada this September — after all, no matter how much computer assistance there is, as the name says, it’s still powered by a human.

Apple’s Shortcuts will flip the switch on Siri’s potential

Matthew Cassinelli
Contributor

Matthew Cassinelli is a former member of the Workflow team and works as an independent writer and consultant. He previously worked as a data analyst for VaynerMedia.

At WWDC, Apple pitched Shortcuts as a way to ”take advantage of the power of apps” and ”expose quick actions to Siri.” These will be suggested by the OS, can be given unique voice commands, and will even be customizable with a dedicated Shortcuts app.

But since this new feature won’t let Siri interpret everything, many have been lamenting that Siri didn’t get much better — and is still lacking compared to Google Assistant or Amazon Echo.

But to ignore Shortcuts would be missing out on the bigger picture. Apple’s strengths have always been the device ecosystem and the apps that run on them.

With Shortcuts, both play a major role in how Siri will prove to be a truly useful assistant and not just a digital voice to talk to.

Your Apple devices just got better

For many, voice assistants are a nice-to-have, but not a need-to-have.

It’s undeniably convenient to get facts by speaking to the air, turning on the lights without lifting a finger, or triggering a timer or text message – but so far, studies have shown people don’t use much more than these on a regular basis.

People don’t often do more than that because the assistants aren’t really ready for complex tasks yet, and when your assistant is limited to tasks inside your home or commands spoken inton your phone, the drawbacks prevent you from going deep.

If you prefer Alexa, you get more devices, better reliability, and a breadth of skills, but there’s not a great phone or tablet experience you can use alongside your Echo. If you prefer to have Google’s Assistant everywhere, you must be all in on the Android and Home ecosystem to get the full experience too.

Plus, with either option, there are privacy concerns baked into how both work on a fundamental level – over the web.

In Apple’s ecosystem, you have Siri on iPhone, iPad, Apple Watch, AirPods, HomePod, CarPlay, and any Mac. Add in Shortcuts on each of those devices (except Mac, but they still have Automator) and suddenly you have a plethora of places to execute these all your commands entirely by voice.

Each accessory that Apple users own will get upgraded, giving Siri new ways to fulfill the 10 billion and counting requests people make each month (according to Craig Federighi’s statement on-stage at WWDC).

But even more important than all the places where you can use your assistant is how – with Shortcuts, Siri gets even better with each new app that people download. There’s the other key difference: the App Store.

Actions are the most important part of your apps

iOS has always had a vibrant community of developers who create powerful, top-notch applications that push the system to its limits and take advantage of the ever-increasing power these mobile devices have.

Shortcuts opens up those capabilities to Siri – every action you take in an app can be shared out with Siri, letting people interact right there inline or using only their voice, with the app running everything smoothly in the background.

Plus, the functional approach that Apple is taking with Siri creates new opportunities for developers provide utility to people instead of requiring their attention. The suggestions feature of Shortcuts rewards “acceleration”, showing the apps that provide the most time savings and use for the user more often.

This opens the door to more specialized types of apps that don’t necessarily have to grow a huge audience and serve them ads – if you can make something that helps people, Shortcuts can help them use your app more than ever before (and without as much effort). Developers can make a great experience for when people visit the app, but also focus on actually doing something useful too.

This isn’t a virtual assistant that lives in the cloud, but a digital helper that can pair up with the apps uniquely taking advantage of Apple’s hardware and software capabilities to truly improve your use of the device.

In the most groan-inducing way possible, “there’s an app for that” is back and more important than ever. Not only are apps the centerpiece of the Siri experience, but it’s their capabilities that extend Siri’s – the better the apps you have, the better Siri can be.

Control is at your fingertips

Importantly, Siri gets all of this Shortcuts power while keeping the control in each person’s hands.

All of the information provided to the system is securely passed along by individual apps – if something doesn’t look right, you can just delete the corresponding app and the information is gone.

Siri will make recommendations based on activities deemed relevant by the apps themselves as well, so over-active suggestions shouldn’t be common (unless you’re way too active in some apps, in which case they added Screen Time for you too).

Each of the voice commands is custom per user as well, so people can ignore their apps suggestions and set up the phrases to their own liking. This means nothing is already “taken” because somebody signed up for the skill first (unless you’ve already used it yourself, of course).

Also, Shortcuts don’t require the web to work – the voice triggers might not work, but the suggestions and Shortcuts app give you a place to use your assistant voicelessly. And importantly, Shortcuts can use the full power of the web when they need to.

This user-centric approach paired with the technical aspects of how Shortcuts works gives Apple’s assistant a leg up for any consumers who find privacy important. Essentially, Apple devices are only listening for “Hey Siri”, then the available Siri domains + your own custom trigger phrases.

Without exposing your information to the world or teaching a robot to understand everything, Apple gave Siri a slew of capabilities that in many ways can’t be matched. With Shortcuts, it’s the apps, the operating system, and the variety of hardware that will make Siri uniquely qualified come this fall.

Plus, the Shortcuts app will provide a deeper experience for those who want to chain together actions and customize their own shortcuts.

There’s lots more under the hood to experiment with, but this will allow anyone to tweak & prod their Siri commands until they have a small army of custom assistant tasks at the ready.

Hey Siri, let’s get started

Siri doesn’t know all, Can’t perform any task you bestow upon it, and won’t make somewhat uncanny phone calls on your behalf.

But instead of spending time conversing with a somewhat faked “artificial intelligence”, Shortcuts will help people use Siri as an actual digital assistant – a computer to help them get things done better than they might’ve otherwise.

With Siri’s new skills extendeding to each of your Apple products (except for Apple TV and the Mac, but maybe one day?), every new device you get and every new app you download can reveal another way to take advantage of what this technology can offer.

This broadening of Siri may take some time to get used to – it will be about finding the right place for it in your life.

As you go about your apps, you’ll start seeing and using suggestions. You’ll set up a few voice commands, then you’ll do something like kick off a truly useful shortcut from your Apple Watch without your phone connected and you’ll realize the potential.

This is a real digital assistant, your apps know how to work with it, and it’s already on many of your Apple devices. Now, it’s time to actually make use of it.

In Army of None, a field guide to the coming world of autonomous warfare

The Silicon Valley-military industrial complex is increasingly in the crosshairs of artificial intelligence engineers. A few weeks ago, Google was reported to be backing out of a Pentagon contract around Project Maven, which would use image recognition to automatically evaluate photos. Earlier this year, AI researchers around the world joined petitions calling for a boycott of any research that could be used in autonomous warfare.

For Paul Scharre, though, such petitions barely touch the deep complexity, nuance, and ambiguity that will make evaluating autonomous weapons a major concern for defense planners this century. In Army of None, Scharre argues that the challenges around just the definitions of these machines will take enormous effort to work out between nations, let alone handling their effects. It’s a sobering, thoughtful, if at times protracted look at this critical topic.

Scharre should know. A former Army Ranger, he joined the Pentagon working in the Office of Secretary of Defense, where he developed some of the Defense Department’s first policies around autonomy. Leaving in 2013, he joined the DC-based think tank Center for a New American Security, where he directs a center on technology and national security. In short, he has spent about a decade on this emerging tech, and his expertise clearly shows throughout the book.

The first challenge that belies these petitions on autonomous weapons is that these systems already exist, and are already deployed in the field. Technologies like the Aegis Combat System, High-speed Anti-Radiation Missile (HARM), and the Harpy already include sophisticated autonomous features. As Scharre writes, “The human launching the Harpy decides to destroy any enemy radars within a general area in space and time, but the Harpy itself chooses the specific radar it destroys.” The weapon can loiter for 2.5 hours while it determines a target with its sensors — is it autonomous?

Scharre repeatedly uses the military’s OODA loop (for observe, orient, decide, and act) as a framework to determine the level of autonomy for a given machine. Humans can be “in the loop,” where they determine the actions of the machine, “on the loop” where they have control but the machine is mostly working independently, and “out of the loop” when machines are entirely independent of human decision-making.

The framework helps clear some of the confusion between different systems, but it is not sufficient. When machines fight machines, for instance, the speed of the battle can become so great that humans may well do more harm then good intervening. Millions of cycles of the OODA loop could be processed by a drone before a human even registers what is happening on the battlefield. A human out of the loop, therefore, could well lead to safer outcomes. It’s exactly these kinds of paradoxes that make the subject so difficult to analyze.

In addition to paradoxes, constraints are a huge theme in the book as well. Speed is one — and the price of military equipment is another. Dumb missiles are cheap, and adding automation has consistently added to the price of hardware. As Scharre notes, “Modern missiles can cost upwards of a million dollars apiece. As a practical matter, militaries will want to know that there is, in fact, a valid enemy target in the area before using an expensive weapon.”

Another constraint is simply culture. The author writes, “There is intense cultural resistance within the U.S. military to handing over jobs to uninhabited systems.” Not unlike automation in the civilian workforce, people in power want to place flesh-and-blood humans in the most complex assignments. These constraints matter, because Scharre foresees a classic arms race around these weapons as dozens of countries pursue these machines.

Humans “in the loop” may be the default today, but for how long?

At a higher level, about a third of the book is devoted to the history of automation, (generalized) AI, and the potential for autonomy, topics which should be familiar to any regular reader of TechCrunch. Another third of the book or so is a meditation on the challenges of the technology from a dual use and strategic perspective, as well as the dubious path toward an international ban.

Yet, what I found most valuable in the book was the chapter on ethics, lodged fairly late in the book’s narrative. Scharre does a superb job covering the ground of the various schools of thought around the ethics of autonomous warfare, and how they intersect and compete. He extensively analyzes and quotes Ron Arkin, a roboticist who has spent significant time thinking about autonomy in warfare. Arkin tells Scharre that “We put way too much faith in human warfighters,” and argues that autonomous weapons could theoretically be programmed never to commit a war crime unlike humans. Other activists, like Jody Williams, believe that only a comprehensive ban can ensure that such weapons are never developed in the first place.

Scharre regrets that more of these conversations don’t take into account the strategic positions of the military. He notes that international discussions on bans are led by NGOs and not by nation states, whereas all examples of successful bans have been the other way around.

Another challenge is simply that antiwar activism and anti-autonomous weapons activism are increasingly being conflated. Scharre writes, “One of the challenges in weighing the ethics of autonomous weapons is untangling which criticisms are about autonomous weapons and which are really about war.” Citing Sherman, who marched through the U.S. South in the Civil War in an aggressive pillage, the author reminds the reader that “war is hell,” and that militaries don’t choose weapons in a vacuum, but relatively against other tools in their and their competitors’ arsenals.

The book is a compendium of the various issues around autonomous weapons, although it suffers a bit from the classic problem of being too lengthy on some subjects (drone swarms) while offering limited information on others (arms control negotiations). The book also is marred at times by errors, such as “news rules of engagement” that otherwise detract from a direct and active text. Tighter editing would have helped in both cases. Given the inchoate nature of the subject, the book works as an overview, although it fails to present an opinionated narrative on where autonomy and the military should go in the future, an unsatisfying gap given the author’s extensive and unique background on the subject.

All that said, Army of None is a one-stop guide book to the debates, the challenges, and yes, the opportunities that can come from autonomous warfare. Scharre ends on exactly the right note, reminding us that ultimately, all of these machines are owned by us, and what we choose to build is within our control. “The world we are creating is one that will have intelligent machines in it, but it is not for them. It is a world for us.” We should continue to engage, and petition, and debate, but always with a vision for the future we want to realize.

Facebook’s new AI research is a real eye-opener

There are plenty of ways to manipulate photos to make you look better, remove red eye or lens flare, and so on. But so far the blink has proven a tenacious opponent of good snapshots. That may change with research from Facebook that replaces closed eyes with open ones in a remarkably convincing manner.

It’s far from the only example of intelligent “in-painting,” as the technique is called when a program fills in a space with what it thinks belongs there. Adobe in particular has made good use of it with its “context-aware fill,” allowing users to seamlessly replace undesired features, for example a protruding branch or a cloud, with a pretty good guess at what would be there if it weren’t.

But some features are beyond the tools’ capacity to replace, one of which is eyes. Their detailed and highly variable nature make it particularly difficult for a system to change or create them realistically.

Facebook, which probably has more pictures of people blinking than any other entity in history, decided to take a crack at this problem.

It does so with a Generative Adversarial Network, essentially a machine learning system that tries to fool itself into thinking its creations are real. In a GAN, one part of the system learns to recognize, say, faces, and another part of the system repeatedly creates images that, based on feedback from the recognition part, gradually grow in realism.

From left to right: “Exemplar” images, source images, Photoshop’s eye-opening algorithm, and Facebook’s method.

In this case the network is trained to both recognize and replicate convincing open eyes. This could be done already, but as you can see in the examples at right, existing methods left something to be desired. They seem to paste in the eyes of the people without much consideration for consistency with the rest of the image.

Machines are naive that way: they have no intuitive understanding that opening one’s eyes does not also change the color of the skin around them. (For that matter, they have no intuitive understanding of eyes, color, or anything at all.)

What Facebook’s researchers did was to include “exemplar” data showing the target person with their eyes open, from which the GAN learns not just what eyes should go on the person, but how the eyes of this particular person are shaped, colored, and so on.

The results are quite realistic: there’s no color mismatch or obvious stitching because the recognition part of the network knows that that’s not how the person looks.

In testing, people mistook the fake eyes-opened photos for real ones, or said they couldn’t be sure which was which, more than half the time. And unless I knew a photo was definitely tampered with, I probably wouldn’t notice if I was scrolling past it in my newsfeed. Gandhi looks a little weird, though.

It still fails in some situations, creating weird artifacts if a person’s eye is partially covered by a lock of hair, or sometimes failing to recreate the color correctly. But those are fixable problems.

You can imagine the usefulness of an automatic eye-opening utility on Facebook that checks a person’s other photos and uses them as reference to replace a blink in the latest one. It would be a little creepy, but that’s pretty standard for Facebook, and at least it might save a group photo or two.

UK report warns DeepMind Health could gain ‘excessive monopoly power’

DeepMind’s foray into digital health services continues to raise concerns. The latest worries are voiced by a panel of external reviewers appointed by the Google-owned AI company to report on its operations after its initial data-sharing arrangements with the U.K.’s National Health Service (NHS) ran into a major public controversy in 2016.

The DeepMind Health Independent Reviewers’ 2018 report flags a series of risks and concerns, as they see it, including the potential for DeepMind Health to be able to “exert excessive monopoly power” as a result of the data access and streaming infrastructure that’s bundled with provision of the Streams app — and which, contractually, positions DeepMind as the access-controlling intermediary between the structured health data and any other third parties that might, in the future, want to offer their own digital assistance solutions to the Trust.

While the underlying FHIR (aka, fast healthcare interoperability resource) deployed by DeepMind for Streams uses an open API, the contract between the company and the Royal Free Trust funnels connections via DeepMind’s own servers, and prohibits connections to other FHIR servers. A commercial structure that seemingly works against the openness and interoperability DeepMind’s co-founder Mustafa Suleyman has claimed to support.

There are many examples in the IT arena where companies lock their customers into systems that are difficult to change or replace. Such arrangements are not in the interests of the public. And we do not want to see DeepMind Health putting itself in a position where clients, such as hospitals, find themselves forced to stay with DeepMind Health even if it is no longer financially or clinically sensible to do so; we want DeepMind Health to compete on quality and price, not by entrenching legacy position,” the reviewers write.

Though they point to DeepMind’s “stated commitment to interoperability of systems,” and “their adoption of the FHIR open API” as positive indications, writing: “This means that there is potential for many other SMEs to become involved, creating a diverse and innovative marketplace which works to the benefit of consumers, innovation and the economy.”

“We also note DeepMind Health’s intention to implement many of the features of Streams as modules which could be easily swapped, meaning that they will have to rely on being the best to stay in business,” they add. 

However, stated intentions and future potentials are clearly not the same as on-the-ground reality. And, as it stands, a technically interoperable app-delivery infrastructure is being encumbered by prohibitive clauses in a commercial contract — and by a lack of regulatory pushback against such behavior.

The reviewers also raise concerns about an ongoing lack of clarity around DeepMind Health’s business model — writing: “Given the current environment, and with no clarity about DeepMind Health’s business model, people are likely to suspect that there must be an undisclosed profit motive or a hidden agenda. We do not believe this to be the case, but would urge DeepMind Health to be transparent about their business model, and their ability to stick to that without being overridden by Alphabet. For once an idea of hidden agendas is fixed in people’s mind, it is hard to shift, no matter how much a company is motivated by the public good.”

We have had detailed conversations about DeepMind Health’s evolving thoughts in this area, and are aware that some of these questions have not yet been finalised. However, we would urge DeepMind Health to set out publicly what they are proposing,” they add. 

DeepMind has suggested it wants to build healthcare AIs that are capable of charging by results. But Streams does not involve any AI. The service is also being provided to NHS Trusts for free, at least for the first five years — raising the question of how exactly the Google-owned company intends to recoup its investment.

Google of course monetizes a large suite of free-at-the-point-of-use consumer products — such as the Android mobile operating system; its cloud email service Gmail; and the YouTube video sharing platform, to name three — by harvesting people’s personal data and using that information to inform its ad targeting platforms.

Hence the reviewers’ recommendation for DeepMind to set out its thinking on its business model to avoid its intentions vis-a-vis people’s medical data being viewed with suspicion.

The company’s historical modus operandi also underlines the potential monopoly risks if DeepMind is allowed to carve out a dominant platform position in digital healthcare provision — given how effectively its parent has been able to turn a free-for-OEMs mobile OS (Android) into global smartphone market OS dominance, for example.

So, while DeepMind only has a handful of contracts with NHS Trusts for the Streams app and delivery infrastructure at this stage, the reviewers’ concerns over the risk of the company gaining “excessive monopoly power” do not seem overblown.

They are also worried about DeepMind’s ongoing vagueness about how exactly it works with its parent Alphabet, and what data could ever be transferred to the ad giant — an inevitably queasy combination when stacked against DeepMind’s handling of people’s medical records.

“To what extent can DeepMind Health insulate itself against Alphabet instructing them in the future to do something which it has promised not to do today? Or, if DeepMind Health’s current management were to leave DeepMind Health, how much could a new CEO alter what has been agreed today?” they write.

“We appreciate that DeepMind Health would continue to be bound by the legal and regulatory framework, but much of our attention is on the steps that DeepMind Health have taken to take a more ethical stance than the law requires; could this all be ended? We encourage DeepMind Health to look at ways of entrenching its separation from Alphabet and DeepMind more robustly, so that it can have enduring force to the commitments it makes.”

Responding to the report’s publication on its website, DeepMind writes that it’s “developing our longer-term business model and roadmap.”

“Rather than charging for the early stages of our work, our first priority has been to prove that our technologies can help improve patient care and reduce costs. We believe that our business model should flow from the positive impact we create, and will continue to explore outcomes-based elements so that costs are at least in part related to the benefits we deliver,” it continues.

So it has nothing to say to defuse the reviewers’ concerns about making its intentions for monetizing health data plain — beyond deploying a few choice PR soundbites.

On its links with Alphabet, DeepMind also has little to say, writing only that: “We will explore further ways to ensure there is clarity about the binding legal frameworks that govern all our NHS partnerships.”

“Trusts remain in full control of the data at all times,” it adds. “We are legally and contractually bound to only using patient data under the instructions of our partners. We will continue to make our legal agreements with Trusts publicly available to allow scrutiny of this important point.”

“There is nothing in our legal agreements with our partners that prevents them from working with any other data processor, should they wish to seek the services of another provider,” it also claims in response to additional questions we put to it.

We hope that Streams can help unlock the next wave of innovation in the NHS. The infrastructure that powers Streams is built on state-of-the-art open and interoperable standards, known as FHIR. The FHIR standard is supported in the UK by NHS Digital, NHS England and the INTEROPen group. This should allow our partner trusts to work more easily with other developers, helping them bring many more new innovations to the clinical frontlines,” it adds in additional comments to us.

“Under our contractual agreements with relevant partner trusts, we have committed to building FHIR API infrastructure within the five year terms of the agreements.”

Asked about the progress it’s made on a technical audit infrastructure for verifying access to health data, which it announced last year, it reiterated the wording on its blog, saying: “We will remain vigilant about setting the highest possible standards of information governance. At the beginning of this year, we appointed a full time Information Governance Manager to oversee our use of data in all areas of our work. We are also continuing to build our Verifiable Data Audit and other tools to clearly show how we’re using data.”

So developments on that front look as slow as we expected.

The Google-owned U.K. AI company began its push into digital healthcare services in 2015, quietly signing an information-sharing arrangement with a London-based NHS Trust that gave it access to around 1.6 million people’s medical records for developing an alerts app for a condition called Acute Kidney Injury.

It also inked an MoU with the Trust where the pair set out their ambition to apply AI to NHS data sets. (They even went so far as to get ethical signs-off for an AI project — but have consistently claimed the Royal Free data was not fed to any AIs.)

However, the data-sharing collaboration ran into trouble in May 2016 when the scope of patient data being shared by the Royal Free with DeepMind was revealed (via investigative journalism, rather than by disclosures from the Trust or DeepMind).

None of the ~1.6 million people whose non-anonymized medical records had been passed to the Google-owned company had been informed or asked for their consent. And questions were raised about the legal basis for the data-sharing arrangement.

Last summer the U.K.’s privacy regulator concluded an investigation of the project — finding that the Royal Free NHS Trust had broken data protection rules during the app’s development.

Yet despite ethical questions and regulatory disquiet about the legality of the data sharing, the Streams project steamrollered on. And the Royal Free Trust went on to implement the app for use by clinicians in its hospitals, while DeepMind has also signed several additional contracts to deploy Streams to other NHS Trusts.

More recently, the law firm Linklaters completed an audit of the Royal Free Streams project, after being commissioned by the Trust as part of its settlement with the ICO. Though this audit only examined the current functioning of Streams. (There has been no historical audit of the lawfulness of people’s medical records being shared during the build and test phase of the project.)

Linklaters did recommend the Royal Free terminates its wider MoU with DeepMind — and the Trust has confirmed to us that it will be following the firm’s advice.

“The audit recommends we terminate the historic memorandum of understanding with DeepMind which was signed in January 2016. The MOU is no longer relevant to the partnership and we are in the process of terminating it,” a Royal Free spokesperson told us.

So DeepMind, probably the world’s most famous AI company, is in the curious position of being involved in providing digital healthcare services to U.K. hospitals that don’t actually involve any AI at all. (Though it does have some ongoing AI research projects with NHS Trusts too.)

In mid 2016, at the height of the Royal Free DeepMind data scandal — and in a bid to foster greater public trust — the company appointed the panel of external reviewers who have now produced their second report looking at how the division is operating.

And it’s fair to say that much has happened in the tech industry since the panel was appointed to further undermine public trust in tech platforms and algorithmic promises — including the ICO’s finding that the initial data-sharing arrangement between the Royal Free and DeepMind broke U.K. privacy laws.

The eight members of the panel for the 2018 report are: Martin Bromiley OBE; Elisabeth Buggins CBE; Eileen Burbidge MBE; Richard Horton; Dr. Julian Huppert; Professor Donal O’Donoghue; Matthew Taylor; and Professor Sir John Tooke.

In their latest report the external reviewers warn that the public’s view of tech giants has “shifted substantially” versus where it was even a year ago — asserting that “issues of privacy in a digital age are if anything, of greater concern.”

At the same time politicians are also gazing rather more critically on the works and social impacts of tech giants.

Although the U.K. government has also been keen to position itself as a supporter of AI, providing public funds for the sector and, in its Industrial Strategy white paper, identifying AI and data as one of four so-called “Grand Challenges” where it believes the U.K. can “lead the world for years to come” — including specifically name-checking DeepMind as one of a handful of leading-edge homegrown AI businesses for the country to be proud of.

Still, questions over how to manage and regulate public sector data and AI deployments — especially in highly sensitive areas such as healthcare — remain to be clearly addressed by the government.

Meanwhile, the encroaching ingress of digital technologies into the healthcare space — even when the techs don’t even involve any AI — are already presenting major challenges by putting pressure on existing information governance rules and structures, and raising the specter of monopolistic risk.

Asked whether it offers any guidance to NHS Trusts around digital assistance for clinicians, including specifically whether it requires multiple options be offered by different providers, the NHS’ digital services provider, NHS Digital, referred our question on to the Department of Health (DoH), saying it’s a matter of health policy.

The DoH in turn referred the question to NHS England, the executive non-departmental body which commissions contracts and sets priorities and directions for the health service in England.

And at the time of writing, we’re still waiting for a response from the steering body.

Ultimately it looks like it will be up to the health service to put in place a clear and robust structure for AI and digital decision services that fosters competition by design by baking in a requirement for Trusts to support multiple independent options when procuring apps and services.

Without that important check and balance, the risk is that platform dynamics will quickly dominate and control the emergent digital health assistance space — just as big tech has dominated consumer tech.

But publicly funded healthcare decisions and data sets should not simply be handed to the single market-dominating entity that’s willing and able to burn the most resource to own the space.

Nor should government stand by and do nothing when there’s a clear risk that a vital area of digital innovation is at risk of being closed down by a tech giant muscling in and positioning itself as a gatekeeper before others have had a chance to show what their ideas are made of, and before even a market has had the chance to form. 

Microsoft acquires conversational AI startup Semantic Machines to help bots sound more lifelike

Microsoft announced today that it has acquired Semantic Machines, a Berkeley-based startup that wants to solve one of the biggest challenges in conversational AI: making chatbots sound more human and less like, well, bots.

In a blog post, Microsoft AI & Research chief technology officer David Ku wrote that “with the acquisition of Semantic Machines, we will establish a conversational AI center of excellence in Berkeley to push forward the boundaries of what is possible in language interfaces.”

According to Crunchbase, Semantic Machines was founded in 2014 and raised about $20.9 million in funding from investors including General Catalyst and Bain Capital Ventures.

In a 2016 profile, co-founder and chief scientist Dan Klein told TechCrunch that “today’s dialog technology is mostly orthogonal. You want a conversational system to be contextual so when you interpret a sentence things don’t stand in isolation.” By focusing on memory, Semantic Machines’ AI can produce conversations that not only answer or predict questions more accurately, but also flow naturally.

Instead of building its own consumer products, Semantic Machines focused on enterprise customers. This means it will fit in well with Microsoft’s conversational AI-based products, including Microsoft Cognitive Services and Azure Bot Service, which are used by one million and 300,000 developers, respectively, and virtual assistants Cortana and Xiaolce.

The new AI-powered Google News app is now available for iOS

Google teased a new version of its News app with AI smarts at its I/O event last week, and today that revamped app landed for iOS and Android devices in 127 countries. The redesigned app replaces the previous Google Play Newsstand app.

The idea is to make finding and consuming news easier than ever, whilst providing an experience that’s customized to each reader and supportive of media publications. The AI element is designed to learn from what you read to help serve you a better selection of content over time, while the app is presented with a clear and clean layout.

Opening the app brings up the tailored ‘For You’ tab which acts as a quick briefing, serving up the top five stories “of the moment” and a tailored selection of opinion articles and longer reads below it.

The next section — ‘Headlines’ — dives more deeply into the latest news, covering global, U.S., business, technology, entertainment, sports, science and health segments. Clicking a story pulls up ‘Full Coverage’ mode, which surfaces a range of content around a topic including editorial and opinion pieces, tweets, videos and a timeline of events.

 

Favorites is a tab that allows customization set by the user — without AI. It works as you’d imagine, letting you mark out preferred topics, news sources and locations to filter your reads. There’s also an option for saved searches and stories which can be quickly summoned.

The final section is ‘Newsstand’ which, as the name suggests aggregates media. Google said last week that it plans to offer over 1,0000 magazine titles you can follow by tapping a star icon or subscribing to. It currently looks a little sparse without specific magazine titles, but we expect that’ll come soon.

As part of that, another feature coming soon is “Subscribe with Google, which lets publications offer subscription-based content. The process of subscribing will use a user’s Google account, and the payment information they already have on file. Then, the paid content becomes available across Google platforms, including Google News, Google Search and publishers’ own websites.

China’s SenseTime, the world’s highest valued AI startup, raises $600M

The future of artificial intelligence (AI), the technology that is seen as potentially impacting almost every industry on the planet, is widely acknowledged to be a war between tech firms in America and China.

In a notable side-note to that battle, China now has the world’s highest-valued AI startup after SenseTime, a company founded in 2014, announced a $600 million Series C investment round. A source with knowledge of discussions told TechCrunch that the round values the company at over $4.5 billion, while it is also raising an extension to this round. That marks a hefty increase on the company’s most recent $1.5 billion valuation when it raised a $410 million Series B last year.

SenseTime CEO Li Xu said the company plans to use the capital to expand its presence overseas and “widen the scope for more industrial application of AI.”

Beyond the high figures involved — the round is a record fundraising for an AI company worldwide — SenseTime’s investment efforts are notable because of the names that have backed it.

Principally that’s Alibaba, the $429 billion e-commerce giant, which led this Series C round and is reportedly now SenseTime’s largest single investor, according to Bloomberg.

Beyond that, U.S. chipmaker giant Qualcomm signed up last year — seemingly as an early participant in this round — while Singapore’s sovereign fund Temasek and China’s largest electronics retailer Suning, which has taken investment from Alibaba, entered the round as new backers. Indeed, Suning’s push to for its store of the future, which was started by that Alibaba investment, uses SenseTime to power its facial recognition payment at staff-less checkouts and also for customer analysis using big data systems.

“SenseTime is doing pioneering work in artificial intelligence. We are especially impressed by their R&D capabilities in deep learning and visual computing. Our business at Alibaba is already seeing tangible benefits from our investments in AI and we are committed to further investment,” said Joe Tsai, Alibaba’s executive vice chairman.

SenseTime said it has more than 400 customers across a range of verticals including fintech, automotive, fintech, smartphones, smart city development and more that include Honda, Nvidia, China’s UnionPay, Weibo, China Merchants Bank, Huawei, Oppo, Vivo and Xiaomi.

Perhaps its most visible partner is the Chinese government, which uses its systems for its national surveillance system. SenseTime process data captured by China’s 170 million CCTV cameras and newer systems which include smart glasses worn by police offers on the street.

China has placed vast emphasis on tech development, with AI one of its key flagposts.

A government program aims to make the country the world leader in AI technology by 2030, the New York Times reported, by which time it is estimated that the industry could be worth some $150 billion per year. SenseTime’s continued development fees directly into that ambition.

“AI is really changing every profession and every industry. There’s almost nothing that won’t be touched by AI,” investor Kai-Fu Lee, formerly the head of Google in China, said at a TechCrunch event back in 2016.

Even two years ago, the potential was evident, with Lee explaining that teaching, medicine and healthcare were obvious areas for disruption.

Perhaps the main difference between the state of AI development in the U.S. and China is that, in America, much of the technology is being developed in big tech firms like Amazon and Google. In China, however, companies like SenseTime and its rival Megvii (which develops the Face++ platform) are independent entities that operate with the financial backing of giants like Alibaba.

US-China biotech startup XtalPi lands $15M from Google, Tencent and Sequoia

 Google continues to increase its presence in China after it joined Sequoia China and Tencent in a $15 million investment for XtalPi, a U.S.-China biotech firm that uses artificial intelligence and computing to accelerate the development of new drugs. The search giant remains blocked in China, but that hasn’t stopped it from making a series of moves in recent months. It is opening an… Read More

Google declares war against Alexa and Siri at CES 2018

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It’s an artificial intelligence showdown.

This year at CES, the world’s largest electronics trade show (running Jan. 9-12), thousands of companies will travel to Las Vegas to show off their newest products and build new partnerships. But this time around, one unusual exhibitor stands out from the rest: Google.

It’s the first time in many years that Google will have its own, large, standalone booth in the middle of the convention center. But the search giant has gone far beyond buying space on the showroom floor. It’s also commissioned several large advertisements around the city, including one you simply can’t miss. Read more…

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VW taps Nvidia to build AI into its new electric microbus and beyond

 Nvidia will power artificial intelligence technology built into its future vehicles, including the new I.D. Buzz, its all-electric retro-inspired camper van concept. The partnership between the two companies also extends to the future vehicles, and will initially focus on so-called “Intelligent Co-Pilot” features, including using sensor data to make driving easier, safer and… Read More

Google has planted its flag at CES

 Google’s here, and it’s planning something big. The company’s presence is impossible to miss as you drive down Paradise Road toward the Las Vegas Convention Center. Like much the rest of the show, the company’s parking lot booth is still under construction today, but the giant, black and white “Hey Google” sign is already hanging above it, visible from… Read More

Horizons Ventures backs AI startup Fano Labs in first Hong Kong investment

 Horizons Ventures, the VC firm founded by Hong Kong’s richest man Li Ka-Shing, has made a rare early-stage investment after it backed AI startup Fano Labs.
Horizons has invested in the likes of Facebook, Razer, Slack, Improbable, Spotify and more, and now it is putting undisclosed money into Fano Labs, which recently graduated AI accelerator program Zeroth. This deal also marks the… Read More

Hello Aibo, goodbye Alexa: Sony turns robot dog into AI assistant

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That robotic dog you wanted as a kid is back. And sadly, it’s just as expensive.

Sony had announced that after more than a decade since retiring its robot dog product, the Aibo will be coming back for real.

Image: aibo/sony/screenshot

The new Aibo has also learnt some new tricks. Its AI capability will allow it to learn and recognise people’s faces, and remember and avoid obstacles in a room.

It’ll also be voice-capable and cloud connected, being able to record photos and save them online. For example, saying “take a picture” will trigger the Aibo to take a shot and send it to the cloud, accessible later from a companion app.  Read more…

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Primer helps governments and corporations monitor and understand the world’s information

 When Google was founded in 1998, its goal was to organize the world’s information. And for the most part, mission accomplished — but in 19 years the goal post has moved forward and indexing and usefully presenting information isn’t enough. As machine learning matures, it’s becoming feasible for the first time to actually summarize and contextualize the world’s… Read More

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Let's all take a deep breath and stop freaking out about Facebook's bots 'inventing' a new language

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Tesla CEO Elon Musk made headlines last week when he tweeted about his frustrations that Mark Zuckerberg, ever the optimist, doesn’t fully understand the potential danger posed by artificial intelligence. 

So when media outlets began breathlessly re-reporting a weeks-old story that Facebook’s AI-trained chatbots “invented” their own language, it’s not surprising the story caught more attention than it did the first time around.

Understandable, perhaps, but it’s exactly the wrong thing to be focusing on. The fact that Facebook’s bots “invented” a new way to communicate wasn’t even the most shocking part of the research to begin with. Read more…

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iRobot to acquire its biggest European distributor for $141M

 Consumer robot maker iRobot is to acquire its largest European distributor, Robopolis, in a cash deal worth $141 million. The company said it’s signed a definitive agreement to acquire the privately-held, French company, with the acquisition expected to close in October 2017. Read More

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Kakao is putting speech recognition tech into cars from Hyundai and Kia

 Less than a month after announcing plans to spin out its transportation and mobility business, Korean tech firm Kakao has inked deals to put hands-free systems inside cars from Korea’s second largest automotive firm Hyundai and its Kia affiliate.
Kakao is best known for operating Korea’s top messaging app, Kakao Talk, which is installed on over 95 percent of the country’s… Read More

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VCs determined to replace your job keep AI’s funding surge rolling in Q2

 These are good times for AI entrepreneurs. Venture, corporate and seed investors have put an estimated $3.6 billion into AI and machine learning companies this year, according to Crunchbase data. That’s more than they invested in all of 2016, marking the largest recorded sum ever put into the space in a comparable period. Read More

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TrueFace.AI busts facial recognition imposters

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Facial recognition technology is more prevalent than ever before. It’s being used to identify people in airports, put a stop to child sex trafficking, and shame jaywalkers

But the technology isn’t perfect. One major flaw: It sometimes can’t tell the difference between a living person’s face and a photo of that person held up in front of a scanner. 

TrueFace.AI facial recognition is trying to fix that flaw. Launched on Product Hunt in June, it’s meant to detect “picture attacks.”

The company originally created Chui in 2014 to work with customized smart homes. Then they realized clients were using it more for security purposes, and TrueFace.AI was born.  Read more…

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After beating the world’s elite Go players, Google’s AlphaGo AI is retiring

 Google’s AlphaGo — the AI developed to tackle the world’s most demanding strategy game — is stepping down from competitive matches after defeating the world’s best talent. The latest to succumb is Go’s top-ranked player, Ke Jie, who lost 3-0 in a series hosted in China this week. The AI, developed by London-based DeepMind, which was acquired by Google… Read More

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Chinese authorities banned the broadcast of a match between top Go player and AlphaGo AI

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A Go match between the world’s top player, Ke Jie, and Google’s AlphaGo that took place this week was censored by authorities, reports Quartz.

The AI beat Ke Jie in yet another match today, securing a win in the three-part match.

Three journalists have reported receiving verbal directives barring their news organisations from broadcasting the match — as well as the Go and AI summit held in Wuzhen, east China. 

One journalist reported being barred from even mentioning Google’s name while reporting on the event, while another said that while they could mention Google, they were barred from writing about Google’s products. Read more…

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Project recreates cities in rich 3D from images harvested online

 People are taking photos and videos all over major cities, all the time, from every angle. Theoretically, with enough of them, you could map every street and building — wait, did I say theoretically? I meant in practice, as the VarCity project has demonstrated with Zurich, Switzerland. Read More

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DeepGraph feeds enterprise sales teams with hyper-targeted warm leads

 The best way to grow sales is to better understand sales, but unfortunately that’s often easier said than done. Kemvi, a seed-stage startup, is launching out of stealth today to announce DeepGraph, which helps sales teams reach the right potential customers at the right time. The company has closed north of $1 million in seed financing from Seabed VC, Neotribe Ventures, Kepha… Read More

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Media Prima buys Rev Asia for $24M to create Malaysia’s largest digital media platform

 The U.S. isn’t the only market where media companies are consolidating to offer an advertising platform to rival Facebook and Google.
While AOL (which owns TechCrunch) is in the process of acquiring Yahoo, over in Malaysia a similar consolidation was announced this week — although not quite on the scale of AOL-Yahoo (Oath?!) and its $4.48 billion price tag. Media Prima, a… Read More

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Google's new AutoDraw wants to make drawing easier for everyone

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Your doodles are about to get a whole lot better.

Part of Google’s new A.I. Experiments collection, AutoDraw is like an AI-powered Microsoft Paint. The app combines conventional doodling with art from professionals to enhance your doodles and help create better art. 

The app works by trying to guess what you’re drawing and then offering alternatives for you to build on. 

Image: google

Google calls AutoDraw “a drawing tool for the rest of us;” that is, people who aren’t professional designers. What it really does is recognize what you’re trying to draw and replace that with a version drawn by an artist. The tool turned my terrible doodle of a cake that really could have been anything, and offered me this great cake instead.  Read more…

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Commission your own traffic and construction studies without ever leaving bed using SpaceKnow

 The number of things that can be done from the comfort of one’s own bed has increased in recent years — shopping, banking and now geospatial analytics. Ok, it doesn’t sound sexy but it might give you a leg up the next time your friend starts an arcane argument with you over whose neighborhood historically has more vehicles on the road. With SpaceKnow’s online… Read More

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6 River Systems unveils warehouse robots that show workers the way

 When Amazon acquired Kiva Systems in 2012, other retailers and third-party fulfillment centers panicked. The e-commerce giants took Kiva’s robots off the market, leaving their competitors without an important productivity tool. Lots of newcomers have cropped up to help warehouses keep up with demand since then. But one of the most hotly anticipated robots in this space was under… Read More

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Matroid can watch videos and detect anything within them

 If a picture is worth a thousand words, a video is worth that times the frame rate. Matroid, a computer vision startup launching out of stealth today, enables anyone to take advantage of the information inherently embedded in video. You can build your own detector within the company’s intuitive, non-technical, web platform to detect people and most other objects. Reza Zadeh, founder… Read More

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Cognitiv+ is using AI for contract analysis and tracking

 Another legal tech startup coming out of the UK: Cognitiv+ is applying artificial intelligence to automate contract analysis and management, offering businesses a way to automate staying on top of legal risks, obligations and changing regulatory landscapes. Read More

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Goodyear’s AI tire concept can read the road and adapt on the fly

 Goodyear is thinking ahead to how tires – yes, tires – might change as autonomous driving technology alters vehicle design, and as available technologies like in-vehicle and embedded machine learning and AI make it possible to do more with parts of the car that were previously pretty static, like its wheels. Its new Eagle 360 Urban tire concept design builds on the work it… Read More

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IBM and Salesforce partner to sell Watson and Einstein

Server room in data center Two of the best-marketed names in artificial intelligence are coming together to pitch their wares to a sea of unwitting rubes new customers with the announcement that IBM and Salesforce are going to partner. The new partnership amounts to a way for IBM to sell consulting services across both Salesforce’s Einstein and IBM’s Watson AI-branded businesses. Insights from Watson will now… Read More

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Ozlo releases a suite of APIs to power your next conversational AI

Illustration of laptop connected to bookshelf Building on its promise to give the entrenched a run for their money, conversational AI startup Ozlo is making its meticulously crafted knowledge layer available for purchase today. Ozlo’s new suite of APIs that includes tools for both expressing knowledge and understanding language will help to democratize the creation of conversational AI assistants. In the spirit of the expert systems… Read More

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Ozlo releases a suite of APIs to power your next conversational AI

Illustration of laptop connected to bookshelf Building on its promise to give the entrenched a run for their money, conversational AI startup Ozlo is making its meticulously crafted knowledge layer available for purchase today. Ozlo’s new suite of APIs that includes tools for both expressing knowledge and understanding language will help to democratize the creation of conversational AI assistants. In the spirit of the expert systems… Read More

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Chat app Line is developing an AI assistant and Amazon Echo-style smart speaker

line nyse 2 Messaging app Line is taking a leaf out of the books of Amazon, Google and others after it launched its own artificial intelligence platform. A voice-powered concierge service called Clova — short for “Cloud Virtual Assistant” — is the centerpiece of the service, much like Amazon’s Alexa, Microsoft’s Cortana and Google Assistant. Beyond the assistant… Read More

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