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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. 

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.

Facebook has a new job posting calling for chip designers

Facebook has posted a job opening looking for an expert in ASIC and FPGA, two custom silicon designs that companies can gear toward specific use cases — particularly in machine learning and artificial intelligence.

There’s been a lot of speculation in the valley as to what Facebook’s interpretation of custom silicon might be, especially as it looks to optimize its machine learning tools — something that CEO Mark Zuckerberg referred to as a potential solution for identifying misinformation on Facebook using AI. The whispers of Facebook’s customized hardware range depending on who you talk to, but generally center around operating on the massive graph Facebook possesses around personal data. Most in the industry speculate that it’s being optimized for Caffe2, an AI infrastructure deployed at Facebook, that would help it tackle those kinds of complex problems.

FPGA is designed to be a more flexible and modular design, which is being championed by Intel as a way to offer the ability to adapt to a changing machine learning-driven landscape. The downside that’s commonly cited when referring to FPGA is that it is a niche piece of hardware that is complex to calibrate and modify, as well as expensive, making it less of a cover-all solution for machine learning projects. ASIC is similarly a customized piece of silicon that a company can gear toward something specific, like mining cryptocurrency.

Facebook’s director of AI research tweeted about the job posting this morning, noting that he previously worked in chip design:

Interested in designing ASIC & FPGA for AI?
Design engineer positions are available at Facebook in Menlo Park.

I used to be a chip designer many moons ago: my engineering diploma was in Electrical… https://t.co/D4l9kLpIlV

Yann LeCun (@ylecun) April 18, 2018

While the whispers grow louder and louder about Facebook’s potential hardware efforts, this does seem to serve as at least another partial data point that the company is looking to dive deep into custom hardware to deal with its AI problems. That would mostly exist on the server side, though Facebook is looking into other devices like a smart speaker. Given the immense amount of data Facebook has, it would make sense that the company would look into customized hardware rather than use off-the-shelf components like those from Nvidia.

(The wildest rumor we’ve heard about Facebook’s approach is that it’s a diurnal system, flipping between machine training and inference depending on the time of day and whether people are, well, asleep in that region.)

Most of the other large players have found themselves looking into their own customized hardware. Google has its TPU for its own operations, while Amazon is also reportedly working on chips for both training and inference. Apple, too, is reportedly working on its own silicon, which could potentially rip Intel out of its line of computers. Microsoft is also diving into FPGA as a potential approach for machine learning problems.

Still, that it’s looking into ASIC and FPGA does seem to be just that — dipping toes into the water for FPGA and ASIC. Nvidia has a lot of control over the AI space with its GPU technology, which it can optimize for popular AI frameworks like TensorFlow. And there are also a large number of very well-funded startups exploring customized AI hardware, including Cerebras Systems, SambaNova Systems, Mythic, and Graphcore (and that isn’t even getting into the large amount of activity coming out of China). So there are, to be sure, a lot of different interpretations as to what this looks like.

One significant problem Facebook may face is that this job opening may just sit up in perpetuity. Another common criticism of FPGA as a solution is that it is hard to find developers that specialize in FPGA. While these kinds of problems are becoming much more interesting, it’s not clear if this is more of an experiment than Facebook’s full all-in on custom hardware for its operations.

But nonetheless, this seems like more confirmation of Facebook’s custom hardware ambitions, and another piece of validation that Facebook’s data set is becoming so increasingly large that if it hopes to tackle complex AI problems like misinformation, it’s going to have to figure out how to create some kind of specialized hardware to actually deal with it.

A representative from Facebook did not yet return a request for comment.

5 Top Technology Trends That Will Shape 2018

Groundbreaking steps are happening in the technology industry all the time. In the past couple of years alone, leaps and bounds have resulted in better augmented reality, virtual reality, artificial intelligence, speech recognition, and more. This year, you can expect more tech innovations to enhance our lives.

Here are the top technology trends you need to watch out for this year.

Augmented Reality

augmented reality vs virtual reality

We’ve already seen what today’s AR mobile apps can do and games like Pokémon Go are a far cry from it, to say the least.

The AR technology from companies like the startup DAQRI, however, extends well beyond a mobile game experience. Its technology is found in other products, like its $15,000 AR helmets.

You can wear those helmets entirely hands-free and it can work for hours. A requirement for its primary users: industrial workers, sailors, and soldiers.

Take note that these headsets aren’t quite full-scale AR because they suffer from the common problem of most AR headsets. It’s the narrow rectangular view that cuts off images when the user moves.

Now, as the company has partnered with Two Trees, a holography specialist, and is working on developing new dynamic holography technology, it could possibly revolutionize AR.

See Also: How Augmented Reality Is Changing The Game

Google RankBrain

One of the biggest contributors to the advancement of search algorithms in recent years has been Google’s machine learning Artificial Intelligence (AI) system, RankBrain.

Since its inception over two years ago, Google continues to embrace RankBrain, using it to return the best results that match a Google user’s query. It has gone from being used in 15% of Google search queries to now being used in all of them.

Google has also been dabbling in other AI interests. This includes the development of a Cloud Vision API, which has the capability to recognize a huge number of objects. Plus, its Google Brain division has reportedly been developing an AI that can build AI better than humans can.

Artificial Intelligence

Google RankBrain aside, artificial intelligence isn’t only found in data. It’s in just about every industry. Journalism, financial services, video gaming, gambling, automotive, the military, and even healthcare are just some examples.

Currently, the vast majority of AI systems function as a supportive tool that can make certain processes more simplified, effective, and faster.

That said, as AI enters more and more fields, people like Jack Ma question what impact the future of AI will have on society as a whole. The concerns of Alibaba’s founder and Executive Chairman were made known earlier this year during the World Economic Forum (WEF) at Davos.

“The AI, Big Data is a threat to human beings. The AI and robots are going to kill a lot of jobs because, in the future, these will be done by machines,” Ma stated during a discussion panel.

He believes that AI should be used to support people and added that tech giants, like Alibaba, Amazon, and Facebook, need to be responsible and “should spend money on technology that enables people, empowers people, and makes life better”.

See Also: 5 Reasons Why You Should Consider AI Automation for Small Business

Smart speakers

Forget about talking to your smartphone. The future is all about voice-controlled smart speakers now.

This technology perfectly fits into the ecosystem of a smart home as smart speakers can function as the main control hub. They can answer questions, set timers, play music, and control other devices at home.

As you might imagine, there is a fierce competition between market leaders. Amazon, Google, Apple, and Microsoft aim to develop and sell the most sought-after smart speakers.

Today, the competition is tight between Amazon and Google. These companies are leading the market with smart speakers that are affordable, accessible, and superior to Apple’s Siri.

And once Apple’s smart speaker (HomePod) is out later this year, fans will still flock to buy it despite the high price tag. That only reflects people’s desire to always get their hands on the latest technology.

apple homepad
Via Dezeen

Speech recognition

Speech recognition is another tech that has recently advanced both in its capabilities and its use. Whether you’re asking your smartphone a question or your smart speaker, speech recognition is at play.

While there has always been a lot of kinks to work out when it comes to this technology, last August, Microsoft claimed a new speech recognition record. It was able to reduce its error rate to an amazing 5.1%.

This percentage matched the error rate of multiple human transcribers in a well-known accuracy test.

Microsoft’s continued improvements in speech recognition technology are a part of its wider effort to advance state of the art AI and bring these new innovations to the market.

Conclusion

Of course, no one really knows what the future holds for these top technology trends. Maybe full-scale AR will eliminate the need for mobile phones. Perhaps, speech recognition may prove to be superior to human transcribers- or maybe not. Only time will tell where these innovations might take us next

The post 5 Top Technology Trends That Will Shape 2018 appeared first on Dumb Little Man.

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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5 Reasons Why You Should Consider AI Automation for Small Business

If you are aware of the developments in technology, then you have probably heard about Artificial Intelligence (AI). For a lot of people, it’s too complex or high-tech so they don’t really pay a lot of attention to it.

In fact, even small businesses don’t think much of AI. They believe that only big tech companies like Apple and Google can utilize it. However, that’s not true.

AI has numerous benefits for small businesses. It’s something you cannot ignore if you want to stay ahead of your competition.

Today, open-minded businesses have started using AI to create a business logo, respond to emails, comb the Internet for leads identification, help customers with chatbots and a lot more.

If you have not seriously considered AI automation for your business yet, then the following 5 reasons can surely convince you.

Enhanced Bookkeeping

There are plenty of AI tools designed specifically for bookkeeping that you can use. While many offer help with the basic data entry tasks, some are more advanced and can easily perform many roles. You can use it in reading and preparing invoices, set invoice reminders, release payments on schedule and more.

So, instead of expanding your accounting department, you can invest in an AI bookkeeping program which is more affordable and highly useful.

Lead Nurturing

No matter how skilled your sales reps are, they will always have limitations.

For starters, one can handle only a certain number of leads at a time. Secondly, they need a certain amount of time with every lead to learn about their personality, pain points, opportunities for connection building and many other aspects that are required for their nurturing.

However, with AI automation you can take the entire process to the next level and benefit from increased productivity.

An AI program designed for lead nurturing can read and respond to the emails of your prospects using a list of set messages and the Natural Language Processing technology. It can also go through the past conversations you have had with your leads to pinpoint important bits of information. Most importantly, it can work 24/7 since it can function without human intervention.

Online Customer Support

A number of studies have found that customers find it more comfortable to inquire about the services or products of a company through messaging, especially via online chat as opposed to voice calls. However, hiring a full-time customer executive can be expensive for a small business. Again, this is where AI automation can be a great option.

chatbots

Not only AI-powered chatbots are highly popular today, you can also find some highly affordable options easily. You can install one of these on your website so that when your customers need some information, it will be readily available. In addition to that, having AI-powered chatbots can also make your website more attractive.

See Also: How To Boost Your Business with Influence Marketing Chatbots

Cheap but Quality Branding

Usually, it’s hard to find quality and affordability at the same place. However, AI automation seems to have changed that.

This is because it can help you with your company branding in many ways and at modest pricing. There are companies like Tailor Brands that offer an entire suite of branding tools- from logo creation to social media banner creation at a fraction of the price that you would pay to a graphics designer.

Intelligent Personal Assistants

You are probably already familiar with virtual personal assistants, such as Apple’s Siri or Microsoft Corona. Today, a new range of similar assistants is emerging and they are even more intelligent and more suitable for businesses. For instance, there is Amy from x.ai that can arrange meetings for you or Pana that can arrange your travel.

amy intelligent personal assistant
Via slideshare.net

AI has matured enough today that it can be utilized in different ways in every industry. It’s now easily available at affordable costs, too. If you haven’t considered using one for your business, it’s probably the right time to reconsider your strategy.

 

The post 5 Reasons Why You Should Consider AI Automation for Small Business appeared first on Dumb Little Man.

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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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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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Superintelligent AI explains Softbank’s push to raise a $100BN Vision Fund

masayoshi son Anyone who’s seen Softbank CEO Masayoshi Son give a keynote speech will know he rarely sticks to the standard industry conference playbook. And his turn on the stage at Mobile World Congress this morning was no different, with Son making like Eldon Tyrell and telling delegates about his personal belief in a looming computing Singularity… Read More

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Baidu furthers AI push with acquisition of digital assistant startup Raven Tech

baidu Baidu is furthering its push into artificial intelligence after it announced the acquisition of Raven Tech, a Chinese startup that developed an AI voice assistant platform. Baidu confirmed it has bought the startup’s tech, product and staff of 60. The deal comes a month after Baidu hired noted AI expert Qi Lu, formerly with Microsoft, as its COO and Group President.… Read More

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Lobster nets £1M to scale its user-generated content licensing marketplace

lobster U.K. startup Lobster is gearing up to scale its user-generated content licensing marketplace, as it closes a £1 million Series A. It’s expecting to have closed out the round next week, with 85 per cent of the funding committed at this point and only its decision on the last few investors outstanding. Read More

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Here's why those tech billionaires are throwing millions at ethical AI

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Worried about a dystopian future in which AI rule the world and humans are enslaved to autonomous technology? You’re not alone. So are billionaires (kind of).

First it was the Partnership on AI formed by Google, Amazon, Microsoft, Facebook and IBM. 

Then came Elon Musk and Peter Thiel’s recent investment in $1 billion research body, OpenAI. 

Now, a new batch of tech founders are throwing money at ethical artificial intelligence (AI) and autonomous systems (AS). And experts say it couldn’t come sooner. 

LinkedIn founder, Reid Hoffman, and eBay founder, Pierre Omidyar (through his philanthropic investment fund) donated a combined $20 million to the Ethics and Governance of Artificial Intelligence Fund on Jan. 11 — helping ensure the future’s more “man and machine, not man versus machine,” as IBM CEO Ginny Rometty put it to WSJ Thursday. Read more…

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