Google has challenged China's top Go player to a series of games against its artificial intelligence technology. It said the software would play a best-of-three match against Ke Jie, among other games against humans in the eastern Chinese city of Wuzhen from 23-27 May. Last year, the Google program recorded a 4-1 victory against one of South Korea's top Go players. One expert said that result had come as a surprise. "A lot of AI researchers have been working on Go because it's the most challenging board game we have," said Calum Chace, author of Surviving AI. "The conventional wisdom was that machines would ultimately triumph but it would take 10 years or so. "The win was a big wake-up call for a lot of people, including many outside the AI community." Google's AlphaGo software was developed by British computer company DeepMind, which was bought by the US search firm in 2014. Its defeat of Lee Se-dol in March 2016 is seen as a landmark moment, similar to that of IBM's Deep Blue AI beating Garry Kasparov at chess in 1997. Several of the moves AlphaGo made defied conventional wisdom but ended up paying off. However, many Go aficionados did not recognise Mr Lee as the world's top player at the time of the contest. So, the new competition against 19-year-old Mr Ke - who is the current number one according to a popular but unofficial player-ranking system - has the potential to bring additional prestige to Google. "We've been hard at work improving AlphaGo to become even more creative, and since playing Lee Se-dol, the program has continued to learn through self-play training," a spokeswoman for DeepMind told the BBC. "We intend to publish more scientific papers in the future, which will include further details of AlphaGo's progress." Google added that Mr Lee would also be invited, but was not sure if he would attend. Over the past year, DeepMind's technology has also been used to find ways to reduce energy bills at Google's data centres as well as to try to improve care in British hospitals. A fresh wave of positive publicity could help Google find further uses for its tech. "If it loses this match, a lot of people will be delighted to claim that Google and DeepMind has overpromised and that this is the kind of hype we always get with AI," commented Mr Chace. "But I wouldn't have thought Google is taking a huge risk.

In April 2017, DeepMind CEO Demis Hassabis drew on his eclectic experiences as an AI researcher, neuroscientist and videogames designer to discuss what is happening at the cutting edge of AI research, including the recent historic AlphaGo Go, and its future potential impact on fields such as science and healthcare, and how developing AI can help human better understand the human mind and explore new knowledge. Demis Hassabis (born 27 July 1976) was born to a Greek Cypriot father and a Chinese mother and grew up in North London. A child prodigy in chess, Hassabis reached master standard at the age of 13 with an Elo rating of 2300 (at the time the second highest rated player in the world Under-14 after Judit Polgár who had a rating of 2335) and captained many of the England junior chess teams. Now he is a pioneer in artificial intelligence, a neuroscientist, computer game designer, entrepreneur, and world-class games player.

You have to take the stairs to shatter the glass ceiling.

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What are tech titans Google, Amazon and Uber agitating for to further the march of machine learning technology and ultimately inject more fuel in the engines of their own dominant platforms? Specifically, they're pushing for free and liberal access to publicly funded data -- urging that this type of data continue to be "open by default," and structured in a way that supports "wider use of research data." After all, why pay to acquire data when there are vast troves of publicly funded information ripe to be squeezed for fresh economic gain? Other items on this machine learning advancement wish-list include new open standards for data (including metadata); research study design that has the "broadest consents that are ethically possible," and a stated desire to rethink the notion of "consent" as a core plank of good data governance -- to grease the pipe in favor of data access and make data holdings "fit for purpose" in the AI age. These suggestions come in a 125-page report published today by the Royal Society, aka the U.K.'s national academy of science, ostensibly aimed at fostering an environment where machine learning technology can flourish in order to unlock mooted productivity gains and economic benefits -- albeit the question of who, ultimately, benefits as more and more data gets squeezed to give up its precious insights is the overarching theme and unanswered question here.

Researchers studying a deal in which Google's artificial intelligence subsidiary, DeepMind, acquired access to millions of sensitive NHS patient records have warned that more must be done to regulate data transfers from public bodies to private firms. The academic study says that "inexcusable" mistakes were made when, in 2015, the Royal Free NHS Foundation Trust in London signed an agreement with Google DeepMind. This allowed the British AI firm to analyse sensitive information about 1.6 million patients who use the Trust's hospitals each year. The access was used for monitoring software for mobile devices, called Streams, which promises to improve clinicians' ability to support patients with Acute Kidney Injury (AKI). But according to the study's authors, the purposes stated in the agreement were far less specific, and made more open-ended references to using data to improve services.

Google's DeepMind CEO Demis Hassabis shows that AI doesn't only learn from human knowledge, but also creates new knowledge. AlphaGo has it own creativity and intuition, inventing new knowledge and strategies about Go Game for human professionals to study in 2017. Go game was invented in ancient China more than 2,500 years ago, is an abstract strategy board game, aiming to surround more territory than the opponent for two players. It is believed to be the oldest board game continuously played today.Despite its relatively simple rules, Go is very complex, even more so than chess, and possesses more possibilities than the total number of atoms in the visible universe. Compared to chess, Go has both a larger board with more scope for play and longer games, and, on average, many more alternatives to consider per move.

Google-stablemate DeepMind is creating a blockchain-like system to show how sensitive medical data passing through its processors will be used, allowing healthcare professionals to check if data has been tampered with. Its healthcare arm, DeepMind Health, is working to improve medical diagnoses with machine learning tools. Large amounts of confidential data are required to develop these tools – something DeepMind hasn't always been trusted to handle. Last year, DeepMind was criticized for gaining access to current and historic patient records for 1.6 million individuals across three London Royal Free NHS Trust hospitals – which extended well beyond the scope of the research they had publicly disclosed. The announcement of Verifiable Data Audit this week is an attempt to gain back some of the lost trust.

Alphabet's artificial intelligence (AI) division DeepMind continues to enhance its healthcare credentials with the arrival of a Bitcoin-like auditing process to protect the personal data of patients. The London-based firm is calling its data verification process the "Verifiable Data Audit". The idea is that it will give patients peace of mind with a "mathematical assurance about what is happening with each individual piece of personal data." It comes amid growing awareness of the value of personal data, and a loss in trust in organisation's abilities to protect their information. The NHS for example is notorious over its shoddy handling of patient data, with numerous incidents reported over the past few years.

Just over a year ago, an artificial intelligence beat the fourth-ranked player in the world at Go, a complex and ancient game that is said to be a better test of the unique capabilities of the human brain than chess. Now, that same artificial intelligence, called AlphaGo, is preparing for its next public demonstration: a summit in China in May where it will collaborate with human players to come up with strategies, and then face off against the top-ranked player in a series of three matches. If it wins, it will have shown that its underlying algorithms are ready for something more than a game. AlphaGo is the product of DeepMind, a London-based division of Google parent company Alphabet. DeepMind was founded in 2010 around the goal of researching artificial intelligence in order to understand the nature of intelligence and harness the full power of computerized brainpower for humanity. Its experiments with Go -- a game thought to be years away from being conquered by AI before last year -- are designed to bring us closer to designing a computer with human-like understanding that can solve problems like a human mind can.