There were new announcements from Nvidia's GPU Technology Conference and Google's TensorFlow Dev Summit while France announced its own national AI strategy in a report and vowed €1.5bn in public funding. TensorFlow conference - Google hosted the TensorFlow Dev Summit on Friday in Mountain View, California, and announced a range of updates for its code, which remains the most popular software framework for AI and machine learning. Here's a list of the main highlights; all these tools are now going to be rolled out to researchers: If you're a TF nerd, there are more details on the blog and the Youtube channel. Also, here is the download link to TensorFlow 1.7.0 for you to play around with over the Easter weekend. La AI stratégie de France - France's President Emmanuel Macron acknowledged the importance of AI and the need to catch up to the the United States and China.

Demis Hassabis, CEO of Google's DeepMind, poses with late physicist Stephen Hawking. Hassabis, Hawking and Tesla CEO Elon Musk all endorsed a set of guidelines last year for ethical AI development that will benefit humanity. AI has been a buzzword in Korean society ever since. As AlphaGo retired from competitive gaming in March 2017, the company has instead been concentrating on tackling "a very wide range of problems" that humans find difficult to resolve. "The majority of the AlphaGo team now devotes their time to new projects with the intention of using these general-purpose algorithms to help solve some of the world's most complex challenges in science and medicine," said Demis Hassabis, co-founder of DeepMind, in an email interview with the JoongAng Ilbo to mark the two-year anniversary of the high-profile match.

Machine Vision has come a long way since Imagenet, a large repository of labelled images that researchers use to train their newest Artificial Intelligence (AI) agents with, was released, but still to this day images with bad, tricky or just plain weird lighting can still confuse even the best AI's algorithms and get them to misreport whatever it is they're looking at. And there are a multitude of examples where an AI has been tricked or confused, such as an AI that was being used to run an autonomous train prototype that mistook a shadow for a rock and came to a dead stop on the track, and even Nvidia's DAVE 2.0 self-driving car software that under certain lighting conditions would send a simulated car off a cliff, both of which exemplify the issue that machine vision enthusiasts everywhere still face. Over the past couple of years in order to try to overcome the issue researchers have either tried to create special hand crafted rules about how light interacts with objects or used data sets that cover as many lighting situations as possible, but there is a nearly limitless combination of items and light in the real world and that handicaps both approaches. Now though a paper by researchers from MIT and DeepMind has detailed a new AI process that can identify images in different lighting without having to hand craft new rules or train on a huge data set. The process, called a Rendered Intrinsics Network, or RIN for short, automatically separates an image into reflectance, shape, and lighting layers.

Google's parent company Alphabet is increasingly commercializing the technology coming out of its artificial intelligence research unit DeepMind, four years after acquiring it. Earlier this week, Google's cloud business announced a new service that converts blocks of text into natural-sounding speech, the first product containing DeepMind code that's for sale. The new Google Cloud Text-to-Speech application programming interface costs $16 for every million characters of text it processes in DeepMind's artificial male and female voices. Alphabet operates other AI research groups, but DeepMind has been doing more futuristic work, like teaching computer systems to beat top-ranked players of the Chinese board game Go. DeepMind is one of Alphabet's so-called Other Bets, but in pushing the technology closer to Google, commercial applications are becoming more real.

DeepMind's work is based on a solid grounding in neuroscience. This has underpinned the company's strategy of developing AI by teaching computers to mimic the thought processes of our own brains, in particular, how we use information to make decisions and learn from our mistakes. Google's interest in DeepMind likely lies in advancing the fields of machine learning and simulated neural networks – developing machines with more human-like thought processes, with the capacity to carry out jobs which previously would have required trained humans. Aside from winning at games, DeepMind has also been implemented across numerous healthcare projects, such as a collaboration with UCL's radiotherapy department to reduce the amount of time it takes to plan treatments. The group has said that by unleashing machine learning on the process of mapping a patient's head and neck area, the time taken to create treatment plans for these complicated procedures could be reduced from four hours to around one hour. One specific DeepMind project involves a collaboration with London's Moorfields Eye Hospital.

An AI startup including original pioneers from DeepMind – the generalised artificial intelligence company acquired by Google for around $500 million – has roared out of stealth with a pledge to revolutionise the digital economy. Its starting premise is that today's digital economy is disconnected, with assets such as hotel rooms and cars drastically under-utilised and systems such as transport and energy networks poorly optimised. The underlying'smart ledger' contains several world first innovations including built-in AI, a new Useful Proof of Work consensus mechanism and a unique data structure that combines blockchain and Directed Acyclic Graph architecture to achieve the performance and scalability necessary to support millions of agents transacting together. CTO Toby Simpson explains: "Autonomous Economic Agents are set to revolutionise commerce. They're digital entities that can transact independently of human intervention and can represent people, machines or themselves. "Imagine a world that connects anything to anything and everything to everything, where data, services and information get up on their own two feet and deliver themselves with incredible precision.

In a sign Macron's efforts to woo top scientists and businesses may be starting to bear fruit, Samsung Electronics, Japan's Fujitsu and London-based Google-owned Deepmind announced plans to beef up their operations in Paris earlier.

Artificial Intelligence agents created by Google's DeepMind has taught itself to walk without receiving any human instructions beyond the task to somehow move forward. This reinforcement learning helps an AI to move efficiently in an unknown terrain without programming.

A new artificial intelligence that is learning to understand the'thoughts' of others has been built by Google-owned research firm DeepMind. The software is capable of predicting what other AIs will do, and can even understand whether they hold'false beliefs' about the world around them. DeepMind reports its bot can now pass a key psychological test that most children only develop the skills for at around age four. Its proficiency in this'theory of mind' test may lead to robots that can think more like humans. DeepMind reports its bot can now pass a key psychological test that most children only develop the skills for around age four.

True artificial intelligence is on its way, and we aren't ready for it. Just as our forefathers had trouble visualizing everything from the modern car to the birth of the computer, it's difficult for most people to imagine how much truly intelligent technology could change our lives as soon as the next decade -- and how much we stand to lose if AI goes out of our control. Fortunately, there's a league of individuals working to ensure that the birth of artificial intelligence isn't the death of humanity. From Max Tegmark's Future of Life Institute to the Harvard Kennedy School of Government's Future Society, the world's most renowned experts are joining forces to tackle one of the most disruptive technological advancements (and greatest threats) humanity will ever face. Perhaps the most famous organization to be born from this existential threat is OpenAI.