Demis Hassabis, the cofounder and CEO of DeepMind, a Google-owned AI lab in London, is planning to buy a Tesla 3 from Elon Musk -- one of the company's earliest investors. Hassabis congratulated Musk on Twitter after Musk tweeted that 276,000 Model 3 orders had been made by the end of Saturday, just two days after the electric car was launched. He also said he was planning to buy one of the new vehicles. "Really amazing to hear!! Just placing my order...," Hassabis wrote. At 35,000 ( 24,423), the five-seater Model 3 is the cheapest Tesla to date and is due to start shipping in late 2017.

I am trying my own implementation of the DQN paper by Deepmind in tensor flow and am running into difficulty with clipping of the loss function. We also found it helpful to clip the error term from the update to be between 1 and 1. Because the absolute value loss function x has a derivative of 1 for all negative values of x and a derivative of 1 for all positive values of x, clipping the squared error to be between 1 and 1 corresponds to using an absolute value loss function for errors outside of the ( 1,1) interval. This form of error clipping further improved the stability of the algorithm. What I have tried so far is using tf.clip_by_value to clip the loss I calculate between -1 and 1.

What will Google do next? Google's London AI powerhouse has set up a new healthcare division and acquired a medical app called Hark, an article from Business Insider, tells us the latest. DeepMind, Google's artificial intelligence research group, launched a new division recently called DeepMind Health and acquired a healthcare app. The article describes DeepMind Health's new app called Hark, "Hark -- acquired by DeepMind for an undisclosed sum -- is a clinical task management smartphone app that was created by Imperial College London academics Professor Ara Darzi and Dr Dominic King. Lord Darzi, director of the Institute of Global Health Innovation at Imperial College London, said in a statement: "It is incredibly exciting to have DeepMind – the world's most exciting technology company and a true UK success story – working directly with NHS staff.

Demis Hassabis, the cofounder and CEO of DeepMind, a Google-owned AI lab in London, is planning to buy a Tesla 3 from Elon Musk -- one of the company's earliest investors. Hassabis congratulated Musk on Twitter after Musk tweeted that 276,000 Model 3 orders had been made by the end of Saturday, just two days after the electric car was launched. "Really amazing to hear!! Just placing my order...," Hassabis wrote. At 35,000 ( 24,423), the five-seater Model 3 is the cheapest Tesla to date and is due to start shipping in late 2017. Those interested in owning a Tesla 3 need to put down 1,000 ( 702) deposits to reserve their vehicles.

Google has made one its largest European acquisitions to date with a deal to buy DeepMind technologies, a London-based artificial intelligence firm which specialises in machine learning, advanced algorithms and systems neuroscience. The Guardian understands that Google paid 400m ( 650m) for DeepMind, which develops technologies for e-commerce and games, and has demonstrated computer systems capable of playing computer games. It aims, it says, to develop computers that think like humans. The two-year-old artificial intelligence startup was founded by former child chess prodigy and neuroscientist Demis Hassabis alongside Shane Legg and Mustafa Suleyman. DeepMind has reportedly competed with Google and other major artificial intelligence companies for talent and Google's chief executive Larry Page is said to have led the deal himself.

Mastering arcade games seems cute by comparison. Researchers at DeepMind, the Google-owned artificial intelligence lab, announced Wednesday they had achieved a breakthrough not thought possible for at least another decade: a computer program that defeats humans at Go, an enormously complicated strategy game. See Also: This robot can solve Rubik's Cube in one second This network was named by EContent Magazine to its "Trendsetting Products of 2014" list.

There's a wide class of generative models for which variational methods are the only known practical way to do inference. This includes basically any model with black-box ("neural") dependence relations, and many others as well, e.g., Bayesian nonparametrics for any significant dataset size. The point of variational methods is not to calculate partition functions (although you do get that as a side effect); the point is to fit sophisticated models that have complex latent structure. Which does yield improvements across pretty much any metric you'd care about.

DeepMind was a relatively unknown artificial intelligence (AI) startup in London up until 2014, when it was bought by Google for around 400 million. Today some of the smartest people in the world are queuing up to work at DeepMind, according to an article by Celemency Burton-Hill in The Guardian in February. Interestingly, the same article states that no one has ever left DeepMind, which has created a series of algorithms that can learn for themselves and beat the best humans at games like Go and "Space Invaders." Based in up-and-coming King's Cross, DeepMind now employs around 250 people. However, as Burton-Hill points out, getting a job there is far from easy.

The importance of Google owned DeepMind's AI victory over the world's best Go player is difficult to fathom. People expect computers to be smarter than human beings, however, Go is one game that was expected to be beyond what AI is capable of right now. The reason for this is that GO is a deceptively simple game with very few rules. All the pieces on the board have the same value, unlike chess where having more'valuable' pieces means that you will win more often than not. Players themselves describe the game as being based on intuition and'feel' rather than any set rules.

What next for Google's DeepMind, now that the company has mastered the ancient board game of Go, beating the Korean champion Lee Se-Dol 4–1 this month? A paper from two UCL researchers suggests one future project: playing poker. And unlike Go, victory in that field could probably fund itself – at least until humans stopped playing against the robot. The paper's authors are Johannes Heinrich, a research student at UCL, and David Silver, a UCL lecturer who is working at DeepMind. Silver, who was AlphaGo's main programmer, has been called the "unsung hero at Google DeepMind", although this paper relates to his work at UCL.