The Google DeepMind system significantly improved the power efficiency of the Google datacenter, via tweaks to how servers were run and the operation of power and cooling equipment. While the traditional approach to minimizing power consumption was to run as few cooling systems as possible, the AI instead recommended running all the systems at lower power levels. The difference in datacenter power usage when Google turned the machine learning recommendations on and off. To streamline that training process Google built it own specialized chips, known as Tensor Processing Units (TPUs), which accelerate the rate at which useful machine-learning models can be built using Google's TensorFlow software library.
And this was one of the big problems with classical AI, what was called the "symbol grounding problem." Could you give an example of where neuroscience has helped AI researchers give computers these sorts of skills? And trying to really push that far is what made us come with the Neural Turing Machine, where we introduce this idea of having a big external memory connected to the neural network that the neural network can access and use. Now we work with deep learning systems, these very large networks.
On July 5, Demis Hassabis, co-founder and CEO, DeepMind announced "the opening of DeepMind's first ever international AI research office in Edmonton, Canada, in close collaboration with the University of Alberta." In addition to contributing on the research and education end DeepMind plans to invest in programs to promote "Edmonton's growth as a technology and research hub." It welcomes the DeepMind move as yet another advance toward AI research in the country, which is the goal set by "the federal government's Pan-Canadian Artificial Intelligence Strategy." However, such systems tend to eliminate the need for humans on the jobs rather than increase employment opportunities, and new jobs don't magically open up when old ones are filled by machines.
The committee says it is looking for "pragmatic solutions to the issues presented, and questions raised by the development and use of artificial intelligence in the present and the future". The risk of data-based monopolies and'winner-takes-all' economics from big tech's big data push to garner AI advantage should be loud and clear. In another twist pertaining to DeepMind Health's activity in the UK, the country's data protection watchdog ruled earlier this month that the company's first data-sharing arrangement with an NHS Trust broke UK privacy law. Patients' consent had not been sought nor obtained for the sharing of some 1.6 million medical records for the purpose of co-developing a clinical task management app to provide alerts of the risk of a patient developing a kidney condition.
DeepMind, bought by Google for a reported 400 million pounds -- about $580 million -- in 2014, teamed up with scientists at the University of Oxford to find a way to make sure that AI agents don't learn to prevent, or seek to prevent, humans from taking control. The paper -- "Safely Interruptible Agents PDF," published on the website of the Machine Intelligence Research Institute (MIRI) -- was written by Laurent Orseau, a research scientist at Google DeepMind, Stuart Armstrong at Oxford University's Future of Humanity Institute, and several others. DeepMind's work with the Future of Humanity Institute is interesting: DeepMind wants to "solve intelligence" and create general purpose AIs, while the Future of Humanity Institute is researching potential threats to our existence. The founders -- Demis Hassabis, Mustafa Suleyman, and Shane Legg -- allowed their company to be bought by Google on the condition that the search giant created an AI ethics board to monitor advances that Google makes in the field.
Deep learning can screen social media behaviour on Twitter, Facebook and additional news stories to connect data points and make predictions. To figure this out, in 2014 the NASA, the Universities Space Research Association and Google joint the Quantum Artificial Intelligence Lab. Eurekahedge, an independent data provider and alternative investment research firm that specialises in hedge fund databases, stated that their own Eurekahedge AI/Machine Learning Hedge Fund Index has outperformed both traditional quant and more generalized hedge funds since 2010. The Guardian: Google's DeepMind makes AI program that can learn like a human
It sounds banal until you realise that the trainee might be an artificially intelligent voice-recognition system that requires real-world data to learn its trade. "Data collection and analysis is changing so rapidly that systems of governance can't keep up" Such questions of propriety and custodianship have been asked about data before – but medical information is uniquely valuable and sensitive. As revealed by New Scientist, the deal gave the AI company access to 1.6 million people's medical records to develop a monitoring tool for kidney patients: the ICO ruled that they were not properly informed about the use of their data, among other shortcomings. A report by the Royal Society and the British Academy recently concluded that the collection and analysis of data is changing so rapidly that the UK's systems of governance cannot keep up.
Microsoft Corp. is setting up a new research lab focused on artificial intelligence with the goal of creating more general-purpose learning systems. The new lab, called Microsoft Research AI, will be based at the company's headquarters in Redmond, Washington, and involve more than 100 scientists from across various sub-fields of artificial intelligence research, including perception, learning, reasoning and natural language processing. "The field has undergone a tremendous amount of centrifugal force over the years," Horvitz said in an interview, noting how computer vision experts rarely talked to natural language processing experts or vice versa. Microsoft's competitors, such as Alphabet Inc., have also talked about using AI to battle climate change and improve environmental sustainability -- including lowering the power consumption of data centers and factories or boosting crop yields.
Microsoft Corp. is setting up a new research lab focused on artificial intelligence with the goal of creating more general-purpose learning systems. The new lab, called Microsoft Research AI, will be based at the company's headquarters in Redmond, Washington, and involve more than 100 scientists from across various sub-fields of artificial intelligence research, including perception, learning, reasoning and natural language processing. "The field has undergone a tremendous amount of centrifugal force over the years," Horvitz said in an interview, noting how computer vision experts rarely talked to natural language processing experts or vice versa. In addition to its existing researchers, Horvitz said Microsoft plans to hire computer scientists and experts in fields such as cognitive psychology to join the new lab.