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 access sensitive information about 1.6 million patients who use the Trust's hospitals each year. The access was used to create 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.

As part of its projects with Britain's National Health Service, Google's artificial intelligence unit DeepMind announced last week it's developing a new way to protect confidential health data--from itself. Its problem: How to assure hospitals, and the public at large, that patient confidentiality isn't compromised as it processes the sensitive medical health records entrusted to it. DeepMind's proposed solution is to create an indelible data log that can't be tampered with. It would show when a piece of data was used, and for what purpose. Importantly, DeepMind itself wouldn't be able to modify logs to use the data nefariously.

The road to human-level artificial intelligence is long and wildly uncertain. Most AI programs today are one-trick ponies. They can recognise faces, the sound of your voice, translate foreign languages, trade stocks and play chess. They may well have got the trick down pat, but one-trick ponies they remain. Google's DeepMind program, AlphaGo, can beat the best human players at Go, but it hasn't a clue how to play tiddlywinks, shove ha'penny, or tell one end of a horse from the other.

DeepMind's partnership with the NHS proves technology can improve the state of the health and care system The app can immediately alert a clinician as soon as it detects signs of kidney failure in patients as nearly 30 doctors and nurses at the Royal Free Hospital have now started using it on a daily basis. "The app is delivering cultural change to the way technology is being used to improve care. The technology is no longer passive, but is actively helping us to provide better and timelier care to patients. "For example on one day this week, the app alerted us to 11 patients, ranging from a young cancer patient to an elderly patient suffering life-threatening dehydration, who were at risk of developing AKI (Acute Kidney Injury). "These patients had a range of different conditions and without the app it would have taken our staff much longer to realise they were developing kidney problems. The app enabled us to monitor our patients' kidney function, detect kidney failure early and intervene rapidly to manage complications and accelerate their recovery," said Chris Laing, a Renal Consultant involved in the development of the Streams app.

Right now it's easiest to think about an artificial intelligence algorithm as a specific tool, like a hammer. A hammer is really good at hitting things, but when you need a saw to cut something in half, it's back to the toolbox. Train an facial recognition algorithm, but don't ask it to recognize cows. Alphabet's AI research arm, DeepMind, is trying to change that idea with a new algorithm that can learn more than one skill. Having algorithms that can learn multiple skills could make it far easier to add new languages to translators, remove bias from image recognition systems, or even have algorithms use existing knowledge to solve new complex problems.

Computer programs that learn to perform tasks also typically forget them very quickly,

Through massive investments in artificial intelligence (AI) startups, the world's leading tech firms are racing to create markets to transform the economic landscape. DeepMind's technology is accessible to firms that run on Google's cloud. Intel's announcement to acquire Nervana came after Apple disclosed its deal to purchase Seattle-based machine learning and artificial intelligence startup Turi.

Researchers have overcome one of the major stumbling blocks in artificial intelligence with a program that can learn one task after another using skills it acquires on the way. Developed by Google's AI company, DeepMind, the program has taken on a range of different tasks and performed almost as well as a human. Crucially, and uniquely, the AI does not forget how it solved past problems, and uses the knowledge to tackle new ones.

Researchers have overcome one of the major stumbling blocks in artificial intelligence with a program that can learn one task after another using skills it acquires on the way. Developed by Google's AI company, DeepMind, the program has taken on a range of different tasks and performed almost as well as a human. Crucially, and uniquely, the AI does not forget how it solved past problems, and uses the knowledge to tackle new ones. The AI is not capable of the general intelligence that humans draw on when they are faced with new challenges; its use of past lessons is more limited. But the work shows a way around a problem that had to be solved if researchers are ever to build so-called artificial general intelligence (AGI) machines that match human intelligence.

The National Grid has confirmed that it is in the "earliest stages" of discussions exploring the use of Artificial Intelligence (AI), which could potentially maximise the use of renewable energy by predicting peaks in demand across the UK. The National Grid, which operates and owns the infrastructure that transports electricity across the UK, has seen its ability in balancing and stabilising the grid challenged in recent years as intermittent renewables such as solar and wind have been fed into the energy mix. While the introduction of renewables into the mix forms a key role in both national and European legislation to decarbonise the grid, concerns have been raised as to the National Grid's ability to deal with fluctuating wind and solar resources, which can sometimes produce more energy than the system can cope with. Energy storage and demand response initiatives, whereby businesses either store surplus energy or increase or reduce energy consumption based on demand, are being incorporated by the National Grid, which is now "exploring what opportunities" AI could offer to balance the situation. The National Grid revealed that it is in discussions with the UK-based AI company DeepMind about introducing new technologies to help balance the grid and improve the use of renewables.