AI News, Will DeepMind's Breast Cancer Diagnosis AI Replace Specialists? artificial intelligence


or a neural network that may be able to access an external memory like a conventional Turing machine, resulting in a computer that mimics the short-term memory of the human brain.[9][10]

The company made headlines in 2016 after its AlphaGo program beat a human professional Go player Lee Sedol, the world champion, in a five-game match, which was the subject of a documentary film.[11]

A more general program, AlphaZero, beat the most powerful programs playing go, chess and shogi (Japanese chess) after a few days of play against itself using reinforcement learning.[12]

During one of the interviews, Demis Hassabis said that the start-up began working on artificial intelligence technology by teaching it how to play old games from the seventies and eighties, which are relatively primitive compared to the ones that are available today.

DeepMind has opened a new unit called DeepMind Ethics and Society and focused on the ethical and societal questions raised by artificial intelligence featuring prominent philosopher Nick Bostrom as advisor.[33]

In 2017 DeepMind released GridWorld, an open-source testbed for evaluating whether an algorithm learns to disable its kill switch or otherwise exhibits certain undesirable behaviours.[42][43]

To date, the company has published research on computer systems that are able to play games, and developing these systems, ranging from strategy games such as Go[44]

According to Shane Legg, human-level machine intelligence can be achieved 'when a machine can learn to play a really wide range of games from perceptual stream input and output, and transfer understanding across games[...].'[45]

Hassabis has mentioned the popular e-sport game StarCraft as a possible future challenge, since it requires a high level of strategic thinking and handling imperfect information.[46]

As opposed to other AIs, such as IBM's Deep Blue or Watson, which were developed for a pre-defined purpose and only function within its scope, DeepMind claims that its system is not pre-programmed: it learns from experience, using only raw pixels as data input.

Without altering the code, the AI begins to understand how to play the game, and after some time plays, for a few games (most notably Breakout), a more efficient game than any human ever could.[50]

In October 2015, a computer Go program called AlphaGo, developed by DeepMind, beat the European Go champion Fan Hui, a 2 dan (out of 9 dan possible) professional, five to zero.[52]

Go is considered much more difficult for computers to win compared to other games like chess, due to the much larger number of possibilities, making it prohibitively difficult for traditional AI methods such as brute-force.[52][54]

After training these networks employed a lookahead Monte Carlo tree search (MCTS), using the policy network to identify candidate high-probability moves, while the value network (in conjunction with Monte Carlo rollouts using a fast rollout policy) evaluated tree positions.[60]

It won 10 consecutive matches against two professional players, although it had the unfair advantage of being able to see the entire field, unlike a human player who has to move the camera manually.

In October 2019, AlphaStar reached Grandmaster level on the StarCraft II ladder on all three StarCraft races, becoming the first AI to reach the top league of a widely popular esport without any game restrictions.[71]

DeepMind has also collaborated with the Android team at Google for the creation of two new features which will be available to people with devices running Android Pie, the ninth installment of Google's mobile operating system.

It is the first time DeepMind has used these techniques on such a small scale, with typical machine learning applications requiring orders of magnitude more computing power.[73]

In August 2016, a research programme with University College London Hospital was announced with the aim of developing an algorithm that can automatically differentiate between healthy and cancerous tissues in head and neck areas.[75]

Staff at the Royal Free Hospital were reported as saying in December 2017 that access to patient data through the app had saved a ‘huge amount of time’ and made a ‘phenomenal’ difference to the management of patients with acute kidney injury.

Additionally, in February 2018, DeepMind announced it was working with the U.S. Department of Veterans Affairs in an attempt to use machine learning to predict the onset of acute kidney injury in patients, and also more broadly the general deterioration of patients during a hospital stay so that doctors and nurses can more quickly treat patients in need.[79]

Privacy advocates said the announcement betrayed patient trust and appeared to contradict previous statements by DeepMind that patient data would not be connected to Google accounts or services.[82][83]

This included personal details such as whether patients had been diagnosed with HIV, suffered from depression or had ever undergone an abortion in order to conduct research to seek better outcomes in various health conditions.[85][86]

This new subdivision of DeepMind is a completely separate unit from the partnership of leading companies using AI, academia, civil society organizations and nonprofits of the name Partnership on Artificial Intelligence to Benefit People and Society of which DeepMind is also a part.[93]

Google's Deepmind can detect breast cancer using AI more accurately

Digital mammography, or X-ray imaging of the breast, is the most common method to screen for breast cancer, with over 42 million exams performed each year in the U.S. and U.K.

In turn, these inaccuracies can lead to delays in detection and treatment, unnecessary stress for patients and a higher workload for radiologists who are already in short supply.

These findings show that Deepmind's AI model spotted breast cancer in de-identified screening mammograms (where identifiable information has been removed) with greater accuracy, fewer false positives, and fewer false negatives than experts.

and then evaluated it on the data set from women in the U.S. In this separate experiment, there was a 3.5 percent reduction in false positives and an 8.1 percent reduction in false negatives, showing the model’s potential to generalize to new clinical settings while still performing at a higher level than experts.

The human experts (in line with routine practice) had access to patient histories and prior mammograms, while the model only processed the most recent anonymized mammogram with no extra information.

Samsung created an invisible keyboard that uses AI to track your finger movements - Business Insider

Samsung created an invisible keyboard that uses AI to track your finger movements SelfieType will use a front-facing camera to track your fingers and turn any empty surface into a virtual keyboard.

Beyond Meat 'never' says no to creating new fast-food menu item - Business InsiderBeyond Meat is building the capabilities to create unique plant-based meat products for every fast-food chain possible, from chicken to meatballs.

Samsung and LG unveil artificial intelligence-equipped smart fridges - Business InsiderSamsung and LG's AI-equipped smart fridges will use interior cameras to identify foods that need to be restocked, and can suggest recipes based on available ingredients: Store closures reached a new high in 2019 - Business Insider - Business InsiderWhile 2019 saw a record number of store closures, some retailers are giving stores new value by using them to facilitate e-commerce orders: Retailers can follow Walmart & Target that embraced buy online including pickup in-store offerings for consumers to pick up their orders.

The Decade of Deep Learning; AI Experts’ Hopes for 2020; AI Beats Doctors at Cancer Diagnosis?

The author hopes to provide a jumping-off point into many disparate areas of Deep Learning by providing succinct and dense summaries that go slightly deeper than a surface level exposition, with many references to the relevant resources.(Leo Gao) Hopes for AI in 2020: Yann LeCun, Kai-Fu Lee, Anima Anandkumar, Richard has invited Anima Anandkumar, Oren Etzioni, Chelsea Finn, Yann LeCun, Kai-Fu Lee, David Patterson, Richard Socher, Dawn Song and Zhi-Hua Zhou to express their hopes for 2020.( Google Just Beat Humans at Spotting Breast Cancer — But It Won’t Replace ThemGoogle is developing artificial intelligence to help doctors identify breast cancer.

(Boston University) Deep Sparse Rectifier Neural Networks This paper shows that rectifying neurons are an even better model of biological neurons and yield equal or better performance than hyperbolic tangent networks in spite of the hard non-linearity and non-differentiability at zero, creating sparse representations with true zeros, which seem remarkably suitable for naturally sparse data.(Université de Montréal) Happy AI New Year!

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