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The NorthPole processor embeds a small amount of memory into each of its 256 cores, which are connected together in a way similar to the way parts of the brain are connected together with white matter. This means the chip mitigates the bottleneck entirely.

IBM’s NorthPole is more of a proof of concept than a fully functioning chip that can compete with the likes of AMD and Nvidia. It only includes 224MB of RAM, for example, which is nowhere near enough the scale required for AI or to run large language models (LLMs).

The chip can also just run pre-programed neural networks trained on separate systems. But its unique architecture means the real standout is the energy efficiency it can boast. The researchers claim that if NorthPole was created today with state-of-the-art manufacturing standards, it would be 25 times more efficienct than the best GPUs and best CPUs.

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BRUSSELS, Oct 29 (Reuters) — The Group of Seven industrial countries will on Monday agree a code of conduct for companies developing advanced artificial intelligence systems, a G7 document showed, as governments seek to mitigate the risks and potential misuse of the technology.

The voluntary code of conduct will set a landmark for how major countries govern AI, amid privacy concerns and security risks, the document seen by Reuters showed.

Leaders of the Group of Seven (G7) economies made up of Canada, France, Germany, Italy, Japan, Britain and the United States, as well as the European Union, kicked off the process in May at a ministerial forum dubbed the “Hiroshima AI process”.

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Something good about AI.

Sitting down with Bill gates to see how AI can be also be used for something good!

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Continue reading “Can AI really save the World? ft. Bill Gates” | >

Despite many studies showing pigeons are surprisingly smart, from being as good at counting as primates, to being able to identify breast cancer in X-rays, scientists are fighting a losing battle to dispute their widely held reputation as being a bit “dim-witted.”

A new study has pitted the pigeon up against an artificial-intelligence model and found that both bird and computer follow a similar process in order to work out the problem they’re presented with.

“We found really strong evidence that the mechanisms guiding pigeon learning are remarkably similar to the same principles that guide modern machine learning and AI techniques,” said Brandon Turner, lead author of the study and professor of psychology at Ohio State University. “Our findings suggest that in the pigeon, nature may have found a way to make an incredibly efficient learner that has no ability to generalize or extrapolate like humans would.”

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Dr. Lecia Sequist is the Program Director of the Cancer Early Detection & Diagnostics Clinic at Mass General Cancer Center. For nearly 20 years, she’s specialized in lung cancer.

Observing first-hand the obstacles involved in current screenings of lung cancer, Dr. Sequist made a career switch to the research of early lung cancer detection. This led her to meet MIT professor, Regina Barzilay. Together, they created Sybil – an open-source AI tool that uses pattern recognition to predict one’s risk of lung cancer.

Dr. Sequist shares the benefits of AI in preventative medicine, how AI works to assess cancer risks, the logistics of using AI, and the importance of getting screened for lung cancer.

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Continue reading “Detecting Lung Cancer EARLY With AI: Dr. Lecia Sequist” | >

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OpenAI combines the different GPT-4 models into a kind of “supermodel” in ChatGPT-4 powered ChatGPT can now decide for itself how it can best help you.

OpenAI is currently preparing a GPT-4 update for ChatGPT that allows you to upload PDFs and many other file types. Once uploaded, ChatGPT can be used to discuss the information in the document, such as extracting aspects or getting an explanation.

This feature is not new. It was previously hidden in the Advanced Data Analysis model, which you had to select from the model switcher to get the file upload button.

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In a new study, scientists from the US and Taiwan have theoretically demonstrated the existence of a universal lower bound on topological entanglement entropy, which is always non-negative. The findings are published in the journal Physical Review Letters.

Quantum systems are bizarre and follow their own rules, with quantum states telling us everything we know about that system. Topological entanglement entropy (TEE) is a measure that provides insights into emergent non-local phenomena and entanglement in with topological properties.

Given the fundamental role of quantum entanglement in and various information applications, understanding TEE becomes essential for gaining insights into the behavior of quantum systems.

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