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While European nations are ahead on dimensions like equality, social progress, and climate change redressal, they lack technological advancements in comparison to the United States. The European region, including the UK, still lacks the investment and culture necessary for a startup ecosystem prevalent in California’s Silicon Valley.

The Valley is a globally recognized hub for technology and innovation. Many of the world’s leading technology companies, like Apple, Google, Facebook, and Amazon, are based there. However, Europe also has notable… More.


Silicon Valley overshadows the EU in tech, but with the advent of new-age artificial intelligence, Europe’s leading entrepreneurs think it could offer the Euro startup ecosystem to be a key player in the race.

Holographic imaging has always been challenged by unpredictable distortions in dynamic environments. Traditional deep learning methods often struggle to adapt to diverse scenes due to their reliance on specific data conditions.

To tackle this problem, researchers at Zhejiang University delved into the intersection of optics and , uncovering the key role of physical priors in ensuring the alignment of data and pre-trained models.

They explored the impact of spatial and on holographic imaging and proposed an innovative method, TWC-Swin, to restore high-quality holographic images in the presence of these disturbances. Their research, titled “Harnessing the magic of light: spatial coherence instructed swin transformer for universal holographic imaging,” is reported in the journal Advanced Photonics.

Startup Twin Health is developing a program that uses sensor data to construct a replica of a person’s metabolism and then simulate virtual interventions on the body. The simulations suggest non-drug recommendations that help reverse metabolic disorders such as diabetes.

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Researchers examine how the brain processes language by using intracranial recordings in epilepsy patients during reading tasks, revealing the neural networks responsible for semantic integration and distinguishing between semantic coherence and task-based referentiality. The study pinpoints specific brain regions activated during sentence processing and offers new insights into the spatiotemporal dynamics of language understanding.

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.

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”.

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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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.”

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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