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  1. scitechdaily.com

    3 days agoScaling neuromorphic computing to emulate brain efficiency offers a promising future in AI and technology, with strategic collaborations and advanced chip designs leading the charge. Researchers outline a bold strategy to scale neuromorphic computing, aiming to match human brain functionality with minimal energy use.
  2. neuroscience.stanford.edu

    3 days agoA new generation of researchers at Stanford's Wu Tsai Neurosciences Institute is developing tools to modify brain activity for research and clinical applications—without drilling through the skull. ... Other Wu Tsai Neuro scientists are using materials science and engineering to riff on tools that have transformed neuroscience research in ...
  3. english.elpais.com

    2 days agoPushmeet Kohli of Google DeepMind with Fiona Marshall, president of biomedical research at Novartis, and Alison Noble, professor of biomedical engineering at University of Oxford, during an AI panel at Science Forum, which took place in London. Q. Generative AI is supported by gigantic databases, which have already exhausted the entire internet ...
  4. interestingengineering.com

    Nov 7, 2024Scientist uses nanomagnets to build brain-like AI, cut power use, boost efficiency When placed in networks, nanomagnets feel each other much like neurons in the brain. Updated: Nov 07, 2024 08:20 ...
  5. (D) Brain-sensing cells could be used as a general platform to treat a broad set of CNS diseases such as primary and secondary brain tumors, neuroinflammation, or even neurodegeneration. This customizable platform can be used to locally deliver any genetically encodable molecular therapy that is appropriate for a specific CNS disease, thereby ...
  6. May 9, 2024The Google Research team developed advanced AI tools to construct an interactive 3D model of the brain tissue. The model underscores how complex the human brain is: describing just this small sample — one-millionth of the total human brain and about 3 mm long — requires more than a million Gigabytes of data: 1.4 Petabytes.
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