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Intel & NVIDIA Announce Strategic Collaboration

This collaboration will integrate NVIDIA’s AI and accelerated computing technologies with Intel’s CPUs and x86 ecosystem, using NVIDIA NVLink for seamless connectivity.

For data centers, Intel will build NVIDIA-custom x86 CPUs that NVIDIA will integrate into its AI infrastructure platforms and offer to the market. However, the spotlight is on personal computing, for which Intel will build and offer to the market x86 system-on-chips (SOCs) that integrate NVIDIA RTX GPU chiplets. These new x86 RTX SoCs are designed to “power a wide range of PCs that demand integration of world-class CPUs and GPUs.”

Are tech monopolies just becoming even bigger monopolies with less competition? It’s worth noting that Intel has actually done something similar before with AMD, and Kaby Lake-G is now largely viewed as a failure. Still, it’s hard to imagine this happening if Intel weren’t facing serious challenges. NVIDIA’s $5 billion investment in Intel, through common stock purchased at $23.28 per share, goes beyond a mere hint.

Output control of dissipative nonlinear multimode amplifiers using spacetime symmetry mapping

In many optical systems with time-reversal symmetry, it is possible to control the output waves by shaping the input fields. Now a scheme is presented that works for multimode fibres that lack time-reversal symmetry due to thermal effects.

AI model offers accurate and explainable insights to support autism assessment

Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and clear, explainable insights—including a model-estimated probability score for autism.

The model, outlined in a study published in eClinicalMedicine, was used to analyze resting-state fMRI data—a non-invasive method that indirectly reflects via blood-oxygenation changes.

In doing so, the model achieved up to 98% cross-validated accuracy for Autism Spectrum Disorder (ASD) and neurotypical classification and produced clear, explainable maps of the brain regions most influential to its decisions.

Shape-shifting material could transform future of implantable and ingestible medical devices

Researchers led by Rice University’s Yong Lin Kong have developed a soft but strong metamaterial that can be controlled remotely to rapidly transform its size and shape.

The invention, published in Science Advances, represents a significant advancement that can potentially transform ingestible and .

Metamaterials are synthetic constructs that exhibit unusual properties not typically found in . Instead of relying solely on , the effective behavior of these materials is primarily determined by the physical structure, i.e., the specific shape, arrangement and scale of their building blocks.

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