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Artificial intelligenceChips and semiconductors
Researchers propose UnO-NeSy, a unified ferroelectric field-effect transistor in-memory architecture for neuro-symbolic AI. The paper targets the memory demands of combining neural perception with symbolic reasoning and hyperdimensional computing.
Researchers propose UnO-NeSy, a unified ferroelectric field-effect transistor in-memory architecture for neuro-symbolic AI. The paper targets the memory demands of combining neural perception with symbolic reasoning and hyperdimensional computing.
The authors frame the design as a way to address data movement between compute and memory. It is an architectural research proposal; the preprint does not announce a commercially available accelerator.
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At the BUILD 2026 conference, the communications minister cited power, connectivity, cloud access and advanced chips as constraints on local AI growth.
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The Canadian AI-chip company says it will use the new funding to scale Galaxy servers and advance processor technology it licenses to customers.
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Researchers from Ottawa, Columbia and Hanyang reviewed post-CMOS materials and device approaches for artificial neurons; the work is a literature review, not a new chip prototype.
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