A new technical paper titled “Pushing the Envelope of LLM Inference on AI-PC and Intel GPUs” was published by researcher at ...
A call to reform AI model-training paradigms from post hoc alignment to intrinsic, identity-based development.
Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.
Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...
While standard models suffer from context rot as data grows, MIT’s new Recursive Language Model (RLM) framework treats ...
Creating pages only machines will see won’t improve AI search visibility. Data shows standard SEO fundamentals still drive AI ...
DeepSeek's new Engram AI model separates recall from reasoning with hash-based memory in RAM, easing GPU pressure so teams ...
Detailed in a recently published technical paper, the Chinese startup’s Engram concept offloads static knowledge (simple ...
The evidence shows that, under controlled conditions, LLM judges can align closely with clinician judgments on concrete, ...
It sounds trivial, almost too silly to be a line item on a CFO’s dashboard. But in a usage-metered world, sloppy typing is a ...
What if the future of artificial intelligence isn’t just about building smarter systems but rethinking what intelligence itself means? In this walkthrough, Pourya Kordi shows how the latest ...
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