Nature

Strategy inference during learning via cognitive activity-based credit assignment models

To learn complex tasks, individuals (human or animal) often decompose them into elementary sub-tasks and learn an execution order for these elementary sub-tasks (also called actions in reference to ...
Semiconductor Engineering

AI Inference Needs A Mix-And-Match Memory Strategy

Interactive LLMs (chat, copilots, agents) with strict latency targets Long‑context reasoning (codebases, research, video) with massive KV (key value) cache footprints Ranking and recommendation models ...
SiliconANGLE

Red Hat expands agentic AI strategy with new inference, automation and sovereignty capabilities

IBM Corp. subsidiary Red Hat today is unveiling a broad set of product and partnership announcements aimed at helping enterprises put artificial intelligence into operation, modernize infrastructure ...
Digi Times

Groq anchors Nvidia's inference strategy; CPU redefines architecture for AI agents

As AI evolves from generating information to executing tasks, inference scenarios characterized by coding agents and requiring low latency and high throughput are ushering in the next phase of AI ...
Forbes

How AI Inference Costs Are Reshaping The Cloud Economy

While the tech world obsesses over headlines about the $100 million price tag to train GPT-4, the real economic story is happening in inference: the ongoing cost of actually running AI models in ...
Digi Times

Explainer: Why Nvidia's Groq LPU runs on Samsung silicon— Groq's scale and inference strategy

Nvidia CEO Jensen Huang highlighted at GTC 2026 that AI has shifted from early model training to an era defined by inference and agent computing. To meet growing inference demands, Nvidia integrated ...