SambaNova and Intel’s heterogeneous x86 AI architecture https://
cloudcomputing-news.net/news/heterogen
eous-x86-ai-architecture-from-sambanova-and-intel/?utm_source=dlvr.it&utm_medium=twitter
… #Cloud #Automation #Data #Innovation #BusinessStrategy #AIStrategy #EnterpriseAI #CIO
AI HARDWARE
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SambaNova and Intel collaborate on heterogeneous x86 AI architecture
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Scaling AI from 80s to 2000s: Compute Not Enough
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Danny Hillis was scaling up AI with a massively parallel supercomputer in the 80s. In the 90s we had the data mining explosion, a.k.a. scaling up ML. In the 2000s we had the "big data" boom. And each time we noticed that no, compute etc. is not enough – you really need better
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AI ambition easy, execution hard: Dell AI Factory with NVIDIA
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AI ambition is easy. AI execution is the hard part. A lot of companies have ideas, pilots, and demos. Far fewer have the infrastructure, governance, and operational readiness to deploy AI at scale. That’s why the Dell AI Factory with NVIDIA conversation matters: moving
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Jensen Huang on Dell Deskside Agentic AI and Practicality
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This feels like the enterprise AI conversation getting very real. When Jensen Huang talks about Dell Deskside Agentic AI, the key for me is practicality: secure local agents, open sandboxed environments, Dell infrastructure, and services that help teams actually get to
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A Guide to Setting Up Local AI Environments
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Gentle reminder that all you need to start with Local AI is: – 2x RTX 3090s (pick up for $700-$900 on r/hardwareswap) – Qwen 3.6 27B / Gemma 4 31B – Your favorite agent (Claude Code / OpenCode / etc) – Self-hosted SearXNG for web access And you got yourself Opus 4.5 at home
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GPU Memory Math for LLMs Explained
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First, GPU Memory Math for LLMs (or why it is not always about Memory Size)
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Meta experiments with AI-powered neural interfaces for mobility
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Another example: Meta is experimenting with wrist-worn AI interfaces for people with limited mobility.
— The Rundown AI (@TheRundownAI) 18 mai 2026
Cass has a spinal-cord injury, and uses two Meta Neural Bands to play a racing game.
Small forearm signals replace the inputs most players would make on a controller: pic.twitter.com/SnvBdOQaQEAnother example: Meta is experimenting with wrist-worn AI interfaces for people with limited mobility. Cass has a spinal-cord injury, and uses two Meta Neural Bands to play a racing game. Small forearm signals replace the inputs most players would make on a controller:
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NVIDIA-backed sparsity optimization for faster LLM training and inference
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/2 NVIDIA-backed sparsity trick makes LLM training and inference 20% faster on H100s. AI models already do less math than you'd think. Over 95% of neurons stay silent for any given word processed. That's free efficiency, right? Not quite. The problem: GPUs hate irregular work.
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AI races: top contenders in models, data centers, chips
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The three AI races and their top contenders:
Models: OpenAI, Anthropic, Google
Data centers: Amazon, Microsoft, Google
Chips: Nvidia, AMD, Google -
Microsoft missed AI wave, Copilot struggles, NPUs no killer app
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Former Microsoft VP says Microsoft missed the AI wave like the internet and mobile, as Copilot scales back in Windows 11 Microsoft spent $37.5B per quarter on AI. Less than 3.3% of Microsoft 365 users pay for Copilot. OEMs stuffed NPUs into every laptop, and not a single k1ller