I am not sure this will be true, i.e., lower memory demands.
There are some many bottlenecks and opportunities for improvement. If we have better quantization for reducing KV cache sizes via TurboQuant, that just means we will use the memory capacity elsewhere:
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RESEARCH
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Memory optimization bottlenecks and quantization trade-offs in LLMs
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Space Data Centers: Bold New Direction for AI Infrastructure
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one of the boldest ideas in ai infra right now: data centers in space excited to have @philipjohnston
, ceo of @starcloud_
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Verification Layer Critical for Building Reliable AI Skills
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Yeah the verification layer is key, otherwise you're just accumulating broken skills
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Google Completes Fucked SEO Update; Google Sites Still Active
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The "Fucked SEO" update is done. It was fast. mhmm "google sites" is still alive
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Energy and Efficiency: Key Breakthroughs for Industrial-Scale Intelligence
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The two constraints to Industrial-scale Intelligence are energy and efficiency!
— Nina Schick (@NinaDSchick) 25 mars 2026
Solving here, massively, for the latter. A big breakthrough @GoogleResearch. https://t.co/eiT2MLoWzBThe two constraints to Industrial-scale Intelligence are energy and efficiency! Solving here, massively, for the latter. A big breakthrough @GoogleResearch
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Open Source and Science Research Experiments in AI
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Let's gooo! excited to see more open source/ science experiments and research from you!
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Broken retrieval systems can’t be fixed with prompts
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Hard truth for every AI builder: you cannot prompt your way out of a broken retrieval system.
— God of Prompt (@godofprompt) 25 mars 2026
You've probably experienced this. You write the perfect system prompt. You fine-tune the agent instructions. But the agent still fires on the wrong context because the context it was… https://t.co/nlxImXOwqZ pic.twitter.com/tTh1nHgAETHard truth for every AI builder: you cannot prompt your way out of a broken retrieval system. You've probably experienced this. You write the perfect system prompt. You fine-tune the agent instructions. But the agent still fires on the wrong context because the context it was
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SASInnovate Conference: 200+ Sessions on Data and AI Skills
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Don't miss out on the incredible opportunity to join #SASInnovate! Experience 3+ days of invaluable networking, choose from 200+ breakout sessions + learn from expert speakers who will elevate your data and AI skills. Reserve your seat http://
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Self-Evolving Agents: The Future of AI Technology
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Rightly said, I think self-evolving agents are the future.
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RetinaNet and Focal Loss: Solving Class Imbalance in Object Detection
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🎯 RetinaNet & Focal Loss: Fixing Class Imbalance in Object Detection
— Satya Mallick (@LearnOpenCV) 25 mars 2026
Single stage detectors were fast but struggled with class imbalance. In 2017, researchers at Facebook AI introduced RetinaNet with a new loss function Focal Loss.
By down-weighting easy background examples… pic.twitter.com/1gQ9p8Ku7jRetinaNet & Focal Loss: Fixing Class Imbalance in Object Detection Single stage detectors were fast but struggled with class imbalance. In 2017, researchers at Facebook AI introduced RetinaNet with a new loss function Focal Loss. By down-weighting easy background examples