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@faun shared a link, 2 months, 2 weeks ago

How to Build an Asynchronous AI Agent Network Using Gemini for Research, Analysis, and Validation Tasks

The Gemini Agent Network Protocol introduces powerful AI collaboration with four distinct roles. Leveraging Google’s Gemini models, agents communicate dynamically for improved problem-solving...

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@faun shared a link, 2 months, 2 weeks ago

A Reality Check on DeepSeek's Distributed File System Benchmarks

3FSisn't quite matching its own hype. Yes, it boasts a flashy8 TB/s peak throughput, but pesky network bottlenecks throttle usage to roughly 73% of its theoretical greatness. Efficiency’s hiding somewhere, laughing. A dig intoGraySortshows storage sulking on the sidelines, perhaps tripped up by CRAQ..

A Reality Check on DeepSeek's Distributed File System Benchmarks
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@faun shared a link, 2 months, 2 weeks ago

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

FrontierLarge Reasoning Models (LRMs)crash into an accuracy wall when tackling overly intricate puzzles, even when their token budget seems bottomless.LRMsexhibit this weird scaling pattern: they fizzle out as puzzles get tougher, while, curiously, simpler models often nail the easy stuff with flair..

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
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@faun shared a link, 2 months, 2 weeks ago

ChatGPT polluted the world forever, like the first atom bomb

AI model collapsecould hit hard with synthetic data in play. Picturepre-2022 dataas the “low-background steel” savior for pristine datasets. The industry squabbles over thetrue fallout, while researchers clamor for policies that keep data unsullied. The worry? AI behemoths might lock everyone else o..

ChatGPT polluted the world forever, like the first atom bomb
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@faun shared a link, 2 months, 2 weeks ago

Reinforcement Learning Teachers of Test Time Scaling

Reinforcement-Learned Teachers (RLTs)ripped through LLM training bloat by swapping "solve everything from ground zero" with "lay it out in clear terms." Shockingly, a lean 7B model took down hefty beasts likeDeepSeek R1. These RLTs flipped the script, letting smaller models school the big kahunas wi..

Reinforcement Learning Teachers of Test Time Scaling
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@faun shared a link, 2 months, 2 weeks ago

Run the Full DeepSeek-R1-0528 Model Locally

DeepSeek-R1-0528's nanized form chops space needs down to162GB. But here's the kicker—without a solid GPU, it's like waiting for paint to dry...

Run the Full DeepSeek-R1-0528 Model Locally
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@faun shared a link, 2 months, 2 weeks ago

Announcing up to 45% price reduction for Amazon EC2 NVIDIA GPU-accelerated instances

AWS chops up to45%from Amazon EC2 NVIDIA GPU prices. Now your AI training costs less even as GPUs play hard to get...

Announcing up to 45% price reduction for Amazon EC2 NVIDIA GPU-accelerated instances
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@faun shared a link, 2 months, 2 weeks ago

Why AI Features Break Microservices Testing and How To Fix It

GenAIcomplexity confounds conventional testing. But savvy teams? They fast-track validation insandbox environments, slashing AI debug time from weeks down to mere hours...

Why AI Features Break Microservices Testing and How To Fix It
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@faun shared a link, 2 months, 2 weeks ago

Training a Rust 1.5B Coder LM with Reinforcement Learning (GRPO)

DeepSeek-R1flips the script on training LLMs. Armed withGRPO, it challenges the industry heavies like OpenAI's o1 by playing smart with custom data and cleverly designed rewards. Imagine this: a humble 1.5B model, running on merely asingle H100, clocks in at an 80% build pass rate. It’s nibbling at ..

Training a Rust 1.5B Coder LM with Reinforcement Learning (GRPO)
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@faun shared a link, 2 months, 2 weeks ago

AWS' custom chip strategy is showing results, and cutting into Nvidia's AI dominance

Graviton4just cranked up the juice to600 Gbps. In the grand race of public cloud champions, it's gunning straight for Nvidia's AI kingdom, powered by the formidableProject Rainier...

AWS' custom chip strategy is showing results, and cutting into Nvidia's AI dominance
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