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@faun shared a link, 4 months 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, 4 months ago

Automate customer support with Amazon Bedrock, LangGraph, and Mistral models

Welcome to the jungle of customer support automation, fueled byAmazon BedrockandLangGraph. These tools juggle the circus act of ticket management, fraud sleuthing, and crafting responses that could even fool your mother. Integration with the likes ofJiramakes for a dynamic duo. Together, they tackle..

Automate customer support with Amazon Bedrock, LangGraph, and Mistral models
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@faun shared a link, 4 months ago

AI at Amazon: a case study of brittleness

Amazon Alexa floundered amid brittle systems: a decentralized mess where teams rowed in opposing directions, clashing product and science cultures in tow...

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@faun shared a link, 4 months ago

Amazon CEO warns staff: Eat or be eaten by AI

Amazon'sCEO sounds the alarm: AI is gearing up to decimate office jobs. He urges employees to sharpen their skills or risk getting the axe, all while Amazon unleashes a cavalcade of over1,000generative AI projects...

Amazon CEO warns staff: Eat or be eaten by AI
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@faun shared a link, 4 months 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, 4 months ago

Lenovo introduces new AI-optimized data center systems

Lenovo'sThinkSystem SR680a V4doesn't just perform—it explodes with AI power, thanks to Nvidia'sB200GPUs. We're talking4nmchips with a mind-boggling208 billion transistors. Boost? Try11x...

Lenovo introduces new AI-optimized data center systems
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@faun shared a link, 4 months 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, 4 months ago

Scaling Test Time Compute to Multi-Agent Civilizations

Turns out, Reasoning AIs use a single test compute unit to pack the punch of something 1,000 to 10,000 times its size—an acrobatics act impossible before the might of GPT-4.Noam Brown spilled the beans on Ilya's hush-hush 2021 GPT-Zero experiment, which flipped his views on how soon we'd see reasoni..

Scaling Test Time Compute to Multi-Agent Civilizations
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@faun shared a link, 4 months 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, 4 months 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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