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Offline Video-LLMs Can Now Understand Real-Time Streams: Apple Researchers Introduce StreamBridge...

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Asus is developing the ROG Flow Z13 to make more sense...

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Nvidia CEO: PC gaming will never be rendered entirely by AI

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Nvidia’s AI Snake is feeding itself. Announces GeForce GTX 5090 GPU....

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Mergers & Acquisitions

Navigating AI M&A: A Comprehensive Guide to Due Diligence in the...

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LG and Samsung will add Microsoft Copilot to their new TVs.

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AI Hardware

HP at CES: The latest Elitebooks powered by Intel’s AI chips

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Global Policies

Experts say that Trump revoking Biden’s AI EO will cause chaos...

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Global Policies

ServiceNow launches enterprise AI governance capabilities

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Expert Columns

Tips for ChatGPT Voice Mode? What are the best AI uses...

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More and more young people are choosing the agricultural profession, and...

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Education

RL^V: Unifying Reasoning and Verification in Language Models through Value-Free Reinforcement...

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Implementing an LLM Agent with Tool Access Using MCP-Use

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A Step-by-Step Guide to Deploy a Fully Integrated Firecrawl-Powered MCP Server...

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Education

Reinforcement Learning, Not Fine-Tuning: Nemotron-Tool-N1 Trains LLMs to Use Tools with...

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RL^V: Unifying Reasoning and Verification in Language Models through Value-Free Reinforcement...

LLMs have gained outstanding reasoning capabilities through reinforcement learning (RL) on correctness rewards. Modern RL algorithms for LLMs, including GRPO, VinePPO, and Leave-one-out PPO, have moved away from traditional PPO approaches by eliminating the learned value function network in favor of empirically estimated returns. This reduces computational demands and...