ML applications

QeRL: NVFP4-Quantized Reinforcement Learning (RL) Brings 32B LLM Training to a Single H100—While Improving Exploration

ML applications

5 Min Read

QeRL: NVFP4-Quantized Reinforcement Learning (RL) Brings 32B LLM Training to a Single H100—While Improving Exploration

By Editorial Team

October 16, 2025

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Meta AI’s ‘Early Experience’ Trains Language Agents without Rewards—and Outperforms Imitation Learning

ML applications

5 Min Read

Meta AI’s ‘Early Experience’ Trains Language Agents without Rewards—and Outperforms Imitation Learning

By Editorial Team

October 15, 2025

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NVIDIA Researchers Propose Reinforcement Learning Pretraining (RLP): Reinforcement as a Pretraining Objective for Building Reasoning During Pretraining

ML applications

5 Min Read

NVIDIA Researchers Propose Reinforcement Learning Pretraining (RLP): Reinforcement as a Pretraining Objective for Building Reasoning During Pretraining

By Editorial Team

October 14, 2025

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Ivy Framework Agnostic Machine Learning Build, Transpile, and Benchmark Across All Major Backends

ML applications

10 Min Read

Ivy Framework Agnostic Machine Learning Build, Transpile, and Benchmark Across All Major Backends

By Editorial Team

October 14, 2025

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SwiReasoning: Entropy-Driven Alternation of Latent and Explicit Chain-of-Thought for Reasoning LLMs

ML applications

4 Min Read

SwiReasoning: Entropy-Driven Alternation of Latent and Explicit Chain-of-Thought for Reasoning LLMs

By Editorial Team

October 13, 2025

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Meet OpenTSLM: A Family of Time-Series Language Models (TSLMs) Revolutionizing Medical Time-Series Analysis

ML applications

5 Min Read

Meet OpenTSLM: A Family of Time-Series Language Models (TSLMs) Revolutionizing Medical Time-Series Analysis

By Editorial Team

October 12, 2025

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A Coding Guide to Master Self-Supervised Learning with Lightly AI for Efficient Data Curation and Active Learning

ML applications

10 Min Read

A Coding Guide to Master Self-Supervised Learning with Lightly AI for Efficient Data Curation and Active Learning

By Editorial Team

October 12, 2025

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Agentic Context Engineering (ACE): Self-Improving LLMs via Evolving Contexts, Not Fine-Tuning

ML applications

4 Min Read

Agentic Context Engineering (ACE): Self-Improving LLMs via Evolving Contexts, Not Fine-Tuning

By Editorial Team

October 10, 2025

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Microsoft Research Releases Skala: a Deep-Learning Exchange–Correlation Functional Targeting Hybrid-Level Accuracy at Semi-Local Cost

ML applications

5 Min Read

Microsoft Research Releases Skala: a Deep-Learning Exchange–Correlation Functional Targeting Hybrid-Level Accuracy at Semi-Local Cost

By Editorial Team

October 10, 2025

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Tiny Recursive Model (TRM): A Tiny 7M Model that Surpass DeepSeek-R1, Gemini 2.5 pro, and o3-mini at Reasoning on both ARG-AGI 1 and ARC-AGI 2

ML applications

5 Min Read

Tiny Recursive Model (TRM): A Tiny 7M Model that Surpass DeepSeek-R1, Gemini 2.5 pro, and o3-mini at Reasoning on both ARG-AGI 1 and ARC-AGI 2

By Editorial Team

October 10, 2025

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ML applications

QeRL: NVFP4-Quantized Reinforcement Learning (RL) Brings 32B LLM Training to a Single H100—While Improving Exploration

Meta AI’s ‘Early Experience’ Trains Language Agents without Rewards—and Outperforms Imitation Learning

NVIDIA Researchers Propose Reinforcement Learning Pretraining (RLP): Reinforcement as a Pretraining Objective for Building Reasoning During Pretraining

Ivy Framework Agnostic Machine Learning Build, Transpile, and Benchmark Across All Major Backends

SwiReasoning: Entropy-Driven Alternation of Latent and Explicit Chain-of-Thought for Reasoning LLMs

Meet OpenTSLM: A Family of Time-Series Language Models (TSLMs) Revolutionizing Medical Time-Series Analysis

A Coding Guide to Master Self-Supervised Learning with Lightly AI for Efficient Data Curation and Active Learning

Agentic Context Engineering (ACE): Self-Improving LLMs via Evolving Contexts, Not Fine-Tuning

Microsoft Research Releases Skala: a Deep-Learning Exchange–Correlation Functional Targeting Hybrid-Level Accuracy at Semi-Local Cost

Tiny Recursive Model (TRM): A Tiny 7M Model that Surpass DeepSeek-R1, Gemini 2.5 pro, and o3-mini at Reasoning on both ARG-AGI 1 and ARC-AGI 2

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