TagsLiquid AI Releases LFM2-8B-A1B: An On-Device Mixture-of-Experts with 8.3B Params and a 1.5B Active Params per Token

Tag: Liquid AI Releases LFM2-8B-A1B: An On-Device Mixture-of-Experts with 8.3B Params and a 1.5B Active Params per Token

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Sigmoidal Scaling Curves Make Reinforcement Learning RL Post-Training Predictable for LLMs

Mr Hossain - October 17, 2025 0

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

Mr Hossain - October 13, 2025 0

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Google Introduces Speech-to-Retrieval (S2R) Approach that Maps a Spoken Query Directly to an Embedding and Retrieves Information without First Converting Speech to Text

Mr Hossain - October 12, 2025 0

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A Coding Implementation of Secure AI Agent with Self-Auditing Guardrails, PII Redaction, and Safe Tool Access in Python

Mr Hossain - October 12, 2025 0

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5 Most Popular Agentic AI Design Patterns Every AI Engineer Should Know

Mr Hossain - October 12, 2025 0

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Sentient AI Releases ROMA: An Open-Source and AGI Focused Meta-Agent Framework for Building AI Agents with Hierarchical Task Execution

Mr Hossain - October 12, 2025 0

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

Mr Hossain - October 11, 2025 0

AI

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

Mr Hossain - October 11, 2025 0

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