​[[{“value”:” This post was written with Sarah Ostermeier from Comet. As enterprise organizations scale their machine learning (ML) initiatives from proof of concept to production, the complexity of managing experiments, tracking model lineage, and managing reproducibility grows exponentially. This is primarily because data scientists and… Read More »Rapid ML experimentation for enterprises with Amazon SageMaker AI and Comet Vikesh Pandey Artificial Intelligence

​Let’s face it: keeping up with new research, tools, and industry shifts in machine learning can be down-right overwhelming. Let’s face it: keeping up with new research, tools, and industry shifts in machine learning can be down-right overwhelming.  Read More  

​[[{“value”:” Alibaba’s Qwen team has just released FP8-quantized checkpoints for its new Qwen3-Next-80B-A3B models in two post-training variants—Instruct and Thinking—aimed at high-throughput inference with ultra-long context and MoE efficiency. The FP8 repos mirror the BF16 releases but package “fine-grained FP8” weights (block size 128) and… Read More »Alibaba Qwen Team Just Released FP8 Builds of Qwen3-Next-80B-A3B (Instruct & Thinking), Bringing 80B/3B-Active Hybrid-MoE to Commodity GPUs Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Can a 8B-parameter language model produce provably valid multi-step plans instead of plausible guesses? MIT CSAIL researchers introduce PDDL-INSTRUCT, an instruction-tuning framework that couples logical chain-of-thought with external plan validation (VAL) to lift symbolic planning performance of LLMs. On PlanBench, a tuned Llama-3-8B reaches… Read More »MIT Researchers Enhanced Artificial Intelligence (AI) 64x Better at Planning, Achieving 94% Accuracy Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Meta researchers introduced a method that compresses repeated reasoning patterns into short, named procedures—“behaviors”—and then conditions models to use them at inference or distills them via fine-tuning. The result: up to 46% fewer reasoning tokens on MATH while matching or improving accuracy, and up… Read More »Meta AI Proposes ‘Metacognitive Reuse’: Turning LLM Chains-of-Thought into a Procedural Handbook that Cuts Tokens by 46% Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” IBM researchers, together with ETH Zürich, have unveiled a new class of Analog Foundation Models (AFMs) designed to bridge the gap between large language models (LLMs) and Analog In-Memory Computing (AIMC) hardware. AIMC has long promised a radical leap in efficiency—running models with a… Read More »IBM and ETH Zürich Researchers Unveil Analog Foundation Models to Tackle Noise in In-Memory AI Hardware Asif Razzaq Artificial Intelligence Category – MarkTechPost