SymptomAI: Towards a conversational AI agent for everyday symptom assessment
General Science
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Research-Grade EdgeBench Analysis: AI Agent Benchmarking, Leaderboard Analytics, Scaling Laws, and Evaluation Metrics
In this tutorial, we discover EdgeBench as a sensible benchmark for evaluating superior AI brokers throughout various job classes, runtime environments, and interaction-time budgets. We start by downloading the dataset snapshot from Hugging Face, parsing the launched job specs, and analyzing the benchmark taxonomy, execution settings, web necessities, judging logic, and scoring metadata. We then…
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Towards a quantum computer that learns from its errors
Machine Intelligence
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SenseTime’s Galaxy Project targets domestic AI chip scale-up
SenseTime has launched the Galaxy Project, teaming with almost 20 companions to scale domestic AI chip infrastructure in China. In a keynote titled ‘Intelligent Transformation and Symbiosis,’ Yang Fan – the corporate’s co-founder and president of its Large Device Business Group – laid out what SenseTime describes as a closed loop connecting chip-level expertise, ecosystem…
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Unsloth vs Axolotl vs TRL vs LLaMA-Factory: A Fine-Tuning Framework Comparison on Speed, VRAM, and Multi-GPU
Four open supply tasks dominate LLM fine-tuning at present. Unsloth, Axolotl, TRL, and LLaMA-Factory all wrap the identical underlying PyTorch and Hugging Face stack. They diverge on the place they spend engineering effort. Unsloth rewrites kernels. Axolotl composes parallelism methods. TRL defines the coach APIs the others construct on. LLaMA-Factory optimizes for breadth of mannequin…
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FDA-Ready Medical Image Annotation for Healthcare AI: A Complete Guide
At the center of each profitable medical AI system lies one vital requirement: annotated coaching knowledge. Medical AI fashions don’t be taught anatomy, pathology, or illness patterns on their very own; they be taught from examples created by expert-reviewed annotation. Whether figuring out tumors on CT scans, segmenting organs in MRI, or detecting retinal abnormalities,…
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Cisco Foundation AI Releases Antares: 350M and 1B Open-Weight Models That Localize Known Vulnerabilities Inside Real Codebases
Cisco Foundation AI has launched Antares, a household of safety small language fashions (SLMs) constructed for one slim safety activity. The activity is vulnerability localization. Given a vulnerability description and a repository, discover the recordsdata containing the flaw. Two fashions are open-weight and accessible now on Hugging Face, Antares-350M and Antares-1B. Both are Apache 2.0….
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Poolside Releases Laguna S 2.1, an Open-Weight Agentic Coding Model Punching Above Its Weight Class on SWE-Bench Multilingual
Poolside has launched Laguna S 2.1, a 118B-parameter open-weight mannequin constructed for agentic coding. It is a Mixture-of-Experts (MoE) mannequin with 8B activated parameters per token. It helps a context window of as much as 1M tokens in each pondering and no-thinking modes. The weights are on Hugging Face beneath an OpenMDW-1.1 license, and the…
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Google Releases Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber: A Cheaper, More Token-Efficient Flash Tier Built for Agentic Workloads
Developers constructing manufacturing brokers want larger token effectivity, decrease latency, and extra dependable efficiency. Today, Google has released three new Gemini models. The lineup is Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. All three sit within the Flash tier, which Google tunes for velocity, price, and high-volume agentic work slightly than…
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Validating Distributed LLM Serving Benchmarks with NVIDIA srt-slurm, SLURM Recipes, Parameter Sweeps, and Pareto Analysis
In this tutorial, we discover NVIDIA’s srt-slurm framework and find out how we use srtctl to transform declarative YAML configurations into reproducible SLURM benchmark workflows for distributed LLM serving. We arrange the undertaking in Google Colab, examine its inside structure, outline a cluster configuration, dry-run built-in and customized recipes, and mannequin a disaggregated prefill-and-decode deployment…
