Author: Ricardo

Agentic AI Applications

Research-Grade EdgeBench Analysis: AI Agent Benchmarking, Leaderboard Analytics, Scaling Laws, and Evaluation Metrics
ByRicardo July 22, 2026July 22, 2026

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…

Read More Research-Grade EdgeBench Analysis: AI Agent Benchmarking, Leaderboard Analytics, Scaling Laws, and Evaluation Metrics
Machine Intelligence Quantum

Towards a quantum computer that learns from its errors
ByRicardo July 22, 2026

Machine Intelligence

Read More Towards a quantum computer that learns from its errors
AI Business Strategy AI Hardware & Chips

SenseTime’s Galaxy Project targets domestic AI chip scale-up
ByRicardo July 22, 2026July 22, 2026

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…

Read More SenseTime’s Galaxy Project targets domestic AI chip scale-up
Agentic AI AI Infrastructure

Unsloth vs Axolotl vs TRL vs LLaMA-Factory: A Fine-Tuning Framework Comparison on Speed, VRAM, and Multi-GPU
ByRicardo July 22, 2026

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…

Read More Unsloth vs Axolotl vs TRL vs LLaMA-Factory: A Fine-Tuning Framework Comparison on Speed, VRAM, and Multi-GPU
Annotation Healthcare

FDA-Ready Medical Image Annotation for Healthcare AI: A Complete Guide
ByRicardo July 22, 2026

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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AI Shorts Applications

Cisco Foundation AI Releases Antares: 350M and 1B Open-Weight Models That Localize Known Vulnerabilities Inside Real Codebases
ByRicardo July 22, 2026

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….

Read More Cisco Foundation AI Releases Antares: 350M and 1B Open-Weight Models That Localize Known Vulnerabilities Inside Real Codebases
Agentic AI AI Infrastructure

Poolside Releases Laguna S 2.1, an Open-Weight Agentic Coding Model Punching Above Its Weight Class on SWE-Bench Multilingual
ByRicardo July 22, 2026July 22, 2026

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…

Read More Poolside Releases Laguna S 2.1, an Open-Weight Agentic Coding Model Punching Above Its Weight Class on SWE-Bench Multilingual
Agentic AI AI Shorts

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
ByRicardo July 21, 2026July 21, 2026

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…

Read More 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
AI Infrastructure Artificial Intelligence

Validating Distributed LLM Serving Benchmarks with NVIDIA srt-slurm, SLURM Recipes, Parameter Sweeps, and Pareto Analysis
ByRicardo July 21, 2026

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…

Read More Validating Distributed LLM Serving Benchmarks with NVIDIA srt-slurm, SLURM Recipes, Parameter Sweeps, and Pareto Analysis
AI Infrastructure AIAI

The 2026 State of AI and Identity Report
ByRicardo July 21, 2026

A survey of over 300 CTOs, CISOs, and engineering leaders revealed a widening hole between AI adoption and id safety. 88% say AI has already outpaced their id infrastructure. 84% of probably the most assured organizations have already skilled a confirmed id incident. Shared SaaS id setups get hit twice as arduous. Our newest eBook…

Read More The 2026 State of AI and Identity Report

Author: Ricardo

Research-Grade EdgeBench Analysis: AI Agent Benchmarking, Leaderboard Analytics, Scaling Laws, and Evaluation Metrics

Towards a quantum computer that learns from its errors

SenseTime’s Galaxy Project targets domestic AI chip scale-up

Unsloth vs Axolotl vs TRL vs LLaMA-Factory: A Fine-Tuning Framework Comparison on Speed, VRAM, and Multi-GPU

FDA-Ready Medical Image Annotation for Healthcare AI: A Complete Guide

Cisco Foundation AI Releases Antares: 350M and 1B Open-Weight Models That Localize Known Vulnerabilities Inside Real Codebases

Poolside Releases Laguna S 2.1, an Open-Weight Agentic Coding Model Punching Above Its Weight Class on SWE-Bench Multilingual

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

Validating Distributed LLM Serving Benchmarks with NVIDIA srt-slurm, SLURM Recipes, Parameter Sweeps, and Pareto Analysis

The 2026 State of AI and Identity Report

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