AI Tools & Frameworks Directory

Nvidia is leaning hard into the trend of enterprise companies wanting to run their own open models in their own data centers and also trying to make on-device, private AI agents a thing.

A million-token output window changes what you can hand a model in one go, and the benchmarks and the bill show who it actually suits. The post Welcome to Google Gemini 4 Argon appeared first on Towards Data Science.

Lida Li, Sr. Staff Software Engineer, Product ML InfraIntroductionModern recommendation systems, including those used for ads ranking and content discovery, have grown substantially in scale and complexity. This growth stems from both increasingly large model architectures. The resulting memory foot...

At a creative industry event that took place today in Berlin — hosted in collaboration with Adobe, Bertelsmann, NVIDIA and UFA — the latest advancements in intelligent media were on display. Key to the news: the European Broadcasting Union (EBU) is collaborating with NVIDIA to expand its sovereign f...

ML model adoption doesn't stop with acceptance of accuracy; it starts there. The post Can Conformal Prediction Take You from Accurate to Reliable Machine Learning? appeared first on Towards Data Science.

MiniMax has released M3.1 Flash, a 428B-parameter MoE model with about 23B active parameters and a 1M-token context. API pricing is $0.15/$0.60 per 1M tokens, with weights due October 23 The post MiniMax Just Launched M3.1 Flash: 428B MoE Agentic Model at $0.15/M Input appeared first on MarkTechPost...

In this article, you will learn what Python descriptors are and how to use them to build three types of controlled attributes: validated, computed, and...

This summer, I built a small experiment called ContextCue. The idea came from something I kept seeing during my internship. The engineers around me were using AI everywhere in the software development process. GitHub Copilot and Claude models helped with specs, code, reviews, and tests. The team als...

Raising a big round is the easy part. A deeptech founder explains how project-level budgets, evidence-based milestones, and AI-assisted analysis help every pound of R&D capital buy down real risk.

What do AI agents do if you don’t tell them to do anything? The answer looks a lot like play. Researchers repeatedly stranded them alone on a virtual desert island for 30 hours in an experiment reminiscent of the movies Cast Away or Home Alone. The agents—copies of Claude Opus 4.7 nicknamed Eko—were...

arXiv:2610.22379v1 Announce Type: new Abstract: Calibrating expensive engineering simulators requires tuning model parameters to match reference data, a process heavily constrained by computational costs. This study investigates whether Large Language Models (LLMs), conditioned on physical diagnost...

arXiv:2610.22381v1 Announce Type: new Abstract: When a fact becomes harder to elicit from a language model, has the model lost it, or has it merely become less accessible? Parameter-updating test-time continual learning agents are usually evaluated by current output accuracy; we ask whether that me...

NVIDIA has released the full Run:ai GPU orchestration platform as open source under Apache 2.0. The release includes KAI Scheduler, CUDA 13.4 GPU fractioning, quota management, and a local Kind dev environment. The post NVIDIA Open Sources Run:ai Under Apache 2.0 for Kubernetes GPU Orchestration app...

Mistral released Timestral, a time series foundation model family from 5M to 209M parameters. The 209M model leads GIFT-Eval, TIME and fev-bench among zero-shot models and runs on CPU. The post Mistral AI Releases Timestral: A 209M Forecasting Model Family That Outperforms Google’s TimesFM-3 appeare...

This Applied AI edition looks at what organizations actually did with AI over the past two weeks, drawn from our Use-Case Library and from SEC filings. Three things stand out: AI now finds security flaws at record volume, AI agents do a large share of the work at some companies, and test agents keep...

Over three years, we’ve built progressively harder, more realistic benchmarks for medical AI. Here’s what we learned.

An AI agent that reads the web pays 2 kinds of cost. The first is the retrieval charge: what a search or fetch API bills per request. The second is model processing: content passed from retrieved pages into an AI model consumes tokens, while reasoning and generated responses add further costs. TinyF...

After chatbot startup Character.AI filed for bankruptcy earlier this week, many of its employees will have the opportunity to take jobs at Disney. Character.AI’s former CEO Karandeep Anand recently became the entertainment giant’s first CTO, and the startup previously said that Disney had agreed to ...

Every developer hits this wall eventually. A feature behaves in a way you can’t explain, and the code behind it is locked away. No source. No docs. Just a compiled binary or a wall of minified JavaScript. Figuring it out the traditional way means hours in a disassembler, specialist tools like Ghidra...

Google Research released Harness2, an Apache-2.0 framework that rewrites an agent's harness at test time. One refinement step lifted GLM-5 by 11.5 points on WorkBuddy-Bench with no weight updates. The post Google Open-Sources Harness2, a Recursive Agent Harnessing Framework appeared first on MarkTec...

Voxel51 3.0 merges search, curation, annotation and evaluation of multimodal sensor data into one platform for physical AI teams. It adds Voxel51 Agent with 45+ MCP tools, dataset versioning, and a free self-service tier. The post Meet Voxel51 3.0: A Unified Multimodal Data Platform for Physical AI ...

New research can help AI models understand crystalline materials in 3D and reason about their properties.

A Meta spokesperson insisted that the updated terms did not reflect a change in the way Meta crawls the web.