open source AI - Page 19

CrowdStrike says an unnamed, likely Chinese-speaking attacker used ARTEX, an open-source AI penetration-testing agent, alongside several AI models to steal data from South Korean financial firms. What CrowdStrike found, what Korean investigators say, and what it does not prove.

JetBrains has released Mellum2.1, a small open model for coding agents, and Hugging Face has released Carbon-A, a 1.2B-parameter model that predicts protein-coding regions in DNA, plus a database of 566 million predicted loci. What each does, and which numbers are the developers' own.

Hugging Face's FineEnvs team has released an open framework that turns unmodified coding-agent harnesses such as Claude Code, Codex and OpenCode into reinforcement-learning environments. In its own tests, one small model scored 62% in one harness and 33% in another. What a harness is, how the training works, and what the results do and do not show.

Samsung's third-quarter guidance points to about ₩107.4 trillion in operating profit on ₩195 trillion of sales, up from ₩12.17 trillion a year ago, with AI data-centre memory demand credited. AWS becomes a Platinum member of the Linux Foundation, with a board seat. What the numbers say and what they leave out.

A new benchmark, TasteVal, says the best AI model now reaches expert-level results on eight AI research tasks with 2.3 times less compute, though its authors list reasons that may overstate progress. Preference Model has open-sourced Karotte, a framework for training environments that are harder to game, and DatologyAI has released Zephon, a data loader that keeps experiments repeatable when the GPU count changes. What each claims, and who measured it.

Cognition has given its Devin coding agent a memory: short notes kept in a Git repository and tidied each night by a "dreaming" session, with the format open-sourced. Separately, Hark has released Hark Pro, a free assistant built on a model trained to use computers. What each launch is, and which claims are the companies' own.

On 6 October OpenAI launched a Decisions API that returns yes/no probabilities, picks and rubric scores from GPT-6 Luna, and cut its API usage tiers from five to three. Perplexity released pplx-decider-v1.1-27b, an Apache 2.0 open-weight decision model. What decision models are, what each costs, and which scores are the vendors' own.

Nous Research has raised $90 million to build Hermes for Businesses, a company version of its MIT-licensed Hermes agent. The raise is confirmed; the valuation is reported, mostly at $1.5B, with one $1.2B figure in circulation. Nous's "2.5% of global token usage" is its own estimate.

Liquid AI open-sourced two "decision models" that give a structured answer in a single pass, in about 8 ms on an RTX 4090 by Liquid's figures. Perplexity open-sourced two search models that read text, images and PDF pages without OCR, where a small model can query an index built by a big one. What each does, in plain words.

NVIDIA’s LoGRA paper shows low-rank gradient sketches cutting average RL training memory by up to 45.7% on tested Qwen reasoning setups—and making 27B RL runnable on one 8×H100 node where dense Adam OOMs. What the method is, what Table 1 shows, and what it does not prove.