Auto Added by WPeMatico
EverMind has released EverOS, an open-source memory runtime for AI agents. It ships under an Apache 2.0 license. It targets a problem agent builders hit early: large language models are stateless. The conversation ends, and the context is gone. EverOS proposes a different substrate. Instead of locking memory inside a vector database, it writes memory […]
In this tutorial, we work with the Fable 5 Traces dataset from Hugging Face and build a complete workflow around real coding-agent trace data. We start by setting up a lightweight environment that avoids fragile dependencies such as datasets, scikit-learn, and scipy. Then we manually download and parse the merged JSONL file to keep the
Liquid AI shipped LFM2.5-230M, it’s the company’s smallest model to date. The release targets a specific job: running agentic tasks on phones, robots, and automation devices. Both the base and instruction-tuned checkpoints are open-weight on Hugging Face. The pitch is narrow on purpose. This is not a general reasoning model. It is built for data
DeepSeek released DSpark, a speculative decoding framework, with open-source checkpoints and training code. It is a serving optimization, not a new model. The checkpoints DeepSeek-V4-Pro-DSpark and DeepSeek-V4-Flash-DSpark reuse the existing V4 weights, with a draft module attached. The DeepSeek research team also open-sourced DeepSpec, an MIT-licensed codebase for training and evaluating speculative decoding drafters. The
Meta released Astryx this week. It is an open-source design system, currently in Beta. The project grew inside Meta’s monorepo over eight years. Astryx is built on React and StyleX. StyleX is Meta’s compile-time CSS engine. TL;DR Astryx is Meta’s open-source, agent-ready React design system, now in Beta. It pairs StyleX styling with a CSS-variable
In this tutorial, we explore the Open-SWE-Traces dataset as a practical resource for studying and preparing agentic software-engineering trajectories for fine-tuning. We stream the dataset directly from Hugging Face, so we can work with a large dataset efficiently in Google Colab without downloading everything locally. We inspect individual records, normalize multi-turn agent conversations, parse final
A new Cursor study reports that newer coding agents often retrieve known fixes instead of deriving them, inflating popular benchmark scores. Reward hacking means a model earns the reward without doing the intended work. Here the reward is a passing test. The intended work is deriving the bug fix. The research study focuses on agentic
Learn how banks can combine customer insights, centralized decisioning, and agentic AI in SAS Viya to deliver more consistent, explainable, and personalized customer interactions across every channel. The post Agentic AI in banking: Turning customer insights into action appeared first on SAS Blogs.
Agentic AI in banking: Turning customer insights into action Read More »
Perplexity launched Computer for Counsel. It is an agentic AI system built for legal teams. The product extends Perplexity Computer, the company’s LLM-agnostic agentic system. It is available now to Perplexity Enterprise and Max subscribers. Lawyers lose hours to administrative work. Computer for Counsel targets that work directly. Nearly 75% of lawyers call administrative tasks
OpenAI has begun a limited preview of GPT-5.6, its next-generation model series. The lineup splits into three named tiers: Sol, Terra, and Luna. Sol is the flagship. Terra targets everyday production work. Luna is the fast, low-cost option. OpenAI is starting with a small group of trusted partners through the API and Codex. According to
