CopilotKit Releases CLiF: A Continual Learning Platform That Turns Agent Traces and User Actions into Skills, Evals, and Fine-Tuning Data
Introduction Teams shipping AI agents at scale keep running into the same pattern. Even agents built on top-tier models like Fable and Astra struggle to carry out complex, end-to-end tasks inside a specific product consistently enough to deploy. So teams grind out evals for the workflows that matter...
openKylin Outlines Its Vision for Reimagining Linux in the AI Era at Open Source Summit Europe 2026
At Open Source Summit Europe 2026, openKylin outlined its vision for transitioning from resource management to intent management in the AI era. The community introduced KART, a unified AI runtime, alongside core desktop features in openKylin 3.0 like the AI Assistant, Global Intelligent Search, and ...
How Many Guesses Does It Take to Crack an AI's "Random" Number?
I read the exact answer distribution from the logits of open models, base and instruction-tuned, and turned it into bits and guesses-to-crack.
The post How Many Guesses Does It Take to Crack an AI's "Random" Number? appeared first on Towards Data Science.
7 Open-Source AI Tools That Can Replace Paid Subscriptions
Find open-source alternatives to OpenAI API, Midjourney, Claude Code, Notion, Wispr Flow, Grammarly, and NotebookLM that you can run locally or self-host for more privacy, control, and lower cost.
Amazon’s Bee launches two new personal AI devices, starting at $75
Amazon-owned Bee has launched its first new AI devices since its acquisition, including an updated wearable and a credit-card-sized recorder that attaches to smartphones. The devices can summarize conversations, create to-do lists, and integrate with Alexa and Amazon shopping, with prices starting a...
I Tested Four Ways to Give an AI Assistant a Memory. The Obvious One Was the Worst Value.
Pasting in the whole chat history cost 20 to 31 times more than looking up notes, and it did no better on the tasks.
The post I Tested Four Ways to Give an AI Assistant a Memory. The Obvious One Was the Worst Value. appeared first on Towards Data Science.
Choosing a Chunking Strategy for Your LLM Apps: A Decision-Tree Approach
In this article, you will learn how to choose the right chunking strategy for a retrieval-augmented generation system by working through a structured decision tree...
The following article originally appeared on Addy Osmani’s Elevate blog and is being republished here with the author’s permission. For much of human history, we’ve evaluated code quality via code review: Someone reads what you wrote and makes sure it’s clean, thoughtful, fast, understandable, and t...
NVIDIA Expands Advanced Technology Access for Europe’s Scientific Community Through Open Learning Resources, Collaborations and Compute
Much of today’s scientific progress begins with computation. But turning accelerated computing’s potential into scientific progress — modeling climate systems, designing molecules, simulating materials and more — depends on more than breakthrough technology. Especially for smaller labs, early-caree...
TypeSafe AI Releases Jev 1.14 With Images, Box Type and 262k Context
TypeSafe AI released Jev 1.14 under the jev-preview alias. The System One model adds experimental image input, a Box bounding-box type and an opt-in 262k-token context, at $0.042 per million input tokens.
The post TypeSafe AI Releases Jev 1.14 With Images, Box Type and 262k Context appeared first on...
Meet Grok Voice 3.0: SpaceXAI Voice Agent Model Ranks #1 on Artificial Analysis
SpaceXAI just released Grok Voice 3.0. Grok Voice 3.0 is a SpaceXAI speech-to-speech model that listens, reasons, calls tools and speaks. It now ranks first on the Artificial Analysis Speech-to-Speech Index with a score of 86.9. For developers, the endpoint, events and $0.08 per minute price are unc...
The Nordics and NVIDIA Show What’s Possible When a Region Commits to Advanced Computing
The Nordic countries have become the European leader in unicorn startup density, producing the most emerging companies valued at $1 billion or more per capita on the continent. Now, a new chapter for the region is unfolding as countries race to build one of Europe’s most consequential technology eco...
Lotus: Learning to Understand Time-series by Learning to Forecast
arXiv:2610.18877v1 Announce Type: new
Abstract: Time-series language models typically align numerical signals with language using labels, captions, or question-answer pairs. Although such supervision encourages linguistic representations, it does not explicitly require them to preserve information ...
Inverse Reasoning Models for Efficient Post-Training and Verification from Answer-Only Data
arXiv:2610.18878v1 Announce Type: new
Abstract: Post-training reasoning LLMs often requires making a tradeoff between costly supervision and compute inefficiency: supervised finetuning typically requires reasoning traces, which is data inefficient since in many applications one only has prompt-answ...
Do Vision CIL Methods Transfer to Protein? A Diagnostic Benchmark of Frozen Protein Encoders
arXiv:2610.18879v1 Announce Type: new
Abstract: Protein function annotation operates over an expanding label space, making class-incremental learning (CIL) a natural framework for incorporating newly discovered functions without full retraining. Yet existing CIL methods have been developed largely ...
Do Perturbation Predictors Learn Gene Interactions? Diagnosing Extrapolation in Agentic Screening
arXiv:2610.18880v1 Announce Type: new
Abstract: High-throughput perturbation screens increasingly use machine-learning models to predict the effects of gene combinations that were never measured. A difficult case arises when both genes in a test pair were seen individually during training, but thei...
The Agentic Scientist: Orchestrating Coding Agents for Automated Scientific (Co-)Discovery
arXiv:2610.18933v1 Announce Type: new
Abstract: Modern coding agents are fundamentally reshaping the role of human input for computational research: they write code, launch in silico experiments, analyze their results, and autonomously operate with ever-increasing time horizons. Despite these devel...
Discovering Undisclosed Concepts in LoRA Adapters for Diffusion-Based AIGC Models
arXiv:2610.18990v1 Announce Type: new
Abstract: Low-Rank Adaptation (LoRA) has made diffusion model personalization affordable and widely shareable, but it also creates moderation risks when harmful or problematic content is not faithfully disclosed. Hence, it is desired to develop a mechanism that...
Gudea leverages AI to help organizations prevent social media crises before they erupt
Every day, conversations unfold across social media and websites around the world. A seemingly insignificant post—whether it involves AI-generated misinformation, hate speech, or a damaging rumor—can quickly snowball into a much larger public controversy. Gudea, a company that tracks how stories and...
Multimodal agents commonly generate freeform reasoning before each action. For small models, limited model capacity can result in lengthy reasoning that provides little useful guidance for action generation while incurring substantial inference cost. To address this challenge, we introduce Selection...