When Your LLM Reaches End-of-Life: A Framework for Confident Model Migration in Production Systems
arXiv:2604.27082v1 Announce Type: new
Abstract: We present a framework for migrating production Large Language Model (LLM) based systems when the underlying model reaches end-of-life or requires replacement. The key contribution is a Bayesian statistical approach that calibrates automated evaluatio...
End-to-end autonomous scientific discovery on a real optical platform
arXiv:2604.27092v1 Announce Type: new
Abstract: Scientific research has long been human-led, driving new knowledge and transformative technologies through the continual revision of questions, methods and claims as evidence accumulates. Although large language model (LLM)-based agents are beginning ...
Think it, Run it: Autonomous ML pipeline generation via self-healing multi-agent AI
arXiv:2604.27096v1 Announce Type: new
Abstract: The purpose of our paper is to develop a unified multi-agent architecture that automates end-to-end machine learning (ML) pipeline generation from datasets and natural-language (NL) goals, improving efficiency, robustness and explainability. A five-ag...
Microsoft Research’s World-R1 Uses Flow-GRPO and 3D-Aware Rewards to Inject Geometric Consistency Into Wan 2.1 Without Architectural Changes
Microsoft Research's World-R1 Uses Reinforcement Learning to Force 3D Consistency Into Text-to-Video Models
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Reinforced Agent: Inference-Time Feedback for Tool-Calling Agents
This paper was accepted at the Fifth Workshop on Natural Language Generation, Evaluation, and Metrics at ACL 2026.
Tool-calling agents are evaluated on tool selection, parameter accuracy, and scope recognition, yet LLM trajectory assessments remain inherently post-hoc. Disconnected from the active e...
Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale
Safe agents don’t guarantee a safe ecosystem of interconnected agents. Microsoft Research examines what breaks when AI agents interact and why network-level risks require new approaches.
The post Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale appeared fir...
Nemotron Labs: What OpenClaw Agents Mean for Every Organization
By early 2026, the open source project OpenClaw had become a phenomenon. In January, its GitHub star count crossed 100,000 as developer interest surged.
Grok Voice Think Fast 1.0: Build Voice AI Agents That Actually Think
Voice assistants that engage in back-and-forth communication are something you’ve likely experienced. But a voice assistant that provides rational, uninterrupted exchanges via spoken dialogue? That’s what xAI delivered with their Grok Voice Think Fast 1.0 in April 2026 and instantly, it became the t...
I Built Hayat AI to Bridge the First Critical Moments for Hajj and Umrah Pilgrims
For millions of Muslims, Makkah is not simply a destination. It is a place of awe, peace, and spiritual gravity that is difficult to fully…Continue reading on Medium »
If you’ve been following the reasoning model wave, you’ve seen GRPO mentioned in the same breath as DeepSeek-R1 and Qwen3. Both of those…Continue reading on Medium »
FDA approval, fundraising, and the reality of building in healthcare according to BioticsAI founder
BioticsAI CEO Robhy Bustami joined Isabelle Johannessen on Build Mode to discuss how the company has navigated a highly regulated space and kept the team motivated while cutting through all the red tape.
Google’s Gemini AI assistant is hitting the road in millions of vehicles
Google announced on Thursday that it will begin rolling out Gemini to cars with Google built-in, marking a significant upgrade from the current Google Assistant. The move signals Google’s push to bring more advanced, conversational AI into the driving experience. The announcement follows closely beh...
Cat Wu leads product for Claude Code and Cowork at Anthropic, so she’s well-versed in building reliable, interpretable, and steerable AI systems. And since 90% of Anthropic’s code is now written by Claude Code, she’s also deeply familiar with fitting them into routine day-to-day work. Last month, Ca...
This startup’s new mechanistic interpretability tool lets you debug LLMs
The San Francisco–based startup Goodfire just released a new tool, called Silico, that lets researchers and engineers peer inside an AI model and adjust its parameters—the settings that determine a model’s behavior—during training. This could give model makers more fine-grained control over how this...
5 Powerful Python Decorators to Build Clean AI Code
This article outlines five particularly useful Python decorators that, based on developers' experience, haven proven themselves effective to make AI code cleaner.
TurboQuant has recently been launched by Google as a novel algorithmic suite and library for applying advanced quantization and compression to large language models (LLMs) and vector search engines — an indispensable element of RAG systems.