​Language models must be adapted to understand and follow user instructions. Reinforcement learning is widely used to facilitate this — typically using fixed criteria such as “helpfulness” and “harmfulness”. In our work, we instead propose using flexible, instruction-specific criteria as a means of broadening the… Read More »Checklists Are Better Than Reward Models For Aligning Language Models Apple Machine Learning Research

​We present StreamBridge, a simple yet effective framework that seamlessly transforms offline Video-LLMs into streaming-capable models. It addresses two fundamental challenges in adapting existing models into online scenarios: (1) limited capability for multi-turn real-time understanding, and (2) lack of proactive response mechanisms. Specifically, StreamBridge incorporates… Read More »StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant Apple Machine Learning Research

​[[{“value”:” Can safety keep up with real-time LLMs? Alibaba’s Qwen team thinks so, and it just shipped Qwen3Guard—a multilingual guardrail model family built to moderate prompts and streaming responses in-real-time. Qwen3Guard comes in two variants: Qwen3Guard-Gen (a generative classifier that reads full prompt/response context) and… Read More »Meet Qwen3Guard: The Qwen3-based Multilingual Safety Guardrail Models Built for Global, Real-Time AI Safety Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This blog was co-authored with Kuldeep Singh, Head of AI Platform at Innovaccer. The integration of agentic AI is ushering in a transformative era in health care, marking a significant departure from traditional AI systems. Agentic AI demonstrates autonomous decision-making capabilities and adaptive learning… Read More »Building health care agents using Amazon Bedrock AgentCore Kamal Manchanda Artificial Intelligence

​[[{“value”:” Site reliability engineers (SREs) face an increasingly complex challenge in modern distributed systems. During production incidents, they must rapidly correlate data from multiple sources—logs, metrics, Kubernetes events, and operational runbooks—to identify root causes and implement solutions. Traditional monitoring tools provide raw data but lack… Read More »Build multi-agent site reliability engineering assistants with Amazon Bedrock AgentCore Amit Arora Artificial Intelligence

​Choosing the right text representation is a critical first step in any natural language processing (NLP) project. Choosing the right text representation is a critical first step in any natural language processing (NLP) project.  Read More  

​[[{“value”:” Table of contents What problem is it actually solving? Does the sample-efficiency claim hold beyond toy problems? How does the evolutionary loop look in practice? What are the concrete results? How does this compare to AlphaEvolve and related systems? Summary FAQs — ShinkaEvolve Sakana… Read More »Sakana AI Released ShinkaEvolve: An Open-Source Framework that Evolves Programs for Scientific Discovery with Unprecedented Sample-Efficiency Asif Razzaq Artificial Intelligence Category – MarkTechPost

​Large foundation models are typically trained on data from multiple domains, with the data mixture—the proportion of each domain used—playing a critical role in model performance. The standard approach to selecting this mixture relies on trial and error, which becomes impractical for large-scale pretraining. We… Read More »Scaling Laws for Optimal Data Mixtures Apple Machine Learning Research