Anthropic Just Broke A Core Assumption About AI Models

by Rohit Kumar Thakur — A model was trained to love owls.

Medium·19m ago

Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities

Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities The post Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE...

Marktechpost·5h ago

Anthropic releases a new Opus model amid Mythos Preview buzz

Anthropic has released its most powerful "generally available" model to date: Claude Opus 4.7. The company called it a step up from Opus 4.6 for advanced software engineering tasks, particularly in...

The Verge AI·19h ago

UCSD and Together AI Research Introduces Parcae: A Stable Architecture for Looped Language Models That Achieves the Quality of a Transformer Twice the Size

The dominant recipe for building better language models has not changed much since the Chinchilla era: spend more FLOPs, add more parameters, train on more tokens. But as inference deployments...

Marktechpost·1d ago

Claude Opus 4.7 Is Here: Anthropic’s Most Capable Model Yet

by Emilyharbord — Everything you need to know about Anthropic’s latest release, Opus 4.7, new features, benchmark results, and what’s actually changed.

Medium·21m ago

Inside LLM Inference: When the KV Cache No Longer Fits

by Aanchal Karamchandani — Why managing the KV cache is a systems problem, not a model problemIn the previous article, we reduced the KV cache. Techniques like MQA and GQA reduce how much we store per token.But reduction only...

Towards AI·6h ago

openclaw 2026.4.15

Changes Anthropic/models: default Anthropic selections, opus aliases, Claude CLI defaults, and bundled image understanding to Claude Opus 4.7. Google/TTS: add Gemini text-to-speech support to the...

OpenClaw Releases·13h ago

Your Chunks Failed Your RAG in Production

by Priyansh Bhardwaj — The upstream decision no model, or LLM can fix once you get it wrong The post Your Chunks Failed Your RAG in Production appeared first on Towards Data Science.

Towards Data Science·19h ago

Treating enterprise AI as an operating layer

There’s a fault line running through enterprise AI, and it’s not the one getting the most attention. The public conversation still tracks foundation models and benchmarks—GPT versus Gemini, reasoning...

MIT Tech Review·22h ago

How to Build a Universal Long-Term Memory Layer for AI Agents Using Mem0 and OpenAI

In this tutorial, we build a universal long-term memory layer for AI agents using Mem0, OpenAI models, and ChromaDB. We design a system that can extract structured memories from natural...

Marktechpost·1d ago

Monte Carlo Simulations in R for Statistical Modeling

by Saroj Parajuli — Monte Carlo simulation is one of the most powerful and flexible tools in statistics. Whether you’re estimating probabilities, modeling…

Medium·22m ago

Physical Intelligence, a hot robotics startup, says its new robot brain can figure out tasks it was never taught

The new model, called π0.7, represents what the company describes as an early but meaningful step toward the long-sought goal of a general-purpose robot brain.

TechCrunch AI·15h ago

InsightFinder raises $15M to help companies figure out where AI agents go wrong

According to CEO Helen Gu, the biggest problem facing the industry today is not just monitoring and diagnosing where AI models go wrong — it's also diagnosing how the entire tech stack operates now...

TechCrunch AI·19h ago

Introduction to Deep Evidential Regression for Uncertainty Quantification

by Benjamin Li — Machine learning models can be confident even when they shouldn't be. This article introduces Deep Evidential Regression (DER), a method that lets neural networks rapidly express what they don't...

Towards Data Science·23h ago

Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers

Hugging Face·1d ago