The most innovative data science companies of 2026

Why Unstructured, Feedzai, Synchron, and Chalk are among Fast Company’s Most Innovative Companies in data science for 2026.

Nvidia's Nemotron-Cascade 2 wins math and coding gold medals with 3B active parameters — and its post-training recipe is now open-source

Nvidia's Nemotron-Cascade 2 is a 30B MoE model that activates only 3B parameters at inference time, yet achieved gold ...
Machine Design

Physical AI Hype vs Reality: Kung Fu Robots are Cool...But Should You Hire One?

Martial arts robots may play well on stage, but can they get work done? A look at what it takes to deliver the reliability ...
The Financial Express

Hiring trends 2026: Check if your resume lists these 5 must-have AI skills today

As hiring trends evolve in 2026, professionals are urged to ensure their resumes include these five must-have AI skills to ...
XDA Developers on MSN

Qwen3.5-9B tops every AI benchmark right now, but that's not how you should pick a model

There's a lot more to a model than just benchmarks.
GitHub

Boosting Efficient Reinforcement Learning for Vision-and-Language Navigation With Open-Sourced LLM

This repository is the official implementation of Boosting Efficient Reinforcement Learning for Vision-and-Language Navigation With Open-Sourced LLM. We opt for a simple reward function for two main ...
InfoWorld

19 large language models redefining AI safety—and danger

Whether you are looking for an LLM with more safety guardrails or one completely without them, someone has probably built it.
IEEE

RLCoder: Reinforcement Learning for Repository-Level Code Completion

Abstract: Repository-level code completion aims to generate code for unfinished code snippets within the context of a specified repository. Existing approaches mainly rely on retrievalaugmented ...
IEEE

A Reinforcement Learning Environment for Automatic Code Optimization in the MLIR Compiler

Abstract: Code optimization is a crucial task that aims to enhance code performance. However, this process is often tedious and complex, highlighting the necessity for automatic code optimization ...
GitHub

Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learning

REC-R1 is a general framework that bridges generative large language models (LLMs) and recommendation systems via reinforcement learning. Check the paper here.