For Robotaxis, Safety Must Be Built In, Not Bolted On
A car pulls up to the curb. The app says, “Your ride is here.” No one’s in the driver’s seat. For people who live in one of the dozens of cities now hosting robotaxi services, this is already a reality. The robotaxi industry has moved from prototype milestones to commercial operations, with an expan...
Google AI Releases DiffusionGemma, a 26B MoE Open Model Using Text Diffusion for Up to 4x Faster Generation
DiffusionGemma is Google DeepMind's experimental 26B open model using text diffusion for up to 4x faster generation on GPUs.
The post Google AI Releases DiffusionGemma, a 26B MoE Open Model Using Text Diffusion for Up to 4x Faster Generation appeared first on MarkTechPost.
NVIDIA Accelerates Google DeepMind’s DiffusionGemma for Local AI
Today, Google DeepMind released DiffusionGemma — an experimental open model built for exceptionally fast text generation. NVIDIA has optimized DiffusionGemma to run even faster across NVIDIA GeForce RTX GPUs, the NVIDIA RTX PRO platform and NVIDIA DGX Spark systems, from local PCs to the cloud. Rat...
Datadog veterans launch AI coding startup Niteshift on a bet against Big AI lock-in
AI coding agent startup Niteshift has raised a $7 million seed round from a who's who of angels. It's betting companies will want power over, not lock-in with model makers.
Jedify raises $24M to help companies arm AI agents with context on their business
The funding round was led by Norwest, with participation S Capital VC, Cerca Partners, and Oceans Ventures. Snowflake Ventures also participated as a strategic investor.
Decart’s new world model can simulate hours of photorealistic driving — with some caveats
Decart is launching Oasis 3, a real-time world model that generates photorealistic driving environments for autonomous vehicle testing, now available via API for developers to build on.
A quick guide to separating Physical AI from world models, embodied AI, physics AI, and digital twins
The post Physical AI: What It Is and What It Is Not appeared first on Towards Data Science.
The PM’s Playbook for Shipping AI Features That Actually Work in Production
The demo to Production Death Valley If you’ve worked on an AI feature, you know the feeling. You start building something that you are excited about, set launch timelines. The model spits out a perfect response, the prototype works magically, and everybody in the room is mentally calculating how big...
A classic brain test exposed AI's biggest weakness
Researchers gave top AI models a classic attention test used in psychology and found a major flaw. While the models could correctly name colors in short lists, their performance deteriorated sharply as the task became longer and more complex. Some leading systems fell from over 90% accuracy to nearl...
Top AI Coding Agents and Development Platforms in 2026: Atoms, Devin, Windsurf, Cursor, Warp, and More Compared
Software development has changed. Engineers no longer type most code by hand. They describe intent, and AI agents do the work. Modern tools plan tasks, edit across files, run tests, and open pull requests. Many now ship to production with limited supervision. No single tool fits every need. This gui...
Anthropic Releases Claude Fable 5 and Claude Mythos 5: Same Underlying Model, Different Safeguards, New Mythos-Class Tier
Claude Fable 5 ships generally available with classifiers; Mythos 5 stays limited, cyber safeguards lifted, through Project Glasswing.
The post Anthropic Releases Claude Fable 5 and Claude Mythos 5: Same Underlying Model, Different Safeguards, New Mythos-Class Tier appeared first on MarkTechPost.
Building a Code Dataset Pipeline from NVIDIA Nemotron-Pretraining-Code-v3 Metadata with Streaming, Pandas, and tiktoken
In this tutorial, we work with NVIDIA's Nemotron-Pretraining-Code-v3 dataset as a large-scale metadata index for code pretraining research. We stream the dataset instead of downloading it, inspect its schema, and build a manageable sample. We analyze languages, file extensions, repository frequency,...
Uncertainty-aware Multi-fidelity Closure via Conditional Normalizing Flows
arXiv:2606.09857v1 Announce Type: new
Abstract: Reduced-order models (ROMs) provide an efficient surrogate for complex multiscale systems, but their predictive accuracy is often compromised by truncation errors and the inadequate representation of interactions between resolved and unresolved scales...
Mitigating Manifold Departure: Uncertainty-Aware Subspace Rectification for Trustworthy MLLM Decoding
arXiv:2606.09859v1 Announce Type: new
Abstract: MLLMs frequently hallucinate objects inconsistent with visual inputs. This issue is typically attributed to the over-reliance on language priors, which can override the visual context. Recent training-free decoding strategies address this by penalizin...
SynIB: Informational Bottleneck for Maximizing Synergy in Multimodal Learning
arXiv:2606.09853v1 Announce Type: new
Abstract: A central objective in multimodal learning is to capture synergy: task-relevant information that arises only from the joint use of multiple modalities, and is not available from any single modality alone. While most approaches operate at the architect...