Over 170 TanStack, Mistral AI, OpenSearch, UiPath, and other packages were affected in a new Mini Shai-Hulud supply chain ...
Malicious Lightning 2.6.2/2.6.3 released April 30 enable credential theft via hidden payload, leading to PyPI quarantine and ...
The new Hugging Face Reachy Mini App Store already hosts a library of over 200 community-built applications, and Reachy Mini ...
There's a certain comfort in selecting the most powerful model. When you're building an AI-powered product, it feels responsible (almost logical) to pick the most powerful model available. GPT-4o.
Keys built six and seven-figure businesses using AI systems he owns, not rents. A case study in measurable AI ROI for solo founders outside traditional enterprise models.
Hugging Face hosts 352,000 unsafe model issues. ClawHub's registry contains 341 malicious AI agent skills. The AI supply chain is now the most attractive target in software security.
Multi-die assemblies are facing full system-level challenges, but engineering teams need coordinated and repeatable ways to ...
Morning Overview on MSN
PyTorch Lightning versions 2.6.2 and 2.6.3 were compromised on April 30 — check your installs immediately
On April 30, two releases of one of the most popular machine learning libraries on the Python Package Index were caught ...
Cryptopolitan on MSN
Mistral AI and TanStack hit in supply chain attack with SLSA-attested malware
Attackers compromised the official Mistral AI Python package on PyPI along with hundreds of other widely-used developer packages, exposing GitHub tokens, cloud credentials, and password vaults across ...
By putting the weights of a highly capable, 33B-parameter agentic model in the hands of researchers and startups, Poolside is ...
Morning Overview on MSN
Hackers poisoned the PyTorch Lightning AI package and it started stealing credentials the moment you imported it
A single line of Python code was all it took. Developers who ran import lightning after installing versions 2.6.2 or 2.6.3 of ...
As agentic AI moves from pilots to production, enterprises are discovering that the biggest gaps aren’t in the capabilities of the AI itself, but the infrastructure they have in place to support it.
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