<a href="https:&#x2F;&#x2F;vercel.com&#x2F;kb&#x2F;bulletin&#x2F;vercel-april-2026-security-incident" rel="nofollow">https:&#x2F;&#x2F;vercel.com&#x2F;kb&#x2F;bulletin&#x2F;vercel-april-2026-security-in...</a>

Vercel April 2026 security incident

Notion leaks email addresses of all editors of any public page

Vercel says internal systems hit in breach

GitHub's Fake Star Economy

Stop trying to engineer your way out of listening to people

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Tesla concealed fatal accidents to continue testing autonomous driving

The creative software industry has declared war on Adobe

Swiss authorities want to reduce dependency on Microsoft

Related ongoing thread: Swiss authorities want to reduce dependency on Microsoft - <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=47827383">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=47827383</a>

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I ported Microsoft&#x27;s TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac.I replaced the CUDA-specific ops with pure-PyTorch alternatives: a gather-scatter sparse 3D convolution, SDPA attention for sparse transformers, and a Python-based mesh extraction replacing CUDA hashmap operations. Total changes are a few hundred lines across 9 files.Generates ~400K vertex meshes from single photos in about 3.5 minutes on M4 Pro (24GB). Not as fast as H100 (where it takes seconds), but it works offline with no cloud dependency.<a href="https:&#x2F;&#x2F;github.com&#x2F;shivampkumar&#x2F;trellis-mac" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;shivampkumar&#x2F;trellis-mac</a>

Show HN: Run TRELLIS.2 Image-to-3D generation natively on Apple Silicon

Claude Token Counter, now with model comparisons