This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Verace V1 replaces four standard transformer subsystems (attention, KV cache, mixture-of-experts, fixed-depth compute) with continuous, manifold-constrained alternatives: linear-cost attention via an orthogonal state update, O(1) memory with no KV cache, no cross-device expert dispatch, and real per-token adaptive depth. Every manifold and conservation claim is backed by an executable test, not just derived on paper. Reference implementation only, no pretrained weights yet.
👋 Hey Product Hunt,
I'm Krrish, founder of Verace. We're a small AI lab based in Jaipur,
India, and Verace V1 is the first thing we're putting out into the open. 🚀
Verace V1 replaces attention, the KV cache, mixture-of-experts, and
fixed-depth compute with continuous, manifold-constrained alternatives,
each one backed by an executable test, not just a derivation on paper. ✅
It's a reference implementation, not a trained model. No pretrained
weights, no benchmark claims. Just the architecture, the tests, and an
honest write-up of what worked and what didn't . 🔍
📄 Full paper: https://verace.in/research/verac...
💻 Code: https://github.com/Verace-Pvt-Lt...
Would love feedback 🙏, especially from anyone who's worked on
manifold-constrained optimization or linear attention variants.
No comment highlights available yet. Please check back later!
About Verace V1 on Product Hunt
“A next generation AI architecture, open source”
Verace V1 was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #76 on the daily leaderboard. Verace V1 replaces four standard transformer subsystems (attention, KV cache, mixture-of-experts, fixed-depth compute) with continuous, manifold-constrained alternatives: linear-cost attention via an orthogonal state update, O(1) memory with no KV cache, no cross-device expert dispatch, and real per-token adaptive depth. Every manifold and conservation claim is backed by an executable test, not just derived on paper. Reference implementation only, no pretrained weights yet.
Verace V1 was featured in Open Source (68.7k followers), Developer Tools (517.5k followers), Artificial Intelligence (475.9k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 233.9k products, making this a competitive space to launch in.
Who hunted Verace V1?
Verace V1 was hunted by Krrish Choudhary. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Verace V1 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Krrish Choudhary