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O(N) AI Architecture (12x faster than Transformers)

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HN · launched Nov 24, 2025 · 6 upvotes (top 73%) · 0 views

Niche: deep learning frameworks · 48 launches, 0 in the last 7 days · Explore this niche →

Category and tags

  • Horizontal
  • Model & infra
  • Developer
  • AI-native
  • Commercial product

Visit website ↗ Source listing ↗

Could you build this?

No Inventing and training a novel O(N) linear-complexity neural network architecture requires deep theoretical machine learning research and substantial compute resources.

What it would actually take: Developing a viable alternative to Transformers requires deep mathematical expertise in state-space models (SSMs), recurrent neural mechanisms, or linear attention formulations (like Mamba or RWKV). It requires custom low-level CUDA kernels (Triton/CUDA C++) to achieve real-world hardware efficiency and FLOP utilization. Validating the architecture also requires hundreds of thousands of dollars in GPU clusters to benchmark against standard LLM pretraining baselines.

Discussion

8 comments analyzed.

Competitors mentioned: GPT-2, Transformers

Concerns raised: AI hallucinations in code generation, Fake/made-up metrics in benchmarks, Repository credibility issues

Competitors

Other products that read as similar to this one : 4460 launches clear the similarity bar, closest 8 shown.

Attention rank: #3276 of 4461 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 26 days after the earliest competitor.

  • Bare-Metal AI · hn · 2026-09-14 · 5 upvotes · similarity 0.70
  • Hebbs · hn · 2026-03-09 · 6 upvotes · similarity 0.66
  • openloc · github · 2026-10-20 · 21 upvotes · similarity 0.65
  • AegisKernel · hn · 2026-11-06 · 14 upvotes · similarity 0.64
  • mLattice · github · 2026-10-12 · 61 upvotes · similarity 0.63
  • RLT · github · 2026-09-13 · 51 upvotes · similarity 0.63
  • recurrent-transformer · github · 2026-09-25 · 18 upvotes · similarity 0.62
  • kinetic · github · 2026-11-10 · 88 upvotes · similarity 0.61

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