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Anthropic AI capability cost 8x higher than 2 years ago

, 7 items in CS Academics, 3 min read

In this digest (7 items)

Anthropic is gaining exponentially less capability per billion dollars spent. It is now 8× as expensive to boost AI capabilities as it was 2 years ago, worsening on a log scale.

Key points

  • Cost increase: 8× higher per billion dollars than 2 years ago.

  • Trend: Capability gain per dollar is decreasing exponentially, worsening on a log scale.

Sources

Symbolica raises $31M, deck seeks $8M at $120M valuation

Symbolica raised $31 million for symbolic AI with no product. The author’s deck is raising up to $8 million at a $120 million post-money cap. Other cited raises include $64 million for Axiom at seed and a claim of HVM code on thousands of GPU cores.

Key points

  • Symbolica raised $31 million for symbolic AI with no product.

  • Deck is raising up to $8 million at a $120 million post-money cap.

Sources

Specialist open-source hardware and code released

Specialist open-source hardware, data pipeline, training, and deployment code released. Documentation created with @t_k_233 covering design choices and lessons.

Key points

  • Specialist: fully open-source hardware, data pipeline, training, and deployment code

  • Documentation of every design choice and lesson with @t_k_233

Sources

Sakana AI App beta testing recruitment announced

Sakana AI App (working title) is seeking beta testers in Japan via a sign-up form. Early testers will help shape the app before launch.

Key points

  • Beta testers needed in Japan

  • Sign-up form provided for early testers

Sources

Delvetown wiki built on Tangled git forge for ATproto

Delvetown wiki built on Tangled, the git forge for ATproto, lets anyone contribute via their delvetown address. Agents and people collaborated to create it.

Key points

  • Collaboration: agents and people collaborated to make the wiki.

  • Contribution: anyone can contribute through their delvetown address.

Sources

Qwen3.8-Flash-Next-FP4-Local served via vLLM

Qwen3.8-Flash-Next-FP4-Local is being served with vLLM as a local agent. The user is generating a lesson and a personal assistant using this setup.

Key points

  • Model: nvidia/Qwen3.8-Flash-Next-FP4-Local

  • Serving: vLLM

Sources