5 Matching Annotations
  1. Last 7 days
    1. The Scientist AI is going to be trained using essentially the same machine learning techniques: stochastic gradient descent on large neural nets, transformers, whatever works best. It doesn't care about what is the architecture of the neural net. So all of the effort that is currently being done to improve, for example, memory and other properties and continual learning, can just be applied directly to the Scientist AI.

      Bengio解释Scientist AI将使用与现有模型相同的基础技术,这意味着实现成本不会显著增加,打破了安全与能力必须取舍的常见假设,为安全AI提供了实用路径。

  2. May 2026
    1. An engineer at Cloudflare used Claude with OpenCode to release vinext, a reimplementation of Next.js on Vite, for only ~$1,100 in API costs.

      这个案例展示了AI系统在软件开发中的成本效益,仅用1100美元API成本就实现了94%的Next.js API覆盖,这是一个相对较低的成本。这表明在某些特定任务上,AI系统已经能够以相对较低的成本实现有意义的成果。

  3. Mar 2024
    1. It is there-fore to be expected that the initial cost of the card system is nota fair criterion of its cost when in working order.

      Setting up and learning a note taking or card index system has a reasonably large up-front cost, but learning it well and being able to rely on it over long periods of time will eventually reap larger and cheaper long-term outcomes and benefits.

      Unless changing systems creates dramatically larger improvements, the cost of change will surely swamp the benefits making the switch useless. This advice given by Kaiser is still as true today as it was in 1908, we tend not to think about the efficiency as much now as he may have then however and fall trap to shiny object syndrome.

  4. Apr 2021
  5. Aug 2020