AI and efficiency
6a
- Publicado
- Recolectado
We’re releasing an analysis showing that since 2012 the amount of compute needed to train a neural net to the same performance on ImageNet classification has been decreasing by a factor of 2 every 16 months. Compared to 2012, it now takes 44 times less compute to train a neural network to the level of AlexNet (by contrast, Moore’s Law…
overfeed.news indexa y enlaza. Publicamos un extracto breve; el artículo completo sigue en OpenAI News.
Más de OpenAI News
Inicia sesión para seguir esta fuente
How Amplitude ships product improvements in 1–2 days with OpenAI
Built primarily on OpenAI models, Amplitude’s proactive product agent, Wave, identifies what to build, helps teams ship changes with coding agents, and measures the impact.
Gondola doubles revenue as its team builds more with Codex
Gondola helps creatives get credit and get hired, with Codex raising its lead engineer’s output by 50% and ChatGPT simplifying daily work.
Holiday Extras is rethinking what it can build with Codex
With Codex, Holiday Extras is turning customer expertise into better apps, higher booking conversion and new possibilities for growth.
Supporting research on AI and children’s safety
OpenAI commits $2 million to research on AI and children’s safety. The work supports shared tools to measure risks and opportunities for young people.