An Interview With Daniel Gross and Nat Friedman about the Democratization of AI
Ben Thompsonstratechery.com
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An Interview With Daniel Gross and Nat Friedman about the Democratization of AI
Our training data is pretty much from the same place as everybody else’s — which is pretty much the internet. Pretty much every big AI model just pulls off all the data it can, all the text it can, all the images it can. Scientifically speaking, we’re at an early point in the space, where everyone grabs everything they can, they dump it in a huge f... See more
The Verge • “An engine for the imagination”: an interview with David Holz, CEO of AI image generator Midjourney
How did we get to the doorstep of the next leap in prosperity?
In three words: deep learning worked.
In 15 words: deep learning worked, got predictably better with scale, and we dedicated increasing resources to it.
That’s really it; humanity discovered an algorithm that could really, truly learn any distribution of data (or really, the underlying “ru... See more
In three words: deep learning worked.
In 15 words: deep learning worked, got predictably better with scale, and we dedicated increasing resources to it.
That’s really it; humanity discovered an algorithm that could really, truly learn any distribution of data (or really, the underlying “ru... See more
samaltman.com • The Intelligence Age
深夜Coding有感，前几年在腾讯、字节等大厂的时候，我三五天写的几个函数，现在用Claude可能十几分钟就写完了，质量还更好。
信息传递的过程是会失真的，100人的技术团队可能会因为沟通和交流问题降低很多效率，而小团队甚至是个人开发者，失真率很低，效率反而出奇的高，这种效率的提升甚至可能将原本需要三五个月的项目周期缩短到几天[捂脸]
有趣的是，其实AI加持下的前端工作反而比后端、数据分析还麻烦一点，用户交互、视觉设计、debug这方面都是LLM不擅长的
而曾经的researcher如果有一个idea，在初始阶段往往也是个人探索为主，验证可行性之后可能才会对外传播，因为哪怕是面对同门，也要防住不必要的麻烦发生... See more
OpenAI, the other leading provider of GFMs today, also worked closely with CIP to run a grant program on "democratic inputs to AI" that dramatically accelerated research in this area and on the basis of which they are now forming a "Collective Alignment Team" to incorporate these inputs into the steering of OpenAI's models.