筛选结果
6 篇排序
51:08ENThe Transformer Co-Author Who Says Scaling Hit a Wall主持 Jacob EffronCohere CEO Aidan Gomez tells Redpoint that a $100 million model is still an amnesiac genius, and that enterprise AI money is concentrating in support, research, and the back office.
1:09:09EN30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually Think主持 Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.
1:01:39ENGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?主持 Nathan LabenzTraining GPT-3 took about a trillion tokens; GPT-4 took about ten trillion. The next jump is a data question as much as a compute one.
1:21:50EN → 简体中文16K 的上下文窗口只能放下约 350 行,这就是表格需要智能体的原因主持 Nathan LabenzGretel AI 创始人 Alex Watson 向 Nathan Labenz 讲述:为什么大多数公司的数据仍然是一张电子表格,为什么 GPT-4 是生成这些数据的错误工具,以及差分隐私(differential privacy)如何让模型学会一种疾病,却不学会某个病人。
1:17:09ENGPT-4 as Teacher, GPT-3.5 as Student: A Nine-Tenths Cost Cut and an AI Bundle Nobody Will Start主持 Nathan LabenzNathan Labenz reports that chain-of-thought traces from GPT-4 train a cheaper, faster 3.5, then argues for flooring the app accelerator, tapping the brake on GPT-5, and bundling a hundred AI tools for a hundred dollars.
2:00:19EN1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2主持 Nathan LabenzTry this fill-in: Lily likes cats and dogs. She asked her mom for a dog. Mom said no, so she asked for a…









