Digital sozialisiert, Denker, Macher und Angel Investor.
Large language models excel at language tasks that benefit from statistical patterns. So from at the very beginning of GenAI, generating program code was an obvious application. As in many other fields, people stated that there was much more to programming than just writing code. Yes, and then came AI agents. The speed of development of algorithms to generate code and managing all documentation...
The same wisdom again, but this time illustrated by (and mitigated with) AI: Humans don’t scale. With Seed-Coder, the people from ByteDance just released a family of LLMs focused on the generation of code. Aside an excellent performance and an open-source approach, they highlight their curation process of data used for pretraining. In short, LLMs played a central role in filtering and curating...
Digital sozialisiert, Denker, Macher und Angel Investor.