Applications
There's been a talk about how LLMs are only advancing in verifiable areas like math or coding, but that isn't what the data suggests. As mod…
There's been a talk about how LLMs are only advancing in verifiable areas like math or coding, but that isn't what the data suggests. As models have gotten better at that, they are also better at solv
There's been a talk about how LLMs are only advancing in verifiable areas like math or coding, but that isn't what the data suggests. As models have gotten better at that, they are also better at solving business cases in unbounded fields, generating ideas, medicine, law, etc. Cool paper looking at how AIs solve unbounded, complex business problems in many fields by testing how well they can crack the cases we use to teach MBAs in business school: 1) AI already does extremely well across diverse business topics 2) Models are improving rapidly with time
Related
- The most important weird thing about LLMs is that they are so general. A bigger LLM that is better at coding is also better at ideation & et…
- AI is jagged, but I think sometimes it is easy to overly focus on that. The generalness is a surprise too! LLMs may be optimized for verifia…
- While it is obviously true that not having verifiable domains makes training models in those spaces difficult... it is also true that models…
- There are some clear exceptions to the rule, but I feel like the labs got the message that they were scaring people and now tweet about happ…
- The unreasonable effectiveness of LLMs is what makes them so weird. The labs don’t need to decide what kind of AI to build, because better L…
Source: Ethan Mollick (X) | 2026-07-28