Here’s something I sometimes do to avoid boring content when using LLMs: I type out what it gives me and tweak it as I go instead of copy/pasting directly.
It helps me spot the bits that feel flat or don’t add much, so I can cut or rework them—while still getting the benefit of the LLM’s idea generation.
I think the impact of AI is not between good jobs va bad jobs but between good workers and bad workers. For a given field, AI is making good workers more efficient and eliminating those who are bad at their jobs (e.g. the underperforming accountant who is able to make a living doing the more mundane tasks whose job is threatened by spreadsheets and automation)
Why should people who don’t own cars pay for highways?
Why should cyclist have to pay for public transportation?
Also children now will be your future doctor, nurse, bus driver, scientist, plumber, etc. so probably worthwhile making an investment in public goods that support their development.
Great work! I work in financial services and built a similar tool for sentiment analysis and topic modelling on transcribed earnings calls. The idea was to identify topics at a speaker-level (analyst, management, etc.) and evaluate the sentiment around that topic. For example, perhaps "foreign exchange" was discussed negatively by a given company in an earnings call, which would alert the analyst to review that call in greater detail.
Are you guys thinking about incorporating something like this into your product?
Something I’ve always wondered about the programming / software development profession: do people buy insurance for their hands?
My sister is a denturists and she has insurance for her hands. Curious if this is something people in our profession have considered to protect from incidents like this.
It helps me spot the bits that feel flat or don’t add much, so I can cut or rework them—while still getting the benefit of the LLM’s idea generation.