I find myself pushing the team to use LLMs often, but one area it fails is when trying to source diverse feedback when everyone works with ChatGPT on their feedback.
Enterprises are often dissapointing until you meet the org most responsible for company success.
Suggests a power law in terms of the importance of various competencies.
This is super cool. A customer used our Pet Beta Program to hack their own smart pet feeder w/ access control. (Our smart scale is under the automatic feeder).
@matthucius You already shared the way, I think. There is only the present. The future and past don't exist other than memory and projection. Trying to change the past or future are futile.
Focus exclusively on what's in your control, in the present.
@patrick_oshag FWIW, capturing data yourself from your product's usage is an interesting moat and example of @bgurley's idea of the product getting better with more users.
ChatGPT has a critical mass of user ratings on responses. @bottomless is literally generating proprietary training data
@patrick_oshag data is FINALLY the new oil
AI will be able to do roughly anything that is currently done at scale, with data capture (cheaper and faster) and roughly no more than this.
@patrick_oshag requirements: deep market, participants with different time horizons.
It would probably have to be something new, or newly legible.
Probably GPUs.
Maybe residuals on high quality training data. Some text corpuses should be more valuable than most recorded music, for example.
@kirbywinfield Yeah, that makes sense!
Even the mega fund filling out the CRM feels fine... the associates are usually really bright, ambitious people who are learning to "think like VCs". It's usually interesting to speak with them.