It can now:
- browse the web (RIP Bing waitlist, cutoff)
- write and run Python (RIP replit?)
- access org info (RIP docsearch startups)
- add third party plugins from OpenTable, Wolfram, Instacart, Zapier, etc)
- developer SDK in preview
When I talked about the AI Red Wedding last year (
946 people tuned in to an emergency unscheduled ChatGPT space lol
people are so hyped about this, it is unreal.
thanks to special guests @OfficialLoganK, @Altimor@dabit3 and the couple dozen others who joined in to revel in the biggest app store launch of the decade
CHATGPT IS READING AND SUMMARIZING MY REACTIONS TO CHATGPT THAT I MADE 2 HOURS AGO
Wow. GitHub CEO @ashtom just announced GitHub Copilot X:
- Copilot Chat - "ChatGPT-like experience in your editor" powered by GPT-4
- Copilot for Pull Requests - AI-generated descriptions for pull requests on GitHub
- GitHub Copilot for Docs - chat for *any* company's repos and… twitter.com/i/web/status/1…
IMO this is an overreaction. There is no upper bound to human desires. As technology obsoletes old jobs, new jobs arise. My job didn't exist 10 years ago. This laptop I'm typing on wasn't conceivable 10 years ago.
Big Data may be dead, but looking at data is still stupendously underrated even in 2023.
Small collection of examples where looking at ✨analytics✨ changed the trajectory of a whole business:
First (and most famous, but gotta acknowledge the greats), @kevin pivoted his Foursquare mobile check-in competitor after hiring @mikeyk to look at analytics.
Mike saw that out of all the features they shipped, only one got off the charts usage.
ChatGPT’s current killer app isn’t search, therapy, doing math, controlling browsers, emulating a virtual machine, or any of that other cherrypicked examples that come with huge disclaimers.
It’s a lot more quotidian:
Reformatting information from any format X to any format Y.
“ChatGPT reformatting” requires minimal world knowledge, are instantly verifiable, and can reliably save minutes of work multiple times a day.
The reformat can include contextual inference, which saves even more time at the cost of a bit more risk:
Convinced that all devs should work on a database as part of training.
Ever joked about DataStructures & Algorithms only being useful at interviews?
Work on a DB
Ever wondered why {{ FAVE_APP }} is slow?
Probably a DB
Prefer compilers?
allow me to introduce query planners..
Perhaps my real hot take is that databases are the CS grads abstracting away all the Hard Problems so that us bootcamp grads can cosplay being "full stack" with literally 1 day of SQL experience before getting hired to make 6 figures making rectangles on server vs on client
I'm starting to suspect there's only two fundamental value props in verticalized tech: offering a better data schema for the problem, and building a better data store for the schema.