As a customer of Konfig, I am super bummed about this. I think we may even have been their first customer (referenced in the init commit). Dylan and Anh-Tuan solved a number of real problems for us, and they did it spectacularly. They essentially provided a one-stop-shop for generated SDKs and beautiful hosted docs/tutorials that would call our API and immediately allow users to start playing with real data. Prior to Konfig, we were hand-writing a hodgepodge of SDKs to wrap our API and using ReadMe to host the docs (which never quite worked interactively with our API due to request signing that we require on our API).
Tons of respect for these guys and I wish they'd found a way to make it work.
Also, for anyone finding themselves in a similar situation as Konfig (a product that (some? most? all?) customers love, but revenue not scaling as needed), please consider charging more. We probably would have paid 2-3x what Konfig was charging us and more as we grow, but they never asked and never built in any usage-based cost scaling (like $X/month/SDK, $Y/month/demo, etc).
I was looking forward to that as well, but Siri refuses to read ChatGPT's responses to me...which makes it substantially less useful. It's just as frustrating as being told "sorry, you'll have to unlock your phone if you want me to play something on youtube music". Let's hope they iterate, I guess?
One of the biggest contributors to pollinator decline is loss of habitat for native bees. Most bees are actually solitary (don’t live in hives) and live in little crannies or holes in the ground.
One of the coolest things I’ve come across recently is the idea of “bee homes” that you can put in your garden to provide habitat for bees. I’ve bought a couple beautiful wooden units from Scopa and we just got our first bee resident this week!
Thank you, that was a fascinating talk and I learned quite a bit.
However, it did not provide a convincing argument as to why LLMs cannot be a part of a "doomer" AI. In fact, I got the opposite vibe from Andrej explaining expected future developments. The whole section on System 2 thinking sounds like a layer constructed around dumb LLMs that would result in vastly improved and more generalizable intelligence.
I agree that just scaling the size of LLMs is probably not sufficient for AGI...but that just seems like one relatively minor piece of all the possible ways it might be achieved.
As much as I can appreciate Doctorow’s exasperation, I find his dismissal of the doomer vs accelerationist debate rather pithy. I would love to be convinced that “dumb” LLMs can never gain sentience (or be finagled into sentience with a wrapper).
What is the actual argument for why that’s true?
(I realize you could turn the question around and ask why I think it might be possible in the first place, but I feel like my expectations have been blown out of the water so regularly and so increasingly frequently that I can’t default to being a naysayer anymore)
Alpaca is great! As far as brokerage APIs go, theirs is top notch and a breeze to code for. The founders are also really responsive and helpful.
I know this because I wrote an app that connects to Alpaca accounts (as well as other brokerages) to help people build their own custom index funds [0]. It only took a few weeks to build our Alpaca integration, whereas other brokerages often take months/years just to get access to their APIs.
Here are some "sleepers" that people have built over the years [1,2,3]
[0] https://thelaserhive.com/product-category/powermac-g4-conver...
[1] https://old.reddit.com/r/sleeperbattlestations/comments/1gva...
[2] https://old.reddit.com/r/sleeperbattlestations/comments/1871...
[3] https://old.reddit.com/r/sleeperbattlestations/comments/t7tz...