- zuban
- ty (from ruff team)
- pyrefly
One year ago, we had none of them, only slow options.
This is essentially what GraphQL does instead of crafting each of these super tailored API endpoints for each of your screens, you use their query language to ask for the data you want, it queries the DB for you and get you the data back in a single network roundtrip from the user perspective.
(Not an expert, so I trust comments to correct what I got wrong)
None of these nutcases offer true help to society (note: neither do the extreme leftists, just so we're clear that I'm not team red or team blue), and it does no good that our corporations are actively picking a side.
This throughput assumes 100% utilizations. A bunch of things raise the cost at scale:
- There are no on-demand GPUs at this scale. You have to rent them for multi-year contracts. So you have to lock in some number of GPUs for your maximum throughput (or some sufficiently high percentile), not your average throughput. Your peak throughput at west coast business hours is probably 2-3x higher than the throughput at tail hours (east coast morning, west coast evenings)
- GPUs are often regionally locked due to data processing issues + latency issues. Thus, it's difficult to utilize these GPUs overnight because Asia doesn't want their data sent to the US and the US doesn't want their data sent to Asia.
These two factors mean that GPU utilization comes in at 10-20%. Now, if you're a massive company that spends a lot of money on training new models, you could conceivably slot in RL inference or model training to happen in these off-peak hours, maximizing utilization.
But for those companies purely specializing in inference, I would _not_ assume that these 90% margins are real. I would guess that even when it seems "10x cheaper", you're only seeing margins of 50%.
I've often been frustrated by my history not being easily shared between concurrent terminals, difficulties in searching, and lack of other metadata such as timestamp, duration and exit code.
Although I suspect this repo was vibe-coded so far, I think there's a promising problem to solve here.
Also the readme doesn't have the usual emojis for every bullet point.
As of now, I’m seeing no lock-in for any LLM. With tools like Aider, Cursor, etc., you can swim on a whim. And with Aider, I do.
That’s what I currently don’t get in terms of investment. Companies (in many instances, VCs) are spending billions of dollars and tomorrow someone else eats their lunch. They are going to need to determine that method of lock-in at some point, but I don’t see it happening with the way I use the tools.
To make an argument it was Kevin Hou, then we would need to see Antigravity their new IDE being key. I think the crown jewel are the Gemini models.