> For venue recommendations [...] we do not rely purely on the language model. We embed both user requirements and venues into vector representations and retrieve candidates using similarity search. Hard constraints such as capacity and dates are applied first, and results are ranked before being presented.
Huh this surprised me as a forgone opportunity.
I heard second-hand about the process for organizing our last offsite. Searching for venues was not the time-consuming part.
The time-consuming part was actually engaging with the venues to confirm specific details not available online. Our teammate who did this engaged with _hundreds_ of venues. It was a lot of work on their part ... and probably not the most fun part of their job.
Hey we're also a Vertex tuning customer in a similar spot. We're seeing other capacity issues, although not a leap in latency. Can you DM me? I'd love to trade notes. https://x.com/hellofromjames
I love Cerebras. I also love that they've started to scale rate limits to useful levels (which is relatively new).
I still don't know how long they'll support our chosen model.
On Oct 22 I got an email saying that
```
- qwen-3-coder-480b will be available until Nov 5, 2025
- qwen-3-235b-a22b-thinking-2507 will be available until Nov 14, 2025
```
That's not a lot of notice!
I don't want to spend all my time benchmarking new models for features I already built. I don't want my users' experience to be disturbed every few months.
Google[1] also has a "long context" pricing structure. OpenAI may be considering offering similar since they do not offer their priority processing SLAs[2] for context >128K.
You and your friends should email me with your resume and anything you're proud to have built. I'll extend that to any MIT senior/recent grad who wants to discuss moving to SF and helping us apply LLMs to build product features that solve interesting customer problems.
I'm at [email protected]. Include "[responding to HN thread 43614795]" in the title. I'd love to chat.
I am grateful for GCP's quotas that help us prevent similar own-goals.
While this specific error is something we know to avoid, I'm sure quotas have helped us avoid the pain of other errors. So I'm somewhat sympathetic.
I think it's important to read the language of and judgements in the post in the context of someone who just got a large unexpected bill (expensive lesson).
(I suspect you're viewing the "flex" pricing).