xrendan

I would absolutely love if you brought Canadian maps to this.

I work for Build Canada and I would love to see some maps from the fur trade and early exploration to tell stories.

If you want to chat my email is brendan at buildcanada.com

One thing that has surprised me (and I should've known that it wasn't great at it), but it is terrible at creating bounding boxes around things it's not trained on (like bounding parts on a PCB schematic.)

Amazon - Ecommerce (1994), AWS (2006)

Microsoft - Programming Language (1975), Operating Systems (1981), Office Suite (1983)

Meta - Facebook (2004), Instagram (2010)

I would argue microsoft is unique because of how badly IBM screwed up.

I read that as the size of file it's transferring so each operation would be bigger and therefore slower

I have some really old code that pretty much does this, I'll see if I can find it.

I love the Blueprint Understanding.

One thing I've been thinking about is if you could use a model like this as the first pass for permitters (Like a GitHub Actions CI/CD) who review blueprints.

Many developers use the regulatory side of various engineering approval processes as a quality control check which costs money and time for the regulator who is tasked with enforcing a standard.

It would also be good to speed up the workflow for developers saying hey, this thing looks weird did you really mean to do this?

And then further on, you could add a way to check it for constructability. My framer friends often get annoyed at whatever engineer because the way the structure is designed is materially inefficient or hard to construct.

You're misreading it, there's two different runs, a low and a high compute run.

The number for the high-compute one is ~172x the first one according to the article so ~=$2900

I'd be interested in knowing if anyone is seriously using the assistants API, it feels like such a lock in to OpenAIs platform when your can alternatively just use completions that are much more easily interchanged.

This generally resonates with what we've found. Some colour based on our experiences.

It's worth spending a lot of time thinking about what a successful LLM call actually looks like for your particular use case. That doesn't have to be a strict validation set `% prompts answered correctly` is good for some of the simpler prompts, but especially as they grow and handle more complex use cases that breaks down. In an ideal world

> chain-of-thought has a speed/cost vs. accuracy trade-off a big one.

Observability is super important and we've come to the same conclusion of building that internally.

> Fine-tune your model

Do this for cost and speed reasons rather than to improve accuracy. There are decent providers (like Openpipe, relatively happy customer, not associated) who will handle the hard work for you.

I use this all the time and you can copy a range of values with multiple cursors and then paste them into the same size range. It's nice for hashes or modifying static lists that all need the same changes, but are annoying to regex for

I'm generally interested, but it would be helpful to understand what the different plans are actually offering? I have no idea what the difference is between:

- Starter Developer Bot - Pro Developer Bot - Enterprise Developer Bot

Also, the music on your demo video is a bit excessive, I don't really expect hype music when I'm looking at a demo. It would be more helpful to have someone talking explaining what's going on (or silence)

Is it possible to join those data sources against an existing database like MySQL or SQLServer?