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One thing I really like about language models is that they are stateless (they are functional programs of type text -> text). This allows us to share prompts (essentially currying the LM) and reproduce results.

Cool example of its limits

Wild numbers from the latest GitHub Copilot blog post 46% of all code written 🙃

Excited to see everyone at The Commons in SF tonight starting at 6 🤗 Based on the austin/seattle meetups we expected ~20, and rented a space to support 80 people. We currently have 450 people who have RSVPd 🤯 I’ll be at door to personally apologize to people we can’t let in

Go SF!

How much would it cost to train GPT2-1.5B from scratch today? Original was estimated at $43K but we have four years of hardware and algorithmic advances since then, right?

:)

Looking at our inquiry trends on platform engineering. Holy moly. What a rocket ship of a topic.

Mark O'Neill Yep! Platform teams are absolutely starting to trend. I see this in my work, though my view is limited compared to yours! Stream-aligned teams were arranged to facilitate fast production. But now there’s inefficiency in duplication. How do we resolve this? Platform teams!

“Movement is my habitat. My only rest is motion. … Let me go where I have not yet arrived.” — Luce Irigaray, Elemental Passions

GPT-4 is waaay better at programming than given credit for. HumanEval is a benchmark of python programming problems. With some prompt engineering, GPT-4 scores ~85%, destroying Codex's 29% from just 2 years ago And performing much better than OpenAI's publicized accuracy

Imagine if the improvement curve here resembles anything like the evolution from Apple II to modern PC I grew up in

Notable

now reading

People are too focused on code generation and completely ignoring that LLMs are useful for code analysis. I've been personally surprised how useful they were in identifying missing test cases, unreleased leaking resources, or even telling me what's wrong with my IAM policy.

“The most courageous decision that you can make each day is to be in a good mood.” — Voltaire

I've developed a lot of plugin systems, and the OpenAI ChatGPT plugin interface might be the damn craziest and most impressive approach I've ever seen in computing in my entire life.

For those who aren't aware: you write an OpenAPI manifest for your API, use human language descriptions for everything, and that's it. You let the model figure out how to auth, chain calls, process data in between, format it for viewing, etc. There's absolutely zero glue code.