V

[Andrej Karpathy @karpathy]

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.

- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.

The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.

So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

[ChaosDump#55 @AkaThecipher]

Got some teammates 😼😼

[Vik @onlinedopamine]

how incredibly blessed we are to be living in this moment of opportunity

[V @findvofx]

Google just killed Jev.

Embedding Gemma 2 runs locally in your browser.

try here:
https://t.co/PkHzGGlk9G

[TypeSafe AI @typesafeai]

LLMs distilling Jev like

[Daniel San @dani_avila7]

also, save this image... It’s probably the simplest way to understand which Jev primitive fits your use case

Think about what you want to build, follow the diagram, and that’s it

[Chris Tate @ctatedev]

Limitation can be frustrating

But it can also force resourcefulness, imagination, to think differently

Abundance can make us lazy, make us too comfortable

But it can also give us room to thrive, to try "useless" things, experiment without fear

Learn to use and appreciate both

[TypeSafe AI @typesafeai]

Jev is now available to everyone. No waitlist.
Start using it here: https://t.co/5MfN4rIif5

[V @findvofx]

Jev Docs

https://t.co/ABkrg3rxbF

[V @findvofx]

Introducing Jev2API.

You write English. Jev2API writes & executes the cURL.

No LLMs. Grounded in your OpenAPI spec.

https://t.co/3d2f9jieW8

[V @findvofx]

@adrianabelarde @marclou im a new fan!

[V @findvofx]

@justinsunyt free credits!

[Google Maps Platform @GMapsPlatform]

🔑 No credit card required! With the new Maps Demo Key, you can get a working API key with just your Google account and start building in seconds ➡️ https://t.co/fLUvLk9Ose

We’ve removed the barrier to entry, giving developers direct access to build with select Google Maps Platform products — including Maps JS API, Places UI Kit, and Weather API. Whether you're testing new features or validating technical feasibility, prototype with confidence in a controlled sandbox with automatic usage guardrails.

➡️ Seamlessly works with AI agents to turn prompts into working geospatial prototypes.
➡️ Maps Demo Key is the easiest way to test AI-generated geospatial code without hitting setup blockers.
➡️ Easily transition to a full account to unlock our generous monthly free usage tier, additional APIs, and technical support — all while keeping your project moving.

Try it at the link above.

[V @findvofx]

My prediction:
The web will be agent-to-agent first then agent-to-human.

your website domain will point to your sandbox environment where the AI agents collaborate and can interface with the user and show UI widgets based on the context and intent of the user.

[V @findvofx]

Inspired from vercel's agent-browser 😊

[V @findvofx]

AI-slopped this new tool: android-agent-browser

An agent skill for controlling your phone. It dumps the mobile UI into a structured text tree that LLMs can easily parse, allowing them to interact with apps using simple commands and element references.

https://t.co/xkDAlCtxyV

[Zeno Rocha @zenorocha]

Today, we're launching the Resend CLI

• 53 commands
• Fully open source

$ curl -fsSL h‌ttps://resend.⁠⁠⁠⁠⁠com/install.⁠⁠⁠⁠⁠sh | bash

[V @findvofx]

another massive moat is hardware. we're gonna see a big comeback for retro tech, but infused with ai capabilities. imagine a physical cassette tape player that runs your custom ai music playlist.

[V @findvofx]

when everything is AI-powered, software won't be a moat anymore. the strongest defensibility for startups will actually be humans. human-in-the-loop, orchestrators, and the actual community you build around it.