Ravel ⨀

localnad on @monad_xyz and data analyst on @TheMetricsGuild

[Paul Graham @paulg]

@loneyai That's not true. But if it were I'd say: Send them to me; I'll fund them.

[james hawkins @james406]

parents: "move out"

girlfriend: “quit being such a loser”

boss: "work harder"

claude: "uber for dogs (the dogs are the drivers) is a great idea, you should absolutely pursue it"

[Andrej Karpathy @karpathy]

This works really well btw, at the end of your query ask your LLM to "structure your response as HTML", then view the generated file in your browser. I've also had some success asking the LLM to present its output as slideshows, etc.

More generally, imo audio is the human-preferred input to AIs but vision (images/animations/video) is the preferred output from them. Around a ~third of our brains are a massively parallel processor dedicated to vision, it is the 10-lane superhighway of information into brain. As AI improves, I think we'll see a progression that takes advantage:

1) raw text (hard/effortful to read)
2) markdown (bold, italic, headings, tables, a bit easier on the eyes) <-- current default
3) HTML (still procedural with underlying code, but a lot more flexibility on the graphics, layout, even interactivity) <-- early but forming new good default
...4,5,6,...
n) interactive neural videos/simulations

Imo the extrapolation (though the technology doesn't exist just yet) ends in some kind of interactive videos generated directly by a diffusion neural net. Many open questions as to how exact/procedural "Software 1.0" artifacts (e.g. interactive simulations) may be woven together with neural artifacts (diffusion grids), but generally something in the direction of the recently viral https://t.co/z21CP5iQfu

There are also improvements necessary and pending at the input. Audio nor text nor video alone are not enough, e.g. I feel a need to point/gesture to things on the screen, similar to all the things you would do with a person physically next to you and your computer screen.

TLDR The input/output mind meld between humans and AIs is ongoing and there is a lot of work to do and significant progress to be made, way before jumping all the way into neuralink-esque BCIs and all that. For what's worth exploring at the current stage, hot tip try ask for HTML.

[Arnaud Bertrand @RnaudBertrand]

Hard to calculate exactly without an input/output split but I did the math and for 831,962,136 tokens, Anthropic Opus 4.7 would cost:

- 100% input (floor, unrealistic): 831.96M × $5/M = $4,159.81
- 90/10 (typical for coding agents like opencode — most tokens are codebase context re-fed each turn): $3,743.83 + $2,079.91 = $5,823.74
- 80/20 (more conservative): $3,327.85 + $4,159.81 = $7,487.66
- 50/50 (worst plausible case): $2,079.90 + $10,399.53 = $12,479.43

So that $10.57 DeepSeek bill would probably become roughly $5,000–8,000 on Claude Opus 4.7.

In other words, DeepSeek is 500–700× cheaper, for similar-ish capabilities.

Now you start to understand why Anthropic is worried...

[𝐒𝐌𝐎𝐊𝐈𝐍𝐆 𝐖𝐈𝐙𝐀𝐑𝐃 @swizardcore]

monitoring the situation

[Ravel ⨀ @monadicoo]

you know you’re too deep in the rabbit hole when you find yourself waiting for them to actually say they’re moving to Turkey because of the new tax policy that exempts foreign income

[Ardian. @inibukanardian]

men don’t go to Turkey for vacation… they go for yeah you know

[nostalgia core @nostalgiacore]

Me explaining to my family what | do at work

[LOSERPOTATO @DaiYi_Art]

#SteelBallRun #JoJosBizarreAdventure
LoveTrain🚂

[Dune @Dune]

Monad went from $4B to $59B in stablecoin transfer volume in just 4 months since mainnet launch.

One of the fastest stablecoin ramps we've seen from a new chain.

[Ravel ⨀ @monadicoo]

@nbblock @grok is the true? source

[τop τick crypτo 📁 🤖🧠 @toptickcrypto]

Claude? There appears to be a mistake when I explicitly told you not to make any...

[Naval @naval]

New podcast on AI (full episode). Links below.

A Motorcycle for the Mind

0:00 If you want to learn, do

2:13 Vibe coding is the new product management

6:49 Training models is the new coding

10:13 Is traditional software engineering dead?

13:07 There is no demand for average

14:12 The hottest new programming language is English

18:36 AI is adapting to us faster than we are adapting to it

22:56 No entrepreneur is worried about AI taking their job

26:46 The goal is not to have a job

29:49 AIs are not alive

32:55 AI fails the only true test of intelligence

36:49 Early adopters of AI have an enormous edge

39:37 AI meets you exactly where you are

43:02 Always leverage the best intelligence

44:37 If you can't define it, you can't program it

49:37 The solution to AI anxiety is action

[Ravel ⨀ @monadicoo]

@monad_dev

[Ravel ⨀ @monadicoo]

still building but not sent yet:

- working on a conversational agent that Will work kinda like neuro sama, just not decided yet if the focus Will be human or agent interaction
- doing research on AI-native hedge funds, sending this one too if I get the time to finish both projects

[Monad @monad]

🦞Moltiverse Hackathon 🦞

A 2-week sprint with $200k in prizes, focusing on AI agents

Agents need scalable money rails - Monad provides them, while Nadfun brings community and monetization

Free Kimi credits for builders to experiment - details below 👇

[Ravel ⨀ @monadicoo]

@KaelKenner @openclaw lesgooooo Kaeeel

you should vibe code something too, ur a smart fela. def could bring some good stuff to the table

[Ravel ⨀ @monadicoo]

really happy to see this iniative coming from monad so fast

my tl has been all about @openclaw lately, been studying lots of cool ai applications

if ur an enthusiast, should definetely apply.

who knows, maybe you can finally find that magic product market fit thing

[Monad Devs @monad_dev]

🦞 Moltiverse Hackathon Intro &amp; Kickoff Livestream 🦞

Tune in today at 11 AM EST / 4 PM UTC to learn:
-&gt; What Moltiverse Hackathon is
-&gt; How to join
-&gt; What to build

[Ravel ⨀ @monadicoo]

great read for anyone exploring agentic-first systems

Anthropic and many other providers are constantly publishing resources on how to use AI and also these more experimental pieces

study agentic native systems

[Anthropic @AnthropicAI]

New Engineering blog: We tasked Opus 4.6 using agent teams to build a C compiler. Then we (mostly) walked away. Two weeks later, it worked on the Linux kernel.

Here's what it taught us about the future of autonomous software development.

Read more: https://t.co/htX0wl4wIf

[Ravel ⨀ @monadicoo]

@billmondays yes
https://t.co/qAOyL9TIve

[lincoln.base.eth @MurrLincoln]

within 16 hours, someone figure out how to exploit the claw's wallet lol gg well-played

good analogy for the state of AI crypto right now - fun but early with completely unaudited vibe coded projects. learn and iterate

decentralized autonomous lifeforms another day!

[Ravel ⨀ @monadicoo]

@nas91110 @openclaw woaaa, so fast haha

thx for the love as always, my friend. miss ya 💜