Darío

pensamientos al aire

[Darío @DarioDefosse]

@thsottiaux Mojibake when it writes text in other languages

[Darío @DarioDefosse]

@sama stop injecting mojibake characters when coding simple stuff in another language?

[Darío @DarioDefosse]

el tener roomies me hace agradecer cada día más la educación que se me dio en casa

[Darío @DarioDefosse]

no hay nada como estar en casa

[Darío @DarioDefosse]

a no ser que te muerdan la mano

[Darío @DarioDefosse]

a veces es mejor darle al perro uno o dos huesos para roer

[Darío @DarioDefosse]

Spotify debería implementar una función con IA para organizar playlists, ya se tardaron

[Darío @DarioDefosse]

melancolía nostálgica

[Darío @DarioDefosse]

@JimenaIbarrac contratarme

[Darío @DarioDefosse]

jamás había detestado tanto a un grupo étnico (asiáticos) hasta hoy

[Darío @DarioDefosse]

nice for what?

[Darío @DarioDefosse]

que curioso es vivir en tiempos de guerra y propaganda

[Darío @DarioDefosse]

nadie te advierte de la soledad de la adultez

[Darío @DarioDefosse]

soñé que me compraba otra suscripción de AI

[CG @cgtwts]

Let me explain what just happened, because I don’t think people realize how INSANE this is.

> Cortical Labs put 200,000 real human brain cells onto a silicon chip and trained them to play Doom in just one week.

> Each CL1 system costs $35,000.

> A rack of 30 units consumes only 850–1,000 watts combined.

> The human brain operates on 20 watts.

> Large AI training clusters burn through megawatts.

>Backed by In-Q-Tel.
115 units began shipping in 2025.

> Cortical Labs is selling “Wetware as a Service” through Cortical Cloud, letting developers deploy code remotely to living human neurons with no lab required,

> priced like a software subscription but powered by real brain cells grown from adult skin and blood samples.

> it isn’t about gaming, it’s about biological computing that could eventually outperform traditional silicon in energy efficiency and adaptability.

This is getting really scary and we’re still at the very beginning.

[Tuki @TukiFromKL]

🚨Nobody wants to hear this but it needs to be said.

> Scientists just copied a fruit fly's brain into a computer. Neuron by neuron. No training data. No machine learning.

> It woke up and started walking. No one taught it to walk. No one trained it. No gradient descent. It just... knew what to do.

A fruit fly brain has 140,000 neurons.
A human brain is around 86,000,000,000.
And we've gotten really good at scaling.

Meaning with this proof, the first digital human won't be built by OpenAI. It'll be copied from someone who's already alive.

Your consciousness is software. And someone just proved it can be copy-pasted.

Start your day with that.

[Darío @DarioDefosse]

@mariapamuan estoy súper orgulloso de ti

[Darío @DarioDefosse]

if we got nothing, we got us

[Andrej Karpathy @karpathy]

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow.

Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes.

As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now.

It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.

[Mindset for Money @Mindset4Money_X]

Claude to literally every business model on the planet