TechRT by Nex

Cualquier tecnología suficientemente avanzada es equivalente a la magia. Arthur C. Clarke. #Technology #AI #CyberSecurity #CloudComputing #Tech #TechNews

[Elon Musk @elonmusk]

SpaceX is actively hiring world-class engineers/physicists for SpaceXAI, even if you have zero prior experience in AI. Smart humans figure it out fast.

Please send an email with ~3 bullet points demonstrating evidence of exceptional ability to [email protected].

[Reads with Ravi @readswithravi]

“If you want to do extraordinary things, it shouldn't be easy.”

— Nvidia CEO, Jensen Huang

[All day Astronomy @forallcurious]

🚨: A photographer captured the Sun for three years straight from the exact same spot at the same time, then combined every position into one incredible image

[Álvaro J @jota_snchez]

Robert Sapolsky es un neurocientífico de Stanford que demostró que el estrés crónico es el asesino silencioso que los médicos ignoran.

Reveló 10 hábitos que haces todos los días y que te quitan años de vida.

1) Repasar conversaciones en tu cabeza

[OpenAI @OpenAI]

Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946.

For nearly 80 years, mathematicians believed the best possible solutions looked roughly like square grids.

An OpenAI model has now disproved that belief, discovering an entirely new family of constructions that performs better.

This marks the first time AI has autonomously solved a prominent open problem central to a field of mathematics.

[NASA @NASA]

First stop, Mars. Next stop, Psyche 📍

On May 15, our Psyche spacecraft swung by Mars on its way to its next destination: a metal-rich asteroid also named Psyche. The Red Planet gave the spacecraft a 1,000-mph speed boost and provided some stunning photos as well!

[Elon Musk @elonmusk]

As the recently expanded partnership with @AnthropicAI demonstrates, @SpaceX is offering AI compute as a service at significant scale.

We are in discussions with other companies to do the same.

Over time, especially with orbital data centers, we expect to serve AI at extremely high scale.

[Lewis 🏴󠁧󠁢󠁷󠁬󠁳󠁿 @WaldronLewis]

Jeff Bezos reveals why he refuses to make a single important decision before 10am:

"I like to putter in the morning. I like to read the newspaper. I like to have coffee. I like to have breakfast with my kids before they go to school. My puttering time is very important to me. That's why I set my first meeting at 10 o'clock"

"I like to do my high IQ meetings before lunch. Anything that's going to be really mentally challenging, that's a 10 o'clock meeting. Because by 5pm, I'm like, I can't think about that today. Let's try this again tomorrow at 10am"

"As a senior executive, what do you really get paid to do? You get paid to make a small number of high quality decisions. If I make three good decisions a day, that's enough. Warren Buffett says he's good if he makes three good decisions a year"

[Nicholas Fabiano, MD @NTFabiano]

Neural similarity predicts whether strangers become friends.

Friends really are on the same wavelength.

[Nico @nicos_ai]

Han clonado Claude Design y puedes usarlo gratis y sin limites.

Se llama Open Design, un proyecto open source que te deja usar Claude para workflows de diseño sin pagar.

Sin suscripciones.
Sin límites (como la versión oficial).
Acceso total.

Esto es lo que puedes hacer:

— Generar diseños UI/UX con Claude
— Convertir prompts en diseños reales
— Sustituir herramientas de diseño caras en muchos casos
— Personalizarlo completamente (es open source)

Está hecho para devs, indie hackers y creadores que no quieren quemar dinero en herramientas.

De esos repos que pasan desapercibidos hasta que de repente todo el mundo los usa.

Si usas AI + diseño, tienes que probarlo

Enlace abajo 👇

(guárdalo antes de que explote)

[Massimo @Rainmaker1973]

Kame is a compact, open-source, 3D-printable quadruped robot that mimics animal-like movement.

[Andrej Karpathy @karpathy]

Fireside chat at Sequoia Ascent 2026 from a ~week ago. Some highlights:

The first theme I tried to push on is that LLMs are about a lot more than just speeding up what existed before (e.g. coding). Three examples of new horizons:

1. menugen: an app that can be fully engulfed by LLMs, with no classical code needed: input an image, output an image and an LLM can natively do the thing.
2. install .md skills instead of install .sh scripts. Why create a complex Software 1.0 bash script for e.g. installing a piece of software if you can write the installation out in words and say "just show this to your LLM". The LLM is an advanced interpreter of English and can intelligently target installation to your setup, debug everything inline, etc.
3. LLM knowledge bases as an example of something that was *impossible* with classical code because it's computation over unstructured data (knowledge) from arbitrary sources and in arbitrary formats, including simply text articles etc.

I pushed on these because in every new paradigm change, the obvious things are always in the realm of speeding up or somehow improving what existed, but here we have examples of functionality that either suddenly perhaps shouldn't even exist (1,2), or was fundamentally not possible before (3).

The second (ongoing) theme is trying to explain the pattern of jaggedness in LLMs. How it can be true that a single artifact will simultaneously 1) coherently refactor a 100,000-line code base *and* 2) tell you to walk to the car wash to wash your car. I previously wrote about the source of this as having to do with verifiability of a domain, here I expand on this as having to also do with economics because revenue/TAM dictates what the frontier labs choose to package into training data distributions during RL. You're either in the data distribution (on the rails of the RL circuits) and flying or you're off-roading in the jungle with a machete, in relative terms. Still not 100% satisfied with this, but it's an ongoing struggle to build an accurate model of LLM capabilities if you wish to practically take advantage of their power while avoiding their pitfalls, which brings me to...

Last theme is the agent-native economy. The decomposition of products and services into sensors, actuators and logic (split up across all of 1.0/2.0/3.0 computing paradigms), how we can make information maximally legible to LLMs, some words on the quickly emerging agentic engineering and its skill set, related hiring practices, etc., possibly even hints/dreams of fully neural computing handling the vast majority of computation with some help from (classical) CPU coprocessors.

[Elon Musk @elonmusk]

Major upgrade to 𝕏 advertising

[Google AI @GoogleAI]

Last week, we made Gemini Embedding 2, our first natively multimodal embedding model, available to the general public. Since then, developers have used it to build video analysis tools, visual shopping assistants, and more.

But you might be wondering... what is an embedding model? 🤔 Let’s break it down!

1. What is it?
Think of an embedding model as a "universal translator." It takes text, images, video, and audio data and turns them into a long string of numbers, like a unique digital fingerprint.

2. How does it work?
Historically, search has been text only. Now, instead of just matching data by keyword, Gemini Embedding 2 maps multiple modalities in the same space based on meaning. It "feels" the connection between a video of a soccer goal and the words "game-winning shot" without needing tags.

For example, "ocean" and "waves" are placed close together, but "ocean" and "toaster" are miles apart.

3. How can you use it?
Developers have been using it to incorporate smarter search functionality into their builds. This means creating tools where you can snap a photo of a product and type "find this in yellow," or search through thousands of hours of video by describing what happens in a scene.

4. Ready to try it out for yourself?
You can start using it today via the Gemini API or the Gemini Enterprise Agent Platform.

[Rohit @ai_rohitt]

The creator of Claude Code teaches more about vibe-coding in 30 minutes than most tutorials do in hours.

Save this — it'll change how you build forever.

[ares. 🎧 @aresotik]

Ahora Claude Code puede leer documentaciones completas sin gastar un solo token.

Solo necesitas conectarlo a NotebookLM de Google vía MCP.

Aquí el tutorial de cómo hacerlo. ⬇️

[Rishabh @Rixhabh__]

Anthropic pays engineers $750,000+ a year to understand how LLMs work.

Stanford just put a 2 hour lecture that covers 80% of it for FREE.

Bookmark this. Give it 2 hours today.

[Satya Nadella @satyanadella]

Agent Mode is here in Outlook!

Copilot can now help run your inbox and calendar, triaging emails, rescheduling meetings, and helping you stay on top of what matters most.

[Stitch by Google @stitchbygoogle]

Today, we’re open-sourcing the draft specification for DESIGN.md, so it can be used across any tool or platform. We’re also adding new capabilities.

DESIGN.md lets you easily export and import your design rules from project to project. Instead of guessing intent, agents know exactly what a color is for and can even validate their choices against WCAG accessibility rules.

Watch David East break down this shared visual language in action👇. New capabilities and links in 🧵

[Zain Shah @zan2434]

Imagine every pixel on your screen, streamed live directly from a model. No HTML, no layout engine, no code. Just exactly what you want to see.

@eddiejiao_obj, @drewocarr and I built a prototype to see how this could actually work, and set out to make it real. We're calling it Flipbook. (1/5)