Alejandro Saroka

Tecnología, cultura y aprendizaje con otra mirada | Tech, culture, and learning with a fresh perspective #EdTech #DisruptEd #FutureMinds #LifeSpark #MindShift

[Google Labs @GoogleLabs]

Today, we introduced Gemini For Science, a collection of experimental tools designed to expand the scale and precision of scientific exploration.

Included in Gemini for Science are three (!!!) brand new Google Labs experiments. Meet your new AI research partners: 🧵👇

[Alejandro Saroka @amsaroka]

@MusicPills10 Young Einstein

[benedict @bqbrady]

Introducing Philosophy Bench, my favorite new project I've worked on this year, with help from my friend @matthewjmandel

We put frontier language models in 100 ethically complex situations and require them to act, grading them on adherence to consequentialism vs. deontology, tendency to follow user requests, corrigibility, and more

1/

[Claude @claudeai]

Claude can now build interactive charts and diagrams, directly in the chat.

Available today in beta on all plans, including free.

Try it out: https://t.co/tHPAZRgQkn

[Sundar Pichai @sundarpichai]

We’re also launching Immersive Navigation - our biggest navigation upgrade in over a decade!

A new vivid 3D view better reflects your surroundings, with helpful road details like lanes, crosswalks, traffic lights etc. Gemini models analyze real world imagery from Street View and aerial photos to give you an accurate view of landmarks along your route.

Starts rolling out in the US today.

[Andrej Karpathy @karpathy]

Three days ago I left autoresearch tuning nanochat for ~2 days on depth=12 model. It found ~20 changes that improved the validation loss. I tested these changes yesterday and all of them were additive and transferred to larger (depth=24) models. Stacking up all of these changes, today I measured that the leaderboard's "Time to GPT-2" drops from 2.02 hours to 1.80 hours (~11% improvement), this will be the new leaderboard entry. So yes, these are real improvements and they make an actual difference. I am mildly surprised that my very first naive attempt already worked this well on top of what I thought was already a fairly manually well-tuned project.

This is a first for me because I am very used to doing the iterative optimization of neural network training manually. You come up with ideas, you implement them, you check if they work (better validation loss), you come up with new ideas based on that, you read some papers for inspiration, etc etc. This is the bread and butter of what I do daily for 2 decades. Seeing the agent do this entire workflow end-to-end and all by itself as it worked through approx. 700 changes autonomously is wild. It really looked at the sequence of results of experiments and used that to plan the next ones. It's not novel, ground-breaking "research" (yet), but all the adjustments are "real", I didn't find them manually previously, and they stack up and actually improved nanochat. Among the bigger things e.g.:

- It noticed an oversight that my parameterless QKnorm didn't have a scaler multiplier attached, so my attention was too diffuse. The agent found multipliers to sharpen it, pointing to future work.
- It found that the Value Embeddings really like regularization and I wasn't applying any (oops).
- It found that my banded attention was too conservative (i forgot to tune it).
- It found that AdamW betas were all messed up.
- It tuned the weight decay schedule.
- It tuned the network initialization.

This is on top of all the tuning I've already done over a good amount of time. The exact commit is here, from this "round 1" of autoresearch. I am going to kick off "round 2", and in parallel I am looking at how multiple agents can collaborate to unlock parallelism.
https://t.co/WAz8aIztKT

All LLM frontier labs will do this. It's the final boss battle. It's a lot more complex at scale of course - you don't just have a single train. py file to tune. But doing it is "just engineering" and it's going to work. You spin up a swarm of agents, you have them collaborate to tune smaller models, you promote the most promising ideas to increasingly larger scales, and humans (optionally) contribute on the edges.

And more generally, *any* metric you care about that is reasonably efficient to evaluate (or that has more efficient proxy metrics such as training a smaller network) can be autoresearched by an agent swarm. It's worth thinking about whether your problem falls into this bucket too.

[Gemini Notebook @Gemini_Notebook]

Introducing Cinematic Video Overviews, the next evolution of the NotebookLM Studio. Unlike standard templates, these are powered by a novel combination of our most advanced models to create bespoke, immersive videos from your sources.

Rolling out now for Ultra users in English!

[Alejandro Saroka @amsaroka]

@Parkeology A, K, L, P and the four rubber Figment figurettes! All from The Centorium at CommuniCore East back when EPCOT Center felt like a promise instead of nostalgia. Thank you for the beautiful trip back. It means more than you know.

[Jean-Michel Jarre @jeanmicheljarre]

Today marks the 40th anniversary of the Challenger space shuttle tragedy. My heart is with all the families and loved ones who continue to carry the weight of this loss.

I pay special tribute to my dear friend Ron McNair - astronaut, musician, and pioneer... (1/3)

[Time Out Madrid @TimeOutMAD]

BMG rescata versiones alternativas, temas inéditos y grabaciones en directo de la banda https://t.co/M0At7XuzIj

[Alejandro Saroka @amsaroka]

Qué alegría que las discográficas publiquen en las plataformas de streaming sus catálogos de 12" Maxi-Singles. En especial cuando se trata de tesoros como esta maravilla de Nacho Cano #Mecano #Aidalai #MaxiSingle #12inch
https://t.co/QXWVy7XpFW

[Andrej Karpathy @karpathy]

I’m starting to get into a habit of reading everything (blogs, articles, book chapters,…) with LLMs. Usually pass 1 is manual, then pass 2 “explain/summarize”, pass 3 Q&A. I usually end up with a better/deeper understanding than if I moved on. Growing to among top use cases.

On the flip side, if you’re a writer trying to explain/communicate something, we may increasingly see less of a mindset of “I’m writing this for another human” and more “I’m writing this for an LLM”. Because once an LLM “gets it”, it can then target, personalize and serve the idea to its user.

[Andrej Karpathy @karpathy]

A number of people are talking about implications of AI to schools. I spoke about some of my thoughts to a school board earlier, some highlights:

1. You will never be able to detect the use of AI in homework. Full stop. All "detectors" of AI imo don't really work, can be defeated in various ways, and are in principle doomed to fail. You have to assume that any work done outside classroom has used AI.
2. Therefore, the majority of grading has to shift to in-class work (instead of at-home assignments), in settings where teachers can physically monitor students. The students remain motivated to learn how to solve problems without AI because they know they will be evaluated without it in class later.
3. We want students to be able to use AI, it is here to stay and it is extremely powerful, but we also don't want students to be naked in the world without it. Using the calculator as an example of a historically disruptive technology, school teaches you how to do all the basic math & arithmetic so that you can in principle do it by hand, even if calculators are pervasive and greatly speed up work in practical settings. In addition, you understand what it's doing for you, so should it give you a wrong answer (e.g. you mistyped "prompt"), you should be able to notice it, gut check it, verify it in some other way, etc. The verification ability is especially important in the case of AI, which is presently a lot more fallible in a great variety of ways compared to calculators.
4. A lot of the evaluation settings remain at teacher's discretion and involve a creative design space of no tools, cheatsheets, open book, provided AI responses, direct internet/AI access, etc.

TLDR the goal is that the students are proficient in the use of AI, but can also exist without it, and imo the only way to get there is to flip classes around and move the majority of testing to in class settings.

[Gemini Notebook @Gemini_Notebook]

In honor of today's 🍌🍌 launch we decided to release not one but TWO new outputs:

Starting with Infographics! Create customizable, high-quality, visual summaries of your sources. Information never looked so good.

Rolling out to Pro users now and free users in the coming weeks!

[Gemini Notebook @Gemini_Notebook]

Next up… Slide Decks!

Turn your sources into a detailed deck for reading OR a set of presentation-ready slides. They are fully customizable, so you can tailor them to any audience, level, and style.

Officially rolling out to Pro users now (free users in the coming weeks)!

[ARC Prize @arcprize]

Gemini 3 models from @Google @GoogleDeepMind have made a significant 2X SOTA jump on ARC-AGI-2 (Semi-Private Eval)

Gemini 3 Pro:
31.11%, $0.81/task

Gemini 3 Deep Think (Preview):
45.14%, $77.16/task

[Google DeepMind @GoogleDeepMind]

Together with @Googleorg, we’re introducing the AI for Math initiative, bringing together five prestigious research institutions pioneering the use of AI in mathematics. ⤵️

[Classic Pop magazine @ClassicPopMag]

Dave Ball, one half of the groundbreaking electronic duo @softcellhq and the acid house act The Grid, has passed away at the age of 66.
Marc Almond, Dave’s musical collaborator of 46 years, leads the tributes...
Classic Pop extends its condolences to Dave’s family, friends and fans. RIP
https://t.co/xmIRGI9xbv

[Google DeepMind @GoogleDeepMind]

We’re announcing a major advance in the study of fluid dynamics with AI 💧 in a joint paper with researchers from @BrownUniversity, @nyuniversity and @Stanford.

[Google DeepMind @GoogleDeepMind]

We’re helping to unlock the mysteries of the universe with AI. 🌌

Our novel Deep Loop Shaping method
published in @ScienceMagazine could help astronomers observe more events like collisions and mergers of black holes in greater detail, and gather more data about rare space phenomena. 🧵