Atelier de Chile

Tips about start ups.
From Chile, for Chile and Latam.
Coffee as fuel ☕️
Good luck for your start up!

[Atelier de Chile @atelierdechile]

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[Atelier de Chile @atelierdechile]

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[darkzodchi @zodchiii]

Jev Founder, Diogo Amogo, just released a PDF on building a Jev Harness for coding agents

this is a blueprint on how to make your coding agents 200× faster and 400× cheaper

Send this PDF and the article below to your Claude

Code or Codex instance and start shipping 200× faster 👇

[Atelier de Chile @atelierdechile]

https://t.co/bYsIZ3V2wO

[Atelier de Chile @atelierdechile]

https://t.co/nzkvOXJYE6

[Valerio Capraro @ValerioCapraro]

Terence Tao made a very powerful point:

“In most cases in pure mathematics, the problems are posed not because we desperately want the solution to these problems in and of themselves, but because we have seen from past experience that human-directed efforts to solve these problems tend to spur further development of the field through the efforts to solve such problems, and then to digest any partial or complete solutions that emerge for further insights.

Prematurely solving the problem by purely AI-powered methods—particularly without full transparency into the solution process—can contaminate this process to the point where it actually becomes a net negative for the progress of mathematics as a whole.”

I’ve been following Terence Tao for like 20 years, and I have always been impressed by the clarity of his thinking.

This clarity stands out even more in this difficult moment, as AI labs turn mathematics into a battleground in their race for supremacy.

In this race, they risk damaging one of humanity’s highest intellectual endeavours.

[Atelier de Chile @atelierdechile]

https://t.co/mdKtljIsPQ

[Andrew Ng @AndrewYNg]

The most important skills for using AI coding agents effectively. Presenting the AI Engineering Skills Map for using coding agents. https://t.co/GrEw7wG5Wz

[Atelier de Chile @atelierdechile]

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[Atelier de Chile @atelierdechile]

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[Atelier de Chile @atelierdechile]

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[Atelier de Chile @atelierdechile]

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[Atelier de Chile @atelierdechile]

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[Paul Novosad @paulnovosad]

Every college syllabus should include these graphs.

Use AI for homework, you will get it done faster and get a higher grade, and then get crushed on the exam.

[Atelier de Chile @atelierdechile]

https://t.co/37zuClz85S

[Jorge Selaive C. @jselaive]

Cuentas Nacionales de 2T26 del terror. Cae inversión, Construcción con 4 trimestres de caida consecutivos y Consumo cae en todos sus componentes. Muy difícil crecer 1% este 2026

[The Economist @TheEconomist]

In a recent study, pupils using AI saw their average homework score rise by 18% across all subjects after six months. But come exam time, the same students scored 20% below their classmates who had not called on AI’s help. We analyse the data https://t.co/1v1MoCuaXz

[Tech with Mak @techNmak]

A University of Colorado Boulder professor built one of the best AI-learning resources I’ve seen for people who are tired of learning about models through diagrams and code alone.

Prof. Tom Yeh makes students calculate modern AI architectures by hand.

Transformer. Self-attention. Multi-head attention. MoE. Switch Transformer. Mamba S6. CLIP. U-Net. Sparse Autoencoders. BitNet. RLHF. Even Diffusion Transformers.

The idea is simple => shrink the architecture until the full forward calculation fits on a page, then work through every number with a pen. Yeh describes the project as reducing each model to an example small enough to calculate end-to-end by hand.

Learn here: https://t.co/DXfVjhdGkl

[Param @ParamSiddh]

Best YouTube Channels To Learn AI in 2026 (No BS). Save it.

1. Fundamentals – 3Blue1Brown
2. Deep Learning – Andrej Karpathy
3. AI Research – Yannic Kilcher
4. Practical AI – AssemblyAI
5. LLMs – AI Explained
6. ML Theory – StatQuest
7. Papers Simplified – Two Minute Papers
8. GenAI – Matthew Berman
9. AI Agents – Nicholas Renotte
10. Applied ML – Krish Naik
11. PyTorch – Aladdin Persson
12. Math for ML – Serrano Academy
13. Industry Insights – Lex Fridman
14. Real-world AI – DeepLearningAI

[Atelier de Chile @atelierdechile]

https://t.co/ezS9pMOvPI