Emilio Lopez

[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.

[Tesla Europe, Middle East & Africa @teslaeurope]

Tesla has been working hard toward shipping Full Self-Driving (Supervised) in Europe for over 12 months now. We have given FSD demos to regulators of almost every EU country. We have requested early access, pilot release programs or exemptions where possible.

We have developed & shared detailed safety evidence for FSD, now public in our latest Safety Report. And we have driven over 1 million kilometers safely on EU roads across 17 different countries (internal testing). 

Our main path to success is partnering with the Dutch approval authority RDW to gain exemption for the feature. This involves proving compliance with existing regulations (UN-R-171 DCAS) + filing an exemption (EU Article 39) for yet-to-be-regulated behaviors like Level 2 systems off-highway, system-initiated lane changes with hands-off the wheel etc. 

Some of these regulations are outdated and rules-based, which makes FSD illegal in its current form. Changing FSD to be compliant with these rules would make it unsafe and unusable in many cases. While we have changed FSD to be maximally compliant where it is logical and reasonable, we won't sacrifice the safety of a proven system or materially deteriorate customer usability. 

As a result, we are gathering evidence to get exemptions on a specific rule-by-rule basis. Unfortunately, the real world fleet-proven safety wins alone are considered insufficient. 

Currently, RDW has committed to granting Netherlands National approval in February 2026. Please contact them via link below to express your excitement & thank them for making this happen as soon as possible. Upon NL National approval, other EU countries can immediately recognize the exemption and also allow rollout within their country. Then we will bring it to a TCMV vote for official EU-wide approval. 

We're excited to bring FSD to our owners in Europe soon!

https://t.co/FhoK0xX81r

[Emilio Lopez @emiliol0pez]

@ClubTeslaES El modelo tracción trasera sí ha subido de precio. Ha vuelto a 39.760€

[Emilio Lopez @emiliol0pez]

@TeslaNewswire And price increased at least in Spain from 35k to 39k for RWD

[Emilio Lopez @emiliol0pez]

Nice explaination of Transformers vs Mixture of Experts architectures

[Avi Chawla @_avichawla]

Transformer vs. Mixture of Experts in LLMs, clearly explained (with visuals):

[Andrew Ng @AndrewYNg]

There’s a new breed of GenAI Application Engineers who can build more-powerful applications faster than was possible before, thanks to generative AI. Individuals who can play this role are highly sought-after by businesses, but the job description is still coming into focus. Let me describe their key skills, as well as the sorts of interview questions I use to identify them.

Skilled GenAI Application Engineers meet two primary criteria: (i) They are able to use the new AI building blocks to quickly build powerful applications. (ii) They are able to use AI assistance to carry out rapid engineering, building software systems in dramatically less time than was possible before. In addition, good product/design instincts are a significant bonus.

AI building blocks. If you own a lot of copies of only a single type of Lego brick, you might be able to build some basic structures. But if you own many types of bricks, you can combine them rapidly to form complex, functional structures. Software frameworks, SDKs, and other such tools are like that. If all you know is how to call a large language model (LLM) API, that's a great start. But if you have a broad range of building block types — such as prompting techniques, agentic frameworks, evals, guardrails, RAG, voice stack, async programming, data extraction, embeddings/vectorDBs, model fine tuning, graphDB usage with LLMs, agentic browser/computer use, MCP, reasoning models, and so on — then you can create much richer combinations of building blocks.

The number of powerful AI building blocks continues to grow rapidly. But as open-source contributors and businesses make more building blocks available, staying on top of what is available helps you keep on expanding what you can build. Even though new building blocks are created, many building blocks from 1 to 2 years ago (such as eval techniques or frameworks for using vectorDBs) are still very relevant today.

AI-assisted coding. AI-assisted coding tools enable developers to be far more productive, and such tools are advancing rapidly. Github Copilot, first announced in 2021 (and made widely available in 2022), pioneered modern code autocompletion. But shortly after, a new breed of AI-enabled IDEs such as Cursor and Windsurf offered much better code-QA and code generation. As LLMs improved, these AI-assisted coding tools that were built on them improved as well.

Now we have highly agentic coding assistants such as OpenAI’s Codex and Anthropic’s Claude Code (which I really enjoy using and find impressive in its ability to write code, test, and debug autonomously for many iterations). In the hands of skilled engineers — who don’t just “vibe code” but deeply understand AI and software architecture fundamentals and can steer a system toward a thoughtfully selected product goal — these tools make it possible to build software with unmatched speed and efficiency.

I find that AI-assisted coding techniques become obsolete much faster than AI building blocks, and techniques from 1 or 2 years ago are far from today's best practices. Part of the reason for this might be that, while AI builders might use dozens (hundreds?) of different building blocks, they aren’t likely to use dozens of different coding assistance tools at once, and so the forces of Darwinian competition are stronger among tools. Given the massive investments in this space by Anthropic, Google, OpenAI, and other players, I expect the frenetic pace of development to continue, but keeping up with the latest developments in AI-assisted coding tools will pay off, since each generation is much better than the last.

Bonus: Product skills. In some companies, engineers are expected to take pixel-perfect drawings of a product, specified in great detail, and write code to implement it. But if a product manager has to specify even the smallest detail, this slows down the team. The shortage of AI product managers exacerbates this problem. I see teams move much faster if GenAI Engineers also have some user empathy as well at basic skill at designing products, so that, given only high-level guidance on what to build (“a user interface that lets users see their profiles and change their passwords”), they can make a lot of decisions themselves and build at least a prototype to iterate from.

When interviewing GenAI Application Engineers, I will usually ask about their mastery of AI building blocks and ability to use AI-assisted coding, and sometimes also their product/design instincts. One additional question I've found highly predictive of their skill is, “How do you keep up with the latest developments in AI?” Because AI is evolving so rapidly, someone with good strategies for keeping up — such as reading The Batch and taking short courses 😃, regular hands-on practice building projects, and having a community to talk to — really does stay ahead of the game.

[Original post: https://t.co/I3alxNs0vn ]

[Emilio Lopez @emiliol0pez]

@elonmusk You're right Elon, but bringing v13 FSD to HW3 cars will save even more lives... 😉 It's way safer than v12

[Emilio Lopez @emiliol0pez]

Looks like FSD is finally coming to Europe

[Tesla Europe, Middle East & Africa @teslaeurope]

FSD Supervised testing in Rome, Italy

Pending regulatory approval

[Emilio Lopez @emiliol0pez]

@elonmusk Assuming this version will be only available for AI4 cars and will likely become v14, couldn't the same caching and memory optimization be applied to v13 to come to HW3 cars?

[Emilio Lopez @emiliol0pez]

@slcuervo Creo que en un video mencionaste que el tuyo tenía motor de Performance. ¿Puede ser que calcule como un LFP normal y de ahí venga la diferencia en la estimación?

[Emilio Lopez @emiliol0pez]

@QueTesla @tothemoon35 Eso no es un Tesla. Tiene las molduras rectas y todo el mundo sabe que salen de fábrica torcidas o se doblan con el sol

[Emilio Lopez @emiliol0pez]

@CarlosCuezva @ClubTeslaES O me falla la vista o no está el de Manzanares