M. Alex O. Vasilescu @AlexTensor
Developing #causal #tensor framework -TensorFaces, Human Motion Signatures | Alumna @MIT, @UofT | #womenwhocode Los Angeles and New York Joined April 2009-
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Vibe coding gets a lot of bad rap because a lot of things are being mixed up when it comes to separating vibe coding from real coding and software engineering: - Not every use of AI coding agents and tools counts as vibe coding - At the same time, I don't think there are many software engineers who don't use AI coding agents We need to better separate the tool. To me, vibe coding is when you just provide vague and very general prompts (e.g., create a clone of App X but for Y) and very general feedback, without overseeing the model's intermediate decisions (e.g., on architecture) or reviewing the code. Real coding/software engineering (which includes agentic engineering) is when you abide by all the core disciplines of building software but may also use AI coding agents in the process. You own the code, you are aware of the architecture, you can look into the code and investigate errors, and you might do a little manual coding when required. There's nothing wrong with vibe coding. Vibe coding is available to everyone, including non-coders. It is perfectly fine for small personal projects and prototypes and PoCs. Real coding/agentic engineering requires real software engineering skills. It is necessary when you want to create software for sensitive operations, that go into production, or need to be shipped to thousands/millions of users.
I would really love to see what Claude/Codex/Copilot/Gemini can produce in reliable visuomotor control system design in real world scenarios. And pit my system against what the agents remix from OpenCV & other online open robotics repos. They wouldn't stand a chance.
the coding agent haters are getting dunning-kruger'd so hard right now do you really think that your engineering ability is better than the models at this point? it is very very likely that fable is better than you in every branch of software it has been trained on all the
MIT professor Sherry Turkle warns that people have become dangerously enmeshed with chatbots. buff.ly/uI0N9XG
Researchers at The Citizen Lab have for the first time released technical evidence of sophisticated mercenary spyware being distributed via online advertising. buff.ly/K8nohp5
Chain of thought (CoT) was always a stepping stone, not the final destination. There are several studies that show CoT tokens are not a faithful representation of the inner reasoning of AI models, even though they provide an acceptable account of how the model decides and acts. A real and robust solution requires a combination of inner reasoning (in continuous latent space) and intermediate explanations (e.g., an interpretable and controllable graph representation of the model’s action plan). Each step should ideally have a verifiable goal or at least be scored by a decision model like Jev.
The sudden collapse of the value of CoT (even summarized CoT) in the agentic era changes working with AI. Effectively steering AIs and getting any sort of observability now requires you to ask for interim outputs & tests, and to use AI help to troubleshoot problems you find.
The OpenAI employee who allegedly stole over a hundred confidential documents without OpenAI noticing for months sent the documents to his number *in mainland China*...
Human problem solving involves causal reasoning that homes in on most likely solutions which makes it possible to solve complex real world problems. While AI with statistical reasoning needs to generate millions of trials with negligible probability of being novel.
I would really love to see what Claude/Codex/Copilot/Gemini can produce in reliable visuomotor control system design in real world scenarios. And pit my system against what the agents remix from OpenCV & other online open robotics repos. They wouldn't stand a chance.
Like the time he was siding with Effective Altruists like Amanda Askell 🤢 talking about how “shocking” my “allegations” of them were and how he was quote tweeting her. Gotta show all these receipts at some point.
Lol times are strange when I find myself on the same side as Yann LeCun and David Sacks. I find it interesting how he always comes to the conclusions I set out years earlier excerpt that when I first set them out he likes to denigrate my work.
Defense in depth doesn’t mean just “moar security layers”. The layers shouldn’t fail in similar ways. You want controls with independent failure modes, or even better inversely correlated ones. Sorry for the 2am (my time) rant, clearly this drives me crazy.
AI "cyber models" aren't going to solve our security problems. "If we just patch all the vulnerabilities then we're safe" is a convenient story but it's also not true. If you're worried about cybersecurity, the solution involves hard work, not just more tokens.
The key data for training your AI is the data you’ll generate by interacting with it.
As a German, it is a tragedy: in a parallel universe this would be Germany’s moment, as it requires so much that Germany has traditionally excelled at: industrial capacity, engineering, world-leading physics, design and manufacturing excellence. That was exactly what ‘made in Germany,’ stood for.
Jensen Huang has a message for Germany
The AI labs have pushed so much fear that they make the cybersecurity industry look wholesome and honest. Truly impressive work.
Should Germany, UK or more broadly the EU leave frontier AI models to the US and China to build?
Jensen Huang has a message for Germany
Such an important reminder. Review what people wrote (past tense here intentional), not what you would have written in their shoes.
Review this version of the manuscript. Review the paper the authors set out to write, not the one you would've written.
Arthur is right: Europe has a recurring pattern of defeatism. The key to excellence is momentum: Arthur & Mistral have done a great job getting quite close to the frontier, at very small expenditure (relative to other big labs). Given more runway, they *will* get closer still. Further, Europes own frontier AI lab is essential for independence. Europe needs frontier labs where young researchers learn the fundamentals of this technology, as a seed for an ecosystem of applications and new startups: a frontier lab is a never-ending source of startups founded by its alumni, value that Europe can only accrue if it has its own frontier lab. Physical AI - intelligent robots - will require *exactly the same* infrastructure and insights as LLMs do. If Europe gives up on LLMs, Europe will give up its independence on all AI, physical or otherwise. Lastly, perseverance is a muscle that has to be trained: if Europe doesn't learn to not give up in the face of (fierce) competition in the case of LLMs, it will fail at this exercise again when the next innovation comes around. Europe needs a frontier lab like Mistral.
Should Europe leave frontier AI to the Americans and the Chinese? The idea has gained ground in Europe. It is a fundamental mistake. Build or surrender: for now, the choice is still ours. Full article below. x.com/i/article/2110…
@ShlomoArgamon We should have specified: plagiarism is not advice. The jingle is ridicule.
AI-aided to do what? Plagiarize. Current models draw on scientists’ published and unpublished work, often without attribution. I would rather have AI serve as a natural-language interface to tools, data, and computational infrastructure, with sources and contributions visible.
The ideal outcome for science isn't a couple of labs using proprietary models and millions of dollars to crack trophy problems, it's to have millions of AI-aided human scientists who follow their curiosity and become way more ambitious
Yud crashing out over this new interpretability finding gets to the core of my problem with doomers. For any progress we make, they can always say “it’s not enough” or “that won’t work”. They can perma-doom. But the sum of all the things that aren’t enough is what keeps us safe.
As @friedberg and I discussed last week
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