EDITOR IN CHIEF, EVIL MARTIANS

Joined October 2015
Travis Turner retweeted
Replying to @evilmartians
Congrats on the win content > ads every time
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Travis Turner retweeted
Replying to @evilmartians
engineers writing the content is exactly why it gets read. marketing-written tech content is instantly obvious and nobody trusts it
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Yeah!
All our engineers are encouraged to write technical content for the blog, which then powers most of our marketing strategy. This makes all the difference for us. Hundreds of thousands of people read our blog every year and trust our team enough to do business with us. We’re beyond happy to see it rated the top blog in @planetargon’s 2026 Ruby on Rails Community Survey. Thanks to everyone who reads us, and to @travis____t for leading the blog! ♥️ P.S. @sfrubyconf also made the list of the top ten conferences Rubyists plan to attend this year. How exciting!
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Travis Turner retweeted
All our engineers are encouraged to write technical content for the blog, which then powers most of our marketing strategy. This makes all the difference for us. Hundreds of thousands of people read our blog every year and trust our team enough to do business with us. We’re beyond happy to see it rated the top blog in @planetargon’s 2026 Ruby on Rails Community Survey. Thanks to everyone who reads us, and to @travis____t for leading the blog! ♥️ P.S. @sfrubyconf also made the list of the top ten conferences Rubyists plan to attend this year. How exciting!
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That’s what I’ve been saying
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Travis Turner retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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He was also the bomb in Phantoms, yo.
Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models “I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that. “With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor. “You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something. “That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’ “I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
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You may just have to wait for the video of Travis Turner's closing remarks. Is it aliens? Is it God? Or just drugs?
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We are thrilled to announce our next Emerald sponsor. ... Ready? It’s TRMNL, widely loved by fashionable engineers and DIY tinkerers. @useTRMNL is the premier ePaper dashboard powered by Ruby. Ryan is bringing a few devices for sale at the event, and we'll also give some away in exchange for Pier coins.
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Travis Turner retweeted
Lisbon friends, come listen to Nina's talk on how to protect yourself from supply chain attacks. We've talked about this topic a lot and @ninoid_ is one of the people on our team actively building a more secure ecosystem. If you go, send us pics!
Supply-chain attacks are a daily reality now. Even the most widely used npm packages get weaponized to compromise thousands of developers at once, and no project is out of reach. @ninoid_ is a Frontend Engineer at Evil Martians, increasingly focused on what developers can actually do to prevent attacks. She'll review two real dependency updates live using Multiocular, the open-source tool her team built, to show what separates them once you stop trusting the version number and start reading the diff.
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Did we tell you that all the coins you collect on The Pier turn into real gold at the conference!? 👀 Well, not gold gold, but Ruby Goodies. We'll have collectibles, physical and digital Ruby products, and merch that you want to wear. Spoiler alert: there're TRMNL devices available, but you may need to fight @palkan_tula for them. Don't walk, run to The Pier, and complete quests to get coins. (You'll need to walk there, tho, we don't have a running feature available).
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It seems the mainstream is *finally* catching up to my thoughts on AI! Uh oh! 😊
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I’ve got my tickets, looking forward to the conference. This weekend’s task, get my talk down from 5 hours to my allotted length. I guess I’ll have just have to cut the part about nuclear weapons. And the poem. Sad to see the poem go.
Booking my time off for work today because we're almost to Sep 28-29th, I reflected on how our sponsors make this worthwhile. Shoutouts to @gustohq, @honeybadger.io, @appsignal, @beflagrant.com, @typesense, and @evilmartians for making RMR not just doable, but a treat!
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We read the latest RubyAI issue by @mattsolt and were extra bummed about the chart that shows the big decline of new Ruby developers. But the good news is that all engineers who come to SF Ruby are actively participating in making the ecosystem better to attract new people. Being in the same room with founders of successful startups and authors of some of the best OSS tools in the language is the first step to making a better ecosystem and attracting new users. We love Ruby and want to see it succeed. If you do too, let's meet at SFJAZZ this Nov 10–12. Only 22 days to get tickets: luma.com/sfrubyconf2026?utm_…
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Travis Turner retweeted
We've moved from Gatsby to @astrodotbuild. After years of procrastination, surprisingly, 1 engineer and @ClaudeDevs did it in 2 weeks! 61% less homepage JavaScript, mobile score 66 to 90, page weight 2.1 MB to 1.1 MB. The story, happy engineers, bugs and all: evilmartians.com/chronicles/…
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It’s just a stochastic parrot, autocomplete on steroids! 🤤
Announcing a solution to the Navier-Stokes problem, one of the seven Millenium Prize problem. Represents a major milestone for both AI and mathematics, as well as pointing to an upcoming renaissance in scientific discovery. Hoping that the knowledge created by this model can help the community better understand non-linear PDEs, which are used to model much of the physical world.
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Travis Turner retweeted
Come join us at @sfrubyconf this November! Last year’s edition was awesome, and I’m sure this year is going to be even better! ❤️
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