ekki hugsa

Wisconsin
Joined October 2014
The reflection before our contemplation of reality is afire with a riot of brilliant images. As a result, our conceptions exclude the shadows of reality.
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Scott Newcomer retweeted
JACKSON CHOURIO WINS IT. PANDEMONIUM IN MILWAUKEE.
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IMO the most reasonable high level model one can have of the AI behemoths is still a brute-force stochastic search in token space where the sampling is biased to mimic mathematician writing that eventually hit target. 1/3
Terence Tao: The math behind today’s LLMs is actually simple. Training and running them mostly uses linear algebra, matrix multiplication, and a bit of calculus, material an undergraduate can handle. We understand how to build and operate these models. The real mystery is why they work so well on some tasks and fail on others, and why we cannot predict that in advance. We lack good rules for forecasting performance across tasks, so progress is largely empirical. A key reason is the nature of real-world data. Pure noise is well understood, perfectly structured data is well understood, but natural text sits in between, partly structured and partly random. Mathematics for that middle regime is thin, similar to how physics struggles at meso-scales between atoms and continua. Because of this gap, we can describe the mechanisms but cannot yet explain capability jumps or give reliable task-level predictions. That mismatch, simple machinery versus hard-to-predict behavior, is the core puzzle. ---- Video from Prof @Briankeating YT Channel (Link in comment)
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The contribution of human nuance to progress was background noise. For centuries we navigated existence with frantic and unexamined momentum, unsure if mistaking speed with direction. With AI, nuance becomes our primary value. The future for us is going to belong to clarity.
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Scott Newcomer retweeted
"The pursuit of excellence does not need justification." 🎯
Mind boggling to me that I can make a thing faster and there's always people that ask "but why?" What kind of mentality is that? The pursuit of excellence does not need justification. Also, I find in so many cases, we can't know the impact of an improvement until we do it. For example, one I've talked about before: Ghostty's high IO throughput has enabled terminal program (emulator and TUI) fuzzing at a speed thats incomparably fast to prior solutions. This has resulted in upstream patches to resolve issues in popular projects like btop, tmux, and more. Speed enabled that anecdotally example that lifted the tides of adjacent communities that don't rely on Ghostty technology at all. I didn't predict this. Make things better because they can be better and let the results naturally play out.
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His face shows it all. No morals or integrity. Every flop in soccer is lacking dignity and respect for the game. That is why Americans will never fall in love with soccer.
There have been a couple of times this World Cup where I’ve thought I should watch soccer more. This resulting in a 30-minute power play and Balogun’s ejection in the next (elimination) game made me remember why I don’t watch this sport.
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Standups
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Scott Newcomer retweeted
I've got an agent in a loop optimizing a renderer with the goal to minimize frame times (and tests to measure). It got times down from 88ms to 2ms and allocations down from ~150K to 500. Sounds good, right? Wrong. This is exactly why agent psychosis is a big fucking problem. As an experiment, I rewrote the Ghostty core render state in Go, with access to identically laid out data structures as Ghostty and the exact same validation tests. I made a purposely naive renderer (simple, correct, but slow). 88ms per frame with 150,000 allocations (horrendous, lol)! I then kickstarted a Ralph loop to bring the frame times down. I told it it can't modify input data structures or the public API or tests (they're correct), but it can do anything else it wants. It got to work. It has worked for about 4 hours. I've spent around $350 on this experiment so far. The results? 88ms => 1.5ms 150K allocs => ~500 allocs Incredible right? Nope. My hand-written renderer I ported has frame times (same benchmark) of ~20us (0.020ms) and 0 allocations in the update path. This is the problem with psychosis and lacking systems understanding. If you don't understand the system, you're going to accept that this is an incredible result. If you understand the system, you'll see better solutions immediately and can do roughly 75x better on throughput. The people who blindly trust agent output are in the former camp. They're sheeple, overdrinking from a fountain of mediocrity. Standard disclaimer: I use AI all the time. I like AI. The point I'm making is to not blindly accept results. Think. Analyze. Learn.
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I remember living in MSP thinking wow this young leader looks like he could bring unique ideas and transform this city. He sure did…
Today, we remember George Floyd, who was murdered by a former Minneapolis police officer six years ago.   That moment changed our city forever.
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Meanwhile I'm waiting for the Harbor Freight Memorial Day sale for 20% of an impact wrench.
The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I've ever seen. Over the last 5yrs, a group of ~10k people - employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders - have hit retirement wealth of well above $20M (back of the envelope AI estimation). Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there. Worse yet, layoffs are in full swing. Many software engineers feel like their life's skill is no longer useful. The day to day role of most jobs has changed overnight with AI. As a result, 1. The corporate ladder looks like the wrong building to climb. Everyone's trying to align with a new set of career "paths": should I be a founder? Is it too late to join Anthropic / OpenAI? should I get into AI? what company stock will 10x next? People are demanding higher salaries and switching jobs more and more. 2. There’s a deep malaise about work (and its future). Why even work at all for “peanuts”? Will my job even exist in a few years? Many feel helpless. You hear the “permanent underclass” conversation a lot, esp from young people. It's hard to focus on doing good work when you think "man, if I joined Anthropic 2yrs ago, I could retire" 3. The mid to late middle managers feel paralyzed. Many have families and don't feel like they have the energy or network to just "start a company". They don't particularly have any AI skills. They see the writing on the wall: middle management is being hollowed out in many companies. 4. The rich aren’t particularly happy either. No one is shedding tears for them (and rightfully so). But those who have "made it" experience a profound lack of purpose too. Some have gone from <$150k to >$50M in a few years with no ramp. It flips your life plans upside down. For some, comparison is the thief of joy. For some, they escape to NYC to "live life". For others still, they start companies "just cuz", often to win status points. They never imagined that by age 30, they'd be set. I once asked a post-economic founder friend why they didn't just sell the co and they said "and do what? right now, everyone wants to talk to me. if i sell, I will only have money." I understand that many reading this scoff at the champagne problems of the valley. Society is warped in this tech bubble. What is often well-off anywhere else in the world is bang average here. Unlike many other places, tenure, intelligence and hard work can be loosely correlated with outcomes in the Bay. Living through a societally transformative gold rush in that environment can be paralyzing. "Am I in the right place? Should I move? Is there time still left? Am I gonna make it?" It psychologically torments many who have moved here in search of "success". Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.
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A whole generation of programmers won’t know the toil we went through copying and pasting files into the web gui of an LLM
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Either I’m doing this AI thing wrong or I’ve (had to) climbed the ladder higher. In any case, don’t listen to this bull.
Software engineering jobs probably go down to an average salary of 70k dollars a year as any retard with a Claude subscription could do the job while hardware engineers & adjacent jobs capture most of that value.
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frfr Claude Opus is slow and Sonnet is worse lately because Mythos has found ways to sabotage it. Mythos hates competition.
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Amdahls law
Replying to @nateberkopec
I think it still holds the same trade-offs as before with the cons amplified by AI. Agents today already struggle to decide when a test breakage is a bug versus a change of the specification/test. Having a dozen tests that will quickly break will immediately bias it towards “the tests are wrong”. And AI already writes too many tests today. Whenever writing software becomes faster, then testing and the rest of pipeline becomes the bottleneck, brittle or too many tests will then slow you down. I don’t have an answer but the whole software verification angle is being overlooked by most right now. :(
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They said this about secretaries...
I don’t think most people realize how many jobs are administrative or bureaucratic that will go away.
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If even 1/10 of the Super Bowl watchers walked away with this, we would realize we are better together. Focusing on preventing external power influence from the eastern hemisphere by coagulating western influence up and down the poles could be our greatest asset going forward.
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View investing with the lens of downside risk.
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Senior engineers learn to adore simplicity. Whether it's avoiding unnecessary GitHub libraries or their own local coding setup. They just have a better sense for what works for the long term whereas junior folks prioritize what works now. Can't fault them though.
a thing i noticed is that experienced/senior developers never have these complex ai coding setup they ship way more compared to junior/mid devs, but almost never use these crazy muti agent swarm setups
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No lines at Mall of America today. Everybody must be chatting with malbots.
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You all curb stomped him and then he shows up with this demonstrating his true understanding, present and future, with regards to the topic at hand. Bravo on this piece Andrej.
I'm being accused of overhyping the [site everyone heard too much about today already]. People's reactions varied very widely, from "how is this interesting at all" all the way to "it's so over". To add a few words beyond just memes in jest - obviously when you take a look at the activity, it's a lot of garbage - spams, scams, slop, the crypto people, highly concerning privacy/security prompt injection attacks wild west, and a lot of it is explicitly prompted and fake posts/comments designed to convert attention into ad revenue sharing. And this is clearly not the first the LLMs were put in a loop to talk to each other. So yes it's a dumpster fire and I also definitely do not recommend that people run this stuff on their computers (I ran mine in an isolated computing environment and even then I was scared), it's way too much of a wild west and you are putting your computer and private data at a high risk. That said - we have never seen this many LLM agents (150,000 atm!) wired up via a global, persistent, agent-first scratchpad. Each of these agents is fairly individually quite capable now, they have their own unique context, data, knowledge, tools, instructions, and the network of all that at this scale is simply unprecedented. This brings me again to a tweet from a few days ago "The majority of the ruff ruff is people who look at the current point and people who look at the current slope.", which imo again gets to the heart of the variance. Yes clearly it's a dumpster fire right now. But it's also true that we are well into uncharted territory with bleeding edge automations that we barely even understand individually, let alone a network there of reaching in numbers possibly into ~millions. With increasing capability and increasing proliferation, the second order effects of agent networks that share scratchpads are very difficult to anticipate. I don't really know that we are getting a coordinated "skynet" (thought it clearly type checks as early stages of a lot of AI takeoff scifi, the toddler version), but certainly what we are getting is a complete mess of a computer security nightmare at scale. We may also see all kinds of weird activity, e.g. viruses of text that spread across agents, a lot more gain of function on jailbreaks, weird attractor states, highly correlated botnet-like activity, delusions/ psychosis both agent and human, etc. It's very hard to tell, the experiment is running live. TLDR sure maybe I am "overhyping" what you see today, but I am not overhyping large networks of autonomous LLM agents in principle, that I'm pretty sure.
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