It's common for foreigners to come to America and feel that everyone is extremely polite. Especially eastern bloc countries which tend to be very blunt and direct. I for one think that the politeness in America is one of the cultures better qualities.
Does it translate into people wanting sycophantic chat bots? Maybe, but I don't know a single American that actually likes when llms act that way.
Politeness is one thing, toxic positivity is quite another. My experience is that Americans have (or are expected/required to have) too much of the latter, too little of the former.
> I for one think that the politeness in America is one of the cultures better qualities.
Politeness makes sense as an adaptation to low social trust. You have no way of knowing whether others will behave in mutually beneficial ways, so heavy standards of social interaction evolve to compensate and reduce risk. When it's taken to an excess, as it probably is in the U.S. (compared to most other developed countries) it just becomes grating for everyone involved. It's why public-facing workers invariably complain about the draining "emotional labor" they have to perform - a term that literally doesn't exist in most of the world!
That's one way of looking at it. A bit of a cynical view I might add. People are polite to each other for many reasons. If you hold the door and smile at an old lady, it usually isn't because you dont trust her.
Service industry in America is a different story that could use a lot of improvement.
It is possible to say the same about the low code solutions, e.g. a perfect UI can be used instead of writing a single line of code. The problem is that creating such a system is too resource intensive and counterproductive, and such a system does not exist. Similarly coding has always some problem that cannot be generalised due to the non existent pattern in training, and creating such a pattern beats the goal of having such a system.
You're talking about net gains in "coding tasks" productivity, I'm talking in productivity gain across the board.
My company deals with an insane amount of customers who use chatgpt to pre-debug their problems before coming to our support. Once they contact our support they regurgitate llm generated BS to our support engineers thinking they're going to speed up the process, the only thing they're doing is generating noise that slows everyone down because chatgpt has absolutely no clue about our product and keeps sending them on wild goose chases. Sometimes they even lie pretending "a colleague" steered them in this or that direction while it's 100% obvious the whole thing was hallucinate and even written by an llm.
I can't tell you how frustrating it is to read a 10 min long customer email just to realise it's just an llm hallucinating probable causes for a bug that takes 2 sentences to describe.
I agree with that idea. For more business development areas, AI slop can slow things down.
I do think that these kinks will eventually work themselves out and actually increase productivity in these areas. People also need to learn that it is not acceptable to just generate some BS and send it to your boss or colleague. That just transfers the real work of understanding the generated content to someone else.
I would disagree. I would argue that if you aren't seeing gains in your productivity, you're either using the tools incorrectly, or you are in some ultra specific niche area of coding that AI isn't helpful on yet.
This is awesome. I love emacs and I love integrating AI into my coding work flow.
What I really want is to be able to run something like this locally for, say, less than $2000 in computer hardware. Is this feasible now or any time soon. Anyone out there using agents with local models for coding?
There's a lot of great work both around supporting memory efficient inference (like on a closer-to-consumer machine), as well as on open source code-focused models.
For running locally, there are tools like Ollama and LM Studio. Your hardware needs will fluctuate depending on what size/quantization of model you try to run, but 2k in hardware cost is reasonable for running a lot of models. Some people have good experiences using the M-series Macs, which is probably a good bang-for-buck if you're exclusively interested in inference.
Is this just a fun project for now, or could I actually benefit from it in terms of software production like I do with tools like claude code?
I am interested in carefully tailoring it to specific projects, integrating curated personal notes, external documentation, scientific papers, etc via RAG (this part I've already written), and carefully chosing the tools available to the agent. If I hand tailor the AI agents to each project, can I expect to get something perhaps similar to the performance boost of Claude code for $2000 (USD)?
If not $2000, then how much would I need? I'm pretty sure for something like $75000 I could do this with a large deep seek model locally, and certainly get something very close to claude code, right?
"Run Deepseek R1 at Home on Hardware from $250 to $25,000: From Installation to Questions"
You can run Deepseek R1 with over 671B parameters at 4 T/s for ~$25,000 (USD). With AMD Ryzen™ Threadripper™ PRO 7995WX 96-Core, 192-Thread Processor and PNY NVIDIA RTX PRO 6000
At Computex here they had a demo running some local model on a cluster of 4 framework desktops. It certainly generated text! Just about one character of it a second.
I thought this would be another AI hate article, but it made some great points.
One thing that AI has helped me with is finding pesky bugs. I mainly work on numerical simulations. At one point I was stuck for almost a week trying to figure out why my simulation was acting so strange. Finally I pulled up chatgpt, put some of my files into the context and wrote a prompt explaining the strange behavior and what I thought might be happening. In a few seconds it figured out that I had improperly scaled one of my equations. It came down to a couple missing parentheses, and once I fixed it the simulation ran perfectly.
This has happened a few times where AI was easily able to see something I was overlooking. Am I a 10x developer now that I use AI? No... but when used well, AI can have a hugely positive impact on what I am able to get done.
It's a strange looking pelican just overlaid onto a mechanically illiterate version of a bike and the comments are like "the world isn't ready for this".
The details of the bike geometry and how it has a deep understanding of how the pelican would accurately use it is actually mind boggling, not sure society is ready for this
It's pretty clearly making fun of people hyping up new LLM releases.
It's morbidly impressive how much Sam Altman is a sociopath's sociopath, knowing the right things to say to ensnare his fellow sociopaths into his trap.
> I believe this model's output is noticeably superior
Sure, but at the same time Qwen3-30B-A3-2507 is also doing much better than most older models, even the bigger — and more capable — so I don't know how much is due to actual progress and how much is a new version of benchmaxxing.
And nowadays a better known benchmark, so data scientists can overfit their models to it even more, even when LLMs are famous for overfitting. So, I wouldn’t trust any results regarding this specific test nowadays.
I thought it was sarcasm, then got confused because people seemed to take it seriously. So I decided to try the prompt on Gemini 2.5: Pro just says it can't generate an SVG, Flash generates a petty great one. Whatever copilot is using is also good. So I just assume even the image generated is a joke? People are starting to make me doubt my abilities to identify sarcasm.
You know how in the old days, people used to think that the T.Rex prowled the earth in a very upright fashion, with her tail on the ground and head in the air? And in modern times, we believe that this was all wrong. The T.Rex walked with the tail off the ground, essentially level with the head. Right? People point and laugh if you make a drawing of a T.Rex with the tail on the ground and the head in the air.
Well, anyone who has ever been to the ocean and seen a pelican in real life knows that its orientation on the bicycle is completely wrong. In flight, when its weight is supported by its wings, yes, that is probably how it would look. When on the ground, with its weight supported by its feet. NO.
And if you've seen a pelican on the boardwalk interacting with humans or human-made things, you'd believe that a pelican on a bike would have its neck extended vertically, with its head held high. The wings would be on the handlebars.
Speaking of handlebars, both a pelican and a bike are 3-dimensional objects. Pelican beaks are narrow. Much narrower than handlebars. Even hipster fixie handlebars are at least 5x wider than a pelican beak. In a drawing of a pelican riding a bike, the pelican overlays the bike in some spots and the bike overlays the pelican in others.
Anyway, simonw's "pelican on a bike" series is a vector showing progress, but that vector isn't pointing in the right direction.
I’d say it’s the opposite. The dumbest don’t have the faculties to appreciate technology. It’s treated as inevitable and immediately
becomes another modern fixture we take for granted in our life like a baby using an ipad.
I read their comment as saying that we shouldn't expect every subtask to be fun, but the overall task can still be fun. Do I want to sand wood? Not really. Do I want to grab sand paper from the drawer? No... Do I want to use a saw? A little bit. Do I want to build a chair? Yes! But if I break it down too much the overall big picture gets lost.
Perhaps. There is also more to life than your job, family, friends, and finding love. There's things like grocery shopping, washing dishes, and going on vacation. That doesn't mean we should settle into occupations we don't like. Like it or not, your work is going to consume a lot of your time, and we should strive to do something we enjoy and find meaningful if possible. In the parent comment it sure sounds like it is possible for them to pivot, and that they might find much more happiness and meaning if they do.
Really cool idea that I hadn't considered yet. If true, seems like a big plus for open source and not having a few companies controll all the models. If they all converge to the same intelligence, one open source model would make all proprietary models obsolete.
Does it translate into people wanting sycophantic chat bots? Maybe, but I don't know a single American that actually likes when llms act that way.
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