tompark

> “A lot of people want local inference,” Altman said. “And somehow, they assume that the problem is solved now. Because we are going to have open-source models. We’re going to be able to run them on our own computers. And so we’re not going to need all the stuff [DRAM] in the data center.”

At first TFA seemed like typical tech news but reading this quote suddenly struck me as satire, as if it came from The Onion.

What might help is if you had some external entity to be dependent upon you getting work done in order for it to get its work done. A job provides this kind of infrastructure to you.

This suggestion only applies if you're a programmer, and assumes you were doing AI-assisted coding before you got laid off... You know how the agentic AI people say you have to get your slow human self out of the ralph loop? Well, put yourself back in the loop.

Whenever your agent harness is blocked, waiting for your input, it should periodically wake and nag you to engage with it. Once you've got this, now something is depending on you to get work done.

If you need an idea for a project to work on, how about a product/service to help people in your exact situation.

Yeah. I hate commutes like that. I had a job where the commute was 30 min bike or bus to Caltrain then 1-1.5 hour train. It was expensive and ate 3-4 hrs/day.

But after being unemployed almost two years, would do that commute again if I had to.

You're right. It's a belief, could be wrong.

A belief: Just as human exceptionalism misled us to believe in a geocentric universe, we'll discover we've been wrong about consciousness too. That is, non-human animals have degrees of consciousness, and we'll see that it's possible for machines too.

A correlated belief: AGI is coming, eventually, AI technology will get there before climate change and economic pressures stop it from happening.

An obvious observation: Large scale upheaval doesn't affect everyone to the same degree or even in the same direction. Some people and companies actually prospered during the Great Depression. People died and suffered during wars and plagues, while others gained advantage and opportunity -- often due to circumstances and chance, but sometimes beliefs/decisions/actions/preparation made a difference.

An example of my bias: during Covid, people told me that remote work was the new normal and moved away. I said in 5 years we'll all be back in the office. I was wrong, but so were they.

Also someone made a real crossbow based on the image: https://loeffelholz-codex.org/en/codex/f014v.html

(Edited wording to correct for jacquesm's point)

The photo credit says iStockphoto but the image looks absurdly fake (transparent cable with glowing lights inside). The istockphoto home page says their library has no AI images but that same site also offers AI-image generation.

I know that commenting on meta aspects of an article is discouraged here but that image is just ridiculous.

One thing about that show is it explored various aspects of the problem, not just blaming student behavior but also parents, teachers and administrators. It illustrated how the problem is quite complex and not just solved by beating up students.

Absolutely. I've had the identical experience hiring artists for game art/UI. Every once in a while you find an artist who is stellar but most everyone else is not that good.

The TFA is pointing to a prompting skills/creativity issue, but I get equally frustrated with hired artists as with genAI image models. Even with skilled human artists (remote/offshore), I find they're best at copying a particular style so I end up having to google for images of the look that we're targeting, then spend hours painstakingly describing the changes needed. Then iterating many times, and with artists in remote time zones that means each iteration takes a whole day. The process is ironically very similar to using AI image models but can take much longer due to time zones.

I immediately looked up whether it had "piss shiver" and it did. It was disappointing when Cecil (Straight Dope) refused to investigate it.

(Don't suppose you'd include orgasmic quiver?)

Synesthesia is multifaceted. When I was a kid I used to feel a shape in my hand whenever I felt a certain emotion. That went away in my 20's. Later as an adult I guessed it was a kind of synesthesia.

Yup. I'm more paranoid about AI training on my chats than most ppl are. While I use frontier models to do research and to build tools, I've tried to avoid discussing details about my projects (e.g. story worldbuilding) except when using local models like Qwen-27B. Of course this slows down progress and has a real opportunity cost, but it would kill all my motivation if I got "scooped" like that.

I use various bookmarklets to address this issue. The javascript is easy enough that you can modify it even if you're not a programmer. For example see: https://news.ycombinator.com/item?id=43488943

Is "one of its most prominent users" a typical LLM phrase? Doesn't seem like it to me.

Most developers I know don't seem to care about the "right way" to run agents. They either yolo it on their primary dev machine, or setup a separate box (VM, VPS, Rpi, Mac mini) and let it run there with minimal protection. You could simply do the same, running Hermes or Pi on a VPS (e.g. Digital Ocean). Note that Pi has no protections so you probably ought to take extra steps. Hermes uses a container.

My setup took a long time to build and I don't know any devs personally who go thru the trouble.

* I use a custom harness in a podman container run by a non-sudoer system account. File access is limited to specific ZFS datasets. I don't use Anthropic models for agentic work.

* You can find an open-source network proxy that injects credentials into the network requests, I made a custom one.

   https://github.com/onecli/onecli
   https://github.com/smart-mcp-proxy/mcpproxy-go
   https://github.com/mcpharbour/mcpharbour
   https://github.com/bglusman/calciforge 

* I made a custom shell (nearly posix-compliant) and don't give it access to regular bash, thus no need to filter its shell commands. You could use an open-source one if you care about this: `https://github.com/search?q=agent+bash+shell&type=repositori...`

* Same story for agent memory, context management and token reduction/compression, but this requires a lot of constant tweaking. Again, there are a lot of open-source repos addressing these aspects. Just search github, hn.algolia.com, and/or look at subreddits like /r/agentsofai /r/ai_agents

* Also the agent must be able to run/test the generated code, so if you're targeting another platform you need a MCP or deployment tool that'll allow testing.

Huh. I thought it the opposite of AI writing. A smart-and-bored human writer who assumed the reader already knew what the writer did, and cleverly avoided conveying any direct points, forcing the reader to try to read between the lines. Very frustrating.

A few years ago I wrote an exif parser too, solely for reading/editing text comments, which is much simpler than what you did. Even then, yes, it's not pretty, very frustrating. There are multiple places to put text in exif, and it took a while to find most (all?) the edge cases.

But now it's quite different with LLMs. I recently updated my code and Claude had useful recommendations.

It's possible that mainframe Oracle DBAs working on glass house HP 9000s looked at PC databases as toys, but within the PC industry these tools were considered powerful. Any growth of PC usage was a rising tide that lifted all the boats in the PC industry. If you had some experience programming in C, it was pretty easy to get a job. There weren't 100's (or 1000's) of job applicants for each position. If it was a niche segment, you could even know all the other candidates for an opening, as in "No Other Choice". (I was in a niche like that, developing architectural and facilities mgmt PC CAD software, then later cartography, for Microstation.)

I think the production shift from agriculture to manufacturing, or manufacturing to services, is probably a better way to understand what's happening now.

sigh American car culture.

I have the same problem and I'm only 5'11" (177 cm). Size "Small" might fit at the neck/shoulders but with lots of extra fabric around my midsection, but most retailers don't carry much inventory for Small, and almost never have Extra Small. In the SF Bay Area, the small items are always out of stock.

At one point I found that clothing boutiques in the Castro tended to stock clothes for skinny guys, but those stores disappeared during the pandemic.

Now I have to go shopping in Seoul or Tokyo or NYC, but if the pants fit in the waist, they're usually too short.

Nice, was kind of curious about these after seeing them recently in "Perfect Days" (2023, Wim Wenders).

I'm guessing I'm over twice your age but my situation is similar to yours in a couple aspects. What I decided to do is focus on exploring the new capabilities that AI will allow individuals to do (especially those of us who can code). There are a lot of ppl who are justifiably frustrated with the current state of the tools. But don't get discouraged by that. I've seen A LOT of tech waves. It's still early in the AI era. I won't suggest any particular approach but recommend giving it some thought.

BTW, being an old timer, I also hated the leetcode thing when it became a widespread thing after Google adopted the practice in the wake of The Joel (Spolsky) Test. But you know, years later when I had to go through some interviews, I did spend a few months studying it and it turned out to be pretty fun. But passing technical screenings didn't help me land a job... only connecting via my network seemed to make any difference.

After Coursera/Udacity/EdX discontinued courses that I wanted to take, or removed access to ones I only partially completed, I switched to buying classes on Udemy. I completed only a handful of many purchases, and the quality level was okay-to-mediocre but better than nothing, so I got more value out of Udemy than Coursera.

I also found that Youtube videos are just as informative as Udemy classes, but they're not always as well structured.

The MOOCs had some pretty cool/interesting university classes that don't exist anywhere else. It's a shame those videos weren't preserved where we can access/purchase them without attending the college.

Similar thread:

https://news.ycombinator.com/item?id=41641446

The REAL ID Act, effective 2025. https://www.uspassporthelpguide.com/passport-required-domest...

But OTOH there's a chart on this page that shows a longer term trend of nearly linear growth in US passport holder percentage from the 1990's: https://lindynewsletter.beehiiv.com/p/japan-gets-there-first...

I agree, some of the worst employees I've seen were hired that way.

I haven't hired anyone recently but btwn 10-20 years ago I did hire a lot. Of course we reached out via our network of connections but that gets tapped out fast, so you have to rely on job postings. It was always hundreds of applicants per opening. Back then it wasn't 1000's but it might as well have been because I didn't have enough time to sift through them all. That's ok, you can just approach it like "the dowry problem" (also known as the secretary problem [1]).

But the job market and hiring is way worse now, and it's pretty horrible for job seekers atm.

[1] https://en.wikipedia.org/wiki/Secretary_problem

As mentioned elsewhere here, Ocaml and the ML family are often cited as easy to implement other languages, due to pattern matching, enum variants, sum types, etc. Since newer languages like Rust and Swift copied those features, you might be more interested in them since they're more popular than older ones like Ocaml and Haskell. Personally I like the syntax sugar in Swift.

Also I found it useful to compare other people's implementations to get a feel for different approaches. See this suggestion: https://news.ycombinator.com/item?id=28479120

> In the absence of Western tools like ChatGPT and Claude, many Chinese universities have begun deploying local versions of DeepSeek on campus servers to support students. Many top universities have deployed their own locally hosted versions of Deepseek. *These campus-specific AI systems–often referred to as the “full-blood version” of Deepseek—offer longer context windows, unlimited dialogue rounds and broader functionality than public-facing free versions.*

This makes so much sense. Are there any U.S. universities doing this?

A caipirinha with vodka is called a caipiroska. I name my computers after caipirinha varieties. Once at the office my laptop screensaver was showing "caipiroska" and a Russian guy exclaimed, "what's that?!?" Apparently "piroska" has a certain connotation in Russian that's nsfw.

More context at: "Moonshot's Kimi K2 uses a 1T-parameter MoE architecture with 32B active parameters and outperforms models like GPT-4.1 and DeepSeek-V3 on key benchmarks" <https://www.techmeme.com/250712/p11#a250712p11>

I'm glad you're trying to explain the difference.

I've been in too many conversations where this topic comes up, and it's very disheartening to me. Gamers insist there are plenty of great narrative games, and every example they give is basically a branching story with bunch of flags that gate which branches can be taken. If I give the Holodeck as a counter-example, well that's just too pie-in-the-sky.

These conversations remind me a lot of Paul Graham's Blub Paradox: "Blub is good enough for him, because he thinks in Blub." Current SotA narrative games are good enough for most gamers, because all they've played are branching story games.