GPU acceleration, true-color, image display, etc.

Ideally, children would be educated and trained better to think critically; making people harder to manipulate through emotion. But, pragmatically, yeah, marketing/propaganda strategies are useful and even necessary for progress.

Your article made me wonder if there were any theories about ethically appealing to emotion, and I found this (psychological/political) theory interesting: https://semihcakir.com/blog/the-affective-intelligence-theory/. As I understand it, it posits that when people have low anxiety, their thinking is just habitual, but when they experience anxiety, they open themselves up to new information.

With infinite popups.

I think tool calling is just a form of structured output, where the LLM outputs something like json that describes the function to call and the arguments, then you parse that and run the function with the arguments, then feed the output back to the LLM in a new message, if you want. IDK the specific details, I’m guessing there are some special tokens some LLMs produce for tool calling, and I’m also guessing there is “controlled generation” (masking the logits/tokens, and only choosing to generate the tokens that would be valid). Ollama apparently doesn’t support the special tool-calling tokens or output structure that some models use.

This is how it looks when using OpenAI compatible APIs: https://platform.openai.com/docs/guides/function-calling?api-mode=responses.

I’ve never heard of TabbyAPI (I’m new to using local models, in general). I’m also not sure what TabbyAPI brings over Ollama, llama.cpp, or vLLM. So would be curious as well.

Edit: For my little toy project I’m working on, I’m switching to not using tool-calling at all, and building a LangGraph and using structured output, which should be more reliable with my use-case. I.e. just always call the tool manually, feed the output back to the LLM to have the LLM evaluate if the output was correct, retry calling the tool with different arguments if not, and just fail after 5 calls.

I like watching Yannic Kilcher, to keep up with some of the newer developments, and read various papers. I do have a background in ML (mostly the more traditional, non-generative, supervised learning and reinforcement learning) though.

I think this is only a small part. Interest rates are kinda high. VCs only want to invest in companies with AI exposure because of all the hype. From companies I’ve interviewed with, offshoring seems to have accelerated dramatically (companies only had or wanted a few US devs to manage larger Indian teams). I’ve visited career pages of companies working in the business domain I have the most experience with, and all open software positions are exclusively in India.

I have over a decade of experience as well. Nobody in my small personal “network” knows anyone that’s hiring right now (I hate the fakeness of networking for networking sake, and am not very social, so I don’t have much of a network). I’ve applied to hundreds of job postings over 6 months, interviewed with maybe 6 companies, and rejected usually just because they were also interviewing 10-20 people for the same role, and another person had slightly more experience with a specific part of their stack, or they just liked another person more for whatever reason. I believe all remote job postings get 1000s of applicants, and every one local to me get 100s.

It all kind of reminds me of when I tried using online dating apps, lol.

They work for the shareholders, not the customers. For most publicly traded companies, the stock is completely detached from fundamentals, so they just do whatever the large investors like (often just hype the new hottest thing; such as marketplaces or “increasing efficiency” with layoffs), regardless if its good for the “real” business or not.

Hmm, Devstral doesn’t call any tools for me in the current stable Ollama version or the current release candidate. Wonder if it’s a bug in ollama or langchain. I’ve since tried “QwQ-32B-GGUF:Q3_K_XL”, and it’s a little better than Qwen3-14B:Q6, but still not quite satisfactory, and is much slower and “thinks” too much.

Hmm, don’t have any experience with those exact feelings myself, but I suppose they’re valid. There isn’t some kind of “peak” physical attractiveness, at least in my mind. There’s tons of people all with tons of preferences. Like, I find most women attractive, regardless, or for, their unconventionally attractive attributes. I imagine many women are the same way.

For me (also as a not-so-attractive male, IMO), it’s not the yearning for getting laid so much as the being in a loving relationship (masturbating is enough to calm my sex drive down). Thankfully, I’ve been in a very long-term relationship (~10 years). I remember it was literally driving me crazy being so emotionally isolated. I think a lot of people, woman and men, regardless of their sexual activity, have the same problems of isolation.

Guess I just prefer languages that do it this way:

class AClass {
  var aProp = 0

  fun aMethod() {
    aProp++
  }
}

Though I suppose confusion and bugs can happen when you do something like:

class AClass {
  var aProp = 0

  fun aMethod(aProp: Int) {
    // `this.aProp` is needed to access the property
  }
}

Hmm, I’m having trouble just landing interviews. Probably 50-100 applications before an interview. The possibility of losing my home is all that keeps me motivated. I do like software engineering though, and am always working on personal projects that probably won’t make me money.

But yeah, I do find it hard to motivate myself for practicing leetcode problems, and I do suck at them, since most stuff is just about remembering algorithms I learned in a class more than a decade ago, and the few times I’ve needed to implement them myself in my career, I’d just look them up.

I’m not sure it’s “AI” causing lack of demand though. It’s just most large companies have given up “innovating,” and are in rent-seeking mode now. In the US, at least, I’ve heard that many companies are only hiring devs in India to backfill the devs they’ve laid-off or quit. I’ve interviewed with an agentic AI startup, and it was pretty obvious it was “Actually Indians” (underpayed, overworked devs would fix the shitty code their AI agent would write). Most of the interviews I’ve gotten were to lead a team of all-remote Indian devs.

I’ve always found needing to manually add a class instance parameter (i.e. self) to every object method really weird. And the constructors being named __init__. Not having multiple dispatch is kinda annoying too. Needing to use decorators for class methods, static methods, and abstract classes is also annoying. Now that I think about it, Python kinda sucks (even though it’s the language I use the most, lol).

Haven’t used it yet, but venice.ai looks interesting; they have a good privacy policy. Right now, I just use ChatGPT with the “improve models” setting turned off, and use “temporary chat” mode. I don’t really trust OpenAI to be doing the right thing though. I’ve used 14B models locally, but they aren’t as good as 72B+ models.

I’ve heard it claimed social stratification didn’t really start happening until agriculture; that’s when you see many small residential structures and a few large ones. On the other hand, it allowed for specialization and the pursuit of arts and sciences (at least for the elite).

I think it’s mostly regular homebuyers that give them the money (well, the bank, through mortgages).

Mortgage payments are often cheaper than rent. The barrier for poorer people to owning is usually downpayment requirements and credit. There are many reasons for the “housing crisis;” most stemming from real-estate being treated as a speculative asset or “investment,” which incentivizes all kinds of phenomenon harmful to society.

Developers build houses and neighborhoods all the time without landlords paying them to do so. I’m actually not sure if landlords paying for building is common at all. Though, developers do all kinds of shady and harmful shit too.

Privacy policy changes are worrying. They also implemented Privacy Preserving Attribution, which sends anonymized data to advertisers, and enable it by default. I personally like LibreWolf.

I’ve played around a bit with woodworking, and have only used cheap 1x and 2x spf lumber to avoid wasting expensive wood, but it often warps pretty bad. Especially every time I’ve tried to glue-up 1xs to make tops or panels. Is there a trick or something, or is better wood needed?