I fire off the ide switch the model and think oh great this is better. I switch to something that worked before and man, this sucks now.
Context switching llm, Model Release Fatigue
Fine tuning will work for niche business use cases better than promises of AGI.
I was listening to a Taiwanese news channel earlier today and although I wasn't paying much attention, I remember hearing about how Chinese AIs are biased towards Chinese political ideas and that some programme to create a more Taiwanese-aligned AI was being put in place.
I wouldn't be surprised if just for this reason, at least a few different open models kept being released, because even if they don't directly bring in money, several actors care more about spreading or defending their ideas and IAs are perfect for that.
One theory is that they believe the real endpoint value will be embodied AIs (i.e. robots), where they think they'll hold a long-term competitive advantage. The models themselves will become commoditized, under the pressure of the open-source models.
Hats off to the folks who have decided to deal with the nascent versions though.
I use AI mostly for problems on my fringes. Things like manipulating some Excel table somebody sent me with invoice data from one of our suppliers and some moderately complex question that they (pure business) don't know how to handle, where simple formulas would not be sufficient and I would have to start learning Power Query. I can tell the AI exactly what I want in human language and don't have to learn a system that I only use because people here use it to fill holes not yet served by "real" software (databases, automated EDI data exchange, and code that automates the business processes). It works great, and it saves me hours on fringe tasks that people outsource to me, but that I too don't really want to deal with too much.
For example, I also don't check various vendors and models against one another. I still stick to whatever the default is from the first vendor I signed up with, and so far it worked well enough. If I were to spend time checking vendors and models, the knowledge would be outdated far too quickly for my taste.
On the other hand, I don't use it for my core tasks yet. Too much movement in this space, I would have to invest many hours in how to integrate this new stuff when the "old" software approach is more than sufficient, still more reliable, and vastly more economical (once implemented).
Same for coding. I ask AI on the fringes where I don't know enough, but in the core that I'm sufficiently proficient with I wait for a more stable AI world.
I don't solve complex sciency problems, I move business data around. Many suppliers, many customers, different countries, various EDI formats, everybody has slightly different data and naming and procedures. For example, I have to deal with one vendor wanting some share of pre-payment early in the year, which I have to apply to thousands of invoices over the year and track when we have to pay a number of hundreds or thousands of invoices all with different payment conditions and timings. If I were to ask the AI I would have to be so super specific I may as well write the code.
But I love AI on the not-yet-automated edges. I'm starting to show others how they can ask some AI, and many are surprised how easy it is - when you have thee right task and know exactly hat you have and what you want. My last colleague-convert was someone already past retirement age (still working on the business side). I think this is a good time to gradually teach regular employees some small use cases to get them interested, rather than some big top-down approach that mostly creates more work and many people then rightly question what the point is.
About politically-touched questions like whether I should rather use an EU-made AI like the one this topic is about, or use one from the already much of the software-world dominating US vendor, I don't care at this point, because I'm not yet creating any significant dependencies. I am glad to see it happening though (as an EU country citizen).
Another nice thing about waiting a bit—one can see how much (if any) the EU models get from paying the “do things somewhat ethically” price. I suspect it won’t be much of a penalty.
The server is basically just my Windows gaming PC, and the client is my editor on a macOS laptop.
Most of this effort is so that I can prepare for the arrival of that mythical second half of 2026!
[1] https://github.com/ollama/ollama/blob/main/docs/faq.md#how-d...
[2] https://huggingface.co/collections/Qwen/qwen25-coder-66eaa22...
Not useful though, I just like the idea of having so much compressed knowledge on my machine in just 20gb. In fact I disabled all Siri features cause they're dogshit.
Maybe s.th. like a collective that buys the gpu's together and then uses them without leaking data can work.
maybe 128gb of vram becomes the new mid tier model and most llms can fit into this nicely and do everything one wants in an llm
given how fast llms are progressing it wouldn’t surprise me if we reach this point by 2030
I hope I'm wrong though, and we see a large bump soon. Even just 32GB in the mid tier would be huge.
I'm really tempted to try out a Mac Studio with 256+ GB Unified Memory (192 GB VRAM), but it is sadly out of my budget at the moment. I know there is a bandwidth loss, but being able to run huge models and huge contexts locally would be quite nice.
In particular it’s important to get past the whole need-to-self-host thing. Like, I used to be holding out for when this stuff would plateau, but that keeps not happening, and the things we’re starting to be able to build in 2025 now that we have fairly capable models like Claude 4 are super exciting.
If you just want locally runnable commodity “boring technology that just works” stuff, sure, cool, keep waiting. If you’re interested in hacking on interesting new technology (glances at the title of the site) now is an excellent time to do so.
i can understand maybe if you’re spending hours setting it up but to me these are download and go
If they have to enshiffify, I don’t want that baked into my workflow. If they have to raise prices, that changes the local vs remote trade off. If they manage to lower prices, then the cost of running locally will be reduced as well.
I’m also not sure what the LLMs that I’d want to use look like. No real deal-maker applications have shown up so far; if the good application ends up being something like “integrate it into neovim and suggest completions as you type” obviously I won’t want to hit the network for that.
Early days still.
For wage workers, not learning the latest productivity tools will result in job loss. By the time it is expected of your role, if you have not learned already, you won't be given the leniency to catch up on company time. There is no impactful resistance to this through individual protest, only by organizing your peers in industry
I’m big on AI, but vibe coding is such a fuck around and find out situation.
But using AI tools for things like completing simple functions (co-pilot) or asking questions about a codebase can still be huge time savers. I've also had really good success with having AI generate me basic scripts that would have taken 45 minutes of work, but it gets me a working script in 3. It's not the revolution that's been promised, but it definitely makes me faster even though I don't like it
(Aside: Hi Ben! If you are who I think you are, we started at the same company on the same day back in August of 2014.)
Personally I only use Claude/Anthropic and ignore other providers because I understand it the more. It's smart enough, I rarely need the latest greatest.
One way to avoid this: stick with one LLM and bet on the company behind it (meaning, over time, they’ll always have the best offering). I’ve bet on OpenAI. Others can make different conclusions.
Winner gets your attention for a week.