I have a hard time understanding this.

We have plenty of adults with terrible social media addiction that is destroying their lives, and nothing being done about it.

For example, for the US to have a chance in the EU, it would first need to fix its YOLO fiscal policy of sustained 5.5% debt/gdp deficits.

We shall see in a few years as US's debt balloons and the average American becomes pseudo-slaves from a few overlords... to see if the EU is really bad as some Americans believe it to be.

I love working with AI and agents.

But I don't know how long this will go, so I'm investing on getting fit again for random jobs like moving atoms.

Or realizing my life's dream: become a lifeguard in public swimming pool or learn the trades to maintain swimming pools. There's a shortage of them where I live and it's enough money to pay for food etc.

I love swimming and watch people happy enjoying the water, it's such good vibes I'd do this forever.

Our life is mostly suffering and grinding through... but people on swimming pools are always smiling, having a good time & having the basic pleasures of enjoying the water and the moment.

Blizzcon canceled. All of its IP barely got any love.

See what players think about the latest World of Warcraft patch. It's absolutely shit and broken. People say they fired the entire QA department since a few years back and since then the quality has just gone down.

They buy those businesses because they have nothing to do with that free cash flow, and for accounting reasons it makes sense to have them.

They didn't buy those businesses to develop it further and make it worth more.

Github will just become ever more irrelevant.

The key issue is that the US governments let those huge monopolies exist, and then use their money to buy other businesses and enshiftify them.

Unless that changes in the US, this will continue happening.

LLMs for language feels like it's definitely the way to go. I feel like that by just improving it further can definitely reach perfection, if not very close.

My concern is mostly all adjacent fields, like systems thinking, spatial reasoning, "real" human-like reasoning etc or as you put it, "AGI".

Doesn't seen this will take us there at all. I don't feel like we're closer to AGI than we were on the earliest versions of ChatGPT.

MoE: I assume some people just specialize in working with routing as with that, as by reducing the amount of params and just using a subset, you end up making it less costly. So, AI researchers are only working on optimizations on getting this better?

Same question on Reasoning, so AI researchers are working mostly on optimizations on top of it, like CoT and so on, like mini-optimizations.

So basically, they work on those micro-optimizations, put them together and see a % improvement in a benchmark?

I'm sure this is probably awesome for languages, which if I'm not mistaken, it was the use-case initially used on "All you need is attention" and the entire LLM revolution.

But this seems to be a very clear path to be "taking the car to the carwash by foot" for a long time, isn't it?

It feels like we'll keep "taking the car to the carwash by foot" until somebody optimizes for that prompt, or some pre-training done, and then there'll be another prompt that will show that the AI has real trouble with very basic real-world reasoning and imagination.

Isn't it the case, or do you see any kind of research that could take us from that plateau full of micro-optimizations that get us a few cm higher to the peak?

No shop will want to have the expectations to successfully fix a complex GPU, unless it's their main business, as the solution can potentially not be 'reballing the memory modules' and they might just break your GPU in the process, they don't wanna have to pay you back in case they do, otherwise the risk they are undertaking isn't worth the chance of they fixing it and getting your X euros.

Go to hardware communities and ask them if they'd like to have a go at it, find somebody reputable and go with them.

Otherwise based on what you said, you literally will have to trash it, or find a way to constantly cool it down in a very reliable way (Good luck! I tried the same with a CPU with an overheating issue and failed miserably. Hopefully you'll manage it)

A lot of them have burned out and were/are unemployed. Great engineers and all.

The ones that are employed, are grinding like there's no Tomorrow.

This changed a lot from 10 years ago, when it was much more relaxing to work with software.

When using Opus or Codex vs. a chinese or Open source model, it feels like its reasoning capabilities are basically the same.

The difference is typically in coding. It looks like OpenAI and Anthropic invest a lot in pre-training (paying Mercor and the like).

Also a lot in creating synthetic data, I believe this has bigger AI research involvement and techniques.

Of course, there's the RLHF loop that developers using Anthropic/OpenAI products as well, which provides probably yields very good data.

This ends up creating the perspective that it is smart, after all, it has been trained with what you want to do, so it can do that for you.

But overall, is there really much AI research being done on those companies, or are the AI researchers mostly fine-tuning small aspects of the model, akin to what Google engineers used to do for Google search?

I ask this because this all looks like somebody with money could throw money at the problem and end up with a better model at the end, provided they do what I outlined above better -- with AI research being really not that important.

It still often feels like talking with ChatGPT 4 with just better data.

Even the big upgrade of Claude Code being able to work autonomously looks to be mainly due to it knowing how to grab context and do tool calls (not saying that this is easy), rather than the model's raw performance being better.

Or am I wrong, is there something extremely good on those models that AI researchers discovered that the others don't have? Or is it really mostly Data?

Comments URL: https://news.ycombinator.com/item?id=47872916

Points: 3

# Comments: 4

https://nerv.app/en/

This kind of data is actually shared by governments with each other as well.

Science has no borders, much less disasters.

I share a similar sentiment about Germany. I mean, we do have a recession for a couple of years already.

As a Software Developer, I've experienced layoffs of International companies just nuking their German team, for both cost and law risks (from people trying to create a worker council and the like).

I'm still employed because of my YOE, my skills & a wide network of people that have seen the quality of my work, but I see even previous CTOs and great engineers without a job.

Maybe in the years ahead, I might need to work doing something else.

I've always wanted to go to trade school and run my own business anyways, just didn't due to software engineering being so fun, interesting, challenging and ofc, well-paid.

I've been practicing my German a lot (C1+), so in worst case scenario I can do other work, maybe become an electrician or something that involves moving atoms, rather than bits.

Why not do it with the leaves? This is harder as their taste profile is very uneven.

For the sour taste, add citric acid.

I'm pretty sure that if you toy around with the amount of citric acid, sugar & dillution you'll get a similar taste, or something even more palatable for you.

I guess a big part of this is figuring out how to make money doing that. I wonder how did you get there.

I've always had the desire to make soft drinks and I have a similar concern about how we are sitting the entire day...

Hey Americans,

Please just make sure when you let an AI decide to explode your own country and ruin your society, you leave the rest of the world intact, thanks

You can always pay for Anthropic models through the API usage. That still works... but I wonder if anybody will want to pay that much.

You'd probably go with a different model or API provider if you have to pay those costs yourself.

Everybody that plays guitar have tried to transcribe a riff or a song. But not all have become great guitar players.

The way to go is to have an objective. Is it playing a difficult song like Cliffs of Dover? Playing blues? Rock? What is it? Focus on that style or song. COPY. Become a copy machine.

One example is doing bends. There are many ways of doing a bend. Most if not all blue players do it by holding the neck of the guitar in a very specific manner, so if you want to play blues, you need to copy them. It must be a perfect copy.

Playing the guitar is mostly a physical activity where motions and understanding of the body, and how this is wired into your nerves and brain matters.

If you just transcribe and play riffs, you won't be able to play in a high BPM, because in order to do that, you need to be extremely efficient with your movements, understand speed picking... and people have studied and developed those techniques for many years -- you don't invent this over, you watch videos, practice and copy it!

By just playing and transcribing you'll develop terrible habits which at some point will limit your playing, and will feel like it will take an eternity to correct. That's when most of the people stop playing.

And of course, play songs that are at your level, so typically lower speed songs with simpler chords and then from there understand what music style you want to focus on.

A guitar teacher can help you with that because they can easily come up with exercises and songs that would match your skill, but if you want, you can do that yourself.

Once you become advanced in guitar, then you'll for sure know it, and then you can experiment to do bends in a different way, or do something that would make you stand out, but at first, it's mostly about copying. Later you can innovate.

TLDR: best way of learning guitar is focusing on copying everything, the motions of a player being the #1.

But if you compare to other companies with similar rev/profit numbers, you'll be amazed with how cheap they are.

I don't believe Oracle has a wide moat other than its DB -- the Datacenters are mostly commodity.

We still have to see what Anthropic has cooked though

It's a good opportunity for people to try kimi and others, and now that soon we will have an agentic harness similar to Claude Code as its getting rewritten to Rust... I guess let's look elsewhere?

My guess is that Anthropic is focusing on enterprise as it gets ready for an IPO, leaving behind solo devs.

I find it very unlikely for this to change, unless they get even more datacenters and capacity to address how much demand they've got recently.