kamaal

>For non coding related tasks I use local models.

What sort of hardware are you using to run local models? And how do you use them?

>Deepseek will be sanctioned and therefore no provider will offer it anymore.

That is possible inside the US. How do you do it all over the world? You have to convince every country in the world not use frontier models? Even worse how do you convince all the countries to not build their own models?

The question is what work do you do, that burns so many tokens.

Are in you sending it to work in nested for loops? If yes, what sort of work would that be?

>So how these companies and people manage to use these absurd amount of tokens is a mystery to me.

Absolutely!

I know some colleagues who are routinely spending thousands of dollars worth of tokens, I can't see to even max out the subscription limits even if Im working all the time. Curiously enough their output is lower too.

>My impression is that the saying "Perl makes easy things easy and hard things possible" really does hold up.

People who haven't used Perl to its full power have little how idea just how magical a language it was/is.

Have seen people's jaws on the floor watch Perl guys do automation they always thought was impossible, even more so delivered in such record times. CPAN itself as an idea was way ahead of its time.

Around COVID I had a project delivered, in a week. I basically wrote a Perl script that wrote Apache Pig scripts(Basically using Perl like a macro facility, and Perl is great at anything text). It was a massive project which otherwise would have taken more than a year to deliver. When I did show the team what I had done, had them in total awe in the same way people look at Claude Code today. Nevertheless it was the same reaction, when the project got done, they were not comfortable that some programmers could do stuff like this, which seemed alien to the remaining.

I have a belief that proliferation of Java/Python stunted the growth of web dev, and a lot other industries. In some way the last decade was entirely slowed down by adoption of these technologies. If Ruby/Perl were there things would have been way better.

I do love what LLMs are doing to Java and Python today.

Software development was never supposed to be as slow as what Python and Java made it.

Have literally seen a 'architect astronaut' crap on Perl in some 2 hour long call, and eventually had his way with getting the management to approve Java. This was mid-2000s

When our team initially budgeted it, 4 guys over 6 months were enough to get this over the finishing line. The java team took over took more than 3 years, and close to 30 people. It was a AbstractClassFactoryFactorySingletonDispatcher mess with spring decorators all over. Which quite honestly was quite ironic because the original case against Perl was it was hard to read.

The java code was easily 30x more verbose, no body at the end knew how to maintain it. It was all about the guy getting to own his own team, promotions, bonuses, raises etc.

Have seen the same story repeat over and over again, everyone knew they wanted Python because they could get to inflate their headcounts.

Its one of things about tech, its not the good tech that wins, its the tech that helps with office politics wins at the end of they day.

After golang came along a lot of these java things too went out of fashion. Curiously enough golang does feel a lot perly to use. And Python has long moved away from its minimalism activism days. To that Python has transformed into the same feature bloat it once accused Perl of.

>Turns out that Larry (and the team) were much better at language design than project management.

It is true many times to deliver quality products you can't have deadlines. But without a deadline you are never finishing a thing.

Unfortunately for Perl, Larry Wall, and several of its project leads(Patrick Michaud, Audrey Tang) at various times had major health issues. Time moves on, and people have to at times resign entirely from projects due to shifting priorities and personal problems. Parrot VM I guess went through a similar arc.

Other people have moved mountains to get Perl going. But with time people's priorities have entirely moved on. At one time, all Python programmers would do is bad mouth Perl all over the internet, and that never really stopped. Any body who saw a Perl programmer do over a weekend, what they would take a year to do in their language(especially Java and Python)- had a deep rooted seething envy at Perl and Perl programmers. So they went around almost on religious crusade to have Perl gone. This was done entirely to crush competition. They just didn't want other people to wield a power they didn't have. Lisp has had a similar arc of development over the decades.

Perl 5 development being entirely stopped for years further complicated this issue. Eventually as most of the Perl code in many companies bit rotted and died, newer projects were started in Python/Java. And of course Frontend stack entirely moved away to Node/React. We had mobile development of which Perl never was ever a part of.

By the time ML/AI era came into being Python was defacto the language of programming for these kind of tasks.

The best part is now in the LLM era, the whole idea of a programming language itself is pointless.

>We used to romanticize stories of people born into lower socioeconomic conditions (say in the third world) and rising out of it through their intellect.

Many people think the social mobility came through intellectual feats, but when you look at it carefully, it came through agency and ownership.

Talking to toxic people.

Its so exhausting walking on eggshells, and engineering discussions to avoid conflicts.

There is more than that, though. Deadlines, Next Tasks, Weekly list purge/build, Yearly alignment etc etc.

Also how you teach somebody a thing matters.

Stories have a profound effect on humans since the earliest of our days.

Its not marginal improvement.

Validated data coming out of LLM(Itself generated from a recursive/loop process, used to incrementally arrive at solutions) being using to improve the very LLM is a very powerful loop. And there is no real upper limit to this, at least not in the near future.

Like most exponential processes, the start is slow, but it gets fast very rapidly.

This is also what Anthropic has said, the ones training these models today(i.e 2025 - 2027) will be impossible to catch up with, let alone beat.

So we are at a kind of runaway AI already today.

>Intuitively, it seems to me that there must necessarily be some kind of upper limit

I mentioned this in other thread(https://news.ycombinator.com/item?id=48514481), we are at runaway intelligence already.

Mostly because we are looping AI to fix problems, and then the same data is used to improve AI. There is no upper limit to this.

Taken to its logical conclusion, this process needs a hardware scale that might even look laughably huge at this point. Its fairly obvious space is going to play a big role in the coming times.

I could be wrong, and I humbly accept it when Im proven wrong. But it does feel like a lot of people in top places know we are going to need all the energy and resources space has to offer to run this runaway intelligence.

This.

The real profits will eventually come from selling a McMansion on Elysium.

Agency is just to keep moving, like stop at nothing and keep moving, no matter what. Movement generates information, that can be used to make further decisions, even if you actually don't hit your goal at bulls eye accuracy you do end up getting a lot far and learn a lot.

So we are kind of there at runaway intelligence today.

>We just don't know what the maximum capability of AI is

For all theory purposes there is no limit. Thats what the latest loop engineering trend is about, you are asking AI to find solutions to a problem going by listing steps, and if solution not found in those steps, to treat each step as a separate problem and repeat the process until the master solution to the master problem is found.

Once a solution is found, or new data/insights are generated through this process, the LLM can be trained on this. So in theory you can just keep going like this forever.

Secondly. This is as close to agency you can build inside a machine.

Practically speaking, hardware is a limit. But that can scale up with time.

So we are already looking at some kind of runaway intelligence even if not sentient.

>We don’t really need to bother using GPL/Apache licensed software because we can one-shot something of our own and not bother with giving back contributions.

Thinking of a open weight/source AI as gcc/perl was in the 1990s is more helpful line of approach to take here.

The tool used to achieve a thing must be open.

Yes,

You have to start some where. Im guessing, making progress also brings in new ideas how to move further.

The heuristic is this-

Given a problem P-

1. Provide a list(S) of solutions(S1, S2 ... SN) ordered in the most efficient(For some definition of efficiency) implementation means possible.

2. Execute S1, ... SN.

3. If P is fixed by a solution in the list, halt.

4. Else for each S1 ... SN , execute steps 1 through 4 until, all dependencies and sub problems are resolved to eventually solve P.

This obviously needs lots of tokens, which is all the more reason why we need AI to run locally on our machines.

Its the closest terminology we have to describe that process.

https://github.com/cobusgreyling/loop-engineering

Its hard to come up with new names for novel processes, you mostly reuse what is close enough and well known.

>AI is just hillclimbing today

That's what the Fable harness felt like. You give it a goal and it could try to get there through the shortest path given the tree of possibilities to get there. Iteratively, or recursively.

Perhaps if we make a open coding AI, the design must be along these lines. Something that's easy to train, and serve from local machines. Albeit has loop / recursive hill climbing facilities built it. That way the model gradually keeps moving towards the solutions, in iterations/recursions.

Once this is done, other multi modal things could be pursued.

>I'm not sure how we solve this, other than having management come from engineering.

Given the whole point of management is to work to ensure their own survival and growth, it would in their interest to kill genuine competition when its coming up.

Who wants to raise their new competition and lose to them, no one!

Agency is the last human bastion so far as Im concerned, the day AI has a degree of agency or agents/models in general start to drift towards that direction its genuinely over for masses.

You would still have a job to shepherd AI and get the work done, so as long as it didn't have agency. A proactive, self aware(to a degree), especially aware about its agency can be a killer when it comes AI going on and doing things on its own.

There is nothing it won't explore and nothing it won't do. It will be curious to see where things go from here.

As a Indian I envy you.

My whole life has been a struggle for living in places where there could be fewer humans.

>I thought that having this knowledge would set me apart

The whole leetcode movement was designed to sell this idea that knowing a solution that can be looked up in a matter of minutes on the internet some how puts you astronomically ahead of those who don't. Strangely enough go look at that site itself and thousands submit working solutions to those problems.

Knowing a solution discovered by somebody the first time, is no test of capacity or ability to get work done. It would probably matter if you discovered solution to a novel problem by yourself. How does knowing the end result of a long process by other people decide your ability to do anything at all?

During interviews I have seen companies go to absurd lengths to justify these tests. Including asking candidates to imagine they might not have internet and might need to know these solutions.

The only skill that really matters in our line of work is today most popularly known as high agency lifestyle. And delivery skills largely depend on ownership. In my decades of experience with software work, not knowing a thing isn't even a correlating factor in getting things done.

Real question is, are you a 100x prompter?

>Why would we want to sever this last thread of human control?

Trust me a fair bit of boomers and the generation before lost jobs to computer automation in the 1990s through the 2000s. And they used pretty much the same justification, every bit of work, take for example designing something like a machine spare that was earlier done through painstaking process of bringing the thing to life from the meticulous work on the drafting board till machining was now in the domain of computers.

In India alone, banking jobs were considered those commanding tremendous prestige and income potential, got automated through computers. Tax consultants, accountants, postal services etc etc. The list is endless.

AI is some what like that for us in this generation.

>Similarly, the output of programming is not only a program, but also a programmer. It is you.

This can be said about pretty much any job on earth.

By that definition nothing should ever be automated.

Everything thinks they are special, actually no one is. You become special by being rare. Find something that can be done by no one or only a scant few.

Fear works only if delivered occasionally in byte sized quantities, too much of it and people not only stop fearing, they will also likely be indifferent to it, worse case even out right rebel.

If you had a weapon which is powerful, you better use it sparingly. Fear of the weapon is more important than the weapon itself.

Bought a bed last month, the carpenter delivered it and took photographs of it(with his phone) at our home. Next thing I see is he used Gemini to make the bed sit in various(fictional) rooms and interior design contexts. Like in a WhatsApp status with a number at the footer to call if people wanted a similar bed made.

What impressed me is just how realistic and beautiful it looked.

This is in India, the carpenter is barely literate in English.

You will be surprised just how many people use it these days.

Im guessing a fair bit what could have been described as a designers job is now being done by AI by anyone who has a phone.

>It's obvious that AI can't "fix your problems," but just writing stuff down can help us process.

Nobody can fix your problems, but having some one to talk to who listens without judgement and advices accordingly with empathy matters.

Thats what this is about.

Having said this, AI can write out helpful mini booklets on stressful situations in which humans have to work with each other.