skysight-inc/HackerNews huggingface dataset:
"Without her, he would never have succeeded."

A dumb line in an otherwise interesting article.

It may be true that without her he would never have succeeded, but to know that we would need a time travel machine to go and find out. But we know to be impossible to build because of Einstein.
"Should have self healing" can be expanded into "should have systems to address the underlying system failure modes", which starts to shed some light into why distributed systems will always run into failure modes.
There’s Geoff Lawton’s work mentioned. The idea being that referencing a desert being a real test of permaculture:

https://www.greeningthedesertproject.org/about-us/

I think it isn’t a trivial thing to scale, people need skills. Geoff Lawton himself was inspired by the 2000 year old Green valleys in Morocco which alas appear to be threatened:

https://youtu.be/wd-b_C7a_es
Non-Preemptive MultiTasking Unit for Turbo Pascal 4 (1987)
This Time It's Different
You're missing a crucial point - AI learns/is taught by example. So no, future projects will not need to be ultra-specified because the specification will be "Give me one of those [points at thing]."

The equivalent assumption would be that ChatGPT and MidJourney can't work because you have to specify every paragraph and every shape.

Clearly that's not true. Just because every object and every texture had to be defined rigidly by hand in 3ds Max or Blender by highly skilled designers doesn't mean that's how it works today.

In fact AI is the stage of software where abstraction itself is automated. The current Gen 1 AI tools do a little of this, but as Gen 1 they're just getting started.

They're going to be in a very different place ten years from now. And so are we.
The Great Debate (Astronomy)
>Have you ever had to use a sleep() intentionally just to get something shipped ?

no, I'm not that deep in hell
> His prediction was based on the trends he was seeing at the time. But it wasn't even AI. Instead he made this prediction because he saw the rise of no-code tools replacing software developers because managers could finally cut out the pesky "translators", i.e. software developers.

But aren't managers there to coordinate software engineers. So if software engineers are out of a job, so will the managers. Assuming AI replaces software engineering, the ones left may be the product people and the founders, perhaps rolled into one person in several cases?

Which aligns somewhat with what Carmack is suggesting.
Why would dark chocolate be worse than any other chocoloate (apart from concentration). If it's truly worse even per piece of cocoa, is it about the cocoa butter?
Eh, I don't get it. Decode key, please.
We stopped some devs in our project from adding too may TODOs and FIXMEs.

For good reason; the more TODOs and FIXMEs a codebase contains, the less impactfull they are. We had so many TODOs no-one every batted an eye when seeing them, and they never got fixed. It just made you feel bad.

Also a lot of TODO's expressed opinions about the "ideal" scenario, but in practice most of those TODOs were for code that was "fine" or "good enough". In those scenarios it's better to omit the TODO/FIXME keyword and just describe the design decision that was made.
Homer Simpson suggestion: what if we put massive magnets in the production process?
GPT-4 can almost learn games like Tic-Tac-Toe
Recently there has been some debate of GPT-4 can play chess or Tic-Tac-Toe, and if it really understands what it is doing. I am not trying to make any claims but I do wnat to show some evidence that GPT-4 is not just "regurgitating things from the data set".

I described it the rules of a fake version of Tic-Tac-Toe and played against it. It did not do great, but decently, and managed to play me to a draw once. It did not always play optimal moves and and gave the wrong name of winning arrangements when asked. Nevertheless, overall it could play the game.

Interestingly it could also identify that this game is really just Tic-Tac-Toe.

One should really test this on a large scale to get some statistics but that takes a lot of time. I think a very important question is if LLMs can use in-context learning to learn new games and even improve at them. As I understand A. Karpathy for example strongly believes that this is/will be possible and the future of AI.
A domain established to be used as an example of cats on the internet
What's going on here?

* https://news.ycombinator.com/item?id=35217604

* https://news.ycombinator.com/item?id=35217490

* https://news.ycombinator.com/item?id=35158894
They are referring to many worlds interpretations of quantum mechanics that argues that the quantum wave function is as real as anything. As real as say electromagnetic fields. If this is true then the mathematics say that the universe branches or splits at each quantum event.

Here’s a very very good explanation of this:

https://m.youtube.com/watch?v=nOgalPdfHxM
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( / )
\(__)|

http://examplecat.com/cat.txt
I fast regularly. It is pretty well known that our bodies are extremely good at preserving itself during fasting. I would even risk saying that our bodies don't work optimally until we are 2-3 days into a water fast. I feel better and lighter when I am fasting. Having to eat after a week of fasting almost feels like nuisance. Don't get me wrong, it still tastes incredible, but you know that this feeling of lightness is going to be lost with it.

One thing bodies are very good at is preserving stuff when there is little of it, while fasting. Did you know you will be wasting much less muscle if you go on a complete fast than if you do calorie restricted diet? (please don't do calorie restriction)

So this result is interesting but not really surprising to me. I would assume that if our bodies work overtime preserving stuff there is a possibility they will do the same to calcium. After all we are already built to send excess calcium into our bones.
Seconded, and now you say it I'm wondering if the line I quoted might actually be (only) from the series. The book is excellent, but it's not so funny, or with such snappy dialogue (of course, really, of course TV writers have to add that sort of thing).

'[Puts book down, objecting to Charles also occupying himself] I do think you might talk to me - I've had a very exhausting day. Entertain me. Take me out of myself.'
We have technical debt mostly because business guys want it done yesterday with as little people as possible.

I always tell POs that if they want X done until Y day, that is going to result in tech debt.

When they are asking later why Z doesn't work properly or why it takes time, I just remind them of that technical debt they've agreed on.
Clyde: Discord's AI Chatbot
Might just be me, but I think the big difference here is the level of adoption. Everybody with an internet connection can use an LLM. It hits closer to home that way, whereas driving is very dangerous and most people haven't used a self driving car before.
... and companies with privileged access (Microsoft, Midjourney V5, etc.)

There is a waiting list https://openai.com/waitlist/gpt-4-api
Came across this in one of the zines by Julia Evans. Probably the site is hers.
I’ve always thought of The Verge to be an accessible source of new tech, as well as broadening out a bit into more science and culture.
I've had those exact same feelings. Yesterday I used GPT-4 for the first time and it blew my mind. Every time I start to doubt if it's just hype, I go test it, and it blows my mind again. My personal productivity has skyrocketed, so the future seems extremely bright.

I hope we can eliminate all mundane tasks in the world with this. Let's just focus on advancing science, developing new technologies, and addressing all the neglected problems in the world. Let's democratize and open source all these tools and build incredible software for everyone in the world.

I think the curious creative builder -personality will thrive in this new world, because the productivity of an individual is so next level. We'll be able to accomplish huge things with small teams.

I don't even know where to start!
Did you read the paragraph about women? It says there was too much noise in data, they could not measure positive effect of sleep! What conclusions medical professional would derive from that?

Secondly I really do not like the overall tone of the article.
Despite their name, i think TODOs should not be treated like tasks to complete, you should not let them make you feel bad. Instead, they are kind of a shorthand documentation of what's going on in an implementors mind, what extensions did they think of? Where did they feel improvements could be made? When changing or rewriting the code, these thoughts can be considered.
Yeah all this talk about complex systems being written by a language model which has no concept of files, code paths and import systems sounds like a job security to me. I'm a pentester though.
Geoff Lawton’s project is still going

https://www.greeningthedesertproject.org/
The good jobs tend to not have a "product owner".
Depends on the modality of spatial reasoning. I tested it by asking it stroke-by-stroke instructions to write Chinese characters, and it gets something wrong every time and usually in an egregious way.
Ai will still have a hard time understanding the real needs. That is your added value. Understanding clients/your company and their needs. And thinking ahead.
Human programming is easy until you reach the async, concurrent and parallel parts. Then you have to catch lots of exceptions and log the call stack. :)
Horses which are scared of cars and trucks should just learn how to run faster...
Please provide games in pgn format so a proper analysis can be performed. I've seen games from GPT(3.5 and 4) that seem impressive at first glance as well. Once you go through the moves in detail you learn that:

1. It plays a ton of opening theory. So unless you have grandmaster level opening knowledge it will likely get a superior position out of the opening.

2. Once it does, tactical sequences tend to work. It can play a lot of common tactical sequences, sometimes 10 moves long. These sequences can have identical or highly similar algebraic notation in many different positions.

3. This can usually be spotted if you play enough games. Eventually it will attempt a sequence like this when it makes no sense or even includes illegal moves. Or you'll catch it always responding the same way in certain situations. Patterns like this tend to emerge with enough games in every case I've looked at.

I have yet to see a game not explainable by completing common opening theory and tactical sequences.

These claims are pretty unhelpful without detailed analysis of the games by a sufficiently strong player.
AI method for faster and more efficient hash functions
In my experience as the carrier of a developer progresses, it is getting less about coding, and more about other tasks. The difference is probably the strongest between a senior vs principal/staff software engineer. In the places I worked principal/staff engineers are looking after the overall design and architecture, negotiating with teams developing other components, helping management with planning, looking after the progress of other devs especially new joiners, etc, etc. I'd say it's about 15% coding at that level and 85% everything else.
I'm surprised that raw ingredient sourcing wasn't mentioned or maybe it was but I missed it.

To me, reducing your intake doesn't make as much sense as paying for traceability and certification.
"Hi, my name is Werner Brandis. My voice is my passport; verify me."
I think this explains sovereign wealth funds - essentially replacing private sector banks main function of encouraging investment.

As we move inexorably towards digital fiat currency, the role of banks as printers of money will likely vanish - and then the role as "guarntors of investment" - this necessary con trick, will become much harder. if no-one has bank accounts but instead has open wallets where each transaction is tracked on blockchain then there is nowhere to hide the fact that your money has been invested and is not sitting where you think it is

the only (?) solution is to say - yes but if you want it back the government promises to give it back. ?

Oddly Lincoln was a huge proponent of better banking to provide investment in small businesses.
Oh gawd no.

I have predictable functional big buttons and levers to do what I need. The $200 units (let alone cheaper ones) have 2mm buttons and a freaking remote control! Do not get me started on modern car UI :-)))
I think this is way too simplistic.

First, LLMs seem to be still on a trajectory of more parameters is better. So the convergence is a man-made decision to stop for the sake of memory usage and money spend on training.

I don't think there is anything inherent in LLMs which prohibit adjusting weights over time or branch out to another model which is more regularly updated and contains novel stuff. I would well imagine that they integrate a "news model" which is trained every 24h to incorporate text scraped from news-sites. This can be called from the main LLM.

If we look at the human brain we realize that there are dedicated systems for specialized processing (think spatial reasoning vs judging colors). I would imagine that OpenAI would eventually to have a similar more complex system structure.
In case of Google it is. Haven't looked at others. Mozilla is dependent on Google money, Safari irrelevant.
You're assuming that the AI is even generating anything that will make sense to a human. It seems inevitable we'll reach the point that for SaaS the AI will do everything directly based some internal model it has of what it believes the requirements are (e.g. it will be capable of acting just like a live web server), whereas for desktop and mobile apps, while that paradigm still remains relevant, it will generate the compiled package for distribution. And I imagine it would be unrealistic to attempt reverse engineering it. Fixing bugs will be done by telling the AI to refine its model.
My hot take on AI code generation, which matches my understanding of how all of these GPTx models work: if you don't understand the output, you are far worse off using it than not.

At the moment, it works as a pretty powerful suggestion engine. It might suggest the wrong API to call, not handle the edge cases correctly etc. If you assume it does, or don't understand when it doesn't, you're in for a world of hurt.
A digital parrot, no matter how lifelike its utterances, cannot be genuinely creative. Writers of boilerplate and empty drivel will probably be replaced by language models, but not every software developer is like that.
I got a 2:1 from Imperial, guess what I think is on par with top 5% at Harvard ;)

I'm only kidding, but more seriously it's certainly not all equal, and few are really in a position to compare any two, nevermind several - it's a bit of a joke that we then make 'a 2:1 in an engineering or related subject' or 'at least 3.5 GPA' or whatever a requirement as though the institution and cohort doesn't make a difference at all.
Altair 8800 – Loading 4K BASIC with a Teletype (2013)
Modern cars all seem to have integrated units. Even before but LCDs were the norm, so that's not a sole excuse :-/

(fyi it is my 2004 wrx that has a double din cd changer. I go car shopping every year or two, and I stick with my trusty Scooby every time :)
There's no reason this couldn't happen, but surely it would require something better than LLM.
I have to say this is a pretty shitty RSS reader but is pretty impressive to be written by a robot.

Some thoughts on first reading.

- Only supports the RSS format.

- Crashes if some properties are not available.

- Dark mode toggle is never actually read. Instead the internal value is just changed on every click. Mostly poor coding style.

- It used textContent so no HTML injection! Although it just avoided showing the entry content at all. Which would require safely rendering untrusted HTML.
It's from 500 years ago, but it's also from 50 years ago and from 5 years ago; that is, it's continuous and has not really had a specific occasion to change. Although the fur is usually no longer real.

Oxbridge are not called "the dreaming spires" for nothing; there's a timelessness to the place that all the antique surroundings and rituals accentuate. The 20th century has largely got rid of formalwear as an important concept, but (at least while I was there) the gown wasn't just for graduation, it was for formal dinners, which would be held on various occasions or up to several times a week in the larger colleges for the sake of having a nice dinner.
Don't forget the ability to finetune the LLM.
I love these projects.

But i find they do not often communicate of the fragility of the endeavor or outcome. Human society is like a ablative sandstorm that wither the outcome down to zero in the long run. Same goes for wildlife parks. One economic downturn and donations drying up and poachers.
One drought and the nomadic tribes drive there cattle/goat into newly planted, already struggling green.
The project leading person dies and the whole tribe/idea vanishes, the very structure ground to the traditional society, which is basically embracing ecological catastrophe to spread the individuals genes.

My longterm hope for ecological preservation is actually on genetic engineering.

Make treewood give off a awful smell, so its lumber and fireworth goes to zero.
Make it grow strands of kevlar that blunt saws.
Make bushes grow leaves that are poisonous for goats.
Pre spread the bananna fungi, to make burning it down for plantations unviable.
Make djungle-mosquitos reservoirs for bovine diseases.
To touch a nature preserve must be something similar to wishing for death.

Its horrific, but the only way.
I know absolutely nothing about Zig (but I know C) and when I read "FixedBufferAllocator" I immediately guessed what the problem would be. I can see why it is claimed as a C replacement.

I am actually kind of surprised the author spent so much time figuring it out. The name of the allocator is not that well-defined, but at least to me it hints of it being simpler rather than full-featured allocator. I would also imagine he's using this in a very anti-patternic way. One would guess the point of this would be to destroy the entire allocator on every iteration, rather than trying to free everything 'nicely' which would be a lot of wasted work. This is a rather common pattern in a lot of "high-level" embedded development like this.
Running the First Program
idk about that

I mean, all of that is grand but you remain for, for from the metal in all these instances and even in assembly you cannot go under several layers of abstraction with modern architectures

in the days of 6502 and Z80 compatible microprocessors, you could go down to the NAND gate level, to the transistor level - it was doable, not that it made much sense to go there for most people, but it was nearly a requirement to know how many cycles did each instruction take and lock conditions like bus access when dealing with different parts of the memory, etc

there were essentially no hard black boxes then, and now there are many at the hardware level and even the OS level is too impenetrable; not even the CTOs of major OS companies and initiatives have a complete understanding of the OS they produce, perhaps a few select ones have a functional understanding with only 2 or 3 black boxes involved (specific driver magic, hardware detail that goes under C and assembly optimisation etc - which typically outsourced specialists deal with)

GPUs alone these days are more complex than the entirety of the systems back then, and the implications of this are two-fold:

- the culture on the producer end is that software, machines and accessories are sold as black boxes, both by expectations and by enforcement on the manufacturer's end that gets no incentive whatsoever to expose internals of their product, and many reasons to the contrary as the competition might use it; these dynamics are extending to repair-ability as well

- the culture on the consumer end is that internals are not possible to deal with, are best taken for granted and the curiosity is just not there anymore; also if things break you just get new things, which disincentives also producing anything meant to last, as the assumption is that it will be obsolete soon anyway, or the system will just stop working, reinforcing that dynamic and cheapening the value of work
Since your comment seems to be strongly contradicting the blog post, it might be worth checking whether you are really testing the same thing.

The blog post is about playing chess against GPT-4. GPT-4 (or at least, a version without image input capability) is available at https://chat.openai.com/, but only to "Plus subscribers" who pay for it.

So did you test with GPT-4, or did you test the "default GPT-3.5" model which is available for free?
Yes that’s correct ! Oops
You can deserialize the JSONs and filter the resulting arrays or lists. For C# the IDE can automatically generate the classes from JSON and I think there are tools for other languages to generate data structures from JSON.
Well, it pretended to have won but failed to see the 3 X he placed were actually not vertical :-(

https://pastebin.com/LXLhXZjf
I wrote down a small usage example here: https://savannah.gnu.org/forum/forum.php?forum_id=9197

No need for massive distributed clusters when you have a simple perl oneliner
We tend to overestimate the impact of technological change in the near future, and underestimate it on the more distant future.
But they've been doing it for some 15 years, right? With those types of success, I'd expect the map to look like those virus-spreading maps where it starts somewhere and then expands to all directions at exponential speed.

That it doesn't hints at there being some issue. Do you need to tend to each plant constantly with someone who has learned some special skills and that doesn't allow for scaling?

The advantage to having trees instead of desert seems so obvious, I can't see why everyone isn't jumping on it, unless there's some not-talked-about problem that limits these projects to touristy projects and YT filming locations. And with the amount of money that's going around for environmental projects in the developing world, I can't imagine that it's about lack of funding.
I can’t speak for the person you replied to, but I work for a software company that is always on the lookout for mechanical engineers who can write code. It’s a pretty rare combination.
> Are we sure that an AI could not engage in enough back and forth conversation to firm up the spec?

This is the doomsday argument. What would I do if there's a nuclear apocalypse before lunch? I guess I'll die like everyone else.

An AI sufficiently advanced to do that is also sufficiently advanced to run the entire business in the first place, and also argue cases in court, do my taxes, run for president and so on.

You either believe that transformers models are "it", or you haven't actually removed the problem of specifying requirements formally. Which, you know, is actually much harder to do in English than it is to do in C++.
Not to "replace programmers", though. For the same reason you can't replace drivers even though they also make mistakes.
The US response to terrorism was directed overseas, while the UK one has for a longer time been directed at "enemies within". The UK press is entirely behind all these restrictions, sadly.