Sure you can open an accountancy business and refuse to use calculators, but that's just working with a strange self-imposed limit rather than using technology to best support your business.
Yes, calculators do that. I'm arguing that "AI" does not let programmers write better code faster. It lets them write worse code faster, or better code slower.
Turns out that really doesn't matter. I think your argument is incredibly weak; the fact that some people don't use these tools effectively doesn't mean that nobody can. Whoever figures this stuff out is going to win, that's just how it works.
That is to say, there will always be a niche for people who refuse to move up the chain of abstraction: they're actually incredibly necessary. However, as low-level foundations improve, the possibilities enabled higher up the chain grow at an exponentially-higher rate, and so that's where most of the work is needed. Career-wise it might be better to avoid AI if that's what you want to do, but as a business I can't see a dogmatic stance against these tools being anything but an own goal.
Except that it does!
For every level of abstraction, you lose something, and abstractions are leaky.
The lower levels of abstraction make you lose the least, and they are also the least leaky. The higher you go, the more you lose, and the more leaky.
What I'm claiming is that these "AI" tools have definitely reached the point where the losses and the leaks are too large to justify. And I'm betting my career on that.
You're not betting anything because the cost for you to change your mind and start working with AI tools is exactly 0. This rhetoric is just marketing. I'm sure you'll find the customers that are right for you, but you can at least admit that this kind of talk is putting the aesthetic preference of what you want work to look like above what's actually the most effective. Again, I'm sure you'll find customers who share those aesthetic preferences, but to pretend like it's actually an engineering concern is marketing gone too far.
Did I ever deny that? Sure, some of those layers are worth it. That doesn't address my assertion that these "AI" tools are not.
> Telling yourself that the layer above you isn't feasible isn't going to do you any favors but it does generate buzz on social media which seems like it's the goal here.
You're halfway there.
> You're not betting anything because the cost for you to change your mind and start working with AI tools is exactly 0.
And here is where you contradict yourself.
If I'm getting loud about this bet, and making customers because of this bet, then it will cost me a lot to start working with "AI" tools. My customers will have come to be because I don't, so if I start, I could easily lose all of them!
> This rhetoric is just marketing.
Yep! But that's what makes my best actually cost something. I'm doing this on purpose.
> I'm sure you'll find the customers that are right for you, but you can at least admit that this kind of talk is putting the aesthetic preference of what you want work to look like above what's actually the most effective.
No, I will not admit that because I believe very strongly that my software will be better, including engineering-wise, than my competitors who use these "AI" tools.
The idea isn't to write better code faster, it's to build better products faster.
Although IMO in the future, AI will probably also enable programmers to write better code too (faster, less bugs, more secure, more frequently refactored etc)
All else being equal, better code means better products.
Also, to have a better product without better code, you're implying that the design of the product is better and that these "AI" tools help with that.
Until they can reason, they cannot help with design.
And I would bet that AI design would help things where the existing designers are bad, e.g. so much open source UI (that is, not cli UX) written by devs, but it is still a bit away from the top quality like Steve Jobs.
Maybe this is like the transition from hand crafted things to machined things; we go from a world some some excellent design and some meh design to a world with more uniform but less great designs.
"AI" design will not help until we have a true AI that can reason. (I don't think we ever will.)
Why is reasoning necessary? Because design is about understanding constraints and working within them while still producing a functional thing. A next-word-predictor will never be able to do that.
What is your definition of reasoning that you do not think GPT-4 would demonstrate signs of?
Heh, there have been many attempts to define reasoning. I haven't seen a good one yet.
However, I'm going to throw my hat into the ring, so be on the lookout for a blog post with that. I've got a draft and a lot of ideas. I'm spending the time to make it good.
Otherwise it’s just moving the goalposts.
To demonstrate this, ask it to prove something that most or all people believe. Say some "intuitive" math thing. Perhaps the fact that factorial grows faster than exponential functions.
And no, don't just have it explain it, have it prove it, as in a full mathematical proof. Give it a minimal set of axioms to start with.
Merriam-Webster's definition of "reasoning" [1] says that reasoning is:
> the drawing of inferences or conclusions through the use of reason
So starting GPT4 off with some axioms would give it a starting point to base its inferences on.
Then, if it does prove it, take away one axiom. Since you started with a minimal set, it should now be impossible for GPT4 to prove that fact, and it should tell you this.
Having GPT4 prove something with as few axioms as possible and also admit that it cannot prove something with too few axioms is a great test for if it is truly reasoning.
Take this problem instead which certainly requires some reasoning to answer:
“Consider a theoretical world where people who are shorter always have bigger feet. Ben is taller than Paul, and Paul is taller than Andrew. Steve is shorter than Andrew. Everyone walks the same number of steps each day. All other things being equal, who would step on the most bugs and why?”
I think it’s a logical error to say “AI can’t reason about this, so that proves that it can’t reason about anything at all” (particularly if that example is something most humans can’t do!). The LLMs reasoning is limited compared to human reasoning right now, although it is still definitely demonstrating reasoning.
Because Ben is the tallest, his feet are the biggest, and because he takes the same amount of steps as the others, the amount of area he steps on is larger than the area that the others step on.
Therefore Ben is most likely to be the one to step on the most bugs.
Easy. And I'm not brilliant.
The problem with testing these tools is that you need to ask it a question that is not in their training sets. Most things have been proven, so if a proof is in its training set, the LLM just regurgitates it.
But I also disagree: if the "AI" can't reason about that, it can't reason because that one is so simple my pre-Kindergarten nieces and nephews can do it.
But even if not, the LLM's should have "knowledge" about exponential functions and factorial because the humans who wrote the material in their training sets did. So it's not a lack of knowledge.
And I claim that most humans could rediscover theorems from basic axioms; you've just never asked them to.
Ben (tallest) Paul Andrew Steve (shortest) Since shorter people have bigger feet in this world, we can also deduce the following order for foot size:
Steve (biggest feet) Andrew Paul Ben (smallest feet) Assuming that everyone walks the same number of steps each day and all other things being equal, the person with the biggest feet would be more likely to step on the most bugs simply because their larger foot size would cover a greater surface area, increasing the likelihood of coming into contact with bugs on the ground.
Therefore, Steve, who is the shortest and has the biggest feet, would step on the most bugs.”
GPT4 solved it correctly. You didn’t.
And GPT4 didn't solve it correctly. It's a probability, not a certainty, that the shortest person will step on more bugs.
At the very least, this should be evidence that the problem wasn't a totally-trivial easy pre-kintergarden level problem though, and it did manage to correctly solve it.
It required understanding new axioms (smaller = bigger feet) and infering that people with bigger feet would crush more bugs without this being mentioned in the challenge.
Your dismissal that the AI messed up because it didn't phrase the correct answer back in the way you liked is a little harsh IMO, as the AI's explanation does make it clear it is basing it on likelihoods ("the person with the biggest feet would be more likely...").
Equally if it can help devs launch a month earlier, that’s a huge advantage in terms of working out early product/market fit.
All things being equal, I would rather have a company with better product/market fit than one with great code (even though both are important!).
That's a very big "if", and one I just don't think will exist.
Also, that only helps at the beginning. Add the product gets more complex, I believe the AI will help less and less until velocity will become slower than companies like mine.
And product/market fit is just a way for companies to cover up the fact that their founders wanted to found a company, not solve a real problem. If you solve a real problem first, founding a company is simple and you "just" have to sell your solution.
You act like encouraging people not to think is a problem. Thing is, you'd be wrong. We want people not just to think, but to focus. If I'm a pilot and I have to worry about the runtime environment of the command-line calculator I use to hand-calculate my route and cockpit configuration, is that a good use of my focus? I think most people would say no. We definitely want to discourage the pilot from actively thinking about that kind of stuff. Should they have a grasp of the basics in case of emergency? Sure. Do we have a sustainable and efficient system of transportation if that's how our pilots spend their time? No.
Aviation is about redundancy. Redundancy is a good use of a pilot's focus. That's why I did both. I didn't blindly trust my calculator to not have bugs (even though I wrote it!), and I didn't blindly trust my hand calculations to be correct.
If they agree, though, it's a good sign that everything is in good order. That's what redundancy is for, to ensure that a problem in one thing does not lead to another problem, like in the Swiss cheese model of accidents.
If you're just trying to get off Gilligan's island, that's another thing entirely.
A commercial pilot friend has told me that they still check the calculations. When they don't, they get accidents like the Gimli Glider.
It's like saying that putting all of the legal checks on the lawyers is not going to give you a sustainable business. But we all know that's wrong.
When I wrote that calculator, I didn't write it for flight. I wrote it as a general calculator and just used it for flight. I would have used the GNU bc if I didn't write my own.
So it's a bit disingenuous to claim that I am claiming that pilots should write their own.
And pilots are included in those maintaining the system; they're not just using it.
Yes, I know calculators can encourage people to not think; I should know because I wrote one. [1]
But the current "AI" tech is so much worse on that front. It's a difference of degree, and that degree does matter.
By the way, when I was learning to fly helicopters [2], I used my calculator to calculate weight and balances, but I also did it by hand!
[1]: https://git.gavinhoward.com/gavin/bc
[2]: https://gavinhoward.com/2022/09/grounded-for-life-losing-the...