It lacks the ability to self correct and do all the adjacent tasks like client comms etc. So if I come back to it in the afternoon I may have wasted a day in business terms, because I will need to try again tomorrow. What do I tell the client, sorry the LLM failed the simple task so we will have to try again tomorrow? Worse, lie and say sorry this 2 hour task could not be achieved by our developers today. Either way we look incompetent (because realistically, we were not competent, relying on a tool that fails frequently)

Problem with this analogy is that software development != revenue. The developers and IT are a cost center. So yea in a huge org one of the goals is to reduce costs (admin) spent on supporting a cost center.

Doctors generate revenue directly and it can all be traced, so even an extra 20 minutes out of their day doing admin stuff instead of one more patient or procedure is easily noticeable, and affects revenue directly.

I feel like that's how you get Microsoft where each division has a gun pointed at the other division

Doesn't really matter the type of doctor, spending all their time on revenue-generating activities would seem to be better than only 75% generating revenue and 25% on "administrative and bureaucratic tasks" that don't generate revenue and which could be accomplished by a much lower-paid employee ("secretaries and assistants").

Perhaps you're correct that the doctors are simply working much longer hours but that's one group of employees among a hospital's staff who do generally have a lot of power and aren't too easy to make extraordinary demands of.

>When was the last time you looked at the machine code your compiler was giving you?

You could rephrase that as “when was the last time your compiler didn’t work as expected?”. Never in my whole career in my case. Can we expect that level of reliability?

I’m not making the argument of “the LLM is not good enough”. that would brings us back to the boring dissuasion of “maybe it will be”.

The thing is that human langauge is ambiguous and subject to interpretation, so I think we will have occasionally wrong output even with perfect LLMs. That makes black box behavior dangerous.

I disagree. There are personal decisions to make:

Do you bet on keeping your technical skills sharpened, or stop and focus on product work and AI usage?

Do you work for companies that go full AI or try to find one that stays “manual”?

What advice do you offer as a technical lead when asked?

Leadership ignoring technical advice is nothing new, but there is still value in figuring out those questions.

I mean, I'm just some guy, but in my mind:

- They are not making progress, currently. The elephant-in-the-room problem of hallucinations is exactly the same or, as I said above, worse as it was 3 years ago

- It's clearly possible to solve this, since we humans exist and our brains don't have this problem

There's then two possible paths: Either the hallucinations are fundamental to the current architecture of LLMs, and there's some other aspect about the human brains configuration that they've yet to replicate. Or the hallucinations will go away with better and more training.

The latter seems to be the bet everyone is making, that's why there's all these data centers being built right? So, either larger training will solve the problem, and there's enough training data, silica molecules and electricity on earth to perform that "scale" of training.

There's 86B neurons in the human brain. Each one is a stand-alone living organism, like a biological microcontroller. It has constantly-mutating state, memory: short term through RNA and protein presence or lack thereof, long term through chromatin formation, enabling and disabling it's own DNA over time, in theory also permanent through DNA rewriting via TEs. Each one has a vast array of input modes - direct electrical stimulation, chemical signalling through a wide array of signaling molecules and electrical field effects from adjacent cells.

Meanwhile, GPT-4 has 1.1T floats. No billions of interacting microcontrollers, just static floating points describing a network topology.

The complexity of the neural networks that run our minds is spectacularly higher than the simulated neural networks we're training on silicon.

That's my personal bet. I think the 88B interconnected stateful microcontrollers is so much more capable than the 1T static floating points, and the 1T static floating points is already nearly impossibly expensive to run. So I'm bearish, but of course, I don't actually know. We will see. For now all I can conclude is the frontier model developers lie incessantly in every press release, just like their LLMs.

Who does typical code sweat shops churning out one smallish app at a time and quickly moving on? Certainly not your typical company-hired permanent dev, they (us) drown in tons of complex legacy code that keeps working for past 10-20 years and company sees no reason to throw it away.

Those folks that do churn out such apps, for them its great & horrible long term. For folks like me development is maybe 10% of my work, and by far the best part - creative, problem-solving, stimulating, actually learning myself. Why would I want to mildly optimize that 10% and loose all the good stuff, while speed wouldn't visibly even improve?

To really improve speed in bigger orgs, the change would have to happen in processes, office politics, management priorities and so on. No help of llms there, if anything trend-chasing managers just introduce more chaos with negative consequences.

> Sure, if you're content to stack shelves.

Why this example? One of the things automation has done is reduce and replace stevedores, the shipping equivalent of stacking shelves.

Amazon warehouses are heavily automated, almost self-stacking-shelves. At least, according to the various videos I see, I've not actually worked there myself. Yet. There's time.

> AI isn't automation. It's thinking. It automates the brain out of human jobs. You can still get a job that requires a body. My job doesn't require a body, so I'm screwed. If you're say, a surgeon or a plumber, you're in a better place.

Right up until the AI is good enough to control the robot that can do that job. Which may or may not be humanoid. (Plus side: look how long it's taking for self-driving cars, how often people think a personal anecdote of "works for me" is a valid response to "doesn't work for me").

Even before the AI gets that good, a nice boring remote-control android doing whatever manual labour could outsource the "controller" position to a human anywhere on the planet. Mental image: all the unemployed Americans protesting outside Tesla's factories when they realise the Optimus robots within are controlled remotely from people in 3rd world countries getting paid $5/day.

Yes, AI is automation. It automates the implementation. It doesn't (yet?) automate the hard parts around figuring out what work needs to be done and how to do it.

The sad thing is that for many software devs, the implementation is the fun bit.

Except it isn't thinking. It is applying a model of statistical likelihood. The real issue is that it's been sold as thinking, and laypeople believe that it's thinking, so it is very likely that jobs will be eliminated before it's feasible to replace them.

People that actually care about the quality of their output are a dying breed, and that death is being accelerated by this machine that produces somewhat plausible-looking output, because we're optimizing around "plausible-looking" and not "correct"

Honestly, this comment sounds like someone dismissing the internet in 1992 when the web was all text-based and CompuServe was leading-edge. No "revelatory tech" just yet, but it was right around the corner.

In the backend, not directly customer facing. Coca cola is two years in running ai ads. Lovable is cash positive, and many of the builder there are too. A few creators are earning a living with suno songs. Not millions mind but they can live off their ai works.

If you dont see it happening around you, you're just not looking.

Apparently human chess grandmasters also need “oversight” from airplanes, because without those, essentially none of them would show up at elite tournaments.

I try to be optimistic as well. But obviously horses are almost exclusively a hobby today. The work horse is gone. I think the problem is political to a part, if we manage to spread the wealth AI can create we are fine. If we let it concentrate power even more it looks very grim.

B2C businesses need consumers. If AIs take all the jobs, then most of the population-minus the small minority who are independently wealthy and can live off their investments-go broke, and can’t afford to buy anything any more. Then all the B2C businesses go broke. Then all the B2B businesses lose all their B2C business customers and go broke. Then the stock market crashes and the independently wealthy lose all their investments and go broke. Then nobody can afford to pay the AI power bills any more, so the AIs get turned off.

And that’s why across-the-board AI-induced job losses aren’t going to happen-nobody wants the economic house of cards to collapse. Corporate leaders aren’t stupid enough to blow everything up because they don’t want to be blown up in the process. And if they actually are stupid enough, politicians will intervene with human protectionism measures like regulations mandating humans in the loop of major business processes.

The horse comparison ultimately doesn’t work because horses don’t vote.

I am somewhat confident that horses are going to replace cars and tractors pretty soon, possibly within my lifetime and quite likely with my son's.

He's going to learn how to drive (and repair) a tractor but he's also going to learn how to ride a horse.

In the case of horses and cars, you need the same number of people to drive both (exactly one per vehicle). In the case of AI and automation, the entire economic bet is that agents will be able to replace X humans with Y humans. Ideally for employers Y=0, but they'll settle for Y<<X.

People seem to think this discussion is a binary where either agents replace everybody or they don't. It's not that simple. In aggregate, what's more likely to happen (if the promises of AI companies hold good) is large scale job losses and the remaining employees becoming the accountability sinks to bear the blame when the agent makes a mistake. AI doesn't have to replace everybody to cause widespread misery.

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That feels optimistic. This kind of naive free market ideology seems to rarely manifest in lower prices.

Sorry if this is somewhat pedantic, but I believe that only US companies (and possibly only Delaware corporations?) are bound by the requirement to maximize shareholder value and then only by case law rather than statue. Other jurisdictions allow the directors more discretion, or place more weight on the company's constitution/charter.

That’s not a good summary of capitalism at all because you omit the part where interests of sellers and buyers align. Which is precisely what has made capitalism successful.

Profit growth is based primarily on offering the product that best matches the consumer wish at the lowest price, and production cost possible. That benefits both the buyer and the seller. If the buyer does not care about product quality, then you will not have any company producing quality products.

The market is just a reflection of that dinámica. And in the real world we can easily observed that: Many market niches are dominated by quality products (outdoor and safety gear, professional and industrial tools…) while others tend to be dominated by non-quality (low end fashion, toys).

And that result is not imposed by profit growth but by the average consumer preference.

You can of course disagree with those consumer preferences and don’t buy low quality products, that’s why you most probably also find high products in any market niche.

But you cannot blame companies for that. What they sell is just the result of the aggregated buyers preferences and the result of free market decisions.

Well, keep in mind students at UCLA at 1967 were probably among the most wealthy in the country. A lot more average people at UCLA nowadays. Of course being financially well off wouldn't be the most important thing if you were already financially well off.

I wonder what would be the proportion of answers between different society economic levels.

What we know so far though is that many of the traditional values were bound to the old society structures, based on the traditional family.

The advent of the sexual revolution, brought by the contraception pill, completely obliterated those structures, changing the family paradigm since then. Only accentuated in the last decade by social media and the change in the sexual marketplace due to dating apps.

Probably today many young people would just prioritize reputation (eg followers) over wealth and life philosophy. As that seems to be the trend that dictates the sexual marketplace dinámics.

The paradox is that the general principles of the market work, but the market is invisibly dysfunctional in its details.

It is generally true that higher income jobs are allocated to higher productivity workers, but it does not follow that high incomes imply high productivity and vice versa for low incomes.

If you combine the above with a disequilibrium market where supply of labor exceeds the demand for labor, then from a naive perspective it would appear as if the unemployed would deserve their unemployment.

After all, the most productive members are all employed and rewarded for their efforts. The unemployed are just lazy (voluntarily unemployed) and incompetent (society is better off without them). Any form of punishment is seen as justified and not some structural failing of the system.

The problem is that if there is a labor market disequilibrium, there will always be unemployed people and even if you think the productivity ranking is a good thing, it just means that if one of the "lazy" people suddenly becomes "hard working", they will just take the place of someone else and nothing has changed other than that the standard for laziness has risen.

Even if people notice that the system is fundamentally broken, they realize that individually, they are either a beneficiary of the system and therefore don't see a reason to change it or they don't have the ability to change the system and rather focus on taking someone else's place.

This will result in an artificial Darwinian rat race where people see each other as competitors to defeat.

This is my explanation for why immigrants make a good scapegoat even though immigration doesn't affect the rules of the game at all.

Here is an analogy via a game of musical chairs. There is the perception that more immigrants means more players competing for chairs. This is a naive interpretation that looks obvious. What is being forgotten is that each player is bringing a new chair and the number of missing chairs is a percentage of the number of players. The truth is that having more immigrants means you can take their chair away for yourself. So immigration is not causative here. The problem is that there were never enough chairs to begin with no matter how many people are playing the game.

Eyeballing the chart in the OP and the French data shows them to have a comparable pattern. While OP's data is horses per person, and the French is total number of horses, both show a decline in horse numbers starting about 10 years after widespread adoption of the motor vehicle and falling to 50% of their peak in the mid- to late-1950's, with the French data being perhaps a bit over 5 years delayed compared to the US data. That is, it took 25 to 30 years after mass production of automobiles was started by Ford for 50% of "horsepower" to be replaced.

The point isn't to claim that motor vehicles did not replace horses, they obviously did, but that the replacement was less "sudden" than claimed.