> Silly and pointless criticism. Why do the semantics of the word intelligence matter?
It matters because, we're still sorting out what intelligence means for an AI agent. As you pointed out, language evolves over time. The question remains whether or not attributing intelligence to the current iteration of models is correct. This is not settled and I don't see why it's wrong to bring it up.
It's not wrong to bring it up, but the other comment did not "bring it up". It purported to correct someone by categorically stating "it is not intelligence, you are wrong and I am right", while not once saying what, then, intelligence is.
One thing is clear: LLMs at least already are capable of 1) not making the same mistake that person made, and 2) clearly seeing why the other person's post was "wrong" in both reasoning and tone.
Being good in chess was (and still is) associated with being intelligent. But if a computer does it, it is just a calculator (and it is).
Then go, the great game for intelligence, too complex for calculators to have a chance against intelligent humans. Until it was solved.
And then text, the original Turing test solved, AI capable enough to fool humans. And now already replacing humans in jobs strongly associated with intelligence - programming.
I find it hard to debate, that we don't have created artificial intelligence, by the way we used to use the word "intelligence" before.
So if AI is really understanding something?
Likely not in the way we use that term. But it definitely shows intelligent behavior and actions.
When people talk about solving a game like go or chess, they mean proving mathematically if there exists a way to guarantee a win, or if the second player can always guarantee a draw, among related questions. Current game engines have no such knowledge, they just pick statistically what the think the best move is and hope for the best.
No, that is not what "people" in general mean, this is only what some people mean.
Other people know there is no solving go with calculating, but using statistics to achieve the goal of becoming better at humans. And they are. (With a recent unexpected exception unlikely to be repeated more often)
I don't think people "in general" refer to games as "solved" or "not solved" at all. Among people who do, chess and go are definitely not referred to as (fully) solved.
"to have a chance against intelligent humans. Until it was solved."
But this was the original statement - so solved references "chance against intelligent humans". And this is clearly solved. No comment on that there cannot be better go engines, but no matter how painful it is, they beat the best humans. (And it was painful, they did cry)
That's all the more reason to stop talking about it and actually discuss concrete capabilities or lack thereof.
We're all well aware that we have different thresholds for what we consider intelligence, and that these thresholds are constantly changing.
Even if we agree that "LLMs are AI!!!" or "LLMs are not AI!!!" in this thread, all we've established is that this particular set of commentors share a similar enough definition at this point in time.
So let's say we make up a new word, machilligence to serve as a parallel term to intelligence but strictly for machines. How is the world different in that case vs. if we call it intelligence?
Or I guess to put it another way, if we want to coin a new term for the intelligence-esque thing that AI has, but the key differentiator is that it's an AI thing and not a human thing, then what linguistic value does the new word have? If I said "Claude is intelligent" then the fact that we're talking about AI "intelligence" is already captured in the sentence anyway; no new word needed
I think "intelligence" carries baggage. When most people hear it, they're thinking of the constellation of things: judgment, consistency, moral reasoning, the ability to decide something and stick with it. An intelligent person has an internal model of the world, values they apply consistently, and the capacity to learn from mistakes in a meaningful way.
LLMs don't do any of that. They perform statistical pattern matching on text at an extraordinary scale. They're shockingly good at mimicking the surface features of intelligent behavior.
I think the overuse of the word intelligence is something to criticise as grandma is not across the tech details.
It matters the same way that calling a dog or a cat intelligent matters. It humanizes the thing, even if that isn't your intention. Right now that's not a big deal since most people agree that machines should not have rights, but I wouldn't take that for granted.
Why compare the M1 MBA discounted at Walmart but not give the same edu discount to the Neo? The target audience for Neo is likely people who would be able to use the edu discount.
I know many people who would not care about the differences you have outlined and gladly pay $499 for the Neo.
These models respond differently and have their own "personality". Even in coding, there are people who swear by one model over the other. I know engineers who just stick with Claude and could not care to try Codex. For them, if it's not broken, why fix it?
> Even in coding, there are people who swear by one model over the other
I just swear at the models. =P But jokes aside, I liked Claude Code and found it a big productivity boost for a month or two. Then the honeymoon phase slowly ended and I realized how much of its code I was rewriting myself. I don't use assistants anymore except to summarize changes for commit messages or PRs (and then I rewrite those summaries).
Not sure how many developers are like me, but I am very open to Claude, very open to Gemini, open to open source models (including gpt-oss), but am very reluctant to use frontier OpenAI models. The Microsoft distrust runs extremely deep, the browser authentication dance demanded of users for ChatGPT was the most extreme of the major frontier models, and early OpenAI API service stability was absolutely terrible. Llama had my back back then.
This is is no way dismissing your concern but I think this reinforces my point about branding. Whether or not Microsoft is handling AI in a responsible way, we don't trust them due to their poor practices on Window.
That's one way of putting it. The other way of putting it is that the affected are bearing the cost of climate change imposed on them by the rest of society, who are benefiting.
It sounds like what you're arguing for is that companies ought to have employees that are irreplaceable. Wouldn't that impose a huge risk to the company? If said employee gets hit by the proverbial bus or leaves, the company should just fold?
Companies need to build systems where everyone is replaceable to de-risk the business and not because they don't get programmers.
If a company doesn't have irreplaceable people, then that company is not doing anything interesting. Conversely, if replaceable people can produce your (software) product, then any other company can also do it.
As much as I don't like LLMs that much personally, do you think ChatGPT was produced with replaceable people?
> Companies need to build systems where everyone is replaceable...
No they don't. They need to build systems where everyone is happy with their job and don't need to constantly hop jobs for better salary, environment, etc.
The way to mitigate the bus factor is not to make everybody replaceable; it is to have a process to develop more irreplaceable people with overlapping expertise in their areas.
Overlapping expertise is another form of replacing someone. At a basic level, employees need to go on vacation, parental leave and all sorts of other personal leave. If you were irreplaceable, you couldn't go on leave.
Companies who develop these systems successfully are able to allow employees to go on leave for 4-6 months and have them easily come back. This is a good thing.
But they ( companies ) don't. Looking back at my career, what you do get is, various ranges of alignment to an idea ( whatever it may be ). Some companies do it better than others. Usually, the smaller the company, the easier it is for the owner/founder/main guy to make sure his vision is appropriately enforced, but that gets so much harder in bigger ones so the systems they generate get progressively less sensible. And yes, I don't think search for absolutely replaceable employees shows any kind of faith in one's company. It does, however, show an interesting frame of mind that I personally like to avoid.
For all the talk about innovation, you don't get that by making everyone an interchangeable cog. You want at least some people, who are difficult to be replaced, because they are your competitive edge ( I am saying difficult, because I personally also do not believe anyone is truly irreplaceable ).
And again, the risk to a company, especially a tech company, is falling behind. Losing an employee is a fact of life type of risk; effectively unavoidable. Still, that kind of fake modularity is wrong, not because modularity is a bad idea ( it is not ), but because companies absolutely fucking suck at designing that kind of a system ( as evidenced by reality itself ).
All this is before we get to some of the more human aspect of all this ( up until now we were talking about companies as if they are a living thing with wills and what not and an amalgamation of humans, where one action is a function of thousands little decisions ) like: people messing with systems in a way that does the exact opposite of what the company 'wants'.
All in all, it is an interesting argument, and I even agree with it at some level, but I do not think it survives closer inspection.
I did not understand it that way. Putin is probably smarter than Trump (though he does not deserve to be regarded as a mastermind IMHO). The parallel I find interesting is that both are authoritarians who were helped to power by billionaires who thought it would serve their interests. We know the fate Russian “oligarchs” later met.
Russians close to power have historically often met that fate - at least since 1917, I suspect either prison or forced internal or external exile was more common before that. Americans not so much I think, so this probably won't transfer.
Java was so bad that Android took a hard pivot to Kotlin. If anyone understands the importance of code maintenance, it's Google. They built a language for it (Go). I think it's ok to look at historical Java for what it is and learn from it's mistakes. Modern Java is better. Unfortunately, it's developed a bad rap, and it looks like it's in a decline. Fortunately we have Kotlin, Go, Typescript, etc.
Have you spent a lot of time trying to hire people? I guarantee you there is no shadow council trying to figure out how to hire "busywork" worker bees. This perspective smells completely like "If I were in charge, things would be so much better." Guess what? If you were to take your idea and try to lead this change across a 100 people engineering org, there would be "out of the box thinkers" who would go against your ideas and cause dissent. At that point, guess what? You're going to figure out how to hire compliant people who will execute on your strategy.
"talk about their past projects, their past teams, how they learn, how they collaborate"
You have now excluded amazing engineers who suck at talking about themselves in interviews. They may be great collaborators and communicators, but freeze up selling themselves in an interview.
- “big” tech companies like Google, Amazon, Microsoft came up with these types of tech interviews. And there it seems pretty clear that for most of their positions they are looking for cogs
- The vast majority of tech companies have just copied what “big” tech is doing, including tech interviews. These companies may not be looking for cogs, but they are using an interview process that’s not suitable for them
- Very few companies have their own interview process suitable for them. These are usually small companies and therefore the number of engineers in such companies is negligible to be taken into account (most likely, less than 1% of the audience here work at such companies)
And what is wrong with being a cog? Not everyone is going to invent the next ai innovation and not everyone is cut out to build the next hot programming language.
Bugs need to be fixed. Features need to be implemented. If it weren't for cogs, you'd have people just throwing new projects over the fence and dropped 6 months after release. Don't want to be another cog? Join a startup. Plenty of those hiring. The reality is that when you work at a large company, you're one of 50,000 people. By definition, only 1% are in the top 1%.
Someone has to wash the dishes and clear the tables. Let's stop looking down at jobs just because it's not hot and sexy. People who show up and provide value is great and should be appreciated.
The interview process being a circus of how many hoops you'll jump through. Which in this case is upwards of 3 months of trivia, beauracracy, and politics. And these days they don't even give you the grace of a response; they may just ghost you.
But being a cog itself is personally fine. Work to live, not live to work. But leading people on to drop them on the tip of a hat is disrespectful of everyone's time. At least a 1-2 stage interview for a dishwasher or table busser is only wasting a few hours per role applied. Time is the most valuable resource we have, of course people want to use it carefully.
Human cogs are going to be phased out. I'm not an AI doomer who thinks engineers are going to be replaced across the board, but the need for a human being who functions like a robot is going away fast. We need humans to do what humans do well, and humans don't do well as cogs in a machine—machines are better at that role.
The days of leetcode interviews are numbered not because they're too easy to cheat at, but because they were always optimizing for the wrong traits in most companies that cargo culted them, and even the companies that used them correctly (Big Tech) are going to rapidly need a different type of interview for the new types of hires they need.
> You have now excluded amazing engineers who suck at talking about themselves in interviews. They may be great collaborators and communicators, but freeze up selling themselves in an interview.
This is the job of a good interviewer. I've run the gauntlet from terrible to great answers to the exact same questions depending on the interviewer. If you literally just ask that question out of the blue, you'll either get a bad or rehearsed response. If you establish some rapport, and ask it in a more natural way, you'll get a more natural answer.
It's not easy, but neither is being on the other side of the interviewer, and that's never been accepted as an excuse
> I guarantee you there is no shadow council trying to figure out how to hire "busywork" worker bees.
The council itself is made of "busywork" worker bees. Slave hiring slaves - the vast majority of IT interviewers and candidates are idiot savants - they know very little outside of IT, or even realize that there is more to life than IT.
> You have now excluded amazing engineers who suck at talking about themselves in interviews. They may be great collaborators and communicators, but freeze up selling themselves in an interview.
This was the norm until perhaps for about the last 10-15 years of Software Engineering.
> I guarantee you there is no shadow council trying to figure out how to hire "busywork" worker bees.
I didn't say that. I said that this style of interview was designed to hire pluggable cogs. As others have noted, that was the correct move for Big Tech and was cargo culted into a bunch of other companies that didn't know why their interviews were shaped the way they were.
> there would be "out of the box thinkers" who would go against your ideas and cause dissent. At that point, guess what? You're going to figure out how to hire compliant people who will execute on your strategy.
In answer to your original question: yes, I'm actively involved in hiring at a 100+ person engineering org that hires this way. And no, we're not looking to figure out how to hire compliant people, we're hiring engineers who will push back and do what works well, not just act because an executive says so.
> You have now excluded amazing engineers who suck at talking about themselves in interviews. They may be great collaborators and communicators, but freeze up selling themselves in an interview.
Only if you suck at making people comfortable and at understanding different (potentially awkward) communication styles. You don't have to discriminate against people for being awkward, that's a choice you can make. You can instead give them enough space to find their train of thought and pursue it, and it does work—I recently sat in on an interview like that with someone who fits your description exactly, and we strongly recommended him.
It matters because, we're still sorting out what intelligence means for an AI agent. As you pointed out, language evolves over time. The question remains whether or not attributing intelligence to the current iteration of models is correct. This is not settled and I don't see why it's wrong to bring it up.
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