"We have no current plans to make revenue."
"We have no idea how we may one day generate revenue."
"We have made a soft promise to investors that once we've built a general intelligence system, basically we will ask it to figure out a way to generate an investment return for you."
The fact he has no clue how to generate revenue with an AGI without asking it, shows his lack of imagination.
I wouldn't take this statement at face value any more than anything else a CEO says. For example, maybe he still had to appease the board, and talking about making profit would be counterproductive. Maybe he gave this answer because it signals that he's in it for the long game and investors should be too.
Sam Altman himself doesn't know whether it's the case. Nobody knows. It's the natural of R&D. If you can tell whether an architecture works or not with 100% confidence it's not cutting edge.
I think that was before 4o? I know 4o-mini and o1 for sure have come out since he said that
You say unironically on an article stating that Sam Altman cannot be taken at his word in a string of comments about him hyping up the next thing so he can exit strongly on the backs of the next greater fool. But seriously, I’m sure GPT-5 will be the greatest leap in history (OpenAI equity holder here).
I suspect it's a little different. AI models are still made of math and geometric structures. Like mathematicians, researchers are developing intuitions about where the future opportunities and constraints might be. It's just highly abstract, and until someone writes the beautiful Nautilus Mag article that helps a normie see the landscape they're navigating, we outsiders see it as total magic and unknowable.
But Altman has direct access to the folks intuiting through it (likely not validated intuitions, but still insight)
That's not to say I believe him. Motivations are very tangled and meta here
That’s dead. OpenAI knows that much. There will be more, but they aren’t going to report that we’re doing incremental advances until there’s a significant breakthrough. They need to stay afloat and say what it takes to try and bridge the gap.
Based on all of the behaviour psychology books I've read, Claude would have to introduce a model that is 10x better and 10x cheaper - or something so radically different that it registers as an entirely new thing - for it to hit the radar outside of the tech world.
I encourage you to sample the folks in your life that don't work in tech. See if any of them have ever even heard of Claude.
Also, in what way has OpenAI become the Kleenex of the LLM space? Anthropic, Google, Facebook have no gpts, nobody “gpts” something, nobody uses that companies “gpt”.
I would say perhaps OpenAI has become the Napster, MySpace, or Facebook of the LLM space. Time will tell how long they keep that title
That seems like the same thing to me.
I feel like I hear “ask Claude” as much as “ask chatGPT”
I just sampled my family and nobody could name an LLM that wasn't GPT. In this very small, obviously anecdotal scenario, GPT == LLM.
They seemed vaguely aware that there are other options; my wife asked if I meant Bing.
Meanwhile, I have literally never heard the words "ask Claude" out loud. I promise to come back and confirm if/when that ever changes.
I keep hearing from people who find these enormous benefits from LLMs. I've been liking them as a search engine (especially finding things buried in bad documentation), but can't seem to find the life-changing part.
2. To break procrastination loops. For example I often can't name a particular variable, because I can see few alternatives and I don't like all of them. Nowadays I just ask ChatGPT and often proceed with his opinion.
3. Navigating less known technologies. For example my Python knowledge is limited and I don't really use it often, so I don't want to spend time to better learn it. ChatGPT is just perfect for that kind of tasks, because I know what I want to get, I just miss some syntax nuances and I can quickly check the result. Another example is jq, it's very useful tool, but its syntax is arcane and I can't remember it even after years of occasional tinkering with it. ChatGPT builds jq programs like a super-human, I just show example JSON and what I want to get.
4. Not ChatGPT, but I think Copilot is based on GPT4, and I use Copilot very often as a smart autocomplete. I didn't really adopt it as a code writing tool, I'm very strict at code I produce, but it still helps a lot with repetitive fragments. Things I had to spend 10-20 minutes before, construction regexps or using editor macroses, I can now do with Copilot in 10-20 seconds. For languages like Golang where I must write `if err != nil` after every line, it also helps not to become crazy.
May be I didn't formulate my thoughts properly. It's not anything irreplaceable and I didn't become 10x programmer. But those tools are very nice and absolutely worth every penny I paid for it. It's like Intellij Idea. I can write Java in notepad.exe, but I'm happy to pay $100/year to Jetbrains and write Java in Idea.
Respectfully but that's a bit like saying you don't need to learn how to ride a bicycle because you can use a pair of safety wheels. It's an excuse to not learn something, to keep yourself less knowledgeable and skillful than you could really be. Why stunt yourself? Knowledge is power.
See it this way: anyone can use ChatGPT but not everyone knows Python well, so you 'll never be able to use ChatGPT to compete with someone who knows Python well. You + limited knowledge of Python + ChatGPT << someone + good knowledge of Python + ChatGPT.
Experiences like the one you relay in your comment makes me think using LLMs for coding in particular is betting on short-term gains for a disproportionately large long-term cost. You can move faster now, but there's a limit to what you can do that way and you'll never be able to escape it.
Slow down, cowboy. Getting a LLM to generate code for you that is immediately useful and doesn't require you to think too hard about it can stunt learning, sure, but even just reading it and slowly getting familiar with how the code works and how it relates to your original task is helpful.
I learned programming by looking at examples of code that did similar things to what I wanted, re-typing it, and modifying it a bit to suit my needs. From that point of view it's not that different.
I've seen a couple of cases first hand of people with no prior experience with programming learn a bit by asking ChatGPT to automate some web scraping tasks or spreadsheet manipulation.
> You + limited knowledge of Python + ChatGPT << someone + good knowledge of Python + ChatGPT.
Substract ChatGPT from both sides and you have a rather obvious statement.
> Respectfully but that's a bit like saying you don't need to learn how to ride a bicycle because you can use a pair of safety wheels.
How did you learn to ride a bicycle?
You are making a lot of assumptions about someone's ability to learn with AND without assistance, while also making rather sci-fi leaps about our brain somehow being able to differentiate between learning that has somehow been tainted by the tendrils of ML overlords.
The models and the user interface around them absolutely will continue to improve far faster than any one person's ability to obtain subject mastery in a field.
If you want to have a debate, I'm all for it, but if you're going to go around imagining things that I may have said in another timeline then I don't see what's the point of that.
You could be right, but I strongly suspect that you are actually wrong.
The OP said:
>>> For example my Python knowledge is limited and I don't really use it often, so I don't want to spend time to better learn it.
And I replied:
>> Respectfully but that's a bit like saying you don't need to learn how to ride a bicycle because you can use a pair of safety wheels. It's an excuse to not learn something, to keep yourself less knowledgeable and skillful than you could really be. Why stunt yourself? Knowledge is power.
"It's an excuse to not learn something (...) Why stunt yourself?".
Do you care how a car engine works to drive a car?
The AI is pretty good at answering "I know this is possible, remind me what it's called or what the syntax is."
For a lot of these the reason I want to look it up is I don't use it enough to build muscle memory. If I did, I'd already have the muscle memory. And in practice, it's just a faster version of looking for examples on stackoverflow.
So learning syntax nuances of yet another programming language which I'll forget soon is wasted time. There's some "fundamental" knowledge, like understanding what functional value is, but the specific syntax that Python invented for lambda - that's not something valuable when I use Python few times a year.
Rereading your comment I think I got the wrong impression from it. You said:
>> I don't really use it often, so I don't want to spend time to better learn it
And I focused more on "I don't want to spend time to better learn it" than on "I don't really use it often". I also don't use Python often and I have to look up its syntax, same with e.g. R. I guess in that case it makes sense to not spend too much time learning the ins and outs of a language. On the other hand, Python is a staple, like Java was back in the day, and Perl and so on. It's useful, like speaking English. I don't think I would ever feel comfortable saying "I don't want to learn" it; or anything else.
All with much lower latency than an HTTP request to a random place, knowing that my data can’t be used to trading anything, and it’s free.
It’s absolutely insane this is the real world now.
Not wanting my data to be sent to random places is what has limited my use of tools like copilot (so I'd only use it very sparingly after thinking if sending the data would be a breach of nda or not)
And I could say this about just about every domain of my life. I've trained myself to ask it about everything that poses a question or a challenge, from creating recipes to caring for my indoor Japanese maple tree to preparing for difficult conversations and negotiations.
The idea of "just" using it to compose emails or search for things seems frustrating to me, even reading about it. It's actually very hard for me to capture all of this in a way that doesn't sound like I'm insulting the folks who aren't there yet.
I'm not blindly accepting everything it says. I am highly technical and I think competent enough to understand when I need to push back against obvious or likely hallucinations. I would never hand its plans to a contractor and say "build this". It's more like having an extra, incredibly intuitive person who just happens to contain the sum of most human knowledge at the table, for $20 a month.
I honestly don't understand how the folks reading HN don't intuitively and passionately lean into that. It's a freaking superpower.
It is difficult to get a man to understand something when his salary depends upon his not understanding it.
Many of us here would see our jobs eliminated by a sufficiently powerful AI, perhaps some have already experienced it. You might as well. If you use AI so much, what value do you really provide and how much longer before the AI can surpass you at that?
There's a lot of people in technical roles who chose to study programming and work at tech companies because it seemed like it would pay more than other roles. My own calculation is that the tech-but-could-have-just-as-easily-been-a-lawyer cohort will be the first to find themselves replaced. Is that a revealing a bias? Absolutely.
Actual hackers, in the true sense, will have no trouble finding ways to continue to be useful and hopefully well compensated.
A calculator needs direction on what to calculate because the machine doesn't have agency.
We are going to a higher level of abstraction and at that higher level you probably need a different skill set than before. Humans aren't going to get cut out of the loop but you always have to level up your skills.
I think there is just a generation of tech workers that got lazy and thought they were immune to change some how. I didn't even know anyone that had been on the internet when I graduated high school. Someone older and wiser though told me I would have to constantly reinvent myself, always learn new skills and will have several different careers. They were so spot on. Guess what? Nothing has changed.
A tip of my hat to you, sir/ma'am.
It a super power for the intellectually curious while the highly specialized that thought they were done learning can only see the threat to their intellectual moat. They aren't wrong.
I feel like I level up on a weekly basis practically.
I feel like this has become one of the most taboo things to even wonder about out loud, because it drives a different part of the Venn diagram into a freaking rage. How dare you force me to consider that perhaps I am only slightly above average in a population of billions?
It's helped me stay productive on days when my brain just really doesn't want to come up with a function that does some annoying fairly complex bit of logic and I'd probably waste a couple hours getting it working.
Before I'd throw something like that at it, and it'd give me something confidently that was totally broken, and trying to go back and forth to fix it was a waste of my time.
Now I get something that works pretty well but maybe I just need to tweak something a bit because I didn't give it enough context or quite go over all the inconsistencies and exceptions in the business logic given by the requirements (also I can't actually use it on client machines so I have to type it manually to and from another machine, so I'm not copy pasting anything so I try to get away with typing less).
I'm not typing anything sensitive, btw, this is stuff you might find on Stack Overflow but more convoluted, like "search this with this exception and this exception because that's the business requirement and by these properties but then go deeper into this property that has a submenu that also needs to be included and provide a flatlist but group it by this and transform it so it fits this new data type and sort it by this unless this other property has this value" type of junk.
[0] https://norcalrecord.com/stories/664710402-judge-tosses-clas...
It's not trivial. "Mere puffery" has netted Tesla about $1B in FSD revenue.
Perhaps if you have a selective memory. There's plenty of collections of straight-up set-in-stone falsehoods on the internet to find, if you're interested.
I'm sure the defence is always, "but if we just had a bit more money, we would've got it done"
You can make a case that partial self driving is a route to FSD, the ISS is en route to Mars and (you can make a potentially slightly less compelling case) LLMs are on the way to AGI.
No one can make a case that lady was en route to the tech she promised
I think the more abstract and less defined the end goal is, the easier it is to make everything look like progress.
The blood testing lady was a pass/fail really. FSD/AGI are things where you can make anything look like a milestone. Same with SpaceX going to Mars.
Ceos are more often come from marketing backgrounds than other disciplines for the very reason they have to sell stakeholders, employees, investors on the possibilities. If a ceos myth making turns out to be a lie 50 to 80 percent of the time then hes still a success as with Edison, Musk, Jobs, and now Altman.
But i think AI ceos seem to be imagining and peddling wilder fancier myths than the average. If AI technology pans out then i dont feel theyre unwarranted. I think theres enough justification but im biased and have been doing AI for 10 years.
To ur question, If a ceos lies dont accidently turn true eventually as with the case of Holmes then yes its a big problem.
I remember all the articles praising the facade of a super-genius. It's a stark contrast to today.
People write about his trouble or his latest outburst like they would a neighborh's troubled kid. There's very little decency in watching people sink like that.
What's left after reality reassesserts itself, after the distortion field is gone? Mostly slow decline. Never to reach that high again.
Given Altman seems to be extremely vague about exact timelines and mainly gives vibes, he's probably doing fine. Especially as half the stuff he says is, essentially, to lower expectations rather than to raise them.
What you need a CEO for is to sell you (and your investors) a vision.
It saddens me how easily someone with money and influence can elevate themselves to a quasi religious figure.
In reality, this vision you speak of is more like the blind leading the blind.
If so many people wouldn't fall for claims without any proof, religions themselves would not exist.
If you want to call it suckering suckers into parting with their money that works too.
It’s not all that different from crypto.
Progress depends on irrational people though. Even if 50 companies fail for every one that succeeds, that’s progress.
But it is always about the narrative.
But you are right, we live in a post truth influencer driven world. It's all about the narrative.
Which model? Sonnet 3.5? I subscribed to Claude for while to test Sonnet/Opus, but never got them to work as well as GPT-4o or o1-preview. Mostly tried it out for coding help (Rust and Python mainly).
Definitely didn't see any "leap" compared to what OpenAI/ChatGPT offers today.
OpenAI decides what they call gpt5. They are waiting for a breakthrough that would make people "wow!". That's not even very difficult and there are multiple paths. One is a much smarter gpt4 which is what most people expect but another one is a real good voice-to-voice or video-to-video feature that works seamlessly the same way chatgpt was the first chatbot that made people interested.
Otherwise people might get the impression that we’re already at a point of diminishing returns on transformer architectures. With half a dozen other companies on their heels and suspiciously nobody significantly ahead anymore, it’s substantially harder to justify their recent valuation.
I think the job of a CEO is not to tell you the truth, and the truth is probably more often than not, the opposite.
What if gpt5 is vaporware, and there’s no equivalent 3 to 4 leap to be realized with current deep learning architectures? What is OpenAI worth then?