People here like to slag on google for being late to the chatbot party, but they've been using ML the entire time and integrating it into various products for ages. I kind of wonder if the only reason they were "behind" was the lawyers were less brazen about the copyright situation.
I agree with the commodity take, and I personally bet on Google eating everybody else's lunch eventually, because there's a lot of other business behind them and they can afford to undercut competitors. They aren't a one trick pony.
The market demands models that don't fail constantly with HAL-like "Sorry, Dave, I cannot do that for you" moralizing responses.
An API that is used for mission-critical purposes and that randomly fails with "HTTP/1.1 406 You Are A Terrorist And/Or Hitler" is a BUG, and the market will coalesce around models that don't have this bug.
did anything good come from wework?
More coworking spaces.
Adam and Rebekah Neumann got exposed for being the frauds that they are.
Commodities can be massive businesses with competitive moats. Oil is a commodity BP and Exxon do just fine financially speaking.
In 2024, they are projected to bring in $3.4 billion in revenue and lose $5 billion dollars.
They just had a massive fundraising round for $6.6 billion which at the current costs and growth is what, 6-8 months of spend?
If they bring in $11 billion in 2025, I expect them to lose at least $18 billion dollars. Good luck!
There are three likely outcomes:
1. AI plateaus. OpenAI slashes the R&D budget to become profitable with revenue in double digit billions and profit in single digit billions. Valuation likely similar to today's.
2. AI doesn't plateau. OpenAI makes a killing. (Hopefully metaphorically, not literally)
3. Scenario 1 or 2, but it's a company other than OpenAI that wins.
The Information estimates that OpenAI is spending $4 billion just to run ChatGPT and their APIs, along with $3 billion in training and $1.5 billion in salaries.
https://www.axios.com/2024/10/03/openai-investors-profit-mon...
I'm running Phi3, Llama 3.2 and Mistral Nemo locally and they're decent enough for many things.
Couple that with a lack of pricing power thanks to all the other similar products in the market.
Greenlighting training a new foundation model is very expensive, but is also a human decision that can be postponed based on available capital.
Didn't Sam ask TSMC to spend $7 trillion on new fabs? By comparison, $18 billion/yr spend seems very small.
They invested in exploration and now they control those oilfields. They built refineries and have the systems and experienced people to operate them. Meta can't release a LLamaOilfieldAndRefinery which I can operate by just spending a few thousand on gpu's.
I don't see how a chatbot meets any of those criteria
> I don't see how a chatbot meets any of those criteria
Calling these things "a chatbot" is likely limiting your vision: some of the stuff people build by fine-tuning LLMs, such as the ones OpenAI offer, use them to generate database queries matching their customers' database schemas.
"Chatbot" is simply a convenient UI for an LLM in the same way that a web browser is a conventional UI for email. (And in this analogy, anyone calling an LLM "autocomplete on steroids" would be making the same mistake as someone saying "Wikipedia is just TCP on steroids").
I expect LLMs to continue to be extremely generic in the same way that web browsers are (market history shows periods where one browser dominates the market despite open source) or like spreadsheets (where Microsoft Office is, or was last I looked, dominant despite free offerings being good enough for most people).
Society needs intelligence. We started using mechanical aids because it became impractical to perform census work by hand as the population increased, AI is a continuation of this process: we need it, it's a commodity, there may be a market opportunity despite free and/or open source competition, and (like Netscape, like Internet Explorer) there's no guarantee that the winner in one year will still be leading the next year or even existing a decade later.
I'm as cynical as it gets on this forum, as evidenced by my comment history.
But you're comparing these AI companies to WeWork? Really?
WeWork was a real estate company operating in a historically favourable environment (0% interest rates) pretending to be a tech company. They literally rented office space. What do they have in common?
I notice there's a new generation of "grey beard" programmers constantly talking about how "useless" AI is for programming, and they can do everything faster. Meanwhile, there are tons of us out there who are paying $20, $30, $50 per month and upwards for these tool as they are, and wouldn't want to go without. Ever. And we have no idea where it's going to go. Maybe you're missing something?
I'm paying for Claude, which I find super helpful (although mostly for side-projecty stuff rather than dayjob). I'd definitely pay double what it costs today, particularly if I went back to shorter-term environments where I think it shines.
If you can't hook it up to your codebase/you write in a language where it's not great (it doesn't seem good at Elisp at all, at all) then I could see how people might not find the value.
Nonetheless, despite finding these tools useful, I too am sceptical about whether or not there's a valuable business there.
For context, I said this about Uber, WeWork and a bunch of other startups that never really monetised. Note that I also said that about Facebook, where I was completely wrong.
If you are paying attention, this is a pretty terrifying prospect if you are building a $200k+/yr life on the basis that SWE will pay like this forever. A machine is coming along that genuinely might be 80% of your skill set in a few years, makes it very difficult to negotiate generous packages with the remaining 20%.
Something similar happened when COBOL came out. Same with website builders. The big difference between most industries versus software is we aren't even close to satisfying the world's desire for software yet, so increases in productivity just gives us bigger leverage.
Is this supposed to be scary? This scenario is absolute stonks if you're a developer worth your salt. A machine makes me 5 times more productive, and I don't even have to commoditize my complement because they're taking care of that themselves?
The rate of change could make the short term bumpy as companies try to play around with less dev work. Eventually though competition will push companies to raise their productivity to the new baseline (programmers + AI).
One thing that is a danger is if devs ignore what's happening in AI. I remember when Google first came out having to learn the art of querying Google to get what I was looking for. AI/LLMs looks to be the same - ignore learning how to leverage them at your own peril.
That does happen. Obviously no programmers employed at those companies to talk about it on HN though.
Hire a team to build a project, when it's finally satisfied most of your requirements, you progressively cut staff until only Jim is left, and Jim spends the next two decades maintaining the system, growing out his hair and beard, piling kludge on top of kludge, and drinking heavily until retirement.
The HN bubble, focused so intently on BigTech and FAANG, is woefully unaware of how things work basically everywhere else.
Pre-musk, links to random tweets seemed to load almost instantly. Now?
Last time I tried, took 48 seconds to show a "please login or create account" message.
My Performa 5200 in the 1990s booted up faster than that.
If he'd kept things as is, without fiddling, that would've been an improvement over what he actually did.
Still, I'm glad he reduced my compulsive use of the service.
Personally I think its cyclical as software is such a key component of communication and automation - and so we'll see future growth periods but probably not to the same extent as the last decade where seemingly every undergrad was compelled to study Computer Science.
I'd rather argue that every hyped topic is polarizing, and your argument can be adjusted to basically every hugely hyped topic.
Comparing to airlines was fine, but you take issue with a comparison to real-estate? WeWork was also beloved by their customers and had leadership who were a bit off the rails.
The fact that switching models is changing one string in AWS bedrock means that nobody is going to be able to charge a significant premium.
I've always found the time-consuming part of this job to be understanding the context of the change rather than making the change itself. Essentially, trying to understand the existing code and business requirements and how they all fit together. I can definitely see the potential for AI to help make this easier but I haven't found the current tooling to be any good at this.
It's the first tool that came to hand: I'm sure there are better historical comparisons if I bothered to look. For professional reasons, I was well acquainted with WeWork when they were a big deal. It was clear to many of us in advance of their collapse that WeWork was heading for a hard crash based on their lease commitments and other public data. In this case, public data, such as for OpenAI and Anthropic, strongly suggests that, like WeWork, the economics of the businesses don't make sense. There are some fundamentals that no amount of innovation can overcome. Committing to leases you can't conceivably cover is one of them. Spending $2.35 for every $1 of revenue is clearly another, absent some breakthrough.
WeWork is not a perfect example. But if OpenAI flames out, it will be mentioned in the same breath as WeWork. The reasons are not the same, but they do sort of rhyme.