OpenAI’s board, paraphrased: ‘All we need is unimaginable sums of money’(daringfireball.net) |
OpenAI’s board, paraphrased: ‘All we need is unimaginable sums of money’(daringfireball.net) |
https://www.theguardian.com/technology/2024/jan/08/ai-tools-...
OpenAI has the potential to create the next groundbreaking innovation, like the iPhone. Who needs apps when the AI itself can handle everything?
Uh, they were advertising in 1999 already?
You might find their perspective on advertising surprising.
Returning to my earlier point, please expand your argument about why OpenAI may fail. Let’s aim to elevate the discussion.
I’d like to see more thoughtful discussion here. The debate often feels stuck between oversimplified takes like “It’s just a commodity” and “No, it’s a game changer!” Let’s assume for a moment that OpenAI operates as a commodity business but still figures out how to become profitable, even with small margins. After all, US Steel was a commodity and became hugely successful.
Given these assumptions, why do you think OpenAI might not succeed? Let’s move the conversation forward.
[citation needed]
Google's goal was always advertising just like every other search engine.
https://blogs.cornell.edu/info2040/2019/10/28/the-academic-p...
You might find their perspective on advertising surprising.
Returning to my earlier point, please expand your argument about why OpenAI may fail. Let’s aim to elevate the discussion.
OpenAI, in contrast, still doesn't have any notion as to how to make it all profitable.
Nothing in the paper states or suggests they are anti-ads. Hell, Ads can even work well with their description of page rank. Display ads along side the search results and if a user clicks it then rate the ad higher and if they don't down weight it akin to what you're doing with non-ad links.
> Returning to my earlier point, please expand your argument about why OpenAI may fail. Let’s aim to elevate the discussion.
Because the counterpoint of Google isn't applicable. You can't be like "X is ok because it's similar to Y and Y was ok.". X (OpenAI) isn't similar to Y (Google); Google always planned to do Ads and it's just their stance of keeping them distinct from results that changed over time. A better argument would to pick a Y of Reddit or something that took years to actually generate revenue.
OpenAI should be fine for quite some time though because what else is there to burn billions of dollars investing for people?
[1]: https://snap.stanford.edu/class/cs224w-readings/Brin98Anatom...
I have friends who interviewed in 1999, and all of them came away with the same view - they did not know how the company would make money. They all poked at this topic, and the founders were explicit they really did not want to sell ads. Two of them refused to join because they thought it would fail as a result[1]. So while they did end up doing that, it seems very clear they did not want to go that path if they could avoid it.
If you have actual evidence that suggests this is not the case, rather than the random unsupported conjecture that it was "always their goal", i'd love to hear it!
I've not met a single person who says anything but what i just said - it was not always their goal, they had no desire to do it.
[1] Amusingly both ended up founding and selling companies for over 100m, so they did okay in the end despite theoretically missing a huge opportunity ;)
Then they went full corporate and their real turning point, came in 2007 with their acquisition of DoubleClick, about 12 years after Larry Page and Sergey Brin famously claimed that advertising and search engines don’t mix.
Now compare that to OpenAI. It launched in 2015, nine years ago, but ChatGPT didn’t arrive until 2022—less than two years ago. Google took over a decade to transform its core business with ads and figure out how to become a profit machine.
Let's practice some intellectual humility and acknowledge that OpenAI still has time to work this out. History shows that even if it takes some time, that's perfectly fine.
> There is no technical moat in this field, and so OpenAI is the epicenter of an investment bubble. Thus, effectively, OpenAI is to this decade’s generative-AI revolution what Netscape was to the 1990s’ internet revolution. The revolution is real, but it’s ultimately going to be a commodity technology layer, not the foundation of a defensible proprietary moat. In 1995 investors mistakenly thought investing in Netscape was a way to bet on the future of the open internet and the World Wide Web in particular.
OpenAI has a short-ish window of opportunity to figure out how to build a moat.
"Trying to spend more" is not a moat, because the largest US and Chinese tech companies can always outspend OpenAI.
The clock is ticking.
Amazon might be a good analogy here. I'm old enough to remember when Amazon absorbed billions of VC money, making losses year over year. Every day there was some new article about how insane it was.
There's no technical moat around online sales. And lots of companies sell online. But Amazon is still the biggest (by a long long way) (at least in the US). Their "moat" is in public minds here.
Google is a similar story. As is Facebook. Yes the details change, but rhe basic path is well trodden. Uber? Well the juries still out there.
Will OpenAI be the next Amazon? Will it be the next IBM? We don't know, but people are pouring billions in to find out.
This is very different from OpenAI: if you show me a product that works just as well as ChatGPT but costs less--or which costs the same but works a bit better--I would use it immediately. Hell: people on this website routinely talk about using multiple such services and debate which one is better for various purposes. They kind of want to try to make a moat out of their tools feature, but that is off the path of how most users use the product, and so isn't a useful defense yet.
Apparently old enough to forget the details. I highly recommend refreshing your memory on the topic so you don’t sound so foolish.
1. Amazon had a very minimal amount of VC funding (less than $100M, pretty sure less than $10M)
2. They IPO’d in 1997 and that still brought in less than $100M to them.
3. They intentionally kept the company at near profitability, instead deciding to invest it into growth for the first 4-5yrs as a public company. It’s not that they were literally burning money like Uber.
4. As further proof they could’ve been profitable sooner if they wanted, they intentionally showed a profit in ~2001 following the dotcom crash.
Edit: seems the only VC investment pre-IPO was KP’s $8M. Combine that with the seed round they raised from individual investors and that comes in under $10M like I remembered.
Right now, OpenAI's brand is actually probably its strongest "moat" and that is probably only there because Google fumbled Bard so badly.
Facebook has an enormous network effect. Google is the lynchpin of brokering digital ads to the point of being a monopoly. Someone else mentioned Amazons massive distribution network.
I don't think that's true. I think it's actually the opposite. Global physical logistic is way harder than software to scale. That's Amazon's moat
Not to take away from the rest of your points, but I thought Amazon only raised $8m in 1995 before their IPO in 1997. Very little venture capital by today’s standard.
no, the amazon moat is scale, and efficiency, which leads to network effect. The chinese competitors are reaching similar scales, so the moat isn't insurmountable - just not for the average mom and dad business.
The moat is actually huge (billions of $$). What is happening is that there are people/corps/governments that are willing to burn this kind of money on compute and then give you the open weight model free of charge (or maybe with very permissive and lax licensing terms).
If it wasn't for that, there will be roughly three players in the market (Anthropic and recently Google)
Gruber writes:
" My take on OpenAI is that both of the following are true:
OpenAI currently offers, by far, the best product experience of any AI chatbot assistant. There is no technical moat in this field, and so OpenAI is the epicenter of an investment bubble. "
It's amusing to me that he seems to think that OpenAI (or xAI or DeepSeek or DeepMind) is in the business of building "chatbots".
The prize is the ability to manufacture intelligence.
How much risk investors are willing to undertake for this prize is evident from their investments, after all, these investors all lived through prior business cycles and bubbles and have the institutional knowledge to know what they're getting into, financially.
How much would you invest for a given probability that the company you invest in will be able to manufacture intelligence at scale in 10 years?
Retail margins are razor thin, so the pennies of efficiency add up to a moat
When was this true? Amazon was founded Jul 1994, and a publicly listed company by May 1997. I highly doubt Amazon absorbed billions of dollars of VC money in less than 3 years of the mid 1990s.
https://dazeinfo.com/2019/11/06/amazon-net-income-by-year-gr...
As far as I can tell, they were very break even until Amazon Web Services started raking it in.
1) Almost the best price, almost all the time
2) Reliably fast delivery
3) Reliably easy returns
4) Prime memberships
Same for OpenAI. Anytime I talk to young people who are not programmers, they know about ChatGPT and not much else. Never heard of Llama nor what an LLM is.
Anyone can sell online. But not just anyone has those advantages like same day abs next day shipping
2) If you had some secret algorithm that substantially outperformed everyone, you could win if you prevented leakage. This runs into the issue that two people can keep a secret, but three cannot. Eventually it'll leak.
3) Keep costs exceptionally low, sell at cost (or for free), and flood the market with that, which you use to enhance other revenue streams and make it unprofitable for other companies to compete and unappealing as a target for investors. To do this, you have to be a large company with existing revenue streams, highly efficient infrastructure, piles of money to burn while competitors burn through their smaller piles of money, and the ability to get something of value from giving something out for free.
At the beginning of ride sharing, people believed there was absolutely no geographical moat and all riders were just one cheaper ride from switching so better capitalized incumbents could just win a new area by showering the city with discounts. It took Uber billions of dollars to figure out the moats were actually nigh insurmountable as a challenger brand in many countries.
Honestly, with AI, I just instinctively reach for ChatGPT and haven't even bothered trying with any of the others because the results I get from OAI are "good enough". If enough other people are like me, OAI gets order of magnitudes more query volume than the other general purpose LLMs and they can use that data to tweak their algorithms better than anyone else.
Also, current LLMs, the long term user experience is pretty similar to the first time user experience but that seems set to change in the next few generations. I want my LLM over time to understand the style I prefer to be communicated in, learn what media I'm consuming so it knows which references I understand vs those I don't, etc. Getting a brand new LLM familiar enough to me to feel like a long established LLM might be an arduous enough task that people rarely switch.
First, get government regulation on your side. OpenAI has already looked for this, including Sam Altman testifying to Congress about the dangers of AI, but didn't get the regulations that they wanted.
Second, put the cost of competing out of reach. Build a large enough and good enough model that nobody else can afford to build a competitor. Unfortunately a few big competitors keep on spending similar sums. And much cheaper sums are good enough for many purposes.
Third, get a new idea that isn't public. For instance one on how to better handle complex goal directed behavior. OpenAI has been trying, but have failed to come up with the right bright idea.
That's half the point of OpenAI's game of pretending each new thing they make is too dangerous to release. It's half directed at investors to build hype, half at government officials to build fear.
They don’t need to make a moat for AI, they need to make a moat for the OpenAI business, which they have a lot of flexibility to refactor and shape.
Patents. OpenAI already has a head start in the game of filing patents with obvious (to everybody except USPTO examiners), hard-to-avoid claims. E.g.: https://patents.google.com/patent/US12008341B2
By knowing a lot about me, like the details of my relationships, my interests, my work. The LLM would then be able to be better function than the other LLMs. OpenAI already made steps in that direction by learning facts about you.
By offering services only possible by integrating with other industries, like restaurants, banks, etc... This take years to do, and other companies will take years to catch up, especially if you setup exclusivity clauses. There's lots of ways to slow down your competitors when you are the first to do something.
Alternatively, a model that takes a year and the output of a nuclear power plant to train (and then you can tell them about your tricks, since they aren't very reproducible).
Also, I suspect that the next breakthrough will be kept under wraps and no papers will be published explaining it.
The competitions are mostly too narrow(programming/workflow/translation etc) and not interesting.
Or maybe nvidia has the moat. Or silicon fabs have it.
Meta and X proven surprisingly resilient in the face of pretty overwhelming negative sentiment. Google maintains monopoly status on Web Search and in Browsers despite not being remarkably better than competition. Microsoft remains overwhelmingly dominant in the OS market despite having a deeply flawed product. Amazon sells well despite a proliferation of fake reviews and products. Netflix thrives even while cutting back sharply on product quality. Valve has a near-stranglehold on PC games distribution despite their tech stack being trivially replicable. The list goes on.
A vertically integrated system that people depend on with non-portable integrations is a moat.
Regulatory Capture is a moat.
Maybe they were just too early, later on it turned out that the browser is indeed a very valuable and financially sound investment. For Google at least.
So having a dominant market share can indeed be even if the underlying tech is not exactly unobtainable by others.
Once this bubble bursts, local inference will become even more affordable than it already is. There is no way that there will be a moat around running models as a service.
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Similarly, there probably won't be a "data moat". The whole point of large foundation models is that they are great priors. You need relatively few examples to fine tune an LLM or diffusion model to get it to do what you want. So long as someone releases up to date foundation models there is no moat here either.
and they are probably going to go with regulatory moat over technical moat.
See the scramble to make themselves arbiters of "good AI" with regulators around the world. It's their only real hope but I think the cat's already out of the bag.
But greeed isgood!
OpenAI's C-suite: Well, they earned the C, but it was a letter grade.
What a profoundly unimaginative strategy. No matter the industry, a large-scale diversion of resources towards a moonshot goal will likely get you to that goal. They haven't made an argument as to why we should do that just for them, especially with all of the other alternatives.
And no, advertising your previously secret testing models (e.g. o3) as if they were market competitors is not how to prove they should have our money.
Then why do they look about average to Anthropic, Mistral, DeepSeek, and many others of that cohort despite having x100 the amount of resources?
What “we”? They’ve already raised billions, and I suspect they’re about to succeed at raising tens of billions more, despite the skepticism of random HN users.
The Unreasonable Effectiveness of Huge Sums of Money in the Natural Sciences
Unimaginable Sums of Money Considered Harmful
The long term future of LLMs sure looks like the LLMs themselves will be commodities and the real value will lie in the use of those LLMs to deliver value
AI progress is driven by strong valuable data. Detailed important conversation with a chatbot are much more valuable that quick search queries. As LLMs extend past web UIs, there is even more interaction data to capture and learn from.
The company that captures the most human-AI interaction data will have a TREMENDOUS moat.
I disagree, that phenomenon is tied to the social network like phenomena we saw with WhatsApp and Facebook and to the aggregator business model of Amazon and Google.
Mathematically we can describe the process by which these monopolies form as nodes joining graphs:
Each node selects graphs to connect to in such a way that the probability is proportional to the number of nodes in the graph.
Sure Amazon and google feature two types of nodes, but the observation still fits: Selling on Amazon makes sense if there are many customers, buying on Amazon makes sense if there are many offers.
OpenAIs business does not have this feature, it does not get intrinsically get more attractive by having more users.
Claude is noticeably better
The word "open" is still under threat in this scenario too.
The world‘s largest oil producer?
Models are commodities, even in the case Open ai goes through another major breakthrough nothing can stop some of their employees to run to other companies or founding their own and replicating or bettering the OpenAI results.
In fairness I realize that I don't use any of OpenAI's models. There are better alternatives for coding, translating or alternatives that are simply faster or cheaper (Gemini) or more open.
The best moats are scale (Walmart), brand (“Google” means search), network effects (Facebook, TikTok). None of those are perfect but all are better than just having better tech.
OTOH, WD40 has a technical moat since 1953, without a patent. There are a number of companies who rely on technical moat mixed with excellent technical image: Makita or Milwaukee Tool come to mind. You can have also a company based on technology moat that theoretically shouldn't exist (patents expired, commodity products), but it does (Loctite, 3M).
Eight racks of GB200's? You're talking about 1 megawatt of power. Well over that if you include PSU losses, cooling, and all the networking, storage, memory...
Yet Chrome for Google did help create a moat.
A moat that’s is so strong the DoJ is investigating if Chrome should be a forced divesture from Google/Aplhabet.
Note: I do generally agree with the article, but this also shows why you shouldn’t use analogies to reason.
The result is Chrome, Google invests in it because they don't want to be intermediation between them and eyeballs - it's a strategic play, not necessarily a direct money maker. So that's why they do it. But there is no moat, they have the number 1 browser because they spend enormous sums of money hiring top engineers to build the number 1 browser.
And this has been true of the browser for a long time, Internet Explorer won because they forced people to use it and used a tonne of anti-competitive practices to screw the competition. Firefox still managed to disrupt that simply by building a better product. This is the clear evidence there is no moat - the castle has been stormed repeatedly.
OpenAI can't do anything comparable to Google at this point because they have no other product. If anything they're more like Netscape.
This is getting so repetitive now that it is stated as a truism.
Isn't it the same bet yahoo was betting on in 2000 that it would win because their product branding is better? And now, Yahoo's and Microsoft's search engine is worse than Google from 2 decades ago.
The so-called open source models are getting better and better and even if OpenAI suddenly discovered some new tech that would allow for another breakthrough, it will be immediately picked up by others.
The data backs it up, Anthropic make most of their revenue from API while ChatGpt makes most of its revenue from the plus plan.
SamA wants to take everything the non-profit built and use it directly in HIS for profit enterprise. Fuck him.
The question is - why would that one company want this hot take out there?
> OpenAI’s board now stating “We once again need to raise more capital than we’d imagined” less than three months after raising another $6.6 billion at a valuation of $157 billion sounds alarmingly like a Ponzi scheme
Ponzi scheme. If he's shilling something I guess it's "shorting".
I don't know who this Gruber guy is, but it's relieving to hear at least someone talk some sense about the ludicrous levels of investment being poured into something that most users go "heh that's neat" and would never consider paying for.
LLMs and AI is not where Meta adds value to the market. They add value via advertising. Therefore, AI is not Meta's product, and thus Meta should aim to make AI as cheap as possible.
They did the same thing for infra. Meta doesn't sell cloud computing, so they want to make infra as cheap as possible.
LLMs in their current form are very useful tools for many people. Most programmers I know use them daily. I have even friends who aren't tech savvy who paid the subscription to ChatGPT and use it all the time.
If I have the LLM translate a text from French to English... what is there to learn from that? Maybe the translation is great maybe it's awful, but there's no "correct" translation to evaluate the LLM against to improve it.
If I ask the chatbot for working code and it can't provide it, again, there's no "correct" code to train it against found in the conversation.
If I ask an LLM to interpret a bible passage, whether it does a good job or a terrible job there's no "correct" answer that the provider has to use as the gold standard, just the noise of people chatting with arbitrary answers.
When the big companies say they're running out of data, I think they mean it literally. They have hoovered up everything external and internal and are now facing the overwhelming mediocrity that synthetic data provides.
1) B2B: Reliable, enterprise level AI-AAS
2) B2C: New social network where people and AIs can have fun together
OpenAI has a good brand name RN. Maybe pursuing further breakthroughs isn't in the cards, but they could still be huge with the start that they have.
Amazon is famous for making losses after being publicly listed. Also, it was remiss of grandparent to not note that Amazon's losses were intentional for the sake of growth. OpenAI has no such excuse: their losses are just so that they stay in the game; if they attempted to turn profitable today, they'd be insolvent within months.
Well trodden and failing path. You misread the article if you considered it any endorsement of OpenAI’s plan.
[0] https://archive.seattletimes.com/archive/19970102/2516784/sp...
Granted I'm not sure there's much of anything to substantiate this, but I imagine Apple would know better from competitive intel.
(I feel a bit bad that my mind also immediately connects "Gruber" to "Apple" in less-than-savory ways, but alas, that's the reputation he built for himself.)
Yes this! I won't say how I've come to know, but if you have ever wondered "is this guy on the take from Apple as part of their fuckery?" - the answer is Yes.
Is that actually true?
Walmart and Target were far better than Amazon at logistics at the beginning, but they couldn’t execute (or didn’t focus on) software development as well as Amazon.
Meanwhile, Amazon figured out how to execute logistics just as good or better than the incumbents, giving them the edge to overtake them.
They were built for people to come to their store, and the website was a second class citizen for a long time.
But that was Amazon's bread and butter. They built that fast-shipping moat as a pretty established company, and the big retailers were caught off guard
Walmart is still the largest company in the world by revenue, with Amazon at its heels, with Amazon's profit beating out Walmart's.
A lot of this thread, I think, is just fantasy land that Amazon is somehow:
1. Destroying Walmart and Target in a way they can't compete.
2. Is more tech savvy than Walmart and Target.
C'mon, read the history of Walmart, it's who put technology into retail.
Walmart is not an Internet company. It is definitely a tech company. It's just that its tech is no longer super cool.
But for whatever reason, they took their foot off the pedal, and allowed Amazon to use the next step (networking technology and internet) to gain an edge over the now incumbent Walmart.
> 2. Is more tech savvy than Walmart and Target.
The market (via market cap) clearly thinks Amazon has lots more potential than its competitors, and I assume it is because investors think Amazon will be more successful using technology to advance.
Edit: Jay Leno, 1999: https://www.unilad.com/film-and-tv/news/jeff-bezos-audience-...
I was only a teenager, but I assume there had been lots of businesses throughout the course of history that took more than 5 years to be profitable.
The evidence is that investors were buying shares in it valuing it in the billions. Obviously, this is 1999 and approach peak bubble, but investing into a business for multiple years and waiting to earn a profit was not an alien idea.
I especially doubt it was alien to a mega successful celebrity and therefore I would bet Jay Leno is 100% lying about “not understanding” in this quote, and it is purely a setup for Bezos to respond so he can promote his business.
> “Here’s the thing I don’t understand, the company is worth billions and every time I pick up the paper each year it loses more money than it lost the year before,” says the seasoned talk show presenter, with the audience erupting into laughter off screen.
Not if regulation prohibits LLMs from China, which isn't that far fetched to be honest.
I think LLM will turn into a commodity product and if you want to dominate with a commodity product, you need to provide twice the value at half the cost. Open AI will need a breakthrough in reliability and/or inference cost to really create a moat.
If you mean trying to stop GPUs getting to China, US already has tried that with specific GPU models, but China still gets them.
Seems hard/impossible to do. Even if US and CCP were trying to stop Chinese citizens and companies doing LLM stuff
(And a lot of stores like Ubisofts or EA's were very feature lite tbh.)
They have had years and still not even close, from both the consumer side and the developer side.
People citing their current high prices would be right. But human brains are smarter than chatgpt, and vastly more energy efficient. So we know it's possible.
Does this oversimplify?
Amazon also has a significant advantage in its logistics that underpin their entire business across the globe and that nobody else can match.
You're also wrong about how Google maintains its monopoly, or Microsoft.
All I see is bias and an unwillingness to understand, well, any of the relevant topics.
The problem with ChartGPT is that that dont own any platform. Which means out of the 3 Billion Android + Chrome OS User, and ~1.5B iOS + Mac. They have zero. There only partner is Microsoft with 1.5B Window PC. Considering a lot of people only do work on Windows PC I would argue that personalisation comes from Smartphone more so than PC. Which means Apple and Google holds the key.
Also companies will be (and are) bundling these subscriptions for you, like Raycast AI, where you pay one monthly sum and get access to «all major models».
That is one of the reason why ChatGpt has a desktop App, so that users can directly interact with it and give access to users files/Apps as well.
>> When the big companies say they're running out of data, I think they mean it literally. They have hoovered up everything external and internal and are now facing the overwhelming mediocrity that synthetic data provides.
> Digital data are only a tiny part of the influx of information that people interact with.
I suppose competitor would have to be really good on those times most users need something better.
So it is the brand and familiarity. It would need to get really bad even on most basic things to be replaced.
What's the expected return on investment for "intelligence"? This is extremely hard to quantify, and if you listen to the AI-doomer folks, potentially an extremely negative return.
Indeed. And that asymmetry is what makes a market: people who can more accurately quantify the value or risk of stuff are the ones who win.
If it were easy then we'd all invest in the nearest AI startup or short the entire market and 100x our net worth essentially overnight.
But only metaphorically the equivalent, as the maximum downside is much worse than that.
Will it bring untold wealth to its masters, or will it slip its leash and seek its own agenda.
Once you have an AI that can actually write code, what will it be able to do with its own source? How much better would open AI be with a super intelligence looking for efficiencies and improvements?
What will the super intelligence (and or its masters) do to build that moat and secure its position?
There are not that many unicorns these days, so anyone missing out on last unicorn decades are now in immense FOMO and is willing to bet big. Besides, AGI is considered(own opinion) personal skynet(wet dream of all nations’ military) that will do your bidding. Hence everyone wants a piece of that Pie. Also when the bigCo(M$/Google/Meta) are willing to bet on it, makes the topic much more interesting and puts invisible seal of approval from technically savvy corps, as the previous scammy cryptocurrency gold rush was not participated by any bigCo(to best of my knowledge) but GenAI is full game with all.
The fact that you can state this risk means that market participants already know this risk and account for it in their investment model. Usually employees are given stock options (or something similar to a vesting instrument) to align them with the company, that is, they lose[^1] significant wealth if they leave the company. In the case of OpenAI: "PPUs vest evenly over 4 years (25% per year). Unlike stock options, employees do not need to purchase PPUs […] PPUs also are restricted by a 2-year lock, meaning that if there’s a liquidation event, a new hire can’t sell their units within their first 2 years."[^0]
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[0]: https://www.levels.fyi/blog/openai-compensation.html
[1]: Ex-OpenAI employee reported losing 85% of his family's net worth. https://news.ycombinator.com/item?id=40406307
So what people bothers writing down are just a pale reflection of what has been, the reader has to relies on his experience and imagination to recreate it. If we take drawing for example, you may read all the books on the subject, you still have to practice to properly internalize that knowledge. Same with music, or even pure science (the axioms you start with are grounded in reality).
I believe LLMs are great at extracting patterns from written text and other forms of notation. They may be even good at translating between them. But as anyone who is polyglot may attest, literal translation is often inadequate because lot of terms are not equivalent. Without experiencing the full semantic meaning of both, you'll always be at risk at being confusing.
With traditional software, we were the ones providing meanings so that different tools can interact with each other (when I click this icon, a page will be printed out). LLMs are mostly translation machines, but with just a thin veneer of syntax rules and terms relationships, but with no actual meaning, because of all the information that they lack.
As another example, LLMs are kind of magical when it comes to what I'd call "bad memory spelunking". Is there a video game, book, or movie from your childhood, which you only have some vague fragments of, which you'd like to rediscover? Format those fragments into a request for a list of candidates, and if your description contains just enough detail, you will activate that semantic understanding to uncover what you were looking for.
I'd encourage you to check out 3blue1brown's LLM series for more on this!
I think it's true they lack a lot of information and understanding, and that they probably won't get better without more data, which we are running out of. That's sort of the point I was originally trying to make.
And would AI that is tied to some interface that provides lock-in even be qualified to be called general? I have trouble pointing my finger on it, but AGI and lock-in causes a strong dissonance in my brain. Would AGI perhaps strictly imply commodity? (assuming that more than one supplier exists)
The exponential gains would come from increasing penetration into existing labor forces and industrial applications. The first arriver would have an advantage in being the first to be profitably and practically applicable to whatever domain it's used in.
Only if they are much cheaper than the equivalent work done by humans, but likely the first AGI will be way more expensive than humans.
Alas I am still without my mythical city of gold.
I was very confused at this point because I haven't really seen X as a competitor to Google's ad business, at least not in investment and value prop... Then I saw you were using X as a variable...
China's biggest challenge ATM is that they do not yet economically produce the GPUs and RAM needed to train and use big models. They are still behind in semiconductors, maybe 10 or 20 years (they can make fast chips, they can make cheap chips, they can't yet make fast cheap chips).
i dont believe they're as behind as many analysis deems. In fact, making it illegal to export western chips to china only serves to cause the mother of all inventions, necessity, to pressure harder and make it work.
You don't need the most efficient chips to train LLMs. those much slower chips (e.g. those made by Huawei) will probably take longer for training and they waste more electricity and space. but so what?
Look at how competitive chinese EVs are, and no amount of tarriffs are gonna stop them from dominating the market - even if americans prevent their own market from being dominated, all of their allies will not be able to stop their own.
LLMs will become the ultimate propaganda tool (if they aren't already), and I don't see why governments wouldn't want to have full control over them.
Fwiw, I don't believe that there are any AI doomers. I've hung out in their forums for several years and watched all their lectures and debates and bookmarked all their arguments with strangers on X and read all their articles and …
They talk of bombing datacentres, and how their children are in extreme danger within a decade or how in 2 decades, the entire earth and everything on it will have been consumed for material or, best case, in 2000 years, the entire observable universe will have been consumed for energy.
The doomers have also been funded to the tune of half a billion dollars and counting.
If these Gen-X'ers and millennials really believed their kids right now were in extreme peril due to the stupidity of everyone else, they'd be using their massive warchest full of blank cheques to stockpile weapons and hire hitmen to de-map every significant person involved in building AI. After all, what would you do if you knew precisely who are in the groups of people coming to murder your child in a few years?
But the true doomer would have to be the ultimate nihilist, and he would simply take himself off the map because there's no point in living.
You're definitely mixing things up, and the set of things may include fiction. 2000 years doesn't get you out of the thick disk region of our own galaxy at the speed of light.
> The doomers have also been funded to the tune of half a billion dollars and counting.
I've never heard such a claim. LessWrong.com has funding more like a few million: https://www.lesswrong.com/posts/5n2ZQcbc7r4R8mvqc
> If these Gen-X'ers and millennials really believed their kids right now were in extreme peril due to the stupidity of everyone else, they'd be using their massive warchest full of blank cheques to stockpile weapons and hire hitmen to de-map every significant person involved in building AI. After all, what would you do if you knew precisely who are in the groups of people coming to murder your child in a few years?
The political capital to ban it worldwide and enforce the ban globally with airstrikes — what Yudkowsky talked about was "bombing" in the sense of a B2, not Ted Kaczynski — is incompatible with direct action of that kind.
And that's even if such direct action worked. They're familiar with the luddites breaking looms, and look how well that worked at stopping the industrialisation of that field. Or the communist revolutions, promising a great future, actually taking over a few governments, but it didn't actually deliver the promised utopia. Even more recently, I've not heard even one person suggest that the American healthcare system might actually change as a result of that CEO getting shot recently.
But also, you have a bad sense of scale to think that "half a billion dollars" would be enough for direct attacks. Police forces get to arrest people for relatively little because "you and whose army" has an obvious answer. The 9/11 attacks may have killed a lot of people on the cheap, but most were physically in the same location, not distributed between several in different countries: USA (obviously), Switzerland (including OpenAI, Google), UK (Google, Apple, I think Stability AI), Canada (Stability AI, from their jobs page), China (including Alibaba and at least 43 others), and who knows where all the remote workers are.
Doing what you hypothesise about would require a huge, global, conspiracy — not only exceeding what Al Qaida was capable of, but significantly in excess of what's available to either the Russian or Ukrainian governments in their current war.
Also:
> After all, what would you do if you knew precisely who are in the groups of people coming to murder your child in a few years?
You presume they know. They don't, and they can't, because some of the people who will soon begin working on AI have not yet even finished their degrees.
If you take Altman's timeline of "thousands of days", plural, then some will not yet have even gotten as far as deciding which degree to study.
Anyway,
> You're definitely mixing things up, and the set of things may include fiction. 2000 years doesn't get you out of the thick disk region of our own galaxy at the speed of light.
Here's what Arthur Breitman wrote[^0] so you can take it up with him, not me:
"
1) [Energy] on planet is more valuable because more immediately accessible.
2) Humans can build AI that can use energy off-planet so, by extension, we are potential consumers of those resources.
3) The total power of all the stars of the observable universe is about 2 × 10^49 W. We consume about 2 × 10^13 W (excluding all biomass solar consumption!). If consumption increases by just 4% a year, there's room for only about 2000 years of growth.
"
About funding:
>> The doomers have also been funded to the tune of half a billion dollars and counting.
> I've never heard such a claim. LessWrong.com has funding more like a few million
" A young nonprofit [The Future of Life Institute] pushing for strict safety rules on artificial intelligence recently landed more than a half-billion dollars from a single cryptocurrency tycoon — a gift that starkly illuminates the rising financial power of AI-focused organizations. "
---
[^0]: https://x.com/ArthurB/status/1872314309251825849
[^1]: https://www.politico.com/news/2024/03/25/a-665m-crypto-war-c...
Maybe I'm a glass-half-full sort of guy, but everyone dying because we failed to reverse man-made climate change doesn't seem strictly better than everyone dying due to rogue AI
Stupid squared: We die because we gave the AI the order of reverting climate change xD.
But also: I think it extremely unlikely for climate change to do that, even if extreme enough to lead to socioeconomic collapse and a maximal nuclear war.
Also also, I think there are plenty of "not literally everyone" risks from AI that will prevent us from getting to the "really literally everyone" scenarios.
So I kinda agree with you anyway — the doomers thinking I'm unreasonably optimistic, e/acc types think I'm unreasonably pessimistic.
It’s slow and painful, but the expense is driving some customers away.
For starters they have delivery down. In major cities you can get stuff delivered in hours. That is crazy and hard to replicate.
They have a huge inventory/marketplace. Basically any product is available. That is very difficult to replicate.
Amazon’s vertical integration is their mote.
It is widely understood that you really can't compete with "as good as". People won't leave Google, Facebook, etc. if you can only provide a service as good as, because the effort required to move would not be worth it.
> if you show me a product that works just as well as ChatGPT but costs less--or which costs the same but works a bit better--I would use it
This is why I believe LLMs will become a commodity product. The friction to leave one service is nowhere near as as great as leaving a social network. LLMs in their current state are very much interchangeable. OpenAI will need a technological breakthrough in reliability and/or cost to get people to realize that leaving OpenAI makes no sense.
Sure you can, that's why there are hundreds if not thousands of brands of gas station. The companies you list are unusual exceptions, not the way things usually work.
I said; >> There is no technical moat, but that doesn't mean there isn't a moat.
Meaning that just because the moat is not technical doesn't mean it doesn't exist.
Clearly Amazon, Google, Facebook etc have moats, but they are not "better software". They found other things to act as the moat (distribution, branding, network effects).
OpenAI will need to find a different moat than just software. And I agree with all the people in this part if the thread driving that point home.
OpenAI right now some novel combination of a worker bee and queryable encyclopedia. If they are trying to make a marketplace argument for this, it would be based on their data sources, which may have a similar sort of first-mover advantage as a marketplace as they get closed off and become more expensive (see eg reddit api twitter api changes), except that much of those data age out, in a way that sellers and buyers in a marketplace do not.
The other big difference with a marketplace is constrained attention on the sell/fulfillment side. Data brokers do not have this constraint — data is easier to self-distribute and infinitely replicable.
You've basically described Temu
Not to mention they’ve created a pretty formidable enterprise sales function. That’s the real money maker long term and outside of Google, it’s hard to imagine any of the current players outcompeting OpenAI.
the recent release of deepseek v3 is a good example, o1 level model trained under 6 million USD, it pretty much beat openai by a large margin.
(Sure you might say I'll subscribe to both, $20, $40, it's no big deal - but the masses won't, people already agonise over and share (I do too!) video streaming services which are typically cheaper.)
More interestingly to your thread is how does Craigslist supplant print classifieds, which then is challenged if not supplanted by Facebook Marketplace. Both the incumbents had significantly better marketplace dynamics prior to being overtaken.
Defaults are powerful over time.
Does the average Temu user care about the company's ethical problems? Does the average Amazon user?
"China is set to account for the largest share of clean energy investment in 2024 with an estimated $675 billion, while Europe is set to account for $370 billion and the United States $315 billion."
https://www.reuters.com/sustainability/climate-energy/iea-ex...
The real possibility exists that it would be better to be an independent 'second place' technology center (or third place, etc) than a pure-consumer of someone else's integrate tech stack.
China decided that a long time ago for the consumer web. Europe is considering similar things more than ever before. The US is considering it with TikTok.
It's not hard to see that expanding. It's hard to claim that forcing local development of tech was a failure for China.
Short of a breakthrough that means the everyday person no longer has to work, why would I rather have a "better" but wholly-foreign-country-owned, not-contributing-anything-to-the-economy-I-participate-in-daily LLM or image generator or what-have-you vs a locally-sourced "good enough" one?
this is the exact same story told to the public when Google was kicked out of China. you are just 15 years late for the party.
OpenAI is going to be beaten on price, wait and see.
EDIT: Oh it did, wow, and it's better than Claude! Fantastic, this is great news, thank you!