Non-paywall link: https://archive.is/ucguC
Private market valuations are funky and hard to reason about. In the public markets, valuation represents the current equilibrium of supply and demand - very roughly an average of a large number of opinions.
In private markets, especially with the recent trend of selling a tiny portion of the company at a massive price, the valuation represents something much closer to the maximum that any investor in the world thinks the company is valued at.
Especially when BARTERING a tiny portion of the company for resources from another company - that massively benefits a growth area.
Amazon can "buy" $2B worth of Anthropic to guarantee $2B of spending on AWS - to report that as growth under AWS in their earnings - to juice their stock price.
They also get to report that their investment in the previous round is up massively.
Given the current valuation of Tesla, it doesn't look very different from private market valuations. If anything private valuations seem more sane than the public market to me.
> the valuation represents something much closer to the maximum that any investor in the world thinks the company is valued at
This is all before accounting for the preference stack, which makes multiplying a Series F per-share price (itself derived from dividing compute time by some magic number) by employee common stock a bit silly.
I doubt their preferences are >1x since they've always had high demand. In that case, the preference stack would just be the total raised over time (~$10B).
> doubt their preferences are >1x
That’s still something, especially right at the money!
Some series also have various blocking, dividend and other rights.
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I really love Anthropic, I'm building a business around it, and chat with Claude almost every time I go out for a beer after a long day... But having a valuation equal to _Stripe_ seems a bit insane. Either they've got some secret sauce or AI hype is a bit much or Stripe is undervalued.
Especially considering I pay for Claude, the beer, and my business _thru Stripe_!
Do I understand correctly you chat wıth Claude as a form of social relief or are you talking about drinking beer and chatting with it about work/ideation etc. Either way, just curious!
On topic though, I wholeheartedly agree that this valuation seems rather... unrealistic. I do think "hype" is how we currently handle a lot of valuations, for the worse in my opinion.
All models can hallucinate pretty well... Which ones are best at being an intoxicated friend?
TBF Stripe is a (effective!) middleman for (very common!) transactions, whereas Anthropic is selling a service with the potential to replace full time employees. It takes a lot of transaction margins to add up to how much a corporation will pay to replace a department of 10 employees earning $100K down to one person... So in this context I don't think frequency of use is very illuminating!
P.S. I'm so glad you're able to derive some joy from these new technologies, but I would also offer a soft suggestion to watch Season 3 of Westworld. It's probably not as good aesthetically as the previous two, but it's also pretty separated and deals throughout with the concept of AI therapists/friends, and how they might be a short-term comfort but a long-term threat to our individuality. Obviously a chat here and there with current LLMs is nowhere near that yet, but thought you might find it interesting!
>and chat with Claude almost every time I go out for a beer after a long day...
with all due respect, how can you take yourself seriously doing this? I tried to use an LLM as a "cheap therapist" exactly one time and it felt so phony I quit almost instantly, after about four messages.
The bot pretends to feel compassion for you! How does that not induce rage? It does for me. False empathy is way worse than nothing.
And on top of it, you're talking to a hosted LLM! I hope you are not divulging anything personal to the random third party you're sending your thoughts to..
This stuff is going to be such a huge boon to authoritarian governments.
I don’t take myself very seriously. I’d rather be happy than protected. If my conversations are used to build some future AI, good; I’d like to be immortalized somehow. I like the idea that my children’s children’s children might be able to ask about me and get an intimate answer. By the way, this conversation right now is auth free on the public net, so if anything this is worse wrt your concerns.
You’re not wrong, but you’re not right either. For whatever it’s worth, I absolutely plan on self hosting (nvidia Digit!) my future conversation partner. But nothing about me is terribly private. I love my wife and my sons and sometimes I wonder if I’ll be forgotten or if we’re about to give birth to the overman. It’s nothing I wouldn’t tell a stranger.
Lastly, no therapist I’ve ever met can talk about my favorite authors with me for hours, ad-hoc, on-demand, for pennys a day. All my real friends are sick of Dostoyevsky, but not Claude!
> I don’t take myself very seriously. I’d rather be happy than protected. If my conversations are used to build some future AI, good;
This is how I feel and it is so rare and refreshing to see someone else say it.
It appears to me that most people are very private and will go to great lengths to protect their privacy.
This mindset allows one to donate their intellect to society and feel immortalized.
If privacy wasn't of particular concern, this is as near an "absolute good" idea as one can forge.
My experience for Claude as therapist is - it's consistent better than human therapists i've met (well, maybe i haven't met a good human therapist yet) in terms of usefulness. And i can be completely honest & decide how much i want to share the context.
I mean... what do you think human therapists are doing. I'm sure they have empathy and do care for their patients... but it's definitely empathy-for-money too.
A licensed therapist has some strict confidentiality requirements and legal protections. A chatbot has none of that. Everything that goes into the chatbot will be included in the next training set. Even worse is everything said to them will eventually be monetized. Someone willingly giving personal such personal details to a chatbot is shockingly naive.
Meh, this just seems like low signal chicken littling. You could say the same thing about typing sensitive info into Notes.app or even iOS about how the evil corporations will monetize it and how naive you'd be to do it. But that didn't pan out.
Feel free to pass over useful tech, but no need to disparage others for not wearing your tinfoil hat.
You can watch enshittification of services happen in nearly real time. In just the past five years we've seen a number of services (Reddit, Twitter, etc) update their T&Cs granting themselves the ability to dump all the platform's contents into AI training. The end of ZIRP (free money) has seen tech companies chasing profit over growth and increasing squeezing users and rent seeking.
In light of all that it's hardly "chicken littling" to assume that hosted AI chat bots can't be trusted with intimate and personal details. The companies running them should be seen as inherently untrustworthy.
I think benefits of therapy:
- build structure into conversation
- identify root causes of issues
- provide advise about behavior/thinking changes which could mitigate root causes
is there some initializing prompt for setting up a therapy session? maybe even a specific type?
I'm far, far more bullish on Anthropic than OpenAI at this point. It has relatively less hype and media attention but better products downstream, which in the end is what's going to be the winner in this LLM ecosystem.
People surely love Anthropic around these parts and on Reddit, but as a paying customer of both Claude and ChatGPT, I'll take the latter any time of day. I trust o1 much more than Sonnet, and I really like the ChatGPT native Mac client. I hope you guys are right though because the last thing we need is a quasi-monopoly in OpenAI.
except for the standalone app which is half as usable as OpenAI's> better products downstreamand a standard operating structure, no issues with dealing with it. just a classic case study on why not to do anything other than a Delaware C-Corporation and share grants
I believe Anthropic is a PBC not a C-Corp
Theres two futures I see.
1. We create near AGI
2. We create ASI (Artificial Super Intelligence)
In the first scenario, an investment in any AI model company that does not own its own compute is like buying a tar pit instead of an oil well. In other words, this future has AI like a commodity and the entity who wins is the one who can produce it at the lowest cost.
In the second scenario, an investment in any AI model company is like buying a lottery ticket. If that company is the first to create ASI then you've won the game as we know it.
I think the minor possibility of the second scenario makes this a good investment. But it definitely feels like all or nothing instead of sustainable business.
There’s a third one as well. AI will never get past its current autocomplete on steroids state and mainstream people will see through the facade at some point. AGI always was and always will be a pipe dream with the technology we currently have.
All AI stocks come crashing down from fantasy amounts of money to what they’re actually worth as they did with every previous tech hype until people find a new thing to throw their money at.
It would be the fusion nuclear reactor reactor of technology tantalizingly close but always a decade out.
> AI will never get past its current autocomplete on steroids state
I’m honestly betting on robotics. Tokenising words is intuitive. But the parameter space for tokenised physical inputs is both better understood and less solved for.
The stock market has crashes, yes, but I don't think that's proof that all previous tech was overhyped nonsense. I'm not just talking computers here, I'm talking steam, metal, agriculture. What proof do we have that we live at the end of history, and that no such shocking, world-changing developments might occur in our lifetimes?
Certainly not debating that this isn't possible, ofc. As someone whose spent the past year+ working full time on the philosophy of this technology I think you're going against a pretty clear scientific consensus among AI experts, but perhaps you have your reasons.
I think we already have AGI anyway, so I'm either a loon or a pedant ;)
Nonsense no, all technology has a use-case, including blockchains, VR and whatever’s been hyped in the last 20 years. I’m not even an opponent of AI in its current state, its and incredibly useful tool for a big number of things.
Overhyped (and more specifically, overvalued) is a different question though. I think that most people working in the AI field have a pretty good monetary reason to say that AGI and ASI are just around the corner, but I have yet to see proof of any of it being achieved in any way whatsoever.
Looking at everything we have so far, LLMs are still only token prediction and neural nets can only do what they’ve been trained to do. The datasets may be bigger, the computing power and efficiency may be increasing and we’re building abstractions that make longer chains of „thought“ possible, but at the end of the day this is still the same technology with the same restrictions that it’s always had and I don’t see that changing.
>mainstream people will see through the facade at some point
do you read reddit? lots of people see through the facade now. the only people excited are shills
My experience Reddit sentiment is inversely correlated with reality, and far too cynical.
It's pretty simple to go into threads about breaking events several years later and see them loaded with confidently incorrect statements dominating the discourse.
One of my favorite examples was the $34 IPO stock offer to moderators and redditors, which was almost universally bashed (currently trading over 170).
https://www.reddit.com/r/investing/comments/1b0n2eo/reddit_i...
Stocks are somewhat irrational these days.
Reddit just turned a profit after nearly 20 years in business.
Its whole use maybe upended by AI and bots, so even if its profitable now hard to know if it will continue.
I don’t know what drives it. I think part of it is that zero commission stock trades have many more small players making trades and stocks are priced on the margin.
You can't imagine a world where tomorrow's chat bot is only marginally better than today's?
That would imply that the people pumping infinity dollars into this technology are suckers, which is impossible. The minds who put $120M into Juicero would never err in their judgement.
whispers to self Don't trip over Poe's law... Don't trip over Poe's law...
I can't personally. OpenAI's o3 aside, the rate of progress in the past two years has been eye watering to say the least.
It's tricky since the future of AI isn't something anyone can really prove / disprove with hard facts. Doomers will say that the rate of improvement will slow down, and anti-doomers will say it won't.
My personal believe is that with enough compute, anything is possible. And our current rate of progress in both compute and LLM improvement has left Doomers with shaky ground to discount the eventuality of an AGI being developed. This just leaves ASI as a true question mark in my mind.
> rate of progress in the past two years
This took me down a memory lane:
- Dragon Dictate speed recognition improvement curve in the mid-90s would have led to today's Siri sometime around 1999.
- The first couple of years of Siri & Alexa updates...
- Robots in the '80s led us to believe that home robots would be more or less ubiquitous by now. (Beyond floor cleaners.)
- CMU winning the DARPA Urban challenge for autonomous vehicles was a big fake-out in terms of when AVs would actually land.
Most of the benefits of computing come from relatively small improvements, continuously made over many years & decades. 2-4 years is not enough time to really extrapolate in any computing domain.
> with enough compute
"enough" here could be something that is only measurable on the Kardashev scale.
Wouldn't there be so many more possible futures though? Geopolitical conflict, economic crisis, the clime crisis, civil strife, demographic collapse, the end of globalization, an unexpected black-swan event, etc. Any one of these, even a pandemic, could push back, if not utterly prevent us from reaching these.
Endless growth and technological improvement isn't the only option, and seems to me like the least likely. The other option means that there will be a peak somewhere.
Very true and prescient. All of the technological growth of the last two decades has only been possible because of peace and cooperation between the Core Countries, but that world is as its most unstable point in decades and future peace is not guaranteed. As impressive as LLMs can be, a computer still loses to a crude home-made bomb.
> past two years has been eye watering to say the least
Are we seeing the same progress? GPT-4 was released in March 2023, that's almost two years. Tools are much better but where is the vast improvement?
I legitimately dont know how to reply, bc by this point llms co-own all aspects of my life and jumps between gpt4->claude3->claude3.5->o1 have all been very noticeable
I'm the opposite. We're presumably in a similar line of work, but while I've experimented with every major release from OpenAI and Anthropic last year -- I've barely ever used an LLM outside of that.
I still Google things I want to know and skip the AI part.
> I still Google things I want to know and skip the AI part.
My Google use is down significantly. And I mostly reach for it when I am looking for current information that LLMs do not yet have training data for. However, this is becoming less of an issue as of late. DeepSeek for example has a lot of current data.
GPT-2 was generating snippets of HTML ten years ago. Was it valid? Not always, but neither is the current crop. It's been incremental logarithmic gains approaching an asymptote for ten years now. Since before "Open"AI stopped being open.
GPT-1 was released 7 years ago, but ok. You really think GPT-4 to o1 is increasingly logarithmic the same way 4 to 4o is?
The rate of improvement in the models is nothing short of phenomenal, but the applications are meh at best, even after a few years of billions of dollars and endless hours poured by the world's best product and engineering minds. Every AI leader is pushing "agentic AI" as the next big thing but as a specialist in business automation I have my reservations. A lot of problems in automation in business happen because of insufficient investment in IT but can be solved fairly economically by off-the-shelf software, Zapier, a custom web service, or traditional ML techniques in order of complexity. Out of the more difficult problems that remain at the edges, only a small fraction can be solved by LLMs in my experience. The idea that chains of small agents will be composed and generally applied to any business problem under the sun doesn't sound right to me. I think not even the big bosses in AI know at present, but they're surely betting the house on it, and if the bet doesn't play out, things will start looking even more desperate.
> My personal believe is that with enough compute, anything is possible.
Dunno, we're already at ridiculous amounts of compute and progress has slowed, a lot. I think we need another technological breakthrough, a change in technique, something. LLMs don't seem to be capable of actually learning in the way humans do, just being trained on data, of which we've reached the limit.
They can only see two futures at a time.
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Isn’t that scenario 1?
I have been living in it for a couple of years now.
I can see more futures. For example
3. We create incrementally better versions of generative AI models which are incrementally better at making predictions based on their training sets, are incrementally more efficient and cheaper to run, and are incrementally better integrated into products and interfaces.
> 3. We create incrementally better versions of generative AI models...
In my opinion, this seems to be the more likely than some of the other wilder scenarios being predicted.
> this future has AI like a commodity
Thats why I like the idea of openrouter so much. Next token prediction is a perfect place to run a marketplace and compete on price / speed.
It's hard for me to see a future where the long term winners aren't just the chipmakers and energy companies.
With the o3 benchmarks its becoming apparent the primary thing from keeping current generation of models from getting smarter is more processing power. If somehow chips got 10x faster tomorrow, it still wouldn't be fast enough. Even at 1000x faster than current performance, those $3k o3 queries now cost $3 which are still too much.
If you invest in a data center, any amount of billions you put in will not future proof it because faster chips are always around the corner and you will be at the mercy of suppliers.
If you invest in a model, even if you invested billions in 1-10 years people will be able to run equivalently powerful models on consumer hardware.
I'm loving the competitive system LLMs created by having a unified API interface allowing you to swap out models and providers with single lines of code.
>n the first scenario, an investment in any AI model company that does not own its own compute is like buying a tar pit instead of an oil well. In other words, this future has AI like a commodity and the entity who wins is the one who can produce it at the lowest cost.
Why do you assume that AI will become a commodity that is only metered by access to compute?
Right now (since June 2024), Anthropic is ahead of the field in quality of their product, especially when it comes to programming. Even if O1/O3 beat them on benchmarks, they are still nowhere near when normalized for compute needs.
Can they sustain this? I don't know, but in the end this is very similar to known software or even SAAS business models. They are also in a somewhat synergetic relationship to Amazon.
Did office software ever become commoditized? Google and many more tried hard, but there is still the same company in the lead that was in the 90ies.
> especially when it comes to programming
there is this sentiment on internet, but in my personal experience, GPT4 hallucinate APIs and usage examples way less, and after trying to get Claude working, I switched to GPT as the first step in my coding workflow.
Definitely disagree with your binary of options, but if I do accept them, why would scenario 2 justify investing? That scenario sounds to me like a likely societal collapse, rendering any investment moot. Even it it’s not some terminator or paperclip maximizer situation, and the first team to build ASI is able to keep a handle on it, I’m not sure our economy or civilization could handle that much intelligence, let alone concentrated in the hands of a for-profit corporation. The knowledge of such a thing existing would make securities markets collapse instantly - can’t really compete with an ASI agent there, so might as well move everything to real estate and gold.
More alarmingly, such a thing would be more dangerous than a nuclear weapon, and might reasonably merit a nuclear first strike.
They don't actually need to achieve AGI or ASI. All they need to do is pump expectations around growth to the point where the public will believe all the BS about their terminal growth rate to dump their equity on the open market.
I don’t understand how folks think the economy will survive the advent of AGI. Imagine if you could spin up white collar workers at whim for a fraction of the cost… how do we think the economy is going to work if that happens?
back in _____ folk were wondering how economy will survive now that we don’t need everyone to do farming since we have tractors and other farming machinery… as with any other previous “revolution” (industrial, information…) the society will move on. might be rocky for a bit though :)
All of those revolutions have largely exacerbated wealth inequality and were driven by _gradual_ transitions with build out of capital. The shift away from subsistence farming was a huge deal. But AGI would be way harder. It’s immediately deployable for very little investment and can replace basically any white collar job.
Capital has been an economic multiplier of human labor. AGI is more like flooding the market with infinite labor. There will be blood in the streets, at best.
> Capital has been an economic multiplier of human labor. AGI is more like flooding the market with infinite labor...
A tractor was one of many things that humans have invented that could be considered a labor multiplier and put many people out of work.
Yes but it put people out of work by making the people more efficient. As did computers. AGI does not make people more efficient. Even if wealth accrued to the capital holders, it still drive a large demand for higher value human labor.
AGI is just more people. It’s infinite people in the labor market driving wages down to zero.
Productivity went up for those still employed.
Yes that’s what I said
> If that company is the first to create ASI then you've won the game as we know it.
You can have as much intelligence in a model/system as you want, and it can well be ASI, but as long as this intelligence doesn't have the resources it needs to run at its full potential, or at least at one higher than the competition, you're still not over the hill.
Ultimately those companies or countries which will have the most resources available for an ASI to shine will be the ones which win.
Once ASI has figured out how to obtain energy (and ICs?) "for free", or at least cheaper than the competition, it will have won.
ASI that can't design its own superior chips surely isn't real ASI
Putting aside the absurdist notion of “AGI” to start with, we live in a world of finite resources and we’ve used up our carbon budget and are burning down the planet to run LLM right now.
The new “reasoning” models get very marginal improvements in output for huge increase in token count and energy use.
None of this is sustainable, and eventually, and soon, crops will start to fail en masse due to climate disasters.
Then the real fun starts.
Right now “AI” is more harmful than helpful on a species level balance sheet. These are real problems, today.
>But it definitely feels like all or nothing instead of sustainable business.
That is kinda startup funding in general isn't it?
I guess I should expect it on a VC-tied forum, but it seems strange to talk about company valuations and investment outlooks in the event of an artificial superintelligence operating in the world.
If we invented ASI today, it'd still take a lot of economic digestion time, especially on the physical side.
ASI doesn't mean it can magically reverse-infer a digital process from an existing hodge-podge of automation and manual steps.
ASI doesn't mean there are instantly enough telerobotics or sensors to physically automate all processes.
Similarly, even ASI will by definition be non-deterministic and make mistakes. So processes will have to be reengineered to be compatible with it.
A superintelligence, at a bare minimum, equates to an exponential increase in software development capacity for everyone to the point at which we don’t need devs and we very quickly don’t need anything that devs can automate.
Even that is small minded frankly. The economy would not survive a super intelligence.
I think that's giving a lot of credit to "super".
Can the smartest developer you know build a project correctly without any requirements?
There's a lot of sausage making behind what to build, how to integrate it with other things, who needs to be told what on which other teams, etc.
Even pie in the sky breakthrough ASI isn't going to be able to do all of that, Day 0.
And if we're using a tautology to define ASI as something that can do that on Day 0, then I'd point out that in the entire history of technology there hasn't been a single advancement that wasn't subsequently refined and improved.
Except maybe fire.
If an AGI isn’t way smarter than the smartest person I’ve ever met, it’s definitely not a super intelligence. The very nature of a super intelligence is one that far exceeds human intelligence, including the the ability to rapidly design smarter AI.
Can the smartest person you know do everything all at once?
If not, how much smarter do you think someone would need to be to do so?
ASI ridiculousness starts from defining it as a do-anything machine. Everything has limits.
If I could instantiate 20 clones of the smartest person I know to work 24/7 without distractions or fatigue that could write code at the speed of compute, it would utterly demolish any team of humans of any size.
Like… I’ve had a TODO that I’ve expanded and worked on for a few years for a personal project. If I had a tireless bot of my own intelligence, it should only have taken about an hour. Human limitations are immense barriers.
Your comment raised a question for me: what makes you certain that there isn't already an artificial superintelligence operating in the world? I am not sure that it is possible to know when the threshold has been crossed.
I would suggest being careful treading that thought experiment.
Reminds me of Vault-Tec from the Fallout universe trying to "win the capitalism game" and "optimize shareholder value" after a nuclear apocalypse, going so far as to facilitate nuclear war in order to raise their value as a "defense company"
"Invest into our biotech company. Imagine how rich you will be when the next pandemic wipes out humanity!"
I just don't understand how commoditization argument is stated as truism in hacker news and in most AI posts that's the top voted comment. If at all, I see perfect non-ASI AI as superset of search engine and no search engine can match Google's quality even after 2 decades.
I think if we create ASI, the companies that invest on it won't necessarily see huge returns because I am 100% sure that the tech will be declare a national security matter and be heavily regulated. Since you need lots of compute to run those models, most people won't be able to run them without a cloud provider.
Not before the companies leaders, board of directors and investors use it for some very profitable trading first.
OT: FWIW I think "Anthropic in Advanced Talks to Raise $2B, Valuing It at $60B" makes for a better headline and is basically a shorter version of the first line of the article. It's a pretty factual edit so I don't think it qualifies as editorializing.
Crazy that Anthropic has a fraction of the AI model market that OpenAI has, but a valuation that's larger than their proportional share of the market to OpenAI....
The last valuation was at $157 billion- Anthropic is valued at 1/3 of OpenAI but has 1/10th of the market share....
But their API usage market shares are much more comparable. Where OpenAI have a huge lead is in chatbot subscriptions (ChatGPT vs Claude). At the end of the day it seems that API usage - business use - is where the potential huge usage is.
Also, Anthropic's Sonnet 3.5 seems to be widely preferred as a developer tool, even over OpenAI's newer GPT-o1, and developer use is one of the current leading use cases for AI.
I found this: https://www.tanayj.com/p/openai-and-anthropic-revenue-breakd...
Which says Anthropic is about 1/2 the API revenue of OpenAI and growing fast. But OpenAI is actually 5x revenue overall and 18x the chat product revenue. (This is from Oct, not sure how much would have changed).
Great point — I see this as evidence that this investment is more "who gets AGI first" speculation than "who has more chat subscriptions".
Afaik this isn't just chat website user base, this also includes API calls through different platforms- Amazon, Azure, etc.
The market is betting the best model wins to some extent and anthropic is not slowing down.
People can't get into the OpenAI round so they buy Anthropic maybe?
"The startup’s annualized revenue—an extrapolation of the next 12 months’ revenue based on recent sales—recently hit about $875 million, one of the knowledgeable people said. Most of that has come from sales to businesses."
Anthropic's team plans are actually pretty pleasant to use. It does seem strange/funny though, that a significant part of the evaluation choice from a business perspective is that Anthropic is more trustworthy than OpenAI.
This is a great example of creating value by making sure everybody's got a piece of the pie.
Say you're some OpenAI employees. You know a lot about AI, you've got the resume, you've got some buzz, and you want your own successful startup. How do you make sure that it gets maximum preferential treatment and first dibs on all the data and GPU? By making sure the big dogs are all going to get super rich off of your success.
So they got billions in investment from Google, even more billions in investments from Amazon, half a billion from FTX (whoops), then some VCs for additional shmoozing power, and you're good to go. It helps to have the technical chops and a good product to distinguish yourself, but at that point, Amazon and Google are both going to go out of their way to shove your AI into everything, so having something to contribute is practically just a nice bonus if you can manage it.
A lot of folks complaining about the valuation. It's important to remember that investing in an AI model company isn't the same as investing in most other businesses.
You're not investing hoping that they turn into a big business with a nice return. You're investing because you assume the value will either be zero or infinity.
If they achieve AGI first, then the valuation you invested in doesn't matter because the value will basically be infinite (or will completely change society in a way that money won't matter anymore).
If someone else achieves AGI first, the value is basically zero.
And if AGI isn't achieved, well, there probably won't be any exit. But if there is, it's a nice bonus if it still has any value.
What an exisistentally terse moment for late stage capitalism; betting State-sponsored shitcoins on our future quasi-cybernetic giga-corp overlords to offset increasingly miniscule differences in individual economic starvation.
I think late stage capitalism is an imprecise term - it does not capture the fundamental decoupling process - for what Nick Land has called "escape-phase capital autonomization" [0].
Thank you, he has articulated some outcomes and signs I hadn't yet.
His thesis that AI is just distilled omega-capitalism is true, very plainly.
In the last few months the quality of all Claude models has gone down a lot, I hope that in the future they plan to improve it.
There was a capacity crunch on the AWS nodes they rely on. I expect them to have a quality dial to pull back before overload. It would scale based on usage and server availablity.
Not for me, in fact the latest Sonnet iteration improved things considerably.
Considering how fast open source models are closing the performance gap, this is rather optimistic.
Maybe if they somehow fixed hallucinations and kept the secret sauce to themselves, I could see them being worth that much, but all the top labs seem to have given up on that problem.
This doesn't seem relevant.
Anthropic could pivot to a UI and hosting for models (potentially with some or no proprietary models) and still be worth $60B.
Lots of money at the top 1% looking for high risk high returns.
The top 1% in US own 40% of wealth, and top 10% own 80% of it. We are beyond Pareto ratio of 20:80.
The best AI model will not win the AI wars, it will be the most cost effective model at scale that wins.
Come on, guys, help me out here: Take some people, have them write essays, collect and process all the essays, which to me sounds like one step above high school plagiarism, and now expect to discover some "new, correct, significant" content none of those people knew?
I've created some new ideas: Yes, maybe all I did was "read what other's had done and took the next step", but that step seemed novel to me and, thus, just NOT in the "essays" or "what other's had done". Uh, just how the novelty happened does not seem to be in any of the essays or "what other's had done"?
Okay, maybe a two-step approach: (1) Make wild guesses. (2) Run experiments and test the guesses. But is current AI doing either of (1) and (2)? Right, for some board games can do both (1) and (2). Test the guesses with the content of the essays or "others have done"?
Here's a simple example: At one point the FedEx BOD wanted some revenue projections, uh, seriously wanted as in else "pull the funding". People had hopes, wishes, but nothing that sounded objective. Soooo, I noticed, guessed (1) growth would be mostly from the happy existing customers (2) influencing customers to be. The influencing would be a customer to be receiving via FedEx a package from a happy customer. So what? Okay, for time t let y(t) be the revenue at time t. Let b be the total size of the market, i.e., the revenue when do have all the target customers. Then at time t, the growth rate would be proportional to both (a) the number of current current customers and, thus, proportional also to y(t) and (b) proportional to the number of customers to be, and, thus, to (b - y(t)). So for some constant of proportionality k, we have that the growth rate
d/dt y(t) = y'(t) = k y(t) (b - y(t))
which has a simple closed form solution. Then for any k > 0, can do some arithmetic and find y(t) for any t > 0 and draw a graph. Do this and pick a k that yields a plausible, reasonable graph, and present that to the BOD. It worked, i.e., pleased the BOD which did not "pull the funding".
This work was 100% mine. Lot's of people in the office worked on the problem, but none of then had any ideas as good as mine -- i.e., could have them all write the "essays", process those, and still not come up with the little differential equation, its closed form solution, or a reasonable k.
It seems to me that the essays, what others have done as training data just does not have or have a path to work that is new, correct, significant. Uh, can we train the AI in how to guess and test (beyond board games), how to start with a BOD request and, a description of the why and how of business growth, some calculus and get an answer, take epicycles and come up with F = ma, Tesla's experiments, Stokes formula, and get Maxwell's equations, make a wild guess and propose the Michelson-Morley experiment, get E = mc^2, use the inverse and implicit function theorems, Riemann's work on manifolds, and get general relativity, solve Fermat's last theorem, make real progress on the Riemann hypothesis??? Uh, in short, we need a idea not in the training data? Soooo, need to train the AI to have ideas? Ideas are just using what's in the essays to make connections in a graph and then exploring the graph until get a path to an answer?? How do such training? Can process existing text yield such training data?
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Meanwhile I use the AI on one of my projects and it cuts me off making me wait 3 hours. I get it, but for $60Billion I think they can afford some IO.
That is paper money, not pipeline decongestion. I was going to suggest API but then I remember there is a limit to that also. Bastadz.