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Comment by mehulashah

10 hours ago

Most of the folks on this topic are focused on Meta and Yann’s departure. But, I’m seeing something different.

This is the weirdest technology market that I’ve seen. Researchers are getting rewarded with VC money to try what remains a science experiment. That used to be a bad word and now that gets rewarded with billions of dollars in valuation.

> This is the weirdest technology market that I’ve seen.

The phenomenon you're seeing is well described here: "The Perfect AI Startup" (https://www.bloomberg.com/opinion/newsletters/2025-09-29/the...)

“It was the most absurd pitch meeting,” one investor who met with Murati said. “She was like, ‘So we’re doing an AI company with the best AI people, but we can’t answer any questions.’”

Despite that vagueness, Murati raised $2 billion in funding...

  • From a certain angle, this is the market correcting towards the abstraction.

    Between inflation, fiscal capture, and the inane plethora of ridiculous financial vehicles that are used to move capital around these days, the argument could be made that the money was already funny. This is just the drop of the final veil, saying "well it's not like these numbers mean anything anymore. I do have enough yachts. Fuck it, see what you can do with it".

  • I wonder how the investors feel now seeing what the initial product is?!

    Maybe investing in all well-connected AI startups is safer than trying to pick the winners and losers?

    • If you have N startups, and expect at least 1 of them to make >N times what you invest in each, then investing that amount in each one of them will still be expected to have a positive ROI. If none of them "hits it big" then you lose all the investment money, but if any of them grow enormously you profit. Trying to pick winners & losers in advance is much more difficult, investing in an entire business sector is the VC version of an index fund.

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That's been true for the last year or two, but it feels like we're at an inflection point. All of the announcements from OpenAI for the last couple of months have been product focused - Instant Checkout, AgentKit, etc. Anthropic seems 100% focused on Claude Code. We're not hearing as much about AGI/Superintelligence (thank goodness) as we were earlier this year, in fact the big labs aren't even talking much about their next model releases. The focus has pivoted to building products from existing models (and building massive data centers to support anticipated consumption).

  • Meta hiring researchers en masse at $100m+ pay packages is fairly new, as of this summer.

    I don't know if that's indicative of the market as a whole though. Zuck just seems really gutted they fell behind with Llama 4.

  • You must not watch broadcast television (e.g American Football). Anthropic is doing a huge ad blitz, trying to get end customers to use their chatbot.

    • Anthropic, frankly, needs to in ways the other big names don't.

      It gets lost on people in techcentric fields because Claude's at the forefront of things we care about, but Anthropic is basically unknown among the wider populace.

      Last I'd looked a few months ago, Anthropic's brand awareness was in the middle single digits; OpenAI/ChatGPT was somewhere around 80% for comparison. MS/Copilot and Gemini were somewhere between the two but closer to Open AI than Anthropic.

      tl;dr - Anthropic has a lot more to gain from awareness campaigns than the other major model providers do.

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  • If Claude Code is Anthropic’s main focus why are they not responding to some of the most commented issues on their GitHub? https://github.com/anthropics/claude-code/issues/3648 has people begging for feedback and saying they’re moving to OpenAI, has been open since July and there are similar issues with 100+ comments.

    • Hey, Boris from the Claude Code team here. We try hard to read through every issue, and respond to as many issues as possible. The challenge is we have hundreds of new issues each day, and even after Claude dedupes and triages them, practically we can’t get to all of them immediately.

      The specific issue you linked is related to the way Ink works, and the way terminals use ANSI escape codes to control rendering. When building a terminal app there is a tradeoff between (1) visual consistency between what is rendered in the viewport and scrollback, and (2) scrolling and flickering which are sometimes negligible and sometimes a really bad experience. We are actively working on rewriting our rendering code to pick a better point along this tradeoff curve, which will mean better rendering soon. In the meantime, a simple workaround that tends to help is to make the terminal taller.

      Please keep the feedback coming!

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    • It's entirely possible they don't have the ability in house to resolve it. Based on the report this is a user interface issue. It could just be some strange setting they enabled somewhere. But it's also possible it's the result of some dependency 3 or 4 levels removed from their product. Even worse, it could be the result of interactions between multiple dependencies that are only apparent at runtime.

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> Researchers are getting rewarded with VC money to try what remains a science experiment. That used to be a bad word

I’ve worked for multiple startups and I’ve watched startup job boards most of my career.

A lot of VC backed startups have a founder with a research background and are focused on providing out some hypothesis. I don’t see anything uncommon about this arrangement.

If you live near a University that does a lot of research it’s very common to encounter VC backed startups that are trying to prove out and commercialize some researcher’s experiment. It’s also common for those founders to spend some time at a FAANG or similar firm before getting VC funded.

  • Certainly research has made it into product with the help of the innovators that created the research. The dial is turned further here where the research ideas have yet to be tried and vetted. The research begins in the startup. Even in the dotcom era, the research prototypes were vetted in the conferences and journals before taking the risk to build production systems. This is no longer the case. The experiments have yet to be run.

  • Yeah, but Sutskever and Murati wouldn't even tell investors what they were working on, and LeCun only has a long-term research direction - not any breakthrough or prototype to commercialize.

  • I agree there is nothing uncommon about that type of arrangement, but the amount of money involved is unprecedented.

I personally see this as a positive trend. VC in its earliest form was concerned with experiments that had high technology risk. I am thinking of companies like Genentech and scientists like biochemist Herbert Boyer, who had pioneered recombinant DNA technology.

After that, VC had become more like PE, investing in stuff that was working already but needed money to scale.

  • This isn't that.

    This is VCs FOMOing as global-economy-threatening levels of leverage are being bet on an AI transformation that, by even the most optimistic estimates, cannot achieve a tiny portion of the required ROI in the required time.

  • Yeah there has been some lamenting at all the money being thrown at technology hasn't been for anything truly game changing, basically just variations of full stack apps. A few failed mooonshots might be more interesting at least.

  • I agree, if anything spending money on high technology risk is Silicon Valley going back to its roots.

    Nobody had a way to do silicon transistor manufacturing at scale until the traitorous eight flipped Shockley the bird and took a $1.4M seed investment from Sherman Fairchild.

    Big bets on uncertain technology is what tech is supposed to be about.

> This is the weirdest technology market that I’ve seen.

You must have not lived through the dot com boom. There was almost everything under the sun was being sold under a website that started with an "e". ePets, ePlants, eStamps, eUnderwear, eStocks, eCards, eInvites.....

  • Those things all worked, and all of those products still exist in one form or another. It was a business question of who would provide it, not a technology question.

  • That was certainly a bubble but I don't think pets.com was doing a research experiment.

    From what I recall there were some biotech stocks in that era that do fit the bill.

  • It's funny that the Netherlands seems to still live in the dotcom boom to this day. Want to adopt a pet? verhuisdieren.nl. Want to buy wall art? wall-art.nl. Need cat5 cable? kabelshop.nl. 8/10 times there is a (legit) online store for whatever you need, to the point where one of the local e-commerce giants (Coolblue) buys this type of domain and aliases them to their main site.

    • This is still the case in the US, too. I don't know why people are talking like it stopped happening. amazon.com, amazon.com, amazon.com, amazon.com

      All these things are still e-tail here, too. We didn't go back to B&M.

    • Pretty funny, looks like it works in France too! animaux.fr redirects to a pet adoption service, cable.fr looks like a cable-selling shop. artmural.fr exists but looks like a personal blog from a wall artist, rather than a shop.

  • It did make sense though. ePlants could have cornered the online nursery market. That is a valuable market. I think people were just too early. Payment and logistics hasn’t been figured out yet.

Agree on weirdness but not on the idea of funding science experiments:

>> away from long-term research toward commercial AI products and large language models - LLMs

This feels more like what I see every day: the people in charge desperately looking for some way - any way - to capitalize on the frenzy. They're not looking to fund research; they just want to get even richer. It's pets.ai this time.

This doesn’t feel that new or surprising to me, although I suppose it depends what you consider the line between “science experiment” and “engineering R&D” to be.

Biotech has been a YC darling. Was Ginkgo Bioworks not doing science experiments?

Clean energy was a big YC fad roughly 15 years ago. Billions were invested towards scientific research into biofuels, solar, etc.

I can’t help but wonder: if we had poured the same amount of money into fusion energy research and development, how far might we have come in just three short years?

  • The minimum cost of capital just to run fusion experiments is probably $100m. And the power bills are probably almost as high as the ones from OpenAI, which is to say, they are the highest power bills in the history of mankind ...

  • Forreal that’s what really gets me about this haha. Literally billions of dollars burned on bullshit.

If a "science experiment" has the chance to displace most labor then whoever's successful at the experiment wins the economy, period. There's nothing weird or surprising about the logic of them obsessively chasing it. They all have to, it's a prisoner's dilemma.

  • Fusion power has the chance to displace most power generation, and whoever is successful at the experiment wins the energy economy, period. However given the long timelines, high cost of research, and the unanswered technical questions around materials that can withstand neutron flux, the total 2024 investment into fusion is only around $10B, versus AI's 250+B.

    Why are these so different?

    • I think there are two reasons. First, with AI, you get see intermediate successes and, in theory, can derive profit from them. ChatGPT may not be profitable right now but in the longer run, users will be paying whatever they have to pay for it because they are addicted to using it. So it makes sense to try and get as many users as you can into your ecosystem as early as possible even if that means losses. With fusion, you won't see profitability for a very very long time.

      The second reason is by how much it's going to be better in the end. Fusion has to compete with hydro, nuclear, solar and wind. It makes exactly the same energy, so the upside is already capped unlike with AI which brings something disruptive.

    • Energy is only ~10% of world GDP whereas AGI might be 25-75% and if paired with advanced robotics would be closer to 100%.

      Capital always chases the highest rate of return as well, and margins on energy production are tight. Margins on performing labor are huge.

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    • People are unsophisticated and see how convincing LLM output looks on the surface. They think it's already intelligent, or that intelligence is just around the corner. Or that its ability to displace labor, if not intelligence, is imminent.

      If consumption of slop turns out to be a novelty that goes away and enough time goes by without a leap to truly useful intelligence, the AI investment will go down.

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  • Technology know-how spreads rapidly, so no need to be first. Look how fast Google caught up with Gemini when they chose to, or how fast X.ai developed Grok.

    Maybe it's cheap insurance to invest in, say, LeCun just in case JEPA or the animal intelligence approach takes off, but if it does show significant signs of progress there'd also be opportunity to invest later, or in one of the dozen copycats that will emerge. In the end it'll be the giants like Google and Microsoft that will win.

Its not really an outlier

If you think about Theranos, Magic leap, openai, anthropic they are all the same, one idea thats kinda plausible (well if you don't look too closely), have a slick demo, and well connected founders.

Much as a lot of people dislike LeCun (just look at the blind posts about him) he did run and setup a very successful team inside meta, well nominally at least.

  • Ridiculous. Theranos was a literal crime scene. Its products didn't work at all, and physically couldn't work due to the nature of blood itself.

    Magic Leap was an honest if overhyped effort that didn't achieve product-market fit.

    Meanwhile, products from OpenAI and Anthropic have both done useful work for me this week.

This looks more like a return to form than anything.

The first ventures were funding voyages to a New World thousands of miles away, essentially a different planet as far as the people then were concerned.

Venture capital for a new B2B application is playing it safe as far as risk capital goes

Hey listen, corporate owners will pay flesh to ultimately reduce spending on the workforce.

It makes sense, it’s a simple expected value calculation.

There are trillions of labor dollars that can be replaced by software. The US alone has almost $12 trillion of labor annually.

If an AI company has a 10% shot of developing a product that can replace 10% of it, they are worth $120 billion in expected value. (These numbers are obviously just for illustration).

The unprecedented numbers are a simple function of the unprecedented market size. Nobody has ever had a chance of creating trillions of dollars of economic value in a handful of years before.

  • >If an AI company has a 10% shot of developing a product that can replace 10% of it, they are worth $120 billion in expected value.

    that's not how profits work. Companies don't get paid for the value they create but for the value they can capture, otherwise the ffmpeg people would already be trillionaires.

    If you have a dozen companies making the same general purpose technology, not product, your only hope is being able to slap ads on top of it, which is why they're so keen on targeting consumers rather than trying to automate jobs.

    • Yeah, it was intentionally oversimplified to illustrate a point. Not everybody knows what the phrase expected value means or realizes the size of the market that is being addressed here.

      This is the same game of poker investors have been playing forever, there just are a few more zeros on the chips.

Has someone done a survey to ask devs on how much they are getting done vs what their managers expect with AI? I've had conversations with multiple devs in big orgs telling me that Managers and dev's expectations are seriously out of sync. Basically its

Manager: Now you "have" AI, release 10 features instead of 1 in the next month.

Devs: Spending 50% more working hours to make AI code "work" and deliver 10.

Lecun always struck me as an institutional clown who completely botched Meta's AI outlook.

If it ever feels weird - just watch Silicon Valley show again.

"Revenue? No no no no. Why would you go after revenue? If you show people revenue, they’ll ask ‘how much?’. And it will never be enough. The company that was the 100x-er or the 1000x-er becomes the 2x dog. But if you have no revenue, you can say you’re pre-revenue and you’re a potential pure play.”

We took it now from no revenue to no actual product, or even a concept of a product.

I think that's a good thing and VC getting back to it's roots. I'm glad that scientists doing AI are getting big money and don't know exactly what the product will be rather than some business person with a slick deck and hockey stick charts.

  • VC isn't "getting back to it's roots", though it is certainly displaying one of it's fundamental drives: FOMO.

Having raised more than $100M myself, I’m not sure I would call VC money a reward. However, VC money should be allocated in part to massive upside science experiments. PE money is focused on things already figured out.

You're right to feel like you're seeing something different. You are. But you're mistaking the symptom for the disease.

That's because you're trying to make sense of it as a technology market. It's not. It's a resource extraction market, and the VCs are the ones running the logging operation. Their sole mission is to find a dependable way to strip a forest bare, and they've been using the same playbook for decades.

Those "science experiments" you're talking about? They aren't the product. They're the story, the sizzle. They are the disposable lighter used to start the fire; the VCs have no intention of keeping it lit forever. The real tool is the chainsaw, and the "science experiment" is the brand name printed on the side.

Think of it as clear-cutting. The dot-com bubble was one forest. The story then was that a company losing millions selling pet food online was a "new economy" giant because it had "eyeballs." That was the sales pitch for the chainsaw. VCs funded hundreds of these operations, created a frenzy, and took the most plausible-sounding ones public. The IPO wasn't a milestone; it was the moment they sold the timber and exited the forest, leaving the stumps and worthless pulp for the pension funds and retail investors.

The "long-term" part of their strategy isn't about the health of any single tree or company. It's about finding the next forest to clear-cut. After dot-coms, it was social media. Now, it's the AI forest. They aren't betting on AI; they're betting on their ability to sell the world on the idea that this particular forest is magical and will grow forever.

So you're right, what you're seeing is weird. But it's not a new kind of weirdness. It's the oldest story in finance. A bubble being inflated so the smart money can cash out, leaving everyone else to marvel at the fancy new chainsaw after the forest is already gone.

If a science experiment works and is transformational can be worth a trillion dollars, how much is it worth if it has a 5% chance of being transformational?

  • What it's transformational but takes a decade or so, instead of a year or so?

    It's not like this isn't following exactly the same hype cycle as every other technological transformation.

  • What if it is a 99% chance of being transformational and the results of that transformation are completely unpredictable?

It's the world's biggest game of "let's throw shit at the wall and see what sticks."

They're trying desperately to find profit in what so far has been the biggest boondoggle of all time.

Agree. This is just gambling with almost free money.

Feeding, housing, and educating people would benefit society, and these companies, so much more than AI ever will.

Get the popcorn ready for when that all implodes. Most of these folks getting funding don’t have the slightest clue on how to build a sustainable business.

When the bubble pops, and it’s very close to popping, there’s going to be a lot of burning piles of cash with no viable path to reviver that money.

Yes - I had similar thoughts when I saw the word "startup" used alongside something so far-out (same 'critique" should apply to Fei-Fei Li's World Labs - https://www.worldlabs.ai). These are VC-funded research labs (and there is nothing wrong with tat). Calling them "startups" as if they are already working on an MVP on top of an unproven (and frankly non-existent) technology seems a little disingenuous to me.

Because when the recipe is open and public, the product's success depends on Distribution (which has been cornered by MS, Google, Apple). This is good for the ecosystem but not sure how those particular VCs will get exits.

  • Very few startup products depend on distribution by Microsoft / Google / Apple. You're really just talking about a limited set of mobile or desktop apps there. Everything else is wide open. Kailera Therapeutics isn't going to live or die based on what the tech giants do.

> Researchers are getting rewarded with VC money to try what remains a science experiment.

That's not all that new. Commercial fusion power startups are an example. I think the first one was General Fusion, founded in 2002. Today, there are around 50 of them. Every single one of those "remains a science experiment", and probably has much lower chance of success than some of the AI science experiments.

Of course, fusion startups have apparently "only" received about $10 bn in funding to date, so pale in comparison to the overall AI market. But if you just look at the AI "science experiments", it's possible the amounts would be comparable.

Is it like VCs throwing money at a young Wozniak while eschewing Jobs?

That either gives the AI tech more legitimacy in my mind … or a sign we've not arrived yet.

Yeah, that's quite unusual. Buisness was always terrible at being innovative, always dared to take only the safest and most minute of bets and the progress of technology was always paid for by the taxpayers. Business usually stepped in only later, when technology was ready and did what it does best, opimize manufacturing and put it in the hands of as many consumers as possible rakink in billions.

I wonder what changed. Does AI look like a safe bet? Or does every other bet seem to not have any reasonable return?