dkrich

I think a lot of his decisions can be boiled down to being hellbent on disrupting Apple.

I think the metaverse was his first crack at it until Wall Street gave him the hook for over spending.

Then when AI came around he again became fixated on the meta verse but using AI as the means of generating content for it.

I think these are all moon shot bets and meta still has no track record of success in hardware despite multiple attempts.

It seems that the next great hardware platform is probably a long ways away and will require some breakthrough that hasn’t happened yet and likely to come from a person with maniacal focus on a single application because that seems to have been the pattern in the past.

In other words I think it’s highly unlikely a current incumbent fosters the next hardware platform. I remember a time not so long ago when a lot of smart people were saying that Alexa was going to disrupt everything as we know it.

Also this AI shit on Facebook these days just seems really weird. But maybe there’s a vision of the future that suddenly makes it’s indispensable. Who knows?

If the stock market continues to rise there will be a bubble in defense stocks and a lot of defense IPOs

One of the unusual trends of the past several years is that higher education has become less and less respected and people now look to private industry for the R&D that universities were designed to perform for the public good.

I think 2025 Will mark a bottom for that in one way or another- either private industry (the FANGs) suffers a setback or (more likely in my view) research universities start a comeback as a new set of startups begin to launch out of a department (not necessarily CS or hardware). Perhaps in another field like gene therapy.

These tests are meaningless until You show them doing mundane tasks

That’s because it sparked a virtuous feedback loop at a time when it just so happens people’s credulity levels are off the charts. The creators of AI tools have a benefit in hyping it, as do software vendors as do hardware companies as do hyper scalers as does meta as does musk as do systems integrators like Accenture and on and on.

I think OP is saying despite all that there is little evidence that end users are actually paying significant sums of money to use it. To this point it’s a great marketing tool for companies that are all eager to be viewed as innovative and you have lots of very wealthy smart people with clout like Bezos and Zuckerberg talking it up. Like any good bubble you have to have at the core a real asset.

So of course there are people who use it daily as many anecdotes here in the comments point out. It’s a genuinely interesting and useful technology. That doesn’t mean though that it’s going to result in AGI or become profitable while liquidity conditions are still easy. I promise you Mark Zuckerberg would be singing a very different tune regarding chip investment if he were having to compete with bonds yielding 6-7%+.

The iPhone had enormous demonstrated demand

Interestingly it seems like we are investing many more magnitudes of capital for smaller and smaller gains.

For example, the jump in productivity from adding an operating system to a computer is orders of magnitude larger than adding an LLM to a web development process despite the LLM requiring infrastructure that cost tens of billions to create.

It seems that while tools are getting more and more sophisticated, they aren’t really resulting in much greater productivity. It all still seems to be resulting in software that solves the same problems as before. Whereas when html came around it opened up use cases that has never been seen before despite being a very simple abstraction layer by today’s standards.

Perhaps the opportunities are greatest when you are abstracting the layer that the fewest understand when LLMs seem to assume the opposite.

This seems to apply to all areas of AI in its current form and in my experience 70% may be a bit generous.

AI is great at getting you started or setting up scaffolds that are common to all tasks of a similar kind. Essentially anything with an identifiable pattern. It’s yet another abstraction layer sitting on an abstraction layer.

I suspect this is the reason we are really only seeing AI agents being used in call centers, essentially providing stand ins for chatbots- because chatbots are designed to automate highly repetitive, predictable tasks like changing an address or initiating a dispute. But for things like “I have a question about why I was charged $24.38 on my last statement” you will still be escalated to an agent because inquiries like that require a human to investigate and interpret an unpredictable pattern.

But creative tasks are designed to model the real world which is inherently analog and ever changing and closing that gap of identifying what’s missing between what you have and the real world and coming up with creative solutions is what humans excel at.

Self driving, writing emails, generating applications- AI gets you a decent starting point. It doesn’t solve problems fully, even with extensive training. Being able to fill that gap is true AI imo and probably still quite a ways off.

As someone (who likes to think) is pretty unbiased politically, I can say I’ll go wherever the people I’m interested post. I have been somewhat surprised that pretty non political accounts have moved to Bluesky which I have interpreted as both political and motivated by the loads of political bs that are posted on x that normal people simply get tired of. I think Bluesky will gain more traction than threads but will end up being a more successful mastodon. A place where people with massive followings who simply don’t like x will post and there will be two competing apps.

I love that so many people keep saying this so confidently yet if anyone bothered to look they’d see that the correlation between the two is nearly perfect over any timeframe including the past five years

This may make sense in theory but in reality is wrong. The DJIA has historically had a very close correlation to the S&P. Plus there is an inescapable psychological aspect to the Dow that is unique. When the Dow is off 1500 points it hits much differently than the S&P falling 200 points.

This is precisely why I’m skeptical. It assumes that that first advertiser can sell more of the same products just with better copy or more targeted placement and that more advertisers can backfill the previously used inventory that the first advertiser no longer needs and enjoy better sales too.

But doesn’t that then mean that many more product sales are taking place as opposed to the same number of sales spread across more impressions? I don’t see how many more sales can take place without users spending more money or the number of users going up and my original point was that meta is surely tapping into that addressable market as it is. There are only so many consumer dollars to go around.

This is a well thought out bull case for AI paying off at Meta. I just wonder what the upper limit is on ad spend in this economy from that long tail of advertisers, especially to Meta users which seem to be mostly focused on consumer goods. Surely Meta is already tapping into an enormous portion of that limit.

Yes and it’s negative

Not with the overhead of a draftkings or fanduel

Casinos are a proven business and have their highs and lows but will be fine. I’m talking specifically about betting apps. The fact that casinos have barely even entered the online space tells you all you need to know about how profitable it is

This is backwards. Casinos offer huge cross subsidization opportunities like getting people to spend lots of money in clubs and bars or gamble on games like slots that have a huge house edge while apps have near zero cross subsidization opportunities and massive overhead. An app running at draftkings scale costs a lot to operate.

I’ve believed for a long time and continue to that the math on these businesses just doesn’t work. Eventually they won’t exist because they aren’t profitable.

its going to end with these companies going towards zero and then possibly being acquired by private equity

I actually think this will be a self correcting problem.

Contrary to popular belief, running a sportsbook is a terrible business. Look at draftkings for instance. They’ve gotten gambling legalized nearly everywhere yet are still wildly unprofitable.

I guarantee you that they will never be profitable unless they are granted a monopoly which will never happen.

It’s fairly obvious. If you travel to Vegas and go to the Aria, one of the premier casinos on the strip, you will have to walk around to find the sportsbook. When you do you may be surprised to see that it’s not out in the center of the floor inviting people in, it’s in a dark remote enclosed corner that feels like a large coat room.

Now ask yourself why that would be? And why do casinos devote so much floor space to slot machines and table games?

Betting apps offer the terrible aspects of running a book- relatively unwealthy gamblers with the inability to cross subsidize more profitable games and alcohol along with the added drag of attracting disloyal users who can and will easily use other books to compare lines or take advantage of promos.

Ben is a smart dude and I don't often find myself at odds with any of his findings.

But in this case I very strongly disagree with his conclusion regarding Palantir. He seems to suggest that Palantir is a possible significant player in the first wave of AI because they are embedding themselves in the enterprise and doing the legwork of integrating data to make it useful and that the resulting benefits will outweigh the enormous costs.

Here's the problem(s). First of all, enterprise data is extraordinarily complicated as it evolves over many years and has the fingerprints of the prevailing technologies of the day all over it. It is nearly impossible to rip and replace or integrate those systems in flight because there is too much at stake and each system is endlessly complicated. That's to say nothing of the processes themselves which tend to evolve alongside the technology and are often inefficient because of the reliance on the dated technology. So Palantir has two challenges- overhauling data and processes.

Second, if the solution is integration work, what is special about Palantir? They hire the best analysts? C'mon. If it's a matter of talent that will become democratized with enough cash. There are loads of SI's that do this today. Are they just bad at it? If there isn't something special about Palantir then they have no edge.

Most damning though is that if you can integrate the data you don't really need AI because there are all sorts of tools available that would work amazingly well with the proper data. The challenge is always integration and making use of disparate data. There are hundreds of thousands of people who's job is solely being the glue between systems. Robotics could solve this but they are very inflexible, expensive and limited in functionality. Put differently, in this scenario AI is not the secret sauce it's the integrated data.

There is always this impulse when something new comes along to assume the existing way is dumb and those who use it or conceived it were ill-informed and this new thing or team will fix it all very easily. But once you get into it you realize there are an infinite number of considerations that make it very difficult to make any meaningful change.

I think the idea of agents is a great one but making them useful consistently will be very difficult and the question becomes does the benefit outweigh the enormous cost of building and training them. I suspect that with this enormous AI buildout you will end up with a lot of unused capacity that is later repurposed for an unintended use that nobody predicted. That is largely how bubbles eventually play out.

Ha in this case that’s actually the word I meant but Reddit has basically made that an impossible word to use in its intended form

Probably just comes down to less friction in getting paying users in their cars since they already have the app installed and these are small roll outs. From the announcement it sounds like the streets of Austin will be covered in waymos but after having been downtown a few weeks ago I can say there are like 10 of them. Partnering with a ubiquitous app makes getting real users in these small launches feasible.

Just a guess but if that’s accurate and then waymo expands to where it becomes the de facto option and familiar for a large number of ride hailers you can rest assured the next step will be to take back operations and cut Uber out

The economics of this seem highly questionable. After all how many robotaxi companies can there possibly be given the costs associated with vehicle ownership and autonomous software development? In a world where it costs nothing to create content or launch a drop shipping business aggregators like meta and Amazon make sense. But if you end up with like three AV providers, Uber seems like an unnecessary middleman in a business where margins are already incredibly tight.

You have to always remember that the competition is a guy in a car charging a couple bucks a mile

100% this. Dara came in and pulled all the P&L levers he could- basically closing down their own autonomous unit and buying a stake in aurora technology to allow another company to lose money and not have it show on their balance sheet. Then raising prices and lowering pay as much as possible.

They are now entirely reliant on quarter to quarter consumer spending and the performance of three stock holdings which are completely out of their hands.

Expect more and more manufactured headlines to keep the AV story in tact.

This five year prediction seems odd to me. Autonomous vehicles have to navigate in a world that was designed for human driven vehicles. If you were to design an autonomous transportation system in the middle of New Mexico from scratch it would almost certainly look nothing like what we have today which is comprised primarily of visual cues designed to be highly noticeable to human eyesight. That’s to say nothing of cars themselves being designed around the assumption of a human driver.

I guess what I’m trying to say is that it’s very difficult to imagine that if AVs take over let’s say over the next 30 years that the end result will still be running on the same infrastructure we rely on today and that if we will still be a society where most people drive most of the time that AVs will really be all that transformative in the first place since they would be filling a sizeable but still relatively small use case- taking a cab around a major city. I can’t tell whether it’s the amazement of seeing a driverless vehicle or the actual utility of it that generates the excitement

This has been a phenomenon of the endless liquidity train of the past 3-4 years. People doing very stupid things with money knowing more is always coming. There are certain stocks like palantir that are very obviously in bubbles where the market celebrates its inclusion in a stock index and sends the shares up 15%. The CEO just self produced a video recognizing retail traders and using the term “tendies.” The mistake this cycle though has been to assume that won’t work

The other main difference that I can’t get past is that the Internet and cell phone were so obviously useful to a layman that you didn’t really have to explain the value proposition.

The ability to type an email for instance, and send it instantly to someone on the other side of the planet for free was something that was in such contrast to the tools of the time it can’t really be understood by someone who didn’t live through that period.

AI to me is really hyped up by some very highly regarded CEOs with strong track records in other domains and tech enthusiasts who seem hell bent on being able to look back and say they called the next Industrial Revolution. In short everyone thinks they’re the counter to Paul Krugman saying the internet would be as useful as the fax machine. Credulity levels are off the charts. It’s gotten to the point where skeptics are automatically assumed to be wrong.

But what’s missing is the obvious amazement that should come to an ordinary person and frankly I still don’t see most people naturally gravitating to these tools.

Perhaps that could be explained by how amazingly fast technology has advanced in recent years but then that in and of itself seems to call into question whether this technology that’s being called AI is truly revolutionary when compared to what’s already available.

It’s valuable for use cases where the problem is “I don’t know the answer to this question and don’t know where to find it.” That’s not in and of itself a multibillion dollar business when the alternative doesn’t cost that much in the grand scheme of things (asking someone for help or looking for the answer).

Are you suggesting a chatbot is a suitable replacement for a teacher?

Let’s call it for what it is- taking poorly organized existing information and making it organized and interactive.

“Here are some sharepoint locations, site Maps, and wikis. Now regurgitate this info to me as if you are a friendly call center agent.”

Pretty cool but not much more than pushing existing data around. True AI I think is being able to learn some baseline of skills and then through experience and feedback adapt and be able to formulate new thoughts that eventually become part of the learned information. That is what humans excel at and so far something LLMs can’t do. Given the inherent difficulty of the task I think we aren’t much closer to that than before as the problems seem algorithmic and not merely hardware constrained.

This sounds good in theory. Then you try to use these tools and they don’t really make you more productive. More like asking someone for help, them giving a half baked response, giving up and walking away.

I had a conversation recently about this very thing. They were complaining that Salesforce is very hard to learn, even for simple tasks.

I asked why not use AI assistants? Because in practice they just aren’t capable of connecting the dots between documentation and configuration to complete the task at hand at the required level of customization. And that gap that exists between how things are stated to work and what’s actually required is where a lot of jobs are done and AI isn’t close to fixing. Which is why I still remain convinced that what’s being called AI is nothing more than a marketing tool to sell enterprise software and that jobs are going to be destroyed by it.