What if there are no other killer apps for Enterprise? Only CC will produce the level of token churn that could drive huge profits for model providers.
The Enterprise market is not as substantial as the rapid success of CC makes seem.
Like, that feels like it's also a huge amount of token churn ("sure, I can search every xls file on your machine to find the 2023 invoice from that company"), and very early in its adaption curve.
Most people are still using AI as a webpage chatbot to ask questions to and copy+paste between, but running an "openclaw" like assistant, which can access your files, email, and opens you up to wild security attacks, that seems like a really big killer app.
Cowork to me also seems like it'll take longer to reach the broader market since the models are less good at "use the mouse and keyboard to do this repetitive task" than "write code", but I see it as having killer-app potential with lots of token churn.
I’ve been using these types of functions for a while for some specific use cases, and it’s super useful for this. Eg go into my budgeting app and explain to me why a certain discrepancy between forecast and actual occurred, which would otherwise cost me a huge amount of time.
I’ve also been using Cowriter AI, which actively learns from what you’re doing by taking screenshots of your screen every few seconds.
These types of utilities are just starting, they’re underexplored, and will definitely burn lots of tokens (while creating value).
This is the same issue many managers of people have for the same reason.
The ideal experience is where one’s resources are able to be allocated such that one can achieve some goal with minimal effort. We are very far away from this ideal with llm’s and absurd amounts of money has already been spent.
I think we all have had experiences with people treating their computers as magic boxes and not understanding why certain requests simply are not possible to satisfy.
Granted, it's possible that a majority of people will not acquire proper 'manager brain' either and we'll see how that pans out. Evolutionarily, managerial skills are much more aligned with what many hunter-gatherers might learn as they mature and become more of an advisor than a doer.
Even if only 10-20% of people end up using multiple autonomous agents regularly for their work and business, that will change the economy. Contrast this with <1% of people who develop software professionally.
Basic forms can be a challenge. Even things like selecting a dropdown menu or pushing a button can be surprisingly hard.
I’m sure many here live in delulu land wondering why everyone doesn’t find the open claw stuff as fascinating as they do.
If you believe you can do better, then build it! I don't think the tide has changed though.
So if you’re going to need the data center to process it, then you run into the same issue Microsoft did when they announced the OS feature where they took screenshots of your desktop all the time for advanced search or whatever. People consider it to be a privacy issue.
Read that again and really ask yourself if you want a private company to have access to all that and the ability to do whatever it wants with your system at the OS level.
Tools like Claude are best at answering things when the user understands the question.
It’s telling how scarce vision is.
It just isn’t the next Microsoft Office. A market of 10M people vs 2B!
I think it's more likely that the companies that employ large numbers of people to perform manual push-the-button-then-the-other-button workflows will replace the tools that need button-pushing with other sorts of automation.
And outside of work I wouldn't spend any money on something to save myself the ten minutes of logging in to pay my credit cards or check my bank statements once a month or so. I have no real need for an always-running assistant and even the things that it seems most useful for today (beating unassisted humans to the punch for limited-quantity things) are only something it could help with as long as only a very few people have access.
Similarly, customers who rely on AI cowork tools will come to favor systems and applications that expose AI-friendly interfaces, which shouldn't be difficult to implement in most cases under the assumption that the models in question are already good at consuming API documentation and writing code (and, for that matter, writing API documentation, refactoring, and generating relatively straightforward wrapper code).
I have less faith in the market's ability to effectively respond to security threats in a timely fashion, alas.
Too busy trying to make TikTok for preteens with $4/generation videos that lost their novelty the minute IP was off the table. Didn't even identify the professional market in video was the correct place to invest, like Kling and ByteDance did.
Chasing consumer killed their ascendency.
Sam is a ruthless leader and knows how to build an empire, but he's also a distracted leader who chases too many flights of fancy. Without a golden goose like Zuckerberg, every mistake is a knife wound.
Its pretty embarassing how they have blown the lead. Instead of finding a pathway toward selling tokens in volume (software production) they spread themselves thin and tried to hype up research, sora, web browser... blah blah.
Again - they get what they deserve.
I'm in the film and engineering spaces, and I can honestly say the same about image and video models.
There is so much fun in all of these tools, and the productivity gains are insane.
I shoot film, but I never would have been able to do anything like this before:
https://www.youtube.com/watch?v=HDdsKJl92H4
https://www.youtube.com/watch?v=oqoCWdOwr2U
Today, I saw AI OR DIE with this banger:
https://www.youtube.com/watch?v=CNbmoVdirxw
Gossip Goblin is doing incredible work as usual. Dude is a savant and would have killed it in Hollywood if he'd had a chance before:
https://www.youtube.com/watch?v=-Rzl7nUdEs4
Corridor Crew is leaning in and building new tools:
https://www.youtube.com/watch?v=Y3Dfw969itU
There's just so much incredible stuff being made by really brilliant people that never would have had the chance before. And these tools are literally brand spanking new. We're just getting started.
Google and OpenAI are both really far behind the Chinese at this point. Perhaps Google will unveil something groundbreaking at Google I/O, but both companies have been trailing for well over a year at this point.
One of the reasons OpenAI gave up was not only were they losing money, but they were also ridiculously far behind (11th or below in the rankings).
The models most professionals use are Kling o3, Kling 3.0 and, more recently, Seedance 2.0. These are all Chinese models.
Seedance 2.0 stands out as an almost order of magnitude improvement over everything else in the industry. It's truly the SOTA model. It blows everything else out of the water, and it's truly remarkable to experience it in use.
On April 30th, Alibaba's new Happy Horse model rolls out. They poached folks from Kling to build it. It's supposedly 2-5x cheaper than Seedance 2.0, and its ELO scores rank it as the new highest performing model.
https://artificialanalysis.ai/video/leaderboard/text-to-vide...
https://artificialanalysis.ai/video/leaderboard/image-to-vid...
Some shots are indeed impossible to one shot, but others can serendipitously turn out better than you wanted.
I'd say it averages 2.5 generations per shot. A lot of single one off one shots, and some (few) shots that just won't work no matter how hard you prompt.
That said, it's likely you'll find usable footage even in the losses. Videos are meant to be cut. A failed generation might still have salvageable contents you can cut to/from.
Editors are the super powered folks in AI video.
Sure, that's happening too, but to a lesser degree than I thought. CC with a number of "enterprise integrations" (really: corporate MCPs) is a pretty hefty force-multiplier for operations teams. "Go summarise and dissect this weird client request for me. Documentation is spread across at least $THESE_ENTERPRISE_DATA_SILOES." Saves a bunch of time pinging the different people across continents who happen to know intimate details. That was not entirely unexpected.
It's the technically minded but not necessarily otherwise technical people who keep surprising me in weird and wacky ways. People are building themselves and their immediate peers disposable dashboards. Who needs a service to pull data for a real-time display when CC can collect the necessary information and construct a local, static HTML file with all the info neatly in one place? I'm sure there will be a hangover because the compute cost for doing these in JIT fashion will surely feel like death by a thousand cuts at some point, but the ability to really quickly validate whether certain types of data aggregations are useful is proving to be ... a positive development.
I disagree about the ease of maintaining the software, though. You still need the skills to really understand what the code is doing, and with the original "why" possibly lost in the adrenaline haze, the maintenance effort floor has shifted.
Are they actually driving any profit? I mean actual profit, not "tokens" or users or profit but ignoring inference costs, same ignoring training, R&D, etc. I'm not arguing against how useful it is, nor how popular, just the basic total spent - total earned.
This is not an AI thing, this is a stocks thing, which Ive been complaining about incessantly.
If a given domain, like AI, has competition, that means you have to sell things at cost + margin, and rush ahead or be crushed by competitors. Will definitely make you good money, but wont make you a king.
This is not the kind of money people involved with these kinds of companies are looking for.
AI right now looks like a competiton, with many horses in the race, which are more or less building the same product.
It will hard to squeeze and enshittify this considering people can just jump to another vendor, thus if the current market structure were to prevail, investors would go.
Thus competition has to go.
Altman knows this, and tried to position OpenAI as the obvious winner in this competition, but I guess in the process he managed to alienate people, so now he's not doing so well.
But who knows what the future will bring?
That means a monopolistic company is great investment vehicle, while one that sells goods at cost is a crappy one.