Like I said last week. I think zucks original llama thesis is proving more correct by the week. The rent market on intelligence never materialized, if you have THE frontier model, you can charge rent (for a few weeks, maybe month). But after a certain capability level it's price that drives the decision.
Zuck is doing the thing he's really good at, and building a moat around the network (Muse is VERY sticky), and now that we're all going to standardize on Meta's model, we're going to optimize the heck out of the infra to run the model making it cheaper for him to scale, thus bringing in more participants to his network, and thus making his network more valuable.
I think any personal AI agent at this point is "very sticky", not just Muse. You really aren't going to switch when a lot of the value is in the agent memory and there's no easy way to export that, similarly to how you aren't going to switch away from Spotify when it's learned all your song preferences which you can't export. Right now, maybe the agent memory is small enough that if you ask the agent to export you'll get most of it out (Claude has notably made official export instructions to encourage switching from ChatGPT in the past), but in the future the memory will be too large and complex to do that effectively, and platforms could also block the memory export or degrade it deliberately.
So, in the long run you pretty much have to pick one personal agent and stick with it, and switching is costly (unless you are using an open agent that lets you just download the memory, in which case it actually becomes cheap, because AI agents make other parts of switching way easier in general). For the purposes of Meta this means whatever user they get they'll probably keep.
HOWEVER, the thing that Muse doesn't have is network effects. They're running into the exact same problem as ChatGPT in this area, IMO. There's no reason for you to be running specifically Muse even if all of your friends are running it. So that gives other vendors a chance to catch up.
I don’t follow why “in the future the memory will be too large and complex to [export] effectively”.
to me, export should be easier and easier since you should just be able to ask the model for the memory files. it’s literally list text on a hard disk, even if there are some new formats in the future, they’ll just be files on a disk that another agent can then inspect and integrate. in fact, i think exporting data from services will become easier and easier since agents can do the work even if platforms try to block it.
> a lot of the value is in the agent memory and there's no easy way to export that,
Can't speak for muse and grok bot. But all other agents like openclaw, Hermes simply store then add files and it's trivial to migrate to another agent. Just point the agent to it
If you’re falling for “sticky” interfaces, you’re not going make it. Your competitor won’t have the stickiness and the ability to use any harness and that will overcome Muse in the long-run. Let’s not forget, Muse is a close to SOTA model right now, but so was Google, and now they’re irrelevant. Google is one of many funded models that were close to SOTA, but we realized it’s benchmaxxed.
People are going to say that it doesn’t matter if you’re the best. If Muse, Grokbot, and Dot are able to reach mass appeal, it doesn’t matter if a person using a custom harness is better.
I respectfully disagree. There is a big difference between someone that’s running a custom harness that’s almost like a personal OS versus someone using something out of the box. And if you’re for using this to run your business, think for yourself who’s going to win, the person customizing everything or the one using what the big corps give you.
These are good points, though OP did specifically say that Meta is going to win "consumer" AI. I don't think the average consumer of AI is going to ever have to think about harnesses or worry about SOTA, they really will continue to interact with whatever is stickiest.
But this is what I’m saying, consumer AI is forever changing. Investing your time and money into a closed harness will put you behind someone running their own system that’s model agnostic.
If you’re on a forum like HN, would you realisticly invest your time and widgets into a closed harness instead of building your own? What if Meta’s model falls behind and all your things are on there? My advice is to invest in building your own because no one lab has shown they are worth using.
As far as “consumer,” I’m simply comparing consumer AI to a custom built one. One of OpenAI, Anthropic, Meta will probably win since they have the most distribution.
And, "stickiest", mind, where most are allready soul-sucked into the neverending doomscrolling dopamine nightmare that is Zuckbook - to beging with.-
First they "captured", or moated "communication". Now, they are going to capture "utility" ("I am actually doing something useful, not just doomscrolling. I can spend an extra 8h here. It feels good").-
>For a Linux user, you can already build such a system yourself quite trivially by getting an FTP account, mounting it locally with curlftpfs, and then using SVN or CVS on the mounted filesystem. From Windows or Mac, this FTP account could be accessed through built-in software.
> And if you’re for using this to run your business, think for yourself who’s going to win...
That's not consumer AI though. The whole "vs out of the box" is pretty much the definition of consumer AI. People don't want to fiddle with things. That's why UX matters. SOTA only matters in consumer if it translates to the UX. And no one has landed that yet. Many are working on it.
I’m talking from experience. I’m run a software factory building open source alternatives and Argon is the worst model. Wrecked multiple codebases. But every use case is different. If you’ve found success in yours, use it.
When I worked at Microsoft, I learned that the average user will fail to do ANY process that is longer than 2 steps. Let that sink in and then reread your comment. Nobody cares about SOTA outside of tech. They want the basic floor of “it does what I need at a reasonable price” that’s it.
> The rent market on intelligence never materialized
So where is the ~$100B combined revenue for OpenAI and Anthropic coming from? Open source models have been close enough to the frontier for over a year now, yet the $$ shows no sign of shifting.
OpenaAI and Anthropic models are priced quite competitively with open ones, they even cut prices by quite a bit since spring. So it's not too surprising that their revenue is pretty high, the question is whether the competition and downward price pressure from open model providers combined with their extremely high R&D spending is sustainable.
last year was google winning AI, this year is meta winning AI. I think what is true is Meta, Google will all find their place in the AI world and continue to make huge amount of money. A consumer will use many different AI products, each with a different use case. Everyone will make enough money to live well.
I'm looking forward to seeing Muse devices like Amazon's devices but with superintelligence:
- Muse-equivalent of Alexa
- Muse-equivalent of Ring security devices: doorbells, cameras, alarms, etc
- Muse home automation devices (lights on/off, smart roller, smoke detector, water detecto, etc)
- Muse ring
...
Also honestly, the models don't have to get much smarter to handle the consumer side of things. They could innovate a ton on the harness to farm out requests and manage the state of the agent. They have an incentive to do this to reduce the infra usage so they can go wider with the agent.
Bold statement. I wouldn’t count anyone as a winner on consumer market at this point.
I think the weight of people who dislike Meta is going to be a problem - that and forcing to give a lot of information just to use it is problematic for adoption.
I disagree. Google is doing a phenomenal job at capturing use cases at the edge, right where "normie" consumers live. Google's models absolutely suck at coding but if you haven't tried Google Transcribe, you should.
Google has also, far larger distribution and stickiness than Meta.
How much does the engineers at Meta make? Spend enough time together with others making $250k+ and eventually you start suggesting that two 512 GB M5s is something you can put on your desktop. I mean, it's one banana, Michael. What could it cost? 10 dollars?
”Serve the model on either two Mac Studios, with M5 Ultra and 512GB of unified memory; or four Mac Studios with 256GB of unified memory, for a total of 1TB of unified memory, enough to hold a NVFP4 quantized version of Muse Spark Open”
The model license requires large inference providers to contact Meta separately to obtain a license to serve the model. I know we've seen this before with other large models, but it's still a bit irritating.
The usual effect of separate licensing is decreased price competition from public providers (like we saw with Kimi K3). I guess it's better for the providers if the price is fixed: any efficiency improvements directly improve margin rather than driving prices down over time. Still, to provide my own anecdata, the main thing keeping me on a paid subscription is token costs for the more capable models.
Then it's not open-weight. Open-weight means "weights available under an open-source license", and licenses prohibiting commercial use are not open-source.
The nearest analogue would be "weights available", I guess.
There's obvs decreased price competition, but it also does help with ensuring model quality.
Quite a lot of providers on OpenRouter run degraded or broken models. I think some is deliberate, but I think a lot is just providers not setting up models properly; especially with the rush to day zero models.
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[ 0.23 ms ] story [ 4.2 ms ] threadZuck is doing the thing he's really good at, and building a moat around the network (Muse is VERY sticky), and now that we're all going to standardize on Meta's model, we're going to optimize the heck out of the infra to run the model making it cheaper for him to scale, thus bringing in more participants to his network, and thus making his network more valuable.
Meta is going to win consumer AI.
How, exactly?
So, in the long run you pretty much have to pick one personal agent and stick with it, and switching is costly (unless you are using an open agent that lets you just download the memory, in which case it actually becomes cheap, because AI agents make other parts of switching way easier in general). For the purposes of Meta this means whatever user they get they'll probably keep.
HOWEVER, the thing that Muse doesn't have is network effects. They're running into the exact same problem as ChatGPT in this area, IMO. There's no reason for you to be running specifically Muse even if all of your friends are running it. So that gives other vendors a chance to catch up.
to me, export should be easier and easier since you should just be able to ask the model for the memory files. it’s literally list text on a hard disk, even if there are some new formats in the future, they’ll just be files on a disk that another agent can then inspect and integrate. in fact, i think exporting data from services will become easier and easier since agents can do the work even if platforms try to block it.
Can't speak for muse and grok bot. But all other agents like openclaw, Hermes simply store then add files and it's trivial to migrate to another agent. Just point the agent to it
Who's this "we" exactly?
People are going to say that it doesn’t matter if you’re the best. If Muse, Grokbot, and Dot are able to reach mass appeal, it doesn’t matter if a person using a custom harness is better.
I respectfully disagree. There is a big difference between someone that’s running a custom harness that’s almost like a personal OS versus someone using something out of the box. And if you’re for using this to run your business, think for yourself who’s going to win, the person customizing everything or the one using what the big corps give you.
If you’re on a forum like HN, would you realisticly invest your time and widgets into a closed harness instead of building your own? What if Meta’s model falls behind and all your things are on there? My advice is to invest in building your own because no one lab has shown they are worth using.
As far as “consumer,” I’m simply comparing consumer AI to a custom built one. One of OpenAI, Anthropic, Meta will probably win since they have the most distribution.
First they "captured", or moated "communication". Now, they are going to capture "utility" ("I am actually doing something useful, not just doomscrolling. I can spend an extra 8h here. It feels good").-
The real money is coming from C-suites trying to reduce head count or at least multiply productivity for their existing head count.
>For a Linux user, you can already build such a system yourself quite trivially by getting an FTP account, mounting it locally with curlftpfs, and then using SVN or CVS on the mounted filesystem. From Windows or Mac, this FTP account could be accessed through built-in software.
That's not consumer AI though. The whole "vs out of the box" is pretty much the definition of consumer AI. People don't want to fiddle with things. That's why UX matters. SOTA only matters in consumer if it translates to the UX. And no one has landed that yet. Many are working on it.
Argon is tied for first at worst.
> Google is one of many funded models that were close to SOTA, but we realized it’s benchmaxxed.
Who is "we"? Google is the least benchmaxxed.
I hope Google can catch up to OpenAI. The more competition the better.
So where is the ~$100B combined revenue for OpenAI and Anthropic coming from? Open source models have been close enough to the frontier for over a year now, yet the $$ shows no sign of shifting.
That zucks.
its not. ppl downloaded it in hype arent using anymore
Are you defining consumer AI as just AI as it relates to a narrow subset of social networking?
Donald, is that you?
Theyve had a few million downloads on what, DAU of billions?
Lol get a reality check.
That's a bold statement lol.
I think the weight of people who dislike Meta is going to be a problem - that and forcing to give a lot of information just to use it is problematic for adoption.
I disagree. Google is doing a phenomenal job at capturing use cases at the edge, right where "normie" consumers live. Google's models absolutely suck at coding but if you haven't tried Google Transcribe, you should.
Google has also, far larger distribution and stickiness than Meta.
Wait read that again. Two 512GB, unreleased model M5s.
This is gonna cost like 50k to run at home.
Can not find any info on inference speed.
The usual effect of separate licensing is decreased price competition from public providers (like we saw with Kimi K3). I guess it's better for the providers if the price is fixed: any efficiency improvements directly improve margin rather than driving prices down over time. Still, to provide my own anecdata, the main thing keeping me on a paid subscription is token costs for the more capable models.
The nearest analogue would be "weights available", I guess.
Quite a lot of providers on OpenRouter run degraded or broken models. I think some is deliberate, but I think a lot is just providers not setting up models properly; especially with the rush to day zero models.