Illinois has laws against biometrics, which basically can be interpreted as broadly as anything that even looks for a face as a binary classifier. The translation demo uses video, intended to be your face.
I speak English and Spanish, so I recorded some English sentences and listened to the Spanish output it generated. It came damn close to my own Spanish (although I have more Castilianisms in mine, which of course I wouldn't expect it to know)
I tried it and it sounded nothing like me at all - just some random "generic" male voice that translate what I said into german. My wife put it as "that's shit - sounds nothing like you". Nuff said.
I also tried speaking German and translating it to English and when I said "Hallo ich wollte das nur mal ausprobieren" (Hello I just wanted to try this out) it translated it to "Hi, how are you? Do you know anyone who quit smoking?".
I translated from French to English and vice versa and the voice sounded nothing like me in either case. The English to French translation also made me sound about 90 years old.
Whether "we're there yet" on translation technology is still debated, but at some point we'll consider it "good enough" for most practical use cases, truly removing the linguistic barrier. This is actually both terrifying and exciting, because then it'll definitely start influencing spoken language to at least some degree.
It depends how much tolerance you have for mistakes. For a waiter or asking directions or things like that, 100% this works great. For a diplomatic discussion where nuance is very important however... It also doesn't work great for translating works of art where the translation itself is open-ended and can be done in a bunch of different ways and requires a lot of editorial/artistic decisions from the translator.
The seamless transition demo is fantastic. The translated voice is passable for my own native voice. It would be incredible when we can achieve this in real-time.
We can! At Kyutai, we released a real-time, on-device speech translation demo last week. For now, it is working only for French to English translation, on an iPhone 16 Pro: https://x.com/neilzegh/status/1887498102455869775
Meta believes the dollars at the end of the AI race will be in walled gardens and prop data, not data centers and models.
They are going to do everything they can to make sure no one uses the time that models and data centers are limiting factors to disrupt them.
In the same way google demonetized the application layer of the web to prevent walled gardens from blocking search.
If models and hardware become commoditized at the end of the race meta will have a complete psychographic profile of people on an individual and group level to study, and serve incredibly targeted content to.
Their only real competition in that would be someone developing a 'her' like app that takes people out of social media and into their own individual silo'ed worlds. In a lot of ways discord is the alternative world to meta's ecosystem. hyper focused invite only small communities.
> Their only real competition in that would be someone developing a 'her' like app that takes people out of social media and into their own individual silo'ed worlds
I take it you have not tried the new Gemini models on ai studio? It does real time streaming video input and conversation you can genuinely ask it questions about what you are looking at in a conversational audio in-out way. This is basically "her"-level technology in an unpolished form, right here today.
> Meta believes the dollars at the end of the AI race will be in walled gardens
Will those walls keep AI-generated content out, or will they keep the people outside from accessing the AI-generated content in the garden?
If it's the first, somebody should tell them the slop's already up to their navels and they probably shouldn't be helping people generate more of it.
If it's the second, then the models that supply the content to the garden must have some kind of uniqueness/value, because otherwise you could get identical content from anywhere.
This is a genuine question, because I don't understand the logic here.
(I had assumed it was more like hardware companies funding open source way back when - Commoditize Your Complement).
Apple tried that and it’s crumbling. Meta/Zuckerfuck is always behind the curve.
- AR (failed)
- “metaverse” (failed)
The only thing that has kept them above water is social media and selling off user data, and that’s crumbling as well. Smaller players have been eating their lunch and the user base is aging out.
Joel Spolsky in 2002 identified a major pattern in technology business & economics: the pattern of “commoditizing your complement”, an alternative to vertical integration, where companies seek to secure a chokepoint or quasi-monopoly in products composed of many necessary & sufficient layers by dominating one layer while fostering so much competition in another layer above or below its layer that no competing monopolist can emerge, prices are driven down to marginal costs elsewhere in the stack, total price drops & increases demand, and the majority of the consumer surplus of the final product can be diverted to the quasi-monopolist. No matter how valuable the original may be and how much one could charge for it, it can be more valuable to make it free if it increases profits elsewhere. A classic example is the commodification of PC hardware by the Microsoft OS monopoly, to the detriment of IBM & benefit of MS.
This pattern explains many otherwise odd or apparently self-sabotaging ventures by large tech companies into apparently irrelevant fields, such as the high rate of releasing open-source contributions by many Internet companies or the intrusion of advertising companies into smartphone manufacturing & web browser development & statistical software & fiber-optic networks & municipal WiFi & radio spectrum auctions & DNS (Google): they are pre-emptive attempts to commodify another company elsewhere in the stack, or defenses against it being done to them.
great question, i was wondering about that. I think it's mostly in discovery phase right now, similar to how they dabbled in crypto before, and the largely finished by now "metaverse" experiment. (yes, this dabbling involves a ton of money sometimes). These demos actually show what they might end up using AI for, but whether it's truly game-changing for their business and whether it will be good for the regular users, considering their shitty UI's both in FB and even Instagram by now are grossly obsolete, haven't changed in over a decade despite 70,000 people working there, and are nowadays mostly focused on violently shoving more ads over actual usefulness, is still an open question.
If their business remains a shitty declining buggy 20-year-old Facebook and a 10+year-old Instagram app, but they contribute to advancing open source models similar to how they did with React, I'll consider that a net win though.
After the 'metaverse' stuff flopped, desperate to spend their money on some other thing that might be The Future(TM)?
Arguably this would be kind of rational behaviour for them even if they thought that LLM stuff had a low chance of being the next thing; they have lots and lots of money, and lots of revenue, so one strategy would be just to latch on to every new fad, and then if one is a real thing they don't get left behind (and if it's not, well, they can afford it).
My suspicion is that this is where most Big Tech interest in LLMs comes from; it's essentially risk management.
Paraphrasing from someone who is involved in this - their angle in AI is better targeting of Ads - better classification, clustering, better "recommendations" for the advertiser, including visuals, wording, video etc.
These and others are just side benefits or some form of "greenwashing". Meta's main (and only) business is advertisement. They failed to capitalize on everything else.
Enabling experiences with AI that will drive people sharing content with each other, communicating online, and which can be utilized in AR/VR, where they have a lead position. In-house AI improvements have also helped ad placement and ad generation for clients
People who think Meta's main business focus is Facebook and Instagram don't pay attention.
What makes you think that more artificial stuff is going to reinvigorate the business? Metaverse was supposed to be such savior, but this time they didn’t even rename the company…
I think this is it. I'm kicking myself for not going harder, but I was very much into LLMs/ML back in 2019, had I not given up I might have a startup right now.
I'd need like 70k and a minimum of 6 months, but I still have a few ideas for AI driven startups.
Both do search, devices, OS and browsers - very natural verticals to integrate with AI, and both have cloud platforms where they can sell it to developers.
With Meta I can’t think of a single existing vertical where AI would be desirable. Maybe Quest
I'm pretty impressed with the segment anything[0] demo, is this integrated into an actual product anywhere? I do some simple video editing for friends as a hobby and can see some of this be pretty useful.
Photoroom [0] is from Y Combinator and their product is essentially SAM plus a lot of polish along with a good user experience. I'm not sure if they're using it, but if they're not, I think they should be.
SwarmUI, a front-end for image generation models, has integrated SAM2 as a quick way to mask parts of an image for things like inpainting. It's wonderful.
Readit News
Segment Anything 2: Create video cutouts and other fun visual effects with a few clicks.
Seamless Translation: Hear what you sound like in another language.
Animated Drawings: Bring hand-drawn sketches to life with animations.
Audiobox: Create an audio story with A1-generated voices and sounds.
Not accessible if you're in Illinois or Texas.
They must have anti-AI laws, probably with voice conversion moreso than image segmentation and cartoon animation.
Hopefully the lawmakers see beneficial use cases and fix their laws to target abuse instead of a blanket coarse-grained GenAI restriction.
Knowing meta they save all of it.
Heartland v. Kraft Foods is worth a read.
Dead Comment
I speak English and Spanish, so I recorded some English sentences and listened to the Spanish output it generated. It came damn close to my own Spanish (although I have more Castilianisms in mine, which of course I wouldn't expect it to know)
I'm bilingual and still can't understand him. I'm not even sure half the things he says are actual words.
I also tried speaking German and translating it to English and when I said "Hallo ich wollte das nur mal ausprobieren" (Hello I just wanted to try this out) it translated it to "Hi, how are you? Do you know anyone who quit smoking?".
I feel gaslit.
It put me off from actually trying it, I might reconsider.
We released inference code and weights, you can check our github here: https://github.com/kyutai-labs/hibiki
They are going to do everything they can to make sure no one uses the time that models and data centers are limiting factors to disrupt them.
In the same way google demonetized the application layer of the web to prevent walled gardens from blocking search.
If models and hardware become commoditized at the end of the race meta will have a complete psychographic profile of people on an individual and group level to study, and serve incredibly targeted content to.
Their only real competition in that would be someone developing a 'her' like app that takes people out of social media and into their own individual silo'ed worlds. In a lot of ways discord is the alternative world to meta's ecosystem. hyper focused invite only small communities.
I take it you have not tried the new Gemini models on ai studio? It does real time streaming video input and conversation you can genuinely ask it questions about what you are looking at in a conversational audio in-out way. This is basically "her"-level technology in an unpolished form, right here today.
Will those walls keep AI-generated content out, or will they keep the people outside from accessing the AI-generated content in the garden?
If it's the first, somebody should tell them the slop's already up to their navels and they probably shouldn't be helping people generate more of it.
If it's the second, then the models that supply the content to the garden must have some kind of uniqueness/value, because otherwise you could get identical content from anywhere.
This is a genuine question, because I don't understand the logic here.
(I had assumed it was more like hardware companies funding open source way back when - Commoditize Your Complement).
Apple tried that and it’s crumbling. Meta/Zuckerfuck is always behind the curve.
- AR (failed)
- “metaverse” (failed)
The only thing that has kept them above water is social media and selling off user data, and that’s crumbling as well. Smaller players have been eating their lunch and the user base is aging out.
Deleted Comment
Joel Spolsky in 2002 identified a major pattern in technology business & economics: the pattern of “commoditizing your complement”, an alternative to vertical integration, where companies seek to secure a chokepoint or quasi-monopoly in products composed of many necessary & sufficient layers by dominating one layer while fostering so much competition in another layer above or below its layer that no competing monopolist can emerge, prices are driven down to marginal costs elsewhere in the stack, total price drops & increases demand, and the majority of the consumer surplus of the final product can be diverted to the quasi-monopolist. No matter how valuable the original may be and how much one could charge for it, it can be more valuable to make it free if it increases profits elsewhere. A classic example is the commodification of PC hardware by the Microsoft OS monopoly, to the detriment of IBM & benefit of MS.
This pattern explains many otherwise odd or apparently self-sabotaging ventures by large tech companies into apparently irrelevant fields, such as the high rate of releasing open-source contributions by many Internet companies or the intrusion of advertising companies into smartphone manufacturing & web browser development & statistical software & fiber-optic networks & municipal WiFi & radio spectrum auctions & DNS (Google): they are pre-emptive attempts to commodify another company elsewhere in the stack, or defenses against it being done to them.
If their business remains a shitty declining buggy 20-year-old Facebook and a 10+year-old Instagram app, but they contribute to advancing open source models similar to how they did with React, I'll consider that a net win though.
Arguably this would be kind of rational behaviour for them even if they thought that LLM stuff had a low chance of being the next thing; they have lots and lots of money, and lots of revenue, so one strategy would be just to latch on to every new fad, and then if one is a real thing they don't get left behind (and if it's not, well, they can afford it).
My suspicion is that this is where most Big Tech interest in LLMs comes from; it's essentially risk management.
These and others are just side benefits or some form of "greenwashing". Meta's main (and only) business is advertisement. They failed to capitalize on everything else.
People who think Meta's main business focus is Facebook and Instagram don't pay attention.
Not that I'm complaining about their open-weights model releases destroying openai's moat... but still.
I think this is it. I'm kicking myself for not going harder, but I was very much into LLMs/ML back in 2019, had I not given up I might have a startup right now.
I'd need like 70k and a minimum of 6 months, but I still have a few ideas for AI driven startups.
With Meta I can’t think of a single existing vertical where AI would be desirable. Maybe Quest
[0]https://sam2.metademolab.com/
[0] https://www.photoroom.com/
[1]: https://en.wikipedia.org/wiki/Meta_AI