sell enough units to convince Khosla Ventures that you aren't just burning their money, forcing them to double down on the vision and bring in new investors for the next round. Rinse and repeat until the Large Action Model is either extraordinarily valuable or you've torched all the money.
I think a lot of founders want to finish the analogy, as Steve Jobs was to the early Personal Computer, I will be to the early AI scene. They look at the marketplace and realize if they build on android or iOS they are subject to the whims and destruction of Apple and Google. They therefore decide the only option is to build their own hardware and see how it goes. I think it will be almost impossible to beat a phone connected to a peripheral with a camera mic and speaker like the meta glasses paired to your phone though in the long run.
1. Sell hardware that has a decent margin.
2. Use that margin to pay for cloud inference costs for an LLM.
3. Gain popularity enough to either raise hardware prices or add a subscription.
I believe they are betting on being able to monetize things around their "Large Action Model".
Could be market for the automations, where people can for example sell "buy tickets on ticketmaster" actions.
They could also monetize all the data they have and will have training that particular model, which is very lucrative if the AI bubble continues to inflate.
Voice skill discoverability was a huge issue for Amazon's alexa, and I don't see how this is any different except it's more expensive for both hardware and processing.
Same as Humane Ai Pin, Apple Vision Pro etc. They’re making a bet and hoping that when the world moves on from smartphones, they’ll be _the_ platform for the next frontier.
In software we see a lot of these “re-imaginings” come and go, see Arc browser, new cloud databases and myriad other things rolling the dice and hoping that they can disrupt and monetize later.
I think this is rarer in hardware because
a. It is harder, requires more planning, inventory management, higher standards and budget
b. Higher barrier to entry means not a lot of small players taking risks. I suppose it takes a technological shift like AI or spatial computing to re-imagine hardware interaction as well.
The saddest part is, when software companies come and go all that is wasted is some VC money and Twitter rants. With hardware, we’re making more junk to fill up oceans and waste precious resources…
Arguably there's an energy cost to running that software as well that's wasted. Plus potential waste on cloud providers adding hardware to support it all.
My understanding is the hardware is just for early adopters. They don't have the AI ready for mass consumption, it still needs to be trained on many of the tasks people are going to ask of it. Therefore, the early adopters who will go through that pain are willing to fork out for the hardware.
Then, they will either
a) sell a new hardware with subscription
b) sell only software likely as a subscription
c) plan just to be acquired.
It’s an “all you can eat” business model. They’re offering more than any user will realistically use, therefore bringing in more users for the deal they’re offering, therefore more units sold, therefore more profit.
The R1 is more a platform attempt at this point. Their aim is to disrupt if possible - hence their logic over putting this in dedicated hardware and owning the entire experience - and not just publishing a phone app.
I could see some future LAM integrations be paid service extras.
sell enough units to convince Khosla Ventures that you aren't just burning their money, forcing them to double down on the vision and bring in new investors for the next round. Rinse and repeat until the Large Action Model is either extraordinarily valuable or you've torched all the money.
I think a lot of founders want to finish the analogy, as Steve Jobs was to the early Personal Computer, I will be to the early AI scene. They look at the marketplace and realize if they build on android or iOS they are subject to the whims and destruction of Apple and Google. They therefore decide the only option is to build their own hardware and see how it goes. I think it will be almost impossible to beat a phone connected to a peripheral with a camera mic and speaker like the meta glasses paired to your phone though in the long run.
1. Sell hardware that has a decent margin. 2. Use that margin to pay for cloud inference costs for an LLM. 3. Gain popularity enough to either raise hardware prices or add a subscription.
I think the same as Teenage Engineering's: selling most people a fancy paperweight.
I believe they are betting on being able to monetize things around their "Large Action Model".
Could be market for the automations, where people can for example sell "buy tickets on ticketmaster" actions.
They could also monetize all the data they have and will have training that particular model, which is very lucrative if the AI bubble continues to inflate.
Voice skill discoverability was a huge issue for Amazon's alexa, and I don't see how this is any different except it's more expensive for both hardware and processing.
Same as Humane Ai Pin, Apple Vision Pro etc. They’re making a bet and hoping that when the world moves on from smartphones, they’ll be _the_ platform for the next frontier.
In software we see a lot of these “re-imaginings” come and go, see Arc browser, new cloud databases and myriad other things rolling the dice and hoping that they can disrupt and monetize later.
I think this is rarer in hardware because
a. It is harder, requires more planning, inventory management, higher standards and budget
b. Higher barrier to entry means not a lot of small players taking risks. I suppose it takes a technological shift like AI or spatial computing to re-imagine hardware interaction as well.
The saddest part is, when software companies come and go all that is wasted is some VC money and Twitter rants. With hardware, we’re making more junk to fill up oceans and waste precious resources…
Arguably there's an energy cost to running that software as well that's wasted. Plus potential waste on cloud providers adding hardware to support it all.
Disagree. It's all part of iterations or being part of destructive path to something great at the end.
My understanding is the hardware is just for early adopters. They don't have the AI ready for mass consumption, it still needs to be trained on many of the tasks people are going to ask of it. Therefore, the early adopters who will go through that pain are willing to fork out for the hardware.
Then, they will either a) sell a new hardware with subscription b) sell only software likely as a subscription c) plan just to be acquired.
raise more funding or sell, isn't that the business model of most startups these days? profitability is a problem for the bag holders
It’s an “all you can eat” business model. They’re offering more than any user will realistically use, therefore bringing in more users for the deal they’re offering, therefore more units sold, therefore more profit.
The R1 is more a platform attempt at this point. Their aim is to disrupt if possible - hence their logic over putting this in dedicated hardware and owning the entire experience - and not just publishing a phone app.
I could see some future LAM integrations be paid service extras.
This play makes sense, I am just surprised it is coming from a startup. They must be backed by somebody with deep pockets.
They're not really a startup. They've changed their name a bunch of times.
To sell hardware just like any other hardware & software company.
At least it is not a complete subscription on the device itself or a SaaS for once.
They're using flutter under the hood so worst case for them they could pivot off hardware and into an app based agent.
grift?
I think the move is to raise more and more money and try to find a business model?
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