I'm not a VC so maybe you don't care what I think, I'm not sure.
Last night as my 8yo was listening to childrens audio books going to sleep, she asked me to have it alternate book A then B then A then B.
I thought, idunno maybe I can work out a way to do this. Maybe the app has playlists and maaaaaaaaaaybe has a way to set a playlist on repeat. Or maybe you just can't do this in the app at all. I just sat there and switched it until she fell asleep, it wasn't gonna be more than 2 or 3 anyway, and so it's kind of a dumb example.
But here's the point: Computers can process language now. I can totally imagine her telling my phone to do that and it being able to do so, even if she's the first person ever to want it to do that. I think the bet is that a very large percentage of the world's software is going to want to gain natural language superpowers. And that this is not a trivial undertaking that will be achieved by a few open source LLMs. It will be a lot of work for a lot of people to make this happen, as such a lot of money will be made along the way.
Specifically how will this unfold? Nobody knows, but I think they wanna be deep in the game when it does.
How is this any different than the (lack of) business model of all the voice assistants?
How good does it have to be, how many features does it have to have, how accurate does its need to be.. in order for people to pay anything? And how much are people actually willing to spend against the $XX Billion of investment?
Again it just seems like "sell to AAPL/GOOG/MSFT and let them figure it out".
> How is this any different than the (lack of) business model of all the voice assistants?
Voice assistants do a small subset of the things you can already do easily on your phone. Competing with things you can already do easily on your phone is very hard; touch interfaces are extremely accessible, in many ways more accessible than voice. Current voice assistants only being able to do a small subset of that makes them not really very valuable.
And we aren't updating and rewriting all the world's software to expose its functionality to voice assistants because the voice assistant needs to be programmed to do each of those things. Each possible interaction must be planned and implemented invidually.
I think the bet is that we WILL be doing substantially that, updating and rewriting all the software, now that we can make them do things that are NOT easy to do with a phone or with a computer. And we can do so without designing every individual interaction; we can expose the building blocks and common interactions and LLMs may be able to map much more specific user desires onto those.
I wonder if we'll end up having intelligent agents interacting with mobile apps / web pages in headless displays because that's easier than exposing an API for every app
> How is this any different than the (lack of) business model of all the voice assistants?
Feels very different to me. The dominant ones are run by Google, Apple, and Amazon, and the voice assistants are mostly add-on features that don't by themselves generate much (if any) revenue (well, aside from the news that Amazon wants to start charging for a more advanced Alexa). The business model there is more like "we need this to drive people to our other products where they will spend money; if we don't others will do it for their products and we'll fall behind".
Sure, these companies are also working on AI, but there are also a bunch of others (OpenAI, Anthropic, SSI, xAI, etc.) that are banking on AI as their actual flagship product that people and businesses will pay them to use.
Meanwhile we have "indie" voice assistants like Mycroft that fail to find a sustainable business model and/or fail to gain traction and end up shutting down, at least as a business.
I'm not sure where this is going, though. Sure, some of these AI companies will get snapped up by bigger corps. I really hope, though, that there's room for sustainable, independent businesses. I don't want Google or Apple or Amazon or Microsoft to "own" AI.
Hard to see normies signing up for monthly subs to VC funded AI startups when a surprisingly large % still are resistant to paying AAPL/GOOG for email/storage/etc. Getting a $10/mo uplift for AI functionality to your iCloud/GSuite/Office365/Prime is a hard enough sell as it stands.
And again this against CapEx of something like $200B means $100/year per user is practically rounding to 0.
Not to mention the OpEx to actually run the inference/services on top ongoing.
You'd be very surprised at how much they're raking in from the small sliver of people who do pay. It only seems small just because of how much more they make from other things. If you have a billion users, a tiny percentage of paying users is still a gazillion dollars. Getting to a billion users is the hard part. Theyre betting theyll figure how to monetize all those eyeballs when they get there.
The voice assistants are too basic. As folks have said before, nobody trusts Alexa to place orders. But if Alexa was as competent as an intelligent & capable human secretary, you would never interact with Amazon.com again.
Would you not, though? Don't the large majority of people, and dare I say probably literally everyone who buys something off Amazon first check the actual listing before buying anything?
I wouldn't trust any kind of AI bot regardless of intelligence or usefulness to buy toilet paper blindly, yet alone something like a hard drive or whatever.
One could ask: how is this different from automatic call centers? (eg “for checking accounts, push 1…”) well, people hate those things. If one could create an automated call center that people didn’t hate, it might replace a lot of people.
Now call centers, not sexy, but the first rational achievable use case mentioned for LLMs in an HN response I've seen in a while!
The global call center market is apparently $165B/year revenue, and let's be honest even the human call center agents aren't great. So market is big and bar is low!
However, we are clearly still quite far from LLMs being a) able to know what they don't know / not hallucinate b) able to quickly/cheaply/poorly be trained the way you could a human agent c) actually be as concise and helpful as an average human.
Also it is obviously already being tried, given the frequent Twitter posts with screenshots of people jailbreaking their car dealership chat bot to give coding tips, etc.
Talking to an electronic assistant is so antiquated. It feels unnatural to formulate inner thoughts into verbal commands.
An ubiquitous phone has enough sensors/resources to be fully situationally aware and preempt/predict for each holder any action long time ahead.
It can measure the pulse, body postures and movements, gestures, breath patterns, calculate mood, listen to the surrounding sounds, recall all information ever discussed, have 360 deg visual information (via a swarm of fully autonomous flying micro-drones), be in an network with all relevant parties (family members, friends, coworkers, community) and know everything they (the peers) know.
From all gathered information the electronic personal assistant can predict all your next steps with high confidence. The humans think that they are unique, special and unpredictable, but opposite is the case. An assistant can know more about you than you think you know about yourself.
So your 8yo daughter does not need to tell how to alternate the audio books, the computer can feel the mood and just do what is appropriate, without her need to issue a verbal command.
Also in the morning you do not need to ask her how she slept tonight and listen to her subjective judgement.
The personal assistant will feel that you are probably interested in your daughters sleep and give you an exact objective medical analysis of the quality of the sleep of your daughter tonight, without you needing to ask the personal assistant of your daughter.
I love it, it is a bottomless goldmine for data analysis!
> The personal assistant will feel that you are probably interested in your daughters sleep and give you an exact objective medical analysis of the quality of the sleep of your daughter tonight, without you needing to ask the personal assistant of your daughter.
Next step: the assistant knows that your brain didn't react to much to its sleep report the last 5 mornings, so it will stop bothering you altogether. And maybe chitchat with your daughter's assistant to let her know that her father has no interest in her health.
Cool, no?
(I bet there is already some science fiction on this topic?)
Think speech will be a big part of this. Young ones (<5yo) I know almost exclusively prefer voice controls where available. Some have already picked up a few prompting tricks ("step by step" is emerging as the go-to) on their own.
Last night as my 8yo was listening to childrens audio books going to sleep, she asked me to have it alternate book A then B then A then B.
I thought, idunno maybe I can work out a way to do this. Maybe the app has playlists and maaaaaaaaaaybe has a way to set a playlist on repeat. Or maybe you just can't do this in the app at all. I just sat there and switched it until she fell asleep, it wasn't gonna be more than 2 or 3 anyway, and so it's kind of a dumb example.
But here's the point: Computers can process language now. I can totally imagine her telling my phone to do that and it being able to do so, even if she's the first person ever to want it to do that. I think the bet is that a very large percentage of the world's software is going to want to gain natural language superpowers. And that this is not a trivial undertaking that will be achieved by a few open source LLMs. It will be a lot of work for a lot of people to make this happen, as such a lot of money will be made along the way.
Specifically how will this unfold? Nobody knows, but I think they wanna be deep in the game when it does.