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- [00:00]
A
Welcome to the AI Hustle podcast. Today on the show, we're talking about a brand new product that is coming out of Thinking Machines. It is a AI model that essentially listens while it talks. So similar to a human. A lot of times we've had this latency issue with things like 11 labs or other of these kind of AI voice receptionists. There's so many different industries that this applies to, but there's a latency where you speak and it has to try to take in all the data, compute it, think of its response and spit it out to you as fast as possible. And there's kind of a little latency gap. So they're trying to solve this by essentially having the AI model listen and actively take in information while it's also talking and be able to do this kind of simultaneously like a human would. We're going to get into all of this. It's fascinating also because this is coming out of Thinking Machine, which is from Maratti, who's raised a ton of money and hasn't had a ton of products come out. So anyways, a lot to get into here. But before we do, I wanted to mention if you haven't already joined our AI Hustle school community, we would love to have you as a member. Every single week we record a a bonus video where we break down a tutorial on the tools, strategies and things we're using to grow and scale our businesses with AI. We show you the actual products that we're and projects we're actively working on. We show you revenue numbers, we show you deep dives, everything we can't share publicly. We show you the tools we're using. And so it's an amazing place you can go join. It's only $19 a month. We try to make this affordable for everybody. We'll keep this price low and if you lock in this price, if we raise it in the future, it won't be raised on you. There's over 200 members in here, so lots of people that are actively building and sharing what they're working on and we'd love to have you be one of them. So I'll leave a link in the description to that. Jamie, taking over to this story with Thinking Machine Labs, I guess what was the most interesting part of this software to you because I know you personally are working on and you have tools and you help businesses with kind of these AI receptionist kind of things. So for you, what are your first thoughts on this?
- [01:56]
B
I mean, I think this is a great idea. I think that's a real problem that they need to solve because, you know, even have you, if, even if you have really quick latency with a, let's say an AI receptionist, there's still a little bit of unnatural lag that happens between the time you finish speaking and then it starts talking back to you. And sometimes if you, even if you pause, but it's a natural pause, like I just stopped talking for a moment, it will start responding even though you haven't finished your thought. So I, you know, I think there's up to this point, this air AI, you know, receptionist, AI voice agents have gotten really good, but they're still not quite to that, that human level yet where, you know, as I'm talking right now, you could be, you're, you are thinking and processing what I'm saying. A traditional, you know, agent will has to first turn all of your, your what, your sentence into a text, then figure out the context and respond. And it's, it's kind of like a, a chain process where this is, this is trying to make it more conversational. Anyways, I think it's a great idea. I also think it's interesting because we've talked about Thinking Machines Lab on this podcast before and how it's kind of funny because their website was very cryptic for a long time.
- [03:13]
A
Yeah.
- [03:14]
B
Last year they raised $2 billion in last July, giving them a $12 billion valuation. Yet they had, it was basically, from my perspective, all based around the, you know, Miriam Moradi's name, her credibility and things like that. All that to say is we finally have a product, or at least this is a, they're calling it a research project. They haven't officially released a product yet, but I think it's going to actually solve a really a big problem. And I think, you know, the evaluation maybe will be legit. So what are your thoughts on it, Jaden?
- [03:52]
A
Yeah, I mean, I, I do think one of the interesting parts about this whole business, I want to get into this, some of the technical stuff here because I do think it's really fascinating. But like, as far as the whole business, because we've talked about Thinking Machine before and, and we're like, you know, like they've raised so much money and it's all kind of off of mirror. Maria Moratti. One interesting thing about her though, that I will say is she is probably a multi, multi billionaire just from her OpenAI stake. So when, when she goes and raises a couple billion dollars, people aren't like just giving it to someone. I guess that is just Pure, you know, kind of clout and credibility. There was recently an article that I talked about how Ilya Suskever, one of the other co founders of OpenAI, he went up on trial to kind of defend why he kicked out Sam Altman. Anyways, there's all the drama between Elon Musk and Sam Altman trial. My favorite thing about the trial though, is that we're getting all of the, like, nitty gritty details because of discovery and because it's like a legal case that you don't get anywhere else. And in all of that, he had to reveal that he has about a $7 billion OpenAI stake. So he's one of the co founders with Mario Morti, one of the originals. So you can imagine Mario Morati, maybe she may have joined like a little bit later and maybe he was a little bit more of an OG. But I mean, she's got to have somewhere between 4 and $7 billion in equity or a stake in OpenAI, especially as it's kind of growing and stuff. So she's over there doing her thinking machine labs. She's, you know, raising it like a $2 billion valuation. She's raising $2 billion for it, um, and get a higher valuation. But she also has like a massive fortune just tied to OpenAI, and at the end of the day, like, that's where she can make a lot of her money. So anyways, I do think that's a very interesting part of the whole story. But as far as the tech of what they've released, I actually love it. I think I was, you know, I was really curious what she was going to come out with, because obviously if she was just trying to make another competing LLM to chat GPT, which they very well might, who knows. But, like, it didn't seem like it was, I don't know, you know, you go, leave OpenAI and just make another OpenAI clone. This is cool because it's something completely unique, which is kind of what I expected her. And even Ilya is working on something and they're making these kind of completely unique platforms and solutions that didn't exist before. And so specifically what they have done with this, it's called a full duplex. That's the technical term. And like you mentioned, voice assistants right now, they run on this, what's called a sequential loop. So I'm talking. It listens, it transcribes it, it sends it back. But when you have an actual conversation with someone, you'll know it's. It's quite a Bit different. Right? Like especially imagine like a heated argument. I'm thinking of like a podcast, but maybe you have a heated argument with someone you know and like you kind of talk over each other and they say something and you say no and then whatever. Right. Or like a negotiation that's like really active or people like talking really fast and they're all talking over each other. That is incredibly hard slash impossible for an AI model. I'm just thinking about myself having conversations with Chat GPT on their voice mode, which of course the voice mode. It sounds natural, it sounds good. But the problem with ChatGPT voice mode is it's like giving me a long response and it kind of already answered the question in the first half of its response. And so I'm like, okay, anyways, like I don't really need that, like move on. Tell me more about this. As soon as I start talking, it's like it like freezes. It's like, sorry, I missed that. What did you see? Like it, you know, it just like cuts itself off and it's like has this awkward moment where if I was just talking and it had kind of, maybe it would finish its sentence and listen to me at the same time and then immediately start talking to me throughout it. And it's kind of reminds me of what we're actually getting out of something like Claude Cowork or maybe even OpenAI is kind of doing this too where mid response you can actually ping it with new information as it's kind of writing out its response and it will change dynamically the response, which for quick little responses isn't that important because it does them pretty fast. But when it's doing like something like Claude Cowork, it's doing like this massive multi step project or building a website or a webpage for you. And you know, it takes five minutes and halfway through you send it a message and then it can kind of pivot and change. I don't know, it feels like the same concept, but they've done this in a technical way where it's not seconds or minutes, it is milliseconds that they're able to get the turnaround and latency down. Which is incredible.
- [07:45]
B
Yeah. I mean, what do you think the implications are for this? Because you know, right now I think, I think people are still turned off by the idea of like for example, AI receptionists. So it takes a lot of ability, it takes a lot of, you know, you have to be very creative in how you present that to somebody as far as something that they would want for their business, especially because people are thinking back two years to the last time they called tech support somewhere and they had to talk to like a very robotic answering service and they're like, I absolutely don't want that. It's changed a lot already. But this is kind of going to take it to the next level. So, you know, how do we. What are your thoughts as far as, like, how long will this take to be adopted by. By the masses or at least by. By companies so that they feel comfortable with this?
- [08:33]
A
So, yeah, I mean, I think there is a limited research preview that's coming in the next few months. They're going to have a wider release later this year, I think, until this piece of the puzzle gets solved. And I'd be So curious if OpenAI just clones this, which very possibly they can, or if people integrate with them to help them do it. I'm not sure what the, you know, how technical it actually gets, but I think until this piece of the puzzle is solved, people are still going to feel like it's quite robotic because if you're talking and it's talking and then it pauses and you have this glitch, it's just this awkward moment and just feels like a robot and we don't like it. I think at the end of the day, the AI receptionist idea will be fully realized and people won't mind or care if it is sounds perfect, acts perfect, it accomplishes everything in AI reception. And a reception is going to accomplish. Maybe it has all of the same authorizations to issue refunds or whatever. Like for me, when I talk to chatbots on a company's website, if it can issue me my refund or help me with my problem or, you know, whatever the issue is, if it has authorization to actually solve my problem for me, I don't care if it's a human. In fact, I'd rather it not be a human. I'd rather just talk to a bot that can solve my problem. But the problem is a lot of times we talk to these bots and they ask all these questions. They're like, let me route you to a human. And then it's just annoying. You just feel like you kind of wasted your time. Like there was a screener kind of like screening you. So I think that's probably part of the issue. And then there's like the whole latency problem, which is what they are basically solving here. And I think once this rolls out and with the right authorization that these, these bots will be awesome. The other Thing that I do think is interesting because you mentioned this a couple times of how people don't really like the concept of AI and even when you talk about a receptionist, they, they have these bad experiences. They think back to one thing that I, I think would give people a better, more positive connotation to all of this is less of replacing a person with the AI so like replacing your receptionist with the AI and more of, hey, you can do more than you did before. Like, you know, before your customer support people, they would get around, you know, within six to 12 hours to customer support requests. Or maybe you're getting super bogged down, you get days behind. Like, you know, that's a very bad experience or maybe you're really bad at calling people back and it just doesn't happen. So I think pitching things as like you, you were unable to do this before and now you're able versus like you can, you know, now I just can replace that person or do it a little faster. Like a little better isn't as good as like you are dropping the ball in this whole area and now this is going to fix that problem. So I don't know. That's a kind of a perspective shift that I think might be a better pitch for people for sure.
- [11:02]
B
I have one, I have one more question for you because I just thought of this, but you know, someone who is. Has seemed to expand beyond just like voice agents recently that I've noticed has been 11 labs. You know, they have, they've adopted on some actual agent functionality. They have, you know, a little music production. They're, they're really trying to expand on beyond voice just to audio in general. Do you think? I mean, I, I feel like that would be a perfect pairing with Thinking Machines product here, the, the full duplex. Do you think they're going to partner with someone like that or do you think they're going to try to. I'm just trying to think of how they can market this and actually make money off this, this new development they've come up with.
- [11:44]
A
If it's incredibly hard and technical and like they solved something that's very difficult for other people to solve, then I would see companies like 11 Labs, 100% partnering with them on this. If it's just like they figured out something cool, but they figured out at first and everyone else can kind of figure it out, which is what it feels like happens so often in AI, right. Like as soon as OpenAI is like we have a reasoning model and it's just running through a whole bunch of prompts. Everyone could kind of see how the reasoning worked. They reverse engineered it, all the Chinese labs cloned it and, and then now we all have the reasoning models because they weren't like a crazy technical thing to figure out. If that's the case, then I think you'll probably see companies like Opening and Google roll their own version of it. You might see OpenAI and Google roll their own version regardless because they don't really like integrating or working with other people. They can just try to figure out how to figure it out. But yeah, for a lot of smaller companies, I mean Open11Labs is getting to be one of the bigger companies now. But for ones that aren't OpenAI and Google, I think you'll see a lot of partnerships with with them to be able to get stuff down. I mean they're able to get the response time in.04 seconds, which is faster than OpenAI and Google. And I mean they solve a real problem. But my question is when they say look, limited research preview is coming in the next few months, wider rollout later this year, it's like, yeah, is later this year is Google and OpenAI not gonna have figured this out and already rolled this out? So I think that'll be the big questions timing for sure.
- [13:04]
B
Yeah, no. Thanks for your input. Hey, if you enjoyed this episode, we'd really appreciate a rating or review while you're listening. Those help us reach more people and we really appreciate them. Also be sure to check out our AI Hustle school community. We release bonus content over there each week about how you can actually use some of these tools. We try to stay up to date on the latest ones that are released and give you guys tutorials. Try them out, see if they can actually make you money. You're going to want to check out our school community. We'd love to have you be a part of it. Thanks for listening and we'll see you next time.