323. Building Next Generation AI Based on 20 Years of Research w/ Manish Patel | Jiva.ai

2 Jul 2026 · 35 min · 19 chapters

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In short

Episode 323 features Manish Patel, CEO/co-founder of Jiva.ai, discussing his 20-year journey from PhD research to building “next generation” AI intended to outperform today’s LLMs. He describes a machine-learning approach based on model fusion/“multiple models talking to one another,” aiming to create a reasoning layer beneath LLMs.

Key claims

LLMs are token predictors with performance leveling off; future gains require “more intelligence per byte,” better compute/energy efficiency, and deeper world/human understanding.

Notable examples

Jiva’s healthcare diagnostics (prostate cancer, liver disease) and non-health use like a virtual assistant that schedules meetings; optimizing LLMs with ~10% of the energy/compute. Guest/guests: Manish Patel only; he credits co-founders including a doctor and Sarah (co-founder), plus his chair Paul Codin and T. Kotak.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

Journey from Geneticist to AI Innovator

0:45 to 2:14

Mani shares his transition from genetic research to AI development.

“But I was a much better programmer and much better at maths than I was at the lab work.”

The Challenge of Early AI Adoption

2:14 to 3:28

Mani discusses the difficulties of gaining investor trust in early AI concepts.

“And obviously in those early days, I imagine you had to try and convince people that like, oh, this AI thing is going to be a big deal and people might not have believed you.”

Navigating the Healthcare Landscape

3:28 to 4:32

Mani talks about transitioning to healthcare and the challenges faced.

“And your original co-founder as well was a doctor, right?”

First Revenue and Client Experience

4:32 to 6:00

Discussion on how Jeeva made its first revenue and client insights.

“That's quite difficult to put together for a small company and be a platform as well.”

Building a Team During COVID

6:00 to 6:50

Mani describes remote team building and attracting talent during the pandemic.

“So we're, yeah, well, we're actually, the founders are all in London.”

Attraction of Talent to Jeeva

6:50 to 8:07

Mani explains what draws talent to Jeeva beyond financial incentives.

“And we ended up getting some really amazing talent on the team.”

Transitioning to CEO and Leadership Lessons

8:07 to 11:15

Mani reflects on his transition to CEO and the challenges of leadership.

“Same platform, two very different use cases.”

Finding Confidence in Public Speaking

11:15 to 14:00

Mani discusses building confidence in pitching and public speaking.

“You just kind of just bring and bear it and just get on and do it.”

Managing CEO Loneliness

14:00 to 15:12

Learn how CEOs cope with the loneliness of leadership and the importance of communication.

“With somebody working for you, they don't have that same control.”

The Importance of Co-Founder Relationships

15:55 to 16:43

Explore how co-founders can support each other and the dynamics of their relationship.

“And obviously you had Sarah who joined as a co-founder as well, right?”
Show all 19 chapters

Navigating Early Business Growth

16:43 to 18:34

Understand strategies for gaining customers and revenue in early-stage startups.

“I think the best co-founder partnerships are the ones where you actually complement each other's things, right?”

The Challenge of Self-Promotion

18:34 to 20:36

Discuss the balance between humility and self-promotion in business.

“But how we actually make that work is that we're not direct B2B, we're indirect B2B through partnerships, channel partners.”

Raising Your Voice in a Crowded Market

20:36 to 22:32

Learn how to stand out in a saturated market dominated by loud voices.

“I think it's the whole thing about is the means to an end, right?”

Building Next-Gen AI

22:32 to 26:38

Discover the vision for advanced AI that combines reasoning and language models.

“And you said as well, the idea behind this building is super intelligence.”

The Future of AI and Energy Efficiency

26:38 to 28:00

Explore how AI can be optimized for better energy efficiency in data centers.

“And then you can embed that in wherever you want.”

Optimizing AI Efficiency

28:00 to 29:28

Learn about new methods to enhance AI performance while reducing energy consumption.

“same tech to optimize large language models.”

Understanding LLMs and Their Limitations

29:28 to 31:36

Explore the fundamentals of large language models and the common misconceptions surrounding them.

“The same technology that goes into the same thinking that goes into making those efficiencies, I think are going to lead to the super intelligent pathway eventually.”

Recognizing Innovators in AI

31:36 to 33:30

Discover notable figures in AI entrepreneurship and their contributions to the field.

“There's the large language model and the tooling that's associated with it.”

Closing Thoughts and Networking Opportunities

33:30 to 34:36

Final insights on collaboration and networking within the AI community.

“And it's great to see that all three of those people here in the UK, not in the US.”
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Transcript

Automatic transcript. May contain errors.

0:00Hi, my name is Mani. I'm CEO, co-founder of Jeeva and we are building deep tech AI in the UK that's going to blast away LLM technology in the next few years.

0:12Amardeep Parmar:So you told me that it came out of your PhD, right? Yes. And you've been working and tinker on this for years and years. Yeah. Tell us that journey. Yeah. It's a bit crazy, right? So I actually started my PhD at around the time the Human Genome Project was finishing. So back then, machine learning was relatively new. I mean, obviously, it's been around for a while, but, you know, it actually being applied to real world stuff was a relatively new thing. And I was actually a geneticist at the time, molecular geneticist at undergrad. My lab skills were atrocious. None of my labs worked. I was terrible.

0:51I don't know why I did that subject. But I was a much better programmer and much better at maths than I was at the lab work. So I switched over to that and I did my master's and my PhD in that particular subject. And it started off very much as a how do you solve complex problems? How do you solve complex systems? And we kind of discovered a way in which we can do machine learning at a pretty grand scale. But in a way that enables you to get lots of different models to talk to one another, merge and fuse. and that's quite similar to the way your brain works. So fast forward 20 years, we kind of realized that actually we could probably use this for real world machine learning, real world AI, and this would probably be the basis for real world reasoning.

1:41And so that's what we've been working on under the hood. And I think we were a little bit early, if I'm honest, to the pie. So we ended up doing a lot of no-code AI and that kind of thing in the interim. But in actuality, the real thing that we're going inside the company is how to build super intelligent machines, which is why it's called Jeeva. And I think a lot of you are Asian. Listeners probably understand that word, but we'll let the listeners figure that one out.

2:07Amardeep Parmar:And it's a critical, right? Because you said where AI is now this big boom, right? You did it before it was cool. Yeah. And obviously in those early days, I imagine you had to try and convince people that like, oh, this AI thing is going to be a big deal and people might not have believed you. People didn't get it. One of the big investors that we had at the start was like this high net worth network. And I remember I had to do this massive IM. And I was told to demote the platform vision type of stuff in the favor of a very specific use case, which is prostate cancer, which we were doing at the time.

2:45and we had to do that specific use case just because people didn't get that you could do this big platform where you're doing things. So it's weird that it actually dictated the way we had to take the company because investors didn't get it. And so we had to tell this story in this particular way. We ended up getting into med tech and healthcare and people still associate us a lot with healthcare. Actually, we're not a healthcare company. But it's weird how you are kind of made to go in a certain direction and just because you're either too early or people just don't get what you're doing. And I get it.

3:21I understand why that has to happen. But if I was to do that again, I'd probably be a bit more stubborn about not going that way.

3:30Amardeep Parmar:And your original co-founder as well was a doctor, right? Yeah, he's a doctor. So that made sense, right? So before we even started, he joined the clinical entrepreneurship program with Tony Young. and it's incredible entrepreneurs there and it's great to see how they've all evolved.

3:50So the idea was, look, healthcare is right here. There's a really big upside. Healthcare is a big industry, right? Really big upside. Even if we weren't industry agnostic and we were just concentrating on healthcare, that's still a massive market to operate in. And we did it. We did a prostate cancer diagnostic. We did a liver disease diagnostic. We've done various other very high fidelity healthcare applications. And we're showing that we do that on the platform. But the reality hits when you actually try to make that real, right? So I could create a diagnostic all day long. But to commercialize that, that is a whole different story.

4:28You've got to go through our own regulatory thing. You've got to have a whole dedicated team that can do those kind of things. That's quite difficult to put together for a small company and be a platform as well. So we made the strategic choice of, okay, look, we can enable those things, stay generic in terms of our platform. So we make a big deal of the fact that when a company comes to us to build something, the IP they generate on the platform is theirs. So if you want to build a diagnostic, you can build it on the platform and that IP is yours. You can do whatever you like with it afterwards.

4:58But hopefully it stays with the platform and you run it in the platform and that's how we make our revenue.

5:02Amardeep Parmar:How did you make your first revenue? Was it in the same way or how did you? That's how we did it in the first place. It was a weird one. I still remember the first client. It was a diagnostic. And we realized that actually, although we were saying we were a platform in order, license generic, actually, again, reality hits. You're like, okay, there's still all these things that don't work. You've got to figure all these things out. That's going to be like 12 months worth of development. it um so we realized pretty quickly actually we've got to get people on the platform get people using it we've got to get feedback and actually start building that in rather than it just being a brainchild of us as a team and we're all technical people so we're probably not the right people to be to be building it um or to be building ux had us uh yeah that first revenue was it was difficult together but we got it we got it made it work and and and got it got it running it's but it was a learning process for sure.

5:58Amardeep Parmar:And you also said as well how it's a Welsh company, right? And a lot of the team is in Wales. So we're, yeah, well, we're actually, the founders are all in London. Most of the team is in Cardiff or Newport. That's actually, it was quite fortuitous. We got investment from Development Bank of Wales, and therefore you had to headquarter in Wales, which is all fine. That was during COVID, so it was a weird time anyway, and no one was kind of traveling anyway. And what we found was Cardiff, Newport, Bristol, those areas have an amazing tech talent, amazing for about half the price you get in Reading and London.

6:38And it just worked because it was during COVID. We did actually technically, we had an office, but no one was going in because of COVID. Everyone was working from home. And so we just grew in this remote kind of way. And we ended up getting some really amazing talent on the team. And we pack a big punch, right? We got like a quantum physicist PhD, we got a machine learning PhD, we've got an imaging PhD, like crazy, crazy clever people for what I think was, you know, got a little bang for our buck, basically, right? Young in their careers, really raring to go, still really excited to work on stuff.

7:16It's great. I mean, I love my team. They're They're a great bunch to work with.

7:20Amardeep Parmar:How were you able to attract that kind of talent? My stunning charm. No. I think it's a couple of things. I think because we started off in healthcare, actually, there was that draw that you're doing something. I was setting the draw for my CTO. It was you're doing something for a greater benefit than just money. And whilst we're technically industry agnostic, I think that draw is still there given that we still do a lot in healthcare and life sciences anyway. So yes, of course, we have to generate revenue. We have to create value in the company. The stuff that we're working on is so fundamental.

8:02Like if I told you you can use Jiva to either create a diagnostic or create a virtual private assistant for yourself, that would arrange your meetings. Same platform, two very different use cases. The productivity gain is awesome for you as a founder, for you as a company, whoever you might be. If it's a diagnostic, even more so because there's a long-term thing there as well. So I think that's actually what attracted people to the company. is just the long-term benefits of what we're doing. I think that's really important.

8:37Amardeep Parmar:How has your role changed over time as well, right? Because obviously you started this when you started it and then now you've hired a team and you're doing some different things. Yeah, so I started off as the CEO. Right at the beginning, I started off as the CTO. We didn't have a CEO. We hired a CEO. It didn't work out. And my chair was like, look, Manning, it's got to be you. And I said, no, I don't want to pitch. I would much rather be sitting behind a screen, at least at the time anyway. Much harder to be sitting. This I would find really hard. I'd find it hard to talk to someone on camera.

9:14That's not my, I'm not innately built like that. And I had to really force myself. At the time, we were just jumping onto the KQ Live Accelerator. I don't know that one. And so it's a accelerator program in Kings Cross just for life science companies, healthcare companies. It's a really good accelerator, I've got to say.

9:34Amardeep Parmar:Francis Carrick. Yeah, yeah. Francis Crick Institute, yeah, yeah. Carrick, I was there, footballer. You're not Carrick. I was made then, because it was happening during that time, I was made then to do the demo day, which was then to pitch to 200 or 250 odd people at the Crick. and I like I remember that day I was nervous for two two and a half weeks I was all I could think about was how I'm gonna be when I do it because I feel so you know like you know pitching in front of people it's hot um so yeah I had to try to make that transition to CEO and I gotta say that's even if you've been a CEO before like this is my second startup not I wasn't C2 and the other one you just don't learn enough right and then when you're a ceo is a whole different ballgame because everything just comes up to you whether it's good or bad or whatever it is everything you're the only person that knows everything and it's really difficult to keep your head screwed on and mentally okay having to like do that transition right of like there's gonna be plenty of people as well who will say like okay i'm an introvert i don't want to be pitching get on that kind of stuff.

10:44Amardeep Parmar:Was it just reps or how do you think you got the confidence? Yeah, there's a few techniques, I think. So the number one thing I learned was I'm not good at memorizing words. I'm not good at memorizing, I mean, not words, I'm not good at memorizing whole texts. I should have known that from English, like English lit, we have to memorize a sonnet. Got about a third of the way through it and started making it up. It was terrible. But I'm quite good at memorizing bullet points. So now I think it was just about technique right so if i do it i'm doing a pitch i generally just have some bullet points in the back of my mind that i've memorized and then i'll just ad-lib through it and i'm quite i've found i'm quite good at ad-libbing and it's just like a self-discovery process right i still get really nervous i still get really nervous at pitches last week when you were there uh i you know when i get up there i forget about it but up to that point i'm quite nervous and but i can't show it i've You've got to remain confident and look confident on the way to smile.

11:46Amardeep Parmar:I don't think there's any fix for that. You just kind of just bring and bear it and just get on and do it. I think that's it. I think in my head, something just clicks and says, okay, look, just do it. I find what helped me in the end is I just got so busy that I didn't have time to stress about it. Just stress about it. Yeah, it's like I need to just get something done. Okay, I'm on stage now. Your mind doesn't have the bandwidth to deal with that stress. Yeah, he's like, yeah. It's like, well, our demo day is in like two weeks. And I'm hosting it, but I haven't thought about anything I'm going to say yet.

12:15Amardeep Parmar:And even I'm doing the talk soon. It's like, I kind of almost in the way, like, if you keep putting yourself in a pretty situation, it's like, well, I did it last time. It was like, yeah, it should be fine. It should be fine. Yeah. Yeah. I think for me, it's, I still, I need a framework in my head. Otherwise, I'll just, I'll just like babble. I need a framework. But so long as I have a framework, I feel confident when I'm standing up there and I'll just deliver it. But I understand that because there's loads of founders that especially academics, especially like really mathematical people or really deep tech people, they're not used to that.

12:51And it's difficult then to get up and be passionate about the thing that you're talking and put that across.

12:58Amardeep Parmar:And like even the other parts of the year or you said you've got, everything comes up to you eventually, right? Have you found that? How do you think your style has changed over the years? Yeah, people management is difficult. I've got to say I was quite lenient to begin with. I was quite open and I'm all about transparency and all that kind of stuff. And then you realize that actually that's a double-edged sword. It's great to be transparent, but you've got to be really smart about what you reveal to certain people. Because certain people, for the things that I'm like, other people will panic about that situation.

13:34So you've got to be sensitive to, is the right word? Empathetic? to what they might feel respond to a certain situation. That was my biggest lesson. You've got to learn how someone else might respond to something. That's quite hard to predict. I think I was too straight. I think I was too transparent before. Is that right? Too transparent, too straight is probably the one thing.

13:55Amardeep Parmar:I think it's that thing of where, as a founder, you've got to be able to believe you're just going to get through it. With somebody working for you, they don't have that same control. It's out of their control. They've got to believe that you can get through it. Yeah, exactly. And sometimes the more they know. Yeah, exactly. And if you reveal, it's a weird one because you're often told that you should reveal how you feel about stuff. I actually think, yes, that's true. Okay, fine. Be open about that stuff. But if you reveal your fears, if you reveal that something you're actually really worried about to someone in your team who is not used to that kind of stress.

14:30Amardeep Parmar:Yeah. That has a really deleterious effect. and what's worse is that you know it happens in small teams people talk and then you get Chinese whispers and it gets out of control sometimes it's better not to say anything or just say this is the situation, I'm handling it and it's quite a hard thing to do because sometimes that makes you feel quite alone on that journey and I think that's the number one thing for CEOs is the loneliness co-founders helps, I've got to say you can share that with the co-founders I have a lot of respect for entrepreneurs a lot of respect because they don't have anyone really to tend to Hello, hello I hope you've enjoyed the show so far I'm Amiri Parma, co-founder of BayHQ and the host of this show For those of you who don't know BayHQ is the community for high growth Asian heritage founders and investors in the UK Over 7 ,500 people have attended our events 200 people have been through our impact programmes and obviously there's been over 250 episodes of this podcast.

15:37Amardeep Parmar:If you want to join us and take part in the programs and come to the events, go to behihq.com forward slash join. We also just released our first ever book called Startups for Outsiders, which you can get on Amazon now and the link is in the bio. Hope to see you soon at our event. Hope you enjoy the rest of the episode. And obviously you had Sarah who joined as a co-founder as well, right? Yeah, exactly. There's three of us in total. And, you know, she's got her head screwed on, has her head screwed on. And we, you know, we have our founders meeting this Friday. And we have that on a regular basis where we just go out, we have a drink, we talk about issues.

16:16We might argue a few times, that's fine. But we unburdened. I think that's really important. It's just unburdening.

16:23Amardeep Parmar:Yeah. It's the same thing with your co-founder, that I'm in the public face with a lot of what we do. But then actual, a lot of the work and like the partnerships and the documents and all that stuff is all through him. Him, yeah. So it's kind of the interesting dynamic of where people might find out about us because of me, but then he's the one actually doing the details. Yeah. And it's like that constant alignment that we need to keep doing. Yeah, but that's a really good... I think the best co-founder partnerships are the ones where you actually complement each other's things, right? I'm terrible.

16:51I'm like, I'm terrible with detail on things like documents. Sarah's doing my head in when I don't read... I sign something in my ass, man. Sign her... You're like, well, you didn't know it's a positive way to make it. She does all the things really well that I don't do well, right? And vice versa. And similarly with chat. So I think it's important when you're finding a co-founder that you have that cadence. But communication is key, right? So again, we have a founder meeting every Thursday morning as well. It's just half an hour for us to just, not just unload, but just to say, look, this is the situation.

17:26This is what we're doing. communication is one of the most important things that early stage companies that I didn't appreciate was you know I've got everything up here if I'm not communicating that then that's it's a problem right yeah similar with everybody else again that's another skill to learn and you said at the

17:46Amardeep Parmar:moment as well because now as like things are getting further you're now kind of more focused on like you need to get the word out about what you're building because if people don't know what building, then how, one, are you going to get investment, but also customers? And like you said, okay, you now pitch more confidently or you need to force yourself to do it. Yeah. How have you been thinking about that? Like how did you get the word out initially? Like how did you get your first customers? How did you get the revenue building up to where it is? Is it more word of mouth? Yeah. So it was close network is where it started.

18:13And it's been a bit of a journey figuring out how to get revenue. Got good revenue through network, that's okay. But Now we just have to be out there and people need to see you for what you're doing and get them to be able to use your product and then have confidence in it. That's more about marketing than anything else for us. But how we actually make that work is that we're not direct B2B, we're indirect B2B through partnerships, channel partners. That way we found actually much better than direct. And again, I don't think it's very easy to figure that out from the beginning. You've got to kind of meander your way there and find that, oh, look, this works.

18:56So that's how we kind of got there. We didn't show off enough. I think that's a British problem. It might be an Asian problem as well, maybe. That we just kind of like... Double weakness.

19:07Amardeep Parmar:Yeah, yeah, yeah. It's like, okay, look, this is what we're doing. You're really straightforward about it. But when I talk to other people about it, they kind of look at this and say, Man, that's amazing. And we're like, is that? But I think we lack that Americanism. Yeah. We can do this. So often I miss your kid, but it's like, so often you see people pitching, and it's like, it's all about the product, product, but the team slide is like 10 seconds. That team slide is a bit that matters. Yeah. If you're not going into the team, and you're not telling us why you're the right person for this company, you're not going to get investment.

19:43My last chair, and my current chair also, Paul Codin and T. Kotak, they both have told me that I don't like enough. And I'll tell you now, I didn't tell you in my introduction, I literally wrote the book on AI agents in 2011 and published it. I didn't say that before. I don't show off enough about it. Because it just feels a bit dicky, right?

20:13Amardeep Parmar:The problem is that people don't say it. The ones that do say other stuff, they're They're the ones that get stuff. Yeah, yeah, exactly. Exactly. There's a balance, right? Stay, try to stay grounded. You know, one of our core company values is to be humble. Keep your feet on the ground. No one is better than anyone else. But since there is a balance, sometimes you do have to show off a bit to be able to get the things that you need. Yeah. I think it's the whole thing about is the means to an end, right? Is that the people are trying to show off because that's the end for them. They want people to think they're amazing.

20:43Amardeep Parmar:Whereas the people who think it's a means to an end, it's like, But by somebody knowing you're an AI agent, now they're going to know that you have a really deep understanding compared to everybody on LinkedIn now who's apparently an AI agent. Yeah, all of a sudden, like that. And the problem is that some of those people are speaking so loudly about it, and then people are like, oh, I need to learn from that person, rather than the person who actually wrote a book on it 15 years ago now, right? And that's the problem. There's a miscommunication, misalignment in the industry a lot where there are all these people who just speak really loudly constantly yeah and it seems for example like this right it's like with the podcast we don't generally get people on who ask to be on we're kind of selecting people yeah because by me kind of having tech are not argue but like kind of get people on yeah they're more likely to be like have the right mindset yeah whereas people who are like desperate to come on so do they just want to come on to show off or why do they want to come on right so it's always that thing about like how to frame that correctly because a lot of people listening right?

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21:40Amardeep Parmar:A lot of stuff they see on LinkedIn is actually going to be a load of bull most of the time, right? Because some of the people might not post as much because you're all humble about it. But then they're seeing stuff that isn't quality. It's a problem. And the other thing is there's a lot of voices. We were talking about it before. How do you get your head above the water when there's three million other people saying almost the same thing is you, it's really hard. And I guess these podcasts and things, these are the right way to get your head up in the water because you get the right audience.

22:18You get people understanding what you're saying, more or less. Not another LinkedIn post where I'm trying to get 300 likes. It's a real thing where you're having a conversation and there are people that are actually natural and actually listening.

22:32Amardeep Parmar:And you said as well, the idea behind this building is super intelligence. What is that road map for you? Where do you see this, everything going in the next few years? Controversially, or maybe not so controversially now, I think that the large language market is going to have a mini burst. I think probably one of the big companies is going to have a serious dent put into them. I'll tell you afterwards, in case I get sued, I'll tell you which one I think it is. I think people are starting to realise that there is a levelling off of performance, and we can see that in the numbers as well. So for every dollar that's being spent on large language models, there is an incremental decrease in the performance benefit that you get from that model.

23:12Which is not that surprising, right? If you think about how your brain works, you're not thinking, of course, you're thinking in language in some sense, but you're thinking about something deeper when you're thinking about what next question you're going to ask me. Now you're trying to understand what I'm trying to tell you. You're thinking in images. Large language models are only token predictors. and there's only so much intelligence you can get out of them. I've had that argument a lot, especially on LinkedIn and X, that people are trying to say that this is the next step to AGI. Yes, it is a step.

23:46But for us, I think the next step actually is creating that underlying reasoning layer that can sit below LLMs. I'm not saying LLMs are useless. They're actually extremely useful. There's a certain level of reasoning that can do, and obviously excellent language generation. But that layer underneath of understanding the real world, how the world works, how humans work, how interactivity works, you know, those kind of things. That's the next level of intelligence. And that's what we're working on, right, with model fusion is a way to be able to represent complex concepts to a machine in which they can actually reason over.

24:24And the corollary of that is that you can do that in disjoint ways. so you can learn about small things, right? Just like when you were at school, you learned about English in your English class. Then you went to your maths class, but your teacher was teaching you in English. So your brain was great at meshing those two things together. This is what we're trying to replicate, is you learn something about one particular knowledge base. And in a machine, it's quite hard to integrate a different knowledge into it. And we've figured that out. We figured out how to fuse those things together. and in the hope that you can actually create a bigger and bigger and bigger intelligence.

25:03And that's what we're building with Jeeva. To you, it looks like a no-code AI platform. You do your things on it. You build stuff. Actually, what we're doing under the hood is learning how you are thinking. And in doing so, we're teaching the machine how to do bigger, more complex stuff. And eventually, we'll have a model that is able to reason properly and in a way that is able to do it at a human level more than just a language level.

25:30Amardeep Parmar:Long term, does that then mean, say, the big names at the moment, right? The way they're doing things, actually what you're doing, is it almost a replacement or is it working together? I think it's parallel, right? So the way I visualize it is that there is a dimension that has all the large language models. There's a dimension that has all of the zero code tooling. And there is a dimension that is working on deep intelligence. And we kind of sit at the nexus of all three. So machine intelligence, which is the company that Jan LeCun started, is very much on that deep tech side. But not very much on the delivery side.

26:09Whereas the no-code, like for example, H2O and Data Robot, these kind of things, they're very much on the delivery side. They're not actually that intelligent. But they have all the tooling available to do some really complex stuff.

26:25Amardeep Parmar:And large language models are just large language models. And so I think it's actually amalgamating all those three things into one roof. That's actually what we're trying to get to. And that will give us the thing that we think is going to give you super intelligence. And then you can embed that in wherever you want. So you could embed that in a robotics framework to drive a physical machine to do something. You can embed that into a surgical robot to do what a doctor does and actually understand what they're looking at rather than just machine learning or pattern match. Possibilities are endless then, right?

27:07Amardeep Parmar:And so looking at that, right, so say long-term future with the next two years. So what we say is like, so we're like now this will be up to 300 or something, right? we're saying in two years time, so 20 episodes later, we'll get the same guest back on again to look at what's happened in those two years. What would you love to say in two years time you've been able to do? I'd love to be able to say that we've got some amazing investors on board who understand what we're doing and our mission and our grand vision. And I'd love to be able to say that we've been able to show that you can squeeze way more intelligence for every byte in a machine than an LLM ever could.

27:53Those two things I want to start out and prove. And we've already started to show that. We've applied the same tech, so I've reversed it a little bit, I guess, but applied the same tech to optimize large language models. and we've shown that actually we can optimize a large language model with 10 % of the energy and compute than anyone else that was my next question is going to be because obviously a big

28:16Amardeep Parmar:thing right now so i hosted some glass suite for the mayor's office which was i think urban data sensors yeah and about how that's becoming a big problem now it's like okay people want fast ai and inference but they don't want to deliver next web data center and obviously you're seeing the whole like the gold rush now is the shovels, right? And there's so much now demand for how do you make energy more efficient rather than obviously we're doing, it's like we'll make the AI more efficient and you don't need as much of that. And is that also like a big play of like what you're building? Massive.

28:47Yeah, massive. Because at the moment, what are the biggest constraints, right? So a lot of people are buying into data centers. Data centers necessarily need a bunch of GPUs. There is a massive supply pressure on GPUs. That's why NVIDIA is so... its market cap is ridiculous at the moment. And energy costs are going up. So everything is pointing to how do you get more from less? Everything is pointing to that right now. So I don't think we're too far away from having GPT-level performance type models that are able to run in a quantized way on your phone without killing the battery. It's that crazy.

29:31without an internet connection. We're not too far away from that. The same technology that goes into the same thinking that goes into making those efficiencies, I think are going to lead to the super intelligent pathway eventually. What we're seeing at the moment with LLMs, I think it's just not sustainable. You can't just keep growing data sets. You can't just keep throwing loads and loads and loads of compute at this thing and saying it's intelligent.

29:56Amardeep Parmar:I just don't see how the maths works. I don't see how the economics works. And you can see that with the revenue numbers for some of these companies as well. So I think the key is more from less. And say for example, right, with you, it's like, if people are using a platform and the usage increases massively, and we know for example, the traditional AI models is that that also increases the compute or the cost per token significantly, right? Yes, yeah. Do you not suffer from that same challenge? It's possible that we would, right? And it's just a matter of whether your curve looks like this or your curve looks like this.

30:30And we're trying to look for the shallower curve, essentially. I think there's any getting away from you trying to do more, you trying to get more reasoning, and you actually spending more compute. I think that's a pretty straight line. um i would be surprised but i would strive for a way in which we can get a leveling off of compute so beyond a certain level of complexity in your task the amount of compute that you require it remains consistent that's not too different from the way your brain does it So there is a physical precedent already for that to be the case. Therefore, is it beyond the realm of possibility that it's not possible to do in machines?

31:17I don't think so.

31:19Amardeep Parmar:So before we go to wrap up questions, right? So there's obviously a ton of new generation AI founders who maybe don't really understand the fundamentals of AI. What do you think some of the biggest mistakes other AI founders are making? What LLMs can actually do. So try to understand what an LLM actually is, right? There are two things. There's the large language model and the tooling that's associated with it. LLM, all it's ever doing is predicting tokens based on the context. I still find it amazing. You can suck in the whole internet and then some and get this model that can predict language so beautifully and respond to questions and all that kind of thing.

31:58But it's fundamentally not intelligent. It becomes a bit more intelligent when you give it tooling. So if you give it coding tools, for example, then okay, you can start generating random numbers properly and things like that. But it can't be your creative partner as such. It's only really regurgitating stuff that it's actually already surmised about and then maybe changed a little bit along the way. So understand what it actually can do for you, what it actually is. Don't over-rely on it, not yet anyway. Maybe in the next two years, again, and different technologies will come in and change things again.

32:35But as it stands, large language models are what they are, and just understand what they are.

32:39Amardeep Parmar:So we're going to get to a rough questions now. So first one is, who are three Asians of Britain you think are doing amazing work? I just want to shout them out. Ad Gandhi from AmmoDisc is doing some pretty cool stuff with Oliver Wiley. They're both co-founders. They're doing some medtech stuff, which I think is really cool. um i'll wrap two in one with deepak kotak who happens to be my chair as well and um ashir gratior who is uh both co-founders who are both co-founders of a health tech company called and they started off doing stuff in the asthma world and now going off into the cardiac world and they're the way they're going about doing these uh diagnostic tools like or you know predictive tools that can help pharmaceuticals and those kind of things.

33:29I think it's just going to change the way we do pharma. And it's great to see that all three of those people here in the UK, not in the US.

33:38Amardeep Parmar:Awesome. And then if people want to find out more about you and more about Jeeva, where do they go to? Website's a good start. LinkedIn to me. Happy to chat to people and happy to have a chat about what we do. But essentially, we put pretty much everything, very open. We're trying to put everything now on LinkedIn and X and various other channels. And we're trying to be very open about what the future of AI is going to look like with Jeeva. Is there any way that the audience today might be able to help you? One thing I've learned through this whole journey is network is everything. I'm more than willing to network with anybody and everybody who can slot in, plug into any one of my gaps or I can slot in to their gaps and together we create an awesome ecosystem that does awesome stuff.

34:28Awesome.

34:29Amardeep Parmar:Thanks so much for coming on. Thank you. Thank you for having me. Any final words? Yeah, rock on. Don't keep going. Don't give up.

From the publisher

Amardeep Parmar from Bae HQ welcomes Manish Patel, CEO at Jiva.ai


Amardeep Parmar:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Manish Patel:

Jiva.ai

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