Founder's Story - The Future of AI is Private: Gavin Whyte's Bold Vision at Brew AI | Ep. 191

Episode Date: March 18, 2025

Gavin Whyte is a visionary leader with over a decade of expertise in artificial intelligence. Transitioning from a background in design and mathematics to becoming a pioneer in secure, private AI, Gavin has redefined what’s possible in enterprise technology. His journey, marked by roles as Deloitte Australia’s chief scientist and adjunct professor, underscores a relentless pursuit of innovation.HIS JOURNEYUnconventional Beginnings:Gavin’s story began in design, where his passion for aesthetics and creativity merged with a natural talent for mathematics. A pivotal shift led him to computer science, igniting his lifelong commitment to AI.Career Milestones:With significant stints at Deloitte Australia and as director of data science at KPMG, Gavin honed his skills in predictive analytics, neural networks, and deep learning. His academic and industry experience set the stage for founding Brew AI, where he now leads cutting-edge research and development.VISION & IMPACTAt Brew AI, Gavin is dedicated to building secure, private large language models that empower industries such as law, finance, and government. His work ensures data integrity while driving scalable innovation. By developing advanced AI solutions that reduce hallucinations and enhance predictive accuracy, Gavin is transforming how organizations harness data.INNOVATION & THE FUTURE OF AIGavin’s forward-thinking approach centers on integrating deep reasoning models and AI agents to create smarter, more efficient systems. His vision is to unlock the full potential of AI, enabling businesses to make better, faster decisions while safeguarding their intellectual property.CONNECTLearn more about Brew AI and explore Gavin’s transformative journey at brewai.com. Connect with Gavin on LinkedIn for further insights into the future of artificial intelligence.Our Sponsors:* Check out Avocado Green Mattress: https://avocadogreenmattress.com* Check out CoinFlip and use my code FOUNDERS for a great deal: https://coinflip.tech* Check out Indeed: https://indeed.com/FOUNDERSSTORY* Check out Kinsta: https://kinsta.com* Check out Plus500: https://plus500.com* Check out Rosetta Stone and use my code TODAY for a great deal: https://www.rosettastone.comAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

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Hey everyone, welcome back to Founder's Story. Today we have Gavin White and Gavin, you are the global CEO of Brew AI with over 10 years of experience working with AI, former chief scientist at Deloitte Australia. We're going to get into all things AI, which is my absolute number one topic. I think it's our most popular topic right now, because I can be a little bit pessimistic, a little bit optimistic, but I'm gonna be very curious around your thoughts

with the future of AI. But before we get into that and all the things that you're building at Brew AI, how did you get started with AI specifically? And then why did you create Brew AI? Daniel, firstly, thank you for having me here today. So how did I get started? Kind of a strange story, actually. But I'll tell you anyway. So when I was younger, I was actually a designer. So I love to design clothing.

And I was really good with mathematics for whatever reason. And one day I was really angry with my parents because I was in the studio and it was there. They had a whole fashion house and they had a background in retail and clothing. And I said to them, this is not quite working. I'm changing all the designs. They got really angry with me. They kicked me out of it and said, you're going to go to university and study mathematics. I went to university to study mathematics, but I didn't quite take mathematics. I took computer science and mathematics and realized that I actually loved it so much so that I got into it and it was amazing. I started to program and that's how I got myself into AI. I started to do statistics

and write algorithms and code these algorithms at scale. And I was really good at it. So that's how I actually got into it. I know it's strange, but hey. Well, it's a good thing that your parents pushed you to do that. Otherwise you might've been in fashion, right? Although I could say you are very fashionable and I need some help on that end.

So maybe AI, you can build me something that AI can help. But so how, so amazing story. I obviously you've been doing it for a while. You've seen a lot of the transitions the last 10 plus years. Then why Peru AI? And I see what you're doing with private LLMs, which I feel like are going to be a massive part of our future. Absolutely, Daniel.

So one of my roles previous to starting as chief scientist, I was the junk professor at the University of Technology in Sydney. So I was teaching deep learning and mathematics to students. And some of the key areas where I did a lot of research in was in neural nets and back propagation, not to go too technical. here, so I'm going to try to keep it a bit high level. One of the key areas of focus was in research. How do we ingest large volumes of data?

How do we predict accurately? Those days, I was doing predictive analytics with neural nets, not only just your basic predictive algorithms. That's where the interest started quite a lot. I got into the industry and previous to Deloitte, I was the Director of Data Science at KPNG. I started to apply this at scale in banking, et. Utilizing that background and thought process, I started to put a lot of effort into how the neural net neural nets and LLM area. It was around 2019 when Stanford released the paper on neural nets.

When I really got really excited, I know predictive analytics, you need scientists, and now suddenly we've got this large language models where the AI can talk to you and produce information. That got me really excited. That's when I set up a team of researchers around the globe from Oxford University, University of New South Wales, and that's when Brew AI evolved and I left Deloitte and I started Brew AI to actually then research, build these platforms and grow that in the industry. If somebody has no idea what a neural net is, can you explain that? Yeah, sure.

I'll explain it in probably the most simplest way. Neural nets, you think of it like your brain. It has connections, et cetera, and it can ingest large volumes of data. Prior to neural nets, you have your basic algorithms that were stifled by data and stifled by training, but neural nets allowed you to grow. Hinton, as we call the godfather of deep learning, invented what we call back propagation, which allowed scientists like myself and others to ingest large volumes of data and give you accurate predictions.

That was the whole premise. So think of it where the synapses in your brain grows, the same with neural nets, the more data you feed it, the more intelligent it became. And then you apply a whole lot of algorithms onto it. And that's how we came up with LLMs or the scientific community has. No, Gavin, that's amazing. And thank you for explaining that because I think a lot of people are okay when it is a, you know, a techie explanation. But I think a lot of people are being lost because there's not a

lot of people explaining things. You know, and I feel like this is at one of the most amazing times in our lifetime, I believe. We're at this inflection point where all these technologies coming together. So you've done all this, you create Brute AI. Are you... and there's the reason why you created it because there's a lot of talks around corporations and data. If you use ChatGBT for example, will somebody else see what I'm having? Or if I use DeepSeek, who sees that data?

There's a lot of these talks around who's really having access or who can see this data. Is that why corporations are more apt to use a private LLM to ensure that sensitive information doesn't get out? Yeah, absolutely, Daniel. And I think one of the key areas in corporations is to keep their data safe, private. So if you start using other types of LLMs that are open, and generally, I don't like to refer to their names. You are sharing your data with the world. You are sharing your company's IP with the world. Whether you ask it a question with fake data, you are sharing how you think as a company and

you are training that LLM. Now, if you're in a business and you want to keep your IP safe, Now, if you're in a business and you want to keep your IP safe, going to these open LLMs, as we call it, and sharing your questions and your information to the whole world will only train that brain. That is one very large big brain that works at scale, which is not specific to any industry. But when you start using private LLMs, we can encrypt the data, we can store it on these servers, and we can provide the same level of intelligence as you would get on the larger ones on smaller machines, but more accurate. Are you finding that governments around the world or government organizations, are they

leaning on this? And I'll talk a little bit about that from an Australian perspective. When we did start in Australia about three years ago, we started to grow into mining groups, into big legal firms, and into government as well. And the reason for this is because governments want to keep citizens' data safe and they don't want the private LLMs to be biased. They want to train it and control it to allow citizens to interact with it without outside influence. Hence, that's why we have deployed it in these scenarios as well. We use it for case law, for legal companies where the LLM

can analyze the cases and very specifically spit out the outcomes. And there's one thing I want to point out, Daniel. You may have used chat GPT and other types of GPT where you may have heard it made up information. It created information. Michael Cohen is a famous Trump lawyer, we submitted information and the, and Chia Gbt created a whole case, which was all fake, which is submitted to the judge, which he had to retract when they did find out that case was made up. Now we call that hallucinations in the tech industry. These LLMs hallucinate. And that's okay. It depends on the level of hallucination that you want to reduce. So what we did is last year we released a global mathematical paper on how to reduce hallucinations.

We were first on the globe and we were very welcomed by all scientists around the globe at this very large mathematical conference and we actually solved that problem. So we have a very extreme rate of hallucination reductions around above the 90s and we've included that in this private technology. So now we're starting to see we're in the forefront of how we get answers out from the questions you ask it without it hallucinating, which was a huge milestone for the company as well. My LLMs hallucinate all the time, my GBTs, and I've gotten into the situation where I have used wrong information,

not knowing it was wrong information. So I can see the massive value in and I'm doing small things. I can imagine if it's, if I'm an attorney or something. So can you, can you talk to me too about, so is a private LLM like an empty brain and it only works as you add things or does it like if you give it to a company or you or a company starts using it, does it already have a certain amount of information based on what they want? How does this work? Yeah, so there's many ways to use private LLMs. There's a lot of open source LLMs which you can incorporate into private or you can train

your own. So we do a whole mixture of all of these. You have your base models. But I think what's really important is when we do test this, for example, in legal, you know, we had to give them a base model. You can train it with, there's a lot of court cases around the globe. You know, they all open anyway. But in the Australian setting, you cannot train it with existing client data.

So we don't do that. So we want the LLM not to be biased as well. So we give them base models and these base models, they upload the data, they index it, and just by uploading a PDF or a whole folder of cases, and they can ask it all the questions. And it does a very, very good accurate outcome. And one of the largest law firms in Australia today uses our product. So we make it as easy as we can for our customers. We have these base models. They don't need to do any more training.

You can't from a legal perspective, but you can in other industries in marketing, etc. You can actually utilize this LLMs at scale and further fine tune it to refine it to your outcomes as well. Thank you for explaining that because no one has ever told me the details and the detailed differences between public and private. I can see a massive industry. I would imagine this might be the fastest or highest grossing part of AI going forward just because it's a huge topic around these companies using, like you said, something that is more open. using, like you said, something that is more open. So when you look at the future of just artificial intelligence in general, there's talks about AGI and, you know, some people say a year, some say 10, then there's talks of possible

ASI if that's even a thing and we have no idea what that even means. Technically, unless you do, I would love to hear know but what do you what do you see as the impact on society overall? Let's talk about the definitions of the two. You know AGI refers to an AI system with human level intelligence and AICI it's where it surpasses human intelligence in all areas. So let's just talk about those two and just drill down a little more. I think with AGI, we are getting closer. There's no doubt about it. We've released a reasoning model recently that allows you to actually observe through

an audit trail how the LLM thinks, which is kind of scary sometimes when you look at it and look at the answers it's producing. I wouldn't say we are there yet, we are getting closer. ASI, we're not too far away from ASI because once quantum computers go live and become more affordable and adaptable, we will get there. Because at the end of the day, it only comes down to one little thing. It's how much data you train it with and how it actually produces the outputs.

With the reasoning models, it's quite interesting. We went from what we call our legacy LLMs into deep reasoning. You may have heard that from DeepSeq. It tanked the Nvidia stock recently. You use less GPUs, less power, and better reasoning capabilities. And there was nothing new in the algorithms there. They were just existing algorithms

and they were just reordered to give you a better outcome. But we can clearly see that we are getting closer to human reasoning and sooner or later it'll start making decisions for you as well. Now the biggest question I get asked is what's the impact? I'm sure you're going to ask me that. What's going to happen to the human race? But I'm happy to answer that now. Are we going to have to, since there might not be much, you know, many jobs left, are we all going to be on universal basic income or what?

Yeah, what's the future look like here? Are we, by the way, for me, we're already at AGI because LLMs are already way smarter than I am. So in my world, I am already less smart than AI, but please, I would love to hear your opinion. Look, these AI systems are really good at prediction. LLMs are just predicting the next word or predicting the next sentence or predicting the basic reasoning.

Now I've said this at a Google conference, I think it was around 2018 and 2019, okay? Human predictions are weak. The AI is going to do better. They're going to produce better predictions and better outcomes. But I do not think the AI is going to replace human judgment. What it will do is make us produce or judge better outcomes. Okay.

It's going to make us smarter, quicker, faster in our thought processes and make us more wealthier. So that's what it's gonna do. It'll choose better stocks, it'll allow us to decide, it'll run our lives and make us, you know, give us the free time at all those menial tasks we have done before. Okay, I really don't want to talk to a machine in the future. I want to have a cup of tea with my friends and have normal human conversations. But all those menial tasks will be gone

and AI will come and help us to lead, so that we can lead better lives. I mean, hey, we're happier. We're spending more time with other humans and our friends and family, and we're richer. I mean, that sounds like paradise. This is like the perfect storm, and I can't wait. I can't wait for this to happen.

But is there any concerns about AI around the world? Or if you don't have any concerns, maybe can you share anything from the research you've done in terms of is there something that people don't know but probably should? Well there's a lot going on in AI. You know the scientists around the world are just gonna make it smarter. I will tell you this though, the deep reasoning is going to get smarter and smarter and smarter. It's because of the way we're reordering the algorithms and the amount of volumes of data we have. Okay. So we can ask other LLMs questions and use it to train our private LLMs without sharing info. You know, We can do some amazing things these days in the labs with these LLMs.

So we are going to get smarter at what we do. I do get afraid sometimes is autonomous weaponry, but that's a whole different ball game that I'm not even going to go into given that I worked in these industries before. You know, that is my biggest fear. But overall for just better health and human life, I think AI can actually help quite tremendously. It can, you know, why do we need to go to the doctor? Maybe once a year, twice a year when we get sick, why can't we track and trace our heart rate, etc. using AI and it could recommend things, improve our diet, improve our lifestyle.

I think that is important. Understand our heart rate, our anxiety levels, and help us through that process. I think AI can be useful good, and it'll improve our lives quite tremendously. Yeah, we just had a guest on who is building AI to help therapists because there's this mental health crisis and there's not enough therapists, and that got me excited. I was like, you know what?

I love the health angles and that and how like you said We can why who knows how many times we can catch something before? Because we're not always very preventative when it comes to health care and in many countries Preventative health care doesn't even exist at all It's very reactive and if they get sick wipes out their entire wealth of their family for generations. So what if we can solve these things and the cost gets lower and lower. So Gavin you have got me I am gonna change I'm like more optimistic now than pessimistic which was the opposite before we started talking. So I appreciate you today really diving in and explaining these things because I've

been wondering all about this private LLM, how this is working, data, biases, hallucinations, everything there. If you want to get in touch with you, they want to find out more about Brew AI. I know a lot of people that need this. So how can they do so? Yeah. So our website is BrewAI.com. My name is Gavin White.com. My name Gavin White.

You'll find me on LinkedIn, you know, quite easily because everyone finds me on LinkedIn and happy to share my email. It's Gavin.white at Brew AI.com. So happy to share my details as well. Yeah. So Gavin, I would love to dive in with you more about the products that a Brew AI is creating or building or how companies are using it specifically. Yes, Daniel.

Thank you for asking. We focus on multiple areas. One of them is in government. But the more exciting areas we are focusing in is in law and finance. In finance, it's quite interesting. We have Merchant Bank using it to analyze financial reports by just uploading PDFs. And the very exciting part of this is we're currently building... I love learning a few words before traveling. It's opened up doors to new friends and unforgettable experiences all thanks to Rosetta Stone. This isn't just any language tool.

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Now this is exciting because you're data kits, but you're safe and you can actually talk to your accounting system or type questions in to say, give me an instant cashflow, give me a predictive cashflow. Could you do my tax return for me? So that's very exciting. And we are about to release that very shortly for millions of businesses in the United States. I'm really excited about that.

I think LLMs and deep reasoning can help small medium businesses to really grow their business quite significantly and not worry about all the main yield task of returns or understanding the cash flow etc. I'm curious this is amazing it seems like you could solve a million problems I mean I could I could just I could tell you 100 new products and services that Brew AI could additionally solve just because there are so many that need to get better like you said you can do so much with this how do you hone in because I can if it was me I have ADHD I would just be going crazy like I would have like a thousand things which would be

obviously it's like impossible to do but how do you really hone in just because there's it sounds like to me Brew AI could solve and create better products and services for so many industries in so many ways. Now Daniel I have that question asked quite regularly you know and it's great that we can do these things but you know as a business and business, we really need to focus on specific industries. While we grow those industries, then while we grow the company revenue, we will then tackle other types of industries. We are already in law, we are already in merchant banking scenarios. We are working with small and medium businesses and accounting practices to optimize that

entire process. Absolutely, we can do it for marketing. We can do it for literally every industry. I think when we first started the company in the first year, we did have a triumphant many things and very quickly realized we can't tackle them all. So we had to do a bit of focusing and given my background coming from Deloitte from audit in consulting, et cetera, I decided to take the more the areas that we would more familiar with. And then from there, obviously, we'll hire individuals to grow into various other industries as well. I can't wait to try this new accounting software. It's almost like having my own accountant in 24-7. How do you feel about a lot of people are talking about AI agents or agent AI, they're

talking about both or this seems to be the thing. Everyone's talking about AI agents. I don't know if everyone fully understands how this will impact us, but how do you see the future of AI agents? So I think, you know, as we grow, you might, AI agents will be overlaid into these reasoning models or into these LLMs, and we'll play very specific role. I'll give you an example in accounting. So you might have an AI agent that's a senior auditor. You might have an AI agent that's a junior auditor. So the AI agents are going to talk to each other and start to audit the agents.

So the agents can be audited by other agents. And this is quite exciting because you can train each agent to look at it in a specific manner. And this is how exciting it becomes. So the question then becomes, how do we pay these agents? How do they work in the firm? Do we have these human and agents working together? We call them human in the loop. You may want to have an agent that analyzes it

and a human that analyzes it. It might go to a senior human or a senior agent to do the final check. So it's going to be very exciting because we are ingesting these agents to help. It's basically to help humans better do their job or improve their output in the workforce as well. So it could be looking at banking fraud for that matter, or look at unusual transactions that goes through your business where the AI agents can immediately alert the human in the process.

And it could look at your transactions 24-7. So there's a whole range of ideas that comes out of these agents. It's very exciting with AI agents being implemented in the workforce today. I mean, I need to use this accounting software. So I'm excited when this comes out. I need my own senior AI agent, accountant. That sounds amazing. How are you seeing AI now crossing over into humanoids or

machines mixed with AI? I know there was, you know, talks a few months ago that everyone will have, I know there was talks a few months ago that everyone will have their own machine or humanoid robot that can do whatever tasks you need around the home. Look, it's still early days. Yes, it will work really well. We've seen good examples of it. I haven't specifically focused on robotics, but given robotics and with the emergence of AI, we'll find manufacturing will become easier, goods will become cheaper, better quality outputs as well.

That will play a very important part in the home. It will help with cleaning and cooking and all the tasks you don't like or don't want to do. So it's gonna be very exciting. And it's definitely gonna help humans to a degree we will become so reliant on these AIs to help improve our lifestyle. But this has been great. You just realized your business needed to hire someone yesterday.

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of this show will get a $100 sponsored job credit to get your job's more visibility Just go to Indeed.com slash podkatzca right now and support our show by saying you heard about Indeed on this podcast. Terms and conditions apply. Hiring Indeed is all you need. You just realized your business needed to hire someone yesterday. How can you find amazing candidates fast? Easy, just use Indeed. Stop struggling to get your job post seen on other job sites.

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