Daniel Bertram
China is quite well known for economic espionage and gathering information from inside companies. They have big state-sponsored hacking departments, but their job is to acquire that kind of information. So, I think it's a fantastic thing if that's your goal, it's a fantastic thing for them to have an app that people love and they're just willingly handing over their data.

Daniel Bertram
Like that's an awesome thing. You don't have to hack into people's stuff and run all the risks that has if people are just coming to you, right?

Georgie
Hello everyone. Welcome to another episode of In the Blink of AI. A particularly interesting episode today, I will say it's all about DeepSeek. This knowledge just came out 24 hours ago and it's really impacted both the private and public markets in such an exceptional way.

Georgie
The memes are out of control. My Instagram has completely exploded. We're very lucky today because we've got Daniel Bergstrom, the CEO and co-founder of GigaBuddy on the show. They're an AI startup that's backed by Australia's biggest VC fund, Blackbird. They were also recently in the Google AI accelerator, a very competitive accelerator for seed and series A startups.

Georgie
They were one of eight startups to go through that. Essentially, we were able to have someone with such a deep technical background unpack the news headlines about DeepSeek. Why do the U.S. ban AI chips from being exported into China? How were they able to, as a tiny Chinese company, build a model comparable with OpenAI's O1 model with a fraction of the cost?

Georgie
What is reasoning? Why does it matter? What are the privacy and security implications? And so much more. I do feel like I understand everything that's going on now. And I really hope you find this episode incredibly helpful like I did. Thank you for listening. Hey, Dan, thank you so much for joining In the Blink of AI.

Georgie
I have been pestering you to come on the show for some time now. Tell me, first of all, before we dive in, what'd you get up to over the weekend? We had an Australia Day public holiday.

Daniel Bertram
Hey Georgie. Uh, yeah, the weekend. So, I mean, it's been half a day now of work and we've gotten all about it.

Georgie
It's a long distant memory.

Daniel Bertram
I actually had quite a lovely day yesterday. It was 41 in Melbourne, so I was slightly terrified, but I went to a friend's house and he's got a nice swimming pool and I hung out with his lovely family. We had a nice lunch. I smoked some pulled pork and we cooked a nice steak the day before because we weren't allowed to barbecue.

Georgie
I did not know where you were going with the smoking. I was like, wow, we have, we have gotten into spicy territory straight up, which is what I want from my guests. But you were really over-delivering there for a second, but we, we turned it back. It's back to PG. Yeah, it's 37. I was telling you before we pressed record, it is sweltering here.

Georgie
So for those watching on YouTube, I do apologise if you just start to see me dripping halfway through the episode. Look, we have some exciting breaking news to discuss. We had a full episode planned about Stargate, about executive orders that have been overturned. And then, poor you, Dan, at like 6 a.m. this morning, I'm like, we're not talking about any of that anymore. We've got something more exciting. How did you feel when I did that to you?

Daniel Bertram
I felt, I felt fine. Perfectly okay. Just like a regular day in startups.

Georgie
That's true. That's true. Everything changes.

Georgie
That's true. You're quite accustomed to moving goalposts.

Georgie
Let's dive in. I'll stop talking around it. You had a great weekend, I had a great weekend, but I'll tell you who did not have a great weekend and that's Nvidia. Their stock dropped nearly 17 percent on Monday, 589 billion of market cap they lost. What happened, Dan? What happened to Nvidia over the weekend?

Daniel Bertram
I know it's wild. It's a lot of money, isn't it?

Georgie
Yeah.

Daniel Bertram
I don't quite understand exactly what happened, but it seems to be in reaction to DeepSeek releasing their new models. So they released two new models, DeepSeek v3 and R1, which is their reasoning model, which is comparable to OpenAI's reasoning model.

Daniel Bertram
And they claim to have done it in a way that's a lot more efficient. So they claim it cost them 5.6 million to train or something. Yeah. Which is a fraction of the cost of what OpenAI spent training their models.

Georgie
Yeah. And this is what investors are obsessed about, right? Like the market cap of Nvidia dropping, um, how we all thought it, well, it does cost so much to train and build these models, billions of dollars.

Georgie
And then, uh, yeah, cheap GPT four apparently cost a hundred million to train and DeepSeek, as you said, 5.6 million. And then it's kind of like blown our minds, right. About what it means to build an amazing model. Um, maybe you could tell us a little bit, like, what you think happened? Like, how could they do such a thing?

Georgie
You don't have, you know, behind the curtain access to DeepSeek's income statement, I'm sure, but any thoughts?

Daniel Bertram
Yeah. I mean, it's hard to know exactly what happened, but I'm sure like they seem like smart people and that they've found some efficiencies that have allowed them to get a lot more done with a lot less resources.

Daniel Bertram
And, you know, sometimes that's how big innovations happen. It's not just piling more money and resources at something it's, you know, working smarter, not harder.

Georgie
Hmm. Something I'm sure you're familiar with. But for those of us sitting at home, right, uh, you got me to do this exercise earlier. You can go onto DeepSeek's website.

Georgie
Remind me the domain for people listening at home. I think

Daniel Bertram
it's deepseek.com. If it's not, if you type DeepSeek into Google, you'll probably find it. Yeah. The,

Georgie
the interface looks very similar, right? The context window looks very similar, but tell us. You know, tell everyone the experience that I got with the reasoning part of that model and why that's so special about this, this new DeepSeek R1 model.

Georgie
Like what, what's reasoning Dan?

Daniel Bertram
Yeah. So I've been obsessed with reasoning for a long time and you know, it was interesting to see OpenAI with their reasoning model, but really it's, you know, as simple as the model thinks before it speaks like a person does. It's got an internal reasoning monologue that leads to better outcomes because instead of just predicting the first thing that comes to mind or, you know, the way models work to predict tokens.

Daniel Bertram
So instead of predicting the first tokens that come to mind, it actually First prompts itself like, Oh, what, what did they mean by that? You know, and then once I think through the first thing, it's like, well, what might that mean? You know, is there any other edge cases I should consider? Like what, you know, have I covered all the bases?

Daniel Bertram
So it's got like this internal monologue that leads to a better outcome in the end because it's actually, you know, kind of covered more thinking space like a human would.

Georgie
Yeah, I found it equally like incredible from, you know, I've never seen behind the scenes what a model's doing when it's doing that thinking it's like a narrator's there going, Dan has asked me a question about medieval films and I'm going to try my best to give him a great answer based on what I know about gross box office, whatever.

Georgie
You never really see that behind the scenes narration, right? In the other models.

Daniel Bertram
Yeah, I guess also that people haven't been doing that before, at least not in the model, you know, OpenAI's O1 model does something similar, but it just says thinking, and it doesn't actually show you it's thinking. But there's been times where the thinking has been leaked and people posted it, you know, on the internet.

Daniel Bertram
And it's very similar to what R1's doing in terms of, it's just an internal monologue. And there's an instruction in its system prompt that says never disclose this internal thinking.

Georgie
And why is that? Like, you know why this isn't, but I'm going to be completely frank. If it exists already and all the models are doing it already, why can't me as a user see the thinking process written out loud?

Georgie
I don't, yeah. What's so special about it?

Daniel Bertram
Yeah, I think with OpenAI. It's like really quite close. They are. That's the joke, but you know that they felt like that's part of their competitive advantage is having this reasoning technique that they don't want other people to see, but inevitably if it's happening in the model context window, cause everything's in the same context window, sometimes as the window gets larger, it can't pay attention to everything and inevitably forgets the instruction that says, don't communicate this.

Daniel Bertram
And that's where the instructions get leaked. Cause Other things end up competing with that for relevance.

Georgie
Yeah, totally. I mean, this is perfect for you to tell me a little bit more about open models versus closed models. Now, this is a listeners of the show have probably heard us talk about open and closed models before, but why does it matter?

Georgie
Why do we care? What are they like? Why is an open-source model so special? And why did I, for a very brief moment in history, like Mark Zuckerberg, do you think?

Daniel Bertram
Yeah, well, I think it's. I mean, I think it's amazing what Meta have contributed with the LLAMA models. Like that was pushing, you know, what was available to everyone with open source.

Daniel Bertram
For free. For free. Yeah. Yeah. I mean, I think that it, it is a great thing because it kind of levels the playing field. Everyone has access to the same level of intelligence. And not only that, they can see kind of behind the curtain a bit, like how it's operating. Which means that there's no mystery. It's, you know, it's, you put it on some hardware that you control and it's going to, like, while it still behaves in a probabilistic way, you at least know nothing externally is affecting what it's generating.

Daniel Bertram
So you can have more confidence over the results you'll get. And that's been something that's been super challenging working particularly with OpenAI is they. have a tendency to, you know, try and optimize things in the model. Maybe they're adding caching layers. Maybe they're experimenting with new model optimizations.

Daniel Bertram
And while you think you're using the same model, what we've seen is the results are vastly different from day to day. And, you know, that's very difficult as someone that's building. On a system where you want, it's already unpredictable, but to add even more layers of unpredictability is very frustrating.

Daniel Bertram
So open models are fantastic. And yeah, uh, DeepSeek making their models open source has really like leveled the playing field for, for a lot of people.

Georgie
I would love to see, um, the reaction from Sam Altman, you know, founder of OpenAI with his closed model, very expensive latest models. What are they charging per month for their best models?

Georgie
It was something insane, right?

Daniel Bertram
Oh yeah. It was 2, 000. A month? Yeah. Yeah.

Georgie
Something crazy like that. I mean, this is not a fair question, but you're a founder of an AI company. Like what should Sam Altman do? Like, how can he justify that cost now that it seems impossible, right?

Daniel Bertram
Yeah. I mean, I guess what's the competitive advantage that they have.

Daniel Bertram
I mean, I think OpenAI has done a lot of things. To appeal to like a broad consumer audience, you know, with the voice stuff's fantastic. And, you know, the user experience is generally very good, but if people are just looking for raw intelligence. They're just going to use whatever is the most intelligent, you know, they're going to not worry so much about how they interface with it as long as it's accessible for their use case.

Daniel Bertram
And so, yeah, I think that being able to charge a premium and possibly the premium is justified, like I'm not, it's not necessarily a money-making exercise. to charge that amount, but, um, you know, their costs are very high. So if DeepSeek's costs are also much lower, I mean, that gives them a lot more margin to work with.

Daniel Bertram
So yeah, super hard to compete on the model front, but, you know, I always thought competing on models is kind of a, like a losing game because someone's always gonna.

Georgie
Yeah, very, very great take, and we'll get into kind of the big hyperscalers and that kind of stuff later into the show, I would love to get your take on another key player in all of this, which is NVIDIA.

Georgie
Now maybe for the listeners, we haven't really talked about NVIDIA before on the show. Can you give a quick, quick synopsis on what are NVIDIA and what are they best known for in the industry? Great.

Daniel Bertram
Well, for the longest time, I've known NVIDIA for making graphics cards, and if you wanted to play, play games Yeah, like it's What's your

Georgie
favourite game, Dan?

Georgie
I'd love to know.

Daniel Bertram
What's my favourite game? Probably one that doesn't need an NVIDIA graphics card, I think. I really love Slay The Spire. It's a roguelike deck-building game that works on your phone as well. It's on everything. But yeah, no graphics card required.

Georgie
Amazing. If I was into gaming, it would be something with a medieval lance for sure.

Georgie
What a nerd. Sorry, continue in video. They're known for graphics cards and more recently,

Daniel Bertram
more recently, well, more recently, I mean, it's still actually graphics cards. It's, but it's, you know, chips. And memory on a card that can be used for AI inference, which, you know, is very similar to the kind of maths that was done to compute graphics.

Daniel Bertram
So, and we've seen it in the past with NVIDIA, you know, with like the Bitcoin or crypto rush, you know, people were buying up graphics cards to mine crypto. And then over time we saw like more optimized purpose-built miners being developed, which now NVIDIA's delivering more purpose-built. You know, AI chipsets, but ultimately, like you need lots of cores and lots of really fast available memory, which is like the graphics memory on the chipset, which means that the whole model can be hosted in memory and Then you can do things in a blazing fast way.

Georgie
Yeah. I, I'm a very visual person. I needed to see what a chip looks like. Cause I kept hearing about AI chips. I am not a gamer and I started to feel very, very out of my depth. They're bigger than I thought they'd be. I thought it was like a little tiny USB type of situation. Can you tell the listener what we're looking at?

Georgie
If, if you were to visualize it for everyone.

Daniel Bertram
I'm not sure entirely how, how big the current chipsets are, but the chip might actually be. Quite small. Okay. The stuff that makes it big is the stuff to keep it cool, like it's the additional, because it's, you know, using a lot of power and it's very challenging to, like heat is the biggest problem.

Daniel Bertram
Like how do you disperse enough heat so that you can keep pumping energy through it? And so yeah, like heat sinks and fans and like, that all makes things larger.

Georgie
Yes. So when I see Jensen Huang, who's the CEO of Nvidia holding up this. I'm holding up my hands like I'm holding, I don't know, bigger than an A4 pad.

Georgie
Is that the chip? Is that the chip plus all the other accessories to the chip? Or are we getting into deep water here?

Daniel Bertram
Well, I think, I mean, it depends which time he was holding something up. But I mean, recently he held something up that was like a whole kind of computer in a box. And he was like, this is our new computer that does AI.

Daniel Bertram
And that was You know, the chip and the cooling and other parts like a processor and stuff so it could actually run the whole unit and so they've made these like smaller units, but they're obviously finding efficiencies in how much they're able to do on a small chip with like low energy.

Georgie
Yeah. That's really genuinely something that I want to dive into a bit more.

Georgie
Data centres, cooling towers, servers, where does it all fit in together? It's all a lot, but that's not really what I care about for today. What I care about is how DeepSeek, one, managed to build the model they had on old NVIDIA A100 chips. Why were they using old chips, Dan? Why not? Why weren't they using new chips?

Georgie
Shouldn't everyone use new NVIDIA chips?

Daniel Bertram
Yeah, well, I guess they should if they want it to be as efficient as possible. But from what I understand is export controls to China. So they weren't able to acquire the newer, like H100 chips, because also it's very competitive, like everyone wants them. So, you know, if you're trying to get them.

Daniel Bertram
In a large quantity and you don't have the proper channels like it's going to be even more difficult. So, you know, they bought the lower demand hardware and I guess that constraint led to them having to find efficiencies that made it work well on a less powerful chip. And, you know, ultimately, sometimes, you know, your constraints are what leads to innovation.

Daniel Bertram
And I think that seems to have happened in this case.

Georgie
You know, hearing this tiny company from China, they've got a cute little whale logo as their DeepSeek, you know, um, platform when you log in, they're the underdog, we're Australians, Dan. Are we on team DeepSeek? Do we, do we love what they're doing? Are we, are we, you know, Screw the crypto and tech bros of America.

Georgie
We're all in on DeepSeek now.

Daniel Bertram
Yeah. Well, I don't know about that, but I think that, I mean, good on them for releasing an open-source model. I think that that does a lot to build trust, but you know, I, I wouldn't be necessarily adopting. DeepSeek for all of my things at the moment, like for one, if you want to host the model yourself, you need some serious hardware, which is like very expensive to run.

Daniel Bertram
It's also optimized for the hardware that people don't have, which makes it harder for them to run it as efficiently as they are. So that's that's interesting as a byproduct. And then, yeah, I think using their hosted solution is hosted in China, which, you know, really don't have any. Control over what they do with the data.

Georgie
And when you say the data, when I typed in, tell me my favourite medieval movies that I need to watch this week, that, that they, that's the data you're talking about, right?

Daniel Bertram
Yeah. I mean, anything that you communicate or share, you know, is now in China and, you know, that's a whole different jurisdiction, different laws and.

Daniel Bertram
You know, they're not necessarily incentivized to protect your data in the same way. And, you know, some of the, like, governmental policy, you know, requires that the government has access to companies data. So, really, like, that's just the default in China, right? I mean, same is true for America and other countries.

Daniel Bertram
Like, if the FBI wants the data, they can get the data.

Georgie
Is this why, um, things have been, like, pretty Like we, we had this TikTok ban, like, is this related to this at all? Or we've got a cat that's entered the conversation. She's really interested in TikTok. No, she loves TikTok.

Daniel Bertram
Yeah. Yeah. Well, I think the concerns over TikTok were, I mean, really, you know, what, what could the Chinese government be doing with this data?

Daniel Bertram
Like it's giving them an insight, not just. You know, from what people are recording, but also from what people are looking at, you know, it's giving you an insight into people's everyday lives and what people are up to. And, you know, at such a mass scale, it becomes concerning because, I mean, there's a number of ways to use the data.

Daniel Bertram
And historically China's, you know, my background's in security and I guess China's quite well known for economic espionage and. You know, gathering information from inside companies. I have big state-sponsored hacking departments, but their job is to acquire that kind of information. So, you know, I think it's a fantastic thing.

Daniel Bertram
If that's your goal, it's a fantastic thing for them to have an app that people love and they're just willingly handing over their data like. That's an awesome thing. You don't have to hack into people's stuff and run all the risks that that has if people were just coming to you, right?

Georgie
Yeah. I told you that I'd been watching this show alone and you know, there's people that go out and get their bow and arrow and they try and attack like, you know, wildlife, which is where I have to close my eyes, but then you can also set these snares.

Georgie
And this, this kind of like use our free open model, um, sounds like a snare. I'm giving them my data and they are just sitting idle and they're like, thank you.

Daniel Bertram
Yeah. And, and even if it's not being used now for anything like nefarious. I mean, it's an obvious thing to do. So, like, why, why wouldn't they?

Daniel Bertram
Because there's nothing stopping them. It's like, you know, you've handed it to them. It's in their jurisdiction. They can do what they want. And that, you know, I guess that's, that's their thing. So,

Georgie
yeah.

Daniel Bertram
You know, anything that you value, you know, you really should think about, well, where, where does it go? And that's always, like, what I'm thinking about when I was working as Uh, security manager is like, where does the data go?

Daniel Bertram
That's ultimately like the most important thing is then, you know, what rules apply.

Georgie
And, and for the people listening at home, you're using these models all the time. We're using meta AI on our WhatsApp. We're using chat GPT. We're using Gemini. We might be trying, you know, deep seek now, like it's, it's quite, you know, an interesting new platform to try that reasoning model.

Georgie
Right. What should we not be typing in there, Daniel?

Daniel Bertram
Yeah, well, I think anything that shouldn't be shared. So I guess like in a corporate setting, anything that's like confidential about the business, certainly. No personal information about any people because, you know, privacy laws are important. I think people are kind of starting to forget that these regulations exist because it's so convenient and so certainly no personal information, but also, you know, company secrets like even if you're debugging some technical problem, that is potential security implications because someone reading that would now know like what technology you're using.

Daniel Bertram
What you're struggling with, you know, and also potentially you as an individual, while now you're easier to target, I mean, we go talk, go on about this for ages, but yeah, you know, like really sophisticated social engineering attacks. There's like, this is a thing called like a watering hole thing where you, if you know enough about a person, you can create a very compelling website that caters exactly to what they're looking for.

Daniel Bertram
And then they just happen to come across it and, you know, then you still like more information, right? You get them to log in or ask them for what you're looking for. So, you know, just from a social engineering perspective, it's, it's extremely valuable. The more you know about your, your target, right?

Georgie
And is this what the U.

Georgie
S. government cares about? Or are they thinking even bigger picture, like a national security issue of like, American government secrets that could get leaked?

Daniel Bertram
Yeah, I mean, I think with the U. S., I mean, it's with China having access to a lot of information about individuals. I mean, yes, there's people, you know, recording on military bases and uploading it to TikTok.

Daniel Bertram
And like, that's obviously a breach and sensitive, but then there's also, you know, people working in companies. Um, you know, disclosing what their job is and also like that if they're disgruntled with their employer or the government or being able to understand like people's psyches and then target them individually, like if you are looking for someone to be a spy for you, all it takes is understanding like that they're upset and they need money, right?

Daniel Bertram
Or they've got a gambling problem and you like. Here you go. You do this for me. I'll make your problems go away or whatever, or I'll cause you problems, right? There's different ways you can get leverage over people. So, you know, having that insight to like a whole population or a large portion of a population kind of gives you a lot of power in, in the aggregate.

Georgie
Okay. So the cute little whale logo, we're going to kind of remember that it might not be as innocent as it looks, and we're gonna be really careful what we type into these LLMs, aren't we Dan?

Daniel Bertram
Yeah. But I think that's true for any LLM because, yeah. Even if the company has the best intentions and, you know, not saying DeepSeek doesn't it, they can still be a victim of an attack and be compromised or have the government or the FBI or, you know, whatever country it is.

Daniel Bertram
Request that data. So, you know, you always need to be aware of what data you're putting where.

Georgie
Yeah. A great message for today, actually. Look, you've got an AI startup yourself, GigaBuddy's, you know, VC-backed AI startup. You've got a tremendous technical background. Um, democratizing AI models. We've touched upon these open-source models.

Georgie
Does it make your life better or worse? Um, like this sounds a lot cheaper. It must, it must make your life so much better. What am I missing, Dan?

Daniel Bertram
Yeah. Well, I mean, it's interesting. Um, I guess it doesn't directly affect what we're doing, but it's, you know, it's another option and it's potentially a good option that we could leverage where, where it was.

Daniel Bertram
Um, you know, I guess what, what we're working on is we're also very interested in reasoning systems. And I think that one thing that I don't quite understand where the delineation is, is between like a model and, you know, some software or a system because. Really, these reasoning models are models with more steps, like it's kind of, is, um, is it still a model?

Daniel Bertram
Like at which point is it not a model? Is it one step or two or 10 or, you know,

Georgie
Yeah, cause when I typed in the reasoning model, the context window for those at home, it just kept going line after line, after line, after line. It was, it was a lot more. Is that what you're talking about when you go from model to reasoning and, and the difference?

Georgie
Thanks.

Daniel Bertram
Yeah, I mean, to implement something like that, it's, you know, first do this,

Georgie
until

Daniel Bertram
you're, you know, you think you know what you want to say, then stop thinking, then respond. This is like

Georgie
me after a few beers actually, but yes, continue.

Daniel Bertram
Yeah, but I mean, really that's.

Georgie
Stop talking now.

Daniel Bertram
That's like a system, right?

Daniel Bertram
It's like, you've got one step and then it goes to another step. And um, that's why I, like, I wasn't surprised that OpenAI's reasoning models performed better because that's like what I've been working with for a long time is like, you know, do, do things in many stages to get it to pay attention to the things that matter.

Daniel Bertram
And. People have been doing chain of thought and stuff for a long time and which was, you know, a technique where you told it how to think or like what steps to go through first and then it responded. And really, this is just that built into the model. But I don't know, like, is it a model? Is it a system?

Daniel Bertram
Does it matter? I think it's good that we can see what's happening now because I think that that's You know, we'll shift how people think about, about these things and also how you can get better outcomes.

Georgie
This is something that you're quite passionate about, right? Are you building something in this space, um, to try and meet that need?

Daniel Bertram
Yeah, like I'm really interested in controlling how AI thinks. And I guess in these models, there's a reasoning approach, which is go through and think about the things you could do and then kind of. Look for whether you've considered all the options and, you know, maybe think about some kind of counterpoints and right, but that's not always the best way to go about things like I think you'll find if you use the reasoning model, if you ask something really simple, it'll do a bunch of thinking, even though it's just.

Daniel Bertram
like a straight-up obvious answer. And similarly, like it can get caught in a loop of overthinking. Like I was playing with R1 and asked something somewhat complicated and it was thinking for a really long time, but all of that context it's generating with its thinking is no longer helping it get to a better outcome.

Daniel Bertram
It actually ended up doing far worse than that. The three model, which didn't

Georgie
think really, so it kind of, you know, when someone's telling a story and then they kind of forgot what the question was, it wasn't like that because it

Daniel Bertram
was something where there wasn't an obvious answer.

Georgie
Oh, wow.

Daniel Bertram
Yeah, you've exactly, that's a very good analogy.

Daniel Bertram
So yeah, kind of forgot what the question was. And it answered in the end, but sort of in a really vague way where it didn't answer the full question in any good detail at all.

Georgie
Really?

Daniel Bertram
Yeah.

Georgie
Well, I was, I was only going to say like, is it because reasoning is, you know, the next frontier for these models that we're all going to start seeing reasoning in models because, you know, it does show you like, you know, Behind the scenes, what the model's doing so that you as a user can prompt it more effectively on, no, no, no, I didn't mean that I meant this, or is it certain companies should go after this, but not all should like V3 is perfectly good, but it depends on the use case.

Daniel Bertram
Yeah, I think it heavily depends on the use case. And it's like, if you, you as a person, if you were to think about a domain, would you need to like, what would you want to consider? And I think that most people, the products that they're building and not for general use cases, necessarily they're for a specific use case.

Daniel Bertram
Now, if you've got a specific use case, There's only certain things you'd want considered, and then you'd also want them considered in the context of your business or product or use case. So building purposeful reasoning systems, I think, is key to getting to like the next step change in intelligence. And that's what I'm working on at GigaBuddy is like, how do we Make it easy for people to like embed their thought processes in a system powered by AI so that they can get to the right outcome more efficiently because, you know, if you're following your thinking for a specific use case.

Daniel Bertram
Then you're not going to get caught in this endless reasoning loop unnecessarily because you're only covering the thought processes which are, are critical. You can still handle generic cases, but you know, where there's a better solution, why not use that? Like that's how you get efficiency, like work smarter, not harder, right?

Georgie
Yeah. I couldn't agree more. And maybe, you know, seeing these reasoning models GigaBuddy's proposition is even more compelling because we can genuinely see.

Daniel Bertram
Yeah.

Georgie
Wow. I actually need the technology to help me out here a little bit, please.

Daniel Bertram
Yeah. I think that there's been a lot of just, I guess, magic, like people assumed magic.

Daniel Bertram
And, um, when I was talking about this to people, you know, like 18 months ago, people Thought I was crazy. You know, it's like seems so far like, you know, what do you mean reasoning? I think, I mean, that's back to the start of the conversation. The question about NVIDIA. I think that, you know, we're, we're really only scratching the surface of what an intelligent system is.

Daniel Bertram
And I think LLMs play part of it, but you know, LLMs are good at language and they're good at, you know, synthesizing language and understanding language. And that's, you know, an important part of how we think as humans as well. But there's a lot of decisions and reasoning that we do that's not language based.

Daniel Bertram
It might be, you know, visual or, you know, it's just, we've got a sense, right? Like we've got lots of senses going on that we process to, to reason about what to do. And I suspect that people will start building specialized models for reasoning about all different kinds of things. And really, they still need hardware to run it on.

Daniel Bertram
So, I don't think NVIDIA is like, going anywhere. I think that if we've got more efficient LLMs, awesome, but we can also build far more intelligent systems if we start stringing together more complex things instead of being like, well, this thing can answer a hard question, you maths exam or whatever.

Daniel Bertram
We've reached the pinnacle of AI. Okay, we'll Sell all the NVIDIA stock, they're obviously not going nowhere. I just really don't think that's the case. I think it's just getting started still.

Georgie
Okay. So all those Wall Street investors can like calm down. It's not all over. Well,

Daniel Bertram
I don't know who was panicking, but it seems crazy to me.

Georgie
The internet always is panicking, Dan. I saw so many memes today. It's ridiculous. Look, um, I have one more question before we get to the rapid fire. You know, we've got this, um, this DeepSeek. The new models seem to be. You know, at least making Sam Altman of OpenAI a little bit hot under the collar because they seem to be, you know, directly in competition with at least one of his models.

Georgie
But what about the hyperscales? What about Google, Amazon? Um, you know, they've got AI offerings. Should they be freaking out as well?

Daniel Bertram
Yeah, I mean, for some things, maybe if they were relying on those AI things to be the source of their income, but you know, they're so diversified, ultimately, people still need to run models somewhere and Google and Amazon own the infrastructure that's convenient and for the most part, people are going to still want to use cloud services and applications.

Daniel Bertram
You know, there's a lot of infrastructure optimizations that people don't want to have to think about. So, I mean, people still got to be using that no matter what. I mean, maybe I think people building models and trying to compete in that like frontier model space, potentially a lot of money is going down the drain there, but it doesn't mean that there's still not a lot of, you know, a lot for them to offer like Google's, um, you know, Gemini being heavily embedded into their workspace, you know, ecosystem is hugely valuable and, you know, they're not going to turn around necessarily and use DeepSeek, but, but they could, and, you know, as long as they're embedding something in there, the value is being created for their products, which is ultimately what matters, I think.

Georgie
Yeah. Fantastic example. Um, I did lie to you though. I do have another question. Well, you've sparked, you've sparked a thought. We, um, we were going to talk about Stargate, right? This, this new initiative, this new project, Oracle, OpenAI coming together. Who's the third one? Um, Oracle, OpenAI, SoftBank. Oh my gosh, how could I forget SoftBank, the WeWork heroes of our time.

Georgie
Um, and they're building, you know, 500 billion with a B guys, B, worth of data centres. So can they compete with DeepSeek now, seeing DeepSeek can do it for so much cheaper, but if they build enough data centres, what, what, what does this mean? What does this mean, Dan? Like why are they building these data centres and, and it, do they not even care what DeepSeek are doing?

Georgie
Cause their vision is. So much more into the future. I wonder if you get what I'm getting at.

Daniel Bertram
Yeah. I mean, I suspect that, you know, they're, they're want to be the first people to get some kind of super intelligence, right?

Georgie
We're on the same wavelength.

Daniel Bertram
Someone said to someone in the government, Hey, if we get super intelligence, we'll be able to solve everything and be the most dominant power in the world.

Daniel Bertram
And so.

Georgie
America's not into that, Dan. I don't know what you're talking about.

Daniel Bertram
No, and I'm sure people didn't be like, well, what if China doesn't first? And, you know, now they're like, okay, it's 500 billion and off. I don't know. Yeah. I mean, it's an interesting proposition and. I think the biggest question is like, well, what do you do with 500 billion?

Daniel Bertram
And, you know, you can, I mean, it's always been true in computing and more. So in modern computing is like, you can like back in the day when there were a lot of constraints around, you know, CPU and memory, people worked and, you know, like take a Nintendo or something, for example, like people had to make sure that it fit on the cartridge and optimize it to run on a system that was very slow.

Daniel Bertram
And people took great care to write good code and optimize algorithms and, you know. It's amazing, but those people seem to have retired and replaced by people that are like, Oh, we'll just throw more computers at it. And you know, I, I guess this deep thing thing is an example is like, wow, actually, if you just think a bit harder and clever, you can save a hell of a lot of money and also energy.

Georgie
Spoken like a true founder that has probably gone through a few funding life cycles, Dan. I love this. Look, I only have three questions to finish off. Um, you've been so generous with the spicy questions earlier that I'm not even going to really call it a rapid fire because it's just been, you know, rapid, excellent question after excellent question.

Georgie
Thanks to me a little bit, thanks to you. I didn't, you know, okay. Number one, do you think that this DeepSeek development, these models that people are aware of now, I think they were launched, you know. Some time ago, like few years ago, perhaps, but now that we're all aware of them, do you think it will accelerate adoption of AI tech now that you know, that the people like me know that they exist?

Daniel Bertram
I mean, I don't, I don't necessarily think so. I mean, I think if people were not using AI, I don't think some cheaper thing coming from China is necessarily going to be the thing that gets people jumping on board. I don't think cost was necessarily the barrier. For most people, like I think in professional environments, people have been adopting AI where they can.

Daniel Bertram
And, you know, I think the cost is well worth it if you're like, you know, subscribing to, you know, Cloud or chat GPT or whatever, because, you know, it can give you so much productivity in almost every role. But yeah, I don't think that this is as big a deal as people make it out to be. I think it's interesting though, in that before, if you.

Daniel Bertram
We're making like, you know, one API call to, to, to get a response now that it's so much cheaper, you might want to make three or five or 10 and actually, you know, take your pick of results. And like, that's a cool thing to do. If that's still cost effective, because then ultimately you're going to end up with better results that way.

Daniel Bertram
So I, you know, I think it's, it's great that it's more efficient. Um, but I doubt anyone new is going to jump on.

Georgie
Yeah, totally. You're using it already. Um, and now you've just got another tool in your arsenal, right? What about regulations? Do you think that this, this, you know, incredible. Competitor from China will change the way that we do things here in Australia, in America.

Georgie
What, what do you reckon?

Daniel Bertram
I guess we'll see what happens with TikTok, but, uh, but I think that if DeepSeek gained any traction with the US population, the, you know, the government would be equally if not more concerned because the information is likely to be even more sensitive that's being shared, even if there's less.

Daniel Bertram
So I could see, I mean, there's already, you know, regulation, export controls on chips, but I can see like ramping up, you know, not sharing data because that is potentially weakening the advantage US companies have.

Georgie
And, um, something that, you know, I've been joking a lot on the, on the show today, but there are ethical considerations perhaps, um, that, you know, we, we might need to consider.

Georgie
Is there anything that, you know, that concerns you when it comes to ethics of these new models, especially like the DeepSeats coming from China?

Daniel Bertram
Yeah. I mean, I think AI ethics. Generally is something that I'm concerned about. I think China, you know, probably isn't motivated by personal data protection, particularly of foreigners necessarily, but, you know, at the same time, I think that the U.

Daniel Bertram
S. Roll back safety regulations for AI. And I think just Generally, adoption of AI in an unsafe way is like quite scary because, you know, it all comes down to risk. It's like what decisions or what is the AI informing that people are relying on? And the more important that becomes. Kind of the scarier it is if you're not thinking about what is it making those decisions on and like what could go wrong.

Georgie
And we're getting more and more reliant on the models. I feel like I, it's almost like I can't put the toothpaste back in the tube. I can't imagine not having my work proof right now. I can't imagine going on a holiday without asking a model where I should go. It's going to send me somewhere weird.

Daniel Bertram
I mean, for that kind of, you know, for low risk stuff, I think, I think it's great.

Daniel Bertram
Like I, I use AI a lot. So, you know, this helped me think, cause my brain doesn't work most of the time, but, you know, like it just, it helps to offload certain types of information, but you know, when it's something really critical or like. You know, it's code that's going into, you know, your product and your product does sensitive things like it's kind of critical that someone understands still what that's doing.

Daniel Bertram
And I guess, you know, people, well, Mark Zuckerberg saying, well, that you're not hiring engineers that, you know, I was going to be doing the job of mid-level engineers. And I think that. Sure, but that's still like a scary, that's kind of a scary proposition where the senior engineers like can no longer check the volume of code that's being produced.

Daniel Bertram
Um, and then, you know, things creep into the products that, and people's kind of stop understanding what it's doing. Um, you know, I think it opens us up to like a whole, a whole bunch of new risks where, you know, we just don't know what could go wrong. I guess you hope your AI security team picks up on the problems before someone else does.

Georgie
If only I knew someone in AI security, Dan.

Daniel Bertram
Before someone else's AI hacking team, right? It's going to be, it's just the same arms race with AI.

Georgie
Yeah, beautifully articulated. This has been one of my favourite episodes. I genuinely learned so much. It's 37 degrees and I'm. Like my brain's overcooking from all this amazing information, um, and I'm loving it.

Georgie
I'm so grateful. Um, thank you for joining the show, but I'm not going to let you leave because I would like to give you an opportunity. You've been so generous, you know, sharing everything with us. What would you like to share about what you're building to the listeners?

Daniel Bertram
Yeah, so I'm glad you didn't pass out Georgie.

Georgie
I did, I did warn you. I know you

Daniel Bertram
sacrificed by not having a fan due to the way it would affect the audio. But um, we appreciate your sacrifice. Well, we're building a platform to enable people to control how AI thinks. So, you know, building and iterating on complex reasoning processes. And I guess at the stage we're at, we're just working with our first customers and use cases.

Daniel Bertram
And I'm really interested in hearing from people that have interesting use cases where reasoning is a core part of it. You know, we'd love to take on a few more foundation customers and, you know, work with them and solving interesting problems. So if you think you've got an interesting problem that you're solving with AI, like Yeah.

Daniel Bertram
Reach out. We'd love to get involved. And similarly, if you're, if you're an investor that's interested in the AI reasoning space, like also feel free to reach out

Georgie
your current investors are going to be so mad. You're kind of holding the tails of quite a few exciting releases, but being very modest. Um, we will put all the details to your LinkedIn and the website and stuff like that in the show notes.

Georgie
Thank you so much, Dan, for joining In the Blink of AI. So grateful for you jumping on board in this groundbreaking breaking news about DeepSeek and AI. It's moving so quickly. So thank you. Exciting times.

Daniel Bertram
Thanks for having me, Georgie. It's been fun.

Georgie
Bye.

Georgie
Thank you for listening to In the Blink of AI. You can check out the show notes for anything discussed in this week's episode, and we will be back next week. This podcast was produced by Day One. With music by Dan Hanson and visual artwork by Sophie Tyrell. If you loved the episode, please tell your mates.

Georgie
And I love AI News. Please share your thoughts and suggestions to GeorginaRoseHealy@gmail.com.