January #2 - DeepSeek's Seismic Shift | Artefact's GenAI News

Description

Welcome to The GenAI Chronicles, the ultimate podcast for anyone captivated by the cutting edge of GenAI.

This week, we deliver the week’s most fascinating AI stories : DeepSeek's breakthrough

🎧 For Our Listeners:If you’re an AI enthusiast, industry professional, or simply curious about how AI is transforming our lives, this podcast is for you.

🌟 What Makes Us Special:

This podcast is automatically generated by Generative AI. Each episode, we explore how GenAI is reshaping industries, enhancing creativity, and tackling real-world challenges. We deliver our “Thoughts of the Week”, giving you advanced views on trends and the future of Generative AI for business.

Presentation by NotebookLM

Hosted on Ausha. See ausha.co/privacy-policy for more information.

Transcription

Speaker #0
Welcome to the Gen AI Chronicles, your podcast for all the latest in generative AI. It really does feel like every week there's something new.
Speaker #1
It's incredible how fast things are moving.
Speaker #0
Just look at this past week, please. An AI chip startup is getting ready to go public.
Speaker #1
Oh, yeah.
Speaker #0
We had former President Trump come out swinging and announce Stargate, his huge AI infrastructure investment.
Speaker #1
Right. And then...
Speaker #0
Of course, Mistral AI just launched their crazy fast... Small three model.
Speaker #1
And even Google and the Associated Press are teaming up for real-time AI news.
Speaker #0
I know it's hard to keep up with it all, but there is one thing that has everyone talking. Deep Seek R1.
Speaker #1
Yeah, it's a big one.
Speaker #0
And that's what we're diving deep into today.
Speaker #1
Should be interesting.
Speaker #0
So for anyone listening who might not be familiar with it, Deep Seek R1 is this new AI model developed over in China. Yeah. And it's gotten a lot of attention because it's basically doing what GPT-4o does. Right. But for way cheaper.
Speaker #1
That's the big thing. that has everyone so excited. DeepSeq R1 was reportedly trained for something like six million dollars per cycle. Wow. To give you an idea that's less than a tenth of the cost of training some similar models.
Speaker #0
Less than a tenth. Yeah. That's insane. And they pulled this off by using what's called a mixture of experts architecture or an MOWI architecture.
Speaker #1
Exactly.
Speaker #0
So what exactly does that mean?
Speaker #1
Well, a MOE architecture is basically a way to build a neural network. But with all these different specialized... parts, kind of like having a bunch of experts each for a different task. This approach lets you make the model bigger and more powerful without the computational costs getting out of control.
Speaker #0
So it's not just about throwing more computing power at it.
Speaker #1
No, no. It's about being smarter about how you design the model itself. Gotcha. DeepSeek also used something called cold start fine tuning.
Speaker #0
Oh yeah. I read about that.
Speaker #1
It's actually one of the key reasons they're so efficient.
Speaker #0
Cold start fine tuning though. I'm not really sure what that is.
Speaker #1
Sure. So basically... Instead of fine tuning this whole massive model for every new task, they just train smaller, more specialized modules that are better for specific tasks.
Speaker #0
Oh, so it's kind of like having a toolbox.
Speaker #1
Exactly.
Speaker #0
With specialized tools for each job.
Speaker #1
That's a great way to think about it.
Speaker #0
Instead of just one giant tool that's supposed to do everything. Yep. So they're getting more out of their training. Right. By focusing on those specific areas. Exactly. Not trying to make the model good at everything.
Speaker #1
Right. And you can really see it in the performance. Yeah. DeepSeek R1 is doing amazing things, especially when it comes to things that need logic, like math problems.
Speaker #0
I think I read it got 97.3% accuracy on some standardized math benchmark. Yes. That's not just good. That's better than some of the big models out there.
Speaker #1
Yeah, it beat GPT-4o even.
Speaker #0
It did, yeah.
Speaker #1
So you can really see the potential.
Speaker #0
Absolutely. And it's not just the training that's cheaper, it's the inference costs too.
Speaker #1
Oh yeah, that's huge. The cost of actually using the model in real world stuff has been cut by like 30 times compared to its competitors. 30 times. Yeah. That's huge, especially for businesses who want to use these tools.
Speaker #0
Absolutely. That kind of price drop opens up a whole new world of possibilities, things that were just too expensive before suddenly become realistic. Right. And we're already seeing the shockwaves from all of this.
Speaker #1
Oh, for sure. Just look at NVIDIA. Their stock price tanked after DeepSeek's announcement. I know. They lost over $112 billion in market value in just a few days.
Speaker #0
Wow. It really shows you how disruptive this is.
Speaker #1
Like the whole power dynamic in the AI market is being challenged.
Speaker #0
For sure.
Speaker #1
It's not just about technology. It's about who controls the market. Right. Meanwhile, the Hang Seng Technology Index over in Hong Kong.
Speaker #0
Where DeepSeek is based. Yeah,
Speaker #1
that one shut up. Of course. It's like the market is saying that China is the new hub for AI innovation.
Speaker #0
It's looking that way.
Speaker #1
And people have definitely taken notice. Oh, yeah. The DeepSeek app is already at the top of the App Store charts.
Speaker #0
I saw that.
Speaker #1
Over a million and a half downloads in just one week.
Speaker #0
It's clear that people want access to these AI tools. They want something affordable that actually works.
Speaker #1
Absolutely.
Speaker #0
But DeepSeek's success isn't just about good architecture and efficient training. No. They also had to overcome some real obstacles.
Speaker #1
Like the embargo on the H100 GPUs from the US.
Speaker #0
Exactly. Right. They needed a workaround to get the computing power they needed. So instead of the H100s, they used H800 GPUs for their training.
Speaker #1
They were able to adapt.
Speaker #0
They didn't let that stop them.
Speaker #1
And still got incredible results.
Speaker #0
It's pretty amazing. Yeah. So DeepSeek is definitely shaking things up with their affordable and powerful model.
Speaker #1
For sure.
Speaker #0
But what does this actually mean for the future of AI?
Speaker #1
That's the big question, isn't it?
Speaker #0
Yeah. Is this a fluke or is DeepSeek showing us the new way forward for everyone?
Speaker #1
I think DeepSeek has shown that cost efficiency is the new battleground.
Speaker #0
Right. It's not just about bigger and more complex models anymore.
Speaker #1
We're moving beyond that.
Speaker #0
So performance isn't the only thing that matters.
Speaker #1
No, not anymore. Efficiency and accessibility are just as important. Companies are realizing that the real winners will be the ones who can deliver these amazing AI capabilities. Yeah. But at a price that everyone can afford.
Speaker #0
Okay, so if that's the case, what does that mean for companies like Google and OpenAI?
Speaker #1
Well, that's a good question. Are we going to see a race to the bottom in terms of price? Or will the focus shift to more specialized AI applications?
Speaker #0
It makes me wonder what's going to happen next.
Speaker #1
Yeah. The answers to those questions will really shape the future of AI as a whole.
Speaker #0
It's not just about the technology itself, though.
Speaker #1
No, not at all. Yeah. We also need to think about what these developments mean for the world.
Speaker #0
You mean like the impact on different industries and the global economy?
Speaker #1
Exactly. DeepSeek's success could speed up how quickly businesses start using AI, potentially leading to things like more automation jobs being displaced and maybe even a whole new industries we haven't even thought of yet.
Speaker #0
There's so much to consider.
Speaker #1
It's a lot to unpack.
Speaker #0
It really is. And we're just getting started. We'll dig into these bigger questions a little later.
Speaker #1
I think DeepSeek's rise could really kickstart a ton of innovation and disruption.
Speaker #0
Like a ripple effect kind of spreading out from them and changing the whole AI world.
Speaker #1
Exactly. Exactly. And some are definitely going to benefit more than others.
Speaker #0
Right. So who are the winners here?
Speaker #1
Well, think about the companies that are building AI software and agents. They're the ones who are really going to benefit from having these cheaper, faster, more efficient models.
Speaker #0
Right. It's like giving them a superpower.
Speaker #1
Exactly. They can use these new models to make their products even better, improve performance and offer better prices.
Speaker #0
So it's not just about saving money.
Speaker #1
No, it's about getting a real advantage over their competition.
Speaker #0
Makes sense. And what about the big platforms, the ones with huge distribution networks?
Speaker #1
Oh, yeah, like Google, Amazon, Microsoft even Dupseek themselves. They're in the perfect spot to take advantage of this trend.
Speaker #0
Because they can roll out these new AI tools to tons of users right away.
Speaker #1
Exactly. And they already have the infrastructure to deal with the increased demand for AI.
Speaker #0
So they're in a good position.
Speaker #1
Yeah, for sure. And then you have the companies that are providing the computing power for all of this.
Speaker #0
I bet they're pretty happy about this.
Speaker #1
Oh, yeah. The compute providers, especially those focused on inference.
Speaker #0
Right. That's the part where you actually use the trained model.
Speaker #1
Exactly. They're going to see huge demand.
Speaker #0
Like an AI gold rush.
Speaker #1
You could say that. And of course, the early adopters.
Speaker #0
The companies that have already been using AI.
Speaker #1
Yeah, they're going to get huge benefits from being able to use these super powerful models. but at a much lower cost.
Speaker #0
Like getting a free upgrade.
Speaker #1
Pretty much. And don't forget about the companies that are vertically integrated.
Speaker #0
The ones that have the expertise to both build the models and the applications on top of them.
Speaker #1
Exactly. They have the whole package.
Speaker #0
So they're in a great spot to win big. Right.
Speaker #1
Their ability to move quickly with these new, more efficient models gives them a huge advantage.
Speaker #0
They can get their AI solutions out there faster and cheaper than everyone else.
Speaker #1
Exactly.
Speaker #0
Okay, so it sounds like there are a lot of winners here. But what about the other side of the coin? Who are the losers in all of this?
Speaker #1
Well, some companies are definitely going to struggle.
Speaker #0
Like who?
Speaker #1
Think about the underperforming LLMs, the ones that are expensive to run and maintain.
Speaker #0
Right. They're going to have a tough time competing.
Speaker #1
They'll need to adapt or they'll get left behind.
Speaker #0
It's like survival of the fittest in the AI world.
Speaker #1
Yeah, that's a good way to put it. And then there are the companies that have been really focused on RLHF.
Speaker #0
Reinforcement Learning from Human Feedback.
Speaker #1
Right. They might find it hard to keep up.
Speaker #0
Can you remind me what RLHF is again?
Speaker #1
Sure. It's a way of training AI models where you use feedback from human trainers. Got it. It's been a popular approach, but it's expensive and can take a long time.
Speaker #0
So you're saying that DeepSeek's success with pure reinforcement learning could make RLHF less appealing?
Speaker #1
It's possible as pure RL gets better and cheaper. Companies might not see the need for RLHF anymore, especially since it needs so many human trainers.
Speaker #0
It's amazing how one company can shake things up so much.
Speaker #1
It really is. DeepSeek has forced the whole industry to rethink its strategies and adapt.
Speaker #0
It just shows how fast things are moving in AI.
Speaker #1
That's for sure. What's cutting edge today might be outdated tomorrow.
Speaker #0
And speaking of fast advancements, DeepSeek isn't just changing the game for language models. No, they're not. They're also making waves in image generation with their Janus Pro 7B model.
Speaker #1
Yeah, it's really impressive what they've done.
Speaker #0
I've heard it can create super realistic images.
Speaker #1
It can, even better than models like DALI 3 and Stable Diffusion.
Speaker #0
And they did it so fast.
Speaker #1
It's incredible how quickly they're innovating. And just like their language model, they've focused on making it efficient and accessible.
Speaker #0
You mean the fact that Janus can run on less powerful hardware?
Speaker #1
Exactly. It doesn't need a supercomputer to run.
Speaker #0
So more people can use it.
Speaker #1
That's the idea. And they were incredibly efficient with their development, too.
Speaker #0
But they developed it in a couple of months for under $6 million.
Speaker #1
You're right. And to put that in perspective, similar projects in the U.S. often take way longer and cost way more.
Speaker #0
It shows that you don't need tons of money to make breakthroughs.
Speaker #1
Exactly. DeepSeek is proving that.
Speaker #0
But beyond these specific examples, I think we need to talk about the bigger picture.
Speaker #1
Right. What does DeepSeek's success mean for who's going to control AI in the future?
Speaker #0
Exactly. Especially on a global scale.
Speaker #1
That's a question that has a lot of people worried, especially in the U.S.
Speaker #0
Yeah, the U.S. has always been seen as the leader in AI.
Speaker #1
Right. But DeepSeek is challenging that.
Speaker #0
It's a sign that things are changing.
Speaker #1
The world of AI is becoming more global.
Speaker #0
More countries are investing in AI.
Speaker #1
And they're catching up. And in some cases, they're even surpassing the U.S.
Speaker #0
So this isn't just about DeepSeek. It's about how the balance of power and technology is shifting.
Speaker #1
Absolutely. And it makes you wonder what's going to happen with international cooperation in AI.
Speaker #0
Yeah. Will we see more competition and rivalry?
Speaker #1
Or will countries work together to deal with the challenges and opportunities that AI brings?
Speaker #0
Those are important questions, especially with everything going on in the world right now.
Speaker #1
They are. We're already seeing concerns about AI being used for military purposes.
Speaker #0
And there are ethical questions, too.
Speaker #1
Of course, about what it means to have these powerful AI systems.
Speaker #0
These are issues that affect everyone, not just one country.
Speaker #1
Exactly. We need global solutions.
Speaker #0
The future of AI isn't something that one country can decide on its own.
Speaker #1
It's a global issue that needs a global perspective.
Speaker #0
And it's not just governments and companies that need to be part of the conversation.
Speaker #1
No, everyone needs to have a voice. Academics, ethicists, everyday people.
Speaker #0
We need to think about how AI is going to affect society.
Speaker #1
Both the good and the bad. And make sure these technologies are used to benefit everyone.
Speaker #0
It's a big challenge.
Speaker #1
It is, but it's also incredibly exciting.
Speaker #0
We're living in a time of amazing technological advancements.
Speaker #1
And AI is at the forefront of it all.
Speaker #0
The possibilities seem endless.
Speaker #1
They do. And it's up to us to make sure we use this power responsibly and ethically.
Speaker #0
It's a lot to think about, but it's also inspiring to see how companies like DeepSeek are pushing the boundaries and showing us what's possible.
Speaker #1
They're definitely a company to watch. It'll be fascinating to see what they do next.
Speaker #0
And it'll be just as interesting to see how the rest of the world responds. I feel like we could talk about this for hours.
Speaker #1
There's so much more to unpack.
Speaker #0
But we are out of time for today's deep dive.
Speaker #1
It goes by fast, doesn't it?
Speaker #0
It really does. But before we go, any final thoughts?
Speaker #1
I think the biggest thing we can learn from DeepSeek is that the AI world isn't just about the U.S. anymore. Right. Innovation is happening all over the world. Yeah. And the power dynamics are definitely shifting.
Speaker #0
It's a wake-up call for the big players and a huge opportunity for everyone else.
Speaker #1
Exactly. And I think it shows how important collaboration is. We're all facing the same challenges with AI. we can accomplish so much more if we work together.
Speaker #0
So it's not just about who has the best technology.
Speaker #1
It's about how we use that technology to solve real problems and make the world a better place.
Speaker #0
Exactly. Well, this has been an amazing conversation. Thank you so much for sharing your expertise with us today.
Speaker #1
My pleasure.
Speaker #0
We'd like to thank the GenAI team for once again automatically generating us. Thanks for listening to the GenAI Chronicles. See you in two weeks for more.

Description

Welcome to The GenAI Chronicles, the ultimate podcast for anyone captivated by the cutting edge of GenAI.

This week, we deliver the week’s most fascinating AI stories : DeepSeek's breakthrough

🎧 For Our Listeners:If you’re an AI enthusiast, industry professional, or simply curious about how AI is transforming our lives, this podcast is for you.

🌟 What Makes Us Special:

Presentation by NotebookLM

Hosted on Ausha. See ausha.co/privacy-policy for more information.

Transcription

Speaker #0
Welcome to the Gen AI Chronicles, your podcast for all the latest in generative AI. It really does feel like every week there's something new.
Speaker #1
It's incredible how fast things are moving.
Speaker #0
Just look at this past week, please. An AI chip startup is getting ready to go public.
Speaker #1
Oh, yeah.
Speaker #0
We had former President Trump come out swinging and announce Stargate, his huge AI infrastructure investment.
Speaker #1
Right. And then...
Speaker #0
Of course, Mistral AI just launched their crazy fast... Small three model.
Speaker #1
And even Google and the Associated Press are teaming up for real-time AI news.
Speaker #0
I know it's hard to keep up with it all, but there is one thing that has everyone talking. Deep Seek R1.
Speaker #1
Yeah, it's a big one.
Speaker #0
And that's what we're diving deep into today.
Speaker #1
Should be interesting.
Speaker #0
So for anyone listening who might not be familiar with it, Deep Seek R1 is this new AI model developed over in China. Yeah. And it's gotten a lot of attention because it's basically doing what GPT-4o does. Right. But for way cheaper.
Speaker #1
That's the big thing. that has everyone so excited. DeepSeq R1 was reportedly trained for something like six million dollars per cycle. Wow. To give you an idea that's less than a tenth of the cost of training some similar models.
Speaker #0
Less than a tenth. Yeah. That's insane. And they pulled this off by using what's called a mixture of experts architecture or an MOWI architecture.
Speaker #1
Exactly.
Speaker #0
So what exactly does that mean?
Speaker #1
Well, a MOE architecture is basically a way to build a neural network. But with all these different specialized... parts, kind of like having a bunch of experts each for a different task. This approach lets you make the model bigger and more powerful without the computational costs getting out of control.
Speaker #0
So it's not just about throwing more computing power at it.
Speaker #1
No, no. It's about being smarter about how you design the model itself. Gotcha. DeepSeek also used something called cold start fine tuning.
Speaker #0
Oh yeah. I read about that.
Speaker #1
It's actually one of the key reasons they're so efficient.
Speaker #0
Cold start fine tuning though. I'm not really sure what that is.
Speaker #1
Sure. So basically... Instead of fine tuning this whole massive model for every new task, they just train smaller, more specialized modules that are better for specific tasks.
Speaker #0
Oh, so it's kind of like having a toolbox.
Speaker #1
Exactly.
Speaker #0
With specialized tools for each job.
Speaker #1
That's a great way to think about it.
Speaker #0
Instead of just one giant tool that's supposed to do everything. Yep. So they're getting more out of their training. Right. By focusing on those specific areas. Exactly. Not trying to make the model good at everything.
Speaker #1
Right. And you can really see it in the performance. Yeah. DeepSeek R1 is doing amazing things, especially when it comes to things that need logic, like math problems.
Speaker #0
I think I read it got 97.3% accuracy on some standardized math benchmark. Yes. That's not just good. That's better than some of the big models out there.
Speaker #1
Yeah, it beat GPT-4o even.
Speaker #0
It did, yeah.
Speaker #1
So you can really see the potential.
Speaker #0
Absolutely. And it's not just the training that's cheaper, it's the inference costs too.
Speaker #1
Oh yeah, that's huge. The cost of actually using the model in real world stuff has been cut by like 30 times compared to its competitors. 30 times. Yeah. That's huge, especially for businesses who want to use these tools.
Speaker #0
Absolutely. That kind of price drop opens up a whole new world of possibilities, things that were just too expensive before suddenly become realistic. Right. And we're already seeing the shockwaves from all of this.
Speaker #1
Oh, for sure. Just look at NVIDIA. Their stock price tanked after DeepSeek's announcement. I know. They lost over $112 billion in market value in just a few days.
Speaker #0
Wow. It really shows you how disruptive this is.
Speaker #1
Like the whole power dynamic in the AI market is being challenged.
Speaker #0
For sure.
Speaker #1
It's not just about technology. It's about who controls the market. Right. Meanwhile, the Hang Seng Technology Index over in Hong Kong.
Speaker #0
Where DeepSeek is based. Yeah,
Speaker #1
that one shut up. Of course. It's like the market is saying that China is the new hub for AI innovation.
Speaker #0
It's looking that way.
Speaker #1
And people have definitely taken notice. Oh, yeah. The DeepSeek app is already at the top of the App Store charts.
Speaker #0
I saw that.
Speaker #1
Over a million and a half downloads in just one week.
Speaker #0
It's clear that people want access to these AI tools. They want something affordable that actually works.
Speaker #1
Absolutely.
Speaker #0
But DeepSeek's success isn't just about good architecture and efficient training. No. They also had to overcome some real obstacles.
Speaker #1
Like the embargo on the H100 GPUs from the US.
Speaker #0
Exactly. Right. They needed a workaround to get the computing power they needed. So instead of the H100s, they used H800 GPUs for their training.
Speaker #1
They were able to adapt.
Speaker #0
They didn't let that stop them.
Speaker #1
And still got incredible results.
Speaker #0
It's pretty amazing. Yeah. So DeepSeek is definitely shaking things up with their affordable and powerful model.
Speaker #1
For sure.
Speaker #0
But what does this actually mean for the future of AI?
Speaker #1
That's the big question, isn't it?
Speaker #0
Yeah. Is this a fluke or is DeepSeek showing us the new way forward for everyone?
Speaker #1
I think DeepSeek has shown that cost efficiency is the new battleground.
Speaker #0
Right. It's not just about bigger and more complex models anymore.
Speaker #1
We're moving beyond that.
Speaker #0
So performance isn't the only thing that matters.
Speaker #1
No, not anymore. Efficiency and accessibility are just as important. Companies are realizing that the real winners will be the ones who can deliver these amazing AI capabilities. Yeah. But at a price that everyone can afford.
Speaker #0
Okay, so if that's the case, what does that mean for companies like Google and OpenAI?
Speaker #1
Well, that's a good question. Are we going to see a race to the bottom in terms of price? Or will the focus shift to more specialized AI applications?
Speaker #0
It makes me wonder what's going to happen next.
Speaker #1
Yeah. The answers to those questions will really shape the future of AI as a whole.
Speaker #0
It's not just about the technology itself, though.
Speaker #1
No, not at all. Yeah. We also need to think about what these developments mean for the world.
Speaker #0
You mean like the impact on different industries and the global economy?
Speaker #1
Exactly. DeepSeek's success could speed up how quickly businesses start using AI, potentially leading to things like more automation jobs being displaced and maybe even a whole new industries we haven't even thought of yet.
Speaker #0
There's so much to consider.
Speaker #1
It's a lot to unpack.
Speaker #0
It really is. And we're just getting started. We'll dig into these bigger questions a little later.
Speaker #1
I think DeepSeek's rise could really kickstart a ton of innovation and disruption.
Speaker #0
Like a ripple effect kind of spreading out from them and changing the whole AI world.
Speaker #1
Exactly. Exactly. And some are definitely going to benefit more than others.
Speaker #0
Right. So who are the winners here?
Speaker #1
Well, think about the companies that are building AI software and agents. They're the ones who are really going to benefit from having these cheaper, faster, more efficient models.
Speaker #0
Right. It's like giving them a superpower.
Speaker #1
Exactly. They can use these new models to make their products even better, improve performance and offer better prices.
Speaker #0
So it's not just about saving money.
Speaker #1
No, it's about getting a real advantage over their competition.
Speaker #0
Makes sense. And what about the big platforms, the ones with huge distribution networks?
Speaker #1
Oh, yeah, like Google, Amazon, Microsoft even Dupseek themselves. They're in the perfect spot to take advantage of this trend.
Speaker #0
Because they can roll out these new AI tools to tons of users right away.
Speaker #1
Exactly. And they already have the infrastructure to deal with the increased demand for AI.
Speaker #0
So they're in a good position.
Speaker #1
Yeah, for sure. And then you have the companies that are providing the computing power for all of this.
Speaker #0
I bet they're pretty happy about this.
Speaker #1
Oh, yeah. The compute providers, especially those focused on inference.
Speaker #0
Right. That's the part where you actually use the trained model.
Speaker #1
Exactly. They're going to see huge demand.
Speaker #0
Like an AI gold rush.
Speaker #1
You could say that. And of course, the early adopters.
Speaker #0
The companies that have already been using AI.
Speaker #1
Yeah, they're going to get huge benefits from being able to use these super powerful models. but at a much lower cost.
Speaker #0
Like getting a free upgrade.
Speaker #1
Pretty much. And don't forget about the companies that are vertically integrated.
Speaker #0
The ones that have the expertise to both build the models and the applications on top of them.
Speaker #1
Exactly. They have the whole package.
Speaker #0
So they're in a great spot to win big. Right.
Speaker #1
Their ability to move quickly with these new, more efficient models gives them a huge advantage.
Speaker #0
They can get their AI solutions out there faster and cheaper than everyone else.
Speaker #1
Exactly.
Speaker #0
Okay, so it sounds like there are a lot of winners here. But what about the other side of the coin? Who are the losers in all of this?
Speaker #1
Well, some companies are definitely going to struggle.
Speaker #0
Like who?
Speaker #1
Think about the underperforming LLMs, the ones that are expensive to run and maintain.
Speaker #0
Right. They're going to have a tough time competing.
Speaker #1
They'll need to adapt or they'll get left behind.
Speaker #0
It's like survival of the fittest in the AI world.
Speaker #1
Yeah, that's a good way to put it. And then there are the companies that have been really focused on RLHF.
Speaker #0
Reinforcement Learning from Human Feedback.
Speaker #1
Right. They might find it hard to keep up.
Speaker #0
Can you remind me what RLHF is again?
Speaker #1
Sure. It's a way of training AI models where you use feedback from human trainers. Got it. It's been a popular approach, but it's expensive and can take a long time.
Speaker #0
So you're saying that DeepSeek's success with pure reinforcement learning could make RLHF less appealing?
Speaker #1
It's possible as pure RL gets better and cheaper. Companies might not see the need for RLHF anymore, especially since it needs so many human trainers.
Speaker #0
It's amazing how one company can shake things up so much.
Speaker #1
It really is. DeepSeek has forced the whole industry to rethink its strategies and adapt.
Speaker #0
It just shows how fast things are moving in AI.
Speaker #1
That's for sure. What's cutting edge today might be outdated tomorrow.
Speaker #0
And speaking of fast advancements, DeepSeek isn't just changing the game for language models. No, they're not. They're also making waves in image generation with their Janus Pro 7B model.
Speaker #1
Yeah, it's really impressive what they've done.
Speaker #0
I've heard it can create super realistic images.
Speaker #1
It can, even better than models like DALI 3 and Stable Diffusion.
Speaker #0
And they did it so fast.
Speaker #1
It's incredible how quickly they're innovating. And just like their language model, they've focused on making it efficient and accessible.
Speaker #0
You mean the fact that Janus can run on less powerful hardware?
Speaker #1
Exactly. It doesn't need a supercomputer to run.
Speaker #0
So more people can use it.
Speaker #1
That's the idea. And they were incredibly efficient with their development, too.
Speaker #0
But they developed it in a couple of months for under $6 million.
Speaker #1
You're right. And to put that in perspective, similar projects in the U.S. often take way longer and cost way more.
Speaker #0
It shows that you don't need tons of money to make breakthroughs.
Speaker #1
Exactly. DeepSeek is proving that.
Speaker #0
But beyond these specific examples, I think we need to talk about the bigger picture.
Speaker #1
Right. What does DeepSeek's success mean for who's going to control AI in the future?
Speaker #0
Exactly. Especially on a global scale.
Speaker #1
That's a question that has a lot of people worried, especially in the U.S.
Speaker #0
Yeah, the U.S. has always been seen as the leader in AI.
Speaker #1
Right. But DeepSeek is challenging that.
Speaker #0
It's a sign that things are changing.
Speaker #1
The world of AI is becoming more global.
Speaker #0
More countries are investing in AI.
Speaker #1
And they're catching up. And in some cases, they're even surpassing the U.S.
Speaker #0
So this isn't just about DeepSeek. It's about how the balance of power and technology is shifting.
Speaker #1
Absolutely. And it makes you wonder what's going to happen with international cooperation in AI.
Speaker #0
Yeah. Will we see more competition and rivalry?
Speaker #1
Or will countries work together to deal with the challenges and opportunities that AI brings?
Speaker #0
Those are important questions, especially with everything going on in the world right now.
Speaker #1
They are. We're already seeing concerns about AI being used for military purposes.
Speaker #0
And there are ethical questions, too.
Speaker #1
Of course, about what it means to have these powerful AI systems.
Speaker #0
These are issues that affect everyone, not just one country.
Speaker #1
Exactly. We need global solutions.
Speaker #0
The future of AI isn't something that one country can decide on its own.
Speaker #1
It's a global issue that needs a global perspective.
Speaker #0
And it's not just governments and companies that need to be part of the conversation.
Speaker #1
No, everyone needs to have a voice. Academics, ethicists, everyday people.
Speaker #0
We need to think about how AI is going to affect society.
Speaker #1
Both the good and the bad. And make sure these technologies are used to benefit everyone.
Speaker #0
It's a big challenge.
Speaker #1
It is, but it's also incredibly exciting.
Speaker #0
We're living in a time of amazing technological advancements.
Speaker #1
And AI is at the forefront of it all.
Speaker #0
The possibilities seem endless.
Speaker #1
They do. And it's up to us to make sure we use this power responsibly and ethically.
Speaker #0
It's a lot to think about, but it's also inspiring to see how companies like DeepSeek are pushing the boundaries and showing us what's possible.
Speaker #1
They're definitely a company to watch. It'll be fascinating to see what they do next.
Speaker #0
And it'll be just as interesting to see how the rest of the world responds. I feel like we could talk about this for hours.
Speaker #1
There's so much more to unpack.
Speaker #0
But we are out of time for today's deep dive.
Speaker #1
It goes by fast, doesn't it?
Speaker #0
It really does. But before we go, any final thoughts?
Speaker #1
I think the biggest thing we can learn from DeepSeek is that the AI world isn't just about the U.S. anymore. Right. Innovation is happening all over the world. Yeah. And the power dynamics are definitely shifting.
Speaker #0
It's a wake-up call for the big players and a huge opportunity for everyone else.
Speaker #1
Exactly. And I think it shows how important collaboration is. We're all facing the same challenges with AI. we can accomplish so much more if we work together.
Speaker #0
So it's not just about who has the best technology.
Speaker #1
It's about how we use that technology to solve real problems and make the world a better place.
Speaker #0
Exactly. Well, this has been an amazing conversation. Thank you so much for sharing your expertise with us today.
Speaker #1
My pleasure.
Speaker #0
We'd like to thank the GenAI team for once again automatically generating us. Thanks for listening to the GenAI Chronicles. See you in two weeks for more.

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