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$AMD CEO: “Inference will be a much bigger market than training.” Inference is growing so fast that more than half of the AI workloads will be inference next year. $NVDA bought Groq to enhance its inference capabilities; $GOOG is developing a new custom ASIC with $MRVL specifically to boost...

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Oguz Erkan

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84,874 views • 2 months ago •via X (Twitter)

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$NVDA CEO: “Demand for inference will go up by a billion times.” $AMD will be one of the biggest winners as it has the upper hand in inference thanks to larger memory bandwith and capacity of its chips. Stock is still at 22x 2027 earnings. How can’t you be bullish on $AMD?
0:20

$NVDA CEO: “Demand for inference will go up by a billion times.” $AMD will be one of the biggest winners as it has the upper hand in inference thanks to larger memory bandwith and capacity of its chips. Stock is still at 22x 2027 earnings. How can’t you be bullish on $AMD?

Oguz Erkan

282,229 views • 2 months ago

While everyone is crying, Zuck has gone all in on $AMD. Llama runs inferences exclusively on $AMD MI300X. This deal shows $AMD has an edge in inference over $NVDA, which will be a much larger market than training.
12:28

While everyone is crying, Zuck has gone all in on $AMD. Llama runs inferences exclusively on $AMD MI300X. This deal shows $AMD has an edge in inference over $NVDA, which will be a much larger market than training.

Antonio Linares

170,180 views • 1 year ago

$META is betting on $AMD for AI inference. As AI models become more commoditized, total cost of ownership for token generation matters more than ever. $AMD GPUs are far more cost-efficient than $NVDA for inference. With 3.5B daily users ready to use its AI models, $META is going all-in on $AMD
3:17

$META is betting on $AMD for AI inference. As AI models become more commoditized, total cost of ownership for token generation matters more than ever. $AMD GPUs are far more cost-efficient than $NVDA for inference. With 3.5B daily users ready to use its AI models, $META is going all-in on $AMD

Daniel

20,558 views • 5 months ago

Groq founder Jonathan Ross explains why their architecture is better for inference than GPUs. Inference doesn't require as much compute power as training. What matters in inference is speed, cost, and energy consumption. $NVDA was going to lose market share as AI workloads shift to inference. They saw this and made a highly strategic move by striking a deal with Groq. $NVDA is already dominating training, and now it's also well-positioned to dominate inference.
1:45

Groq founder Jonathan Ross explains why their architecture is better for inference than GPUs. Inference doesn't require as much compute power as training. What matters in inference is speed, cost, and energy consumption. $NVDA was going to lose market share as AI workloads shift to inference. They saw this and made a highly strategic move by striking a deal with Groq. $NVDA is already dominating training, and now it's also well-positioned to dominate inference.

Oguz Erkan

97,186 views • 6 months ago

$NVDA CEO: “Inference demand will go up by a billion times.” We are just in the very early innings. Compute demand will likely grow by another 10x over the next decade and current TAM projections for GPU/CPU will look too conservative in hindsight. $AMD $NVDA $INTC $ARM
0:20

$NVDA CEO: “Inference demand will go up by a billion times.” We are just in the very early innings. Compute demand will likely grow by another 10x over the next decade and current TAM projections for GPU/CPU will look too conservative in hindsight. $AMD $NVDA $INTC $ARM

Oguz Erkan

198,071 views • 1 month ago

This is why Nvidia bought Groq. If Groq deploys a ton of low-cost inference chips, demand for training will increase massively. The more inference you have, the more training you need, and vice versa. Nvidia can keep its high margins selling chips for training forever.
0:35

This is why Nvidia bought Groq. If Groq deploys a ton of low-cost inference chips, demand for training will increase massively. The more inference you have, the more training you need, and vice versa. Nvidia can keep its high margins selling chips for training forever.

Lin

92,571 views • 6 months ago

No wonder Jensen got so defensive over $NVDA GPUs against custom chips. $GOOG will start using different custom chips for inference and training. $AMZN has already adopted this approach as they have Trainium for training and Inferentia for inference. Hyperscalers obviously see better price/performance in this approach, and this is where the industry is headed. $AVGO and $MRVL are poised to be big winners, while $NVDA dominance will be under increasing pressure.
3:25

No wonder Jensen got so defensive over $NVDA GPUs against custom chips. $GOOG will start using different custom chips for inference and training. $AMZN has already adopted this approach as they have Trainium for training and Inferentia for inference. Hyperscalers obviously see better price/performance in this approach, and this is where the industry is headed. $AVGO and $MRVL are poised to be big winners, while $NVDA dominance will be under increasing pressure.

Oguz Erkan

223,244 views • 2 months ago

$AMD $NVDA| called it! 🚨🚨🚨 $NVDA produces expensive tokens. Inference (Cost per Million Tokens) ~$NVDA B200 / HGX: ~$0.02–$0.08 ~$AMD Helios Racks: $0.0003-$0.0005 (Read more below to understand) Companies are capping Inference token! This is how AMD shareholders gonna be in 2030.
0:26

$AMD $NVDA| called it! 🚨🚨🚨 $NVDA produces expensive tokens. Inference (Cost per Million Tokens) ~$NVDA B200 / HGX: ~$0.02–$0.08 ~$AMD Helios Racks: $0.0003-$0.0005 (Read more below to understand) Companies are capping Inference token! This is how AMD shareholders gonna be in 2030.

Mike

19,813 views • 23 days ago

$AMD is providing receipts right now winning inference workloads from one of the best implementers of AI on the planet in $META And don’t @ me about the warrants. No one will care when AMD market cap goes above a trillion. 👏🏻🔥🚀
1:22

$AMD is providing receipts right now winning inference workloads from one of the best implementers of AI on the planet in $META And don’t @ me about the warrants. No one will care when AMD market cap goes above a trillion. 👏🏻🔥🚀

Daniel Newman

21,024 views • 4 months ago

"Inference, if you look at it as a market, will be much, much bigger than cloud computing was pre-ChatGPT." Lightspeed’s Bucky Moore says inference is an underrated investment category in AI, and expects the market to break up into large, specialized platforms for each modality: "The GPU supply crunch that we're seeing right now is largely, as Dylan Patel has said on the show before, due to the fact that not only these consumer products, but also B2B products like Claude Code and Codex are just really taking off and creating insane demand for inference." "We're talking hundreds of billions in spend every year. And if that's true, I think there will be very, very large inference platforms built in each modality." "So there will be an inference platform for real-time video models, there will be an inference platform for open-source and custom language models, there will be an inference platform built specifically for long-running agents." "So I think we're just going to see that industry, which today looks like one industry, break up into many because of how big it is and how much room for specialization there is."
1:02

"Inference, if you look at it as a market, will be much, much bigger than cloud computing was pre-ChatGPT." Lightspeed’s Bucky Moore says inference is an underrated investment category in AI, and expects the market to break up into large, specialized platforms for each modality: "The GPU supply crunch that we're seeing right now is largely, as Dylan Patel has said on the show before, due to the fact that not only these consumer products, but also B2B products like Claude Code and Codex are just really taking off and creating insane demand for inference." "We're talking hundreds of billions in spend every year. And if that's true, I think there will be very, very large inference platforms built in each modality." "So there will be an inference platform for real-time video models, there will be an inference platform for open-source and custom language models, there will be an inference platform built specifically for long-running agents." "So I think we're just going to see that industry, which today looks like one industry, break up into many because of how big it is and how much room for specialization there is."

TBPN

33,278 views • 3 months ago

IN NEWS: Baseten raises a $150M series D round. Tuhin Srivastava (Founder & CEO, Baseten) on the future of inference: “I think the token price goes down and inference should get cheaper over time. And that really just means there is going to be more inference.” “Every time we lower prices or optimize models to make it cheaper, four months later customers are spending more anyway.” “Inference prices will go down, but if the world is run by AI in 10 years, there is going to be a lot of inference. It better be cheap.”
0:52

IN NEWS: Baseten raises a $150M series D round. Tuhin Srivastava (Founder & CEO, Baseten) on the future of inference: “I think the token price goes down and inference should get cheaper over time. And that really just means there is going to be more inference.” “Every time we lower prices or optimize models to make it cheaper, four months later customers are spending more anyway.” “Inference prices will go down, but if the world is run by AI in 10 years, there is going to be a lot of inference. It better be cheap.”

TBPN

17,057 views • 9 months ago

📢 ATTN: AI Developers Are you ready to optimize, accelerate, and compete? Join the AMD Developer Challenge 2025: Inference Sprint. Push inference performance to the limit on the AMD ROCm software platform with cloud-based AMD MI300X. 🏆 $100K grand prize + $50K in additional cash prizes 💻 Register:
0:38

📢 ATTN: AI Developers Are you ready to optimize, accelerate, and compete? Join the AMD Developer Challenge 2025: Inference Sprint. Push inference performance to the limit on the AMD ROCm software platform with cloud-based AMD MI300X. 🏆 $100K grand prize + $50K in additional cash prizes 💻 Register:

AMD

40,350 views • 1 year ago

So now everyone is talking about how AMD is going to have edges over NVDA in inference? Listen to Jense explain inference problem and how Nvidia is also dominating it.
3:15

So now everyone is talking about how AMD is going to have edges over NVDA in inference? Listen to Jense explain inference problem and how Nvidia is also dominating it.

The AI Investor

27,271 views • 10 months ago

💡 Inference is hitting a major inflection point in 2025. The future of AI computing will be shaped by who can deliver performance and efficiency at scale. At AMD Advancing AI, Daniel Newman & Patrick Moorhead sat down with Andrew Dieckmann and Anush Elangovan to explore how AMD is strategically positioned to lead in both AI training and inferencing—two of the fastest-growing segments in AI compute. Learn how they're scaling real-world deployments across both training and inference. Catch the full conversation:
0:56

💡 Inference is hitting a major inflection point in 2025. The future of AI computing will be shaped by who can deliver performance and efficiency at scale. At AMD Advancing AI, Daniel Newman & Patrick Moorhead sat down with Andrew Dieckmann and Anush Elangovan to explore how AMD is strategically positioned to lead in both AI training and inferencing—two of the fastest-growing segments in AI compute. Learn how they're scaling real-world deployments across both training and inference. Catch the full conversation:

Six Five Media

29,588 views • 1 year ago

The market is once again completely wrong about $AMD. Free cash flow per share is growing exponentially. $AMD is now ready to take the entire inference market.
16:18

The market is once again completely wrong about $AMD. Free cash flow per share is growing exponentially. $AMD is now ready to take the entire inference market.

Antonio Linares

45,893 views • 4 months ago

Dylan Patel: “CPUs are sold out.” $INTC earnings and conference call confirmed the looming CPU shortage. There are three main drivers: - Agentic systems, as CPUs do the planning and orchestration. - Increasing complexity of and demand for reinforcement learning environments that run on CPUs. - Increasing deployment of AI instilled apps. Models run on GPUs but apps themselves run on CPUs. Demand for all these will grow secularly as AI systems will only get more agentic, RL environments will only get more complex, and deployment will only accelerate. As a result, GPU-to-CPU ratio in AI workloads will move from 1:8 to 1:2 or maybe even 1:1 in the future. CPU supercycle is about to start. $AMD $INTC $ARM
1:44

Dylan Patel: “CPUs are sold out.” $INTC earnings and conference call confirmed the looming CPU shortage. There are three main drivers: - Agentic systems, as CPUs do the planning and orchestration. - Increasing complexity of and demand for reinforcement learning environments that run on CPUs. - Increasing deployment of AI instilled apps. Models run on GPUs but apps themselves run on CPUs. Demand for all these will grow secularly as AI systems will only get more agentic, RL environments will only get more complex, and deployment will only accelerate. As a result, GPU-to-CPU ratio in AI workloads will move from 1:8 to 1:2 or maybe even 1:1 in the future. CPU supercycle is about to start. $AMD $INTC $ARM

Oguz Erkan

93,419 views • 2 months ago

Dojo 2, Dojo 3 Chips and AI5 Chips Are Critical for Tesla and Battle for Future of AI. Tesla and XAI are buying about one million AI GPUs this year. This would be about 20% of the entire Nvidia production of B200/B300 chips that will be made in 2025. If XAI were to buy a mix of half Dojo 2/3 chips in 2025 and 2026 this could make them bigger than AMD. AMD is making about 400,000 AI GPU chips. Tesla will switch to AI5 chips for driving its cars but those chips will also act as inference chips with about 500 Teraflops of compute. Tesla could make 3-4 million AI5 chips in 2026. This would make Tesla the largest maker and user of AI inference chips in the world. Tesla could become the number 2 maker of AI training chips just by supplying a lot of those chips to XAI and Tesla internal use. Tesla is and will be the number one maker and user of AI inference chips. Sawyer Merritt Elon Musk Randy Kirk Herbert Ong Warren Redlich - Chasing Dreams 🇺🇸 Ale𝕏andra Merz 🇺🇲 Ray Emmet Peppers Bradford Ferguson
56:36

Dojo 2, Dojo 3 Chips and AI5 Chips Are Critical for Tesla and Battle for Future of AI. Tesla and XAI are buying about one million AI GPUs this year. This would be about 20% of the entire Nvidia production of B200/B300 chips that will be made in 2025. If XAI were to buy a mix of half Dojo 2/3 chips in 2025 and 2026 this could make them bigger than AMD. AMD is making about 400,000 AI GPU chips. Tesla will switch to AI5 chips for driving its cars but those chips will also act as inference chips with about 500 Teraflops of compute. Tesla could make 3-4 million AI5 chips in 2026. This would make Tesla the largest maker and user of AI inference chips in the world. Tesla could become the number 2 maker of AI training chips just by supplying a lot of those chips to XAI and Tesla internal use. Tesla is and will be the number one maker and user of AI inference chips. Sawyer Merritt Elon Musk Randy Kirk Herbert Ong Warren Redlich - Chasing Dreams 🇺🇸 Ale𝕏andra Merz 🇺🇲 Ray Emmet Peppers Bradford Ferguson

nextbigfuture

23,809 views • 1 year ago

Jensen Huang thinks demand for inference will go up by billion times. And you still have $AMD trading at 23 times forward earnings. Talk about the market efficiency..
0:20

Jensen Huang thinks demand for inference will go up by billion times. And you still have $AMD trading at 23 times forward earnings. Talk about the market efficiency..

Oguz Erkan

90,441 views • 1 year ago

What is AI inference engineering, why is it such an in-demand skill, and how do you break into the field? With author of Inference Engineering Philip Kiely and head of training at Baseten Charlie O'Neill 0:00: What is inference? 2:47: History of inference 4:59: Downstream effects of AI research on inference 13:54: What you'll learn from Inference Engineering 16:14: Advice for engineers transitioning into AI 19:00: Open source models driving inference growth 20:55: Specialization vs. frontier closed models 23:51: "Big Token" and the importance of open source AI 27:18: Where to get Inference Engineering
27:58

What is AI inference engineering, why is it such an in-demand skill, and how do you break into the field? With author of Inference Engineering Philip Kiely and head of training at Baseten Charlie O'Neill 0:00: What is inference? 2:47: History of inference 4:59: Downstream effects of AI research on inference 13:54: What you'll learn from Inference Engineering 16:14: Advice for engineers transitioning into AI 19:00: Open source models driving inference growth 20:55: Specialization vs. frontier closed models 23:51: "Big Token" and the importance of open source AI 27:18: Where to get Inference Engineering

Madison Kanna

119,268 views • 3 months ago