The evolution of computing has significantly impacted both business and personal lives, expanding from personal computers to AI. AI is expected to continue driving technological advancements and will permeate various aspects of life and business. AMD plans to integrate AI into every product they ...
Key Takeaways
- The evolution of computing has significantly impacted both business and personal lives, expanding from personal computers to AI.
- AI is expected to continue driving technological advancements and will permeate various aspects of life and business.
- AMD plans to integrate AI into every product they build, making it foundational to their applications.
- Generative AI has made AI technology more accessible, accelerating its adoption among the general public.
- High performance computing is crucial for training advanced AI models, supporting AI’s capabilities.
- The semiconductor industry thrives on collaboration and open ecosystems, with no single company able to do it all.
- Different applications require tailored AI solutions and compute resources, necessitating diverse engines.
- Companies are prioritizing speed and adaptability over traditional business moats to stay competitive.
- Open ecosystems and interoperability are vital for success in the rapidly evolving AI landscape.
- Open standards in hardware technology promote innovation and ensure interoperability among systems.
- Generative AI’s accessibility has been a key factor in its rapid adoption and integration into daily life.
- The strategic vision for AMD includes making AI a core component of their future product development.
Guest intro
Lisa Su serves as Chair and Chief Executive Officer of AMD. She previously served as AMD’s Chief Operating Officer, integrating its business units, sales, global operations, and infrastructure into a single market-facing organization responsible for product strategy and execution. Under her leadership, AMD has transformed into the industry’s high-performance and adaptive computing leader, powering AI solutions.
The evolution of computing technology
- The evolution of computing has expanded from personal computers to AI, impacting various sectors.
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I do think it has been an evolution of how semiconductors and sort of the power of chips have really infiltrated every you know aspect of the business world, you know our personal lives and for the good.
— Lisa Su
- Semiconductors play a transformative role in technology evolution, influencing both business and personal lives.
- AI is becoming a significant driver of technological advancement.
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And then along comes this thing called AI and you know it’s like compute, it’s everywhere.
— Lisa Su
- The integration of AI into technology is expected to continue growing.
- Understanding the historical context of computing technology is essential for grasping its applications.
- The pervasive influence of semiconductors is highlighted in their role in technological evolution.
AI’s role in AMD’s future
- AI will become foundational in every product built by AMD.
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My belief is AI is gonna be everywhere in every product that we build but importantly it’s at the foundation of what enables all of these great applications.
— Lisa Su
- AMD’s strategic vision includes integrating AI into their product development.
- Generative AI has made AI technology more accessible to the public.
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The fact that we can make technology now so accessible I think is what makes this generative AI arc so so interesting and and it’s it’s what accelerated the adoption.
— Lisa Su
- The accessibility of AI technology has accelerated its adoption.
- Understanding AMD’s role in the tech industry is crucial for comprehending their focus on AI integration.
- The transformative impact of generative AI on user interaction with technology is significant.
High performance computing and AI
- High performance computing is essential for training advanced AI models.
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When you look going forward you see that high performance computing is really important in the industry in so many places and it is at the the heart of what makes AI possible because if you think about what makes AI possible it’s the ability to train these you know models with hundreds of billions of parameters trillion you know parameters so that they become ultra smart.
— Lisa Su
- The relationship between high performance computing and AI capabilities is critical.
- Understanding the role of high performance computing in AI development is important.
- The technological foundation necessary for advancements in AI is supported by high performance computing.
- The ability to train models with vast parameters is a key aspect of AI development.
- High performance computing supports AI’s capabilities and advancements.
- The critical relationship between high performance computing and AI is highlighted in technological advancements.
Collaboration in the semiconductor industry
- The semiconductor industry thrives on collaboration and open ecosystems.
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I don’t think there’s any one company that can do it all… the opportunity to closely collaborate and partner is so important.
— Lisa Su
- Collaboration is necessary due to the limitations of individual companies.
- An open ecosystem is crucial for innovation in the semiconductor industry.
- Different applications require tailored AI solutions and compute resources.
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You need the right compute for the right form factor for each application… you’re gonna need different types of AI and so you’ll have different engines for that.
— Lisa Su
- Tailored AI solutions are necessary for specific applications.
- Understanding the dynamics of the semiconductor industry is essential for grasping the role of collaboration.
Strategic shifts in business priorities
- Companies should prioritize speed and adaptability over strict adherence to traditional business moats.
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I think you know companies are willing to you know really take much more risk than they would normally because the risk reward payoff is such that you’d rather be fast and maybe not perfect than be slow and miss the boat.
— Lisa Su
- The competitive landscape in technology pressures rapid innovation.
- Open ecosystems and interoperability are crucial for success in AI.
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I’m a big believer in open ecosystems interoperable is really important… closed walls usually end up being a problem.
— Lisa Su
- Flexibility and collaboration are vital for innovation in technology development.
- The strategic shift in business priorities responds to fast-paced technological advancements.
- Understanding the importance of open ecosystems is crucial for success in the AI landscape.
The importance of open standards
- Open standards in hardware technology allow for innovation while ensuring interoperability.
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The ultra accelerator link and ultra ethernet consortium are great examples where competitors and peers can come together and say, you know what we’re gonna adopt open standards and we’re we’re each gonna innovate on top of that.
— Lisa Su
- Collaboration among competitors is facilitated by open standards.
- Open standards promote innovation in the tech industry.
- Ensuring interoperability among systems is crucial for technological advancement.
- Understanding the significance of open standards is essential for grasping their impact on the tech industry.
- The importance of collaboration in technology development is highlighted by open standards.
- Open standards are crucial for advancing industry standards and promoting innovation.

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