In a hotel in San José, in the heart of Silicon Valley (California, USA), AMD has presented the next piece of the artificial intelligence revolution, amidst lights and euphoric applause. This is the MI300, an accelerator that fits in the palm of a hand and that the Californian company claims will be able to run artificial intelligence software faster than any product currently on the market. “Perhaps by now we are tired of hearing about artificial intelligence, but it is surely the most transformative technological revolution of the last 50 years, probably even more so than computers and the Internet,” said Lisa Su, CEO of the company Advanced Micro. Devices (AMD), during an event to which EL PAÍS was invited at the beginning of December.
The launch is one of the most important in the five decades of history of the company, whose processors with artificial intelligence are already being used by the most relevant companies and researchers in the sector to manufacture computers with integrated AI, including Microsoft, Open AI and Goal. The vice president and general manager of AMD, Jason Banta (Lubbock, USA, 44 years old), spoke with EL PAÍS at the end of the event about the possibilities of this technology, which claims to be advancing at “dizzying and exciting” rates.
Ask. How is it possible that something that no one was talking about five years ago has become the most important topic of the moment?
Answer. One of the most transformative aspects has been large-scale language models. They have been evolving quite quickly since 2017, and really gained momentum when many people saw their stunning beauty and everything they can do. That created a lot of additional interest, whether in chatbots or other generative AI applications. And it has probably been the fastest development of a new technology that we have seen in the industry, becoming a transformative tool in the cloud, on the PC and on other devices.
Q. What does it mean to have artificial intelligence directly integrated into computers?
R. That computers are more personal, that they are capable of better understanding how each user wants to interact. If before we were the ones who had to learn to use them, in the future computers with artificial intelligence will be able to anticipate our needs. This will enable new audio and video experiences, making it easier to generate creative content, a process that can be challenging on a traditional computer. Devices with built-in AI will take care of that and handle it all for the users. But they will also make computers more secure, by being able to detect and manage threats.
Q. On a practical level, what can already be done?
R. Today, most of the most important applications we see are collaborations with different tools. If you use Zoom or Teams, there are many fields where AI is used, such as image enhancement. And what can be achieved is that this happens with greater battery performance. Another field is the creation of content or applications, in the fields of audio and video editing: this is a sector that will continue to grow. However, it is still too early to see the full potential of this technology applied to personal computers. We will see most of the advances in the near future.
Q. How long will it be before everyone has an AI computer?
R. I think we'll see more of that sometime in 2024, although for a big inflection we'll have to wait until 2025. We'll have to take a big step forward in this direction first, and then it will grow from there. But we are going to start to see much stronger adoption in the coming months, until really in the next two years the AI laptop will begin to take hold.
Q. Is the power of current computers enough to develop AI adequately?
R. Much of the development and training of AI models is still happening in the cloud. But in the next few years, I hope to see training of smaller models running in real time on computers. This way, while you are interacting with an application, you can train it in real time to adjust the way it interacts with you.
Q. In which fields are the most radical changes expected?
R. On both mobile phones and laptops, the challenges are similar: adapting AI models to work efficiently on these devices. We are starting to see progress in this regard. Many of the phones coming out today already have artificial intelligence integrated, but they need to be able to be used without having to charge them six or seven times a day.
Q. What are the current limits of this technology?
R. Our biggest challenge is to scale down this technology and get it to run efficiently on laptops. Some of this is beginning to emerge. We just released a software package that enables so-called quantization: basically making those large models smaller so they can run efficiently on laptops. Stay within a laptop's memory, run efficiently, and not harm the life of a battery. That is the challenge we have to deal with as an industry, and we are putting the tools in place so that can happen.
Q. Asian countries dominate the semiconductor supply chain. Can we expect Europe and the United States to improve their production?
R. Our goal is for there to be a geographically diverse semiconductor ecosystem, we believe this is positive for the industry as a whole. We are collaborating with governments and supply chain partners to encourage this to happen. It's something we're seeing evolve over time, but we think it's important not to rely too much on a single geography for semiconductor supply.
Q. Is AI being developed with environmental impact in mind?
R. We take the ecological perspective very much into account, it is at the forefront of our approaches when thinking about the development of these technologies. It is also true that some of the things that a computer with integrated AI can do, compared to a normal laptop, is to save workload and time, which entails real efficiency on a large scale. We are working on ways to optimize energy consumption, and these are very real implications that we take into consideration at every stage of our development.
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