Re-engineering the computer to solve impossible math problems with AI accelerators
08/22/24 • 20 min
There are math problems that are hard. So hard that even current computers cannot solve them. To get around these problems, we need to re-think the very foundation of how we architect our IT, by using a technological field called 'novel accelerators'.
It sounds complicated, but today's guest is particularly skilled at explaining incredibly complicated concepts. He says: "Right now, Generative AI and accelerators are at the forefront of being able to help with these major advances, and the world could change in really significant ways. Medicine, materials, energy, information technology... to harness these systems to help us - not to replace us."
Joining us today is Ray Beausoleil, a physicist, senior fellow and senior vice president at HPE. He leads the large scale integrated photonics lab at Hewlett Packard Labs.
This is Technology Now, a weekly show from Hewlett Packard Enterprise. Every week we look at a story that's been making headlines, take a look at the technology behind it, and explain why it matters to organizations and what we can learn from it.
Do you have a question for the expert? Ask it here using this Google form: https://forms.gle/8vzFNnPa94awARHMA
About this week's guest:
Ray Beausoleil: https://www.linkedin.com/in/ray-beausoleil-22b148a/
Sources and statistics cited in this episode:
Bloomberg report into AI growth: https://www.bloomberg.com/company/press/generative-ai-to-become-a-1-3-trillion-market-by-2032-research-finds/
Fusion and mayonnaise: https://engineering.lehigh.edu/news/article/lehigh-university-researchers-dig-deeper-stability-challenges-nuclear-fusion-mayonnaise
There are math problems that are hard. So hard that even current computers cannot solve them. To get around these problems, we need to re-think the very foundation of how we architect our IT, by using a technological field called 'novel accelerators'.
It sounds complicated, but today's guest is particularly skilled at explaining incredibly complicated concepts. He says: "Right now, Generative AI and accelerators are at the forefront of being able to help with these major advances, and the world could change in really significant ways. Medicine, materials, energy, information technology... to harness these systems to help us - not to replace us."
Joining us today is Ray Beausoleil, a physicist, senior fellow and senior vice president at HPE. He leads the large scale integrated photonics lab at Hewlett Packard Labs.
This is Technology Now, a weekly show from Hewlett Packard Enterprise. Every week we look at a story that's been making headlines, take a look at the technology behind it, and explain why it matters to organizations and what we can learn from it.
Do you have a question for the expert? Ask it here using this Google form: https://forms.gle/8vzFNnPa94awARHMA
About this week's guest:
Ray Beausoleil: https://www.linkedin.com/in/ray-beausoleil-22b148a/
Sources and statistics cited in this episode:
Bloomberg report into AI growth: https://www.bloomberg.com/company/press/generative-ai-to-become-a-1-3-trillion-market-by-2032-research-finds/
Fusion and mayonnaise: https://engineering.lehigh.edu/news/article/lehigh-university-researchers-dig-deeper-stability-challenges-nuclear-fusion-mayonnaise
Previous Episode
Formula E: Bridging the gap between the digital and real worlds
In this episode, we’ll be taking you on a trip to London for the final race weekend of the 10th season of the Formula E championship, which was held on the weekend of the 20th and 21st July.
We’ve been looking at the tech behind the event, how Formula E is transforming the world of racing, and what our organisations can learn from the cutting edge of motorsport.
One of those areas is in training and familiarity. Knowing the circuit and how the car will behave at any given moment is obviously a huge advantage. But how do you work that out when you’ve only got the race weekend?
Well, one way is to use track and car simulations - essentially, incredibly accurate digital twins of a racetrack with a full suite of driving controls and simulated movement, where drivers can test their setups in a variety of conditions, to prepare for race day.
Here to talk more about that are this week’s guests, from Maserati MSG racing: Cyril Blais, deputy team principal, and driver Maximillian Günther.
This is Technology Now, a weekly show from Hewlett Packard Enterprise. Every week we look at a story that's been making headlines, take a look at the technology behind it, and explain why it matters to organizations and what we can learn from it.
Do you have a question for the expert? Ask it here using this Google form: https://forms.gle/8vzFNnPa94awARHMA
About this week's guests:
Cyril Blais : https://www.linkedin.com/in/cyril-blais/
Maximillian Günther: https://en.wikipedia.org/wiki/Maximilian_G%C3%BCnther
Sources and statistics cited in this episode:
Formula E: https://www.fiaformulae.com/en
2024 Hankook London ePrix: https://www.fiaformulae.com/en/calendar/2023-24/r16-london
Japan abandons floppy disks (English coverage): https://www.bbc.co.uk/news/articles/cx82407j1v3o
Next Episode
Re-imagining how we train LLMs using physics-based AI
Machine-learning based Generative AI is inherently inefficient. Training models by sifting findings again and again until a suitable output is generated is a time-consuming – end energy-consuming – process. So, could there be a better way to look at training our AI systems?
Well, one possible option is physics-based AI, where training is viewed as an energy grid, and the best possible route though that grid mapped to find outputs. It’s a novel way of thinking, but it could change our whole approach to AI.
Joining us again today to find out more is Ray Beausoleil, a physicist, senior fellow and senior vice president at HPE. He leads the large scale integrated photonics lab at Hewlett Packard Labs.
This is Technology Now, a weekly show from Hewlett Packard Enterprise. Every week we look at a story that's been making headlines, take a look at the technology behind it, and explain why it matters to organizations and what we can learn from it.
Do you have a question for the expert? Ask it here using this Google form: https://forms.gle/8vzFNnPa94awARHMA
About this week's guest: Ray Beausoleil: https://www.linkedin.com/in/ray-beausoleil-22b148a/
Sources and statistics cited in this episode:
WEF paper on data centre energy usage: https://www.weforum.org/agenda/2024/07/generative-ai-energy-emissions/
IEA sats on energy usage in IT: https://www.iea.org/energy-system/buildings/data-centres-and-data-transmission-networks#overview
Novel insulins grand challenge: https://type1diabetesgrandchallenge.org.uk/funding/closed-funding/novel-insulins-innovation-incubator/
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