Science, Innovation and Technology Committee
17 June 2026
Speaker dots
- Speakers in the chapter
- Colour: political group
- Grey: no group
Tap or click a chapter's dots to see names and groups.
Contents updated on 17 Jun 2026
Legend
Transcript markers
- text Sentence being played
- text Search result
- text Intervention cited by the link you opened
Click a sentence to play the video from that moment. Select text to quote it with the speaker, timestamp and link.
More options
Official source
Offset
Transcript offset
0s
Text size
Export
Live capture
Versions of this video
Transcripts may differ slightly from one version to another.
Science, Innovation and Technology Committee Actual start House of Commons
16:50 - 18:26
Speaker 1
Order, order. Welcome to today's meeting of the Science, Innovation and Technology Select Committee. As the leaders of the G7 meet with the CEOs of the world's most powerful AI companies, I'm sure energy consumption will be on the agenda. And so it's really timely that today is the first session of our new inquiry looking at the future of compute in terms of power and capacity, specifically whether emerging innovations in low-energy computing can support more sustainable use of artificial intelligence and machine learning tools.
Now I just want to say that we launched this inquiry following pitches to our Under the Microscope initiative, and we received over 30 pieces of written evidence, so a big thank you to everyone who took the time to contribute. Now today we will be looking at the science underpinning advances in neuromorphic computing and silicon photonics in particular, and we are particularly interested to hear how well-positioned the UK is to ensure research breakthroughs can be translated into real-world applications. So a big welcome to my panel, and I'm going to ask each of you in turn, starting with Professor Trefzer, to introduce yourself, your area of research, and to define or explain for us what neuromorphic computing is, and particularly for me, I'm interested in how it differs from neural networks.
18:26 - 18:28
Speaker 2
So Professor Trefzer, over to you.
18:28 - 18:30
Speaker 4
Yep, great.
The rest of the transcript is for Pro customers
Unlock the full transcript, chat, and every analysis feature with Polyfact Pro.
The video itself stays free to watch, in full, no account needed.
Ask anything about this video — I analyse its transcript to answer.