Kendrew Lecture 2021 pt1 - Using AI to accelerate scientific discovery - Demis Hassabis
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- เผยแพร่เมื่อ 7 ก.พ. 2025
- MRC Laboratory of Molecular Biology John Kendrew Lecture 2021 part 1
Using AI to accelerate scientific discovery
Speaker: Demis Hassabis, Founder and CEO, DeepMind.
Abstract:
The past decade has seen incredible advances in the field of Artificial Intelligence (AI). DeepMind has been in the vanguard of many of these big breakthroughs, pioneering the development of self-learning systems like AlphaGo, the first program to beat the world champion at the complex game of Go. Games have proven to be a great training ground for developing and testing AI algorithms, but the aim at DeepMind has always been to build general learning systems ultimately capable of solving important problems in the real world. Excitingly, I believe we are on the cusp of a new era in science with AI poised to be a powerful tool for accelerating scientific discovery itself. We recently demonstrated this potential with our AlphaFold system, a solution to the 50-year grand challenge of protein structure prediction, culminating in the release of the most accurate and complete picture of the human proteome.
Read more about the lecture and David's work here: www2.mrc-lmb.c...
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About the MRC Laboratory of Molecular Biology (LMB):
The LMB is one of the world's leading research institutes. Discoveries and inventions developed at the LMB, for example DNA sequencing and methods to determine the structure of proteins, have revolutionised all areas of biology. Its scientists work to advance understanding of biological processes at the molecular level. This information will help us to understand the workings of complex systems, such as the immune system and the brain, and solve key problems in human health.
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Official Site: www2.mrc-lmb.c...
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AI research we often hear about mostly seems to be language related, computer graphics or recommending stuff to buy. Not saying it's not useful, but seeing Demis makes leaps and bounds in such fundamental and important applications is a breath of fresh air.
Fabulous talk
At 15:32 there’s that beautiful dynamic slide. I wonder if there’s any loops to previous plays representing maybe more of a gradient (not gradient decent mind you) instead of a tree..?
Inspiring!
very inspiring work
This is truly a great talk!
Fantastic talk!
@Alex you have all things AI in your home picture but no videos? If you’re watching this I’m curious what else you’ve found in the area
@@quaidcarlobulloch9300 haha, great catch my friend. That's just a preview of a future project I aim to bring to light soon
@@alexmorehead6723 Very cool! Are you coming at it from the hardware or software perspective?
@@quaidcarlobulloch9300 Most likely AI from the software perspective, but I'm not opposed to digging into the hardware of it all (I'm studying Computer Science at the PhD level, with an open mind towards hardware)
@@alexmorehead6723 Nice! Broad computer science with a focus on AI or broad AI with a focus on computer science? I’m considering getting a PhD in eecs for parallel processing that mimics the brain more closely, and software is definitely an interest!
중요하면서도 유머가 넘치는 훌륭한 강의!
I was here in November 2021 ;)
"Chess and Go, and one other game which I've forgotten..."
How could you forget Starcraft?!
If the AI is based on a scientist then it should also be able to modulate its thinking time.
Furthermore/through temp outputs which could even indicate that it was thinking such as “hold on I need more time to think.” That temp output example could even be a preexisting output from which the AI learns that it gets more thinking time. But I guess that’s an observation it would be making in and of itself spending time on, ah recursion! But maybe it would learn that only once and use something like memory to avoid repetitive thoughts!
uhoh
Next comes "Dr. Eldon Tyrell", fully genetically engineered organics :-P