You might have heard the audio version of this podcast which we recently published to the channel by mistake - but this is the full, video version, we hope you enjoy!
Such an amazing interview on a topic that I couldn't have even imagined would ever be possible. It makes me want to study biology. Thanks to The RI, Lisa, and Janet for putting this together!
I find it much easier to be understood by the general public than most of the lectures produced by the Royal Institute! I encourage more person-to-person interviews (not in radio program style) on intricate topics like this as the moderator plays the role of a guide and a bridge between experts & the audience, and the experts still have a chance to demonstrate some abstract science objects straightforwardly and vividly.
Wonderful to see behind the scenes of real AI applications. Most AI use seems hidden due to commercial interests or all over the place with images and prompts for very little other than entertainment purposes. Thank you for making this!
I have enjoyed the podcasts in the past but the video improves them tremendously as I have in the audio only casts wished I could see the body language and enthusiasm your speakers have and in the case of this one the simple but very clarifying examples of the models. Please keep up the excellent output.
9 місяців тому
Thank you Royal Institution (RI), greetings from Bimac Research Group at universidad del Cauca, Colombia.
Mind-blowing interview! I never imagined witnessing AI crack the protein problem in my lifetime. Thanks a million for sharing this insightful podcast. 👏
So excited for the podcast and love this video version! If I could make a suggestion though, I found the lighting to be quite distracting due to the bright colors. If it could be subdued in future, it'd be perfect for me! Great work!!
Are there ways to check the predicted protein structure is correct without having to use the techniques (e.g. x-ray crystallography) standardly employed to determine structure? Does the AI _always_ get it right?
Do you mean experimentally? X-ray crystalography is the best method. But other techniques are also very useful and look at other aspects of the structure. It is not just the shape but how the structures 'jiggle' and that is very important to identify rules for how the structure ('shape') relates with function.
A prediction: Alphafold and the people behind it will be the first AI team to win a Nobel prize for chemistry (with the proviso of the three people issue )...
12:18 Interviewer forgot to bring Thornton back to the 2nd problem originally mentioned at the beginning of that explanation. I suspect Thornton forgot she had listed two problems: the first being "folding" and the second being...?
I appreciate her expertise but I disagree about her assertion that protein folding still has not been solved. Her argument would be like saying a chess AI that actually played perfect chess would still not have solved chess if it didn't explain to everyone exactly how it finds the perfect move (like in the typical neural net type). Whether it can explain it so you understand it is a different matter than whether it can do it or not. And actually in terms of how proteins fold (or how chess moves are judged), we actually DO know exactly how it works, all it is is the physical laws being followed by the matter involved. So in fact, what she means by "understanding" is really nothing more than finding the right shortcuts of calculation to those physical laws to make their impossible computation something possible to do, in the same way that meteorology doesn't predict the whether by calculating every single particle's trajectory, but instead finds shortcut to that by deriving macroscopic behavior predictions. All of that being said, I don't think calling something solved should have to do with us being provided all the possible calculation shortcuts, they're just that in the end: shortcuts. Making the correct calculation is the thing to solve, not doing it in the most understandable "speaks-to-us" way. We know the actual complete mechanics driving the folding: the physical laws, and we can calculate the end result of those laws.: Solved.
Great video. However the production could be improved. Lighting should come from above to avoid shadows. More soft light too dark.Framing of each speaker should be as such they are facing each other. The editing works well. My two cents
You might have heard the audio version of this podcast which we recently published to the channel by mistake - but this is the full, video version, we hope you enjoy!
Wondered about that! Thank you.
What a good mistake to have! This was an interesting conversation. This video version is well polished. Hope to see more like it in the future!
Such an amazing interview on a topic that I couldn't have even imagined would ever be possible. It makes me want to study biology. Thanks to The RI, Lisa, and Janet for putting this together!
I find it much easier to be understood by the general public than most of the lectures produced by the Royal Institute! I encourage more person-to-person interviews (not in radio program style) on intricate topics like this as the moderator plays the role of a guide and a bridge between experts & the audience, and the experts still have a chance to demonstrate some abstract science objects straightforwardly and vividly.
Wonderful to see behind the scenes of real AI applications. Most AI use seems hidden due to commercial interests or all over the place with images and prompts for very little other than entertainment purposes. Thank you for making this!
Actual practical uses for AI other than selling cars or chatbots. Yeah, they'll be selling drugs, but a lot more drugs that work, cheaper and faster.
Good afternoon RI and Dame Janet Thornton
Super facts in science and AI application explained splendidly.
Truly grateful for you and your work.
💜
I have enjoyed the podcasts in the past but the video improves them tremendously as I have in the audio only casts wished I could see the body language and enthusiasm your speakers have and in the case of this one the simple but very clarifying examples of the models. Please keep up the excellent output.
Thank you Royal Institution (RI), greetings from Bimac Research Group at universidad del Cauca, Colombia.
Mind-blowing interview! I never imagined witnessing AI crack the protein problem in my lifetime. Thanks a million for sharing this insightful podcast. 👏
Thank you for this, wonderfully curated and superbly explained.
So excited for the podcast and love this video version! If I could make a suggestion though, I found the lighting to be quite distracting due to the bright colors. If it could be subdued in future, it'd be perfect for me! Great work!!
Thank you so much for another gift of knowledge
Amazing, thank you!
That just tickled my brain a little. I didnt really understand it. Encouraging to see great humans using great tools to help the world.
such a lovely interview, This was wonderful
Are there ways to check the predicted protein structure is correct without having to use the techniques (e.g. x-ray crystallography) standardly employed to determine structure? Does the AI _always_ get it right?
Do you mean experimentally? X-ray crystalography is the best method. But other techniques are also very useful and look at other aspects of the structure. It is not just the shape but how the structures 'jiggle' and that is very important to identify rules for how the structure ('shape') relates with function.
Really interesting podcast thank you Ri 👏🏼
Great job producer Lia Hale 😊
Now AlphaFold 3 is out, and can predict which drugs will actually work with much higher accuracy than before.
Thank you. This was so interesting - even for a non-scientific golden oldie like me
Fascinating
A prediction: Alphafold and the people behind it will be the first AI team to win a Nobel prize for chemistry (with the proviso of the three people issue )...
they won already now
"How they fold determines how they work"
I am still wondering why I kinda thought of string theory for a moment there...
Nice 👍
12:18 Interviewer forgot to bring Thornton back to the 2nd problem originally mentioned at the beginning of that explanation. I suspect Thornton forgot she had listed two problems: the first being "folding" and the second being...?
8:25 being the point at which Thornton mentions that the folding problem has two aspects, the 2nd of which seems to have been left behind.
❤❤❤❤❤
Bring demis
She said a young child should understand the protien folding problem. 😂😂
I appreciate her expertise but I disagree about her assertion that protein folding still has not been solved. Her argument would be like saying a chess AI that actually played perfect chess would still not have solved chess if it didn't explain to everyone exactly how it finds the perfect move (like in the typical neural net type). Whether it can explain it so you understand it is a different matter than whether it can do it or not.
And actually in terms of how proteins fold (or how chess moves are judged), we actually DO know exactly how it works, all it is is the physical laws being followed by the matter involved. So in fact, what she means by "understanding" is really nothing more than finding the right shortcuts of calculation to those physical laws to make their impossible computation something possible to do, in the same way that meteorology doesn't predict the whether by calculating every single particle's trajectory, but instead finds shortcut to that by deriving macroscopic behavior predictions.
All of that being said, I don't think calling something solved should have to do with us being provided all the possible calculation shortcuts, they're just that in the end: shortcuts. Making the correct calculation is the thing to solve, not doing it in the most understandable "speaks-to-us" way. We know the actual complete mechanics driving the folding: the physical laws, and we can calculate the end result of those laws.: Solved.
I folded some.
Great video. However the production could be improved. Lighting should come from above to avoid shadows. More soft light too dark.Framing of each speaker should be as such they are facing each other. The editing works well. My two cents
Nothing wrong with a nice bit of chiaroscuro and some mood lighting. There's nothing at all wrong or substandard about this video's production.
I found some of the shadows distracting particularly the hand shadows over bodies.
Personally I enjoyed the lighting, although yes it could be a little distracting, and possibly would work better in a different seating layout.
Unique, not eunuch.
the background music of the intro is unbearable
Ai solve the problem without without we can understand the process. The next ai revolution will be ai will explain the process.
Whos the cutie interviewing Thornton?