Speaker 3
It's a good one. And if i may add, at least for chemists, you know, loin probability statistics and programen helps alon way,
Speaker 2
helps in life. And general, it helps in life, an general
Speaker 2
akesalit. I have a ten age son who, who knows what field or fields he may go into, but he's, he's learning the m the cormath skills and computing skills, programming skills, c the future's clear in that regard, for sure. The paper a, the transformational role of gpu computing and deep learning and drug discovery, available on line now. You can go to nature dot com a nature machine intelligence. It was published 20 third of march 20 22. So you can, you can search it up using those perometer s and take a read for yourselves. Other places that listeners might want to go on line to learn more either about either of your too, particular, your individual work, or our resources, to learn more about the field in general, that you would direct listeners to go to? Well,
Speaker 1
i guess everything is newtonat dhese days is ficion in these fields. So if you will, look up in gugl cholar publications from od co ote somtatou a start.
Speaker 2
Excellent. I will. Alexander artem again, gentlemen, thank you so much. And a thanks extended to your other co authors as well, who weren't able to join for the paper. The review, as you said, a great resource that had been missing up until now for folks in the field, or perhaps already in the field, but trying to get up to speed and using the latest in gpu accelerated and a i techniques. And also for all the workthat you've been doing, obviously through covid previously, and going forward. You know, we're all to say that were we're anticipating what comes next from your field is an understatement, caus it's really a matter of life and death. And i don't mean to be over dramatic there. So thank you for all the work that you and your colleagues are doing.
Speaker 1
Oh, thank you so much. Fo handing here that.
