Відео

I really learn from these podcasts, especially from the questions you ask the guests.

"Thank you, Neil Ashton and Prith Banerjee, for this insightful podcast! It was fascinating to hear Prith share his experiences across academia, startups, and corporates, and to explore how these different perspectives shape innovation. I also appreciated the discussion on opportunities and how balancing Horizon 3 and Horizon 1 activities can drive impact across startups, corporates, and academia.

I had the honor and privilege of being Juan's PhD student at Stanford in the late 90s and early 2000s. I was in NorCal recently and he graciously made himself available and gave me a demo of Luminary Cloud. My jaw was on the floor! I have been doing CFD on and off since 1997. I couldn't believe how fast, simple, well-thought and smooth Luminary Cloud was. I used to assume that one could either get fast results with limited fidelity by using the likes of OpenVSP (VSPAero) or FlightStream, or high fidelity results that were computationally slow and expensive using the likes of STAR-CCM+ (or God forbid Fluent and its painful workflow). Once I saw Juan's demo of Luminary Cloud it felt like one could have one's cake and eat it too. It's essentially a sleek and extremely high-fidelity RANS solver that runs as fast (or even faster than) OpenVSP, it is all cloud-based, it is unbelievably smooth with a gorgeous and modern GUI, it runs in a simple browser, and it's always up-to-date without the need to download and install GBs of software updates every few months. It's truly on a different level than anything else out there.

Thank you for posting this video Neil. I had the privilege and honor to learn from Prof. Jameson at Stanford during my PhD. In the late 90s I was looking for some reference paper and he reached into his drawer and gave me a copy of his 1984 "Transonic Flow Calculations" (Princeton University Report MAE 1651). It was no ordinary document. It was close to 100 pages long and held together by a thick binder clip. It turned out to be one of the best CFD references I used during my PhD. I also made extensive use of Tony's FLO103 and FLO107 codes to conduct my own PhD research. He has a truly unique mind and I don't think I ever saw him without a notepad, a pencil, and an eraser. Beyond his innumerable contributions to CFD and his accomplishments in aircraft analysis and design, Tony is always kind, caring, and curious. Back then when I was a student, it didn't matter whether one needed help with an obscure equation in some esoteric paper, or finding the best ergonomic office chairs for the entire lab at an unbeatable price, he always surprised you with his resourcefulness and caring. He also organized wonderful gatherings at his home with great food and great company that certainly made you feel like you belonged, especially if you were an international student far from home. A truly wonderful man! It is great to see his kind face and hear his voice in your video. It brings back many great memories...

Thanks for a great interview. Tony gave such an interesting insight into the Jaguar F1 saga.

excellent interview!!!

Thank your for your valuable thoughts and time! I have been informed about this AI for Science further. Foundation is more important as it could easily help people shift their field and pick up AI as a fundamental tool.

Thanks for an awesome podcast! Season 1 was a standout, especially with the in-depth discussions on CFD and machine learning. And, it's always great to hear what the legends thinks about doing PhD. I'm really looking forward to Season 2, especially with the focus on aerospace and F1-it’s exactly what I’ve been eager to explore!

Hi Neil. Great podcast. I didnt know it was on Spotify so ended up ”listening” through YTube. I actually searched on Spotify but didnt find it. I guess I wasn’t very thorough. But how about adding links to other platforms under the description of each video?

Great podcast once again.. very interesting points and questions discussed here. Would definitely recommend to all students and early career professionals in the AI + Science domain. I agree with the point that there is a need for all the respective professionals from AI and Science/Engineering domains to interact with each other and explore each other's ideas, for a more fruitful progress in this field. Neither one can thrive without the help of the other! That's what I feel. It is an exciting time to be living and working on these hard problems, especially with these new tools.

Loved the season 1, particularly listening to the backgrounds and stories of some of the legends in CFD and Machine Learning fields. Regarding the question of the medium of consumption, I personally prefer watching it over UA-cam, as it lets me feel like I am in the moment and more connected. Suggestions: May be bring some of the founders in the Space Tech or Deep Tech industries to have a perspective about entrepreneurship, and hopefully giving some advice to PhDs or postgraduates who want to embark on that path. Also, if you could touch upon the consultanting side of things, like how people from Science and Tech with good research/industry experience move into specialised consulting roles, that would also be interesting and helpful I guess. Nevertheless, looking forward to the next season 👍 Cheers😊

Thanks for the upload. I'm not convinced about what Professor Anima said at 50:00 regarding the medical catheter. At 44:00, she said that "we/our collaborators in fluid dynamics had a simple idea...of ridges, vortices....". So the originator is the Human. The design concepts generated can be and are generated by AI models. These designs are then validated after 3D printing and testing....etc. My point here is that AI models do not and will NEVER be able to come up with the idea in the first place. They don't understand and they don't reason. NEVER will. They can generate trillions of options to drown in. So yes it remains science fiction for AI models to produce by themselves something that works and is as expected. They can test this by asking their AI model to create a medical catheter that reduces/eliminates bacteria. My guess is it will provide zillions of options (including one to remove the tube altogether to achieve 0 bacteria flow) and then it remains up to the team to eliminate most and possibly test others but whichever way you do it the Human brain is a must in this loop and AI models are simply tools like computers, simulators...etc, granted advanced and very useful tools.

Thoroughly enjoyed the entire conversation. Thank you for putting this out.

Super! The 80-20 analogy is very interesting.

This is one of the gems amongst all the career podcast/advice videos, even a rare one focusing on career advice for PhDs. Loved your perspectives and arguments for each career path. I do agree with you (although I am also biased) that with the advent of AI and it's application on various domains and industries, the tech sector and the core industries both are looking for domain experts with AI skills to sort of have a balance in the team I guess. This hopefully continues so that PhD students like us get more opportunities to migrate to industries and the tech sector for better paid positions. Although, I do want to get your perspective Dr. Neil, on the case when someone, who has gained several years of experience in any Industry (space sector), and then comes back to pursue his PhD (with AI based research). What would you suggest for those people, who might be in their late 30s by the time they complete their PhD?

Thanks for sharing

Great chat Pat, loved hearing your story. I still remember you running your suspension program on punched cards at Huntington College in the early days at Royale. It has been a privilege to have worked for you over many years.

Fantastic discussion! Bringing lots food for thought. I am very happy to see long-form podcasts getting more and more into my favorite domains of science :)

Amazing! Commenting for reach

And then if you cant get enough of Max: ua-cam.com/video/HohUBYHO2dc/v-deo.html

Can't wait for the other episodes!

Super interesting topic!

Great job, Neil!

Very fascinating and informative sir, so let's use this technology for the betterment of the world, for instance diseases are a big one and I know if say cancer is cured, that would put alot of people out of work and that's what scares me. That if diseases get cured would the news ever see the light of day......

Sir, my department is Electrical engineering. I have completed Bsc in EEE. I want to pursue career in Renewable energy. Sir, Should i do a master's in renewable energy or i should go for technical learning or industry experience

Formula One is soft boy, rainbow 🌈 racing at its finest....What a disgrace of a sport.

Great interview! Very clever Mr. Symonds !

5min foreword %(

How “informed” are the VCs about the actual addressable market size of paying someone to do CFD?

Juan is the GOAT

Another gem of an interview. Juan is the GOAT!

Dear Dr.Ashton, I come from a background in aerospace and materials engineering at a BSc level and did my thesis on computational materials science. After this I have been working for a year in the industry while doing my MSc in applied mathematics focusing on optimization, inverse problems, HPC , CFD , FEM etc . My question now is ; would you recommend to get another year or two in the industry before going for a phd after my MSc or go straight to phd after msc ? I love fluid dynamics and control theory and in general everything that has to do with aerospace but since I am 26 , I think I may have missed the train when it comes to pursuing a phd..

Hi Neil! What a great suprise finding you in YT... Thank you for sharing!

This is immensely helpful to students. Thank you for sharing!

Very solid advice!!

Dear Dr. Ashton, saw your video from LinkedIn and jumped right in. As a PhD student near completion, this really gave me a good perspective about the differences. Thank you!

Really interesting podcast!

This is gold. Thank you for interviewing the legend himself.

Interesting. Thanks

Now this is a podcast series I'll definitely watch.

I had the pleasure of attending a lecture of Florian in Dresden. Truly inspirational - great job, Neil!