Thanks for busting these typical myths for pursuing PhD as an entry point to these distinguished roles. Your guidance was extremely helpful in making me decide the career i wanted to pursue.Kudos to you @Charles Weill
Well, let's get it right! 0) Most people in DeepMind, OpenAI have PhDs (I'm not talking about software engineering). 1) You must have at least a master's degree (example: like you)! Courses are unlikely to help without education ((( 2) there are very few people like Sara Hooker and Aleksa Gordić. PhD is a big plus!
I'm not sure if this really is the shortcut. I mean, when going for a research job without PhD, you essentially have to prove that you've had the experience that a general PhD holder has; and in my limited understanding of the world, that's quite a big deal.
Thanks for this very interesting and insightful video. My situation is as follows: I have a bachelors degree in CS (Germany‘s best university), focused especially at the end on deep learning and ML also in my thesis. Did some internship in deep learning research, am working for 4 years as a full time Senior Research Engineer in a mid-size tech company in ASR but here is the caveat. Since my daily work consists of more the development part of delivering ML models to production rather than the research part or publishing papers etc, what would you recommend me and how are my chances to Land a real research engineer/scientist job at an AI lab? So my plus is job experience in the field as well as quite some profound ML/Deep Learning theory knowledge in either NLP or Computer Vision, while my minus is lack of Masters and PhD and rusty coding (as my current role has a dedicated team for coding the pipeline for production)
Hi Charles, I would like to express my biggest thank to your great video. I am currently working as a research engineer in the field of autonomous driving. Nowadays, I begin to worry about having a valid publication in one of top-tier conferences might be a mandatory qualification in near future. I would like to know what is your opinion about this, and whether the publication is actually a 'must-to-have' to become a research engineer, according to your experience. Best regards!
@@user-ns4jr2qk5h thanks for you comment. When I got into my research role, it was 2017 and there was much less competition. I'm not sure what it's like now. You're best bet is to work as close to the researchers you want to work with as possible, and try to participate in the research community. Whether it means publishing or organizing workshops. Doing machine learning research in an industry lab is very competitive, so anything you can do to stand out will help. But don't let that stop you from trying and applying. Good luck!
Common paths in the US are to get a bachelor's degree in computer science then going to work in industry. Another option is to attend a coding boot camp.
I wanna do my Phd on deep learning. But i am confused about which part should be the best for research in deep learning recently. Can you suggest some of them which can be the field of deep learning research for Phd. Thanks in advance
Have you considered not doing a PhD? The field moves so fast that by the time you finish your PhD, Deep Learning will have changed a lot already. Consider working a few years in industry in a data-intensive role where you can apply computer vision or NLP first.
Hey charles... Thnx for the video.... As I am having very less knowledge in this field and wants to recontinue my studies as doing phd abroad so whats ur idea where should I learn with best guidance....
You might can you to upload a video about the salary of programation jobs and which are more needed for future? I thinking in ML or AI but i don´t know the salary, also which curriculum choose because looking choise for join to university Cheers From Chile
The best source of compensation information is www.levels.fyi/?compare=Google,Facebook,Microsoft&track=Software%20Engineer#. I can make a video about it too if you'd like. Compensation in the US is quite a bit higher than the rest of the world, but this site can give you an idea of what to expect.
Deep learning is a subset of machine learning that focuses on neural networks. While neural networks excel at many problems like computer vision and natural language processing, they aren't always the best solution for every problem. While you could start with Keras NN models to solve simple problems, you do want a more broad understanding of tools in machine learning so that you can handle those situations when they come up. As an engineer you have your toolbox, and neural networks are just one tool in that box. You want to have more tools than just that. As for minimum things to learn? Definitely learn basic linear algebra, tree-based methods, and common feature engineering techniques. Also learn Python; you're gonna need it!
really can recommend learning machine learning, since its often a lot easier and faster but not as powerful as deep learning You appriciate deeplearing more if you have a (small) ml background. You can start with randomForests classifiers and go from there. Best of luck
As far as I know, Apple and Facebook are the only companies doing the AI Residency in 2022. I'm no longer at Google, so I'm not sure, but I haven't heard anything.
@@chiragbansal9260 Yes I left Google for good now lol. I returned from my sabbatical, but could only manage 3 months before i felt the urge to leave and pursue my own adventure, to focus on TH-cam and microstartups. I recently built ytctr.com as my latest project. And thank you for your support!!
It will only impact then insofar as Deep Learning researchers will focus on building bigger and bigger overparameterized models. With GPT3 and Codex take their jobs? Highly unlikely.
Why not both? Most highly successful software engineers study CS. If you want to expand beyond making cookie-cutter applications, I highly recommend studying CS.
nhắc nhở cho bản thân rằng đây là lúc bản thân đang viết research paper về unaware transmitter to receiver in a semantic communication system. và các conferences mention trong đây là NeurlPS, ICML, ICLR,
I recommend 1) Andrew Ng's Stanford Machine Learning course on Coursera and 2) the Machine Learning Crash Course for learning TensorFlow. Great idea for a next video! [1] www.coursera.org/learn/machine-learning [2] developers.google.com/machine-learning/crash-course
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Thanks for busting these typical myths for pursuing PhD as an entry point to these distinguished roles. Your guidance was extremely helpful in making me decide the career i wanted to pursue.Kudos to you @Charles Weill
Well, let's get it right!
0) Most people in DeepMind, OpenAI have PhDs (I'm not talking about software engineering).
1) You must have at least a master's degree (example: like you)!
Courses are unlikely to help without education (((
2) there are very few people like Sara Hooker and Aleksa Gordić.
PhD is a big plus!
Extremely helpful to clarify the exact roles. I appreciate this content. Thx!
I love shortcuts, so I'll be doing these courses instead of a PhD! My parents would prefer the PhD status though
what shortcuts? PhD sure is long journey
I'm not sure if this really is the shortcut. I mean, when going for a research job without PhD, you essentially have to prove that you've had the experience that a general PhD holder has; and in my limited understanding of the world, that's quite a big deal.
@@psibarpsito prove it is really hard indeed
Man I love your lighting so much.
Thanks! It's the power of Aputure!
This is a great video!
Thanks John 🙏
I am doing my phd in Physics, now Iam really interested to transition into industry after phd.
Thanks for this very interesting and insightful video. My situation is as follows:
I have a bachelors degree in CS (Germany‘s best university), focused especially at the end on deep learning and ML also in my thesis. Did some internship in deep learning research, am working for 4 years as a full time Senior Research Engineer in a mid-size tech company in ASR but here is the caveat. Since my daily work consists of more the development part of delivering ML models to production rather than the research part or publishing papers etc, what would you recommend me and how are my chances to Land a real research engineer/scientist job at an AI lab?
So my plus is job experience in the field as well as quite some profound ML/Deep Learning theory knowledge in either NLP or Computer Vision, while my minus is lack of Masters and PhD and rusty coding (as my current role has a dedicated team for coding the pipeline for production)
Are you thinking about getting a PhD? Let me know why below. 👇
yes, I wanna do it because I love research and wanna do it in AI and Big Data.😁
Yes, to one day work on AGI
Hi Charles, I would like to express my biggest thank to your great video.
I am currently working as a research engineer in the field of autonomous driving.
Nowadays, I begin to worry about having a valid publication in one of top-tier conferences might be a mandatory qualification in near future.
I would like to know what is your opinion about this, and whether the publication is actually a 'must-to-have' to become a research engineer, according to your experience.
Best regards!
@@user-ns4jr2qk5h thanks for you comment. When I got into my research role, it was 2017 and there was much less competition. I'm not sure what it's like now. You're best bet is to work as close to the researchers you want to work with as possible, and try to participate in the research community. Whether it means publishing or organizing workshops. Doing machine learning research in an industry lab is very competitive, so anything you can do to stand out will help. But don't let that stop you from trying and applying. Good luck!
My question is, if you want to become a professional software engineer, where do you even start?
Common paths in the US are to get a bachelor's degree in computer science then going to work in industry. Another option is to attend a coding boot camp.
I wanna do my Phd on deep learning. But i am confused about which part should be the best for research in deep learning recently. Can you suggest some of them which can be the field of deep learning research for Phd. Thanks in advance
Have you considered not doing a PhD? The field moves so fast that by the time you finish your PhD, Deep Learning will have changed a lot already. Consider working a few years in industry in a data-intensive role where you can apply computer vision or NLP first.
Very informative brother
Hey charles... Thnx for the video.... As I am having very less knowledge in this field and wants to recontinue my studies as doing phd abroad so whats ur idea where should I learn with best guidance....
Thanks for the vid! Where can I get the T-Rex?
Thanks! It's from Lego Set 21320, but I love the look too.
sorry for off topic, as a kid i had the same dinosaur
Damn I just realized the internship I've had the last 5 months is falls into the research engineer category haha.
You might can you to upload a video about the salary of programation jobs and which are more needed for future? I thinking in ML or AI but i don´t know the salary, also which curriculum choose because looking choise for join to university
Cheers From Chile
The best source of compensation information is www.levels.fyi/?compare=Google,Facebook,Microsoft&track=Software%20Engineer#. I can make a video about it too if you'd like. Compensation in the US is quite a bit higher than the rest of the world, but this site can give you an idea of what to expect.
Good morning . I like tour video . is it possible to apply for a research scientiste with a Eng.D 's degree ( Doctorate of Engineering)
I want to become deep learning engineer.. Can I skip ml.. If no what are the minimum things to learn before diving into deep learning..
Deep learning is a subset of machine learning that focuses on neural networks. While neural networks excel at many problems like computer vision and natural language processing, they aren't always the best solution for every problem. While you could start with Keras NN models to solve simple problems, you do want a more broad understanding of tools in machine learning so that you can handle those situations when they come up. As an engineer you have your toolbox, and neural networks are just one tool in that box. You want to have more tools than just that.
As for minimum things to learn? Definitely learn basic linear algebra, tree-based methods, and common feature engineering techniques. Also learn Python; you're gonna need it!
@@CharlesWeill thank you so much..
really can recommend learning machine learning, since its often a lot easier and faster but not as powerful as deep learning
You appriciate deeplearing more if you have a (small) ml background. You can start with randomForests classifiers and go from there. Best of luck
Is the AI residency program still running? There wasn't one last year due to COVID and there is no residency information for 2022.
As far as I know, Apple and Facebook are the only companies doing the AI Residency in 2022. I'm no longer at Google, so I'm not sure, but I haven't heard anything.
@@CharlesWeill Aah go it! Thanks a lot! When did you leave google? weren’t you on a sabbatical?
Love the content btw, keep going
@@chiragbansal9260 Yes I left Google for good now lol. I returned from my sabbatical, but could only manage 3 months before i felt the urge to leave and pursue my own adventure, to focus on TH-cam and microstartups. I recently built ytctr.com as my latest project.
And thank you for your support!!
do you think gpt 3 and codex affect AI researchers at all? it's worth it? please answer me
It will only impact then insofar as Deep Learning researchers will focus on building bigger and bigger overparameterized models. With GPT3 and Codex take their jobs? Highly unlikely.
So i am software engineer and i wanna switch to ai research engineer.and i am doing a course also...so i can get into deepmind right?
Should I study CS or go to software engineer?
Why not both? Most highly successful software engineers study CS. If you want to expand beyond making cookie-cutter applications, I highly recommend studying CS.
@@CharlesWeill To become an ai expert
nhắc nhở cho bản thân rằng đây là lúc bản thân đang viết research paper về unaware transmitter to receiver in a semantic communication system. và các conferences mention trong đây là NeurlPS, ICML, ICLR,
Which introductory machine learning courses would you recommend? Will this be the topic of a follow-up video? :P
I recommend 1) Andrew Ng's Stanford Machine Learning course on Coursera and 2) the Machine Learning Crash Course for learning TensorFlow. Great idea for a next video!
[1] www.coursera.org/learn/machine-learning
[2] developers.google.com/machine-learning/crash-course