Kian Katanforoosh

Deep learning is a subset of what we call Artificial Intelligence. I would say that AI is about developing machines (computers, smartphones, websites, robots) able to perform tasks that normally require human intelligence, thanks to algorithms mixing mathematics and computer science. It can be seen as a science of automation that can affect many industries. It is like a science of automation that applies to any type of industry.
Deep learning is a family of algorithms in artificial intelligence inspired by the interactions between neurons in the human brain, namely « neural networks ». It has recently boomed after outstanding results have been observed in applications such as image detection, natural language processing and speech recognition, sometimes exceeding the human-level performance.

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  1. shinichi Post author

    “AI Will Revolutionize The Way We Live” Interview With Kian Katanforoosh From Stanford University

    unilance

    https://blog.unilance.co/ai-will-revolutionize-the-way-we-live/

    Today, we visited Kian Katanforoosh in the Silicon Valley , researcher, entrepreneur and student from Stanford University. He gave us some insightful information about Artificial Intelligence, Coursera and the growing interest for Unilance in the US.

    1) Hello Kian, can you please introduce yourself to the community?

    Hi everyone, I am French-Iranian who loves soccer and French rap. I have recently graduated from Stanford University and I am currently working with my advisor Andrew Ng in his new venture called deeplearning.ai. You might have heard about our 5-course sequence « Deep Learning Specialization » announced on Coursera a couple of weeks ago.

    2) Tell us about about your journey, from the suburbs of Paris to Stanford University

    I have always wanted to be a soccer player or rapper but my career did not take-off yet… (I still dream on becoming the next drake or Akhenaton, please stay tuned. Concerning my soccer star career, I am little bit worried, especially since I saw the 18-year-old forward Kylian Mbappé ). As an ersatz, I did some mathematics and then attended French engineering school (CentraleSupelec formerly Ecole Centrale Paris) to finally end up at Stanford. I started working with the cryptography group before being joining the Artificial Intelligence (A.I) department where I met my advisor: Andrew Ng who told me about some of his new ideas.


    3) Your current big project is related to something called « Deep Learning »,could you tell us more about this field?

    Deep learning is a subset of what we call Artificial Intelligence. I would say that AI is about developing machines (computers, smartphones, websites, robots) able to perform tasks that normally require human intelligence, thanks to algorithms mixing mathematics and computer science. It can be seen as a science of automation that can affect many industries. It is like a science of automation that applies to any type of industry.

    Deep learning is a family of algorithms in artificial intelligence inspired by the interactions between neurons in the human brain, namely « neural networks ». It has recently boomed after outstanding results have been observed in applications such as image detection, natural language processing and speech recognition, sometimes exceeding the human-level performance.

    4) Therefore, today you gives classes related to that ?

    With Andrew Ng and a friend of mine, Younes Bensouda Mourri, we built the series of deep learning courses available on Coursera. The demand for these skills is incredibly high today. As Andrew often says, we need much more data scientists and AI experts in order to build an « AI-powered society » with access to low-cost resources, quality education for all or cheap medical care. The first learners who master these skills will have an advantage on the job market as companies will be hiring for AI talents.

    https://cdn-images-1.medium.com/max/1600/1*5BFz2EhJYA9Cd4fBdOmFmg.jpeg

     

    5) I saw that you are part of a startup « (Asker or Deeplearning) », what is it?

    When I was studying in France, I launched an educational start-up called Asker with some friends. We had a lot of fun and started the first partnerships, before deciding to resell our shares to a French entity. Today, Asker is called Daskit and no longer belongs to me, although I try to keep in touch from far away. Deeplearning.ai is a different story to write. One of our main goals is to make the field evolve by democratising AI, and providing comprehensive AI education for all. I am really grateful to Andrew and learn from him every single day

    6) You also worked for Ebay, how is the silicon valley atmosphere?

    It is one of the historical companies of the Silicon Valley, launched by a Franco-Iranian (Pierre Omidyar). I enjoyed it a lot, it was my first experience in a large company’s AI research lab. It was an opportunity for me to meet and be mentored by experts from a specific industry. A great place to learn and to acquire industry-level knowledge in an area.

    7) What is the future for you now?

    Nothing is certain. I still hope to become a rap superstar (I am actually working on a song). But if it does not work, I stay in Silicon Valley for now, it has been a great environment to learn so far.

    8) Any pieces of advice for all those dreaming of studying at Stanford and embarking on Deep Learning / AI?

    I am probably not qualified to give advice, but I would say that the important thing is not to study at Stanford or another top-tier university. Actually, the future of education does not necessarily happen in universities. There is high-quality open-source material today on almost any subject. The only thing we need is motivation and one can get it either with passion or with a good working environment (find some friends!). Thus, I believe a good strategy to break into AI ​​would be:


    1. Learn how to code AI algorithms using open-source resources (Machine Learning or Deep Learning on Coursera for example ). If you are not a student, create a commodious working environment with a group of friends.

    2. Find an area that you are passionate about motivated and apply what you have learned. Being a field-expert gives you a competitive advantage and much more intuition when applying AI to your field.

    I think that with motivation and 6 months of work, one can from high-school maths level acquire the knowledge to apply deep learning in our society.

    9) What do you think about being a student/freelance?
    I am very much in favor of being a student/freelance. I think that the vast majority of French schools are not sufficiently involved. In Sciences, learning the theory can be very useful, I observed it in the US where our level in theoretical mathematics and physics allows us to learn quickly and formulate complex problems. On the other hand, the students here (Stanford) know how to build things, they know how to create a product from A to Z in a very short amount of time. That is a big advantage.

    Freelancing can allow students to deal with concrete hands-on problems during their studies. However, you have to choose your projects carefully, in order to acquire skills valuable skills. For companies, I think freelance with students is a way to outsource tasks at reasonable costs and also test the performance of a student for future hiring.

    10) What about Unilance in your university? ⬅
    I know Unilance has raised a huge interest in the student circles. The idea of collaborating with foreign companies on tasks related to your department is really appreciated. Moreover, it can help students pay back their loans or living expenses. I see a lot of interest coming from students here towards Unilance and it is a good thing

    11) Last question, your favorite entrepreneur and why?
    It may seem biased, but I will say Andrew Ng . Beyond being a researcher, he is an entrepreneur that had a huge impact on the lives of millions of people around the world. By launching Coursera, he has given access to high-quality education and cutting-edge education to numbers od people around the world .

    We are humbled to receive feedback from people who have decided to redirect their careers or who have found a job after taking our course. I think there is still much to be done, and Andrew Ng has some great ideas for deeplearning.ai.
    I also closely follow Xavier Niel’s educational projects, and I often agree with his views in terms of education.

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