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As a full-time AI researcher myself, I'd say that a PhD in machine learning would certainly be one useful option. However, in order make much-needed progress, AI needs avoid falling into the trap of thinking that currently fashionable methods are any kind of 'silver bullet'. There's some danger that a PhD that heads straight into (say) some sub-sub-sub area ...


8

Good Mathematics Foundation Begin by ensuring full competency with intermediate algebra and some other foundations of calculus and discrete math, including the terminology and basic concepts within these topics. Infinite series Logical proofs Linear algebra and matrices Analytic geometry, especially the distinction between local and global extremes (minima ...


7

Here are my suggestions Her, the AI part (movie spoiler): Ex Machina the AI part (movie spoiler): Eagle Eye, the AI part (movie spoiler): Big Hero 6, the AI part (movie spoiler):


6

EE Math Refresh AI is an interdisciplinary field. You can begin by ensuring you are fresh in the mathematics you've already taken. You may already have all the books from your BS and MS. Infinite series Logical proofs Linear algebra and matrices Analytic geometry, especially the distinction between local and global extremes (minima and maxima), saddle ...


6

I work as a professor, and recently designed the mathematics requirements for a new AI major, in consultation with many of my colleagues at other institutions. The other answers, particularly @FauChrisian's do a good job of cataloging all the specific topics that might be useful somewhere in AI, but not all of them are equally useful for understanding core ...


5

Research on AI seems to be getting wider these days (2016). First, "obvious" few departments (no order): Computer Science (e.g. computation theory, algorithms): AI researchers there assume that intelligence is a kind of computation, under various forms (e.g. a neural network, a logic system). Software Engineering: Assuming we find a good model for AI, how ...


5

2001 (1968) HAL 9000 is a great example of an artificial general intelligence that goes astray, where the humans don't understand the reasoning process as values dis-align. (This is a nod to Asimov in the sense of humans not understanding the implications of a logical framework. Marvin Minsky was an adviser on the film.) BladeRunner (1982) The critical ...


4

I cannot comment about the process for AI for academia. I can compare AI for competitions and AI for business. To clarify whatever I say is about ML not any other AI techniques. The process might be different for other techniques. But most of things that I say are general enough that I am assuming should still apply. The main difference that I saw while ...


3

Just A Rather Very Intelligent System (J.A.R.V.I.S.) in Iron Man (and related films, such as The Avengers) is something (a personal assistant) that people are already trying to develop, so JARVIS is a quite realistic artificial intelligence. Examples of existing personal assistants are Google Assistant (integrated into Google Home devices), Cortana, Siri and ...


3

Methodology bias is difficult to avoid, since we can only see the methodologies that have been developed to proof of concept. Time is a continuous horizon of bias breaking in research. ARPAnet, which is now the Internet, was designed to reduce the bias by narrowing the gap between research laboratories, but it does not bridge across time. Luger's book is ...


3

I've done a masters in AI and graduated almost a year ago. In my experience, it was definitely worth it. Completing any computer-oriented degree is bound to attract employers (or rather recruiters/headhunters working for the employers) that will want to hire you. There's is currently a higher demand than an offer. With that being said, do you wish to work ...


3

Welcome to AI.SE @Romain B. I have several undergraduates working on multiagent deep RL problems for their theses, but most of them have been working for 8-9 months. 2 might be a stretch. Good multiagent deep RL problems for a bachelor's thesis might look something like: Pick an older video game, which has been studied using Deep RL, but not in depth. ...


2

Here are the best movies about artificial intelligence 2001: A Space Odyssey (1968) Colossus: The Forbin Project (1970) Blade Runner (1982) A.I. Artificial Intelligence (2001) Her (2013)


2

A great movie to watch would be A.I. Artificial Intelligence, which is a sort of modern retelling of Pinocchio. Another good AI movie where the main character is a robot would be Bicentennial Man, based on Isaac Asimov's the positronic man.


2

The Machine, which came out a year before Ex-Machina, features topics such as ethics, AI testing (specifically, the Turing test), artificial consciousness, emotional intelligence, artificial general intelligence, super-intelligence, the singularity and AI safety. An old but milestone movie is Wargames, which will likely get you some points for digging back ...


2

Transcendence was a a pretty good look at a super-intelligent AI.


2

As far as simple algorithms like Gradient Descent are concerned, you need to have a good grasp of partial derivatives. Especially if you want to implement neural networks. Also most algorithms are vectorised to improve computing speed and so you need to be comfortable with matrix math. This involves being really quick and comfy with dimensions of matrices, ...


2

There are a few universities that offer MSc in AI. The highest ranked of these include: Ulretch University which promises to empower students with the skills to carry out AI research in academic or R&D environments and to identify how AI techniques can provide intelligent solutions to IT problems in companies and organisations. KU Leuven which is ...


2

If you aren't looking to be accredited, here are some good options: Stanford Berkeley University of Toronto metacademy If the links are dead, a google search on the relavant course code should yield results. If you are looking for accreditation, then you might want to try: Coursera But note that in my opinion, the class materials from the links above ...


2

Understanding a human brain fully, how hippocampus and neocortex works would surely help AI enthusiasts to make better AI algorithms with superior memory, ability to learn and finding what precisely intelligence, feelings and conciousness are by itself. The AI looks at psysiological and anatomical data as a source of suggestions regarding possible mechanisms ...


2

Determining the ROI (return on investment) of a degree is a complicated projection depending on a few main factors. How much will the tuition and fees cost? Will the student endure the grueling parallel work and study? If not, how much will the loss of income and potential debt affect the student's accumulation of assets by retirement? What will the masters ...


1

I would like to mention WOPR from War Games, maybe is an old movie for your students, but it is a more realistic IA centered around the problem of playing board games (if you exclude the part about deciding that a game is not worth the time). Also I remember an artificial assistant in "The Time machine" that was more convincing than J.A.R.V.I.S because it ...


1

Not very sure about the AI in competitions, as I have not taken part in any competitive competitions. On comparing AI in Academia and Industry, the biggest difference is probably freedom. In academia, considering a research project or so, a large number of experiments and trying new things are encouraged. New learnings are heeded to, and it usually ...


1

This is a very vague question as well as a really vague statement. Deciding on your career based on "one person who did x said y..." shouldn't be a sole guide to anything in life. Even gathering a multitude of opinions would be useless if your sample is biased on either opinion, good or bad. Personally if I had the rep I would flag the question as it is also ...


1

First of all, it is imperative that you have good grades. So work on that. Mathematics is considered as appropriate background for an AI masters so having good grades will get you on the entry radar! Then, since you are on your last year you could select an elective related to AI or even better choose a final project on AI, if available on your course ...


1

Well, mathematics is a very strong field in AI as that is what most AI algorithms revolve around. You only need to learn how to write code (Mostly python or c++, python is easier to learn in my opinion) and how to write mathematical equations in code. Once you have that down it should be enough but I don't how courses work at yours as I know our University ...


1

As student and TA, I found that: Mathematical foundations, or at very least pointers on where to get them. Some students might find this not useful, but structuring the functioning of models in terms of mathematical constructs will help the student in later phases. Computational resources as Google colab, Kaggle kernels and the likes. Some people don't ...


1

Step one, engage with the seniors. Since, self-driving is a complex task the seniors are (with high probability) using a pipelined system with multiple modules. Ask them for a ceiling analysis. If they do not know what that is (you've already wowed them). Assuming that they know what ceiling analysis is, they can provide you with one for one of their ...


1

What are the top contributions from neuroscience to artificial intelligence and vice versa? Here is a glimpse of one of my favorite companies doing it big in artificial intelligence field,inline with its contribution to neuroscience;otherwise. DeepMind It's goal is to build a general AI systems with the ability to think,reasoning and learn flexibility ...


1

You can look into applying on-policy learning in environments generated via GAN architectures. There’s work on “imagination augmented agents”, where environment information from rollouts are passed into a policy learning network. https://arxiv.org/abs/1802.03006 This work unrolls the model in latent space, but is in the same vein of passing environment ...


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