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  #51  
Old 12-13-2017, 11:22 AM
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If you're truly passionate about AI, then DO IT!
If money is a bigger factor than passion for the field then don't do it.
PhDs are the ones making big bucks (most likely) and do you really want to consider PhD now?
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  #52  
Old 12-13-2017, 12:44 PM
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Originally Posted by pinguino View Post
Georgia Tech? It's an online masters with almost no opportunities for networking. I would recommend an in-person program instead.
I've seen some anecdotal evidence that people out of that particular online masters do extremely well. It appears to be rigorous and has the attention of major tech firms.
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  #53  
Old 12-13-2017, 03:17 PM
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Originally Posted by pinguino View Post
Georgia Tech? It's an online masters with almost no opportunities for networking. I would recommend an in-person program instead.
I'm kind of considering U Chicago, but it's really expensive. If I take one class per year for 9 years, I could get it covered on the company's dime. I could maybe do four years and pay half. Then again, I haven't even applied yet which I will probably try to do in the not too distant future. We'll see.

GA tech is only $7k and is a well regarded program, so it's very tempting.
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Don't you even think about sending me your resume. I'll turn it into an origami boulder and return it to you.
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  #54  
Old 12-13-2017, 06:38 PM
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Originally Posted by Colonel Smoothie View Post
Yeah I dunno what is up with game AI's inability to form a meaningful army of any sort. Most of the games just send the units in one at a time in a suicide attack.
They are mostly dumb decision trees.

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Originally Posted by AbedNadir View Post
They chose a setting where the optimization function was tractable. That setting does not represent the entirety of the game.

-Riley
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  #55  
Old 12-13-2017, 10:21 PM
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Originally Posted by Colonel Smoothie View Post
I'm kind of considering U Chicago, but it's really expensive. If I take one class per year for 9 years, I could get it covered on the company's dime. I could maybe do four years and pay half. Then again, I haven't even applied yet which I will probably try to do in the not too distant future. We'll see.

GA tech is only $7k and is a well regarded program, so it's very tempting.
UChicago may be expensive, but you'd get the network and the brand recognition.
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  #56  
Old 12-13-2017, 10:47 PM
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Kristen Stewart already co-wrote an AI paper: http://www.actuarialoutpost.com/actu...d.php?t=318374

Step your game up. Marcus, PSP.
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  #57  
Old 12-14-2017, 12:26 AM
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Originally Posted by ronaldy27 View Post
If you're truly passionate about AI, then DO IT!
If money is a bigger factor than passion for the field then don't do it.
PhDs are the ones making big bucks (most likely) and do you really want to consider PhD now?
The ones making big bucks are established researchers who have published in important journals. We're talking about a small number of people. Don't expect big bucks just for getting a PhD.

Last edited by MathStatFin; 12-14-2017 at 12:30 AM..
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  #58  
Old 12-14-2017, 10:08 AM
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Originally Posted by MathStatFin View Post
The ones making big bucks are established researchers who have published in important journals. We're talking about a small number of people. Don't expect big bucks just for getting a PhD.
Further proves my point. I wouldn't waste my on doing this unless I was fully passionate about the field with almost no expectation to earn the big bucks.
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  #59  
Old 12-18-2017, 07:12 PM
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Yann LeCun, the director of Facebook AI Research and one of the world’s most prominent AI academics, told Business Insider last week that he employs certain tactics to get people to come and work for him.

"There’s various things ... but a lot of it is nurturing relationships with academic laboratories that have a track record of producing interesting students," said LeCun, who is also a professor at New York University.

He went on to say that allowing scientists to publish their work — something that Apple does not do — is also key. "It’s very important for a scientist because the currency of the career as a scientist is the intellectual impact," he said. "So you can’t tell people 'come work for us but you can’t tell people what you’re doing' because you basically ruin their career. That’s a big element, which I think we pioneered within this context."

LeCun could not be drawn on how much Facebook is willing to pay the top AI people who hold expertise in fields like machine learning, computer vision, mobile robotics, and computational neuroscience. However, online forums suggest the tech giants are willing to pay the best candidates salaries that run into the hundreds of thousands of dollars.

"[Salary] is important," said LeCun. "Particularly when there is a competitive situation with Microsoft, DeepMind, Google etc. But the other fundamentals have to be right. If they’re not right, people are just not even considering coming to work for you."

LeCun added that the FAIR group, who refer to themselves internally as the "FAIRies", is now about 75 people strong, with offices in New York, Palo Alto, Seattle, and Paris.

"The role of FAIR is to advance the science and the technology of AI and do experiments that demonstrate that technology for new applications like computer vision, dialogue systems, virtual assistants, speech recognition, natural language understanding, translation, things like that," he said.

"There’s a lot of basic science behind it which is not particularly geared towards an application; it’s more about making progress and understanding intelligence and AI.

"Then we work very closely with another group, which is about twice our size, called applied machine learning. They turn the science into visible technology and build platforms for the company that product groups can use to deploy AI-based services in the company."
http://uk.businessinsider.com/interv...epmind-2016-10

You can check the job openings for "applied machine learning" here

https://code.facebook.com/applied-machine-learning/

As an example

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We are looking for experienced Applied Researchers in Machine Learning and AI with strong software engineering skills. The Core Machine Learning Team is part of the Applied Machine Learning organization. The team carries out applied research in ML/AI and designs, develops and deploys state of the art ML/AI algorithms to the rest of Facebook. The team has developed and optimized various algorithms including Neural Networks, Boosted Decision Trees, Sparse Linear Models, and Deep Learning for several ranking teams including Ads, Feed, Search, Instagram and others.
Responsibilities

Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies
Combine broad and deep knowledge of relevant research domains with the ability to synthesize a wide range of requirements to make significant contributions to the feature roadmap for the applied machine learning platform
Apply expert coding skills to platform development projects in partnership with other engineers on ranking and infrastructure teams
Adapt machine learning and neural network algorithms and architectures to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)

Minimum Qualifications

MS degree in Computer Science or related quantitative field with 5+ years of relevant experience, or Ph.D degree in Computer Science or related quantitative field
Knowledge of machine learning and deep learning research.
Experience building systems based on machine learning and/or deep learning methods
Knowledge developing and debugging in C/C++, Java, and/or Scala
Experience with filesystems, server architectures, and distributed systems
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  #60  
Old 12-18-2017, 07:15 PM
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M.S. minimum

No surprise there.
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