learning


Will Robotics and AI Take Over The Jobs Of Millennials ?

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It is a revolution -or it will be- that would change the way we produce goods and the way these are distributed. This is particularly challenging for millennials and the younger generations, who will have to cope with a future technological world that challenge their work expectations and usual ways of doing and managing a business. To start with, the RSA mentioned that It is four years now since the University of Oxford published its landmark study predicting 35 percent of UK jobs could be made obsolete by new technology. That's why a balance between robotic implementation and job losses is a big issue that has to be tackled in a meanings of ways.


Introductory resources on AI safety research

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Potential risks from advanced artificial intelligence. A formalization of the reward misspecification problem in terms of true and corrupt reward, a proof that RL agents cannot overcome reward corruption, and a framework for giving the agent extra information to overcome reward corruption. This paper studies the interruptibility problem as a game between human and robot, and investigates which incentives the robot could have to allow itself to be switched off. A blog on designing safe, efficient AI systems (approval-directed agents, aligned reinforcement learning agents, etc).


Survey Results - Impact Of AI/Machine Learning On Workforce Capability - eLearning Industry

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The Automation era which has been called the'fourth industrial revolution' – is driving new ways of doing business often at the cost of traditional businesses. Is the fear of Artificial Intelligence/Machine Learning (AI/ML) surpassing human capability justified? Our recent survey on our webinar on Impact of Artificial Intelligence/Machine Learning on Workforce Capability highlights the effects of new and emerging technologies like AI/ML and what this will require of HR/L&D teams. We surveyed 65 Learning and Development and HR Professionals.


5 ways AI is being used in learning Sponge UK

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AI computer systems are able to perform tasks that would normally require human intelligence. Creating content from source material and subject matter experts is one of the time consuming parts of building digital learning. Content Technologies Inc. (CTI) are the world's largest publisher of higher education material, they use AI to create content based on all the articles and books that are available on a subject. Outsourcing the more straightforward preparation work gives skilled learning designers more time to create an engaging learning experience.


[Discussion] Choosing GPU for Machine/Deep Learning • r/MachineLearning

@machinelearnbot

Hello all, my first post here, nice to meet you! I'm working currently as a backend developer, but I have started to read about all this machine learning stuff - it is going crazy all around job markets - and was thinking about switching, as it should not be hard to learn the stuff (I've got math background). I've read that this kind of science use GPUs a lot to speed up the computations. Right now I am about to build a new home PC and I though I could use new GPU not only for games and cracking neighbours wifi password, but also to learn some ML/DL.


Getting ready for the future of work

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The Consortium for Advancing Adult Learning & Development (CAALD), a group of learning authorities whose members include researchers, corporate and nonprofit leaders, and McKinsey experts, recently met in Boston for the second year in a row to assess the state of the workplace and explore potential solutions. Bob Kegan, William and Miriam Meehan Research Professor in Adult Learning and Professional Development, Harvard Graduate School of Education: The number of employees who are operating in more nonstandard, complex jobs is going to increase, while less complex work is going to be increasingly automated. Bob Kegan: Work will increasingly be about adaptive challenges, the ones that artificial intelligence and robots will be less good at meeting. Tamara Ganc, chief learning officer, Vanguard Group: With our workforce now more dispersed, we're leveraging technology so people don't need to be physically together to still connect live.


[R] Cyclical Learning Rates for Training Neural Networks • r/MachineLearning

@machinelearnbot

Submission statement: Finding the correct learning rate is a pain. But this paper shows how to find reasonable learning rate bounds. Then you can cyclically vary your learning rate to getting better accuracy and often a decreasing training time. P.S There is a PR for this in keras-contrib.


5 Reasons Why Your Data Science Team Needs The DGX Station

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I immediately pulled a container and started work on a CNTK NCCL project, the next day pulled another container to work on a TF biomedical project. By running Nvidia Optix 5.0 on a DGX Station, content creators can significantly accelerate training, inference and rendering (meaning both AI and graphics tasks). Flexibility to do AI work at the desk, data center, or edge The Fastest Personal Supercomputer for Researchers and Data Scientists 15. www.nvidia.com/dgx-station However, for our current projects we need a compute server that we have exclusive access to." By running Nvidia Optix 5.0 on a DGX Station, content creators can significantly accelerate training, inference and rendering (meaning both AI and graphics tasks).


New algorithm studies gender bias in sports journalism • r/artificial

@machinelearnbot

Submissions should generally be about Artificial Intelligence and its applications. Submission's title should clearly indicate what the submission is about. Try to avoid posting submissions that seem like a self-advertisement. The topic of Artificial Intelligence is very broad and there are many good learning resources available on the internet and in print.


Top /r/MachineLearning Posts, August: Andrew Ng is back at it; Reinforcement Learning makes a splash; Fixing your ANN

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Testing our agents in games that are not specifically designed for AI research, and where humans play well, is crucial to benchmark agent performance. The bot learned the game from scratch by self-play, and does not use imitation learning or tree search. It beat players that many considered to be the absolute best at dota. However, there are cases where matchups do boil down to a 1v1 lane setup (at least for the first 10 minutes of the game), and the bot beat the players handily at it.