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PhD student
1 year ago
ArchivedStickied postModerator of r/artificial

/r/artificial is the largest subreddit dedicated to all issues related to Artificial Intelligence or AI. What does that mean? That is actually a tricky question, as the definition of AI is a topic of hot debate among people both inside and outside of the field. Broadly speaking, it is about machines that behave intelligently in some way, but this means different things to different people.

Most notably, there is the distinction between machines that are (at least) as intelligent as humans (artificial general intelligence / AGI) and machines that are capable of performing one task very well that would require intelligence if a human did it (narrow AI / ANI). When people outside the field think of "AI", they often think of AGI and possibly very humanlike AGI, often inspired by sci-fi books, shows and movies. However, today we are unable to create such systems. What we can do is create magnificently useful software and robotic tools, and that is what most of the professional AI field does. So to most professionals "AI" tends to refer to ANI. This can lead to a lot of confusion.

Another important thing to realize is that AI is an incredibly broad field that touches on Computer Science, Cognitive Science, Mathematics, Philosophy, Neuroscience, Linguistics and many others, and includes many subfields like Machine Learning, Robotics, Natural Language Processing, Computer Vision, Knowledge-Based Systems, Evolutionary Algorithms, Search and Planning. Many of these have subreddits dedicated to them as well (see this list). /r/artificial is about all of these things. For instance, posts about computer vision are very welcome here, although the poster should realize people here will have a broader AI background than the specialists on /r/computervision, which might affect the kind of discussion that emerges.

On /r/artificial we welcome anyone who is interested in intelligent and respectful discussion of AI in any form. We want to provide a low barrier of entry, specifically because there are so many misconceptions about AI. We do ask that you put in a little effort before posting. Check out our burgeoning wiki and Wikipedia's article on AI to appreciate the breadth of the field. When you ask a question, do so intelligently. When you post a story, prefer balanced discussion to clickbait, and please seek out the original source (many website just copy each others' stories without attribution). When you post a paper, please link to where it can be (legally) obtained for free and ideally to the landing page rather than directly to a PDF. Also consider jumpstarting the discussion with your own insights, questions, additional links and/or a short summary for people outside the niche the article was written for.

Please use this thread for suggestions, comments and questions about this subreddit.

Let's make this a great place for discussing artificial intelligence!


I think it's safe to say that AI is (or at least will be) a better driver than most, if not all, humans.

You can imagine an autonomous driving system to be much more capable of safely navigating a vehicle closer to the limits of its performance, taking into account all factors like speed, tire type and wear, weight of vehicle, roadway conditions, in addition to more precise command over the controls and better reflex and response time.

That said, perhaps driving behavior would not be limited so much by safety standards but rather personal comfort where you can put your car in different driving modes based on whether you're in the mood to be driven aggressively to get to your destination faster (or just for fun).

Do you think it would it be more the norm for autonomous vehicles to drive slowly and calmly or would the autonomous vehicle revolution actually result in increased speed limits and more (safe) aggressive driving?


Ahoy! Wil jij kans maken op een duurzame, ontdekkingsreis naar Chili?


Just saw this awesome documentary Do you Trust this Computer.

There was a part in the documentary about ai becoming self aware (due to self learning?)

Watch at 52:20 (the 4 legged spider robot thing).

"Watching the neural network, the robot started to track our faces as we moved around. The spooky thing about this is that we never trained the system to recognize faces, but somehow it learned to do that. There is something else going on here, it's not just programming."

How is this possible? How can a program self program itself for certain criteria it was never programmed to do? Are robots and ai like this really becoming self aware? How does ai learn to beat games it's never been taught at? I know it has something to do with continuous data?

Thought the AI experts here might be able to clarify this issue of ai becoming self aware?

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Deep learning all about neural networks and Machine learning is all about few algorithms and techniques. I was looking for how and in which topics people used to do their research before the ML and DL came into trend. Now a days people only think AI is all about Machine learning and Deep learning !!!!!!


For some time I work on MindForger, which is a knowledge management tool. Users work with (personal) remarks, research papers/logs, how-tos, documentations etc. My goal is to make it "smarter" than usual apps in this domain.

I use Support Vector Machine (SVM) to perform named-entity recognition (via MITIE/dlib). However, a default model for recognition of person/location/organization names is relatively big (~350MB) and it loads ~10s. Recognition itself is fast, but it has relatively high number of false positives.

I'm looking for an advice based on real use of NER: Should I go with SVMs (tune model, eliminate false positives using pre/post processing, etc.) or should I rather use RNNs (recurrent neural networks @ LSTM/GRU/...)?

I have a number of use cases for NER in MindForger. In case of common entities (person/organization/... names) big data sets are available, however, in case of other entity types I may have as less as <10k examples.

What's your NER suggestion for a desktop application? I look forward a method which has better results in general (and it's worth to invest time in tuning its model) and is reasonably fast (initialization and recognition).


Join to building Global Robot Economics.


Hi! Me and some friends are building a website, that can be accessed here: It intends to make Artificial Intelligence experimentation on games more fast, intuitive and fun.

We think that we have a very early alpha version of it and we would like to share with you and receive some feedback from the community, not only about its current state but also opinions about where we can go next.

We know that the app at the current state is really simple but we are trying to see if the concept is viable and if it makes sense to keep going this way.

All this is, at the moment, just a study/experiment about how we can integrate AI with games in the user's browser in a intuitive and fast way. Our future goal is to make this a tool where people learn more about AI and its applications while also creating a good platform to experiment different AI techniques with different games/puzzles.

The project is 100% open source and all the code can be found here: and here

If you have any interest in contributing to the project we would be more than happy to have you aboard. You can contact us at Github or send me a PM.

Thank you!

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