notes-computer-ai-aiNotes

Links and books

• General
  • http://www.amazon.com/Artificial-Intelligence-Elaine-Rich/dp/0070522634/ref=sr_1_9?s=books&ie=UTF8&qid=1359272210&sr=1-9&keywords=knight+artificial+intelligence Really good book on the symbolic/GOFAI (good old fashioned A.I) school. I've read a good bit of it.
  • http://www.amazon.com/Artificial-Intelligence-Modern-Approach-3rd/dp/0136042597/ref=sr_1_1?s=books&ie=UTF8&qid=1359272176&sr=1-1&keywords=norvig The most popular intro AI textbook. I haven't read it yet.
• Machine learning
  • Andrew Ng's course handouts: http://cs229.stanford.edu/materials.html . Haven't read it but it looks really good
  • http://www-stat.stanford.edu/~tibs/ElemStatLearn/ Hastie, Tibshirani, Friedman. Available online for free. Haven't read it but it looks good.
  • http://www.amazon.com/Elements-Machine-Learning-Morgan-Kaufmann/dp/1558603018/ref=sr_tc_2_1?ie=UTF8&qid=1359272282&sr=1-2-ent Old but good book on machine learning. I've read a good bit of it.
  • http://robotics.stanford.edu/~nilsson/mlbook.html draft of an old textbook on machine learning. Available online for free (or you can buy a hardcopy of Nilsson's book). I haven't read it yet.
  • Tom Mitchell's 1997 Machine Learning book. Really good. http://www.cs.cmu.edu/~tom/mlbook.html http://www.amazon.com/exec/obidos/ISBN=0070428077/4660-3450753-250555
  • Reinforcement learning
    • http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html Sutton and Barto's book, available online for free. Haven't read it but it looks good.
  • Graphical models / bayes nets
    • http://bndg.cs.aau.dk/ Jensen and Nielsen's book. I haven't read it but it looks good.
  • Other lists
    • http://metaoptimize.com/qa/questions/186/good-freely-available-textbooks-on-machine-learning

Survey Books

• http://artint.info/html/ArtInt.html
• https://en.wikipedia.org/wiki/Outline_of_artificial_intelligence

other toread

• forthcoming book "Neural Networks and Deep Learning".

http://www.amazon.com/What-Computers-Still-Cant-Artificial/dp/0262540673

Surfaces and Essences

Gödel, Escher, Bach: An Eternal Golden Braid

I Am a Strange Loop

Robert Rosen's Life Itself and Essays on Life Itself

Creative Analogies

http://www.tandfonline.com/toc/heco20/24/1#.Umy9Tnim2Kh

Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought

http://cogsys.org/ http://www.agi-conference.org/

" Instead of Hofstadter's GEB, read some of his papers, e.g., "Analogy as the Core of Cognition" http://prelectur.stanford.edu/lecturers/hofstadter/analogy.h...

But there are others who have focused longer on analogy, e.g., George Lakoff:

"Metaphors we Live by"

http://www.amazon.com/Metaphors-We-Live-George-Lakoff/dp/022...

"Where Mathematics Come From: How The Embodied Mind Brings Mathematics Into Being":

http://www.amazon.com/Where-Mathematics-Come-Embodied-Brings...

"Women, Fire, and Dangerous Things"

http://www.amazon.com/Women-Fire-Dangerous-Things-Lakoff/dp/... " http://prelectur.stanford.edu/lecturers/hofstadter/analogy.html http://www.amazon.com/Metaphors-We-Live-George-Lakoff/dp/0226468011/ref=sr_1_1?ie=UTF8&qid=1382636169&sr=8-1&keywords=by+george+lakoff http://www.amazon.com/Where-Mathematics-Come-Embodied-Brings/dp/0465037712/ref=sr_1_1?s=books&ie=UTF8&qid=1382636378&sr=1-1&keywords=Where+Mathematics+Come+From%3A+How+The+Embodied+Mind+Brings+Mathematics+Into+Being http://www.amazon.com/Women-Fire-Dangerous-Things-Lakoff/dp/B0044SLTZE/ref=sr_1_2?ie=UTF8&qid=1382636599&sr=8-2&keywords=Women%2C+Fire%2C+and+Dangerous+Things

Mind's I

zvanness 10 hours ago

I'm not so sure their technology is as futuristic as everyone thinks it is. If I had to take an educated guess, I would say it's some powerful AI that makes their knowledge graph smarter. Currently Google's Knowledge Graph uses more structured data sets and depends on a mechanism like this: http://www.zachvanness.com/nanobird_relevancy_engine.pdf

But the real challenge is to make the knowledge graph update in real time and take meaning from something as unstructured as a blog post or an email. And to do something like that requires some really unique AI.

--mjn - I totally agree!

reply

mjn 10 hours ago

Oh, I'm decidedly agnostic on whether it really is futuristic AI. Just there is some buzz around it, and some of the people involved in it are definitely legit, and have also involved themselves in the "AGI" community, which leads to such speculation (which they've pretty deliberately cultivated). That doesn't prove they've Solved AI for any sci-fi-ish notion of Solved AI. They could just have some good but in the big picture fairly modest knowledge-graph tech, or they could even have not-that-good knowledge-graph tech with great PR! Hard to say without knowing any details.

reply

nl 2 hours ago

Deep learning is pretty impressive as a supplement to knowledge engineering approaches.

Google's Deep Learning team were the people who developed the alogithm that discovered cats on YouTube? (without training). Presumably this team had something that impressed them.

The weakness to knowledge engineering approaches is that they tend to be fragile - they break badly with small holes in recorded knowledge. The IBM Watson team has a great video that showed how the different definitions of "fluid" and "liquid" meant a correct answer would have been missed if evidence collected in the answer verification phase of the DeepQA? pipeline (no relation to Deep Learning) hadn't overridden it.

Edit: Your(?) paper on your (?) relevancy engine is interesting. It seems like an application of skip-grams (which, ironically enough are heavily used by the DeepQA? answer verification phase mentioned above).

reply

gdahl 6 hours ago

There were a lot of pros a DeepMind?. For example: Volodymyr Mnih, Andriy Mnih, Alex Graves, Koray Kavukcuoglu, Karol Gregor, Guillaume Desjardins, David Silver, and a bunch more I am forgetting.

mdeg 6 hours ago

So, Google's list so far:

• Some top ML talent: Geoffrey Hinton, Sebastian Thrun, Peter Norvig, Jeff Dean, Andrew Ng.
• One of D-Wave's quantum computers to establish their 'Quantum Artificial Intelligence Lab'.
• Creepy robot maker Boston Dynamics.
• A stack of other robotics companies: Schaft.inc, Industrial Perception, Redwood Robotics, Meka Robotics, Molomni, Bot & Dolly, Autofuss.
• DeepMind?, obviously.

Am I missing any?

reply

andyjohnson0 2 hours ago

Ray Kurzweil

reply

raldi 5 hours ago

Zagat

reply

swalsh 2 hours ago