Stanley & Lehman – Why Greatness Cannot Be Planned

Fascinating insights by Computer Science / Artificial Intelligence profs …

https://amzn.to/2DlhLnX

some have summarized their insights by writing: “only by doing activities that fulfill our curiosity without any pre-defined objectives, true creativity can be unleashed. They call this the ‘Myth of the Objective’: Objectives are well and good when they are sufficiently modest … In fact, objectives actually become obstacles towards more exciting achievements, like those involving discovery, creativity, invention, or innovation—or even achieving true happiness… the truest path to “blue sky” discovery or to fulfill boundless ambition, is to have no objective at all.”

some of Stanley’s and Lehmans insights:

 

  • “The flash of insight is seeing the bridge to the next stepping stone by building from the old ones. ”

 

  • “[Picbreeder] is just one example of a fascinating class of phenomena that we might call non-objective search processes, or perhaps stepping stone collectors. The prolific creativity of these kinds of processes is difficult to overstate”

 

  • “ measuring success against the objective is likely to lead you on the wrong path in all sorts of situations”

 

  • “You can’t evolve intelligence in a Petri dish based on measuring intelligence. You can’t build a computer simply through determination and intellect—you need the stepping stones. ”

 

  • “ambitious objectives are the interesting ones, and the idea that the best way to achieve them is by ignoring them flies in the face of common intuition and conventional wisdom. More deeply it suggests that something is wrong at the heart of search. ”

 

 

I find their books inspiring and insightful. Reframing questions and providing different lines of attack on AI and Search Optimization to Ambitious Goals …

 

 

 

 

Wikidata Query Service is incredibly POWERFUL

checkout out at https://query.wikidata.org

I was just looking at what it had to say about search engines … it quickly returned:

doesn’t look like much , but it is.
https://query.wikidata.org/embed.html#SELECT%20%3Fsearch_engine%20%3Fsearch_engineLabel%20WHERE%20%7B%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%20%20%3Fsearch_engine%20wdt%3AP31%20wd%3AQ19541.%7DLIMIT%20100

artificial intelligence, natural stupidity.

according to popular legends and urban myths … Amos Tversky is said to have said …

My colleagues, they study artificial intelligence; me, I study natural stupidity.

this, from CoEvolving Innovations which seems like a fascinating resource.

The blog entry there talks about Daniel Kahneman  and Amos Tversky.

The topic is fascinating.  The question of how intelligence and stupidity are related is fascinating.

There’s also a reference to Daniel Kahneman, Paul Slovic, and Amos Tversky book Judgment under uncertainty: Heuristics and biases,  that I now feel compelled to investigate

interesting factoid …Kahneman  was awarded the 2002 Nobel Prize in economic sciences  despite being a psychologist, not an economist.  Which goes to show you … that Forrest Gump’s Mom was right  Life is like a box of chocolates. You never know what you’re gonna get.”

Natural Question Answering Research at Google

just announce on the Google AI Blog …/

Natural Questions: a New Corpus and Challenge for Question Answering Research

 

this is pretty exciting …hope to this grow and have fruitful implementation on the Google search engine.

this is what the Google AI researchers are saying

…. there are currently no large, publicly available sources of naturally occurring questions (i.e. questions asked by a person seeking information) and answers that can be used to train and evaluate QA models. This is because assembling a high-quality dataset for question answering requires a large source of real questions and significant human effort in finding correct answers.

To help spur research advances in QA, we are excited to announce Natural Questions (NQ), a new, large-scale corpus for training and evaluating open-domain question answering systems, and the first to replicate the end-to-end process in which people find answers to questions. NQ is large, consisting of 300,000 naturally occurring questions, along with human annotated answers from Wikipedia pages, to be used in training QA systems. We have additionally included 16,000 examples where answers (to the same questions) are provided by 5 different annotators,

I am really looking forward to digging into this …good questions and good answers are definitely part of the key for solving some great puzzles ….

have fun …

Plant Intelligence – its true, they do have intelligence.

You can talk to plants and make them happy … yup, and likely they can return the favor!   Did you know that Francis Darwin specialized in Plant Physiology … and stirred the pot just like his dad did. Apparently both Charles and Francis were proponents of the idea that plants were intelligent. This is field is just now picking lot of steam! check

Brilliant Green: The Surprising History and Science of Plant Intelligence  by Stefano Mancuso

Turns out Francis wasn’t terribly shy … Brilliant Green recounts Francis Darwin’s opening gambit …

on September 2, 1908, at the opening of the annual congress of the British Association for the Advancement of Science, he threw caution to the wind and declared that plants are intelligent beings.

also, take a look at

  • Trewavas, A. (2014). Plant behaviour and intelligence. OUP Oxford.
  • van Loon, L. C. (2016). The intelligent behavior of plants. Trends in plant science21(4), 286-294.
  • Marder, M. (2013). Plant-thinking: A philosophy of vegetal life. New York: Columbia University Press.
  • Trewavas, A. (2016). Intelligence, cognition, and language of green plants. Frontiers in psychology7, 588.
  • Trewavas, A. J., and Baluska, F. (2011). The ubiquity of consciousness, cognition and intelligence in life. EMBO Rep.12, 1221–1225. doi: 10.1038/embor.2011.218
  • Trewavas, A. (1999). How plants learn. Proceedings of the National Academy of Sciences96(8), 4216-4218.
  • Thaler DS. 1994. The evolution of genetic intelligence. Science264: 1698-1699.√

A lot was motivated by Barb’s Nobel Prize talk –  McClintock, B. (1984). The significance of responses of the genome to challenge. Science 226, 792–801. doi: 10.1126/science.15739260

there’s more to this story … check later .

Deep Learning – a kind of magic

One synthesis of   Stuart Russel’s  reflections on Deep Learning:

“ Some deep learning networks get up to one thousand layers or more  …  The deep learning hypothesis suggests that many layers make it easier for the learning algorithm to find a predictor, to set all the connection strengths  in the network so that it does a good job.  … to a large extent, it’s still a kind of magic, because it really didn’t have to happen that way.   why this happens is still anyone’s guess.

in Marty Ford’s  new book:  principal architects of AI.

Russell Stuart is  lead co-author  of  THE must have  AI textbook

Artificial Intelligence: A Modern Approach (3rd Edition)

this textbook is the main AI textbook used in over 1000 Universities and Colleges.  If he says it’s a kind of magic … it is a kind of magic!  So if you want to be one of the contemporary magicians or wizards … get on with the deep learning wands.

BONUS … Queen’s kind of magic

Deep Learning AI Playbook: Strategy for Disruptive Artificial Intelligence

Today … looking at Carlos Perez’s Deep Learning AI Playbook: Strategy for Disruptive Artificial Intelligence 

The claim: “This book is an opinionated take on the developments of Deep Learning AI” – a reviewers offers that it’s probably good to start out exploring the  Intuition Machine blog on Medium.    Appears oriented to the ‘first-entry into AI ‘ folks who want to get a sense of what’s going on. Really Deep AI /Deep Learning / Deep whatever is another matter.

Ford’s Architects of Artificial Intelligence

 

To place Artificial Intelligence in appropriate context is a complex and intricate challenge.  Marty Ford, a master explainer presents interviews with some of the principal architects of AI.  The Architects in this case are Yoshua Bengio, Stuart Russell, Geoffrey Hinton, Nick Bostrom, Yann LeCun, Fei-Fei Li, Demis Hassabis, Andrew Ng, Rana El Kaliouby, Ray Kurzweil, Daniela Rus, James Manyika, Gary Marcus, Barbara Grosz, Judea Pearl, Jeffrey Dean, Daphne Koller, David, Ferrucci, Rodney Brooks, Cynthia Breazeal, Joshua Tenenbaum, Oren Etzioni, and Bryan Johnson.

What a great list … Dan Ferrucci is of course known from his amazing work with IBM WATSON, and the first ever amazing win of a machine over the best of the best at Jeopardy!  Dennis Hassabis , of Google/Alphabet’s Deep Mind, brought us AlphaGo, AlphaGoZero, and now AlphaGo that exceeds the best of the best in Chess, GO and Shogi (all with the same MCTS algorithm). NYU/FAIR/FaceBook’s Yan LeCun did some serious stuff with Mastering and claiming ‘the prize’ over ImageNet Challenge. Rodney Brooks with iRobot, … each one of the Architects is truly a master architect.  We’ll explore their contributions and significance later … their thoughts are really worth checking out.  I am looking at all kinds of things right now … and there’s just so much.  Maybe I need a nice Intelligent Machine Assistant to help me pull this al together.  🙂

Ford, M. (2018), Architects of Intelligence