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Artificial Intelligence: Past, Present, Futures

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Oz’s Tik-Tok to the Mechanical Turk, from Neural Nets & Genetic Algorithms to Chess & StarCraft, from fighting the Coronavirus to flying Killer Drones, from Facial Recognition to Fakes, Deep Fakes, & Anti-Fakes, Artificial Intelligence (AI) is everywhere today. How did it start? What do we mean by AI? What are the basic AI techniques? How is it being used? What are the benefits? risks? and how should we manage AI going forwards?

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Artificial Intelligence: Past, Present, Futures

  1. 1. Artificial Intelligence John Ashmead Past, Present, & Futures An AI reflects on itself reflection on herself — impossible not to say herself & not just because of Alicia Vikander — ability to know others & self key to all strong AI
  2. 2. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 AI’s are Everywhere three of the 22 here are real Talos — Jason & the Argonauts The Mechanical Turk — popular chess playing fake (18th century) TicTok — Wizard of Oz Robot Maria — Metropolis Joe (transparent robot) — The Proud Robot Roy Batty (replicant) - Bladerunner R2-D2 & C-3PO — Star Wars Terminator — Terminator Rommie (ship avatar) — Andromeda Android Gunslinger — West World Commander Data — Star Trek Next Generation Mecha — AI Sonny — I, Robot BB-8 — Star Wars Eve & Wall-E — Wall-E Asimo — Honda robot Johnny 5 - Short Circuit Sophia — The First Robot Declared a Citizen by Saudi Arabia (2016)
  3. 3. Janet — The Good Place Ava — Ex Machina Samantha — Her Denise Virtual Assistant — NextOS (now Realbotix) Real are Asimo, Sophia, & Denise many from https://www.zdnet.com/pictures/15-of-the-best-movies-about-ai-ranked/16/ https://www.goodreads.com/book/show/19003281-the-proud-robot
  4. 4. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 History • Talos (way old) • Antikythera (200 BC) • Mechanical Turk (1770-1854) • Difference Engine (1833) Mechanical Turk: https://spectrum.ieee.org/tech-talk/tech-history/dawn-of-electronics/untold-history-of-ai-charles-babbage-and-the-turk In 2014, a study by Carman and Evans argued for a new dating of approximately 200 BC based on identifying the start-up date on the Saros Dial as the astronomical lunar month that began shortly after the new moon of 28 April 205 BC.[15][16] Moreover, according to Carman and Evans, the Babylonian arithmetic style of prediction fits much better with the device's predictive models than the traditional Greek trigonometric style.[15] A study by Paul Iversen published in 2017 reasons that the prototype for the device was indeed from Rhodes, but that this particular model was modified for a client from Epirus in northwestern Greece; Iversen argues that it was probably constructed no earlier than a generation before the shipwreck, a date supported also by Jones.[46] The Turk, also known as the Mechanical Turk or Automaton Chess Player (German: Schachtürke, "chess Turk"; Hungarian: A Török), was a fake chess-playing machine constructed in the late 18th century. From 1770 until its destruction by fire in 1854 it was exhibited by various owners as an automaton, though it was eventually revealed to be an elaborate hoax.[1] Constructed and unveiled in 1770 by Wolfgang von Kempelen (Hungarian: Kempelen Farkas; 1734–1804) to impress the Empress Maria Theresa of Austria, the mechanism appeared to be able to play a strong game of chess against a human opponent, as well as perform the knight's tour, a puzzle that requires the player to move a knight to occupy every square of a chessboard exactly once. The Turk was in fact a mechanical illusion that allowed a human chess master hiding inside to operate the machine. With a skilled operator, the Turk won most of the games played during its demonstrations around Europe and the Americas for nearly 84 years, playing and defeating many challengers including statesmen such as Napoleon Bonaparte and Benjamin Franklin. The device was later purchased in 1804 and exhibited by Johann Nepomuk Mälzel. The chess masters who secretly operated it included Johann Allgaier, Boncourt, Aaron Alexandre, William Lewis, Jacques Mouret, and William Schlumberger, but the operators within the mechanism during Kempelen's original tour remain a mystery.
  5. 5. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 What do we mean by Artificial intelligence? • Evolving understanding • Sense of others • Sense of self http://www.decadecounter.com/readingroom/kuttner.htm A robot with self-regard Why now: Big Data Big CPUs Big Wins we will be doing weak AI here: machine learning: minimum cutoff: unsupervised & evolving No context, no ontology, no sense of self or other, still amazing for what it is And if you are a programmer, go here!
  6. 6. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Where is AI now? • NOT strong or general AI. No common sense. No ontology. Invariably narrow focus. • BIG DATA: Google search, Twitter, … • BIG CPUs: (parallel processing, graphics processors, especially NVIDIA) • and BIG WINS: GoogleTranslate, ImageNet, AlphaZero (DeepMind), Watson • Here AI means: unsupervised & evolving machine learning • Which can perform at better than human levels, at least with respect to some characteristics
  7. 7. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Search they make often very good recommendations like but different as the hollywood producers say why are they being so nice to you, as the thanksgiving turkey might ask
  8. 8. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Covid-19 https://www.understandcovid.org At every angle of attack there are web sites to collect all Covid-19 datasets used to find new attack mechanisms used by the coronavirus new lines of attack against it estimates of the spread of the lockdown effectiveness from cell phone usage! drug discovery diagnosis minimizing contact disseminating correct information
  9. 9. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 driverless car terminator view fatal accidents rare but not unknown expect the unexpected nearly safer than humans already I suspect, especially for long haul truck driving in amazon’s own feature upload a self-driving car is used as a murder implement: they are trusted so much that the victim is unsuspecting watch out for unicorns: https://www.nytimes.com/2019/08/26/opinion/3d-printed-unicorns.html
  10. 10. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 AlphaZero • Learns by itself • Beat AlphaGo • Plays chess, checkers, shoji, … that’s not sexy, sexy is taking starfighters to the ends of the Galaxy & blowing up things with tentacles games: reason: well-defined problem space chess the first big win — in fact first chess AI built before first computers — founders fascinated alpha Go biggest win but it was fed games alpha zero plays itself and then learns other games as well using GAN fix the problem of how to get enough data. DeepMind Technologies is a UK based artificial intelligence company and research laboratory founded in September 2010, and acquired by Google[4] in 2014. The company is based in London, with research centres in Canada,[5] France,[6] and the United States. In 2015, it became a wholly owned subsidiary of Alphabet Inc.
  11. 11. The company has created a neural network that learns how to play video games in a fashion similar to that of humans,[7] as well as a Neural Turing machine,[8] or a neural network that may be able to access an external memory like a conventional Turing machine, resulting in a computer that mimics the short-term memory of the human brain.[9][10] The company made headlines in 2016 after its AlphaGo program beat a human professional Go player Lee Sedol, the world champion, in a five-game match, which was the subject of a documentary film.[11] A more general program, AlphaZero, beat the most powerful programs playing go, chess and shogi (Japanese chess) after a few days of play against itself using reinforcement learning.[12]
  12. 12. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Rescuing Trafficked Children With risks
  13. 13. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Finding Exo-Planets huge quantities of boring data — big physics does this as well and crowdsourced finding of XI — exo-intelligence — you heard it here first
  14. 14. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 The Artist in the Machine fun, a high end version of the photoshop filters separate the artist from the scene understand art better
  15. 15. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Twittering Machine • By imitating thought, understand it, • By seeing what is mechanical, have a better appreciation for what is human, • And change & extend what we mean by “human” Paul Klee another crank, and not the last Photography did not replace art, complements, as in last slide
  16. 16. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Inputs input algorithm output like making a cake only not the recipe
  17. 17. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Facial recognition A face in “terminator view” lots of free data, a big requirement for AI eigen faces — eigen noses & so on, then work it from there key metrics see Ekman’s micro expressions
  18. 18. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Algorithms • Neural Nets • Genetic Algorithms • Swarms 
 Stealing from nature arabic word, goes well back
  19. 19. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Neural Nets Idea of CPUs stolen from then ideas of mind like a conspiracy: who is responsible what is going on on the hidden layers — big problem, actually, they work but how?
  20. 20. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Genetic Algorithms
  21. 21. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Cross-over Mutation(s)Tech Uses Start Stages: Selection Cross-over Mutation AND — meta, this diagram included in itself (not normally done in AI)
  22. 22. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Swarms https://www.solutions4u-asia.com/emailc/SwarmIntelligenceForOptimization.html inspired by ants parallel processing: know your losers crowdsourcing drones very literally — tho curiously I don’t know how much the actual drones communicate key to success: 100s or 1000s of entities, but if you kill the rest when one or two succeed, the economics are not bad
  23. 23. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Outputs hand signals the most fun recommender systems: list of images & words robot jazz band playing, not shown here. Music & AI one of many interesting sub-branches
  24. 24. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 DreamCatcher /AutoDesk • Antenna on right 2x more efficient • AI mechanical/ logical/Vulcan? • Actually organic/ alien biology • Neural net designed by a genetic algorithm picture of the crane advantages: cheap at scale reliable explore whole solution space https://www.autodesk.com/research/projects/project-dreamcatcher https://medium.com/intuitionmachine/the-alien-look-of-deep-learning-generative-design-5c5f871f7d10 https://medium.com/intuitionmachine/the-alien-look-of-deep-learning-generative-design-5c5f871f7d10 https://medium.com/intuitionmachine/the-alien-look-of-deep-learning-generative-design-5c5f871f7d10 What happens when you have Deep Learning begin to generate your designs? The commons misconception would be that a machine’s design would look ‘mechanical’ or ‘logical’. However, what we seem to be finding is that they look very organic, in fact they look organic or like an alien biology. Take a look at some of these fascinating designs. These Long Short Term Memory (LSTM) are designed by an algorithm and shown to be more effective than the conventional LSTM (Note: These are Neural Networks designed with memory elements). These are generative neural architectures, machines that learn to learn, more like meta meta-models. Learning apparently is not
  25. 25. uniform and I highly suspect that meta-level reasoning is a primary mechanism in learning and that is reflected by its biological manifestation. After all, isn’t learning enhanced by diversity as well as adaptability? The same ingredients to biological survival?
  26. 26. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Face-recognition AI could only “see” Joy Buolamwini when she wore a white mask Google & the Chimps https://www.newscientist.com/article/mg24732951-400-coded-bias-review-an-eye-opening-account-of-the-dangers-of-ai/ Read more: https://www.newscientist.com/article/mg24732951-400-coded-bias-review-an-eye-opening-account-of-the-dangers-of-ai/#ixzz6aymi5nAd weakness in the training sets: medical trials WEIRD — Basically white, west coast, male, upper middle class, college educated, …
  27. 27. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 I do not think that picture shows what you think it shows Preying Mantis Shih TzuTemple School Bus ostrich, Struthio camelus ostrich, Struthio camelus ostrich, Struthio camelus ostrich, Struthio camelus Szegedy et al — https://arxiv.org/abs/1312.6199 Texture versus shape Szegedy et al — https://arxiv.org/abs/1312.6199
  28. 28. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Avoiding Nuclear War • 1983/Intl Tensions high • 5 US missiles reported • Too few for a strike • Detection system new • Report came in too quickly • No ground radar confirmation Lt. Col Petrov No common sense In the aftermath of the incident, the Soviet government investigated the incident and determined that Petrov had insufficiently documented his actions during the crisis. He explained it as "Because I had a phone in one hand and the intercom in the other, and I don't have a third hand"; nevertheless, Petrov received a reprimand.[4]
  29. 29. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Pay no attention to the man behind the curtain • Typically the AI algorithm requires “tweaking”. • Rate of convergence • Termination conditions Very ad hoc
  30. 30. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Trending Topics: When Bubbles Collide Curiously, the way to actually succeed at internet argument is to listen! Like Traffic Jams — actually this was predicted by Vernor Vinge, the net of a thousand lies or some such Try DuckDuckGo if you would rather not be bubbled
  31. 31. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Deep Fakes https://www.youtube.com/watch?v=6bFN2YkN6bo&t=7s speak in Obama’s voice with lip sync very useful for animations. like autotune (which also uses AI)
  32. 32. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Weapons of Math Destruction • Good teacher fired for not meeting numbers • Appears that previous grades for class had been up-revved (faked) • “Hey, what can you do?” dangers of algorithms applied blindly but fiercely paperclip problems (soviet nail problem)
  33. 33. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 If you are not paying for the product, you are the product • Monitor every click & keystroke • Use AI to assess current emotional state • Use AI to target with appropriate ads for max sales • Deny all the above https://www.nytimes.com/2020/01/24/opinion/sunday/surveillance-capitalism.html “By monitoring posts, pictures, interactions and internet activity in real time,” the executives wrote, “Facebook can work out when young people feel ‘stressed,’ ‘defeated,’ ‘overwhelmed,’ ‘anxious,’ ‘nervous,’ ‘stupid,’ ‘silly,’ ‘useless’ and a ‘failure.’” This depth of information, they explained, allows Facebook to pinpoint the time frame during which a young person needs a “confidence boost” and is most vulnerable to a specific configuration of subliminal cues and triggers. The data are then used to match each emotional phase with appropriate ad messaging for the maximum probability of guaranteed sales. One of the most famous when Target
  34. 34. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 AI will do what we ask; that’s a problem AI is our own reflection, for what that is worth
  35. 35. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 • Chess — easy for AI, hard for humans • Perception/movement — easy even for infants, hard for AI Moravec’s Paradox New Yorker Sep 28th, 2020. Liana Finck, p59 "it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility” As Moravec writes: Ch Encoded in the large, highly evolved sensory and motor portions of the human brain is a billion years of experience about the nature of the world and how to survive in it. The deliberate process we call reasoning is, I believe, the thinnest veneer of human thought, effective only because it is supported by this much older and much more powerful, though usually unconscious, sensorimotor knowledge. We are all prodigious olympians in perceptual and motor areas, so good that we make the difficult look easy. Abstract thought, though, is a new trick, perhaps less than 100 thousand years old. We have not yet mastered it. It is not all that intrinsically difficult; it just seems so when we do it.[3] A compact way to express this argument would be: We should expect the difficulty of reverse-engineering any human skill to be roughly proportional to the amount of time that skill has been evolving in animals. The oldest human skills are largely unconscious and so appear to us to be effortless. Therefore, we should expect skills that appear effortless to be difficult to reverse-engineer, but skills that require effort may not necessarily be difficult to engineer at all.
  36. 36. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Never trust anything that can think for itself if you can't see where it keeps its brain? - Mr. Weasley • AI should not be a chamber of secrets • “DeepDream” lets you see intermediate AI images • & we can use the tech used to probe human brains to probe AI!
  37. 37. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Attention must be paid • Data governance • Humans in kept in the loop • Transparency • Accountability Controlling the WEIRD Aegis as an example avoiding the negative
  38. 38. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Humanity ascendent? • Use the AI for the many things it is good for • Jobs will be lost, but jobs will also be created • Letting us do more of the fun stuff & less of the other stuff • And some stuff we just couldn’t do before • If we pay attention
  39. 39. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 Thanks! • Ferne Welch • Philcon • And all those fighting COVID-19!
  40. 40. http://timeandquantummechanics.comArtificial Intelligence/John Ashmead Philcon 2020 References • Scharre 2018 - Army of None • Pickover 2019 - Artificial Intelligence • Mitchell 2019 - Artificial Intelligence • Miller 2019 - The Artist in the Machine • Shane 2019 - You look like a thing and I love you Miller 2019 - The Artist in the Machine Mitchell 2019 - Artificial Intelligence O'Neil 2016 - Weapons of Math Destruction Pickover 2019 - Artificial Intelligence Scharre 2018 - Army of None Shane 2019 - You look like a thing and I love you Tamboli 2019 - Keeping Your AI under Control Trask 2019 - Grokking Algorithms

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