Key take aways from “Gut Feelings”

  • Gut feelings definition
    • appears quickly in consciousness
    • underlying reasons we are not fully aware of
    • strong enough to act upon
  • Laws in the real world are different from those in the logical idealized world
  • Benjamin Franklin’s Moral Algebra
    • when in doubt weigh out the pros and cons of each side by cancelling out the pros that might weigh the same
  • Our brain
    • adaptive forgetting: data is destroyed with the aggregation of information into actionable insights
    • We can only decipher the output generated by our brain (a neural network) but cannot decipher the series of logical steps taken to derive this output
    • Deliberate thinking about reasons seems to lead to decisions that make us less happy
    • Thinking too much can slow down and disrupt performance
      • The gaze heuristics for catching baseball
    • the more complex a species the longer the period of infancy
    • The short term memory rule of 7 +/- 2
    • Intelligence means making bets, taking risk seeing more than what the eye sees
  • Satisfisers versus Maximizers
    • former is reported to be more optimistic, higher self-esteem and life satisfaction
  • Rule: Create scarcity and develop systematically
    • is a viable alternative in human and organizational development
  • Less is more
    • Stock picking of familiar stocks (partial ignorance) still out perform complex analysis (extensive knowledge)
  • Man and his environment
    • Herbert Simon: A man, viewed as a behaving system, is quite simple. The apparent complexity of his behavior over time is largely a reflection of the complexity in the environment he finds himself
    •  Steve Jobs, structured work place to maximize chance conversations
    • In an uncertain environment good intuitions must ignore information
    • Quality heuristics: we equate recognition to quality – Goldstein and Gigerenzer, 2002
      • why marketing might work in short run despite shitting products
    • One-reason decision making – a short cut people use despite official guidelines
      • implies a fast and frugal decision tree

References

  • Simple rules for a complex world, Epstein

Book Summary: The driver in the driverless car

Conditions the presage the leap into the future in any specific economic segment or type of service

  • Systemic requisite:
    • Widespread dissatisfaction – latent or overt with the status quo
  • Technology requisite:
    • Moore’s Law
      • Cheap computers
      • Cheap sensors – IOT
      • increase in Connection speed
      • Hand hosted AI
    • IOT
      • software
      • data connectivity
      • Handheld computing
    • Artificial Intelligence and Automation
      • Shift of discrete analog task into networked digital one

Five paradigms of computing

  • Electromechanical
  • Relay
  • Vaccuum tube
  • Discrete transistor
  • Integrated circuits – Moores’ Law

Current Concerns

  • Speed of technology evolution versus  speed of regulation – codified ethics
  • Equality, Risks and Dependency versus Autonomy
    • Does the technology have the potential to benefit everyone?
    • What are the risk and rewards?
    • Does the technology more strongly promote autonomy or dependence?
      • cheap software based technologies inexpensively scaled to reach millions-billions
      • the more revenue generated the more motivated developers would want to share it broadly

Future Concerns

  • Biometric theft
  • Merging of humans with computers
  • Extent of Gene alteration that is socially acceptable – new class of humans differentiated by genetic differences
    • mitigating health risk
    • higher intelligence
    • better looks
    • greater strength
  • Privacy will be a thing of the pass
  • Navigating technology trends as a navigator instead of a passenger
  • Large scale drone attacks

Artificial Intelligence

  • Definition: a cheap reliable industrial grade digital smartness running behind everything, Kevin Kelly, Editor of WIRED magazine
  •  Types
    • Narrow AI
    • Strong/General AI
      • Watson
  • Impact of existing human occupations
    • Doctors in health care
    • Lawyers

Education

  • Ancient Greece:
    • Socratic process whereby teacher guided students through the learning process by asking them questions
    • Education was privilege reserved for the elites
  • Middle Ages/Renaissance
    • Remained a priviledge
    • process of learning became more rote
    • more memorization
  • Online Education
    • Example: Khan academy
    • Researchers found people most likely to take advantage of online courses were those who need the least help
    • LA Unified: giving each student a tablet failed to move the needle
  • Minimally invasive Education, Mitra, New Delhi
    • NIIT building, Kalkaji slums
    • Key component of the learning process was the group dynamic
    • Self taught scholars learned as quick as school-bound peers
  • Self directed learning – flipped model of education
    • teacher no longer broadcast information, write lesson plans or stand in front of classes lecturing
    • teachers became coaches and guides to students needing additional help
    • students consumed recorded lectures or videos online at their own pace and in their own time
    • Teachers focus on judgment, nuances and emotional intelligence

Mores law and poverty

  • Comparatively poorer parts of the world will be able to leap frog into more modern and efficient era
    • wireless mobile phones
    • drones for deliver
    • Solar energy power plants
    • driver less cars
      • no need for traffic lights
      • freeways
      • Parking spaces
  • USA has no monopoly on innovation

Driver less Cars

  • Access versus ownership
  • Baidu, Google, Tesla
  • China
    • Bejing, Wuhu and Anhui
  • Singapore
  • city layouts become more flexible
  • commuting is less a hassle

Current trends

  • Plasma based water purification technology: kills 100% of bacteria and viruses
  • Energy

Further readings

  • How to create a mind: the secret of human thought revealed, Ray Krurzweil
  • The inevitable, Kevin Kelly
  • The internet of things: Mapping the value beyond Hype, McKinsey Global Institute
  • Infinite Resource: The Power of Ideas on Finite Planet
  • Abundance: The future is better than you think, Peter Diamandis

Deep learning and Machine Learning resources

A compiled list of sites that are useful for learning about fundamentals of artificial intelligence from a coders perspective:

Deep learning

  • http://course.fast.ai/lessons/lesson1.html –
    • Utilizes a breadth first approach through teaching
    • Focus on code first
    • Human learning flourishes when operating in different context.
  • http://yerevann.com/a-guide-to-deep-learning/

Machine Learning

  • https://www.analyticsvidhya.com/blog/2015/08/common-machine-learning-algorithms/
  • http://machinelearningmastery.com/naive-bayes-classifier-scratch-python/

Business Applications

  • https://medium.com/@thoszymkowiak/120-machine-learning-business-ideas-from-the-new-mckinsey-report-b81b239f336