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Table of Contents
I.The Artificially Intelligent Corpus
II.The Machine Brain and its Senses
III.Deploying AI in Financial Services & Economic Impact
IV.Front Office: Chatbots & Conversational Interfaces
V.Middle Office: Regtech & Identity
VI.Financial Product Manufacturing using AI
VII.The Macro View on Intelligence Explosion
VIII.About Autonomous
Lex Sokolin
Partner & Global Director
Fintech Strategy
Matt Low
Senior Associate
@autonofintech
next@autonomous
April 2018
This content leverages the
work of the analysts at
Autonomous Research,
and in particular:
Jacob Kruse
Stuart Graham
Patrick Davitt
Andrew Crean
Andrew Ritchie
Executive Summary (1 of 2)Artificial intelligence is here because the needed hardware and software have been built
–AI requires hardware with massive computing power and data sets with millions of data points across many
types of human activity, which have emerged from the web
–There are 7.5 billion people but 20 billion smart computing devices, all with access to the storage and
processing power of the Cloud, which is a $100 billion market
–Venture capital has flown into Machine Learning companies at a rate of $5-10 billion per year
There are various scientific approaches to building AI; the current relevant development is
the advance in Machine Learning, and in particular neural networks and deep learning
–Designing software by automating a process top-down is fundamentally different from leveraging AI
techniques, which create probabilistic models that change in response to new data
–Machines have developed the ability to derive information from sensory information, such as vision and
sound, with an accuracy greater than humans
–AI can also be used in a creative capacity to explore a space of ideas quickly or to do emotional tasks
The growth and potential of Artificial Intelligence is a massive challenge for the traditional
economy, and its development is likely to only accelerate
–Most of AI research is publicly available through academic archives and much of the code is open source
–Moore’s law suggesting exponential information processing continues to hold; current number of total
scientific research submissions to ArXiv is 1.3 million, lines of open source code is likely over 100 million
–Popularity of machine learning courses at top universities skyrocketed with compensation levels
–Important to be grounded -- today’s narrow Artificial Intelligence is not a panacea and does not have general
reasoning capacity; but there are many practical applications of automated human judgment