^CategoryMachine Learning

^{Type
post

Author
Eric Holloway
Date
November 11, 2019

Categorized
Machine Learning, Programming

Tagged
Data snooping, Occam's razor, Probability}

Occam’s Razor Can Shave Away Data Snooping

_{The greater an object's information content, the lower its probability.} _{Eric Holloway

November 11, 2019

4

Machine Learning, Programming}

One technique to avoid data snooping is based on the intersection of information theory and probability: An object’s probability is related to its information content. The greater an object’s information content, the lower its probability. We measure a model’s information content as the logarithmic difference between the probability that the data occurred by chance and the number of bits required to store the model. The negative exponential of the difference is the model’s probability of occurring by chance. If the data cannot be compressed, then these two values are equal. Then the model has zero information and we cannot know if the data was generated by chance or not. For a dataset that is incompressible and uninformative, swirl some tea Read More ›

^{Type
post

Author
Brendan Dixon
Date
November 9, 2019

Categorized
Machine Learning, Programming

Tagged
Racism, sexism}

Big Tech Tries to Fight Racist and Sexist Data

_{The trouble is, no machine can be better than its underlying training data. That’s baked in} _{Brendan Dixon

November 9, 2019

4

Machine Learning, Programming}

The problem with machine learning-based AI in police work is not so much its inherent bias (none of us is bias-free) but the delegation to a machine of what should be a human decision.

^{Type
post

Author
Eric Holloway
Date
November 5, 2019

Categorized
Education, Machine Learning, Programming

Tagged
Algorithms, discrimination, Machine Learning, Supervised Learning}

Machine Learning, Part 2: Supervised Learning

_{Machine learning isn’t hard to understand; it’s just different. Let’s start with the most common type} _{Eric Holloway

November 5, 2019

4

Education, Machine Learning, Programming}

The neat thing about machine learning is that the algorithm can extract general principles from the dataset that can then be applied to new problems. It is like the story that Newton observed an apple fall and then derived from it the general law of gravity that applies to the entire universe.

^{Type
post

Author
Denyse O'Leary
Date
October 31, 2019

Categorized
Artificial Intelligence, Machine Learning

Tagged
Alchemy, AlphaGo Zero, Amazon, Artificial Intelligence, Consciousness, COSM, George D. Montanez, Google, Homonculus, Machine Learning, Matt McIlwain, Microsoft, non-algorithmic, Oren Etzioni, Ray Kurzweil, Robert J. Marks, Singularity}

Is Ray Kurzweil’s Singularity Now Nearer — or Impossible?

_{In response to Kurzweil’s talk at the COSM Technology Summit, panelists noted that AI achievements are revolutionary in size but limited by their nature in scope} _{Denyse O'Leary

October 31, 2019

4

Artificial Intelligence, Machine Learning}

George Montañez, Assistant Professor of Computer Science at Harvey Mudd College, took issue with Kurzweil’s claim that AlphaGoZero needed no instructions to beat humans at the game of Go: “For a system like this to work, a human must define the incentive structure, also encoding the assumptions.” The sheer power of a computing system does not cause it to do anything at all.

^{Type
post

Author
Denyse O'Leary
Date
October 24, 2019

Categorized
Machine Learning, Medicine and Health

Tagged
AlphaGo, Artificial Intelligence, Bill Dembski, COSM, Craig Mundie, DeepMind, General Artificial Intelligence, George Gilder, health and medicine, Machines, Medicine, Microsoft, Open AI}

Former Microsoft Head of Research: Machines Will Soon Know Better Than Your Doctor

_{Other experts at the COSM Technology Summit were skeptical of Craig Mundie’s claims} _{Denyse O'Leary

October 24, 2019

3

Machine Learning, Medicine and Health}

Mundie, former Microsoft Chief Research & Strategy Officer, formerly told his audience that Big Data will enable each person to be “completely understood” by machines that can produce a computer facsimile of each detail. It would be far too complex for human physicians to make sense of, he said.

^{Type
post

Author
Eric Holloway
Date
October 22, 2019

Categorized
Education, Machine Learning

Tagged
Goodhart’s Law, Teaching to the test}

The Challenge of Teaching Machines to Generalize

_{Teaching students simply to pass tests provides a good illustration of the problems} _{Eric Holloway

October 22, 2019

4

Education, Machine Learning}

We want the machine learning algorithms to learn general principles from the data, and not merely little tricks and trivia that that score high but ignore problems.

^{Type
post

Author
News
Date
October 10, 2019

Categorized
Global Technology, Machine Learning

Tagged
Carver Mead, COSM, Moore's Law, Richard Feynman}

Carver Mead Asks, Where Did AI Come From?

_{The microprocessor pioneer who was a colleague of Feynman and named Moore’s Law is certainly in a position to know} _{News

October 10, 2019

5

Global Technology, Machine Learning}

In 2002, he received the National Medal of Technology for a number of “pioneering contributions to microelectronics,” which underlies cell phones and computer neural networks.

^{Type
post

Author
Analysis
Date
August 27, 2019

Categorized
Artificial Intelligence, Machine Learning, Philosophy of Mind

Tagged
___longform, Featured, Machine learning history', Perceptrons}

Machines Are Not Really Learning

_{A bit of machine learning history helps us see why} _{Analysis

August 27, 2019

8

Artificial Intelligence, Machine Learning, Philosophy of Mind}

Go talk to a neighbor or a friend. You’ve just done something that Deep Learning can’t do. Worse, it can’t even learn because that’s not a narrow, well-defined problem. Read More ›

^{Type
post

Author
Brendan Dixon
Date
August 22, 2019

Categorized
Ethics, Global Technology, Machine Learning

Tagged
Culture, self-driving cars}

Does a Western Bias Affect Self-Driving Cars?

_{How a driver is expected to act varies by culture} _{Brendan Dixon

August 22, 2019

5

Ethics, Global Technology, Machine Learning}

Self-driving cars (autonomous vehicles) will need to adapt to different rules and we will, very likely, need to change those rules to make the vehicles work. Read More ›

^{Type
post

Author
News
Date
August 20, 2019

Categorized
Data Privacy, Machine Learning, Technocracy

Tagged
Emotion recognition, Featured}

The Machine Knows You Are Angry

_{Okay, it knows if your facial muscles are twisted in a certain way… does the difference matter?} _{News

August 20, 2019

5

Data Privacy, Machine Learning, Technocracy}

Five accomplished scientists representing different camps reviewed over a thousand studies of machine emotion recognition. Essentially, there seems no clear science basis for the claims made. Read More ›

^{Type
post

Author
Jonathan Bartlett
Date
August 5, 2019

Categorized
Artificial Intelligence, Machine Learning

Tagged
Amazon Web Services (AWS), chatbots}

You can build your own chatbot

_{New tools have made it comparatively easy} _{Jonathan Bartlett

August 5, 2019

7

Artificial Intelligence, Machine Learning}

Natural Language Interfaces (the technical term for a chatbot) are becoming more and more popular. Many dial-in phone services have switched from numeric interfaces (“Dial 1 for sales, 2 for service, etc.”) to natural language interfaces (“Please say what you are calling about”). Where they have taken off though is with chatbots. Many online help systems at least start with chatbots, which collect basic information about a problem or situation and point to existing solutions before passing the contact off to a human expert. Additionally, the rise of the Generation Text, as well as the proliferation of chat-based groupware such as Slack, means that text-based natural language interfaces are one of the best ways of interacting with young people. Is Read More ›

^{Type
post

Author
Brendan Dixon
Date
August 2, 2019

Categorized
Machine Learning

Tagged
Deep Learning, open source code}

Lazy Engineers Treat AI as Magic!

_{When software engineers mostly use shared code, they save time but risk losing understanding} _{Brendan Dixon

August 2, 2019

3

Machine Learning}

Building from scratch is different. Knowing when to use a tool and why and knowing the limitations of each tool separates the craftsperson from the novice.

^{Type
post

Author
Brendan Dixon
Date
July 24, 2019

Categorized
Business and Finance, Machine Learning

Tagged
self-driving cars, Uber, Waymo}

Even Uber didn’t believe in Uber’s self-driving taxis

_{We found that out after Google’s Waymo sued the company} _{Brendan Dixon

July 24, 2019

4

Business and Finance, Machine Learning}

Optimism is not driving the recent collaboration and corporate consolidation in the self-driving car industry. Rather, their retrenchment is protection against an uncertain future.

^{Type
post

Author
Robert J. Marks
Date
July 19, 2019

Categorized
Artificial Intelligence, Machine Learning

Tagged
Chicago 1968 riots, Neural networks, Police, Riots, Yippies}

Can AI Predict and Prevent Political Unrest?

_{The 1996 Democratic Convention tried neural networks but discovered a hidden flaw} _{Robert J. Marks

July 19, 2019

5

Artificial Intelligence, Machine Learning}

The police union’s 1996 objection to fingering specific officers as violence risks without a detailed explanation pinpoints a weakness of neural networks even to this day. The neural network is basically a black box.

^{Type
post

Author
Denyse O'Leary
Date
July 11, 2019

Categorized
Machine Learning

Tagged
Language, Linear A}

Could Machine Learning Decipher Lost Languages?

_{It gives us new search powers, based on perennial facts of language} _{Denyse O'Leary

July 11, 2019

5

Machine Learning}

An endless variety of word games derives from the fact that only certain combinations and orderings of words can be correct. Machine learning applies vast resources to cracking the code.

^{Type
post

Author
Eric Holloway
Date
July 5, 2019

Categorized
Machine Learning

Tagged
Business Intelligence, Data analysis, Data Deadlock, False positives, Intelligent design theory}

How Business Intelligence Can Break the Data Deadlock

_{Companies today are awash in information. But which patterns are real? Which are cloud bunnies?} _{Eric Holloway

July 5, 2019

7

Machine Learning}

Contrary to the dogma of hypothesis testing, it is possible to do after-the-fact pattern analysis while limiting the probability of false positives.

Abstract Visualization of data and technology in graph form. 3D Illustration

^{Type
post

Author
Jonathan Bartlett
Date
July 1, 2019

Categorized
Education, Machine Learning

Tagged
Parameterization}

Machine Learning Tip: Set Boundaries for the Problems

_{We cannot take a giant pile of unorganized data, shove it into a machine, and expect useful results} _{Jonathan Bartlett

July 1, 2019

3

Education, Machine Learning}

Humans intrinsically understand causation and, therefore know which pieces of data likely have some correlation. Therefore, when we select data for computers to analyze, we are drastically reducing the size of the problem for computers.

Photo from driver's seat with light trails ahead

^{Type
post

Author
Brendan Dixon
Date
June 18, 2019

Categorized
Artificial Intelligence, Machine Learning

Tagged
self-driving cars}

The Real Future of Self-Driving Cars Is — Better Human Drivers!

_{Manufacturers are improving safety by incorporating warning systems developed for self-driving cars into conventional models} _{Brendan Dixon

June 18, 2019

5

Artificial Intelligence, Machine Learning}

This human-plus-machine combination is proving more potent than the machine-only hype/promise.