Author Archives: GilPress
?The internet is living up to its potential as a major source for news about the presidential campaign
Pew Internet: January 11, 2008 The internet is living up to its potential as a major source for news about the presidential campaign. Nearly a quarter of Americans (24%) say they regularly learn something about the campaign from the internet, almost … Continue reading
Artificial Intelligence: 2017 Predictions from Forrester
Insights matter. Businesses that use artificial intelligence (AI), big data and the Internet of Things (IoT) technologies to uncover new business insights “will steal $1.2 trillion per annum from their less informed peers by 2020.” So says Forrester in a … Continue reading
Posted in AI, Misc, Predictions
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O’Reilly AI Conference: 12 Observations About Artificial Intelligence
At the inaugural O’Reilly AI conference, 66 artificial intelligence practitioners and researchers from 39 organizations presented the current state-of-AI: From chatbots and deep learning to self-driving cars and emotion recognition to automating jobs and obstacles to AI progress to saving … Continue reading
Posted in AI, Machine Learning
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3 Takes on Debugging Machine Learning
S. Zayd Enam: The difficulty is that machine learning is a fundamentally hard debugging problem. Debugging for machine learning happens in two cases: 1) your algorithm doesn’t work or 2) your algorithm doesn’t work well enough. What is unique about … Continue reading
Posted in AI, Machine Learning
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Current Capabilities of Artificial Intelligence (AI)
Andrew Ng: Surprisingly, despite AI’s breadth of impact, the types of it being deployed are still extremely limited. Almost all of AI’s recent progress is through one type, in which some input data (A) is used to quickly generate some simple response (B)… … Continue reading
The Smart Speakers Market
A new study by Juniper Research has found that revenue from smart audio hardware will more than triple over the next four years, rising from an estimated $1.4 billion this year to over $5.5 billion by 2020. While Juniper … Continue reading
Posted in Misc
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Predicting the Presidential Election: What Went Wrong? (Part 2)
Wall Street Journal: When asked about what qualities matter most, about four in 10 people picked the ability to bring about change, and Mr. Trump won more than 80% of their votes. Mrs. Clinton was heavily favored by voters who … Continue reading
Posted in Data Science, Misc
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Predicting the Presidential Election: What Went Wrong?
KDnuggets: …a good lesson for Data Scientists is to question their assumptions and to be especially skeptical when predicting a rare event with limited history using human behavior.