- Are Tera Operations Per Second (TOPS) Just hype? Or Dark AI Silicon in Disguise? - May 27, 2020.
This article explains why TOPS isn’t as accurate a gauge as many people think, and discusses other criteria that should be considered when evaluating a solution to a real application.
AI, Deep Learning, Hype, Neural Networks
- Accuracy Fallacy: The Media’s Coverage of AI Is Bogus - Dec 6, 2019.
Such as the gross exaggerations Stanford researchers broadcasted about their infamous "AI gaydar" project, there exists a prevalent "accuracy fallacy" in relation to AI from the media. Find out more about how the press constantly misleads the public into believing that machine learning can reliably predict psychosis, heart attacks, sexuality, and much more.
Accuracy, AI, Hype, Media
- On the sensationalism of artificial intelligence news - Nov 15, 2019.
With artificial intelligence and machine learning now a mainstay of our daily awareness, news organizations have been seen to overstate the reality behind progress in the field. Learn more about recent examples of media hyperbole and explore why this may be happening.
AI, Hype, Media, Misconceptions
- OpenAI’s GPT-2: the model, the hype, and the controversy - Mar 4, 2019.
OpenAI recently released a very large language model called GPT-2. Controversially, they decided not to release the data or the parameters of their biggest model, citing concerns about potential abuse. Read this researcher's take on the issue.
AI, Ethics, GPT-2, Hype, NLP, OpenAI
- 4 Myths of Big Data and 4 Ways to Improve with Deep Data - Jan 9, 2019.
There is a fundamental misconception that bigger data produces better machine learning results. However bigger data lakes / warehouses won’t necessarily help to discover more profound insights. It is better to focus on data quality, value and diversity not just size. "Deep Data" is better than Big Data.
Big Data, Data Lakes, Data Warehouse, Hype, Machine Learning, Sampling
AI, Data Science, Analytics Main Developments in 2018 and Key Trends for 2019 - Dec 3, 2018.
Review of 2018 and Predictions for 2019 from our panel of experts, including Meta Brown, Tom Davenport, Carla Gentry, Bob E Hayes, Cassie Kozyrkov, Doug Laney, Bill Schmarzo, Kate Strachnyi, Ronald van Loon, Favio Vazquez, and Jen Underwood.
2019 Predictions, AI, Automated Machine Learning, Automation, Bill Schmarzo, Carla Gentry, Cassie Kozyrkov, Doug Laney, GDPR, Hype, Jen Underwood, Meta Brown, Predictions, Risks, Ronald van Loon, Tom Davenport, Trends
- Things you should know when traveling via the Big Data Engineering hype-train - Oct 8, 2018.
Maybe you want to join the Big Data world? Or maybe you are already there and want to validate your knowledge? Or maybe you just want to know what Big Data Engineers do and what skills they use? If so, you may find the following article quite useful.
Big Data, Big Data Hype, Data Engineering, Hype
- The Current Hype Cycle in Artificial Intelligence - Feb 28, 2018.
Over the past decade, the field of artificial intelligence (AI) has seen striking developments. As surveyed in, there now exist over twenty domains in which AI programs are performing at least as well as (if not better than) humans.
AGI, AI, Deep Learning, History, Hype, Jobs, Machine Learning
- The Birth of AI and The First AI Hype Cycle - Feb 13, 2018.
A dazzling review of AI History, from Alan Turing and Turing Test, to Simon and Newell and Logic Theorist, to Marvin Minsky and Perceptron, birth of Rule-based systems and Machine Learning, Eliza - first chatbot, Robotics, and the bust which led to first AI Winter.
AI, Alan Turing, Herbert A. Simon, History, Hype, Marvin Minsky, Neural Networks
- More than the Hype: Beyond Gartner’s Hype Cycle - Nov 3, 2017.
Gartner publishes hype cycles across different technologies and sectors. Here we conduct detailed analysis of Gartner’s Hype Cycles.
Gartner, Hype, Stocks
- Credible Sources of Accurate Information About AI - Oct 9, 2017.
I want to recommend several credible sources of accurate information. Most of the writing on this list is intended to be accessible to anyone—even if you aren’t a programmer or don’t work in tech.
AI, fast.ai, Hype, Jeremy Howard, Rachel Thomas, Research, Twitter, Zeynep Tufekci
I built a chatbot in 2 hours and this is what I learned - Sep 7, 2017.
I set out to test two things: 1) building a bot is useless from a business perspective and 2) building bots is crazy tough. Here is what I learned.
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AI, Chatbot, Hype, NLP
- Is Deep Learning Overhyped? - Jan 29, 2016.
With all of the success that deep learning is experiencing, the detractors and cheerleaders can be seen coming out of the woodwork. What is the real validity of deep learning, and is it simply hype?
Deep Learning, Hype, Matthew Mayo, Quora, Yoshua Bengio
