AI has blasted its way into the public consciousness and our everyday lives. It is powering advances in medicine, weather prediction, factory automation, and self-driving cars. Even golf club manufacturers report that AI is now designing their clubs.
Every day, people interact with AI. Google Translate helps us understand foreign language webpages and talk to Uber drivers in foreign countries. Vendors have built speech recognition into many apps. We use personal assistants like Siri and Alexa daily to help us complete simple tasks. Face recognition apps automatically label our photos. And AI systems are beating expert game players at complex…
Interview in @Hearst publications with @bysarajane about my book “Evil Robots, Killer Computers, and Other Myths: The Truth About AI and the Future of Humanity”. www.aiperspectives.com/evil-robots #ArtificialIntelligence
Check out this article on Forbes.com. @joemckendrick discusses the impact of AI on employment and my book www.aiperspectives.com/evil-robots.
Really enjoyed my @ITIFdc podcast conversation with @RobAtkinsonITIF and @jackie_whisman. We discussed many topics covered in my new book “Evil Robots, Killer Computers, and Other Myths: The Truth About AI and the Future of Humanity” (www.aiperspectives.com/evil-robots).
Excited to announce publication of my new book by Fast Company Press. It explains how AI works in simple terms, why people shouldn’t worry about intelligent robots taking over the world, and the steps we need to take as a society to minimize the negative impacts of AI.
Chapter summaries can be found at www.AIPerspectives.com/chapters.
Available at major retailers including www.amazon.com/dp/1735424536.
Sentiment analysis is used to determine if the sentiment in a piece of text is positive, negative, or neutral. Sentiment analysis is a form of natural language processing and is part of a subcategory of NLP techniques known as information extraction.
One job of a data scientist is to choose the optimal algorithm for a given task. Often, the best approach is to try many different algorithms to see what works best.
The NHTSA website’s section on self-driving vehicles starts off with some compelling statistics:
Moreover, according to the website, today’s driver assistance technologies such as emergency braking and pedestrian detection are already saving lives. And I absolutely believe this is true.
But where I part company with the NHTSA is that we should therefore throw caution to the wind and allow fully autonomous (i.e. driverless) self-driving vehicles onto our streets and highways without adequate testing.
Many of today’s consumer vehicles have Level 2 self-driving capabilities. This means that the car will automatically stay in the correct lane and accelerate/decelerate on its own. However, the driver must always have their eyes on the road and be ready to take over immediately. In GM vehicles, this is enforced by a camera that monitor the driver’s eye movements. In Telsa vehicles, this is enforced by detecting that the driver has a hand on the wheel.
These Level 2 self-driving capabilities are known as driver assist capabilities. They make driving easier and safer. …
Author of “Evil Robots, Killer Computers, and Other Myths: The Truth About AI and the Future of Humanity” published Feb 9, 2021 by Fast Company Press.