Industrial revolutions are central to the desire for technology to make human life easier. Although we can summarize the journey from Industry 1.0 to 4.0 in a paragraph, human beings have been trying to make life easier for centuries. What did this desire create? At what point of the industrial revolution are we now? Is your business ready for this revolution?

Taken in aggregate, the billions of online searches we make every day say a lot about our most private thoughts and biases. Taken in aggregate, the billions of online searches we make every day say a lot about our most private thoughts and biases. When we have a question about something embarrassing or deeply personal, many of us don't turn to a parent or a friend, but to our computers: We ask Google our questions. As millions of us look for answers to questions, or things to buy, or places to meet friends, our searches produce a map of our collective hopes, fears, and desires. Seth Stephens-Davidowitz, a former data scientist at Google, analyzes the information we leave behind on search engines, social media, and even pornography sites.

Digital photographers coined the term "pixel peepers" years ago to denote -- mostly with scorn -- people who focused on flaws in the individual dots that create photos rather than the entirety of the images. Zooming in to 100%, it was said, is nothing but a recipe for perpetual disappointment; instead, judge each camera by the overall quality of the photo it takes, and don't get too mired in the details. Until now, Apple's approach to digital photography has been defined by its commitment to improving the quality of the big picture without further compromising pixel-level quality. I say "further" because there's no getting around the fact that tiny phone camera sensors are physically incapable of matching the pixel-level results of full-frame DSLR camera sensors in a fair fight. Bigger sensors can capture more light and almost invariably more actual pixels than the iPhone's 12-megapixel cameras.

Dr. Lance B. Eliot is a world-renowned expert on Artificial Intelligence (AI) and especially Autonomous Vehicles (AV). As a seasoned executive and high-tech entrepreneur, he combines practical industry experience with deep academic research to provide innovative insights about the present and future of AI and ML technologies and applications. Formerly a professor at USC and UCLA, and head of a pioneering AI lab, he frequently speaks at major AI industry events. Author of over 30 books, 300 articles, and 200 podcasts, he has made appearances on media outlets such as CNN and co-hosted the popular radio show Technotrends. His particular specialty in AI is Autonomous Vehicles and advances in self-driving driverless cars.

Mention artificial intelligence and many people envision a dystopian future like something out of Blade Runner or I, Robot, with an impersonal society run by giant, faceless corporations. The reality is much different, as AI is behind many of the most personal services today, like voice assistants (Alexa, Siri) and predictive entertainment platforms (Netflix, Spotify). And it's not just for large enterprise companies: Thanks to more affordable AI options, small businesses are beginning to embrace it. In fact, while only 8 percent of SMBs currently use AI, research shows an additional 32 percent intend to implement it (which amounts to a potential growth rate of 310 percent). It may seem a bit shocking that so many small businesses would want to jump on board the AI train.

Amazon (NasdaqGS:AMZN) has made the Alexa Echo available in Brazil. The mega popular virtual assistant chatbot is now able to speak Brazilian Portuguese. "Echo Dot and Echo Show 5 are available for pre-order in Brazil today and will begin shipping to customers starting next week, while Amazon Echo will be available to customers in November,'' according to the press release. "We're excited to introduce Alexa to customers in Brazil, with a custom-built experience that honors Brazil's language and unique culture. Customers across Brazil will be able to ask for their favorite music, control their smart home, and enjoy skills from hundreds of customer-favorite Brazilian brands including Show do Milhão, Porta dos Fundos, UOL Esporte, iFood, Leite Ninho, Cinemark, and more.

Generated Photos is a collection of 100,000 human faces, all free to download and use for any purpose. These people are beautiful, diverse, and ready to show up in your next ad campaign. Oh, and none of them are real. They've been generated by artificial intelligence. Most look indistinguishable from real human beings, but they are all just very cleverly arranged pixels, sorted by a machine.

In Part 1 of this 3-part miniseries, we discussed the origins of artificial intelligence (AI), and we considered some low-hanging AI-enabled fruit in the form of speech recognition, voice control, and machine vision. In Part 2, we noted some of the positive applications of AI, like recognizing skin cancer, identifying the source of outbreaks of food poisoning, and the early detection of potential pandemics. In fact, there are so many feel-good possibilities for the future that they can make your head spin. In a moment, we'll ponder a few more of these before turning our attention to the dark side. Another topic we considered in Part 2 was the combination of mediated reality (MR) and AI, where mediated reality encompasses both augmented reality (AR) and deletive reality (DR). In the case of AR, information is added to the reality we are experiencing.

As an exercise for myself I decided to implement SWA, from the paper Averaging Weights Leads to Wider Optima and Better Generalization. I did it with Keras and decided it might make a nice package. If you are not familiar with SWA, it is a trick to approximate ensembling by taking a running average of your weights towards the end of training a model. You can read more in this nice blog post explaining SWA and it's relatives SSE and FGE. I currently only implement the constant learning rate schedule from the paper, hoping to add the cyclic one from the paper soon.