The first three entries in my "2020: A consumer electronics forecast for the year(s) ahead" piece, published back in January, all had to do with deep learning. Why? Here's part of what I wrote back then: The ability to pattern-match and extrapolate from already-identified data ("training") to not-yet-identified data ("inference") has transformed the means by which many algorithms are developed nowadays, with impact on numerous applications. This transformation is already well underway, as even a casual perusal of the titles and coverage topics of content published at EDN, EE Times, and elsewhere will make clear. Don't panic: there's still time to "catch the wave," especially if your focus is on resource-constrained implementations. But you don't want to wait too long lest you end up stuck bobbing around in the water while more foresighted colleagues are already at the beach enjoying the AI "party."

Editor's note: This post is the result of a collaboration with PredictX, a decision automation platform. Author Joni Lindes is a content writer at PredictX. AI is set to disrupt our current society on a major scale. According to Indeed, the number of roles in AI has risen by 485% in the UK since 2014, but the digital skills gap continues to hold back innovation. In 2017, companies spent around $22 billion on AI-related mergers and acquisitions -- 26 times more than 2015.

This is a transcript of the talk I gave at Crowd Supply's Teardown Conference. Growing up, the free toys on the covers of magazines were made of plastic. They were cheap, and cheerful. Yet the last thirty years has reduced the price of computing to the point where cheap and cheerful plastic toys have been replaced by other things. Around this time last year Google and Raspberry Pi did something rather intriguing.

If you've been wanting to dig into artificial intelligence on a personal level, then you have probably been considering one of Google's AIY kits. These allow STEM (science, technology, engineering, and mathematics) audiences to engage in simple projects with a relatively low investment. Now, Google has made things even easier by creating bundles that include the requisite Raspberry Pi single-board computers. The AIY products have two versions aimed at two A.I. applications. There is the AIY Vision Kit that allows experimenting with image recognition and neural networks and the AIY Voice Kit that combines voice recognition and the Google Assistant.

The "technology of the future" is constantly changing. Remember when Google Glass was the future and venture capitalists launched huge funds dedicated to financial Glass app developers? Remember when chat bots were the future and every tech company on the planet burned time and money developing Facebook Messenger bots? Yeah, most "technologies of the future" end up being little more than silly trends that vanish almost as quickly as they arrived. This time around, however, things feel like the might be a bit different when it comes to the latest "technology of the future."

Google's do-it-yourself AIY kits released last year are already a great way to learn the ins and outs of designing a smart home speaker powered by Google Assistant, but they always came with a caveat: You needed to bring your own Raspberry Pi to the party. But with an update available today, Google is giving you everything you need right in the box. Once again available in two flavors, Voice and Vision, Google's new kits are a one-stop solution for building the next-generation of AI devices, and include a Raspberry Pi Zero WH, micro USB connection cable, and pre-provisioned SD card. Each kit also comes with the appropriate hardware you'll need to get your smart device up and running: Google's AIY Voice Kit includes everything you need to make a smart speaker. Google's AIY Vision Kit includes everything you need to make a smart camera.

Back in May, Google announced AIY Projects -- do-it-yourself hardware kits for experimenting with artificial intelligence. Today, Google followed up the first Voice Kit with a new Vision Kit for image recognition and TensorFlow development. These AIY Kits are crude speakers -- and now cameras -- housed in simple cardboard boxes. Builders also need to supply their own Raspberry Pi Zero W and a Raspberry Pi Camera 2 for this latest project. Otherwise, the kit includes everything needed from lenses, wires, and a VisionBonnet board with an Intel Movidius MA2450 that connects to the Raspberry Pi.

I am a heavy user of Raspberry Pis. Every year I build a massive musical lighting setup for Christmas using couple of Pis. During Halloween, I build Pi-powered talking skeletons, spooky pumpkins, and scary lights. I am using Pi to run a Retro gaming rig, and my next project includes a remote controlled car and a possible drone. You get the point, I am a heavy user of Raspberry Pi and IoT.