Looking back at 2021 it was a different kind of year for voice AI than in the past. We could have said that in 2020 as well, but that was true on every societal and economic level due to the pandemic. However, we saw the seeds of change in the voice AI industry in late 2019 that was paused briefly and then accelerated in 2020 which set up 2021 to be the year of enterprise adoption. Voice AI news, innovation, and investment were largely driven by consumer applications in the period 2016 – 2019. Amazon, Google, and Apple (and occasionally Samsung) dominated the headlines related to the technology.

AI had a memorable 2021, although not always for the best reasons. The field unleashed an arousing blend of breakthroughs, applications, and ideas -- but also discharged a steady stream of bigotry, BS, and big tech barbarity. At Neural, we aspire to be like Fox News in its prime: fair and balanced. In this equitable spirit, we've compiled an even mix of AI's best and worst of 2021. Without further ado, here are five stories that made us cherish our robot overlords -- and five that had us reaching for the off switch.

Computer Science is no more about computers than astronomy is about telescopes. When looms weave by themselves, man's slavery will end. Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended. Today we are entirely dependent on machines.

AI Stories is a proposed interactive dialogue system, that lets children co-create narrative worlds through conversation. Over the next three years this system will be developed and tested within pediatric wards, where it offers a useful resource between the gap of education and play. Telling and making stories is a fundamental part of language play, and its chatty and nonsensical qualities are important; therefore, the prologued usage an automated system offers is a benefit to children. In this paper I will present the current state of this project, in its more experimental and general guise. Conceptually story-telling through dialogue relates to the preprint interpretation of story, beyond the static and linear medium, where stories were performative, temporal, and social.

Artificial intelligence (AI) has been celebrated for its application across a ton of fields, from medicine to agriculture, science, computer programming, finance and security. For the 21st century farmer, AI can help detect crop disease, predict crop yields and spray pesticide with pinpoint accuracy. With respect to medicine and health, AI can allow scientists to analyse the genetic code of DNA to detect genomic condition, predict hypoglycemic events hours in advance of them occurring, and detect cancer in tissue slides better than human epidemiologists. AI is also a key driver transforming the banking industry; helping banks save time, boost their revenue and bringing more accessible technology to consumers. But there is one area of banking where little recognition has been given until now of the immense opportunity AI offers: that of making risk analysis easier than ever before, essentially, taking the risk out of risk analysis.

It is an unfortunate truth that most people around the world don't have a real understanding of what artificial intelligence (AI) is. The same is true for many of the influential people who are in active discussions and working with companies where AI plays a significant part in our future. In fact, a recent survey found that most organisations don't have a clear understanding of how AI or machine learning will help their businesses. In general, people's perception of what AI is comes from movies and media, with doomsday scenarios and super intelligent robots taking over the world. It's not surprising given the unprecedented speed of development in AI, and the hype that has come with it.

In this week's edition of the NVIDIA Developer Top 5 video, we revisit the top developer stories of the week. From an AI system that can automatically map vegetation areas in the Arctic to a robot that relies on AI to play Jenga.

In it, CW3 Crifasi describes the inherent tension between human critical thinking and the benefits of Augmented Intelligence facilitating warfare at machine speed. "CAITT, let's re-run the targeting solution for tomorrow's engagement… again," asked Chief Warrant Officer Five Robert Menendez, in a not altogether annoyed tone of voice. Considering this was the fifth time he had asked, the tone of control Bob was exercising was nothing short of heroic for those knew him well. Fortunately, CAITT, short for Commander's Artificially Intelligent Targeting Tool, did not seem to notice. Bob quietly thanked the nameless software engineer who had not programmed it to recognize the sarcasm and vitriol that he felt when he made the request.

Anytime the new cool thing comes around, all the cool engineers have to figure out the best ways to make it work. And we embark on a natural progression – or perhaps succession is a better word – sort of the way a depression along a river changes from pond to wetland to meadow. In general, you can get either performance or one or both of the other two. The thing is, though, that, if the best way to do the new thing isn't known yet, then you're likely to settle for something suboptimal for the sake of flexibility, figuring it out as you go, and perhaps fixing it after it's deployed in the field. After that, you might move to hardware of the flexible sort: FPGAs.

Artificial intelligence (AI) has continued to gain prominence in 2017 as one of the biggest upcoming technologies. It is beginning to have more of an influence on companies' strategies and is predicted to drive significant change for organisations. Every conference this year contains a dead human genius reincarnated as software system or a robot. Yes, there is a lot of hype, but there is real worth in AI and Machine Learning. Read our counseling on how to avoid adopting "black box" approach.