Next-generation technology, like artificial intelligence (AI), touches almost every aspect of our lives: from what we watch, to how we shop, to the way we work and more. But how much does the average person actually know about the technology that shapes many of the decisions that impact us? And with an increasing reliance on technology and computer literacy, what can be done to ensure no one is left behind? On a recent episode of TELUS International Studios, we sat down with Sinead Bovell, founder of WAYE, a community where young entrepreneurs learn about the intersection of business, technology, ethics and the future. Bovell explains that she is driven by a mission to build a progressive, informed and thriving society -- one in which technology is built on the "right side of history."

RSC will help us build new and better AI models, work across hundreds of different languages, develop new augmented reality tools and more. Ultimately, the work done with RSC will pave the way toward building technologies for the next major computing platform -- the metaverse, where AI-driven applications and products will play an important role. To fully realize the benefits of advanced AI, various domains, whether vision, speech, language, will require training increasingly large and complex models, especially for critical use cases like identifying harmful content. With RSC, we can more quickly train models that use multimodal signals to determine whether an action, sound or image is harmful or benign. As RSC moves into its next phase, we plan for it to grow bigger and more powerful, as we begin laying the groundwork for the metaverse.

As we approach the close of a whirlwind 2020, connected devices will continue to define numerous industries in the coming year. Several trends continue to gather momentum, fueling IoT's prominence in 2021, from data-intensive experiences that use Internet of Things (IoT) devices (such as self-driving cars or wearable devices) to basic health-and-safety needs as COVID-19 continues to take center stage. At the same time, the IoT landscape remains fragmented, with various prevailing standards, connectivity options and use cases abounding. This fragmentation will continue, predicted Forrester Research, and connectivity options will be diverse rather than standardized. While 5G has been touted as the holy grail for IoT, "there will be a variety of connectivity options," said Michele Pelino, senior analyst within the infrastructure and operations research team at Forrester.

Reimagining your organization requires major overhauls and not small incremental changes. What it implies is to zero in on areas that lag behind in performance and then search and deploy the right technology solution. With digital disruption going mainstream, cognitive technologies like AI will soon turn out to be the de facto model that organizations pursue. In fact, AI adoption rates among businesses keep escalating and the market is expected to be valued at 190.61 billion USD by 2025. Brimming with possibilities, AI's capabilities extend beyond automation and more into sustaining existing business processes with renewed vigor. Leaning towards a data-centric approach will push organizations to deploy state-of-the-art AI solutions to monetize real value from data.

Currently co-founder and CTO at Nudge.ai, which uses artificial intelligence to help salespeople find useful trigger events at their target accounts. Letting AI do the heavy burden of research allows sales professionals to focus on selling, while never missing a chance to turn latent demand into active demand. Prior to that, co-founder and CTO of Eloqua, a company I helped guide to a market-leading position in marketing automation, while growing it to a $100 million revenue run rate, through its IPO on the NASDAQ, and to ultimate acquisition by Oracle. Tell me about your early career. It may seem strange considering that Nudge.ai is not my first software startup, but I'm not even originally a software guy.

Data-driven digital marketing is big business. According to eMarketer some 55% of all digital advertising dollars will be driven by programmatic initiatives in 2015 where computer speed and machine learning take precedence over human guess work. By 2016 that number is expected to rise to 63% representing over $20 billion in programmatic ad buys. Legions of data scientists and math Ph.Ds have taken over the digital advertising business. They are serving to enhance efficiency for the notoriously inefficient business of marketing.

After graduating with a law degree from the University of Saskatchewan, Andrew identified a problem amid the legal hierarchy – by experiencing it first-hand. "I worked at a small law firm to pay my way through university and law school. When I started out I did a lot of the grunt work that senior lawyers don't do. Legal research takes about 30% of a lawyer's time. Currently legal research works by inputting keywords to search a massive databases of cases – you type in a query and get thousands of results, which a lawyer has to trawl through to pick out key meanings. I was doing that, and I can tell you that it's a mess and takes a long time".

Although a number of Computer Aided Process Planni ng (CAPP) systems have been implemented, human planners are still irreplaceable for actual manufacturing. Because process planning requires multiple types of human expertise, there is a common trend to apply knowledge-based techniques for solving the process planning tasks. This circumstance is conducive to developing so-called CAPP Expert Systems (CAPPES). A few approaches to building CAPPES can be found through means-aids analysis of the research literature since 1980. At the same time, it can be seen that authors' efforts in those papers have mostly been made in special cases of CA PPES implementation, whereas the problem of "How to develop CAPPES" on the whole is still open. Se veral general conceptions and methodologies for CAPP have been published, but no fairly versatile technology is yet known. The aim of the paper is to consider the us age of logical models for development of a CAPPES building technology.