Whether you're hip to it or not, conversational AI--which is really the sequencing of technologies like NLU/NLP, code-free programming, RPA, and machine learning inside of organizational ecosystems--has already begun reshaping the world at large. Lemonade, a tech- and user-centric insurance company is upending its industry by providing customers with a rewarding experience buying insurance that's facilitated by Maya, an intelligent digital worker described as "utterly charming" that can quickly connect dots and get customers insured. Maya is essentially an infinitely replicable agent that is always learning and doesn't make the same mistake twice. Compare that with whatever it costs Allstate to retain more than 12,000 agents in the US and Canada who are likely using outdated legacy systems and it's clear to see which way ROI is trending. Even bigger successes have been enjoyed by Ant Group (formerly Ant Financial) a nimble, Chinese financial giant that had surpassed the number of customers served by today's largest US banks by more than 10 times back at the start of 2020. Their IPO--which would have been the world's largest to date--collapsed after Chinese Communist Party leader Xi Jinping allegedly intervened. Subsequently, the company has broadened its scope past fintech to include sustainability and inclusive services (whatever those might be). Still, its core operations were built around a streamlined business structure that uses conversational AI to deliver meaningful experiences. While this kind of adoption of conversational AI in business settings is roundly expected to boom in the coming years, it will quickly seep into our daily lives as well, going beyond how we interact with the many companies in our lives and taking root in our interactions with all of the different technologies we regularly touch. I've always taken an interest in these topics, but like many cutting-edge things, they're hard to approach. Especially if you have no idea where to start. Especially if you don't have the expertise; the lexicon, the mindset, the lived experience. I'm a bit of an accidental Luddite, someone perpetually late to the party when it comes to the latest and greatest. Not to say that I'm completely unfamiliar with these things, just that integrating them into my work, and my life, is hard.
I have a lot of Alexas. Oh, it's not just because I'm a reviewer, and Amazon keeps sending me devices to review. It's because I purposely bought an Alexa device for every room of the house. Here are your best options from Google, Apple, and more. Some of you will comment about the Big Brother aspects of allowing a global artificial intelligence to listen to everything I say.
As a futurist, every year, I look ahead and predict the key tech trends that will shape the next few months. There are so many innovations and breakthroughs happening right now, and I can't wait to see how they help to transform business and society in 2022. Let's take a look at my list of key tech trends that everyone should be ready for, starting today. Computing power will continue to explode in 2022. We now have considerably better cloud infrastructure, and many businesses are re-platforming to the cloud.
I took a dive into recent history, and read an article written by Lin Grossman from about 4 years ago. How did the future look like before Covid-19 when our reality was just a science fiction saga. So we are not yet blessed by two hours delivery by drones, and physical storefronts are still out there (though we do not visit them as much), and regretfully the virtual fitting room is not yet commercial. But I share the same vision as The Futurist Faith Popcorn and "Given retail's steady migration to mobile and e-commerce, you may be wondering what retail will look like in the future". As predicted by futurist Faith Popcorn, we can continue to expect hyper-customized concierge and on-demand services, and what the writer calls "consutainment," the integration of ultra-convenience, consumption, and entertainment.
Amazon is reportedly aiming to bring some of the tech it uses at cashierless Amazon Go stores to your kitchen. According to Insider, the company has been working on a smart fridge that can monitor items and help you order replacements if you're running low on something. The team behind the Amazon Go systems is said to be heading the charge on the project, which has been in the works for at least two years. The Just Walk Out tech used at Go stores tracks what shoppers put in their carts and automatically charges them when they leave. Members of the Amazon Fresh and Lab126 hardware teams are reportedly involved with the fridge project too.
I wanted to write this piece once my sadness had faded. I don't think it has really. That feeling has been overtaken by other emotions. Why I have been sad, you ask? Modern Family, just like all good things, inevitably came to an end. You'll learn so much about family, friendships, society, and business just by watching the family comedy series. My most favorite bits of the show were those that highlighted technology in modern society; from the closets that pick out outfits for you depending on the weather, the robot concierge, and Fridget.
Within electrical distribution networks, substation constraints management requires that aggregated power demand from residential users is kept within suitable bounds. Efficiency of substation constraints management can be measured as the reduction of constraints violations w.r.t. unmanaged demand. Home batteries hold the promise of enabling efficient and user-oblivious substation constraints management. Centralized control of home batteries would achieve optimal efficiency. However, it is hardly acceptable by users, since service providers (e.g., utilities or aggregators) would directly control batteries at user premises. Unfortunately, devising efficient hierarchical control strategies, thus overcoming the above problem, is far from easy. We present a novel two-layer control strategy for home batteries that avoids direct control of home devices by the service provider and at the same time yields near-optimal substation constraints management efficiency. Our simulation results on field data from 62 households in Denmark show that the substation constraints management efficiency achieved with our approach is at least 82% of the one obtained with a theoretical optimal centralized strategy.
Behaviour selection has been an active research topic for robotics, in particular in the field of human-robot interaction. For a robot to interact effectively and autonomously with humans, the coupling between techniques for human activity recognition, based on sensing information, and robot behaviour selection, based on decision-making mechanisms, is of paramount importance. However, most approaches to date consist of deterministic associations between the recognised activities and the robot behaviours, neglecting the uncertainty inherent to sequential predictions in real-time applications. In this paper, we address this gap by presenting a neurorobotics approach based on computational models that resemble neurophysiological aspects of living beings. This neurorobotics approach was compared to a non-bioinspired, heuristics-based approach. To evaluate both approaches, a robot simulation is developed, in which a mobile robot has to accomplish tasks according to the activity being performed by the inhabitant of an intelligent home. The outcomes of each approach were evaluated according to the number of correct outcomes provided by the robot. Results revealed that the neurorobotics approach is advantageous, especially considering the computational models based on more complex animals.
Indoor navigation systems leverage shortest path algorithms to calculate routes. In order to define the "shortest path", a cost function has to be specified based on theories and heuristics in the application domain. For the domain of indoor routing, we survey theories and criteria identified in the literature as essential for human path planning. We drive quantitative definitions and integrate them into a cost function that weights each of the criteria separately. We then apply an exhaustive grid search to find weights that lead to an ideal cost function. "Ideal" here is defined as guiding the algorithm to plan routes that are most similar to those chosen by humans. To explore which criteria should be taken into account in an improved pathfinding algorithm, eleven different factors whose favorable impact on route selection has been established in past research were considered. Each factor was included separately in the Dijkstra algorithm and the similarity of thus calculated routes to the actual routes chosen by students at the University of Regensburg was determined. This allows for a quantitative assessment of the factors' impact and further constitutes a way to directly compare them. A reduction of the number of turns, streets, revolving doors, entryways, elevators as well as the combination of the aforementioned factors was found to have a positive effect and generate paths that were favored over the shortest path. Turns and the combination of criteria turned out to be most impactful.
Over the last few months here at Carnegie Mellon University (Australia campus) I've been giving a set of talks on AI and the great leaps it has made in the last 5 or so years. I focus on disruptive technologies and give examples ranging from smart fridges and jackets to autonomous cars, robots, and drones. The title of one of my talks is "AI and the 4th Industrial Revolution". Indeed, we are living in the 4th industrial revolution – a significant time in the history of mankind. The first revolution occurred in the 18th century with the advent of mechanisation and steam power; the second came about 100 years later with the discovery of electrical energy (among other things); and the big one, the 3rd industrial revolution, occurred another 100 years after that (roughly around the 1970s) with things like nuclear energy, space expeditions, electronics, telecommunications, etc. coming to the fore. So, yes, we are living in a significant time.