... includes all of the major AI methods for (a) representing knowledge about a task or a problem area, and (b) reasoning about a problem.
It's Monday morning of some week in 2050 and you're shuffling into your kitchen, drawn by the smell of fresh coffee C-3PO has brewed while he unloaded the dishwasher. "Here you go, Han Solo, I used the new flavor you bought yesterday," C-3PO tells you as he hands you the cup. C-3PO arrived barely a month ago and already has developed a wonderful sense of humor and even some snark. He isn't the real C-3PO, of course--you just named him that because you are a vintage movie buff--but he's the latest NeuroCyber model that comes closest to how people think, talk, and acquire knowledge. He's no match to the original C-3PO's fluency in 6 million forms of communication, but he's got full linguistic mastery and can learn from humans like humans do--from observation and imitation, whether it's using sarcasm or sticking dishes into slots. Unlike the early models of such assistants like Siri or Alexa who could recognize commands and act upon them, NeuroCybers can evolve into intuitive assistants and companions.
Computer vision systems sometimes make inferences about a scene that fly in the face of common sense. For example, if a robot were processing a scene of a dinner table, it might completely ignore a bowl that is visible to any human observer, estimate that a plate is floating above the table, or misperceive a fork to be penetrating a bowl rather than leaning against it. Move that computer vision system to a self-driving car and the stakes become much higher --for example, such systems have failed to detect emergency vehicles and pedestrians crossing the street. To overcome these errors, MIT researchers have developed a framework that helps machines see the world more like humans do. Their new artificial intelligence system for analyzing scenes learns to perceive real-world objects from just a few images, and perceives scenes in terms of these learned objects. The researchers built the framework using probabilistic programming, an AI approach that enables the system to cross-check detected objects against input data, to see if the images recorded from a camera are a likely match to any candidate scene.
Famous social media influencer Gary Vayernurchuk says, "The future belongs to Voice." Look at all AI (artificial intelligence) driven assistants around us, from Alexa to Google Assistant, there is inherent convenience in just saying it out loud and having voice based conversations with your'virtual' assistant rather than writing commands or selecting a drop down menu. We all know that healthcare needs to be digitised in order to reach the next level of patient care. Technologies like AI and Blockchain need to be integrated into existing healthcare systems in order to make them more efficient. But these technologies can only work if all our processes are digitised first.
Artificial intelligence (AI) is ubiquitous and set to be a significant driver of the world's economic activity in the next decade. It's a constellation of many technologies working in tandem to enable machines to sense, comprehend, act and learn with human-like levels of intelligence. Tools like machine learning (e.g., your credit card company sends a text about potentially fraudulent activity) and natural language processing (e.g., your phone helps you with the next likely word in a sentence) are part of the AI landscape. They'll continue to affect everything we do as we collect more data and enhance algorithms for better decision-making. As in other industries, AI will transform every layer of self-storage operation, too, including customer service, tenant access, security, finance, sales, marketing and revenue management (RM).
The smart home has never been more accessible, with more affordable entry points than ever. From security cameras to smart light bulbs, pretty much any internet-connected device that you can control via an app is enough to get you started on your smart home journey. But before you dive in, we advise taking a few preliminary steps. For one, don't try to outfit your entire smart home in one go. Not only can this be quite expensive, we think it's generally best to buy just one or two items first to see if you like them. From there, you can figure out if you want to buy more devices, making sure that they're compatible with one another.
The best virtual agents can avoid the need for some tickets to be submitted to help desk by offering up information that a user can use to self-service an issue or by resolving the issue directly by triggering an automated workflow such as a password reset. When a ticket does need to be submitted a virtual agent can ensure that tickets are fully-formed and “actionable”. Virtual agents can also relieve analysts from chasing down users for more information and handling repeatable mundane requests. It shouldn’t come as a surprise, therefore, that many of the most forward-looking IT organizations are already leveraging virtual agents to transform their service desks. Who Is Using Them? What is interesting, perhaps, is that these organizations are not limited to any one industry or type of business. Here are a few examples: City government—wanted to accelerate issue resolution and improve IT costs with a conversational approach to issue determination and resolution; deployed a virtual agent to drive self-service uptake and improve automation; and expect a 30% improvement in costs, along with enhancements to user satisfaction and service desk productivity. Global software company—hoped to streamline user interactions by completing and triaging tickets (or deflecting them altogether), and surveying users once issues have been resolved; installed a virtual agent to optimize the number of requests directed to its service desk catalog and automate as many workflows as possible; and forecast a 35% improvement in overall support costs. Managed service provider—decided to offer a key customer a solution which improved user satisfaction by reducing telephone support wait times; implemented a virtual agent in front of the customer’s interactive voice response system to divert users’ inquiries to a self-service knowledge base whenever possible; predict a 30% reduction in call volumes and a similar improvement in customer wait times. Multinational electronics manufacturer—resolved to increase the productivity of employees by enabling them to report issues on mobile devices removing the need for them to leave the manufacturing floor to access a computer terminal to do so; deploy a virtual agent as a first point of contact, enabling simple requests to be diverted to a knowledge database and issues resolved intuitively; anticipate at least a 30% improvement in support and service costs. State government—elected to improve the adoption of self-service resolution of issues by providing a more intuitive way for users to obtain assistance; installed a virtual agent as a conversational interface with simple issues routed to relevant sections of a help desk knowledge base for self-service resolution; expecting a 3x increase in the amount of issues resolved without analyst involvement. The ability of the best virtual agents to have an impact in such a wide variety of businesses and governments is, in part, due to them being agnostic to the ITSM environments into which they are deployed. They can, consequently, be deployed anywhere. Insight and Learnings Luma, the virtual agent that we’ve developed here at Serviceaide, and purpose-built for IT service management, already integrates seamlessly with leading ITSM solutions from CA Technologies, Cherwell, Freshservice and ServiceNow, and we will be are adding other leading ITSM platforms. And, of course, Luma also connects to our own Intelligent Service Management solution. Organizations, across a variety of industry sectors, have deployed Luma, or are in the process of doing so. I’m excited about these successes and look forward to sharing more details about them with you in future blog articles – I’m especially eager to describe the interesting things we’ve learned during the development and onboarding process in each instance, as I’m sure that this will be very insightful to others about to embark on a virtual agent deployment. Thanks for reading. We hope that our blog articles can inform and start conversations. If this article piques your interest, but leaves you wanting more, let me know.
Hit play on the player above to hear the podcast and follow along with the transcript below.This transcript was automatically generated, and then edited for clarity in its current form. There may be some differences between the audio and the text. Welcome back to Talking Tech. If you used Amazon's Alexa, I will only be saying this name once by the way, because I don't want to trigger anyone who has an Echo speaker, but if you've used Amazon's digital voice assistant, obviously it's got many different ways it can help you play a song, set a reminder, set an alarm. Now Amazon's digital assistant has a new role, helping seniors and caregivers.
Computer vision systems sometimes make inferences about a scene that fly in the face of common sense. For example, if a robot were processing a scene of a dinner table, it might completely ignore a bowl that is visible to any human observer, estimate that a plate is floating above the table, or misperceive a fork to be penetrating a bowl rather than leaning against it. Move that computer vision system to a self-driving car and the stakes become much higher -- for example, such systems have failed to detect emergency vehicles and pedestrians crossing the street. To overcome these errors, MIT researchers have developed a framework that helps machines see the world more like humans do. Their new artificial intelligence system for analyzing scenes learns to perceive real-world objects from just a few images, and perceives scenes in terms of these learned objects. The researchers built the framework using probabilistic programming, an AI approach that enables the system to cross-check detected objects against input data, to see if the images recorded from a camera are a likely match to any candidate scene.
In "Hyping Artificial Intelligence Hinders Innovation" (podcast episode 163), Andrew McDiarmid interviewed Erik J. Larson, author of The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do (2021) (Harvard University Press, 2021) on the way "Machines will RULE!" Erik Larson has founded two two DARPA-funded artificial intelligence startups. Inthe book he urges us to go back to the drawing board with AI research and development. This portion begins at 01:59 min. A partial transcript and notes, Show Notes, and Additional Resources follow.
Apple Music's recently announced Voice Plan will launch alongside iOS 15.2, according to the patch notes the company shared for the update's release candidate. When Apple first announced the more affordable tier at its fall Mac event in October, the company said it would become available "later this fall" in 17 countries, including the US, UK and Canada. Apple also confirmed Apple Music Voice Plan will launch with iOS 15.2 pic.twitter.com/6uHeaTdr41 The plan will offer access to Apple Music's entire song catalog for $5 per month, provided you're willing to rely on Siri for control. You can play specific tracks and playlists, as well as complete albums on your Apple devices.