In a series of posts analyzing what is happening in the digital assistant platform race, this post discusses Apple Siri.
Apple pioneered the personal digital assistant space when they launched Siri in 2011 on their iPhone 4S. It received kudos and funny jokes from all parts of the industry, but overall it was a success. Steve Jobs lured the founders of Siri into Apple in 2010, but to everyone's surprise, the original Siri founders, and rest of the team, started leaving Apple soon after the launch of the iPhone 4S. It is fair to assume, based on the recent announcements of Viv Labs, that the Siri team realized that their objective to make Siri a universal digital assistant for everyone was not Apple’s objective. Apple interest in Siri was another Jobs' genial moment that saw better devices and better user experiences because of Siri. Siri helped Apple sell more products by improving products' user experience and help customers become more productive. The departure of the Siri team must have created some internal challenges at Apple and possibly the reason for the slowdown and the subsequent slow reaction to Alexa. Even after this turbulence though many still see Siri as a smarter digital assistant than Alexa. Considering that iPhones are still selling like hotcakes, Mac has reached a remarkable 7% market share, and Watch is slowly displacing FitBit as the preferred activity tracker, I would say that Siri is not driving customers away for sure. Apple management is not losing sleep over Siri's challenges, but they recognize it needs to keep pace for the simple reason of not allowing competitors an opportunity to encroach on their customer base. In a series of posts analyzing what is happening in the digital assistant platform race, this post discusses Amazon Alexa and the devices it is sold with: Amazon Echo and Echo Dot.
Amazon Alexa has taken the breath away from Siri. Amazon, like Apple, understood that speech was a medium that could make people more productive and get things done faster. Amazon main strategy at the start was to drive customers to their online store. It was a brilliant positioning when they launched the Echo as a speaker that could execute voice commands. They opened the platform to developers only a few months after the launch of the Echo, and after almost two years there are more than 10,000 new skills developed by 3rd parties (as of February 2017). Apple proved with the App Store that you could make a platform incredibly successfully if the developers come and build apps, useful and beautiful apps. Amazon is following the same script with a vengeance and speed that is remarkable. In a white paper a few years back, I opined that adoption of Virtual Digital Assistants platforms was being slowed down by the fact that building and maintaining its ‘knowledge’ was still a predominantly manual task and therefore expensive and slow. Over the last 20 years, many companies have adopted Virtual Assistants on their website, and some with a reasonable success, that showed consistent ROIs and improved customer satisfaction. However, Virtual Assistants never became pervasive during last decade. Many early adopters were excited about the possibilities, envisioned new uses for them, not just for customer support but also as hostess, marketing/product advisors. But one of the issues that muted this excitement was the inefficiency of the knowledge management process. These solutions relied on rule-based systems that required manual intervention to retrain the virtual assistants. While these systems did use machine learning for certain features, e.g., to adjust keyword weights or remember frequently used responses to queries, but the creation and modification of the dialogs was pretty much a manual effort. If in doubt, they accepted the alternative of just placing a static FAQ or search engine that indexed the knowledge automatically, even if the user experience was not nearly as good. This attitude has changed over the last few years, and companies are now recognizing the importance of the conversational user experience to retain customers. For the virtual assistant platforms still around, this could be a renewed opportunity for a breakthrough. The rule-based Virtual Assistants are better for businesses than the modern ML-based models, for two critical reasons: 1) amount and quality of data available to build reliable ML-based systems, 2) simplicity and predictability of rule-based systems. Presentation or slideshow software allows anyone to illustrate concepts and topic overviews very quickly and simply. Microsoft® PowerPoint, Apple® Keynote, and Google® Slides are some of these popular software apps, with PowerPoint being the most common data format supported by all.
What if you want to engage your audience in virtual whiteboard sessions or want to poll them on particular topics or take their pulse on how well they are grasping your presentation? For example, trainers, instructors, and teachers need just that, and while they use presentation software to deliver learning content, its effectiveness is limited for its inability to engage the audience with interactive canvas slides or polls. These users have to resort to separate applications causing a non-ideal user experience for both trainers and trainees. The good news is that Microsoft and Google have opened up their presentation software, online version, to developers to create integrated systems that improve enormously that user experience. We created such a system at LiberCloud, where users could not just use Microsoft PowerPoint Online to author their presentation, we allowed them to integrate polls, surveys, and tests, as well as virtual whiteboards, in their online presentation. Please see this page for an overview of what and how we did it. LiberCloud offers content management and collaboration services for content authors, educators, instructors as well as active learners. The SaaS platform allows individuals to sign-up as well as it gives the ability to educational institutions and businesses to create dedicated instances and private communities for sharing or collaborating on content.
The multi-tenant SaaS platform initially developed on the LAMP stack, was being expanded with a MongoDB NoSQL cluster, Node.js component and Socket.io for asynchronous notifications, and an Ejabberd based real-time XMPP server for group discussion rooms and live-chat. The content management services support multi-media assets as well as interactive assets such as virtual whiteboards, real-time polls and surveys, and assessments. LiberCloud launched its beta services to the public in 2014 and announced the general availability at the international Bett trade-show in London in January 2015. LiberCloud service was targeting international businesses or startups with a distributed workforce, clients, and user base. Therefore, it required designing and deploying the services in a distributed fashion, such that content originated in one region is available in others, and participants in real-time virtual discussions, polls, and group chats could be in any region. LiberCloud intent to offer its services near or in the proximity of the organizations and users we serve required a distributed architecture spread across multiple geographical regions. In the age where many talent managers, educators, philosophers, and trainers have been advocating the adoption of flipped classroom training, blended learning techniques to improve assimilation of content. The main obstacles in these efforts are two-fold:
After an overview on how assessments policies have evolved, the white paper describes the facets of a new cohesive learning and assessment system to help educators implement differentiated instruction with assessments for learning, not just for grading, ultimately to achieve the goal of making sure trainees actually learn what is being taught. I introduced these concepts as guest speaker at the Assessment Tomorrow conference in London City in March 2016. A few years back I wrote a white paper documenting the effort and thoughts that went into building a first generation SaaS platform and subsequent upgrade. While new technologies have been introduced, SaaS is now widely accepted by most companies to deliver their services, and building a SaaS-based application has become increasingly easier, there are some aspects of our original effort that were unique. We developed our first SaaS platform because the traditional web application architecture was inadequate to meet our business objectives. We were in uncharted territory, and customers demanded that we would not mingle their data with other customers' data. So, a common thread in our releases was the isolation of customer data. Many customers today may require the same, for regulatory or privacy concerns, and I thought that by sharing the thoughts that went into designing the first generation SaaS platform and subsequent upgrade would benefit your efforts as well. Our first generation SaaS platform needed some basic components to improve the provisioning and configurability of the application. We needed:
After we launched the first generation platform, over the course of several months we had other important issues to tackle to ensure scalability of platform and scalability of the business processes revolving the operation of the entire SaaS platform. The most significant improvement being the decentralization of the database and ability to use Machine Learning:
Collaboration platforms have existed for years in two primary areas: to collaborate on content and to share presentations. The first is primarily used in content management systems, general purpose ones and those specific to learning, while the second is a function of web conferencing services. The two services serve the same audiences but rarely have intersected from a functional standpoint.
Here we want to make the case that the two could and should intersect, in particular in a modern working and learning environment where content is created by brainstorming, discussions, and assessments. The proposed integrated environment is a lightweight, cloud platform, based on the concepts of real-time collaboration on content and the “Virtual Whiteboard” that provides more flexibility, unleashes the attachment to any particular physical device, and is easy for anyone to use. This white paper provides an overview of its features. Today, we are showcasing LiberCloud at Bett London and announcing its official launch. I have been thinking of starting a blog detailing thoughts and events on technologies that have or will have an impact on our business and lives. This first post is about the ideas behind LiberCloud and the problems we are trying to solve.
The demands for reducing workforce skills gap and improve content assimilation are increasing and companies are faced with outdated processes and technologies to meet this challenge. Talent managers, trainers, and content developers have had to settle for narrow and outdated solutions to improve workforce skills, or for onboarding programs. For instance, instructor-led programs that did not scale, or self-paced programs that were not engaging. A new content platform is needed that combine the best of both methods. |
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