Group conversations over videoconferencing are a complex social behavior. However, the subjective moments of negative experience, where the conversation loses fluidity or enjoyment remain understudied. These moments are infrequent in naturalistic data, and thus training a supervised learning (SL) model requires costly manual data annotation. We applied semi-supervised learning (SSL) to leverage targeted labeled and unlabeled clips for training multimodal (audio, facial, text) deep features to predict non-fluid or unenjoyable moments in holdout videoconference sessions. The modality-fused co-training SSL achieved an ROC-AUC of 0.9 and an F1 score of 0.6, outperforming SL models by up to 4% with the same amount of labeled data. Remarkably, the best SSL model with just 8% labeled data matched 96% of the SL model's full-data performance. This shows an annotation-efficient framework for modeling videoconference experience.

The Conversational AI space has made great strides in the underlying technologies, use cases, and adoption. We are moving past the days of basic question and answer experiences and simple decision trees. Chatbots, voice assistants, and Interactive Voice Response (IVR) solutions have advanced to incorporate sophisticated Natural Language Understanding (NLU) that not only understands a user's Intent, but enables the chatbot to respond appropriately in a way that satisfies the user. Conversational AI solutions are used across a wide variety of use cases and industries -- including customer service, appointment booking, triaging medical symptoms, signing up for an account, and more. The demand for conversational AI continues to grow as users prefer to communicate over digital channels. Businesses are developing chatbots, voice assistant, and IVR experiences to increase customer satisfaction, reduce operational costs, and achieve business goals.

How conversational AI has evolved, and why it is rapidly redefining how customers interact with businesses. Imagine if customers could talk to a business whenever they need something, not just during working hours, not just when a human is available, and not just through protracted processes. People have conversations in person or via text, phone, video chats--the obstacles have never been lower. But when it comes to interacting with a business, points of friction are more numerous, with customers often forced to peruse bespoke websites and apps, deal with phone trees, wait for email responses, or accommodate the limited availability of human staff during business hours. That needn't be the case: it's time for organizations to reevaluate the role of conversational AI in customer experiences.

If you've seen Sci-Fi movies, you very well "know" what AI is! Machines and computers hell-bent on taking over the world and wiping out the human race! Well, they're just fictional movies, so no need to take them that seriously! On a more serious note, AI simply stands for Artificial Intelligence. It's the ability of a computer system, or a machine, to carry out functions that would usually have required human intelligence. To help you better understand the world of AI, we discuss how AI is being used today to help make our day-to-day lives that much easier and simpler.

Do you ever ask Siri if it's going to rain tomorrow? Or ask Alexa to play your favourite song? For millions of us, having conversational interactions with technology has quickly become second nature. This presents a real challenge for many financial institutions, whose traditional, interactive voice response (IVR) systems often fall far below the expectations set by the voice-enabled virtual assistants of their customers' smartphones and smart speakers. Even as banks race to deliver intelligent, conversational self-service over the telephone, they must also work to keep pace with the digital services of online banks and fintech pioneers.

All the sessions from Transform 2021 are available on-demand now. Conversational messaging platform Gupshup today announced that it raised $240 million led by Tiger Global Management, with participation from Fidelity Management, Think Investments, Malabar Investments, Harbor Spring Capital, and others. The tranche, which values the company at $1.64 billion, will be used to build new tools, infrastructure, and services while expanding Gupshup's global reach, CEO Beerud Sheth said. The pandemic has accelerated digital transformation for enterprises, in some cases driving the need for messaging services. Offline businesses are moving online while online businesses are offering more products, and both are looking for tools to better engage customers.

LivePerson, a provider of conversational artificial intelligence technologies, and Tech Mahindra, a provider of digital customer experience solutions, are partnering to help companies deliver marketing, sales, and customer service journeys on the conversational channels consumers prefer. "It's now clear that every brand must build a digital strategy going beyond 800 numbers and traditional websites to survive, let alone thrive. We're excited to partner with Tech Mahindra to amplify the reach of conversational AI and messaging, the keys brands need to unlock true digital transformation," said Rob LoCascio, CEO and founder of LivePerson, in a statement. Tech Mahindra has also built a center of excellence to help companies onboard and operationalize LivePerson's Conversational Cloud for conversational experiences across verticals, including conversational experiences like proactive two-way messaging campaigns, augmented and virtual reality, and conversational ads. "Our partnership with LivePerson offers brands disruptive, end-to-end managed services for sales, marketing, and customer care. With consumers increasingly demanding conversational models for engagement and commerce, we're here to help," said Ritesh Idnani, president of Tech Mahindra, in a statement.

As the pandemic has propelled digital banking adoption among consumers, it has also created an openness to new types of digital interactions. Banks have taken notice, and as they work to better meet customer needs while operating more efficiently, customer service channels have emerged as an area ripe for automation and enhancement. In large part, conversational AI technology will drive this by providing a digital-first channel for customer service engagement that offsets more traditional in-branch and call center interactions. Conversational AI holds the potential to unlock the hyper-personalized experiences that consumers crave. Here's more on what we expect to see, and how banks can benefit by weaving conversational AI into their digital strategies. A shift away from static information: Traditionally, financial information has been presented in a static view, which forces users to interact in a one-dimensional way.

Understanding the direction and context of an ever-evolving conversation is beneficial to building natural, human-like conversational interfaces. Being able to classify utterances as the conversation develops requires managing context across multiple turns. Consider a caller who asks their financial planner for insights regarding their monthly expenses: "What were my expenses this year?" They may also ask for more granular information, such as "How about for last month?" As the conversation progresses, the bot needs to understand if the context is changing and adjust its responses accordingly.

Unlike humans, conversational artificial intelligence (AI), most commonly deployed today via chatbots, are "up" 100% of the time. Beyond chatbots, automated voice response systems (as annoying as they may still be) and virtual voice assistants all utilize conversational AI to power human-to-machine dialog. Conversational AI is the technology that allows users to ask queries to a machine and get automated responses. The most notable of these machines are the virtual assistants such as Alexa, Siri, and Google Assistant. At the heart of Conversation AI, is the utilization of Natural Language Processing (NLP).