Has it really been 10 years of Siri? The Apple voice assistant was originally integrated into the iPhone 4S way back in October 2011, and we're now here to wish Siri a very happy 10th birthday. Sparking a trend for smart voice assistants across the board, Siri certainly changed how we all interact with technology these days, with the rise of Alexa no doubt helped substantially by the presence of Siri before it. It's possible that some of you won't remember the early beginnings of Siri – which is why we've taken a walk down memory lane and looked at the history behind how Siri came to be. We've also looked at just what it was like to use back in those early days, and considered what the next 10 years could mean for the (mostly) helpful voice assistant.

Artificial Intelligence (AI), one of today's most ubiquitous technologies, is one. Conversational AI (CAI), which is based on the human language, is quickly becoming the most popular frontier in this technology. Many businesses are enlisting the help of this technology to stay competitive. According to Markets and Markets, the expected global Conversational AI market size is set to grow from USD 4.8 billion in 2020 to USD 13.9 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 21.9%. Companies, leaders in the industry, and employees must understand exactly what Conversational AI is and why it's so important. Conversational AI, a subset of AI, aims to imitate human conversations and deliver a human-like experience.

Artificial intelligence (AI) used to be a fantasy, found only in science fiction. Today, it propels society forward in countless ways; even the phones in our pockets include multilingual translators, photo apps that recognize faces, and intelligent assistants that can understand spoken commands (thanks, Siri). This is all made possible through the process of deep learning -- and Dr. Pablo Rivas, an assistant professor of computer science at Baylor, has literally written the book on the subject. "I first fell in love with the field of AI and the principles that can explain human intelligence 20 years ago, when it was all beginning," says Rivas. "Now, the industry is booming. And while the advances are incredible, they can also be a little disarming."

From Google and Amazon to Apple and Microsoft, every major tech company is dedicating resources to breakthroughs in artificial intelligence. Personal assistants like Siri and Alexa have made AI a part of our daily lives. Meanwhile, revolutionary breakthroughs like self-driving cars may not be the norm, but are certainly within reach. As the big guys scramble to infuse their products with artificial intelligence, other companies are hard at work developing their own intelligent technology and services. The AI industry even broke records during the global uncertainty of the COVID-19 pandemic, with artificial intelligence startups raising $33 billion in 2020, according to CB Insights.

In the digital world, the consumer industry is heavily powered by virtual assistants and chatbots. Will you believe it if I tell you that chatbots came into existence in 1966? An MIT professor called Joseph Weizenbaum introduced the first chatbot, ELIZA, back in the 1960s. ELIZA used substitution methodology and pattern matching to simulate conversation. Almost six decades later, artificial intelligence developments are powering virtual assistant and chatbot predictions.

For the past two years, the LA-based voice actor has run a sort of reverse call centre, deliberately ringing the people most of us hang up on – scammers who pose as tax agencies or tech-support companies or inform you that you've recently been in a car accident you somehow don't recall. When Okumura gets a scammer on the line, she will pretend to be an old lady, or a six-year-old girl, or do an uncanny impression of Apple's virtual assistant Siri. Once, she successfully fooled a fake customer service representative into believing that she was Britney Spears. "I waste their time," she explains, "and now they're not stealing from someone's grandma." Okumura is a "scambaiter" – a type of vigilante who disrupts, exposes or even scams the world's scammers.

Dear Abby: I am a man in my late 40s who has been looking for love all my life. One factor that has made it difficult is my height. What makes finding someone nearly impossible is that the online dating site profiles always ask for my height. Unfortunately, being extremely short in stature isn't a characteristic women are looking for, so even though I can spend upward of an hour filling out all that profile information, the system invariably returns a no-match for me. Do you think I should lie about my height, and when I meet the person, hopefully she can give me a chance?

When we hear the word Artificial Intelligence (AI), our minds automatically create images of robots. Not all AI is in the form of robots, it can also be in the form of voice detectors, image processors, smart assistants, etc. As much as we claim to know what AI is, we don't have a full grasp of how our lives are steadily becoming dependent on it nowadays. From relying on Netflix to suggest your next movie to watch, to asking Siri to play your favorite song, and using Google Map to get to your location, you'll agree that AI makes living easier. Now let's take you through 5 Eye-opening Facts about AI to Help You Understand it Better… Sure you've found yourself in a situation where for example, you searched Google or an e-commerce website for the specification of a device, clothing, etc. with the intention of maybe buying it.

Ever-increasing smartphone-generated video content demands intelligent techniques to edit and enhance videos on power-constrained devices. Most of the best performing algorithms for video understanding tasks like action recognition, localization, etc., rely heavily on rich spatio-temporal representations to make accurate predictions. For effective learning of the spatio-temporal representation, it is crucial to understand the underlying object motion patterns present in the video. In this paper, we propose a novel approach for understanding object motions via motion type classification. The proposed motion type classifier predicts a motion type for the video based on the trajectories of the objects present. Our classifier assigns a motion type for the given video from the following five primitive motion classes: linear, projectile, oscillatory, local and random. We demonstrate that the representations learned from the motion type classification generalizes well for the challenging downstream task of video retrieval. Further, we proposed a recommendation system for video playback style based on the motion type classifier predictions.

Research interest in Conversational AI has experienced a massive growth over the last few years and several recent advancements have enabled systems to produce rich and varied turns in conversations similar to humans. However, this apparent creativity is also creating a real challenge in the objective evaluation of such systems as authors are becoming reliant on crowd worker opinions as the primary measurement of success and, so far, few papers are reporting all that is necessary for others to compare against in their own crowd experiments. This challenge is not unique to ConvAI, but demonstrates as AI systems mature in more "human" tasks that involve creativity and variation, evaluation strategies need to mature with them. Conversational AI, or ConvAI as it has been abbreviated, is a sub-field of artificial intelligence (AI) where the goal is to build an autonomous agent that is capable of maintaining natural discourse with a human over some interface such as text or speech. The purpose may be to help humans perform tasks as a virtual/digital assistant, provide a natural language interface to another system as in information retrieval or navigation systems, or simply to converse like one would with an open domain chatbot.