With a growing demand for customer engagement, conversational AI improves user experience and business communications as well as provides opportunities for more conversion rates, better revenues, and customer satisfaction. Creative Virtual’s Founder and CEO, Chris Ezekiel, recently talked with Sadika Sayyad and shared his views on the topic “Enhance User Experience with Conversational AI” Sadika: Brief us about your company and offerings. Chris Ezekiel: Creative Virtual is a world leader in conversational AI for customer and employee engagement. As a pioneer in the industry, we have played a pivotal role in the evolution of this technology and the ways it...

As the end of 2022 draws near, it is time once again for Creative Virtual's annual year in review blog post. Every year we take this opportunity to reflect on the hard work of our team, our contributions to the conversational AI industry, and a few of our company's biggest highlights from the past 12 months. Two of the things we are proudest of at Creative Virtual are our experienced, dedicated team and the unique expertise we provide to our customers and partners. Whether it's through our product development or our collaborations with individual clients, it's important to us that we consistently deliver the best solutions possible. Having an analyst group recognise us for this is always an exciting bonus – and that's what happened again this year.

This site is not a substitute or definitive to replace physicians' care. Not only will how clothing is made evolve, according to those involved with the art and operations of fashion, perhaps the way it's presented will also continue to evolve. Will there be major popularity with AI fashion models and figures, whether virtually or on real-life runways, that will assist us in completing our latest appearance? Will AI become an entire replacement for human fashion models? It's probably not likely that AI will completely replace human models or standard human experiences, at least not immediately, but as society and technologies evolve, the acceptability of further developments and the concerns toward sustainability may continue to create an array of new approaches, so who's really certain what's to come?

Understanding point cloud has recently gained huge interests following the development of 3D scanning devices and the accumulation of large-scale 3D data. Most point cloud processing algorithms can be classified as either point-based or voxel-based methods, both of which have severe limitations in processing time or memory, or both. To overcome these limitations, we propose Projection-based Point Convolution (PPConv), a point convolutional module that uses 2D convolutions and multi-layer perceptrons (MLPs) as its components. In PPConv, point features are processed through two branches: point branch and projection branch. Point branch consists of MLPs, while projection branch transforms point features into a 2D feature map and then apply 2D convolutions. As PPConv does not use point-based or voxel-based convolutions, it has advantages in fast point cloud processing. When combined with a learnable projection and effective feature fusion strategy, PPConv achieves superior efficiency compared to state-of-the-art methods, even with a simple architecture based on PointNet++. We demonstrate the efficiency of PPConv in terms of the trade-off between inference time and segmentation performance. The experimental results on S3DIS and ShapeNetPart show that PPConv is the most efficient method among the compared ones. The code is available at github.com/pahn04/PPConv.

Although they achieve it in different ways, they all involve new ways of interacting and experiencing our increasingly digital world. As more and more of our lives – work, socializing, shopping, entertainment – move online, these new ways of interfacing with reality mean we can experience them in ways that are richer and more immersive. In working and professional environments, this means a greater ability to collaborate on projects with colleagues in digital spaces. In entertainment, it means games and activities that feel more "real" than ever before. This digitization of our lives has accelerated greatly since the start of the pandemic, leading to a growth in interest and innovation around XR and virtual worlds.

Autodesk's Will Harris, Foundry's Mathieu Mazerolle and Unity Technologies' Brian Gaffney will discuss how their companies are incorporating machine learning into software tools to make higher quality and more realistic visual effects and boost production speed. Visual Effects Supervisor Ryan Laney will describe the novel way artificial intelligence and machine learning were used to mask the identities of interview subjects in the award-winning HBO documentary Welcome to Chechnya. "Machine learning is poised to transform visual effects production, accelerating workflows and paving the way for a new generation of astonishingly real visual effects," says Barry Goch, who will moderate the discussion. "Will Harris, Mathieu Mazerolle and Brian Gaffney will demonstrate game-changing technologies. Ryan Laney will share his experience in applying machine learning to a real-world production."