Sense | July 26, 2022
Sense, the market leader in AI-driven talent engagement solutions for enterprise recruiting, uncovers the role and impact that Conversational AI and chatbots have in today’s competitive recruiting landscape. The research was conducted in collaboration with Talent Board, the first non-profit research organization focused on the elevation and promotion of a quality candidate experience.
To better understand how talent acquisition teams are coping with the pressures of attracting and communicating with qualified candidates, Sense and Talent Board surveyed over 350 HR and talent acquisition leaders across industries. The resulting data uncovered that the number one challenge for recruiting teams today was connecting and engaging with passive talent (42%) and that the most successful method in contacting and communicating with candidates was via chatbots and Conversational AI (36%). As corporations throughout the U.S. continue to experience critical labor shortages, impactful engagement and communications is the key to driving meaningful candidate experiences - and to accelerate hiring.
Additional findings from the Sense and Talent Board Research Report, “How Chatbots and Conversational AI Improve Talent Engagement and the Candidate Experience” include:
Making the Case for Chabot Implementation
The top three reasons corporations have implemented chatbot technology are to:
Improve the responsiveness of their candidate communications (61%)
Free up recruiters’ time and enhance their productivity (54%)
Enhance the overall quality of the candidate experience (45%)
Measuring Successful Communication and Engagement Benefits of Chatbots
51% of respondents cite a “significant improvement” in candidate satisfaction as a direct result of implementing their chatbots;
49% say their chatbots have enhanced the overall quality of their company’s candidate experience;
35% say chatbots have freed up recruiters’ time and enhanced their productivity.
“Enterprise leaders must understand that quick and intuitive candidate engagement is essential to finding, attracting and hiring qualified candidates,” explained Anil Dharni, CEO and Co-Founder of Sense. “In fact, 51% of talent acquisition leaders say their use of chatbots improved the responsiveness of their candidate communications. To remain competitive, talent acquisition teams must activate cutting edge technologies like Conversational AI and Chatbots to significantly improve the communication flow and attract high quality candidates.”
Chatbots are engineered to enhance a talent acquisition team’s responsiveness and to make this communication feel more natural and personal. When used in the early stages of talent attraction and engagement, chatbots also free up talent acquisition team’s time to attend to time sensitive recruiting matters.
Additional benefits of implementing conversational AI chatbots reported include:
29% -- Accelerating the overall hiring process
27% -- Helping candidates better identify their open job preferences
26% -- Automating the interview scheduling
24% -- Helping candidates submit their job applications easier
21% -- Providing candidates updates about their application throughout various stages of the recruiting process
“Timely and consistent candidate communication is always a critical competitive differentiator in recruiting and hiring,” said Kevin Grossman, Talent board President. “For companies with any hiring volume, smart automation with conversational AI chatbots can help scale candidate engagement from pre-application to onboarding. And each year in our benchmark research we find that candidate sentiment is much more positive when they get questions answered in a timely manner – over 50% more positive.”
Sense and Talent Board surveyed HR and talent acquisition leaders and their teams around the world regarding their efforts to better engage and communicate with qualified candidates and enhance the candidate experiences they’re delivering in 2022. We received a total of 350 anonymous survey responses online from May 15, 2022 to June 15, 2022, representing input from companies of all sizes and across a wide range of industries.
Sense delivers a leading AI-powered talent engagement platform that helps recruiting and talent teams to personalize their interactions with talent at every stage of the recruiting process. More than 700 organizations including Amazon, Dell, Kelly Services, Kindred Healthcare, and Sears rely on Sense to help accelerate hiring, strengthen their employment brand and exceed recruiting targets - all while delivering a personalized candidate experience.
About Talent Board
Founded in 2011, Talent Board and the Candidate Experience Awards is the first non-profit research organization focused on the elevation and promotion of a quality candidate experience. Talent Board delivers annual recruiting and hiring industry benchmark research that highlights accountability, fairness and the business impact of candidate experience.
DDN | July 04, 2022
DDN®, the global leader in artificial intelligence (AI) and multi-cloud data management solutions, today announced that it has received its third consecutive "AI Hardware Innovation Award" in the annual AI Breakthrough Awards program conducted by AI Breakthrough, a leading market intelligence organization that recognizes technological and product leadership in global AI and AI-driven digital transformation markets.
DDN was recognized for its A3I® (Accelerated, Any-Scale AI) AI400X2 system, which has been instrumental in bringing unmatched operational excellence for enterprise digital transformation initiatives in AI, financial services, healthcare, manufacturing, autonomous driving, research, and other enterprise IT infrastructures. DDN has delivered powerful, easy-to-deploy, market-leading AI storage and data management solutions to thousands of organizations globally.
"As organizations develop increasingly sophisticated AI applications and introduce new data types into their analysis, they seek faster and more scalable storage systems that can transparently provide data services to a wider variety of users and systems," said James Johnson, managing director, AI Breakthrough. "The all new AI400X2 appliance from DDN addresses these needs, simplifying deployment for anyone looking to remove complexity from their AI initiatives. It's no wonder companies around the world rely on DDN for their unique combination of advanced capabilities, performance, and ease of management for AI and analytics applications. Congratulations to DDN on a third 'AI Hardware Innovation Award.'"
The AI400X2 doubles the performance over the previous generation, making it an even more efficient building block for companies looking to take their AI applications into production. Additionally, DDN adds significant intelligent AI capabilities including granular insight and optimization capabilities into enterprise AI workloads, client GPU-level performance boost, simplified configuration management and system monitoring. Building these services on top of an optimized data path, AI400X2 accelerates AI and analytics driven workloads for organizations and research facilities globally.
"DDN's next-gen A3I solutions were designed to provide our enterprise customers with the best AI-driven digital transformation storage and data management framework, and the most scalable, reliable and efficient AI data storage platform on the planet," said Dr. James Coomer, senior VP of products, DDN. "It is an honor to be a winner of the 'AI Hardware Innovation Award' for the third year in a row, and it's a testament to our commitment to continuous improvement on solutions like the AI400X2 that will help our customers get into production faster and reduce time to results as well as remove the complexity from their AI initiatives."
Providing high-performance AI-optimized storage for thousands of NVIDIA DGX™ systems globally, DDN A3I appliances are packaged to provide the same capabilities for any customer regardless of size. The enhanced speed, efficiency and intelligence of the upgraded A3I system moves organizations toward an increasingly hands-off approach to AI application management that improves overall customer experience without sacrificing security.
The AI400X2 is an all-NVMe appliance designed to help customers extract the most value from their AI and analytics data sources and is already proven in production at the largest scale. Configurable as all-flash or hybrid, customers can build efficient scale-out AI data pools tuned to their exact performance and capacity needs. Each base appliance is available with 30, 60, 120, 250, and 500TB flash capacity configurations, and can be expanded to 16PB capacity with up to 10 expansion enclosures.
Additionally, DDN, in collaboration with NVIDIA, recently released updated NVIDIA DGX POD™ and NVIDIA DGX SuperPOD™ reference architectures. These new designs build on the success of the already proven DGX SuperPOD, and give customers a highly optimized data storage and data management system for AI which enhances and accelerates business insight while eliminating infrastructure complexity.
The mission of the AI Breakthrough Awards is to honor excellence and recognize the innovation, hard work and success in a range of AI and machine learning related categories, including AI platforms, deep learning, smart robotics, business intelligence, natural language processing, industry-specific AI applications and many more. This year's program attracted more than 2,950 nominations from over 18 different countries throughout the world.
A list of all the featured winners for the 2022 AI Breakthrough Awards can be found here: AI Breakthrough 2022 Award Winners.
About AI Breakthrough
Part of Tech Breakthrough, a leading market intelligence and recognition platform for global technology innovation and leadership, the AI Breakthrough Awards program is devoted to honoring excellence in Artificial Intelligence technologies, services, companies and products. The AI Breakthrough Awards provide public recognition for the achievements of AI companies and products in categories including AI Platforms, Robotics, Business Intelligence, AI Hardware, NLP, Vision, Biometrics and more.
DDN is the world's largest private data storage company and the leading provider of intelligent technology and infrastructure solutions for Enterprise At Scale, AI and analytics, HPC, government and academia customers. Through its DDN and Tintri divisions, the company delivers AI, data management software and hardware solutions, and unified analytics frameworks to solve complex business challenges for data-intensive, global organizations. DDN provides its enterprise customers with the most flexible, efficient and reliable data storage solutions for on-premises and multi-cloud environments at any scale. Over the last two decades, DDN has established itself as the data management provider of choice for over 11,000 enterprises, government, and public-sector customers, including many of the world's leading financial services firms, life science organizations, manufacturing and energy companies, research facilities, and web and cloud service providers.
Mobileye | July 06, 2022
Mobileye, an Intel company, has launched the EyeQ Kit™ – its first software development kit (SDK) for the EyeQ® system-on-chip that powers driver-assistance and future autonomous technologies for automakers worldwide. Built to leverage the powerful and highly power-efficient architecture of the upcoming EyeQ®6 High and EyeQ®Ultra processors, EyeQ Kit allows automakers to utilize Mobileye's proven core technology, while deploying their own differentiated code and human-machine interface tools on the EyeQ platform.
“EyeQ Kit allows our customers to benefit from the best of both worlds — Mobileye's proven and validated core technologies, along with their own expertise in delivering unique driver experiences and interfaces. As more core functions of vehicles are defined in software, we know our customers will want the flexibility and capacity they need to differentiate and define their brands through code.”
Prof. Amnon Shashua, Mobileye president and chief executive officer
How it Works: Through EyeQ hardware and software, automakers have access to a broad set of Mobileye solutions, including computer vision, REM™ crowdsourced mapping, and RSS-based driving policy. Using EyeQ Kit, automakers can further leverage the power of Mobileye’s system-on-chip to augment the advanced driver functions with a look and feel that is unique to their brands. And as the visual demands for interaction and communication between drivers and vehicles grows more complex, EyeQ Kit gives automakers a new path to tailor critical information flows. EyeQ Kit will help support features such as surround visualization, automated lane-keeping, and road-sign recognition through more advanced augmented reality displays.
EyeQ Kit was developed by hundreds of Mobileye engineers drawing on deep experience across Intel and Mobileye, with experts in compilers and development environments such as OpenCL standards, leveraging compilation frameworks used for intensive computing and deep learning. This approach allows automakers to develop their own applications easily and efficiently. It also opens the ability to co-host third-party applications, which lowers the costs of integrating other chips.
Why it Matters: From general-purpose CPU cores to high compute-dense accelerators – including deep-learning neural networks – EyeQ has a scalable and modular architecture that seeks to achieve high performance while offering a suitable power efficiency to deploy artificial intelligence at the edge for automotive applications. Previous generations of the EyeQ chip have been deployed in more than 100 million vehicles, with dozens of the world’s largest automakers using them to provide safety and driver-assistance features in hundreds of models worldwide.
Now, EyeQ Kit aims to reduce development costs, accelerate time to market and enable hardware vendor flexibility for the full development cycle – from conception to deployment and performance tuning.
“Mobileye’s core technologies of computer vision, driving policy, REM and RSS are driven by purpose built SoCs allowing for scale and efficiency. Automakers can now build on top of Mobileye’s core technologies while benefiting from our diverse set of accelerators purpose built for ADAS and AV. Automakers can rely on the EyeQ Kit and EyeQ processor family to bring a technologically advanced vision for their brands to life, quickly and efficiently,” Shashua said.
EyeQ Kit has already been deployed with one major global automaker for future vehicle programs.
Mobileye is a leader in the development and deployment of advanced driver assistance systems (ADAS) and autonomous driving technologies and solutions. Mobileye pioneered ADAS technology more than 20 years ago and has continuously expanded the scope of its ADAS offerings, while leading the evolution to autonomous driving solutions.
Intel is an industry leader, creating world-changing technology that enables global progress and enriches lives. Inspired by Moore’s Law, we continuously work to advance the design and manufacturing of semiconductors to help address our customers’ greatest challenges. By embedding intelligence in the cloud, network, edge and every kind of computing device, we unleash the potential of data to transform business and society for the better. To learn more about Intel’s innovations, go to newsroom.intel.com and intel.com.
Deci | September 26, 2022
Deci, the deep learning company harnessing AI to build AI, today announced a new set of industry-leading semantic segmentation models, dubbed DeciSeg. Deci’s proprietary Automated Neural Architecture Construction (AutoNAC) technology automatically generated semantic segmentation models that significantly outperform the most powerful models publicly available, such as the MobileViT released by Apple, and the DeepLab family released by Google. Deci’s models deliver more than 2x lower latency, as well as 3-7% higher accuracy.
Semantic segmentation is one of the most widely used computer vision tasks across many business verticals, including automotive, smart cities, healthcare, and consumer applications, and is often required for many edge AI applications. However, significant barriers exist to running semantic segmentation models directly on edge devices, such as high latency and the inability to deploy those models due to their size.
With DeciSeg models, semantic segmentation tasks that previously could not be carried out at the edge because they were too resource intensive are now possible. This allows companies to develop new use cases and applications on edge devices, reduce inference costs (since AI practitioners will no longer need to run these tasks in expensive cloud environments), open new markets, and shorten development times.
“DeciSegs are an example of the power of Deci’s AutoNAC engine capabilities to generate custom hardware-aware deep learning models with unparalleled performance on any hardware. AI teams can easily use DeciSegs models or leverage Deci’s AutoNAC engine to build and deploy custom models that run real-time computer vision tasks on their edge devices.” said Yonatan Geifman, PhD, co-founder and CEO of Deci.
Deci’s platform has a proven-track record in enabling AI at the edge and empowering AI teams to build and deploy production grade deep learning models. Earlier this year, Deci announced the discovery of DeciNets for CPUs, which reduced the gap between a model’s inference performance on a GPU versus a CPU by half, without sacrificing the model’s accuracy, enabling AI to run on lower cost, resource constrained hardware.
“In the world of automated deep neural network design and construction, Deci’s AutoNAC technology is a game changer. It uses deep learning to search vast spaces of neural networks for the model most appropriate for a particular task and particular AI chip. In this case, AutoNAC was applied to the Pascal VOC Semantic Segmentation task on NVIDIA’s Jetson Xavier NX™ chip and we are very pleased with the results.” said Ran El-Yaniv, co-founder and Chief Scientist of Deci and Professor of Computer Science at the Technion – Israel Institute of Technology.
Deci’s platform is serving customers across industries in various production environments including edge, mobile, data centers and cloud. To learn more about how leading AI teams leverage Deci’s platform to build production grade models and accelerate inference performance, visit here.
Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company's deep learning development platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to revolutionize industries with innovative products. The platform is powered by Deci's proprietary automated Neural Architecture Construction technology (AutoNAC), which automatically generates and optimizes deep learning models' architecture and allows teams to accelerate inference performance, enable new use cases on limited hardware, shorten development cycles and reduce computing costs. Founded by Yonatan Geifman, Jonathan Elial, and Professor Ran El-Yaniv, Deci's team of deep learning engineers and scientists are dedicated to eliminating production-related bottlenecks across the AI lifecycle.