Xdroid receives innovation award for emotion-detecting AI
AI company Xdroid’s Voice Analytics solution has been recognised for its AI-powered voice and facial analytics.
Consultants Frost & Sullivan awarded the company the 2020 Europe Technology Innovation Leadership Award, which is awarded yearly to a company developing an innovative product that receives rapid traction in their respective markets
Machine learning applications
The solution uses deep neural networks and machine learning algorithms to analyse acoustic information and improve the performance of contact centres, with capabilities including accurate speech-to-text and keyword recognition.
In a press release, Arnaud Bossy, Vice President at Frost & Sullivan, said: "Instead of simply transcribing to text, Xdroid built its language engine on a DNN base that is the latest generation of machine learning algorithms that efficiently use processing power and performance to present real-time results and suggestions to agents.”
"Xdroid offers the technology as an online real-time AgentAssist and an offline VoiceAnalytics. The real-time AgentAssist advises agents in the conversation with pop-up suggestions and alerts, and automated lookup functions to offer quick access to relevant information. It also guides agents to an ideal speech rate and volume and can perform an automated wrap-up to reduce the average handling time significantly. The offline VoiceAnalytics optimizes hardware usage and provides complex analytics after the event."
Real world deployment
Xdroid’s Voice Analytics solution has been deployed in contact centre operations for major companies in industries such as insurance, telecommunications and utilities.
"In addition to the highly scalable solutions, Xdroid is agile and can tailor deployments to customer needs," said Nick Baugh, Best Practices Research Analyst at Frost & Sullivan. "The granularity of Xdroid's processing capabilities informs and enables deep analytics, applicable to performance at the individual and organizational levels. The dashboard displays high-level core indicators such as compliance levels, productivity, and escalation requests. The analytics module can present a clear overview and definable levels of depth and categorizations. Overall, Xdroid draws on its significant industry expertise and next-generation technologies to deliver valuable insights and uniquely address customer needs."
Google launches Visual Inspection AI tool for manufacturers
Google Cloud has launched Visual Inspection AI, a new tool to help manufacturers identify defects in products before they're shipped.
Poor production quality control often leads to significant operational and financial costs. The American Society for Quality estimates that for many organisations this cost of quality is as high as 15-20% of annual sales revenue, or billions of dollars annually for larger manufacturers. Google Cloud’s new Visual Inspection AI solution has been purpose-built for the industry to solve this problem at production scale.
How does it work?
The Google Cloud Visual Inspection AI solution automates visual inspection tasks using a set of AI and computer vision technologies that enable manufacturers to transform quality control processes by automatically detecting product defects.
Google built Visual Inspection AI to meet the needs of quality, test, manufacturing, and process engineers who are experts in their domain, but not in AI.
- Run autonomously on-premises: Manufacturers can run inspection models at the network edge or on-premises. The inspection can run either in Google Cloud or fully autonomous on your factory shop floor.
- Short time-to-value: Customers can deploy in weeks, not the months typical of traditional machine learning (ML) solutions. Built for process and quality engineers, no computer vision or ML experience required. An interactive user interface guides users through all the steps.
- Superior computer vision and AI technology: In production trials, Visual Inspection AI customers improved accuracy by up to 10x compared with general-purpose ML approaches, according to benchmarks from several Google Cloud customers.
- Get started quickly, with little effort: Visual Inspection AI can build accurate models with up to 300x fewer human-labeled images than general-purpose ML platforms, based on pilots run by several Google Cloud customers.
- Highly scalable deployment: Manufacturers can flexibly deploy and manage the lifecycle of ML models, scaling the solution across production lines and factories.
Industry use cases
The demo video shows how Visual Inspection AI addresses use cases to solve specific quality control problems in industries such as automotive manufacturing, semiconductor manufacturing, electronics manufacturing and general-purpose manufacturing.
Kyocera Communications Systems, a manufacturer of mobile phones for wireless service providers, has been able to scale its AI and ML expertise through the use of the solution. “With the shortage of AI engineers, Visual Inspection AI is an innovative service that can be used by non-AI engineers,” said Masaharu Akieda, Division Manager, Digital Solution Division, KYOCERA Communication Systems. “We have found that we are able to create highly accurate models with as few as 10-20 defective images with Visual Inspection AI. We will continue to strengthen our partnership with Google to develop solutions that will lead our customers' digital transformation projects to success.”
Visual Inspection AI has fully integrated with Google Cloud's portfolio of analytics and ML/AI solutions, giving manufacturers the ability to combine its insights with other data sources. The tool integrates with existing products from Google Cloud partners, including SOTEC, Siemens, GFT, QuantiPhi, Kyocer and Accenture.