Daily Archives: October 13, 2022

I was at Intels powerful Israel Development Centre (IDC) recently, and it is a fascinating place. Pat Gelsinger, Intels CEO, is positioning IDC as the heart of Intel to address long-term diversity issues.

Israel has a culture where women are treated more equally than most other geographies I have studied, and IDC has an unusually high level of women engineers in senior operational and development roles. One of the ways you effectively break a glass ceiling is to start at the top. And Gelsinger is using IDC as a template for change across Intel, which has significantly, based on my conversations with Intel employees, changed Intels culture for the better. In effect, IDC is leading Intels renaissance as the company positions for a far better future.

This is having a significant impact on product direction, with a sharp focus on applied artificial intelligence (AI) at the edge. And the next generation of PCs that will make use of the related advancements will, as a result, be significantly improved in several ways.

Here are some of the improvements that Intels IDC group shared during my visit:

Intel showcased both improvements in camera resolution and auto-centering. When you are doing a video conference, the quality of the camera has a direct impact on how you are perceived by others. But we all have lighting, centering, focus, and connectivity issues. Using their AI capabilities, IDC demonstrated significant improvements over similar products in both auto-framing and resolution.

Better video quality is not only critical for how you look, but for anything you are sharing. While we are still working in hybrid form, the ability to share what the PCs camera sees with teammates without requiring a second camera particularly when you are using a laptop and dont have a separate camera could be very important if you do that a lot.

It is interesting to note that Intel went into video conferencing long ago and struggled with video quality. It is fascinating that Intel, decades later, has addressed this endemic issue, and it is working in some of the latest Intel-based products.

Another interesting video conferencing use of AI is better use of the PCs multiple radios. Not only will the future PC be able to connect to multiple Wi-Fi 6 connections, but also 5G simultaneously. So if you are in a meeting, it can aggregate the wireless connections and get a near optical cable level of performance. Should you lose all but one of those connections, the video will, after a short pause, continue without dropping the call.

Another use of AI that was demonstrated was the use of Wi-Fi as a proximity detector to better secure the privacy of your PC.

Using Wi-Fi, the PC will be able to tell when you are close to the PC and when you leave, either waking up the PC when you sit down in front of it or suspending and securing the PC when you leave your desk.

This reminded me that when I first started working in the tech industry, I used to go in and play pranks on my boss when he left his PC unsecured. My favorite prank was to load an app that caused the letters on his screen to increasingly fall off the screen, as if there was failing adhesive holding them on. Thinking back, I am surprised I did not get fired for doing that.

But in use, this is cool. When you approach, the PC starts to power up, and in a few seconds, it is ready to log you in. If you have used Microsoft Hello for facial recognition, you are back to work and functioning again without the risk that someone had access to your stuff while you were away. It is impressively quick.

While these camera capabilities have already appeared on some of Microsofts Surface products and HPs Dragonfly line, most of these features will appear in the next generations of laptop and desktop PCs.

And this is only the beginning, as Intel and others continue to develop AI capabilities that will become more prevalent in PCs, like being able to automatically author papers from outlines and create unique images by simply describing what you want to create.

What Intel is doing is just the beginning of applied AI in PCs. Whats to come from Intel and other vendors will be even more amazing.

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Intel and How AI is Transforming the PC - Datamation

Deepak Gaddipati is founder and chief technology officer at VirtuSense, an artificial intelligence company that aims to transform healthcare from reactive to proactive, alerting care teams of adverse events, such as falls, sepsis and heart attacks, before they occur.

Gaddipati invented the first commercial full-body, automated, AI-powered scanning system, which is widely deployed across most U.S. airports.

He is steeped in the power of AI. Healthcare IT News sat down with Gaddipati to discuss some of his work in healthcare with AI and where he sees the technology headed.

Q. You invented the full-body scanning system. You suggest you can take this AI technology from airports to healthcare and improve efficiencies and drive better outcomes. How?

A. AI already is around us it's in our cars, TVs, phones, favorite streaming services and much more. AI enables these devices to interpret data and make informed, unbiased decisions.

Just as airport security systems use this data interpretation to automate security processes, AI can do the same in healthcare. With AI, you can proactively and efficiently identify any threats before they become detrimental. It's a matter of training AI to find the data you care about.

Airport scanners are trained to find "never events," such as weapons, illegal substances, etc., making their way onto the plane. The same vision can be applied to AI in healthcare. With millions of data points captured for a single patient, healthcare providers can proactively and efficiently protect patients from medical threats and adverse events such as falls, sepsis, heart attacks and pressure ulcers by training AI to identify the data pattern that indicates that malady.

Today's healthcare system is built on sick care. With AI, we can help transition care to healthcare through early detection of these and many other medical conditions.

Q. You have a mission to prevent falls because sadly your grandmother fell and within 10 days passed away. How does AI technology help prevent falls?

A. Yes, my mission to prevent falls is very personal. In 2009, my grandmother, who was healthy and had no severe medical issues, fell while walking to the bank and broke her hip. She died within ten days of the injury.

Even though there were several physicians in our family, she had never been offered existing interventions because she was never identified as a fall risk in the first place. Generally speaking, to be identified as a fall risk, you must first fall, and for many people, that is too late. So many people across the country have similar stories.

So, I wanted to develop AI solutions that prevent falls both in the long term and short term. For the long term, it was about being able to identify and take care of deficits before they become severe, and making that detection accurate, efficient and seamless, so it would be used.

Medicine has standardized tests and assessments for balance and function, but they take time to set up and conduct, and there's always room for human error. So, combining those evidence-based assessments for gait, balance and function with a highly specific AI trained for the smallest variants meant patients' mobility deficits could be proactively identified before they fall. From there, doctors can develop a care plan to help regain strength and mobility.

Short-term fall prevention stopping falls just before they happen is trickier. Proactive detection of an individual trying to get up from a bed or chair is essential as that is the vital moment. By collecting millions of hours of data on what people do before they get up from a bed or chair, AI tools can be trained to proactively detect if a person is going to get up from the bed or chair.

From there, tools need to interface with other tech capabilities, immediate alerting, communication with patients, and nurse coordination. It takes many different pieces to create an AI tool that really works in practice.

It is important to understand that not all AI is the same. Many of the solutions on the market are reactive, detecting and analyzing an event upon its completion. The next level is an AI solution that detects the moment before the event happens to really make care preventative and proactive.

Q. How can AI solve challenges plaguing healthcare today, such as staffing shortages and skyrocketing costs?

A. Healthcare organizations are feeling a squeeze on all sides right now from staffing challenges to rising costs, so it is vital that the tools they adopt actively address both concerns. AI, as a tool, is particularly good at tackling routine problems.

Preventable events, such as hospital-acquired infections and patient falls, are perfect examples of problems that get worse with staffing and resource shortages and are perfectly suited for AI intervention.

For instance, many hospital fall-prevention strategies currently rely on employing bedside sitters and tele-sitters to monitor patients who are at risk of falling. Both approaches rely on staff to stay vigilant while performing mundane work, while also taking those employees out of an active care role.

AI specializes in 24/7 vigilance and pattern recognition, making it a perfect tool to maintain safety and get employees back to performing care, instead of waiting to perform care. AI can transform hours of watching, waiting and record-keeping into a direct notification when action is needed, saving time and relieving task overload from nursing teams.

From a cost perspective, reducing adverse health events directly eases financial strain. To use falls as an example, patients over the age of 65 are 33% more likely to fall. On average, 20% of those who fall will get a major injury. The cost of treating these major falls averages around $34,000 per instance.

On top of this, an elderly person that falls has a 70% likelihood of dying as a result of complications from their fall. Statistically, falls will happen and 20% of those falls will cost the organization financially through direct care costs, staff hours, quality penalties and insurance claims.

Today, the cost of monitoring high-risk patients with sitters or tele-sitters can become astronomical and certainly unfeasible for patients who are classified as lower risk. But when you introduce AI, unit-wide monitoring even hospital-wide monitoring becomes financially feasible, doesn't require increasing staffing and prevents falls. The same can be said for solutions that use AI to prevent pressure ulcers, sepsis and other standard hospital risks.

Leveraging AI to transform healthcare is the future. There are numerous studies showing an uptick in AI being used across the industry.

I most recently came across the 3rd Annual Optum Survey on AI in Health Care report that stated 83% of healthcare executives already have an AI strategy, and another 15% plan to implement one. Fifty-nine percent of the respondents stated they expect to see tangible cost savings from AI which is a 90% jump compared to those surveyed in 2018.

Twitter:@SiwickiHealthITEmail the writer:bsiwicki@himss.orgHealthcare IT News is a HIMSS Media publication.

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AI in healthcare: from full-body scanning to fall prevention - Healthcare IT News

REDMOND, Wash. Oct. 12, 2022 On Wednesday, Haleon, a global leader in consumer health, and Microsoft Corp. announced a new collaboration to make everyday health more accessible for people who are blind, have low vision or have difficulty reading product labels due to low literacy. Together, the companies are expanding functionality in the Microsoft Seeing AI app to provide consumers with more detailed labelling information for over 1,500 Haleon products across the U.S. and U.K. Seeing AI is a free mobile app designed to help people who have trouble seeing by narrating the world around them.

With todays launch on World Sight Day, people will hear packaging information through Seeing AI by scanning the barcode of Haleon products. This will provide an audio read-out of important information, such as product name, ingredients and usage instructions. Through Seeing AIs enhanced functionality, Haleon will help empower people to care for their own health independently by listening to label information narrated through the Seeing AI application.

Haleons inaugural Health Inclusivity Index, which sets a new global standard for measuring health inclusivity, makes clear that to improve health inclusivity, individuals and communities need to be provided with the power and the tools to truly take their health into their own hands. Haleon, driven by its purpose to deliver better everyday health with humanity, is committed to helping make healthcare more achievable, inclusive and sustainable. The Seeing AI collaboration with Microsoft is one of Haleons first new initiatives to champion health inclusivity. The Microsoft Seeing AI app can be a benefit to:

The Seeing AI app was developed by a team of Microsoft engineers spearheaded by project lead and engineering manager Saqib Shaikh, who lost his sight at the age of seven and was driven to develop the app by his passion for using technology to improve peoples lives.

Saqib Shaikh, engineering manager at Microsoft, said: Im really excited to see the launch of this enhanced product recognition functionality, developed in collaboration with Haleon. Seeing AIs intelligent barcode scanner plays audio cues to help you find the barcode, and now the information displayed for Haleon products is coming straight from the manufacturer, providing richer information including usage instructions and ingredients. This can be invaluable for someone who cannot read the label, leading to greater independence.

Katie Williams, U.S. chief marketing officer at Haleon said, We believe everyone should have access to self-care products, services and the information needed to make informed, proactive choices about their health needs. Haleon initiated this collaboration with Microsoft via its Seeing AI app to make consumer health more accessible, achievable and inclusive. We are proud to help make better everyday health more in reach for the blind and those with low vision.

The Seeing AI app is free to download from the Apple App Store and will be available on Android in the future. To use Seeing AI on Haleons products, users should hold their phone camera over the packaging barcode. The app will read out the product name and all text on the package. Users can skip ahead or move back to the relevant section they want to listen to, for example, which flavor or how to use the product. The Haleon barcode functionality will launch today in the U.S. and U.K. first, with plans to expand globally and add additional languages in the future.

About Haleon U.S.

Haleon (NYSE: HLN) is a leading global consumer health company with a portfolio of brands trusted daily by millions of people. In the United States, the organization employs more than 4,700 people who are united by Haleons powerful purpose to deliver better everyday health with humanity. Haleons products span five categories:Oral Health, Pain Relief, Respiratory Health, Digestive Health, and Wellness. Built on scientific expertise, innovation, and deep human understanding, Haleons brands include Abreva, Advil, Benefiber, Centrum, ChapStick, Emergen-C, Excedrin, Flonase, Gas-X, Natean, Nexium, Nicorette, Parodontax, Polident, Preparation H, Pronamel, Sensodyne, Robitussin, Theraflu, TUMS, Voltaren, and more. For more information on Haleon and its brands, please visit http://www.haleon.com or contact [emailprotected].

About the Haleon Health Inclusivity Index

Todays announcement closely follows the launch of the Health Inclusivity Index, developed by Economist Impact and supported by Haleon. The world-first global study of 40 countries measures how successful countries are in using policy to remove the personal, social, cultural, and political barriers which could otherwise prevent people and communities from achieving good physical and mental health. The number of countries assessed in the study will grow to over 80 over the next two years as part of a new three-year partnership between Haleon and Economist Impact. The report has been commissioned by Haleon as part of its commitment to making better everyday health more achievable, inclusive and sustainable, with the company aiming to create more opportunities for people to be included in everyday health, reaching 50 million people a year by 2025.

About Microsoft

Microsoft (Nasdaq MSFT @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

For more information, press only:

Microsoft Media Relations, WE Communications for Microsoft, (425) 638-7777, [emailprotected]

Meghan Sowa, Haleon U.S., (919) 864-0953, [emailprotected]

Note to editors: For more information, news and perspectives from Microsoft, please visit the Microsoft News Center athttp://news.microsoft.com. Web links, telephone numbers and titles were correct at time of publication but may have changed. For additional assistance, journalists and analysts may contact Microsofts Rapid Response Team or other appropriate contacts listed athttps://news.microsoft.com/microsoft-public-relations-contacts.

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Haleon and Microsoft use AI to enhance health product accessibility for people who are blind or partially sighted - Stories - Microsoft

CHICAGO & DALLAS--(BUSINESS WIRE)--Construction Discovery Experts (CDE), the eDiscovery firm custom built for the construction industry, and Reveal, the global provider of the leading AI-powered eDiscovery platform Reveal 11, announced today the significant expansion of the firms existing collaboration to supercharge CDEs AI capabilities for construction eDiscovery and litigation. A first for the construction sector, CDE is working hand-in-hand with Reveal to employ custom layouts and workflows specifically for CDEs construction clients.

Although a necessary component in the litigation process, CDE understands that eDiscovery can be painful, expensive, and confusing for construction litigants and their outside counsel. We own the unavoidable eDiscovery process from start to finish so that our clients and their counsel can focus on winning. Reveals advanced technology helps us to serve this mission, said Brett Lamb, CEO of Construction Discovery Experts.

Reveals AI platform is uniquely equipped to handle complex and large-scale construction litigation matters using custom workflows and AI models that understand the unique nature of construction disputes. With Reveals customized layouts for particular data types relevant to construction project files, CDE is able to seamlessly and quickly uncover critical insights for their clients using more advanced tools and less resources than ever before.

CDE places an emphasis on tailor made solutions, rather than a one size fits all approach. Every matter for a client lays the groundwork for an ever-evolving playbook unique to each client including everything from portable AI models to custom workflows that can be leveraged across matters.

The most exciting partners to work with are those who are masters of their domain and understand the unmatched innovation and value theyre bringing to that domain. The team at CDE are one of those partners pioneering the use of advanced AI in the field of construction, said Wendell Jisa, founder & CEO of Reveal. A true collaborative venture, our work with CDE is already becoming an example of how organizations (and their customers) of any size, in any industry, and in any location, can not only benefit from the power of AI, but can also out smart its competition.

With the most adaptability and scalability of any tech solution on the market, the Reveal 11 AI platform is uniquely equipped to handle matters at any scale. Combined with the industrys most advanced visualization tools on the market, clients can now quickly and more deeply understand their digital environments in ways traditional tools simply cannot replicate.

Am Law 100 firms, Fortune 500 corporations, legal service providers, government agencies and financial institutions in more than 40 countries across five continents have already signed on to use the Reveal 11 platform. For more information about Reveal and its AI platform for legal, enterprise and government organizations, visit http://www.revealdata.com.

About Reveal

Reveal provides world-class document review technology, underpinned by leading processing, visual analytics, and artificial intelligence, all seamlessly integrated into a single platform for eDiscovery and investigations. Our software combines technology and human guidance to transform structured and unstructured data into actionable insight. We help organizations, including law firms, corporations, government agencies, and intelligence services, uncover more useful information faster by providing a world-class user experience and patented AI technology that is embedded within every phase of the eDiscovery process.

About Construction Discovery Experts:

CDE is the construction industrys go-to teammate for eDiscovery expertise in legal technology and efficiency. CDE hosts a team of experts that are skilled at delivering client-centered consulting services focused on three critical components: construction industry expertise, simple fee structure and concierge level service. CDE knows eDiscovery can be painful, expensive and confusing; we own the unavoidable so our clients can prevail.

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Construction Discovery Experts Expands Partnership with Reveal to Create Custom AI Models for Construction Litigation & Workflows - Business Wire

News item | 13-10-2022 | 11:38

Trade mission of 45+ Dutch businesses to London brings together AI and mobility innovators from across the Channel, who are taking technologies in these fields to new levels

As North Sea neighbours, the interests of the Netherlands and the UK in tackling climate change, as well as stimulating sustainable trade and investments are closely entwined. On 18 & 19 October, a Dutch trade mission to London consolidates this momentum, bringing together businesses, knowledge institutes and local and national governments. A Letter of Intent with a value of 250 million euro (218 million GBP) will be signed by Robots of London and Wemeetz to further exploit the potential of AI in remote (net)working. Dutch Minister for Foreign Trade and Development Cooperation, Liesje Schreinemacher, and Dutch Minister for Environment, Vivianne Heijnen, as well as International Trade Secretary, Kemi Badenoch, and other UK representatives will join the mission to share their insights.

The two-day event in London will focus on Artificial Intelligence (AI) for net zero and Sustainable Urban Mobility solutions. The trade mission comes at a relevant time for innovators from both countries, as the recently published Global Innovation Index 2022 has ranked the UK (fourth) and the Netherlands (fifth) as the worlds most innovative countries.

Karel van Oosterom: At the moment, both the UK and the Netherlands are facing strong economic headwinds. Many evolving challenges require international cooperation, such as the energy transition currently complicated by the Russian invasion in Ukraine or the effects of climate change. We have to keep in mind that entrepreneurial spirit can help us move forward in the transition to net zero. This mission will be about strengthening cooperation with UK innovators, as innovation plays a key role in future productivity growth and societally impactful progress in the field of clean technologies or mobility. According to the Dutch, driving innovation is all about collaboration.

This is the first in-person trade mission undertaken by the Dutch government following the EU-UK Trade Agreement. In the past two and a half years, entrepreneurs on both sides of the Channel have had to adapt continuously to the new way of doing business. Nonetheless, the UK and the Netherlands are and remain close trading partners. The Netherlands is the UKs 4th largest trading partner, accounting for 6.5% of total UK trade (DiT). Vice versa, the UK remains in the top 5 of the Netherlands closest trading partners (CBS). In 2021, the UK was the most important export destination for Dutch services after Germany and the US (CBS).

In the Netherlands, AI has been earmarked as one of the key innovation sectors. TheNetherlands AI Coalition(NL AIC) recently received a total investment of 1.05 billion euro (about 890 million pounds) from the Dutch National Growth Fund over the period 2021-2027. According toTechleap, about 650 AI startups and scale-ups are based in the Netherlands, making it the country with the highest density of AI startups in the EU per capita. In 2019, the worlds largest research network for AI,CLAIRE(Confederation of Laboratories for Artificial Intelligence Research in Europe), was established in The Hague. However, to exploit the potential of AI as a force for good, cross-border cooperation is needed.

Ranked first in Europe and third globally, the UK is a global frontrunner in the development and adoption of AI technologies. The UK has an extensive AI ecosystem consisting of the catapult centres, government bodies, outstanding research institutions, accelerator programmes and a rich diversity in AI-companies. Moreover, the UK has recognised AI as a gamechanger in reaching net zero. AI plays an important role in the sustainable energy transition by matching energy supply and demand more accurately. AI can also make industrial supply chains more sustainable by enabling predictive maintenance; creating digital twins and monitoring emissions more precisely. Dutch participants of the trade mission would like to work together with UK businesses and knowledge institutes on AI applications to help reach the goal of net zero in 2050.

The trade mission comes at an exciting time for the mobility sector. The Netherlands is known for its cycling culture, yet the Dutch government aims to shift to a higher gear with its recently published cycling policy. With a stimulus package of 50 million euro, it aims to get an extra 100,000 people commuting by bicycle over the next two and a half years in the interest of accessibility, public health andclean air. Following the launch of Active Travel England earlier this year and a widespread increase in cycling due to the Covid-19 pandemic, the volume of bicycles on the roads has increased. Sales soared to 70+% in 2020 and continue steadily, leading to a higher demand in secure and durable storing (as provided by FietsHangar) or intelligent solutions to increase safety in traffic (Sycada).

But theres more to sustainable mobility than the humble bicycle. In both the Netherlands and the UK, serious efforts are made in the roll out of charging facilities for electrical vehicles. The UK has the ambition to increase the number of charging facilities to 2500 in 2030 and 6000 in 2035. Dutch businesses like Leap24, providing these stations for vans and trucks servicing (ultra) low emission zones, are therefore looking forward to explore partnerships in the UK. During the trade mission, a micro mobility report by Royal HaskoningDHV will be presented to outline the UK market, as well as opportunities for Dutch businesses including as 5G development, e-cargo or last mile journeys.

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The Netherlands and the UK intensify cooperation on AI and mobility solutions - The Netherlands and You

Adaptive AI can be used to continually improve the customer experience with each iteration of an interaction between a customer and a brand.

Adaptive Artificial Intelligence (AI) is able to update its own code to incorporate what it has learned from its experiences with new data. This means Adaptive AI can be used to continually improve the customer experience with each iteration of an interaction between a customer and a brand. AI-driven chatbots will continually refine their conversational skills, and recommendation engines will become more refined, making recommendations that truly resonate with customers. Lets look at adaptive AI, the ways brands are using it today, and the future of adaptive AI for improving the customer experience.

The traditional machine learning (ML) model consists of training and prediction pipelines. A pipeline can be thought of as an interconnected and streamlined collection of operations. The training pipeline aggregates and ingests data throughout the various stages of data cleaning, grouping and transformation. The prediction pipeline then analyzes the data to generate accurate insights and predictions that will be used for fruitful decision making.

Adaptive AI, on the other hand, consists of a single pipeline that monitors and learns the new changes made to the input and output values and their associated characteristics. Additionally, it learns from the events that may change the behavior of consumers and businesses in real time and is able to consistently maintain its accuracy. Adaptive AI incorporates the feedback it has received from the operating environment and then uses it to create data-informed predictions. This allows for super-fast solutions for the verification of ideas and simple deployment functionality in production.

Mike Gozzo, chief product officer at Ada, an AI-based automated brand platform provider, told CMSWire adaptive AI relies on the regular training and extension of ML and Natural Language Understanding (NLU) capabilities, and said this will increase the quality of CX. It works best when trained on millions, or even billions, of customer interactions across different geographies, industries and use cases, Gozzo said. This creates a rich data set that drives personalized and proactive experiences for each customer, in every interaction. Gozzo explained when a global ML model is combined with brand-specific models, the time it takes to train conversational AI and increase reliability is reduced.

The three tenets of adaptive AI are said to be robustness, efficiency and agility.

Robustness refers to the ability of adaptive AI to accomplish high algorithmic accuracy.

Efficiency refers to the ability of adaptive AI to pull off low resource usage.

Agility refers to the capacity of adaptive AI to change operational conditions based on current requirements.

Synergistically, these three core elements of adaptive AI comprise the key metrics for extremely efficient AI-informed actions for many applications.

Ricardo Zuasti, chief product officer at Technisys, a leading global provider of next-generation digital banking platforms, told CMSWire being able to deliver truly tailored experiences customers will increasingly want and expect will depend on a business ability to fuel AI-powered decision making in every channel, in real time. Zuastis business is moving toward the use of AI to power context and behavior-sensitive mechanisms beyond conversational interactions but more broadly to adapt the user experience dynamically to what the person needs and wants in near real time.

Related Article: If You Want to Succeed With Artificial Intelligence in Marketing, Invest in People

AI-driven chatbots are commonly used on websites as a way for customers to instantly locate the goods or services they are searching for, as well as for customer service needs. Adaptive AI is still an emerging technology. However, there are already chatbots using it to enhance the chat experience.

Hyro, for instance, offers an adaptive AI-driven chatbot being used in healthcare, real estate and government industries. Hyro automatically scrapes a variety of data sources including websites, databases, application programming interfaces (APIs) and more, and when content is updated, the conversation is also updated. The unstructured data is mapped to a knowledge graph made to be queryable by Natural Language Processing (NLP).

Adam Dorfman, vice president (VP) of product at Reputation, an online reputation management solution provider, told CMSWire through adaptive AI and ML, an AI-powered chatbot can continually improve service in a number of ways without human intervention. For instance, a chatbot using adaptive AI can improve the accuracy of its replies and learn how to give more personalized responses based on each customers needs (instead of generic, pre-formulated answers), adding Adaptive AI also promises to help chatbots become more human and accessible by learning to give answers in a more natural way by improving a chatbots conversational skills. This is important because when a chatbot can successfully emulate nuances of tone and language style, people are more likely to emotionally trust the customer experience theyre getting with a business.

Related Article: The Role of Journey Orchestration Engines in 2022

One of the areas where adaptive AI is shining is in edge computing.IBM defines edge computing as a distributed computing framework that physically locates applications closer to data sources such as Internet of Things (IoT) devices or local edge servers. A 2022 Gartner Report predicted by 2025, more than 50% of enterprise-managed data will be created and processed outside the data center or cloud using edge computing.

By using adaptive AI, edge systems are able to dynamically adjust their computing needs, effectively lowering compute and memory resource requirements. Adaptive AI allows edge applications to adapt and adjust to their workloads based on their requirements and environments. By using attention and context to use only the parts of its neural network it needs, adaptive AI is able to do the processing locally on edge devices. Adaptive AI is a new method for neural networks to operate that dynamically minimizes the amount of memory and compute horsepower required.

Brian David Crane, founder of Spread Great Ideas, a digital marketing fund, told CMSWire adaptive AI is the next big thing in automation and AI, as programs and machines become self-sustaining mechanisms that continually learn and adapt to human behavior. The self-driving car is based on adaptive AI and is a glaring example of how brands are using AI today. Brands like Amazon, Netflix and Google are already using adaptive AI to provide a better user experience, said Crane.

Companies are exploring how they can use adaptive AI to deliver customized learning solutions to students based on their individual learning capacities and behavior, said Crane, who added cybersecurity companies are also exploring adaptive AI to create an automated self-sustaining protocol that learns and models itself with continual iterations to fight digital threats and cyberattacks in real time.

The implications of adaptive AI on customer experience are vast and game-changing. By analyzing social, behavioral and past interactions, adaptive AI uses continuous interactions to predict and anticipate customer behavior and provide highly personalized solutions to improve the customer journey and deliver positive CX, said Crane, who explained adaptive AI focuses on feelings and emotions and analyzes sentiments to create perfect interactions on a real-time basis.

As an example of such an experience, Crane said to think of hyper-interactive and customized displays at retail points that use facial interpretations, voice analysis and body language analysis to identify shoppers' emotions and mindsets and offer solutions in real-time to deliver a positive experience.

Adaptive AI will enable amazing customer experiences that will be unique, positive, and emotionally connected. With adaptive AI, businesses can predict the next buyer experience and offer personalized recommendations, discounts and individualized offers, thus helping build an emotional connection with the brand through these experiences over time, said Crane.

Adaptive AI takes AI-driven chatbots to the next level through the use of ML, NLU, NLP and real-time decision making, and has the potential to improve the customer experience in real time, enhancing hyper-personalization and recommendation engines, and improving edge computing by minimizing compute and memory resource requirements.

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Adaptive AI Will Improve the Customer Experience - CMSWire

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Global Call Centre AI Market

Global Call Centre AI Market

Dublin, Oct. 13, 2022 (GLOBE NEWSWIRE) -- The "Call Center AI Market with Covid-19 Impact Analysis, By Component, Mode of Channel (Phone, Social Media, & Chat), Application (Workforce Optimization & Predictive Call Routing), Deployment Mode, Vertical and Region - Global Forecast to 2027" report has been added to ResearchAndMarkets.com's offering.

The global Call Center AI Market size is to grow from USD 1.6 billion in 2022 to USD 4.1 billion by 2027, at a Compound Annual Growth Rate (CAGR) of 21.3% during the forecast period.

The services segment is projected to grow at a higher CAGR during the forecast period

The services segment is projected to grow at a higher CAGR during the forecast period. This can be attributed to the need for determining the time and cost required to install the solution that requires fully managed call center AI services. Call center AI solutions ensure the strengthening of customer relationships, resulting in increased first call resolution rate and improved customer experience.The large enterprises' segment will hold the larger market share during the forecast period

The large enterprise segment is estimated to hold a larger market share in 2022. Large enterprises focus on solutions to effectively manage complex business processes to enhance customer engagement. Hence, these organizations are using call center AI solutions to effectively manage complex operations. The SMEs segment is projected to register a higher CAGR during the forecast period due to the growing need to enhance business processes, reach new customers, stay competitive and control their spending.

The social media segment is to grow at the highest CAGR during the forecast period

The social media segment is estimated to grow at the highest CAGR during the forecast period due to the rising demand for social media used in sentiment analysis that helps understand customer perceptions about the brand. It also helps amplify customer service quickly through shares and likes. The phone mode of the channel is expected to hold the largest share in 2022 due to the rising penetration of smartphone users across the globe.The cloud segment is expected to hold larger market size during the forecast period

The cloud segment is expected to hold larger market size during the forecast period. The cloud technology benefit of easy deployment and minimal capital requirement facilitates the adoption of the cloud deployment model. The increasing demand for scalable, easy-to-use, and cost-effective solutions is expected to boost the demand of cloud-based call center AI in the market. Call Center AI solutions are expected to accelerate the growth of the cloud segment in the call center AI market. Moreover, cloud-based call center AI solutions enable business operations to improve employee productivity and save OPEX. Hence, the cloud-based deployment model is gaining traction in the coming years.The predictive call routing segment is expected to have the highest CAGR during the forecast period

The predictive call routing segment is expected to have the highest CAGR during the forecast period. The predictive call routing application ensures the highest possibility of first contact resolution (FCR) and prevents overburdening agents by adapting to their existing call queue in the call center AI market.The BFSI segment is expected to hold the largest market size during the forecast period

The BFSI segment is projected to hold the largest market size during the forecast period. The growth of this vertical is attributed to the increased adoption of call center AI solutions by financial institutions, which helps them flawlessly connect with customers, improve customer experience, and lowers customer churn. The growth of the segment is attributed to the rising need to protect businesses from costly regulatory litigations and reputational risks due to fraudulent activities while storing and managing customer information and serving customers.Among regions, APAC holds the highest CAGR during the forecast period

The market in the Asia Pacific is expected to grow at the highest CAGR during the forecast period due to the increasing penetration of advanced technologies, rising GDP of countries, and high density of contact center outsourcing operations. Asia Pacific consists of emerging economies, such as China, Japan, and India, where call center AI solutions are being deployed at a large scale due to the presence of a lot of data centers and a high density of BPO operations. Moreover, the demand for cloud-based call center AI solutions by business enterprises is expected to enhance the customer experience in the region.

Key Topics Covered:

1. Introduction

2. Research Methodology

3. Executive Summary

4. Premium Insights

5. Market Overview and Industry Trends5.1 Introduction5.2 Market Dynamics5.2.1 Drivers5.2.1.1 Advent of AI in Call Center to Offer Enhanced Customer Support Services and Better Experience5.2.1.2 Rising Development in Customer Engagement Through Social Media Platforms5.2.1.3 Increased Data Generation5.2.2 Restraints5.2.2.1 Unsupervised Learning5.2.3 Opportunities5.2.3.1 Advancements in AI and Ml to Facilitate Real-Time Actionable Insights5.2.3.2 Integration of Gesture Recognition with AI-Based Chatbots and Ivas5.2.4 Challenges5.2.4.1 Data Privacy and Security Concerns During Pandemic5.2.4.2 Lack of Skilled Workforce to Articulate Business Operations5.2.4.3 Preference for Online Chat Over Chatbots5.2.4.4 Slow Digitization Across Emerging Economies5.2.5 Cumulative Growth Analysis5.3 Industry Trends5.3.1 Call Center AI Market: Evolution5.3.2 Ecosystem5.3.3 Supply Chain Analysis5.3.4 Market: COVID-19 Impact5.3.5 Trends/Disruptions Impacting Buyers/Clients of Market5.3.6 Case Study Analysis5.3.6.1 Citibot Used Amazon Lex to Build Conversational Interfaces for Text and Voice Applications5.3.6.2 Osu University Used Amazon Connect and Qnabot to Provide Seamless Experience Across Voice and Chat for Customers and Agents5.3.6.3 Oscar Health Chose Cxone Workforce Management Enterprise to Minimize Administrative Burden and Focus on Scheduling and Forecasting5.3.6.4 Pldt Turned to Oracle Digital Assistant Running on Oracle Cloud Infrastructure to Power Its Self-Service Chatbot5.3.6.5 Echo Chose Oracle Digital Assistant to Help Improve Customer Experience5.3.6.6 Firefly Health Switched to Dialpad to Get New Information Quickly5.3.6.7 Solarzero Used Dialpad to Have a Modern Phone System That is Highly Reliable and Does Not Drop Calls5.3.6.8 Standard Chartered Used Avaya Onecloud to Achieve Personalized and Consistent Client Service5.3.6.9 Preferred Home Care Used Avaya Cloud Office to be Able to Reach Patients During an Outage or Other Crisis5.3.6.10 Vodafone Selected Amazon Connect to Simplify Contact Center Operations by Drawing on AI and Ml5.3.7 Technology Analysis5.3.8 Patent Analysis5.3.9 Pricing Model Analysis, 20215.3.10 Porter's Five Forces Analysis5.3.11 Scenario5.4 Regulatory Implications5.5 Key Stakeholders and Buying Criteria5.6 Key Conferences & Events in 2022-20235.7 Regulatory Landscape

6. Call Center AI Market, by Component6.1 Introduction6.1.1 Call Center AI: COVID-19 Impact6.2 Solutions6.2.1 Platform6.2.1.1 Rising Demand for AI in Call Centers to Enhance Agent Performance and Enable Customers6.2.2 Software Tools6.2.2.1 Call Center AI Software Helps in Deeper Understanding of Customers Across Different Contexts and Channel Modes6.3 Services6.3.1 Professional Services6.3.1.1 Training & Consulting Services6.3.1.1.1 Training and Consulting Services Help in Initial Phase of Implementing Call Center AI6.3.1.2 Support & Maintenance6.3.1.2.1 Support & Maintenance Services Help Organizations Understand Changing Business Conditions and Market Trends6.3.1.3 System Integration & Implementation Services6.3.1.3.1 System Integration & Deployment Services Facilitate Integration of Devices and Software and Their Deployment6.3.2 Managed Services6.3.2.1 Enterprises Must Ensure Provision of Certain Services for Their Clients to Maintain Their Market Position

7. Call Center AI Market, by Organization Size7.1 Introduction7.2 Large Enterprises7.2.1 Focus on Solutions to Effectively Manage Complex Business Processes to Enhance Customer Engagement7.3 Small and Medium-Sized Enterprises7.3.1 Reduced Operational Costs, Government Support, and Enhanced It Infrastructure to Influence Adoption of Call Center AI Solutions

8. Call Center AI Market, by Mode of Channel8.1 Introduction8.2 Phone8.2.1 Phone to be the Most-Used Customer Service Channel to Help Customers Get Quick Resolution for Their Queries8.3 Social Media8.3.1 Customers Use Social Media Platforms to Highlight Positive or Negative Experiences They Have Had with Brands8.4 Chat8.4.1 Chat-Based Call Center AI Software Tools to Improve Response Time and Lower Operational Costs in Long Run8.5 Email or Text8.5.1 Versatile Website Engagement Tool to Communicate Personal Correspondence and One-On-One Conversations8.6 Website8.6.1 Website Chat to be Most Cost-Effective Channel to Support Multiple Customers at One Time

9. Call Center AI Market Size, by Deployment Mode9.1 Introduction9.2 Cloud9.2.1 Cloud-Based Call Center AI Solutions to Gain Traction due to Their Cost-Effectiveness and Global Availability9.3 On-Premises9.3.1 Data Privacy Concerns and Increasing It Infrastructure Costs to Drive Growth of On-Premises Deployment Mode

10. Call Center AI Market, by Application10.1 Introduction10.2 Workforce Optimization10.2.1 Workforce Optimization to Modernize Call Center Technologies and Platforms10.3 Predictive Call Routing10.3.1 Predictive Call Routing to Use Artificial Intelligence-Based Call Center Techniques and Analytics10.4 Journey Orchestration10.4.1 Journey Orchestration to Provide Holistic View of Customer Interactions with Organization10.5 Agent Performance Management10.5.1 Growing Need to Manage and Handle Agent Performance to Drive Market Growth10.6 Sentiment Analysis10.6.1 Rising Need to Automate Contact Center Processes and Gain Customer Insights to Boost Call Center AI Growth10.7 Appointment Scheduling10.7.1 Need to Automate Multiple Tasks and Enhance Personalized Customer Experience to Drive Market Growth10.8 Other Applications

11. Call Center AI Market, by Vertical11.1 Introduction11.2 Banking, Financial Services, & Insurance11.3 Media & Entertainment11.4 Retail & Ecommerce11.5 Healthcare & Life Sciences11.6 Travel & Hospitality11.7 It & Telecom11.8 Transportation & Logistics11.9 Other Verticals

12. Call Center AI Market, by Region

13. Competitive Landscape

14. Company Profiles14.1 Introduction14.2 Key Players14.2.1 IBM14.2.2 Microsoft14.2.3 Oracle14.2.4 Aws14.2.5 Google14.2.6 Sap14.2.7 Avaya14.2.8 Nice14.2.9 Nuance Communications14.2.10 Genesys14.2.11 8X814.2.12 Artificial Solutions14.3 Other Players14.3.1 RingCentral14.3.2 Talkdesk14.3.3 Dialpad14.3.4 Twilio14.3.5 Zendesk14.3.6 Five914.3.7 Kore.AI14.3.8 Inbenta14.3.9 Creative Virtual14.4 Startups/SMEs14.4.1 Haptik14.4.2 RulAI14.4.3 Pypestream14.4.4 Avaamo14.4.5 Senseforth.AI14.4.6 Observe.AI14.4.7 Yellow.AI14.4.8 Ultimate.AI14.4.9 Cognigy

15. Adjacent and Related Markets

16. Appendix

For more information about this report visit https://www.researchandmarkets.com/r/7ewan0

Attachment

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The Worldwide Call Center AI Industry is Expected to Reach $4.1 Billion by 2027 - Yahoo Finance

NEW YORK--(BUSINESS WIRE)--Today, Perfect Corp., the leading artificial intelligence (AI) and augmented reality (AR) beauty and fashion tech solutions provider, introduced its new virtual try-on technology for hairstyles. The innovative solution leverages advanced AI technology, including machine learning and Generative Adversarial Network (GAN), to help brands and hair salon businesses provide customers with hyper-realistic hairstyle simulations. This new virtual try-on solution will help consumers visualize how various haircuts look before committing to a certain style, ultimately helping to increase consumer confidence while personalizing the salon experience in an exciting new way.

Virtual Try-on Tech for Hairstyles Provide Consumers with True-to-Life Previews of 12 Hairstyle Makeovers, Including Hair Color

Perfect Corp.s AI virtual try-on technology for hairstyles allows consumers to experiment with different looks before committing to a new haircut. Users can choose from 12 unique styles, including classic bob cut, bob cut without bangs, curly bob cut, wavy bob cut, short, pixie cut, long curly, long wavy, long wavy with bangs, long straight with bangs, comb over, and buzz cut. The experience is further enhanced with AR hair color try on, delivering a comprehensive suite of hairstyle AR solutions. Featured styles can also be viewed through before and after simulations, helping consumers accurately visualize their next hair transformation. The solution takes the stressful guesswork out of the hairstyle consultation experience, and helps consumers feel confident about their next salon visit.

Cutting-Edge AI, ML, and GAN Technology Ensures Hyper-Realistic Hairstyle Simulations

Perfect Corp.s AR virtual try-on technology for hairstyles leverages highly-sophisticated AI technology, using the latest developments in machine learning and Generative Adversarial Network setups, to guarantee true-to-life hairstyle simulations. When simulating transitions to shorter haircuts and styles, the advanced AI algorithm is capable of recreating parts of the face, ears, neck, and head to ensure a realistic representation of the end result. The technology also takes hair color, and skin tone into consideration when adapting simulations to each consumers unique characteristics, delivering inclusive and impactful AI simulations for all.

Transforming the Hairstyle Consultation Experience with Digital Tech Innovations

Our goal is to solve consumer pain points through the power of AI and AR technology innovations, said Perfect Corp. CEO and Founder Alice Chang, As beauty consumers look to brands and hair salon businesses to provide more personalized and immersive client experiences, Perfect Corp.s AR virtual try-on solution for hairstyles will offer a game-changing tool to supercharge customer satisfaction.

To learn more about Perfect Corp.s AR Virtual Try-On Tool for Hairstyles, please visit: https://www.perfectcorp.com/business/products/virtual-hairstyles

About Perfect Corp.

Perfect Corp. is the leading SaaS AI and AR beauty and fashion tech solutions provider, dedicated to transforming shopping experiences through empowering brands to embrace the digital-first world. By partnering with the largest names in the industry, Perfect Corp.s suite of enterprise solutions deliver synergistic, technology-driven experiences that facilitate sustainable, ultra-personalized, and engaging shopping journeys, as well as equipping brands with next generation of consumer goods. Perfect Corp. offers a complementary suite of mobile apps, including YouCam Makeup and YouCam Perfect, to provide a consumer platform to virtually try-on new products, perform skin diagnoses, edit photos, and share experiences with the YouCam Community. To learn more, please visit PerfectCorp.com.

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New AI GAN-Powered Virtual Try-on for Hairstyles Solution from Perfect Corp. is Poised to Elevate Hair Salon Experience - Business Wire

For instance, TaylorMade Golf Company turned to Microsoft Syntex for a comprehensive document management system to organize and secure emails, attachments and other documents for intellectual property and patent filings. At the time, company lawyers manually managed this content, spending hours filing and moving documents to be shared and processed later.

With Microsoft Syntex, these documents are automatically classified, tagged and filtered in a way thats more secure and makes them easy to find through search instead of needing to dig through a traditional file and folder system. TaylorMade is also exploring ways to use Microsoft Syntex to automatically process orders, receipts and other transactional documents for the accounts payable and finance teams.

Other customers are using Microsoft Syntex for contract management and assembly, noted Teper. While every contract may have unique elements, they are constructed with common clauses around financial terms, change control, timeline and so forth. Rather than write those common clauses from scratch each time, people can use Syntex to assemble them from various documents and then introduce changes.

They need AI and machine learning to spot, Hey, this paragraph is very different from our standard terms. This could use some extra oversight, he said.

If youre trying to read a 100-page contract and look for the thing thats significantly changed, thats a lot of work versus the AI helping with that, he added. And then theres the workflow around those contracts: Who approves them? Where are they stored? How do you find them later on? Theres a big part of this thats metadata.

The availability of DALLE 2 in Azure OpenAI Service has sparked a series of explorations at RTL Deutschland, Germanys largest privately held cross-media company, about how to generate personalized images based on customers interests. For example, in RTLs data, research and AI competence center, data scientists are testing various strategies to enhance the user experience by generative imagery.

RTL Deutschlands streaming service RTL+ is expanding to offer on-demand access to millions of videos, music albums, podcasts, audiobooks and e-magazines. The platform relies heavily on images to grab peoples attention, said Marc Egger, senior vice president of data products and technology for the RTL data team.

Even if you have the perfect recommendation, you still dont know whether the user will click on it because the user is using visual cues to decide whether he or she is interested in consuming something. So artwork is really important, and you have to have the right artwork for the right person, he said.

Imagine a romcom movie about a professional soccer player who gets transferred to Paris and falls in love with a French sportswriter. A sports fan might be more inclined to check out the movie if theres an image of a soccer game. Someone who loves romance novels or travel might be more interested in an image of the couple kissing under the Eiffel Tower.

Combining the power of DALLE 2 and metadata about what kind of content a user has interacted with in the past offers the potential to offer personalized imagery on a previously inconceivable scale, Egger said.

If you have millions of users and millions of assets, you have the problem that you simply cant scale it the workforce doesnt exist, he said. You would never have enough graphic designers to create all the personalized images you want. So, this is an enabling technology for doing things you would not otherwise be able to do.

Eggers team is also considering how to use DALLE 2 in Azure OpenAI Service to create visuals for content that currently lacks imagery, such as podcast episodes and scenes in audiobooks. For instance, metadata from a podcast episode could be used to generate a unique image to accompany it, rather than repeating the same generic podcast image over and over.

RTL Deutschland, Germanys largest privately held crossmedia company, is exploring how to use DALLE 2 in Azure OpenAI Service to engage people browsing its streaming service RTL+. One idea is to use DALLE 2 to generate unique images to illustrate individual podcast episodes, rather than relying on the same podcast cover art.

Along similar lines, a person who is listening to an audiobook on their phone would typically look at the same book cover art for each chapter. DALLE 2 could be used to generate a unique image to accompany each scene in each chapter.

Using DALLE 2 through Azure OpenAI Service, Egger added, provides access to other Azure services and tools in one place, which allows his team to work efficiently and seamlessly. As with all other software-as-a-service products, we can be sure that if we need massive amounts of imagery created by DALLE, we are not worried about having it online.

No AI technology has elicited as much excitement as systems such as DALLE 2 that can generate images from natural language descriptions, according to Sarah Bird, a Microsoft principal group project manager for Azure AI.

People love images, and for someone like me who is not visually artistic at all, Im able to make something much more beautiful than I would ever be able to using other visual tools, she said of DALLE 2. Its giving humans a new tool to express themselves creatively and communicate in compelling and fun and engaging ways.

Her team focuses on the development of tools and techniques that guide people toward the appropriate and responsible use of AI tools such as DALLE 2 in Azure AI and that limit their use in ways that could cause harm.

To help prevent DALLE 2 from delivering inappropriate outputs in Azure OpenAI Service, OpenAI removed the most explicit sexual and violent content from the dataset used to train the model, and Azure AI deployed filters to reject prompts that violate content policy.

In addition, the team has integrated techniques that prevent DALLE 2 from creating images of celebrities as well as objects that are commonly used to try to trick the system into generating sexual or violent content. On the output side, the team has added models that remove AI generated images that appear to contain adult, gore and other types of inappropriate content.

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From Hot Wheels to handling content: How brands are using Microsoft AI to be more productive and imaginative - The AI Blog - Microsoft

As companies look to build diverse workforces, the biggest problem seems to be sourcing candidates from historically underrepresented groups, often because companies dont know where to look. TaTio, an Israeli startup from a couple of HR veterans, has built a platform to help connect companies to candidates who have the skills, but may lack a traditional resume.

Today the company announced a $5.3 million seed investment.

TaTio CEO Maya Huber says she and her co-founder, COO Mor Panfil, have over a decade of experience running HR companies. They personally experienced the frustration of trying to place people from a variety of underrepresented backgrounds, and the biggest problem was getting candidates through the resume review stage.

Every solution out there was still relying on resumes as a first step for people to apply. And we thought that there must be a different way because through the years as we worked with different types of underrepresented populations, we found that the resumes often did not reflect a persons actual skills, Huber explained.

The company developed a solution to help companies fill open positions with workers who are qualified, but lack traditional credentials. These hidden workers are disproportionately from underrepresented groups. TaTiO sources and vets job seekers with their AI work experience simulations and provides employers with pre-qualified candidates to interview, she said.

The company has built a two-sided marketplace. On one side they source candidates and then build tests that simulate the job the person is applying for. The idea is if the person performs well enough, they should be able to do the job. But the important thing is that it gets them over the resume hurdle.

We track candidates and we engage them through tests that simulate the core tasks of the jobSo if youre applying for a job as a sales representative, you will have 20 minutes to close three deals. We give you a pipeline of leads you need to qualify and create interactions with prospective clients, she said.

Using an underlying machine learning model, they judge the candidates performance and give them a score, and then match the candidates to the job openings with the goal of placing them in a job.

The company says that these models should improve over time as they collect more data on each simulation type. For now, the goal is to find a person who will be a good match for an open job with a particular employer, but in the future the company hopes to surface skills beyond what was explicitly being tested for.

They find candidates from a variety of sources including partnerships with NGOs and continuing education and training programs that work with underprivileged populations.

The challenge will be measuring the results. Its difficult to know how many of the candidates are from underrepresented groups unless they self-report. The hope is that by working with the companies using their service, they will be able to collect more data on the connection between their diversity hiring success, and the use of the TaTio platform. Huber says the companies using the platform are already reporting improvements, with some increasing their diversity hiring by 25% since they have been using TaTio.

The company currently has 16 employees, with over 75% women, although they are still trying to get more women in the engineering group. They also have age diversity, with some employees over 50 and some just starting their careers. So they are trying to practice what they preach in terms of diversity.

Todays seed round was led by Mensch Capital Partners and Cresson Management, with help from Cerca Discovery, Tau Ventures Ltd., Techstars, GoodCompany and a number of other industry angels.

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TaTio AI-based work simulations help diverse job seekers showcase their skills - TechCrunch