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venkat k 2019-11-20
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Amazon issued a patent last week for a new technology that enables Alexa to track consumers’ physical, emotional, and behavioral states.

This technology allows Alexa to detect audible cues, such as cough or tone, how the user is feeling, emotionally or physically, and provide responses based on that information.For example, when a user requests voice recognition, Alexa coughs or sniffles, the assistant can respond by asking if the user wants to order the lounges.

Alexa can also use consumer demographic and behavioral information such as age, location, accents, and past search and purchase behavior.Alexa’s ability to constantly monitor and respond in real-time paves the way for brands to communicate with consumers in a simple way, which helps to increase brand awareness and increase voice purchases.

Here’s how:It exposes users to relevant skills they don’t use.

For example, if a user is diagnosed with anxiety through their voice, the voice assistant may suggest an unknown stress relief skill to the user.This allows Alexa to target consumers with brands related products and information.

Alexa can seemingly surface certain products based on consumers ’physical or emotional state at that exact moment, which can increase voice purchases.

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venkat k 2020-02-24
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Analyzing these complex data to obtain meaningful value is often excessive, which hinders our ability to find appropriate solutions in a timely manner.Unlocking these complex scenarios such as how humans can behave and interact can create opportunities.Many large tech companies are already developing artificial intelligence solutions.

They can reduce operational costs and reduce problems in the following ways:Increase automationOptimize asset managementImprove operational performanceIdentify efficienciesDecrease downtimeHealthcareFrom detecting early forms of cancer or disease to diagnosing MRI scans — especially data-driven — machine learning technology brings huge benefits to the health care industry.By analyzing large amounts of medical data, AI can help doctors give their patients faster and more accurate treatment and learn from making better decisions going forward.For patients, the AI-driven health care system can ease some of the burdens on a system that is struggling to keep up with the ever-increasing demand.

Keeping this technology in your pocket can help you make better health decisions, diagnose disease and other health risks early, avoid expensive procedures and live longer.Consumer Goods and ServicesFrom Google search to self-driving cars.

They know what to look for, at what time of day, when you pause, rewind, move fast or skip.

From sentiment to watching habits, Netflix watches it all in real-time.In 2016, SAP announced three programs to empower its ecosystem to make it's business applications smarter and create machine learning applications for customers.These programs help solve problems by eliminating bias in recruiting businesses and automating the time-consuming invoice-matching process.

SAP Clip is a revolutionary new machine learning-enabled intelligence that enables new levels of automation and new ways of doing business.FinanceAI technology is being used to look at financial models to achieve high levels of trend analysis, predict future pricing models, identify new markets and predict supply chain risks.Deep Knowledge Ventures, a Hong Kong-based venture capital firm, has announced that its program, called Vital, will be new to its board of directors.

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venkat k 2019-10-24
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What’s worse, why the sophisticated AI tool is locked inside the walls of a few billion-dollar tech companies, is no longer available.Today we are officially introducing Determined AI, which enables AI engineers everywhere to focus on models rather than infrastructure.

Determined AI supports this:GV (formerly Google Ventures),Extend partners, CRV, Haystack,SV Angel, The House, and Specialty Types.We are in the dark age of AI infrastructureAI and especially deep learning (DL) is becoming a very important computational workload for all types of businesses and industries.

For example, DL has dramatically improved the performance of autonomous vehicles at Waymo; Siri, Apple’s personal assistant who communicates through speech synthesis; And this has revolutionized Facebook’s ability to understand user sentiment.

Everyone has to do with existing tools, which are not bad for AI-based application development, as this example differs from traditional software development.

Consequently, organizations that rely on advances in AI — for anyone who works with vision, speech, or natural language — can mitigate risk without a radically new approach to AI infrastructure.Our focus:At Decisive AI, our goal is to empower deep learning at the speed of thought.

We started from the problems faced by DL researchers today and worked backward to provide a dramatically easier, seamless, integrated environment than traditional tools.Fully Interoperable:Determined AI frees your DL investment from the risk of cloud or hardware lock-in.

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venkat k 2019-12-13
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It adds a plethora of valuable elements and features to the e-commerce platforms.Now, brand performance and user experience are balancing as artificial intelligence or machine learning technology is changing the tedious working pattern.

AI-based mobile and web applications range from the ability to identify patterns, data sets, and create a personalized experience.

This also creates a unique approach that is more effective than any human being.AI has empowered users with many high-tech experiences ranging from websites to stores and from voice assistants to chatbots.

With a simple click, the user can get appropriate and desired results.

Depending on the image, the user can achieve the desired result.Personalized RecommendationsAI is helping by suggesting free recommendations by pop up or text.

As a result, users rate brands and their goods & services that are directly proportional to RoI.Voice AssistanceAs technology progresses it is making the shopping experience pretty worthy.

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venkat k 2019-12-06
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The future of retail looks dire, as more brick-and-mortar stores close their doors.

U.S. retailers have announced 8,558 store closures so far this year, with total U.S. store closures reaching 12,000 by the end of 2019, Cordite Research reported Friday.While the Internet and automation are usually responsible for these closures, the same technology could be a solution for physical store locations, said Paul Winsor, general manager at Data Robot.“If retailers want to stay open at the current stores they operate in, my recommendation to them is: Do they understand the changing habits of those customers, and how are they shopping with them, in those places?” Said Winsor.“To survive in a tough, tough retail market, you have to start your business and make predictions based on learning from your historical data,” he says.

Technology is around to help companies understand their business from a data perspective,” says Winsor.

“Data is not as personal and accurate as machine learning can help you.”To make predictions in the past, retailers look at daily and weekly transaction data and draw conclusions from it, Winsor said.As technology has evolved and convenience has become a priority, online stores have become the primary way to shop.

If retailers refuse to grow and adapt to emerging retail infrastructure, they will inevitably fall behind.AI helps retailers in three ways“With AI, we are dealing with machines that can simulate intelligent behavior or simulate intelligent human behavior, that is, sense, reason, action, and adaptation,” said Altimeter lead analyst Brian Solis.

“One of the most popular ways that leading brands use AI today is machine learning.”“The difference is that with machine learning, systems can differentiate models from pure data sets, and with the right management, learn from those data to predict and predict results and improve performance over time,” Solis says.

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venkat k 2020-05-12
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In U.S Drivers add 81 extra hours to their arrival each year due to traffic.

The other U.S. cities are also worse, these cities are known for difficult driving conditions with hills, bridges, and bikers.Diverse road conditions cause heavy traffic, but companies like Uber are coming to Pittsburgh to test autonomous vehicles.

And, besides the AV, that traffic technology includes an AI system called Sertrack, which allows traffic lights to be adapted to traffic conditions without having to rely on pre-programmed wheels.At installed lights, the team behind the system estimated that travel time was reduced by 25%, braking by 30%, and idle by more than 40%.

It costs about $ 20,000 to wire up and install Surtrack at the intersection.Sertrack works by tracking traffic and creating attendance models.

First, hardware including a computer, camera, or radar device is installed at the intersection.

Through communication with the below models, the processing is done in a way that creates a local plan from multiple data sources.

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venkat k 2019-10-29
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Objective:The aim of this review is to summarize the main topics in Artificial Intelligence (AI), their applications and limitations in surgery.

This paper reviews the key capabilities of AI services to help surgeons understand and critically assess new AI applications and contribute to new developments.Summary of Background Data:AI is composed of various sub-fields that provide potential solutions to each and every clinical problem.

Each of the major subsets of AI reviewed in this piece has also been used in other industries, such as autonomous cars, social networks, and deep learning computers.Methods:A review of AI papers across computer science, statistics, and medical sources has been conducted to identify key concepts and technologies in AI that are innovating in industries including surgery.

Limitations and challenges for working with AI are also reviewed.Results:Four main sub-fields of AI are defined:machine learningartificial neural networks,natural language processing andcomputer vision.Their current and future applications have been introduced to surgical practice, including big data analytics and clinical decision support systems.

The role of surgeons in the development of technology to optimize the implications and clinical impact of AI to surgeons is discussed.Conclusion:Surgeons are well-positioned to help integrate AI into modern practice.

Surgeons must partner with data scientists to capture data and provide a clinical context for the stages of care, as AI has the potential to revolutionize the way surgery is taught and practiced.

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venkat k 2019-12-10
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As Artificial Intelligence (AI) and machine learning are ubiquitous, we will soon be struggling to avoid using the benefits that any industry can offer them.

Telecommunications is one of the fastest-growing industries, as well as using artificial intelligence and machine learning in many aspects of their business, ranging from improving the customer experience to improving operational reliability.

Here are some of the most common applications.Customer service and customer satisfactionAlmost every telecom major uses artificial intelligence and machine learning to improve its customer service by using virtual assistants and chatbots.

In one example, customer satisfaction improved by 68 percent after Vodafone introduced its chatbot TOBi.As a gatekeeper, chatbots analyze requests, learn to guide and raise customer queries if needed, identify sales opportunities and alert the customer to other products and services that are of interest to them, and manage most of them without human intervention.

AT, Verizon, Comcast, and every other large-scale telco uses AI for better customer service.Thanks to artificial intelligence and machine learning, the ability to provide speech and voice services such as chatbots is available.

Not only is it used in chatbots, but it also extends service offerings such as Comcast’s XI Talking Guide, which “speaks” network names/time slots, shows titles and helps users navigate through their television options.

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venkat k 2019-11-06
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Over the past two years, the world has been filled with buzzing expectations about the promises and potential of AI for business.

Discovering new opportunities, working leads and closing deals.For these businesses, there is a “great” attitude.

Until you show me how it works on my day to day business, I’m done.“Others worry that the promise is too real and that the AI is here — and ready to replace them.Interestingly, the response to these two systems of thinking is the same: not just AI, but for small businesses or startups on their path to success, AI is a way of solving everyday business problems that are not only obsolete and reusable, you are better, smarter, more efficient and more More complex people.How AI affects business processes daily and creates more jobs.Simply put, the new world of AI is no longer just for organizations.

Companies like Salesforce, which have been committed to democratizing customer relationship management technology for years, are now doing the same for AI.So AI is real.

Quite simply, their experience of AI in consumer apps means that they expect you to know more about them, so that you can do more for them, and even give them the help and answers they are looking for before they ask.

Everything.Smart business processes mean growing business.For the past 40 years, businesses have seen huge changes in processes and customer expectations due to technological advances.

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0
venkat k 2020-02-12
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Doing so gives the company a competitive advantage while improving marketing and advertising performance.With that said, today I share the emerging trends in the AI industry, and what you need to know about moving into 2020.Also Read: Top 10 AI Trends Marketers Should Watch for In 2020Predictive AnalyticsYou don’t need a crystal ball to know the future.

Using analytics, a company can use models and trends to improve everything from its advertising to security.Not only is it more widely used, but it can also help businesses increase their bottom line while taking advantage of competitors, thanks to:The easy barrier to entry with easy to use and affordable platforms.2.

This is a 21% compound growth from 2016 and seems to be trending toward that, making it a worthwhile AI trend to keep your radar on.Higher Use Of Anomaly DetectionMissing budgets, breakdowns of integrations, and forgetting to start are some of the daily woes the agency faces.

These are all human failings, and also completely normal.

Ultimately, it allows agencies to focus on the things that humans do best, while AI takes care of optimizations in the background.Machine Learning-Driven CybersecurityCybersecurity is a growing concern worldwide.

In fact, 67% of small businesses will experience cyberattacks in 2018.

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venkat k 2020-05-13
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RPA (Robotic Process Automation) deals with the underlying opportunities of Artificial Intelligence that enabled RPA in an ERP ecosystem.Chatbots, simulate automate human conversation through voice commands, text chats, or both.

The boom of AI enables smarter Chatbots to understand unstructured human input by applying natural language processing (NLP).Also Read: Top 10 Ecommerce App Development Companies In New YorkHow to further increase the potential and overcome the limits of RPA?In recent years, RPA has been one of the most impactful technologies in process automation in all kinds of organizations.

However, the static setup does not allow the processing of unstructured data.AI is the needed game changer and adds an intelligence layer on top of RPA systems so that they can handle unstructured data thanks to their dynamic ruleset.Then RPA will be able to manage exceptions, and the system improves itself after further training.

AI can derive sense out of unstructured data and deliver the now structured data to the existing RPA systems.Algorithmisation is the process cycle of the gathering of information out of data for Machine Learning and creates new processes plus data for further processing again.

Chatbots integrated into existing RPA & ERP ecosystems can provide structured data out of the human conversation for the processing of the back-end systems.How can Chatbots support in Master Data Management?Let’s see how Chatbots can further optimize the master data management processes.

It also facilitates back-office employees and they can focus on exception handling or more value-adding tasks.

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venkat k 2019-11-04
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Artificial Intelligence in Insurance — Front Insights:Trends that business leaders need to be aware of.

In this article we will look at three key ways to drive savings for insurance carriers, brokers and policyholders, and enter into the transformations in the insurance industry:Behavioral Policy Pricing: Ubiquitous Internet of Things (IoT) sensors provide personalized data to pricing platforms, secure driver's auto insurance (called utility-based insurance), and allow people with healthy lifestyles to pay less for health insurance.Customer Experience & Coverage Personalization: AI allows for seamless automated buying experience using chatbots that pull users’ geographic and social data for personalized interactions.

Carriers allow customers to customize coverage for specific goods and events (called on-demand insurance)Fast, customized claims settlement: Adjustments to online interfaces and virtual claims make it more efficient to settle and pay claims after an accident while reducing the likelihood of fraud.

Customers can also choose to use their premiums to pay their claims (called peer-to-peer (P2P) insurance).Therefore, the key to introducing new technology is to convince people that automation is not just a Trojan horse to refute their claims — 60% of consumers have expressed concern about buying coverage via chatbot, according to a recent survey by Verta for.Three current AI application trends in insurance / Intertech:We examine three major AI insurance trends one by one, examining current technology, ongoing changes, and changes in the industry.

We begin with “Conduct Price”:1 — Behavioral Premium Pricing: Move IoT Sensors Insurance from Proxy to Source DataIoT Data IoT Data opens three main ways to launch personalized insurance pricing:You Pay Risk: Telematic and wearable sensor data allows lower premiums for less risky behavior, including less driving and more exerciseBundle Policy and Loss Prevention Hardware: Smart Home Companies Offer Policy Deductions to Customers of Censored Loss Prevention Technology, Enabling Device Cross-Selling, and InsuranceVerify and resolve claims: IoT data markets allow carriers faster access to validated risk management information, without relying on expensive estimates and audits.2 — Customer Experience & Coverage Personalization: AI interfaces allow better customer onboardingHere are three key ways that AI can enhance the insurance buying experience:Chatbots Identify You: Use Advanced Image Recognition and Social Data to Personalize Sales ConversationPlatforms Confirm Your Identity: Automatic Personal Identity Verification Accelerates Authentication Required for Coding and BindingCarriers can customize your coverage: machine learning allows for a completely online or app-based shopping experience.3 — Faster, Customized Claims Solution: AI will sue faster when fraud is reducedSpeed and success are the key to insurance business capabilities, as well as two key ways AI can improve customer satisfaction after litigation.Speed in resolving claims: This time-to-settlement metric is as important as what business paths consumers are willing to use.Reduce the likelihood of fraud: This declining-fraud metric is important to the solutions that insurance companies prefer to use.Conclusion: Benchmarking AI Solutions in InsuranceCustomers evaluate the performance of insurance products when they need to pay, not when they buy.

Unlike other products or services, customers are only able to judge the value the insurance carrier has to offer.

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venkat k 2019-11-05
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Artificial Intelligence (AI) technology has been developing for many years now; It can now be found not only in the field of technology but also in various places and industries.Technology that works on the nanometer scale often includes complex systems that do not fit the various aspects of AI.

In addition to merging the two technologies, the combined work in nanotechnology and AI also enhances the study in each field, leading to all sorts of new tools for gaining insights and communication technologies.Consider the following areas where AI and nanotechnology work together.MicroscopeAlthough atomic force microscopy (AFM) has seen significant progress in recent years, obtaining high-quality signals from these imaging devices can still be challenging.

The main problem is that the tip-pattern interactions that rely on this microscope are complex, heterogeneous and therefore not easy to decipher.

Imaging is segmented and combined with an AI algorithm that automatically determines whether or not cell cancer is based on historical current cell data.

The novel imaging system contradicts historical models for the cells being evaluated in real-time.Chemical ModelingAlgorithms are already being used to describe molecules and material frameworks to identify different properties and how they interact in different environments.

Natural advances have led to the integration of AI and the use of complex machine learning algorithms.From the modeling point of view, a variety of parameters must be correlated to create a dynamic description of an image or chemical system.

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0
venkat k 2020-01-31
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AI is one of the most talked-about topics in this digital world.

AI provides the eCommerce industry with smart and innovative business solutions.

It has valuable features and features for e-commerce platforms.Now, artificial intelligence or machine learning technology is balancing brand performance and user experience as it changes the course of work.

AI is one of the fastest legacies of technological advances due to various smart solutions that are transforming the e-commerce industry.

AI empowers users with many high-tech experiences, from websites to stores and from voice assistants to chatbots.

Since AI can pull all the crucial information from big data, it is easier to understand than the search terms they enter.

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0
venkat k 2020-02-28
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Artificial intelligence has been a distant dream for decades, but recent advances in Artificial Intelligence have shown that we can soon use it to solve some of society’s biggest problems.Almost two years ago, in January 2016, AI beat the world’s best game, which is more complex and has more powerful motions than the atoms we have in the universe.It shows that computers can now exceed human capabilities in some complex tasks, even if that task is a game.

AI is better in voice and face recognition, and error rates are getting smaller and lower, which is a sign of the onset of widespread AI use.While playing games and tagging Facebook photos is interesting and promising for AI tools, more practical applications of AI are on the horizon.

Those applications help the transportation industry address our biggest challenges in moving from place to place.Also Read: Artificial Intelligence in the Transportation IndustryHere are 4 important ways that AI can help improve our transportation system.1.

50% of the world’s population already lives in cities, and that percentage is expected to grow to 70% in the next 40 years.Public transport is a mandatory service in urban areas, as pollution and traffic from increasingly personal vehicles are becoming an even bigger problem.

AI helps urban design and traffic control in many ways, including adjusting variable speed zones based on traffic, traffic light timing, and smart pricing for vehicle tolls.2.

Avoiding collisions is a top priority for self-driving car developers, and these efforts have been largely successful.However, mini-communications between drivers, cyclists and pedestrians occur all the time road We don’t often record how often we make eye contact with others on the road.

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0
venkat k 2019-10-31
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The term “Ai services” may be a misnomer because most games do not use real AI techniques.

Game developers are usually not AI researchers and most games use predetermined models.AI in game development goes a long way toward defining the way computer opponents behave.

Behavior ranges from relatively simple models of action games to chess programs that can defeat champion human players.Most early video games, such as Pong (1972), only allowed human opponents to face each other.

Although computer-controlled opponents have been around since the beginning of Computer Space (1971).While human opponents are clearly a lot of fun to play with, the video game industry really took off when microprocessors allowed players to break into more sophisticated and challenging computer opponents.Space Invaders (1978) provided an early example of the challenge that computer-controlled opponents can bring to the game.

When the player shot down the aliens, the game increased significantly with fewer opponents.

This was a downside of the hardware limitations at the time, but Tomohiro Nishikado, who invented the game for Taito, abandoned it because it made the gameplay so exciting.While AI researchers have debated whether AI is the real thing in games, game developers have used technologies from AI research to create more challenging opponents.

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venkat k 2019-11-20
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Amazon issued a patent last week for a new technology that enables Alexa to track consumers’ physical, emotional, and behavioral states.

This technology allows Alexa to detect audible cues, such as cough or tone, how the user is feeling, emotionally or physically, and provide responses based on that information.For example, when a user requests voice recognition, Alexa coughs or sniffles, the assistant can respond by asking if the user wants to order the lounges.

Alexa can also use consumer demographic and behavioral information such as age, location, accents, and past search and purchase behavior.Alexa’s ability to constantly monitor and respond in real-time paves the way for brands to communicate with consumers in a simple way, which helps to increase brand awareness and increase voice purchases.

Here’s how:It exposes users to relevant skills they don’t use.

For example, if a user is diagnosed with anxiety through their voice, the voice assistant may suggest an unknown stress relief skill to the user.This allows Alexa to target consumers with brands related products and information.

Alexa can seemingly surface certain products based on consumers ’physical or emotional state at that exact moment, which can increase voice purchases.

venkat k 2019-10-24
img

What’s worse, why the sophisticated AI tool is locked inside the walls of a few billion-dollar tech companies, is no longer available.Today we are officially introducing Determined AI, which enables AI engineers everywhere to focus on models rather than infrastructure.

Determined AI supports this:GV (formerly Google Ventures),Extend partners, CRV, Haystack,SV Angel, The House, and Specialty Types.We are in the dark age of AI infrastructureAI and especially deep learning (DL) is becoming a very important computational workload for all types of businesses and industries.

For example, DL has dramatically improved the performance of autonomous vehicles at Waymo; Siri, Apple’s personal assistant who communicates through speech synthesis; And this has revolutionized Facebook’s ability to understand user sentiment.

Everyone has to do with existing tools, which are not bad for AI-based application development, as this example differs from traditional software development.

Consequently, organizations that rely on advances in AI — for anyone who works with vision, speech, or natural language — can mitigate risk without a radically new approach to AI infrastructure.Our focus:At Decisive AI, our goal is to empower deep learning at the speed of thought.

We started from the problems faced by DL researchers today and worked backward to provide a dramatically easier, seamless, integrated environment than traditional tools.Fully Interoperable:Determined AI frees your DL investment from the risk of cloud or hardware lock-in.

venkat k 2019-12-06
img

The future of retail looks dire, as more brick-and-mortar stores close their doors.

U.S. retailers have announced 8,558 store closures so far this year, with total U.S. store closures reaching 12,000 by the end of 2019, Cordite Research reported Friday.While the Internet and automation are usually responsible for these closures, the same technology could be a solution for physical store locations, said Paul Winsor, general manager at Data Robot.“If retailers want to stay open at the current stores they operate in, my recommendation to them is: Do they understand the changing habits of those customers, and how are they shopping with them, in those places?” Said Winsor.“To survive in a tough, tough retail market, you have to start your business and make predictions based on learning from your historical data,” he says.

Technology is around to help companies understand their business from a data perspective,” says Winsor.

“Data is not as personal and accurate as machine learning can help you.”To make predictions in the past, retailers look at daily and weekly transaction data and draw conclusions from it, Winsor said.As technology has evolved and convenience has become a priority, online stores have become the primary way to shop.

If retailers refuse to grow and adapt to emerging retail infrastructure, they will inevitably fall behind.AI helps retailers in three ways“With AI, we are dealing with machines that can simulate intelligent behavior or simulate intelligent human behavior, that is, sense, reason, action, and adaptation,” said Altimeter lead analyst Brian Solis.

“One of the most popular ways that leading brands use AI today is machine learning.”“The difference is that with machine learning, systems can differentiate models from pure data sets, and with the right management, learn from those data to predict and predict results and improve performance over time,” Solis says.

venkat k 2019-10-29
img

Objective:The aim of this review is to summarize the main topics in Artificial Intelligence (AI), their applications and limitations in surgery.

This paper reviews the key capabilities of AI services to help surgeons understand and critically assess new AI applications and contribute to new developments.Summary of Background Data:AI is composed of various sub-fields that provide potential solutions to each and every clinical problem.

Each of the major subsets of AI reviewed in this piece has also been used in other industries, such as autonomous cars, social networks, and deep learning computers.Methods:A review of AI papers across computer science, statistics, and medical sources has been conducted to identify key concepts and technologies in AI that are innovating in industries including surgery.

Limitations and challenges for working with AI are also reviewed.Results:Four main sub-fields of AI are defined:machine learningartificial neural networks,natural language processing andcomputer vision.Their current and future applications have been introduced to surgical practice, including big data analytics and clinical decision support systems.

The role of surgeons in the development of technology to optimize the implications and clinical impact of AI to surgeons is discussed.Conclusion:Surgeons are well-positioned to help integrate AI into modern practice.

Surgeons must partner with data scientists to capture data and provide a clinical context for the stages of care, as AI has the potential to revolutionize the way surgery is taught and practiced.

venkat k 2019-11-06
img

Over the past two years, the world has been filled with buzzing expectations about the promises and potential of AI for business.

Discovering new opportunities, working leads and closing deals.For these businesses, there is a “great” attitude.

Until you show me how it works on my day to day business, I’m done.“Others worry that the promise is too real and that the AI is here — and ready to replace them.Interestingly, the response to these two systems of thinking is the same: not just AI, but for small businesses or startups on their path to success, AI is a way of solving everyday business problems that are not only obsolete and reusable, you are better, smarter, more efficient and more More complex people.How AI affects business processes daily and creates more jobs.Simply put, the new world of AI is no longer just for organizations.

Companies like Salesforce, which have been committed to democratizing customer relationship management technology for years, are now doing the same for AI.So AI is real.

Quite simply, their experience of AI in consumer apps means that they expect you to know more about them, so that you can do more for them, and even give them the help and answers they are looking for before they ask.

Everything.Smart business processes mean growing business.For the past 40 years, businesses have seen huge changes in processes and customer expectations due to technological advances.

venkat k 2020-05-13
img

RPA (Robotic Process Automation) deals with the underlying opportunities of Artificial Intelligence that enabled RPA in an ERP ecosystem.Chatbots, simulate automate human conversation through voice commands, text chats, or both.

The boom of AI enables smarter Chatbots to understand unstructured human input by applying natural language processing (NLP).Also Read: Top 10 Ecommerce App Development Companies In New YorkHow to further increase the potential and overcome the limits of RPA?In recent years, RPA has been one of the most impactful technologies in process automation in all kinds of organizations.

However, the static setup does not allow the processing of unstructured data.AI is the needed game changer and adds an intelligence layer on top of RPA systems so that they can handle unstructured data thanks to their dynamic ruleset.Then RPA will be able to manage exceptions, and the system improves itself after further training.

AI can derive sense out of unstructured data and deliver the now structured data to the existing RPA systems.Algorithmisation is the process cycle of the gathering of information out of data for Machine Learning and creates new processes plus data for further processing again.

Chatbots integrated into existing RPA & ERP ecosystems can provide structured data out of the human conversation for the processing of the back-end systems.How can Chatbots support in Master Data Management?Let’s see how Chatbots can further optimize the master data management processes.

It also facilitates back-office employees and they can focus on exception handling or more value-adding tasks.

venkat k 2019-11-05
img

Artificial Intelligence (AI) technology has been developing for many years now; It can now be found not only in the field of technology but also in various places and industries.Technology that works on the nanometer scale often includes complex systems that do not fit the various aspects of AI.

In addition to merging the two technologies, the combined work in nanotechnology and AI also enhances the study in each field, leading to all sorts of new tools for gaining insights and communication technologies.Consider the following areas where AI and nanotechnology work together.MicroscopeAlthough atomic force microscopy (AFM) has seen significant progress in recent years, obtaining high-quality signals from these imaging devices can still be challenging.

The main problem is that the tip-pattern interactions that rely on this microscope are complex, heterogeneous and therefore not easy to decipher.

Imaging is segmented and combined with an AI algorithm that automatically determines whether or not cell cancer is based on historical current cell data.

The novel imaging system contradicts historical models for the cells being evaluated in real-time.Chemical ModelingAlgorithms are already being used to describe molecules and material frameworks to identify different properties and how they interact in different environments.

Natural advances have led to the integration of AI and the use of complex machine learning algorithms.From the modeling point of view, a variety of parameters must be correlated to create a dynamic description of an image or chemical system.

venkat k 2020-02-28
img

Artificial intelligence has been a distant dream for decades, but recent advances in Artificial Intelligence have shown that we can soon use it to solve some of society’s biggest problems.Almost two years ago, in January 2016, AI beat the world’s best game, which is more complex and has more powerful motions than the atoms we have in the universe.It shows that computers can now exceed human capabilities in some complex tasks, even if that task is a game.

AI is better in voice and face recognition, and error rates are getting smaller and lower, which is a sign of the onset of widespread AI use.While playing games and tagging Facebook photos is interesting and promising for AI tools, more practical applications of AI are on the horizon.

Those applications help the transportation industry address our biggest challenges in moving from place to place.Also Read: Artificial Intelligence in the Transportation IndustryHere are 4 important ways that AI can help improve our transportation system.1.

50% of the world’s population already lives in cities, and that percentage is expected to grow to 70% in the next 40 years.Public transport is a mandatory service in urban areas, as pollution and traffic from increasingly personal vehicles are becoming an even bigger problem.

AI helps urban design and traffic control in many ways, including adjusting variable speed zones based on traffic, traffic light timing, and smart pricing for vehicle tolls.2.

Avoiding collisions is a top priority for self-driving car developers, and these efforts have been largely successful.However, mini-communications between drivers, cyclists and pedestrians occur all the time road We don’t often record how often we make eye contact with others on the road.

venkat k 2020-02-24
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Analyzing these complex data to obtain meaningful value is often excessive, which hinders our ability to find appropriate solutions in a timely manner.Unlocking these complex scenarios such as how humans can behave and interact can create opportunities.Many large tech companies are already developing artificial intelligence solutions.

They can reduce operational costs and reduce problems in the following ways:Increase automationOptimize asset managementImprove operational performanceIdentify efficienciesDecrease downtimeHealthcareFrom detecting early forms of cancer or disease to diagnosing MRI scans — especially data-driven — machine learning technology brings huge benefits to the health care industry.By analyzing large amounts of medical data, AI can help doctors give their patients faster and more accurate treatment and learn from making better decisions going forward.For patients, the AI-driven health care system can ease some of the burdens on a system that is struggling to keep up with the ever-increasing demand.

Keeping this technology in your pocket can help you make better health decisions, diagnose disease and other health risks early, avoid expensive procedures and live longer.Consumer Goods and ServicesFrom Google search to self-driving cars.

They know what to look for, at what time of day, when you pause, rewind, move fast or skip.

From sentiment to watching habits, Netflix watches it all in real-time.In 2016, SAP announced three programs to empower its ecosystem to make it's business applications smarter and create machine learning applications for customers.These programs help solve problems by eliminating bias in recruiting businesses and automating the time-consuming invoice-matching process.

SAP Clip is a revolutionary new machine learning-enabled intelligence that enables new levels of automation and new ways of doing business.FinanceAI technology is being used to look at financial models to achieve high levels of trend analysis, predict future pricing models, identify new markets and predict supply chain risks.Deep Knowledge Ventures, a Hong Kong-based venture capital firm, has announced that its program, called Vital, will be new to its board of directors.

venkat k 2019-12-13
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It adds a plethora of valuable elements and features to the e-commerce platforms.Now, brand performance and user experience are balancing as artificial intelligence or machine learning technology is changing the tedious working pattern.

AI-based mobile and web applications range from the ability to identify patterns, data sets, and create a personalized experience.

This also creates a unique approach that is more effective than any human being.AI has empowered users with many high-tech experiences ranging from websites to stores and from voice assistants to chatbots.

With a simple click, the user can get appropriate and desired results.

Depending on the image, the user can achieve the desired result.Personalized RecommendationsAI is helping by suggesting free recommendations by pop up or text.

As a result, users rate brands and their goods & services that are directly proportional to RoI.Voice AssistanceAs technology progresses it is making the shopping experience pretty worthy.

venkat k 2020-05-12
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In U.S Drivers add 81 extra hours to their arrival each year due to traffic.

The other U.S. cities are also worse, these cities are known for difficult driving conditions with hills, bridges, and bikers.Diverse road conditions cause heavy traffic, but companies like Uber are coming to Pittsburgh to test autonomous vehicles.

And, besides the AV, that traffic technology includes an AI system called Sertrack, which allows traffic lights to be adapted to traffic conditions without having to rely on pre-programmed wheels.At installed lights, the team behind the system estimated that travel time was reduced by 25%, braking by 30%, and idle by more than 40%.

It costs about $ 20,000 to wire up and install Surtrack at the intersection.Sertrack works by tracking traffic and creating attendance models.

First, hardware including a computer, camera, or radar device is installed at the intersection.

Through communication with the below models, the processing is done in a way that creates a local plan from multiple data sources.

venkat k 2019-12-10
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As Artificial Intelligence (AI) and machine learning are ubiquitous, we will soon be struggling to avoid using the benefits that any industry can offer them.

Telecommunications is one of the fastest-growing industries, as well as using artificial intelligence and machine learning in many aspects of their business, ranging from improving the customer experience to improving operational reliability.

Here are some of the most common applications.Customer service and customer satisfactionAlmost every telecom major uses artificial intelligence and machine learning to improve its customer service by using virtual assistants and chatbots.

In one example, customer satisfaction improved by 68 percent after Vodafone introduced its chatbot TOBi.As a gatekeeper, chatbots analyze requests, learn to guide and raise customer queries if needed, identify sales opportunities and alert the customer to other products and services that are of interest to them, and manage most of them without human intervention.

AT, Verizon, Comcast, and every other large-scale telco uses AI for better customer service.Thanks to artificial intelligence and machine learning, the ability to provide speech and voice services such as chatbots is available.

Not only is it used in chatbots, but it also extends service offerings such as Comcast’s XI Talking Guide, which “speaks” network names/time slots, shows titles and helps users navigate through their television options.

venkat k 2020-02-12
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Doing so gives the company a competitive advantage while improving marketing and advertising performance.With that said, today I share the emerging trends in the AI industry, and what you need to know about moving into 2020.Also Read: Top 10 AI Trends Marketers Should Watch for In 2020Predictive AnalyticsYou don’t need a crystal ball to know the future.

Using analytics, a company can use models and trends to improve everything from its advertising to security.Not only is it more widely used, but it can also help businesses increase their bottom line while taking advantage of competitors, thanks to:The easy barrier to entry with easy to use and affordable platforms.2.

This is a 21% compound growth from 2016 and seems to be trending toward that, making it a worthwhile AI trend to keep your radar on.Higher Use Of Anomaly DetectionMissing budgets, breakdowns of integrations, and forgetting to start are some of the daily woes the agency faces.

These are all human failings, and also completely normal.

Ultimately, it allows agencies to focus on the things that humans do best, while AI takes care of optimizations in the background.Machine Learning-Driven CybersecurityCybersecurity is a growing concern worldwide.

In fact, 67% of small businesses will experience cyberattacks in 2018.

venkat k 2019-11-04
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Artificial Intelligence in Insurance — Front Insights:Trends that business leaders need to be aware of.

In this article we will look at three key ways to drive savings for insurance carriers, brokers and policyholders, and enter into the transformations in the insurance industry:Behavioral Policy Pricing: Ubiquitous Internet of Things (IoT) sensors provide personalized data to pricing platforms, secure driver's auto insurance (called utility-based insurance), and allow people with healthy lifestyles to pay less for health insurance.Customer Experience & Coverage Personalization: AI allows for seamless automated buying experience using chatbots that pull users’ geographic and social data for personalized interactions.

Carriers allow customers to customize coverage for specific goods and events (called on-demand insurance)Fast, customized claims settlement: Adjustments to online interfaces and virtual claims make it more efficient to settle and pay claims after an accident while reducing the likelihood of fraud.

Customers can also choose to use their premiums to pay their claims (called peer-to-peer (P2P) insurance).Therefore, the key to introducing new technology is to convince people that automation is not just a Trojan horse to refute their claims — 60% of consumers have expressed concern about buying coverage via chatbot, according to a recent survey by Verta for.Three current AI application trends in insurance / Intertech:We examine three major AI insurance trends one by one, examining current technology, ongoing changes, and changes in the industry.

We begin with “Conduct Price”:1 — Behavioral Premium Pricing: Move IoT Sensors Insurance from Proxy to Source DataIoT Data IoT Data opens three main ways to launch personalized insurance pricing:You Pay Risk: Telematic and wearable sensor data allows lower premiums for less risky behavior, including less driving and more exerciseBundle Policy and Loss Prevention Hardware: Smart Home Companies Offer Policy Deductions to Customers of Censored Loss Prevention Technology, Enabling Device Cross-Selling, and InsuranceVerify and resolve claims: IoT data markets allow carriers faster access to validated risk management information, without relying on expensive estimates and audits.2 — Customer Experience & Coverage Personalization: AI interfaces allow better customer onboardingHere are three key ways that AI can enhance the insurance buying experience:Chatbots Identify You: Use Advanced Image Recognition and Social Data to Personalize Sales ConversationPlatforms Confirm Your Identity: Automatic Personal Identity Verification Accelerates Authentication Required for Coding and BindingCarriers can customize your coverage: machine learning allows for a completely online or app-based shopping experience.3 — Faster, Customized Claims Solution: AI will sue faster when fraud is reducedSpeed and success are the key to insurance business capabilities, as well as two key ways AI can improve customer satisfaction after litigation.Speed in resolving claims: This time-to-settlement metric is as important as what business paths consumers are willing to use.Reduce the likelihood of fraud: This declining-fraud metric is important to the solutions that insurance companies prefer to use.Conclusion: Benchmarking AI Solutions in InsuranceCustomers evaluate the performance of insurance products when they need to pay, not when they buy.

Unlike other products or services, customers are only able to judge the value the insurance carrier has to offer.

venkat k 2020-01-31
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AI is one of the most talked-about topics in this digital world.

AI provides the eCommerce industry with smart and innovative business solutions.

It has valuable features and features for e-commerce platforms.Now, artificial intelligence or machine learning technology is balancing brand performance and user experience as it changes the course of work.

AI is one of the fastest legacies of technological advances due to various smart solutions that are transforming the e-commerce industry.

AI empowers users with many high-tech experiences, from websites to stores and from voice assistants to chatbots.

Since AI can pull all the crucial information from big data, it is easier to understand than the search terms they enter.

venkat k 2019-10-31
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The term “Ai services” may be a misnomer because most games do not use real AI techniques.

Game developers are usually not AI researchers and most games use predetermined models.AI in game development goes a long way toward defining the way computer opponents behave.

Behavior ranges from relatively simple models of action games to chess programs that can defeat champion human players.Most early video games, such as Pong (1972), only allowed human opponents to face each other.

Although computer-controlled opponents have been around since the beginning of Computer Space (1971).While human opponents are clearly a lot of fun to play with, the video game industry really took off when microprocessors allowed players to break into more sophisticated and challenging computer opponents.Space Invaders (1978) provided an early example of the challenge that computer-controlled opponents can bring to the game.

When the player shot down the aliens, the game increased significantly with fewer opponents.

This was a downside of the hardware limitations at the time, but Tomohiro Nishikado, who invented the game for Taito, abandoned it because it made the gameplay so exciting.While AI researchers have debated whether AI is the real thing in games, game developers have used technologies from AI research to create more challenging opponents.

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