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AI AI in web development Artifical intelligence

Top 10 Programming Languages to Become an AI Developer

programming languages

Artificial Intelligence (AI) is undergoing a period of intense growth after being stagnant for years. A career path in AI has become a very appealing choice for individuals interested in data science and software engineering, with the demand for AI skilled professionals increasing over these recent years. Here are the top ten programming languages to become an AI developer.

Artificial Intelligence offers businesses and software developers a whole realm of possibilities. AI has brought about a revolution in the technology world, with it still rising and expecting to reach human intelligence.

Required Programming Languages for AI Developers

It is because developers can discover, innovate, and adapt their ability to meet human and organizational needs. Where do you start if you would like to take advantage of this highly in-demand skill?

Top 10 AI Programming languages

Python

Python is an interpreted language, and it is called that because it goes through an interpreter, which turns your code into the language understood by your computer’s processor.

Because of the simplicity and ease of use, Python deserved a chance to be first in the list for Programming languages for AI Developer.

Python’s syntax is very easy and can be learned quickly. This makes it quite simple to implement AI algorithms in it.

Python has been leading in the market with its counterintuitive support and pre-built libraries (like NumPy, Pandas, Pybrain, and SciPy) that help accelerate AI development.

Top features of Python

  • It is easy to use
  • Interpreted and cross-platform
  • Free and open-source
  • Object-oriented
  • GUI programming support
  • Dynamic memory allocation

Java

Java is a highly versatile, robust, and transparent language supported by several libraries. Ever since it first appeared in 1995, it has seen a huge growth in the market. Java is also very user-friendly, easy-to-debug, and runs through platforms without engaging in additional recompilation.

The Java-code can be run on any Java-supported platform with its Virtual Machine technology. Artificial intelligence does indeed have a lot to do with search algorithms, genetic programming, and artificial neural networks, making it one of the ideal choices for Programming languages for AI Developers.

Top features of Java

  • It is simple and easy to use
  • It is an object-oriented language.
  • Platform independent
  • Secured and robust
  • Architecture neutral
  • Interpreted language
  • Multithreaded

Julia

Julia is a high-level, efficient, and dynamic programming language. While it is a general-purpose language and can be used to write any application, many of its features are well-suited for numerical computing that’s required by AI.

The central framework for programming involves a parametric polymorphism and multiple dispatch mechanism. In comparison to the above languages, Julia might not sound like an ideal choice.

As a consequence, a substantial number of libraries or a quickly evolving community do not support it. However, Wrappers like TensorFlow.jl and Mocha provide excellent support for DL.

Top features of Julia

  • It is fast and dynamic
  • It is reproducible
  • It is composable
  • It is open-source
  • Provides asynchronous I/O, metaprogramming, debugging, logging, profiling, a package manager

LISP

Lisp is one of the oldest and most appropriate languages for AI development. It was introduced by the father of Artificial Intelligence, John McCarthy, in the year 1958.

It has the capacity to process symbolic data successfully. Lisp can be represented as a mathematical notation for computer programs. AI developers frequently turn to Lisp for a series of AI projects that are ML centric.

LISP is renowned for its outstanding prototype capabilities with automated garbage collection and the simple dynamic development of new objects. It has an integrated development cycle for analyzing expressions and recompiling functions or files when the program is still running.

Top features of LISP

  • It is machine-independent
  • It an iterative design methodology
  • It provides high level debugging.
  • It is an object-oriented language.
  • It is expression-based.
  • Provides a complete I/O library.

Scala

Scala comes from the JVM family, much the same as Java. Scala is a relatively new language in the AI domain. Recently several companies and start-ups have incorporated it into their business, allowing it to gain some recognition.

Developers from all around the world like Scala because of the many features that it has to offer. Also,  ScalaNLP, DeepLearning4j, etc., are some of the tools that facilitate the smooth AI developing process with Scala.

It is ideal for projects that need versatility. It merges the advantages of functional and imperative programming models while serving as a strong tool that helps to create highly competitive applications while, at the same time, harnessing the strengths of an OO approach.

Top features of Scala

  • Type inference.
  • Singleton object.
  • Immutability.
  • Case classes and Pattern matching.
  • Concurrency control.
  • String interpolation.
  • Higher-order function.

R

R is one of the most powerful languages and environments for statistical analysis and manipulation of data.

In addition to being an open-source and general-purpose language, R includes several packages, including RODBC, Gmodels, Class, and Tm that are also being used in machine learning.

These packages implement machine learning algorithms quite simply. Statistics form the basis of ML, and AI and R are popularly known to revolve around statistics a lot.

R is considered to be similar to the popular statistical applications SAS and SPSS. It is suitable for data analysis, visualization, and general statistics.

However, compared to Python, it is less versatile but also more specialized.

Top features of R

  • It is free and open-source
  • It is robust and highly extensible
  • Effective data handling
  • It provides a storage facility
  • Integrates with  C/C++, Java, Python, etc.
  • It is platform-independent

Haskell

Haskell is a general-purpose, statically typed, purely functional programming language. It was developed in the 1990s with non-strict semantics.

It gained popularity in academic circles but was soon known to be used by tech giants like Facebook and Google. Haskell is being used for research as it supports embedded domain languages, which play a large role in programming language research and AI.

Unlike Java. Haskell is ideal for dealing with abstract mathematics because it enables libraries to construct expressive and efficient AI algorithms.

HLearn, for instance, uses regular algebraic structures such as modules and monoids for expressing and speeding up basic ML algorithms.

Top features of Haskell

  • It is a functional language
  • Modularity
  • Statically typed
  • It is easy and cost-effective
  • Lazy language

Rust

Rust is a multi-paradigm programming language boasting of being secure, efficient, and safe concurrency.

Rust is syntactically similar to C++ and provides memory safety without using garbage collection. Rust has actually been chosen in Stack Overflow’s annual developer surveys for the last 4 years as the most popular and most loved language that fills the void that can be found in other languages.

The newly open-sourced Verona Project also uses Rust principles, an emerging language that may allow Microsoft to safely maintain legacy C and C# code.

Mozilla Research defines Rust as a “systems programming language that focuses on speed, memory safety, and parallelism.â€�

Top features of Rust

  • Zero cost abstraction.
  • Pattern matching.
  • Error messages.
  • Move semantics.
  • Threads without data races.
  • Guaranteed memory safety.
  • Safe memory space allocation.

Prolog

Prolog is a logic programming language associated with artificial intelligence and computational linguistics. When we talk about programming languages for AI developers, this language stands next to Lisp.

Efficient pattern matching, tree-based data structuring, and automated backtracking are some of this language’s features. These features provide a remarkably strong and versatile structure for programming.

Prolog is commonly used in medical projects as well as the production of AI systems for experts.

Top features of Prolog

  • It is a declarative language
  • It uses the language of predicate calculus.
  • It manages lists and recursion naturally.
  • It is a fully object-oriented language.
  • Pattern matching and unification
  • It supports direct linkage with C/C++.

MATLAB

MATLAB is a proprietary multi-paradigm programming language and numerical computing environment that is introduced by MathWorks.

The use of Matlab is suggested for complex mathematical functions. Matlab offers  AI capabilities like Caffe and TensorFlow. It helps you to incorporate AI into the entire workflow.

In a sense, even without machine learning knowledge and experience, you can work around AI with MATLAB. You can use applications and easily play with various approaches.

Top features of MATLAB

  • It is a high-Level language.
  • Interactive environment.
  • Handling graphics.
  • Mathematical functions library.
  • Application program interface (API).
  • Interfacing with other languages.
  • It provides built-in graphics.

To Sum Up

Artificial intelligence is a branch of engineering that ultimately seeks to render intelligent computers and to target the way an intelligent human thinks. There are unique features and advantages of each language.

However, you have to select the perfect language for your AI projects as an AI Engineer and not just follow the herd blindly. It is best to learn about each language individually and then understand if those will work in your favor.

Also, the selection of programming language for AI often depends on a variety of main factors. Consider your business type, whether you are just getting started or already have a setup, how the market looks, who your clients or customers are, what problems you are trying to solve and what your objectives are, etc.

Besides that, many solutions are not dependent on one technology alone. So, keep the experimentation on until you find that ideal language.

The post Top 10 Programming Languages to Become an AI Developer appeared first on ReadWrite.

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AI Artifical intelligence chatbot Customer Service tourism travel industry

Chatbots for Travel and Tourism: Travel Experience Made Better

chatbots for travel

A decade ago, if you had fancied a vacation to the Bahamas, it will take at least or half of it to plan and get the itinerary in place. Booking flight tickets required visiting multiple travel agents in person, comparing costs, and then fixing an agreement with the best of the lot. Then there was planning the itinerary, choosing the place of stay, mode of commute — all of which is not for those who take traveling lightly. Here are chatbots for travel and tourism — travel experience made better.

If you are someone like me, packing the rucksack, wait until a few hours before the flight takes off. Meticulous travel planning is not my cup of tea. Luckily for folks like me, chatbots are taking over travel planning. Along with it, they are also reforming travel and hospitality as we know it for good. 

Here are some real-world applications that are out there right now. The next time you even think of planning a vacation, you might stumble upon them or their likes. 

Real-world chatbot applications in travel and tourism

What can chatbots possibly do in travel planning? 

Aren’t they supposed to be super-complicated software systems that only large enterprises use? 

Well, this is one of the myths that has shrouded chatbots as a mystery technology. The fact is, chatbots are logic-based programs that can be used even for basic functionalities. That makes them a perfect fit for the travel and tourism industry, where the scale of low-priority and high-volume* transactions is high. 

*Low-priority — frequently asked questions that can be easily addressed by a system without the intervention of a human agent. 

High-volume — hundreds, thousands, or even more simultaneous real-time transactions. 

1. Integrating instant messengers with chatbots

Instant messengers have literally replaced emails and text messages for quick messaging. They are fast, convenient, and save a lot of time. Imagine the convenience they can introduce to the travel and tourism industry? 

Let’s take that convenience one step ahead. What if chatbots can converse through instant messengers. As you are reading this piece, there could be countless conversations happening on instant messengers that are being led by chatbots. In fact, WhatsApp, which has become the de-facto medium for instant messaging, offers chatbot integration. Other messengers like Facebook are also popularly used by travelers. 

Business owners like tour operators, hotel property owners, travel aggregators, etc., can use chatbots to automate conversations with customers. The IM-chatbot integration makes it possible for travel businesses to have an always-available virtual assistant who can respond to guests through instant messages. In fact, airlines are already using IMs to send boarding passes and flight details to travelers.

Integrating instant messengers with chatbots

Source: Airline Staff Rates

What benefits do integrating a chatbot with an instant messenger offer?

  • It spares the business owner from having to initiate basic conversations.
  • Standard or canned responses to frequent queries can be handled by the chatbot.
  • The user gets a trail of information in an instant messaging app that they use the most.

2. Make ticket bookings based on real-time fare comparisons

Like I mentioned earlier, flight ticket bookings have taken the online route. Millennial customers have, in fact, moved to the mobile route where travel aggregator apps and flight booking apps make things easier than ever before. 

However, there is one challenge that is still troubling travelers. Finding the best flight tickets. If you have tried booking a flight ticket before, you know how the ticket cost fluctuates with a mind of their own. It is complicated even for a net-savvy person to stay track of it. Also, it is almost impossible to comb through all airline websites to find the best fare. 

Can chatbots help here? Of course, they can. Like how they facilitate booking management for travel business owners, chatbots can help travelers find the best flight tickets as well. 

A chatbot can help determine how much each airline is charging for a flight cost from New Zealand to Copa on a given day. The search gives class-wise details that make it easy to book or look for alternative options instantly.

Skyscanner, a popular website for finding flight ticket prices, has already surpassed one million chatbot interactions (eConsultancy Interview with Filip Filipov, Skyscanner). If the user is not satisfied with the ongoing price, they can instruct the chatbot to set a price alert. The chatbot will notify the user when there is a price change. This is akin to having a personal travel agent who finds the best flight tickets at the nick of the time.

Make ticket bookings based on real-time fare comparisons

Image Credit: Chatbots Life

3. Facilitate web check-ins 

Chatbots can help travelers initiate web check-ins for flights or hotels through a chatbot for social media, instant messenger, or a website. Sounds too futuristic? Well, the truth is most have already used the airline website for web check-ins. A chatbot can make the chore a tidbit easier by enabling you to do it from your mobile phone. 

chatbot Facilitate web check-ins

Image Credit: Engati

This has several benefits to it:

  • You can check-in if you are stuck in traffic en route to the airport.
  • If you don’t have access to a computer
  • Or make use of premium member privileges that are available only on mobile.

4. Sketch a detailed travel itinerary

Until recently, there were two types of travel: business and leisure. But, millennials who value experiences more than material possessions are using their business travels for leisure as well. This has led to the formation of a new travel type: Bleisure. 

Bleisure is travel where business matters and leisure activities are taken care of in the same trip. According to Forbes, Bleisure trips are growing by 20% since 2016. While leisure sounds great as a concept, it poses unique challenges for the traveler. To begin with, finding nearby attractions for exploration. 

Of course, there are travel websites, blogs, and magazines that describe at length where to go, when, and how. However, they are usually written from a leisure travel perspective and do not consider leisure.

For millennials who want to make the best use of the opportunity, a chatbot based recommender system can help. The chatbot, which was probably used to book the flight ticket, can suggest nearby attractions. The traveler can plan the itinerary and also avail of deals for hotel bookings. In short, it is a win-win situation for all the parties involved. 

chatbot Sketch a detailed travel itinerary

Source: Chatbots Life

5. Customer Support— 24/7 

Chatbots do not need recesses, holidays, or weekends off. They are always available. You can make them work on your website, mobile app, or even integrate them with the social handles of your business. That makes them perfect for donning the hat of customer support professionals. 

In their customer service role, chatbots can offer:

  • Real-time flight status updates
  • Request for change in hotel arrival times
  • Cab or hotel service requests
  • Book restaurant tables

If you think about it, travel is a global phenomenon. Travelers are not always from the same time zone or destination. This can cause serious staffing issues in the support department of a travel business. A chatbot can fill the void by fending basic queries that come in large volumes from customers. 

What’s more fascinating is that a single chatbot can handle dozens or more queries at the same time from multiple customers. Compared to that, a single customer service rep can handle only one customer at a time. That is a huge leap in productivity that we are looking at. 

chatbot for Customer Support— 24/7

Source: Chatfuel

Final thoughts: 

Travel is a personal and intimate experience. For the experience-driven millennial generation, it is one of the priorities in life. Like everything else, travel businesses must also take efforts to improve the customer experience with the aid of technology. Chatbots provide just the means for that. 

They enable travelers to make quick travel plans, sketch out a travel itinerary, avail the best deals on hotel bookings, and much more. They provide the convenience of on-the-go lifestyle arrangements that mobile has made us accustomed to.

Still more, chatbots will enable travel business owners to maximize their productivity without shooting their own foot with hefty costs. 

Be it for travelers or travel businesses; chatbots prove to be worthy virtual companions.

The post Chatbots for Travel and Tourism: Travel Experience Made Better appeared first on ReadWrite.

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AI AI in Retail AR/VR Artifical intelligence Augmented Reality Augmented reality in retail covid-19 Impact of COVID-19 Sales virtual dressing room virtual fitting room

Virtual Dressing Room to Increase Sales During COVID-19

virtual dressing room

COVID-19 has changed the way people worldwide behave daily, and nowhere is this felt more keenly than in bricks-and-mortar retail. For decades, retailers have been trying various customer engagement strategies to bring people in and let them browse samples and linger to their heart’s content. But the pandemic has made nearly all those experiences risky and undesirable. Personal safety wins out of the desire to try on clothing, jewelry, makeup, and other wearable products.

Increasingly, with COVID-19, retail businesses are turning to virtual dressing rooms as an alternative for their customers.

A virtual dressing room allows a user to upload a video of themselves and then renders an Augmented Reality image of the person modeling their perspective items.

Certain sectors of the retail industry have already been embracing Augmented Reality dressing rooms, most notably the cosmetics and jewelry industries. But many more retail sectors are adopting virtual dressing rooms, and the pandemic has accelerated the process greatly.

Artificial Intelligence in Virtual Dressing Rooms

Like many digital business applications, virtual dressing rooms are driven by recent advances in technology, from AR and VR to Artificial Intelligence. In fact, technology is advancing so quickly that one of the barriers to adoption is simply that many people don’t realize how good virtual dressing rooms can be if they’ve never tried one before.

But more and more consumers are trying them and generally like their experiences. As a result, the virtual dressing room market looks to have staying power even after COVID-19 becomes less of a clear-and-present threat. By 2027, the virtual dressing market is projected to be a $10 billion industry.

Virtual Dressing Rooms Becoming Mainstream

For several years, certain retailers have toyed with virtual dressing room solutions and related apps, although frequently, these have been limited in scope and with mixed results. However, the combination of technology-driven increases in quality and the pandemic driving customers away from physical store locations has led to a significant uptick in virtual dressing room adoption.

Global retail giants like Macy’s and Adidas have led the way in virtual dressing room implementation, with many smaller retailers following suit.

Amazon is also involved in virtual dressing room development, as its online retail model continues to gobble up market share.

For many retailers, embracing virtual dressing rooms is a necessity right now. They’ve blocked off their physical dressing rooms and forbade customers to handle merchandise like they once did out of fears that these behaviors will spread COVID-19. And many customers simply aren’t coming out to stores regardless.

In today’s retail landscape, the virtual dressing room represents an opportunity to recapture some of the lost business that’s crushing most retailers’ profit margins.

How Virtual Dressing Rooms Work

From a technical standpoint, the two broad technologies pivotal to the virtual dressing room are Augmented Reality and Artificial Intelligence. These are huge domains that stretch far beyond the scope of a virtual dressing room solution, and it’s useful to understand just how these technologies apply here.

The virtual dressing room process begins with video capture of the person who will be trying on the virtual item. Often, the recording device is a mobile smartphone. A smartphone is an ideal vehicle because it contains both the camera to capture video and a screen to display the AR image of the person/body part with the wearable item modeled.

The video is parsed by human pose estimation algorithms that identify a range of key points or locators on the human body, which allow the application to understand the contours, size, and spatial location of the person. Often, AI deep learning routines are used to make these determinations. The accuracy of these AI-driven processes can be far superior to a human programmed process, allowing for far greater fidelity in virtual dressing room development.

Once the body’s dimension and location are fixed, the application then appends the item of clothing or accessory to the image on the screen, allowing the user to model that item virtually in a 3-D, photorealistic display.

Pros and Cons of Virtual Dressing Rooms

Like any business or technological innovation, virtual dressing rooms have their advantages and disadvantages when compared to the traditional model.

It’s important to grasp that virtual dressing room technology continues to develop and evolve, and as the process continues the industry will change. Former drawbacks may be mitigated, and advantages may heighten as supporting technology improves.

But even as some problems may fade in relevance, others may develop. The following pros and cons represent a snapshot of the short — and medium-term projections for the virtual dressing room landscape.

Benefits of Virtual Dressing Rooms

The most obvious benefit to a virtual dressing room is giving the customer the ability to sample and model products remotely. But for this to be worthwhile, the AR rendering has to be realistic enough to be useful. If a user doesn’t feel comfortable with the image they’re seeing, a virtual dressing room is a failure.

Fortunately, the science of capturing the human body and rendering it in a virtual environment is one that engineers and developers are devoting massive amounts of time and resources to. While virtual dressing rooms aren’t the most important or lucrative application of these processes, we reap the rewards of that development and innovation.

The real game-changer is the implementation of artificial intelligence in the video capture and rendering process. Deep learning algorithms can estimate and display the user’s full body, face, head, hands, feet, or any other specific body area with rapidly increasing clarity and accuracy.

This is taking us toward the point where the average shopper regards a virtual dressing room as roughly equivalent in quality to the physical experience. Once we’ve achieved that benchmark, the traditional dressing room is nearly entirely obsolete.

Potential Drawbacks to Virtual Dressing Rooms

Many of the current drawbacks to virtual dressing rooms are temporary issues likely to be addressed in the coming years.

People are excellent judges of the human form, especially their own. If a virtual dressing room image has minor imperfections, this can detract from the immersive experience and leave a customer uncertain about whether they can trust what they’ve seen.

In some cases, virtual dressing room solutions are close but to quite up to the highest standard, meaning that customers would prefer traditional ones if given a choice.

During this pandemic, virtual dressing rooms receive a bump simply by being the only realistic option for people looking to minimize their COVID-19 risk. However, at some point in the next year or so, countries will begin to get the pandemic under control via the release of vaccines.

At this point, the question is whether virtual dressing rooms will offer a seamless and accurate experience, one good enough to keep people using them when life can return more to normal. This is where the industry will be continuing to focus.

One final potential drawback worth mentioning is that virtual dressing rooms can pose a data security issue. The process captures users’ face and body data and background images from wherever the user is filming.

It would be possible for a developer to engineer a virtual dressing room solution that pulls biometrical data and geolocation data from its users. That data could then be used to create profiles of those users, allowing third parties to use this info in a variety of ways.

This particular concern is a universal one in our increasingly digital world, far from unique to virtual dressing rooms. But the video data captured here is particularly intimate, and users may have special concerns.

In 2020, the advent of COVID-19 has reshaped the retail landscape in a seismic way. Consumers avoid stores and businesses find the physical process of trying on and sampling wearable items riskier. In this environment, virtual dressing rooms are being adopted more and more.

But the virtual dressing room concept is more than just a quick-fix workaround for the pandemic. Hand-in-hand with the rise of online retail, virtual dressing rooms have the potential to supplant the traditional dressing room. As AI technology matures, a larger group of consumers will likely find themselves using virtual dressing rooms even afterlife returns more to normal.

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AI ai in fitness Artifical intelligence digital fitness fitness apps fitness trainer Lifestyle

How Artificial Intelligence Innovations are Used in the Fitness Industry

ar in fitness industry

It’s hard to find an industry that isn’t in the process of being transformed by digital technologies, and the world of fitness is no exception. While people have been working out or exercising for decades, if not centuries, how they’re doing so is rapidly evolving. Here is how artificial intelligence innovations are used in the fitness industry.

Technologies like digital wearables enhanced with artificial intelligence are a natural fit for the fitness industry. Some of these products and solutions have already seen increasingly widespread adoption, while others are only beginning to penetrate consumer consciousness.

Finally, coming full circle into the field of fitness-related is AI. Advances in AI allow for more responsive, customizable, and immersive digital fitness assistants and helpers with each successive year.

AI-Based Personal Trainers

One aspect of fitness that has consistently brought people out to their local gym has been a lack of expertise. If you want a sustainable and effective workout routine, you need to consult with someone who knows what works and what doesn’t. And until recently, that means working with a trainer or other fitness professional.

Neural Networks and Trainers

But by harnessing the power of neural networks and AI, digital personal trainers can fill in for that role, tailoring and overseeing workouts from the comfort of users’ homes. The AI-based personal trainers use various AI algorithms to simulate or even surpass the know-how of a human trainer.

The AI-based personal trainers see a noticeable surge in popularity due to the global COVID-19 pandemic. As people continue to deal with local lockdowns and are reluctant to spend more time away from home than needed, digital personal trainers fill a void when it comes to fitness guidance.

AI-based personal trainer offerings attack the concept in a variety of ways. Still, it’s worth taking a look at a couple in particular as representatives of some of the field’s possibilities.

Apps Leveraging AI Processes

The first we’ll look at is the Freeletics app, which leverages a series of AI processes to create a customized workout and then maintains and modifies it to optimize user preferences and development.

The Freeletics app begins by collecting a small amount of personal data. It then cross-references with a massive database of other users and workouts to create a suggested starting routine.

The app will then track the user’s progress and accept feedback to continue to sculpt their workout to their satisfaction. Whether it be general fitness, targeting individual muscle groups or areas of the body, weight loss, or other fitness goals, Freeletics uses machine learning.

With machine learning, the user gives feedback that will zero in on a routine a user can stick with over the long term.

Other apps use human pose estimation that detects and analyzes human posture during physical activities.

Data Gathered Through Apps

The Zenia app gathers data through the mobile camera, which is angled to capture the user’s workout. Under the hood, Zenia uses a sequence of neural networks and a database of hundreds of thousands of captured yoga poses and images.

The database allows the app to identify correct and incorrect postures, giving feedback on users’ form and progress.

AI  — Personal Coach

Creating AI personal coach apps, developers consult with fitness experts in creating the tools. This ensures that these apps have a foundation rooted in expertise within the fitness world and the power of machine learning.

The fusion of the two allows AI-based personal trainers to offer a compelling alternative to the gym, which an increasing number of fitness seekers prefer.

Smart Clothes and Wearables

An even more intimate application of AI tech in the realm of fitness is smart clothes and wearable devices. These products can monitor exercise or athletic endeavors in real-time through readings of biometric measures.

The motion-capture gathers data and offers feedback and guidance either after the fact or when the user is still engaged in their activity.

Smart Wearables

Asensei is a smart apparel developer offering a suite of shirts and pants capable of tracking users’ movements engaged in body movement exercises like lunges, squats, and similar routines.

The Asensei smart clothes use motion capture and AI technology to compare the user’s angles and range of motion to acceptable norms of exercise form and can correct users in real-time to create good exercise habits.

Sensoria offers a similar AI-based wearable system, this one specially tailored to jogging and running. The Sensoria platform gathers data from smart garments (whether Sensoria’s own or other IoT-enabled garments).

The data measures a range of motions and biometrics. This includes heart rate, rate of foot landing and cadence, and impact forces while running.

The Sensoria analysis not only offers suggestions for optimization and improvements for a workout routine but can monitor and spot potential injuries-in-waiting and identify weak points in the kinetic chain.

The Sensoria system is designed with an eye on both fitness and wellness for users engaged in an active lifestyle.

Wearables for Exercise Tech

Nadi is a smart clothes creator-focused specifically on yoga, using many of the same AI and body capture technologies to produce smart yoga pants.

These leggings connect wirelessly to an app for mobile devices, and the mobile app offers a yoga tutorial working through a predetermined routine.

Meanwhile, the leggings themselves utilize a series of gentle vibrations to offer guidance on which parts of the body should be focused on at each step of the routine.

Real-Time Data

These and other smart clothing and wearable manufacturers are starting to scratch the surface of the power AI has when it can be fed real-time data on granular body movements.

Analyzing and offering instruction at that level of precision allows for a greater level of control of a workout than we’ve ever seen before.

AI-Driven Diet Planning

Long before AI was a viable commercial technology, digital diet planning was a massive part of the fitness market.

Tracking calories and meals online and on mobile devices has been popular for more than a decade. With a profusion of competing apps and websites offering services of highly variable quality.

Limitations of the Users

The recurring problem or limitation of many of these solutions is the amount of work they ask the user to do and the expertise they expect from their users. AI has the potential to fix many of these issues.

AI Helps in the Specifics

One area where AI can help is in the easy identification of foods for meal logging.

Asking users to painstakingly enter each of their meals and snacks is far more time consuming than asking them to snap a simple photo.

And apps like Calorie Mama offer the ability to calculate the calories within a dish or meal through a picture.

If users can log their calories with a minimum effort, motivation to stick with a diet plan increases significantly.

Calories

Meanwhile, apps like FitGenie and Neutrino leverage AI-based analytics to tailor meal plans and caloric targets for individual users’ requirements.

By gathering user info up-front and as time goes on, these apps can tap into huge databases of foods, metabolic and physiognomic ranges.

All of the data measurements can chart fitness goals and create recommendations customized to an exacting standard.

Wellness and Fitness

As time goes on, we realize that wellness and fitness are often an intensely personal journey and that one size very much doesn’t fit all.

AI has the potential to discover what works for any given person, even if that diet or routine is significantly different than what works for anyone else.

The Diet Industry

For decades, the diet planning industry has been stunted by untapped promise, often delivering results to a small subset of people while failing the majority of users.

AI-based solutions may be the key that unlocks a wider-spread success rate.

Artificial Intelligence innovations are transforming nearly every industry, and market in existence to one extent or another, or else will be in the near future. It’s already starting to change the fitness industry and the way people exercise and take care of their bodies.

Conclusion

As we grapple with a world forever changed by the COVID-19 pandemic, the possibilities for major changes in consumer behavior are as great as they’ve ever been.

Whether it be smart apparel, AI personal trainers, or AI-driven diet planners, AI technology is making fast inroads in the fitness industry.

Integrating and expanding on the current offerings is the surest route to becoming a leader in the near future.

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AI ai in business Artifical intelligence business

6 Ways to Improve your Business with Artificial Intelligence

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Artificial Intelligence is the technology that bestowed us with a fairytale-like functionality in our homes and offices. Have you seen the “ Beauty and the Beast� movie? In that movie, the beauty was in the beast’s castle, and there was no other living creature there. She was all alone, except she had a talking and moving clock, a candelabra, a teapot, and a teacup. Here are six ways to improve your business with artificial intelligence.

Science didn’t make the magic happen at the Beast’s Castle — but science has developed something close to it for us.

The wonderful technology that can make our lives easier is known as Artificial Intelligence — and you can talk to it, too.

The simplest example of artificial intelligence is Alexa and Siri. Imagine calling someone when Siri was not there. You have to find their name in the contacts, and then you have to dial them up. Now, you can simply say, “ Hey Siri, call XYZ,� and Siri will call them.

Business AI

Artificial Intelligence for Business

As technology is increasing, the demands of users are also increasing. It is becoming hard for businesses to keep up with those demands. If a business wants to grow, they have to come online. Having a business app or website is that you cannot just launch a website/app and not have online support. You have to track who visits your website/app, and you have to do something to convert that potential client into a real client.

But the thing here is that you or your support guy cannot be online 24*7. If a user comes midnight to shop or have an inquiry and message you, you have to reply within a minute or at most in 5 minutes, or else they will leave your site/app. This is a task that is not possible, but deep down, you know that this is a matter that does need to be solved.

In this case, conversational AI can be used that can trigger a reply once they come across a keyword. If they encounter something unknown, they can simply answer that please provide your email address or phone number, and the team will contact you as soon as possible. At least some reply is better than nothing.

Moreover, if you add enough keywords, the conversational AI can talk like a support person. Dish Network has tested this thing, and in their observation, customers rate interactions with virtual agents the same, and sometimes even better, in comparison to the human support staff.

When a machine does work, it is error-free. Moreover, if you let the machine do the job, you will get more time to do tasks that require human interaction. This way, you will enable yourself to do more important tasks and work productively. As a startup or a small business, this can be the competitive gain that you were looking for.

Let’s have a look at how you can improve your business with Artificial Intelligence.

6 Ways to Improve your Business with Artificial Intelligence

1. Effectively target your market

We have so many marketing ideas, but the main reason why many of them don’t work is that we cannot target the right audience. As a content writer, I was writing a blog about cloud computing, and from that day, Google started showing me ads for cloud computing. I am not a buyer here, but as I searched for the same, Google thinks I am interested in buying the same.

This particularly shows that the wrong person was targeted. It is possible they had an awesome offer, but cloud computing is something which I think I never have to buy. The company paid for that to be shown to the right audience, and that didn’t happen.

AI can release you from the stress of targeting the right audience. It’ll target the right audience for you, and there are minimum possibilities of AI to go wrong. This is the feature that most of us need, as finding the right audience is a great challenge.

2. AI helps shopping

Take the phones of two different persons and go to the Amazon or Flipkart app, and you will see the difference.

Different products would be shown on their main page, and this is how people want to experience online shopping. They offer lakhs of products, and no one wants to see what they are not interested in. This is where AI stores what they like and thus show them the related products.

Now, AI is completely changing how people shop online. One of the reasons that people prefer traditional shopping was that they were able to try the clothes at the shop and they were able to see if it suits them or not. Thanks to Augmented Reality, people can now take the trail online.

People can now take a trail of the clothes that they want to buy, and thus this is making their experience more pleasant.

3. Personalized experience

AI is centralized towards creating an awesome customer experience. This helps companies to earn more as customers are willing to pay more for a better customer experience. A simple example is that we pay more when we go to a salon for a haircut, and we pay less to a local barber, and then we even ask for discounts. The willingness to pay is dependent on the experience.

Therefore you should try to create a pleasant customer experience as you can. According to a report by American Express: “ Customers who have a positive customer experience spend 74% more�.

4. Content generation and curation

This feature is one that threatens my job. AI can even write content that is plagiarism-free and filled with the right keywords, and thus they can rank on the google pages.

AI can create eye-catching content. But it is hard to create content that does not contain any plagiarism as facts and studies will remain the same, and if someone uses these facts in their content, this will lead to plagiarism. This gave birth to automated journalism. In this, robots will write the content.

The best example is Heliograf of Washington Post, which has written various articles on the Olympics and politics and has also won awards in Artificial Intelligence.

5. Image recognition

Product tagging and visual search have started taking digital marketing with an impact. Google first founded this, and it was a wow feature. You just have to start your camera and point it to something, and then you can know what it is.

This means that if someone is looking at your product and don’t know what it is, they can just start their camera, and they can know the name and the price of the product. Thus, if someone likes your product and wants to buy it, they are just a camera search away.

This makes it easy for people to find your product and your business.

6. Voice SEO

Technology has become so advanced that phones can identify human voices and address their command. This is not unknown to people due to Siri and Alexa, but still, people cannot use it to their advantage.

Whenever I scroll through Instagram, I do come across some post with an amazing song or beat, but I don’t know the name of, but I liked the song, and I want to listen to it, but how can I do that?

The simple answer is to use Shazam or ask Siri to identify the song. It is no longer limited to mobiles. You can also use your speaker to do so.

You should understand that voice search is very different from traditional search. SEO for voice search requires a different approach. Here, long-tail keywords can help your SEO.

With the help of AI and good advertisement knowledge, ads can be personalized according to the targeted customer.

Conclusion

Artificial Intelligence can help in business by doing your work in an error-free way. It can help you in cutting down your expenses, and it can perform the work faster. You can use Artificial intelligence as the ultimate weapon that you need for competitive gain.

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6 Futuristic HR Technology Trends Amid COVID-19 Crisis

HR tech trends

Businesses are quickly adapting to the COVID-19 reality where HR technology has made the greatest influence to do so. COVID-19 has accelerated the evaluation, training, and implementation of HR tech trends in businesses of all sizes.

The HR team is actively involved in adopting innovative technologies at all levels like – recruitment process, employee engagement practices, and management processes. An emphasis has been laid on mobile connectivity and visual communication as employees started working remotely. The traditional management approach may not address the new challenges and complexities to keep the employee cycle moving.

Also, HR professionals are turning toward more strategic roles. They are catering to business needs like structuring organizations, strengthening the workforce, and managing talent. So, the repetitive tasks are handled through tech tools paving the way to use their potential to spot trends, decision-making, and becoming the true business partners.

In the survey, we can find how HR projects are delivered on their expected business value as said by employers.

Let’s deep dive into the technical aspects of the HR domain and how best HR leaders are cruising through this storm in the ocean. Here is a quick primer on some of the popular HR tech trends that are developing at an unimaginable speed.

Popular HR Tech Trends Amid COVID-19 Crisis

There is a quick shift in HR functionalities amid the COVID-19 crisis. Here are the HR tech trends that are raising the bar and helping the team to make informed and innovative decisions for the organization.

Artificial Intelligence in HR

AI in HR is on the limelight to lessen the administrative burden on the HR team. Artificial Intelligence can be used for various purposes in HR functionalities like screening, recruiting, online and offline training of employees, managing leaves, detecting anomalies, resolving queries, reviewing performance, absenteeism, exit metrics, and initiating retirements. AI use cases include digital coaching, development planning, recognition, and wellness as per ISG reports, 2019.

In brief, AI can streamline redundant and time-heavy tasks. It can quicken the tasks like surfing hundreds of resumes and cover letters, compiling and analyzing survey data, and many more tasks. Also, it removes human bias or error while evaluating candidates. However, one has to take care that there is no built-in bias while programming the algorithms, as this will continue the issue and may not get noticed upfront.

It is essential to train the systems with the right data and algorithms that are easy and transparent to understand. AI-enabled workplace still requires human skills and that’s where leadership in HR shines.

Robotic Process Automation (RPA) in HR

RPA includes robotic skills like natural language processing (NPL), machine learning, chatbots, and Artificial Intelligence (AI). It helps the HR team to increase productivity as it can speed up communications. Many of the modern HR systems have chatbots that can provide answers to employee inquiries. 50 percent of companies will have HR chatbots by 2022, Chatbot News Daily reports.

RPA has a wide range of applications in HR processes, Deloitte reports. RPA can contribute in many aspects like strategic processes, talent management, operation, and total rewards.

  • The strategic processes include workforce planning management, also, employee satisfaction, organization design, establishment, and implementation of HR policies and programs.
  • Similarly, talent management processes involve recruitment, onboarding, employee development, employee training, performance, competency, global employment, career graph, and succession planning.
  • Likewise, operation management involves data administration, management of payrolls, reports, employee health, employee separation, labor, and employee relations.
  • And, total rewards include salary compensation and other related employee benefits.

As per Deloitte studies, RPA tools are best suitable for processes with repeatable and predictable interactions with improved efficiency and effectiveness of services.

Employee engagement tools in HR

Employers today are concerned with the employees’ financial well-being and health. As a solution, they are providing financial and employee wellness apps like budgeting apps, fitness trackers, wearable apps for health, and more. They are given access to many other apps and platforms for child care too.

Moreover, there are apps provided by healthcare providers that maintain the privacy of health data. Given the pandemic situation and raising remote work culture, there are self-service employee experience portals that facilitate employees to handle HR functions all by themselves. Likewise, remote tools like Zoom and Microsoft Teams are also used in maximum while engaging with employees, interviewing, hiring, and recruitment at the remote. This paves the way for the HR team to focus on people more than processes.

Cloud-computing in HR

Cloud computing streamlines the recruitment process and is capable of transforming the whole HR functions. To mention a few trends are omnichannel models, the Internet of Things, employee wellness, learning culture, agile workforce, and data security.

  • Cloud computing ensures streamlined functions and benefits organizations that have implemented it.
  • IoT acts as the perfect tool through greater connectivity. It can be used to transform data into information at a faster rate. And, storage of this humongous data will not be a hurdle due to the cloud.
  • Cloud communication is much better and fills the missing links in the communication facilitating managers to review, communicate, or provide feedback and all through a single platform.
  • As firms encourage e-learning and online training for employees to upgrade their skills, cloud computing enables employees to meet industrial requirements in a comfort zone.
  • Cloud computing connects the workforce from various geographical locations and profiles easily and gives instant communication facilities.
  • Cloud computing is more reliable for data security as the security measures protect the data to the core.

Augmented Reality and Virtual Reality in HR

Virtual Reality (VR) and Augmented Reality (AR) can be used as a tool in HR toolkit. They help in the recruiting and onboarding process by setting up a simulated environment to test candidates’ specific skills, share a virtual tour of the office, create a personalized work-space environment, improve efficiency, save costs and make engaging recruitment process that helps in branding, training employees in new techniques.

It enables the HR professionals and supervisors to identify key areas of improvement, understand elements of concern for accomplishing goals by scanning people’s faces through sentiment analysis. 49% of Gen Z employees in Singapore believed that VR would revolutionize their work, while 45 % in the US confirmed the same. AR and VR have the potential to elevate a team collaboration levels. Though it is not implemented in an appreciable strength, it is more likely to be the top trend in the near future.

Blockchain in HR

Blockchain technology is poised to manage HR capabilities in different ways. The HR industry is envisioning the use cases of blockchain in their arena vowing to its characteristic features like immutability, transparency, trust, security, and decentralization. A few of the use cases could be –

With its security capabilities, blockchain can handle sensitive employee data like their pay, healthcare, banking, performance records, and expense reimbursement. Blockchain will prevent internal and external hacks of sensitive records as there will be authorized persons only.

It is difficult to determine the employees’ work and education history with the current facilities. With blockchain, the HR team can improve recruiting processes, verify the qualifications of the prospect, and make background checks. All records of the candidate will be present in a block that will get accessed through authorization.

Further, blockchain eliminates time lags in payroll systems even when the company goes global. The blockchain ledger helps to track invoices, facilitate distribution, billing, and reporting of all kinds of transactions. Payroll processing will occur in a timely fashion. It also assists in automating taxes, reimbursement system, mitigate audit risks, and give better access to benefits and packages.

To conclude

HR technology is helping the industries to sustain amid the prolonged lockdown led by the COVID-19 crisis. In addition to these technology implementations, an increased focus toward the people aspect will drive the HR domain toward new work habits and its success.

Image Credit: pexels; pixabay

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The Value of AI-Based Visual Inspection in 2020

ai visual inspection

For over a decade, manufacturers have turned to automated solutions to improve their bottom line. Automation and machine vision are now being augmented and even replaced by AI. Here is the value of AI-based visual inspection in 2020.

Value of AI-Based visual inspection

Being replaced by AI is especially true when it comes to visual inspection. The use of AI-based visual inspection technology is transforming manufacturing’s ability to improve business operations.

AI-based visual inspection relies on two of AI’s main strengths: computer vision and deep learning. Every AI system is built with the core capacity to perceive its environment (computer vision) and act on those perceptions (deep-learning).

As a result of deep-learning, AI adapts to a range of environments, making it useful across a multitude of industries. It has unlimited potential and can be developed rapidly to meet a manufacturer’s needs.

Concept of AI-based visual inspection

Well-trained human eyes can detect defects. A well-trained AI-based vision system can do the same — but with greater efficiency. Like a human eye, AI-based vision systems capture an image and send it to a central “brainâ€� for processing.

Like a human brain, an AI “brain� makes detailed meaning from the image by contrasting it against its existing knowledge.

AI-based vision systems are made of two integrated components. A sensing device acts as an “eye,� while a deep learning algorithm acts as a “brain.� The integrated system successfully mimics the human eye-brain ability to interpret images.

AI-based vision systems are more efficient than human eyes because the AI “brain� stores greater amounts of information.

Robust computational power can parse through available data at rapid speeds. The system can classify objects in both photos and videos and perform complex visual perception tasks.

AI-based vision systems can search images and captions, detect objects, and classify multi-media.

Thanks to deep learning-based visual processing, AI-based visual inspection systems can perceive cosmetic flaws and detect defects across general or conceptual surfaces (mobidev dot biz).

Benefits of AI-based visual inspection

1. Fast Implementation

Decades-old automated systems depend on defect libraries, lists of exceptions and complicated filters. The time it takes to accrue this information, clean it for accuracy, and re-implement it decreases its efficacy. It also wastes labor.

AI and deep learning do not require prolonged programming or tediously lengthy algorithms. AI-based visual inspection systems might be constructed by several quality engineers and a dataset of training images. The system learns rapidly and is integrated over several weeks.

2. Improved Analytics and Quality Control

Manufacturers can use AI to document inspection results and to assess product quality. Some overall process improvement initiative metrics that can be successfully tracked and correlated with concrete vision data include:

  • process recipes
  • equipment differences
  • component suppliers
  • factory location

In addition, inspection images and results can also be tracked and documented. These initiatives prevent future failure, which saves time and additional production costs. Applying deep learning-based machine vision across all initiatives and inspections helps manufacturers recognize and address defects early.

3. Labor Costs Reduction

AI solutions have higher rates of consistency than most expert human inspectors. Human inspectors must be trained and are only able to maintain a high degree of focus for 15-20 minutes at a time. Labor costs are incurred yearly and staff turn-over is an issue. For these reasons, AI-based vision inspections are more cost-effective than manual labor.

Use Cases

AI is increasing the competitiveness of manufacturers across every industry. Here are recent use cases from the aviation industry, semi-conductor manufacturing sector, and bio-science.

Alibaba has risen to meet healthcare challenges created by the coronavirus. Alibaba’s deep-learning-based visual recognition system is capable of detecting the coronavirus in chest CT scans at a 96% accuracy rate. The system accessed 5,000 COVID-19 cases and can provide a diagnosis within 20 seconds. Moreover, the system can differentiate between images of viral pneumonia and images of coronavirus.

Fujitsu Laboratories implemented an Image Recognition System at Fujitsu’s Oyama factory. The system ensures that parts are produced at optimal quality levels by supervising the assembly process. The system was so successful that Fujitsu implemented it across the entirety of the company’s production sites.

Airbus introduced an automated, drone-based aircraft inspection system in 2018. The system has improved the quality of inspections and reduced aircraft downtime.

GlobalFoundries is a leader in semiconductor manufacturing. The company designed a visual inspection system that detects defects in a scanning electron microscope (SEM) images. The system detects defects in a wafer map which then helps to determine the semiconductor device’s performance.

The use cases listed above reveal the extent to which AI is capable of automating many aspects of our lives. Although AI vision will never replicate human vision, the technology continues to classify information and advance in ways human eyes and brains cannot. And only humans might consider how to use this technology to get advantages.

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How Will Artificial Intelligence Change the World of Sports?

Today, the technological landscape is expanding by all leaps and bounds, and Artificial Intelligence (AI) remains in the thick of it. A technology that is one for the present and future, AI is playing a massive role in shaping businesses to the core. From healthcare and entertainment to commerce and sports, Artificial Intelligence is transforming every industrial vertical for good. Here is how artificial intelligence will change the world of sports.

Sports and Artificial Intelligence

Speaking of the sports industry itself, the presence of AI today is to be seen in just about every major league around the world. From NHL and NFL to NASCAR and NBA, AI has changed the way we think of the sports world today. Take an example of Northern Sports only, for instance. The industry crossed a staggering figure of $73.5 billion by the end of the year 2019.

Okay — so, COVID-19 has caused a dent in the sports system — and a problem for sports. But we’ll get back on track! And, if you long to know more about how AI has impacted the sports world, here is a compiled, detailed list.

It’s fun and interesting to understand how Artificial Intelligence will shape or change the world sporting ecosystem around the world.

Ways AI will Change the Sports World

AI is changing the Sports world for good.

1. Enhancements in Recruitment Analysis

Be it soccer, basketball, baseball, or any other game, analyzing the performance data of players has been an age-long factor in determining whether a particular player will be successful at the club or not. Not only is the performance data analyzed for the recruitment of the players but also to determine the impact of a player mid-season.

Now while these performance data aren’t as accurate and contain numerous loopholes, the integration of AI into this process is making it more reliable and easy. AI can now analyze all the historical data about a particular player in order to come with a conclusion about whether or not a player would have an impact on the club. This even helps in determining what should be the market value of the player in the transfer window.

2. Use of Deep Learning by AI in NASCAR

Nascar is one of the famed sports around the world watched by millions of people in the US alone. However, there’s a dark side to this sport. Since the year 1950, NASCAR has recorded an average of more than one death annually. So in order to counter this problem, AI has a vital role to play.

With the help of deep learning, Artificial Intelligence is making use of the neural network that can identify a malfunction or kind of issue in the car much before the driver is at risk. Car AI is a technology that has been trained on a dataset to identify more than a thousand images of cars in multiple conditions and can be a boon in the world of NASCAR by making sure that the drivers are safe.

3. The Rise of Automated Journalism

Automated Journalism in the world of sports is now becoming a reality. Thanks to AI, an associated press like Minor League Baseball (MiLB) is now expanding its reach in journalism.

With the help of a platform called Wordsmith that uses statistics and data to come with narratives using the natural language, the press is now able to cover 13 leagues and more than 140 teams affiliated with MLB.

The “sporty” platform has brought a significant rise in the number of stories that the press is now able to cover. As per a report, this rise is a nearly 12-fold increase as compared to the press’ manual ways of reporting. Today, MiLB has covered more than 1500 such stories with the help of Wordsmith and AI. If you are a sports fan, like we all are — try it out.

4. The Role of AI in Coaching

Not only is AI transforming the way we play and cover sports, but it is also transforming the way the players are trained to play on the pitch. Coaches have now begun the use of AI in analyzing the areas where a particular player or the whole team lags behind.

With the help of Artificial Intelligence, coaches around the world can now analyze their own weaknesses as well. This has brought a drastic change in the way we think of traditional coaching methods. Today, there are minimal chances of any issues regarding the playing style of a team being overlooked by a coach.

5. Optimization of Fan’s Experience

Keeping the fans happy is one of the vital things for a league or club to do, and with the help of AI now, the experience of fans is bound to get better. Various teams from different leagues around the world have begun the use of AI-based chatbots to answer the queries of fans.

Similarly, Artificial Intelligence is being integrated to build algorithms that can customize the match highlights in different forms and lengths as per user preferences.

Summing Up

The world of sports offers ample opportunities for technology to expand its horizon. From deep learning systems ensuring the safety of players to a sports app development company (called appinventive dot com) creating apps that optimize fans’ experience. There is a lot to look forward to from Artificial Intelligence in the sports world.

If you like this article and wish to share your views on the increasing role of Artificial Intelligence in sports feel free to share your views in the comments section below.

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