Tag Archives: AI

Technology

How AI Can Help In Building SEO-Friendly eCommerce Website?

If you haven’t been living under a rock for several years, you’ve probably heard of artificial intelligence (AI). However, how can artificial intelligence be applied to e-commerce? 

According to Statista, 1.92 billion people across the globe will engage in ecommerce activities in 2020. By 2023, the number is likely to surpass 3 billion. Because of the increased demand for online products, businesses have had to get more innovative in how they reach out to their target customers. AI is already being used by e-commerce website development companies to better understand their customers, generate new income, and improve the customer experience for existing customers. Companies have had to pull out all the stops to grab online audiences, from dynamic email messages to voice and visual searches. The strength of AI and automation has enabled many of these tools.

Many marketers now use AI to help them improve their ecommerce marketing efforts. Here are a few ways artificial intelligence has influenced ecommerce. When it comes to purchasing, many people choose to do online shopping.

What Impact Will AI Have on E-Commerce?

Because of the current status of the Internet, e-commerce has become more crowded and competitive. To get success business must be faster and savvier than its competition. For example, take the task of custom eCommerce development of a website. All type of data on customers and site visitors is all around us and is constantly collected. What if we could better gather, organize, analyze, and use this data? Artificial intelligence (AI) plays a role and transforms Internet marketing services. So, let’s look at how artificial intelligence can assist you in establishing more effective e-commerce SEO methods.

  • Artificial Intelligence Can Help Reduce Cart Abandonment

The average open rate for abandoned cart follow-up emails is 45 percent. In fact, this figure is linked to email marketing automation. An abandoned cart is one of the most obvious signals that a consumer had a technical issue or had a bad experience prior to making a purchase. They were only a few clicks away from making a purchase, and becoming a customer. To reduce cart abandonment, an eCommerce website development company has started adding the feature of AI in the online store. A triggered email that includes a survey is a persuasive approach to bring consumers back while also collecting information that can help you further prevent cart abandonment.

Therefore, most store owners use AI and Machine learning to target the customers and see the level of interest they show in the products. So, with these tools, they check the online behavior of the targeted customers.

  • Artificial intelligence has aided the rise of voice search

According to a recent study, voice searches will account for 50% of all web searches by 2023. Customers can now search for things using their voices thanks to gadgets like Alexa, Echo, Apple smartphones with Siri, and Google Home. As a result, businesses must ensure that their products can be found using voice search. Companies must start optimizing their websites for voice search. Now, businesses leverage machine learning by allowing clients to shop using Alexa. Customers want more convenience in their online buying experience.

Many customers use images to shop online. So, when a store owner creates a customer Commerce development, they should add the functionality of Visual search along with voice search. In fact, some businesses have developed apps through which users can take pictures of items and search in the marketplace. Also, Google has provided this feature to their users. It is all because of AL and ML. To add the feature of visual and voice search to the online store, businesses refine their marketing strategies.

  • AI Allows to Target Specific Customers

When it comes to appealing to ideal buyers, AI removes the guesswork. Companies may now develop ads that target specific buyers based on their online behavior rather than creating a one-size-fits-all campaign.

Marketing automation and artificial intelligence (AI) tools make it easy to collect buyer data, generate dynamic advertising that uses that data, and broadcast relevant ads and content to platforms where potential buyers like to view it.

With the help of AI tools, marketers can create more effective retargeting strategies. Businesses may now easily retarget adverts in areas where customers go online thanks to social media sites like Facebook. No doubt, Artificial Intelligence is becoming strong to read the intent and behavior of the customer.

  • Improve Search Results

We know that a professional marketer can create an engaging and effective web copy to promote the products. However, if the client can not discover. It would be of no help to meet the target. Moreover, customers use search engines and marketplace searches to find reliable products. Do you know that over 40% of the eCommerce traffic comes through organic Google searches? So, SEO is most important for an eCommerce store to achieve success. 

With the use of SEO-based AI, you can do Site performance analysis. Also, it helps in performing the keyword research. In fact, it will improve the content and recommend appropriate tags. So, if your website is user-friendly with relevant keywords, meta descriptions, and tags will help you reach your target audience.

Conclusion

We hope our blog helps you understand how AI is crucial for an eCommerce business. E-commerce companies can use AI to assess millions of interactions per day and personalize offers for each customer. So, to provide a kind experience to your customer, get custom eCommerce development to add the features of the AI and ML in the online store.

Machine Learning

5 Top AI and Machine Learning Trends for 2022

Artificial intelligence and machine learning are two of the most talked-about technologies in recent years. They are changing the way we live and work and will continue to do so in the future. These technologies will only become more prevalent in the future. They have the potential to change our lifestyle and many businesses are already taking advantage of them.

AI is a process of programming machines to make decisions for themselves, while ML is a method of teaching computers to learn on their own by analyzing data. Both fields have been around for many years, but they are only now becoming more popular due to recent advances in technology. These technologies are making changes in industries across the board, and businesses that don’t adopt them will be left behind.

The future of AI and machine learning is looking bright. These technologies are making an impact in a variety of industries, from healthcare to finance to manufacturing. These technologies are making it possible for machines to learn on their own, and to make decisions based on data. In this blog, you will read about the top Artificial Intelligence and Machine learning trends in 2022.

Artificial Intelligence and Machine Learning Trends for 2022

There are a number of trends that we can expect to see as AI and ML continue to develop in 2022. Here we will take a look at some of the trends that we can expect to see in the future when it comes to AI and ML:

  1. Improved Cybersecurity

As we move into 2022, it is clear that artificial intelligence (AI) and machine learning (ML) will be having a major impact on cybersecurity. Both of these technologies have already begun to play a role in improving security, and their influence is only going to grow in the coming years. These new technologies have the potential to improve security in a number of ways, including by increasing the speed at which threats can be detected and stopped. Cybercriminals are beginning to leverage AI and machine learning themselves in order to launch more sophisticated and difficult-to-detect attacks, so it is essential that businesses have security measures in place that can counter these threats.

AI in cybersecurity can help automate the process of identifying and stopping cyberattacks before they cause serious damage. With the help of AI in cybersecurity, these threats can be mitigated and businesses can continue to enjoy the benefits of these transformative technologies safely and securely. Today, it is more important than ever for businesses to invest in AI-enabled cybersecurity solutions. These threats can be mitigated with the help of AI in cybersecurity solutions, but only if businesses are aware of these dangers and take appropriate precautions.

  1. AI in Metaverse

 Metaverse, a distributed ledger platform and virtual world are known for their innovative applications of blockchain technology. In recent years, AI has been making waves in the Metaverse community. Metaverse is a digital world that enables people to create their own avatars and interact with others online. In 2022, AI will play a huge role in Metaverse, and here are four ways it will change the game:

  • Avatars will be more realistic and lifelike
  • Virtual reality will become even more immersive
  • There will be more opportunities for businesses to use AI in Metaverse for marketing and customer service purposes
  • The overall experience of being in Metaverse will be greatly improved by AI
  • Bots will become more common and smarter, automating many tasks for users
  • Avatars will be able to create a more personalized experience for each user
  • AI-powered marketing and sales bots will help businesses boost their revenue significantly

  In Metaverse, users can create their own avatars, interact with other users, and explore different virtual environments. The development of quantum computers will enable new possibilities for AI in Metaverse, such as real-time translation and realistic rendering of objects. However, we should still wait to know more about the future of work and society in the metaverse.

  1. AI and ML with the Internet of Things (IoT)

The Internet of Things (IoT) is growing rapidly, and by 2022 it is expected to include more than 30 billion devices. With this many devices connected to the internet, it’s no wonder that AI and ML are becoming more important. These technologies will be necessary to manage and process all of the data that will be streaming in from all of those devices.

The internet of things (IoT) is a network of physical objects, vehicles, buildings and other items—embedded with electronics, software, sensors, and network connectivity that enables these objects to collect and exchange data. In 2022, AI and ML will be used with the IoT to create more efficient systems. For example, hospitals will be able to use AI and ML to predict patient needs and better manage resources. Traffic lights will be able to adjust their timing based on the current traffic conditions in order to optimize traffic flow. Buildings will be able to adjust heating/cooling based on occupancy levels and time of day. There will be many more applications of AI and ML in the future. If you know how to master Machine Learning, you can easily be a part of several innovations in the future.

  1. Use of AI for Environmental Threats

 AI and its potential applications for environmental threats were outlined as one of the top trends to look out for in 2022. The report, compiled by analysts, cited concerns over air pollution, water scarcity, and climate change among the major factors that will drive the growth of AI-based solutions in the next few years. As the world becomes increasingly digitized, more and more data is being generated about our environment. This data can be used to create models that predict environmental changes and help us respond to these changes before they become a problem.

With global temperatures on the rise and more natural disasters occurring each year, businesses and governments are starting to realize just how important it is to have systems in place that can help predict and prevent these threats. AI and its potential applications for environmental threats can be used to monitor air quality and track emissions. It can also be used to identify areas that are at risk for pollution and develop strategies to prevent it.

  1. Hyper automation in Healthcare

The use of AI for hyper-automation in healthcare is on the rise. What is hyper-automation in healthcare? It is the application of artificial intelligence and machine learning technologies to automate complex tasks and processes in the medical field. This can include anything from diagnostics to treatment plans. Many experts believe that hyper-automation will play a major role in the future of healthcare.

Many experts believe that hyper-automation will play a key role in reducing costs and improving patient outcomes. Simply put, hyper-automation is the application of AI and automation technologies to healthcare where they can drive significant improvements in efficiency and quality.

To Conclude

The world of AI and machine learning is constantly evolving. Every day, new technologies are emerging that are changing the way businesses operate. As we move into 2022, there are a few trends that we can expect to see more of.  Let’s wait and see what AI and ML have more to bring in 2022!

Author Bio:

Shahista Tabassum is a senior IT Technical Trainer at Time Training Center.  She has extensive work experience of 11 years working in various roles as a software developer, It Consultant and Technical Trainer. She spends her free time learning new things that will enhance productivity and in volunteering activities that help kids to learn new things.

 

Artificial Intelligence

AI in Web Development: Everything You Need to Know

Artificial Intelligence (AI) has become one of the most advantageous fields in the past few years. Regardless of the disturbance 2020 has caused, the opportunities provided by AI show no sign of losing their pace. AI and web development projects are no longer science fiction and are already approved by public and private organizations all around the globe.

People are a long way away from the imaginary thought that AI robots are coming for humans. But the truth is that humans rely a lot on artificial intelligence with its growth as a society. Organizations are using best free AI website builder to build stunning website in less time and price. AI is one step closer towards developing and investing more technological discoveries by implementing the logic and intelligence of humans. The algorithms of artificial intelligence and deep machine learning mechanisms are looking out for ways to make routine activities comfortable.

The advancements and innovation in technology have brought complex but sophisticated new sources called sci-fi technology into reality. Artificial intelligence in web applications has entered every field like healthcare, blockchain, banking, education, and many more. The great way artificial intelligence is providing its activity in the past few years is through web development. For further guidance, you can contact a top CMS development company to be of great help.

What Is Artificial Intelligence?

You must have heard so much about AI and web development projects that now you have been excited to know what AI is and how to implement AI in websites?

Artificial Intelligence in web development is simply an act of programming computers and devices made to decide and carry out actions that humans do. Operations like planning, learning, solving issues, voice recognition, and many more. In simple words, AI can have a machine and a computer to learn and think, a field of integrated knowledge to make computers intelligent.

Voice search, smartphones, autopilot, home cleaning robots, all of these activities are AI. All of them have the efficiency of any action being facilitated a hundred times. Software development services include various steps where the data is transferred to a machine that would be more productive, and that is made possible because of AI.

Role of Artificial Intelligence in Web Development

When we talk about AI and web development projects, the platform provides uses with lots of advantages. The AI development companies learn to embrace innovative technologies that influence all the solutions. These solutions involve integration testing and security issues. The tools that AI is inclined to use are nothing but a bunch of jargon for developers. Thus, if you are thinking of using Artificial intelligence in web development from scratch, reach many organizations.

Thus, big tech giants like Google and Facebook have introduced AI tool kits that provide ready-made plugins if you want to adopt AI web development. These machine learning and natural learning process are to be attributed in web applications. It has made it possible for small-scale businesses to incorporate AI in web applications. Nowadays, developers do not require any codes in AI language to get benefitted from the technology. Rather they word with tools and API that they are already known with. These are some of the ways where the role of Artificial in web development has benefitted the developers:

  • It helps to search faster.
  • It provides a relevant, enhanced user experience and interaction.
  • It also offers productive digital marketing activities to target new customers.
  • It permits the system to modify over time and then adapt to the user habits and change the general mistakes.
  • The role of AI web development has helped web store owners with a personalized experience.

Artificial Intelligence in Web Development

Nowadays, possessing a website is compulsory for all the business fields in the market. Hence, artificial intelligence plays a crucial role in reshaping web design and development. As per the Statista report, the revenue generation from Artificial Intelligence is expected to reach $126 billion by 2025. From healthcare, manufacturing, hotels to every digital service, artificial intelligence has its stakes everywhere in the market. It is because the various web and mobile app development companies have started building AI-enabled sites.

Conclusion

Undoubtedly, AI is transforming with each passing year. And if we look into the positive aspects of using Artificial intelligence in web development, it is pretty apparent that it would bring the best from the tools used. This is why CMS development companies are using the power of AI to develop intelligent web applications.

In the coming future, it is believed that AI will control all the innovations shortly. By enhancing the user experience and allowing the users to build web applications at a faster pace. Thus before you hire your AI developers, you need to ensure that the development requires authentic and consumer concentric.

We hope that this article would have provided you with a piece of brief information and data related to AI and web development projects.

Artificial Intelligence

Difference between RPA and AI

The Robotic Process Automation (RPA) and Artificial Intelligence (AI) has recently shown great interest in being able to significantly reduce labor costs while increasing efficiency, improving the user experience and improving customers. .

According to leading analysts, the global APR market is expected to reach $ 25.56 billion. The artificial market is estimated at $25.56 billion by 2027 and is expected to reach $ 390.9 billion by 2025.

For starters, RPA and AI are two different but complementary technologies. On the other hand, while RPA is used to automate repetitive rule-based tasks, AI improves automation and helps automate decision-based tasks. When these technologies are used together, companies can expand their automation to attract more people to their larger digital innovation goals.

We will take a closer look at what RPA and AI offer, how they differ, and when complementary technologies for end-to-end automation can be used together.

What is RPA?

Robotic process automation (RPA) is a product tool that allows users to modify one or more scripts to automatically generate specific keys. As a result, bots can be used to track or mimic selected tasks in an integrated business or IT system.

RPA works best when using policy-based cycles where work processes don’t change over time or require a lot of personal communication to resolve differences. At the same time, the RPA Course is becoming important to equip employees with the knowledge, practices and tools necessary for the implementation and operation of RPA-powered systems. Among other things, RPA can understand the common and tedious steps that will strengthen your business.

Examples:

  • Log in to the application
  • Logging into the system APIs.
  • Copy and paste information.
  • Reordering information
  • Scratching information from the web
  • Open emails and attachments
  • Cleanup/formatting of Excel worksheets.
  • Navigate various applications/systems for transcribing data.
  • Data extraction using structured documents.
  • Perform predefined tasks as required.

What is AI?

Artificial Intelligence (AI) demonstrates the reenactment of human understanding in machines that are designed to think like humans and records their work. This term can be applied to any machine of a spiritual nature, such as learning and solving problems.

RPA users use very disruptive AI technology. RPA and AI work online to create more facilities and systems. Simply put, AI is a simulation of the human mind through computer systems. These experiences include study, meditation and self-improvement. AI uses data to transform it into a method of the human mind. Some of the most common applications of AI include auto-display, voice recognition, voice recognition, image analysis, and more.

Because almost all organizations have structured and unstructured data, many systems need to work together on RPA and AI to find extreme solutions. AI is designed to solve complex processes that was previously done by only humans.. Today, these AI-enabled robots can make decisions and predict multiple outcomes with large amounts of data. Unlike RPA, AI cannot act alone.

For instance, an AI-enabled bot can:

  • Understand conversations and documents
  • Visualize screens
  • Discover tasks and processes to automate
  • Process language
  • Handle semi-structured or unstructured data

Difference between RPA vs AI?

Artificial intelligence can automate the functions, whereas RPA’s reduce human activity. No doubt these two solutions work well together. The integration of artificial intelligence and RPA functions creates a complete and independent process

For example, if we need special accounts for the system, the accounts are scanned with RPA and added to the computer software. Artificial intelligence is used as an appropriate hierarchy to automatically sort non-productive accounts and uses the procedures implemented by the RPA program. This RPA-AI combination concept is referred to as the Automation Continuum.

RPAAI
RPA is a software robot that may be reflective of human activities.Simulated artificial intelligence is the re-enactment of human knowledge in personalized machines to think like people and copy their activities.
The main point of the RPA is to use robotics on tedious and ordinary commercial measures.2. AI is based on intelligence, which depends on ‘reflection’ and ‘learning’.
RPA robots automate the assignments according to specified rules. 3. Artificial intelligence is the replacement of human work.
The RPP is not a difficult task. Now and again, an RPA can be perplexed with huge organisations of programmers exchanging data between them, but it will actually be an easier suggestion than AI.4. Artificial intelligence replaces human work. In many organisations, robots or machines operate rather than human specialists.
The RPA is supposed to be a cycle-based innovation because the RPA is related to monotonous mechanization and rules-based trade measurement.5. AI requires a ton of work to get in place and run.
RPA is a standard innovation with no insight at all.  It simply mechanizes redundant assignments. 6. Artificial intelligence integrates innovations like ML (Machine Learning) and NLP (Natural Language Processing), which help do more than make rules-based engines to mechanize redundant tasks..
RPA can have a huge impact on huge organisations as they can manage huge measures of information precisely without the need for a manual contribution.7. AI supports the dynamic. It reinforces the process without human inclusion.

Conclusion:

Indeed, AI is a generic term for many different technologies, one of which is robotic process automation. AI makes the RPA stronger and more productive. RPA is like your digital workforce – you show bots what to do and they’ll do all the work. They may interact with any system or application in the same way as humans.They learn from humans and have a goal, to carry out the tasks which humans assign and control. The idea is to program robots performing banal and repetitive tasks that are a real waste of human effort and time. The idea behind AI is to get computers to copy humans into some or every aspect of their behaviour.

Author Bio:

Sowjanya Kodiganti  has been working with various Technologies  for over two years. She is currently working as a Content Writer for Mindmajix. She wrote articles on the trending IT-related topics, including Angular JS,Power Automate, Artificial Intelligence, Data Science, BluePrism, Python, Cloud computing, etc. You can reach me on LinkedIn.

Artificial Intelligence

Github Now Uses AI to Address Open Issues

Large open source projects on Github have lists of daunting issues that need to be addressed. To make it easier to locate the most urgent, GitHub recently introduced the “good first problems” feature, which associates contributors with problems likely to meet their interests.

The initial version, launched in May 2019, produced recommendations based on labels applied to problems by project managers. But an updated version delivered last month incorporates an artificial intelligence algorithm which, according to Github, surfaces for around 70% of the benchmarks recommended to users.

Github notes that this is the first deep learning compatible product to be launched on Github.com.

According to Tiferet Gazit, senior machine learning engineer at Github, last year Github performed analysis and manual curation to create a list of 300 label names used by popular open source repositories. (All of them were synonymous with “good first issue” or “documentation,” such as “friendly for beginners,” “easy bug fixes,” and “weak hanging fruit.”) But based on these, only 40 About% of the recommended benchmarks had problems that could be resolved. In addition, it left the burden of sorting and labeling issues with the project managers themselves.

The new AI recommendation system is largely automatic, however. But to build it, it was necessary to create a training set annotated with hundreds of thousands of samples.

Github started with problems that had one of some 300 labels on the organized list, which he supplemented with a few sets of problems that were also likely to be suitable for beginners. (This included those that were closed by a user who had never contributed to the repository, as well as closed problems that affected only a few lines of code in a single file.) After detecting and removing near-duplication problems , multiple trainings, Validation and test sets were separated between repositories to prevent data leakage from similar content, and Github trained the AI ​​system using only the pretreated and noised problem titles and bodies to make sure it detects the right issues as soon as they are opened.

In production, each problem for which the AI ​​algorithm predicts a probability higher than the required threshold is subject to recommendation, with a confidence score equal to its predicted probability. Open issues from unarchived public repositories that have at least one of the labels in the organized label list receive a confidence score based on the relevance of their labels, with synonyms for “good first broadcast” giving higher confidence than synonyms for “documentation. At the repository level, all the problems detected are classified mainly according to their confidence score (although label-based detections generally have higher confidence than ML-based detections), as well as penalty on the age of the problem.

According to Gazit, the data acquisition, training and inference pipelines operate daily, according to planned workflows to ensure that the results remain “fresh” and “relevant”. In the future, Github intends to add better signals to its benchmark recommendations and a mechanism for maintainers. and triagers to approve or delete recommendations based on AI in their repositories. And he plans to extend the problem recommendations to offer personalized suggestions on the next problems to solve to anyone who has already contributed to a project.