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Designs & Invention Disruption IoT (Internet of Things) Web Development & Design Ideas

AI and UX: A Match Made in Heaven or Hell?

AI and UX are two key trends that are redefining the digital world.

Although they are used for different purposes, the aim of both entities is the same—to enhance user experience. Both are driven by predictive analytics.

Whereas UX enhances the user experience of a virtual product, such as web design, AI can execute tasks mainly associated with human intelligence, like decision making, visual perception, translating languages and speech recognition.

Both are important disciplines to enhance user experience and make technology more human.AI and UX_ A Match Made in Heaven or Hell_

What if AI is used in UX? The outcome will be amazing. Isn’t it?

For example, Netflix uses certain algorithms to create graphics, such as click-through thumbnails or movie posters for multi-devices. The online streaming giant has used thousands of video frames from an existing movie or show as a starting point for thumbnail creation. It annotates and ranks these images according to their highest likelihood of resulting in your click.

For example, people are more likely to click on a thumbnail with specific visual elements or characteristics of that genre or an image of their favorite actor.

Netflix might show you the flick Stranger Things in various thumbnails, from a huge gothic font, close up of individual actors, and mysterious scenes.

All these metrics are based on what other similar users have clicked on. It makes a recommendation of TV shows and movies based on the user’s history of watching.

One of the easiest ways to deploy an AI on your webpage design is a chatbot. It answers simple questions, arranges schedules and book meetings.

However, the combination of AI and UX hasn’t become that mainstream norm yet.

Because of the different industries these two things have, it’s usual to see UX designers and AI experts work in their separate zone even though they are working for enhancing user experience. After all, experts from both fields are not acquainted with each other tools and methods, making them unable to learn what can be achieved by combining AI with UX.

How Can AI Improve UX Design?

  • AI can track user experience with web design. For example, it can process info about site visitors, then applies or shows changes to the model to optimize it for future use.
  • Machine learning is useful to analyze various UX factors, such as device users, location of users, session time, session length, pages visited, bounce rates and exit pages. This way, these key metrics give a clear picture of user behavior with your design.
  • AI can also eliminate bias in testing or any subjective approaches to A/B testing. And it’s important to report impartial views on split testing. AI can play an important role here as it is based on cold hard data.
  • AI systems can also test multiple design variations and then produce alternatives. This can be useful in many stages of UX design, such as developing buttons on a webpage, or images in a mobile app.

How to Combine AI with UX

The vision of the product, concerns, and goals are required to be shared and understood by both teams. Therefore, a common language is required so that they can share their concepts.

UX designers and AI experts should team up to develop a common product blueprint that covers both interfaces and data pipelines. This co-created blueprint will be the foundation of product planning and decisions. Both experts have to work in the same space side-by-side.

Secondly, there is a need to focus on the user experience and business goal you are looking to achieve. For example, if you are developing a news app, the user experience designers and machine learning experts should together create and design the actual use flow of the app. This lets the whole team identify the key points where AI could improve user experience and vice versa. Solid designs, including suggestions from data engineers, data scientists, and designers can help set realistic expectations and goals for the iteration of the product.

The next step is to combine qualitative and quantitative data. To determine the effects of the partnership of UX design and machine learning, both qualitative and quantitative data are essential. Qualitative research can include questionnaires, user testing, and user interviews to determine the user experience with your product. Qualitative data helps determine how users think and feel and quantitative data shows how people behave with the product.

Bottom Line:

AI is the right partner for UX as it enhances the basic norm of the latter—to improve user experience. It is all about making the design simpler, easier and convenient.

Again, AI and UX are two worlds apart with different methodologies, environments, skill sets and tools. So, as I have told you earlier, common language, co-created blueprint and data is required to make the perfect combination of AI and UX.

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CyberSecurity

What Is AI Bias and How It Can Ruin Your Cybersecurity Efforts

Artificial intelligence helps in automating businesses. But unexpected AI bias can cause severe cybersecurity threats. This post explains how.

Ever since its inception, complex AI has been applied to a wide array of products, services, and business software. However, the algorithms that support these technologies are at a huge risk of bias. In fact, unexpected AI bias is one of the biggest issues faced by firms looking to deploy AI systems pan operations. That’s because bias can lead to costly business mistakes and undermine a brand’s reputation.

What’s more? AI is being increasingly deployed by businesses as a powerful tool to detect, predict, and respond to cybersecurity threats and data security breaches in real-time. In a survey report by Capgemini, 61 percent of businesses acknowledge that they will not be able to identify critical threats without AI. Naturally, biases in AI security models can create serious security issues for a firm.

Therefore, it’s critical to understand what AI bias is all about and how it can adversely affect your firm’s cybersecurity.

What Is AI Bias and How It Can Ruin Your Cybersecurity Efforts
Artificial intelligence or man-made intelligence’s main focus is to help in automating business processes. However, unforeseen circumstances may give rise to AI bias that could lead to a fatal loss of business valuables.

What is AI Bias?

Machine learning and deep learning models seem to be dissociated from human intervention; yet, let’s not forget that they are created by humans who are biased. Everyone has biases – conscious or unconscious prejudices that influence decisions. Therefore, these models and algorithms are prone to biases by their creators. Algorithms then learn from these biases and they quickly become the basis for unfair datasets and decisions. Hence, AI models, regardless of where they are applied, shouldn’t be biased.

Depending on where the algorithm is applied, these biases can affect various business operations. For instance, in a financial institution, AI bias can corrupt the ability of a system to conduct credit card fraud prediction. Further, it can negatively affect the way businesses manage their funds.

Source of AI Bias

Humans, of course! All algorithms and models are created by humans. Therefore, they reflect the biases of all those involved in creating these ML models, such as the designers, the data scientists, and others involved. AI models learn to make decisions based on the training data that comes with biased human decisions or portray historical or social discrimination related to gender, race, or sexual orientation.

For instance, Amazon’s hiring algorithm was selecting favored applicants based on words like ‘executed’ or ‘captured,’ words commonly used by men in their resumes. The eCommerce giant finally stopped using this AI recruiting tool to uphold diversity and fairness.

Though training data carries most of the blame for AI bias, the reality is more nuanced. Bias can creep in at any stage of the deep learning process, namely problem identification, data collection, and data preparation. Hence, fixing a bias in an AI-based algorithmic system is not easy.

Now, let’s see;

How AI bias can affect a firm’s cybersecurity efforts

Training data - How AI bias can affect a firm’s cybersecurity efforts
If you are still not sure whether AI bias could negatively impact your organization’s security setup, here are factors that will make you rethink your AI security models.

Faulty Security Assumptions Can Threaten Your Firm’s Security

In the case of firms deploying AI for security, faulty security assumptions are often a result of unconscious biases in the model. Such biases can cause the system to qualify malicious internet traffic and miss out threats that can enter the firm’s network and wreak havoc.

For instance, a web developer may be biased towards an ally nation and allow all the network traffic from that country, considering it to be safe. Such biases can cause the algorithm to overlook a fraud element, a vulnerability, or a breach that may stem from that nation. This can pose a threat to the firm’s security.

Biased Training Data Can Lead to Dodgy Security Outcomes

A deep learning algorithm’s decision-making ability is only as effective and neutral as its training data. Training data is considered to be neutral until human prejudice is detected when it reaches the algorithm. Biased training data and flawed data sampling produce distorted results, causing businesses to make corrupt security decisions and outcomes.

For instance, if a spam classifier isn’t trained well enough on a representative set of benign emails, it is bound to produce corrupt results. So, if it is hit by emails with slang or other linguistic idiosyncrasies, it will produce false positives.

Tunnel Vision in AI Models Can Pose Serious Security Risk

The nature of cyberattacks varies across geographies and industries. If your firm’s AI model for cybersecurity isn’t trained to detect issues outside a particular setting, it will be unable to identify such threat patterns, your organization’s security can be easily compromised.

Since humans from a particular geography or industry domain train algorithms, these AI models often suffer from tunnel vision. In other words, they lead to bad AI security models that lack a 360-degree understanding of the cybersecurity landscape, the firm’s security posture, and the emerging threat patterns. Such models can be easily exploited by cybercriminals.

Hence, when training a security model, a firm should involve professionals from diverse backgrounds, geographies, and industry segments. This allows them to feed a variety of behavioral patterns and scenarios of security threats into the model and fill in the gaps in the threat detection process.

Over to You!

AI is being used by a majority of businesses to supercharge their cybersecurity. However, biases in ML or DL models can dampen these efforts and put your firm’s security at risk.

AI bias is entirely our responsibility. Biases can creep in at any stage of a machine learning process and negatively impact business operations, impact critical decisions, and encourage mistrust and discrimination. However, having a biased algorithm in the cybersecurity arena can cause serious issues.

Therefore, we should do everything within our capacity to tackle bias in AI security models. Here are a few tips to get you started.

  • Set up processes to prevent the creation of biased algorithms. For instance, you can have the code reviewed by a third-party security expert. You can also hire an external developer to create a bias-detection algorithm like AI Fairness 360.
  • Hire a diverse team of security professionals and developers to check for biases in the model.
  • Make sure the training data is untouched and uncategorized. Also, if you are using third-party training data, check to see if the insights and patterns included are relevant to your business.
  • The organization collecting and preparing the data should have a strong security posture and a comprehensive understanding of the threat landscape in your business niche.

AI, if used effectively can revolutionize a firm’s cybersecurity for the better. However, it’s critical to get rid of the biases that exist in various forms. Use the insights and tips shared in this post to identify and eliminate AI bias and boost your firm’s cybersecurity efforts.

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Disruption Healthcare & Healthy Living IoT (Internet of Things) Sports

How Artificial Intelligence Is Taking Over the Fitness Industry

You may not observe it, but artificial intelligence is digging deep into daily life. It is evident from the fact that healthcare to business, everything is changing to respond to ever-increasing automation. Besides this, the role of AI in the fitness industry is increasing swiftly without any prior notice or realization by the consumers. It has increased the influence of technology in routine life to help individuals get maximum benefits.

In response to the growth of AI, the states and industry experts are readjusting their focus towards innovation. It is evident from the fact that the United Arab Emirates is pursuing an AI strategy on the national level. Similarly, various supporting events and activities are happening to support the active deployment of innovative technology. You may also be part of AI in UAE based events to know how artificial intelligence is shaping the world. For now! Let’s get some details about the impact of AI in the fitness industry!

The Impact of Artificial Intelligence on the fitness Industry

Health is wealth, and it is the primary reason that people spend more on getting high-quality fitness products and services to stay healthy. No matter if you are an enthusiastic fitness seeker or casually visit the gym once a week, you should know how robotics is an emerging part of the fitness places, including gyms, gaming zones, and many other such areas.

Let’s consider how things are changing in the fitness and wellness industry while giving rise to higher sophistication:

AI in the Fitness Industry: How Artificial Intelligence Takes Over the Fitness Industry

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AI-based Wristbands

Initially, smart applications are the sole focus on fitness experts and the individuals interested in a regular workout. Over time smart applications have been integrated into smart gadgets. Presently, artificially intelligent wristbands and watches are higher in demand owing to various healthcare indicators and fitness facilities. For example, Apple Watch comprised various fitness features that help the people to track their fitness routine with ease and effectiveness.

AI-based Wristbands is one example of AI in fitness industry
AI-based Wristbands is one example of AI in the fitness industry.

Fitness Apps with AI integration

The progress and evolution of smart devices have considerably helped the people to live a life with comprehensive fitness goals. The most interesting benefit of keeping health-related applications is that individuals can personalize their workout experience. In this regard, Googlefit, Fitbit, and many other apps are getting higher popularity among the people. In this way, AI is transforming the user experience of individuals with progressive fitness plans.Fitness Apps with AI integration

Smart Planners for Diet Conscious

There is no denying the fact that the diet plan is the first and foremost important thing when it comes to staying fit. However, many people want to comply with diet plans, but they are unable to do that owing to laziness or any other reason. Interestingly, smart apps for diet planning help such individuals to eat healthy for staying fit. The AI-driven diet planning applications are smart enough to sense your moods for making suggestions about today’s meal. So, you can adopt a proper routine of eating without feeling bound for anything.Smart Planners for Diet Conscious

Intelligent Shoes for Smart People

Do you want to run away? Take some smart shoes with you – they will support you through the thin and the dark. Surprised? It is true that you can find intelligent footwear that knows how well to keep your feet running, tracking, and hiking. The element of AI in the shoes help you estimate your running speed, the alignment of feet with the surface, and stride. So, you can pursue your fitness goals with strong companions for your feet today!Intelligent Shoes for Smart People

Smart Assistants for Gym

Have you seen robotics? Surely you have not imagined that one-day robots will chase you even in the gym. Yes! It’s the reality as modern-day gyms are hiring robots to help their fitness goals achievers. So, if you find a robot coming to you a say, “keep it up,” say cheers to go the fear! Additionally, robots as intelligent nutritionists are making their way towards slimming clinics. You can also get help from Chatbots and AI-powered Virtual Assistants to get advice for fitness problems.Smart Assistants for Gym

Smart Yoga Suits for Accuracy

Yoga is significantly helpful in getting a relaxed and healthy lifestyle. The benefits of yoga are enormous, and so people prefer adopting a routine for performing it. However, fulfilling all requirements of Yoga poses may be a hard nut to crack for many people. The integration of artificial intelligence in this field has changed almost everything. Now, you can buy AI-based yoga costumes that can help you get accurate yoga moves with better insights. The smart sensors attached to yoga clothes and other equipment help people get better in yoga practices every day.

Smart Yoga Suits for Accuracy
The introduction of smart yoga suits aids the accuracy of exercise reading.

Higher Personalization with VR Workout

Virtual reality is transforming the world for experiencing more reality than ever – the integration of the VR environment in the gyms has considerably increased the level of personalization for the individuals. You can also become the part of modern-day gyms by getting the advanced tools to follow your coach through VR-driven gyms and fitness platforms.

Higher Personalization with VR Workout
Gyms and other fitness tools and programs can now be personalized for individuals with the integration of artificial intelligence.

Final thought – AI is the Future of Fitness!

Hopefully, the above-mentioned insights have helped you understand the importance of artificial intelligence in the fitness industry. It is imperative to note that AI in the fitness industry is not only helping the fitness goal seekers but also contributing to fitness business stability. So, the role of AI in the fitness industry is critical in sales, customers’ services, marketing strategies, training, and other stuff related to the business point of view.

The professionals from various industries are joining hands to foster AI awareness to the present and upcoming generations. Want to know more about the perks of artificial intelligence? You can be the part of exhibitions of AI in UAE to get first-hand information along with practical experience with robotics. Don’t forget to experience innovation with an AI-driven future based on a healthy lifestyle!

Categories
Business IoT (Internet of Things) Money & Finance

How To Leverage AI for Lead Scoring in a CRM?

What is Lead Scoring? 

Lead scoring is an approach to rank their candidates/prospects depending on their relevancy to the company. This eventually helps the sales department know the importance of a particular lead. This can save time as well as efforts. Negligence of such practice may waste too much of your efforts put into marketing and sales.

Importance of Lead Scoring 

This method helps you be more productive and at your sales with minimum efforts. These scores help your team know where they need to be placed in their sales funnel. Whether a prospect needs to be treated as a potential customer, prospect or a guest visitor, lead scoring tells you!

How does it work?

Whenever a visitor visits our website, their actions are measured. In simple terms, the number of actions is directly proportional to the lead score. An action might be anything from clicking on a link on any of our pages, scrolling through pages, watching videos, etc. If a lead scores high, it becomes a hot prospect – which means follow-up is necessary now!

How does CRM help in Lead Scoring?

CRM is capable of storing data like customer interactions and leads. These action potential data or insights are then used to provide scores to the prospects. CRM solutions measure these actions and crawl of visitors and provide accurate lead scores for the sales-end.

This then helps you create a healthy customer database and save your marketing efforts by using those insights. Thus, improving your business’ productivity.How To Leverage AI for Lead Scoring in a CRM_

But, how can you leverage Artificial intelligence (AI) for an effective Lead Scoring methodology in CRM? 

AI technology had been helping human lives for decades in automating their daily mundane and repetitive tasks. Similarly, industries as well, are getting benefited with the integration. One of the most in-trend integrations of AI at organizations is ‘resume parsing’.

Artificial intelligence along with an HR software helps HR pick out the best CV from 100s. But, today the hot topic is – ‘Integration of AI with CRM for better lead scoring!’

Illustrated below is the way AI can excel your lead scoring:CRM and AI

Prospect prediction with AI

CRM software is capable of storing customer’s actions and interactions with the department. We can, therefore, leverage this data for predicting the prospect’s cycle. But, the traditional ways of prediction made by people seems to be out-dating due to failures, as it is purely based on their intuition. Whereas, AI algorithms can effectively predict the outcome of the prospect by studying their actions since 1st day.

How come the prediction be so promising? Let’s read some more below.

Public data

Yes. The sales data makes it possible! Customer insights we receive through our sales team generated from a CRM tool is no less than a magical lamp! Artificial intelligence’s algorithm provides you a predicted result of what the prospect would be in the future based on their interests and clicks. Also, previous predictions/ intuitions of sales’ people are taken into consideration for making an effective algorithm for lead scoring.

And, hence the name Machine-learning!

Isn’t it great?

What are the benefits of AI-driven Lead Scoring?What are the benefits of AI-driven Lead Scoring?

Improved Marketing Efforts

Automatic lead scoring using the CRM software can save a lot of effort from marketing people as well. Due to the automated and effective ranking of leads, salespeople can, therefore, perform better and faster. This brings less pressure on the marketing department of bringing more leads. In short, AI can bring you the best results in minimum efforts. Now, marketing people can focus on developing other effective activities and making the entire process more fruitful and swift.

Never miss a Lead

This is when you leverage your talent in the most righteous way. After you get the estimated scores of your prospect conversion (or leads), you know which one of them is more important. You can pass on that inquiry or prospect’s information to a more experienced or skilled salesperson. Based on the scores, priority could be set easily and allotted to the team members to ensure you don’t lose a lead.

Focus at Right

Right lead scoring helps you save your efforts in lead building and nurturing. The scores define priority for each lead. Now you know which lead you need to invest time on and which not. AI with CRM ensures you do not waste your resources and focus on the right thing. The final outcome is an improved business and out-performing sales.

Improved Employee Morale

AI-based lead scoring tells your employees which leads to nurture the most. In short, it tells you what actually needs to be done and where the actual business is. So, locating and winding a prospect at the earliest helps them finish their goals on time. This boosts their confidence in attending more leads and improves self-esteem.

It sounds practical enough! Isn’t it? AI-based lead nurturing along with the traditional conversion method is like a cherry on the cake. The traditional method of predicting the right prospect would never end, but AI can further improve it. Hence, the sales department level up!

That’s it for the subject. I hope it makes the mark at your business!

Categories
IoT (Internet of Things)

AI in the Manufacturing – How AI can transform the Manufacturing Industry

Computer-based intelligence is right now a really made innovation. It finds extensive use in different organizations, for example, gaming, banking, business, retail, and government applications moreover. The manufacturing industry has been contemplating on jumping on board with the transitory prevailing fashion, so to speak, starting late in understanding the authentic estimation of Industrial Automation. AI-driven machines are as of now making the possible destiny of our solace – they offer new possibilities and improve efficiencies are in progress.

Modern Revolution 4.0 as it is fondly referred makes a more grounded propelled economy on the establishment of robotized assignments, which empowers it to reconfigure how people and machines speak with each other and work together to make the world as we experience it today.

The primary concern we consider when we consider AI isn’t the methods by which it can give the complex essential initiative in the assembling industry, or how it can handle issues related to data over-burden. Be that as it may, it’s everything occurring, and the manufacturing industry is set to experience a segment of its most prominent changes yet!

The manufacturing sector (ranging from production to assembling part) is a perfect fit for the utilization of artificial intelligence (a man-made consciousness). Regardless of the fact that Modern Revolution 4.0 is still in its infancy stage, we’re starting to observe huge advantages from AI. From the structure technique and creation floor to the product supply chain and organization. AI will undoubtedly change the way wherein we manufacture things and procedure materials for a very long time.

Here are the manners by which AI is changing and transforming the manufacturing industry:

AI in the Manufacturing Industry - How AI can transform the Manufacturing Industry
When talking about modern revolution 4.0, artificial intelligence tops the list, the impact of AI in the manufacturing industry is enormous.

1. Coordinated Automation

Artificial intelligence and robots together have changed large scale manufacturing landscape, and this is one of the areas where they have the best impact. Robots can keep repeating similar tasks over and over, without getting exhausted or extending the degree of error as time progresses – accordingly, they can offer elevated levels of value affirmation.

2. Nonstop Production

Robots don’t have comparative human obstacles that human masters have and can continue working for the same term of the night similarly as in the day. In view of this inconceivability, robots can develop the production generation capacities of the organizations, empowering them to scale up and produce excellent results.

3. More secure Environment for Production

Workplaces, especially in the manufacturing industry, are much of a hazardous environment to be in for human specialists. There can be no telling which gear may give issue at some point or another, or when a human slip-up will slither. With robots replacing humans, working environment mishaps and disasters will in like manner go down, since robots are not prepared for committing a comparative kind of errors, or even make them at a comparable scale. This alone is one of the transformative effects of AI in the manufacturing industry.

4. Better Opportunities for Humans

With AI in the manufacturing industry assuming control over the replaceable, low-capacity level of intakes from people will end up being dynamically drawn in to take up occupations that will have any sort of impact in their lives similarly as in their general environment. They can turn their focus to befuddled endeavors that require a mix of both IQ and EQ – something AI will be most likely not going to advance commendably.

5. Lower Cost of Operation

Regardless of the fact that the underlying capital speculation required to integrate AI into any part of the manufacturing business might be critical, it’s going to prompt a significant ROI inside the more drawn outrun. As its data processing power and innovative capabilities expand along the way, AI in manufacturing industry specialists will have the option to decide on a fast automated decision, acknowledge vaster adaptability, and encourage speedier and more profound product development. AI creators will have the choice to choose a speedier robotized choice, recognize vaster versatility, and support quicker and progressively significant item improvement.

This will, clearly, add to the residual income of the organization and at the same time decreases the working costs – considering that artificial intelligence in the manufacturing industry is one-time spending with dependable returns on investment.

Wrapping up that computerized reasoning, also known as AI, is a change in context—from a hard-coded, expensive, first-norms based, and unflinching responses for adaptable self-learning arrangements reliant on a great deal of data and AI calculations. Organizations that understood and have mastered the ability of artificial intelligence ahead of schedule, for instance, Google and Amazon, have far-out shadowed their competitors and grown exponentially, all things considered, on account of their superior capacity than expected and steadily conform to changing conditions and to make higher edges.

For organizations with uncertain controls and public financial statement pressures, the stakes and the open entryway cost of not modifying are high. AI producers with overwhelming resources that can’t examine, interpret, and use their own one of a kind machine-made data to improve execution by keeping an eye on the changing needs of customers and suppliers will quickly pass up their opponents or be acquired.

Luckily, process-industry plants are routinely getting and taking care of tremendous proportions of machine data that they can expeditiously mine to make proper calculations. This suggests in spite of the way that they may have fallen behind on the mechanical front, with given instructions from external specialists and between time outside resources as a framework, solid plants, and producers with overwhelming resources can quickly compensate for some recent setbacks.

Categories
Disruption Information and Communication Technology (ICT) Internet Access IoT (Internet of Things) Startups

VoIP trends to watch out in 2020 and beyond

It’s been more than two decades that VoIP has entered the scene and seeing its impact on business communication calling it one of the biggest communication developments won’t be erroneous. The point to ponder here is that it is growing and evolving since the day of its inception. While businesses are swapping their traditional PSTN phone system with VoIP, keeping a close eye on the trends related to it is important to attain the latest usability of this tool. 

Whether you are a business using VoIP or a VoIP service provider, these VoIP trends surely deserve a look if you are to stay atop in the game.

Top VoIP Trends Worth checking out for 2020 and Beyond

Communication - VoIP trends to watch out in 2020 and beyond
It is no longer news that Voice Over Internet Protocol or simply put, VoIP technology is gradually gaining traction of attention to disrupt the communication industry in the coming months. Here are Top VoIP trends that are worth watching out for in 2020 and years beyond.

Cloud telephony is the future

When VoIP was launched, people were using it as an on-premise tool which was a little costly and cumbersome. However, in the wake of technology, cloud computing has made things simpler and easier. Working on cloud space is more convenient and better than this. Users can easily share data with high great security encryption. They need not worry about system maintenance. With call masking facility, they are never going to lose their customers. That is why cloud telephony is considered as the next big thing after VoIP. digitization - cloud telephony

5G is here

Though VoIP is what you need to have easier and all-inclusive business communication, we can’t ignore some of its caveats. Jitter, latency, and data loss bags the top place in the list. Well, we have good news for you. 5G is about to make its public appearance. 

The fifth generation of mobile communication and data connectivity, 5G will give you an uninterrupted internet connection without digging a hole in your pockets. March of 2019 has already witnessed the detailed testing of this technology. With the launch of 5G, users can experience 10 GB/s upload speed with comparatively lower latency. 

This high speed will also improve overall call quality. Now, web conferencing with 4K and 8K video quality will also be possible. The enhanced network competency will be an added advantage. All in all, it will make your virtual phone number more powerful, capable, and quality-oriented. However, it may need new and compatible hardware for proper functioning.VoiP Trends - 5G Mobile Technology

Say Hi to Artificial Intelligence

AI or Artificial Intelligence is already making high waves in other sectors. With Siri and Alexa at our assistance around the clock, it is helping us in a myriad of ways. VoIP is also not untouched with its impact. Your call center software now comes with auto repair facility a Quality of Service or QoS features. QoS can auto cure some of key issues like network issues or latency to a great extent. It can fix the network breakage without much human intervention.

It is also predicted that the future might witness the AI handling unified communication at multiple levels. It can do auto speech analysis, generate useful data with real-time voice conversation, and can create customer experience enhanced ways depends. Your cloud phone system can already set-up a live chatbot on the website. In the future, you may set bots that can talk with the customers just as Siri and Alexa. So, let’s wait for it.

Artificial Intelligence Tools (AI Tools and AI Disruption Industries)

The future-changing merger of VoIP and WebRTC

WebRTC and VoIP are the two de-facto business communication pillars and may get integrated together by the beginning of 2020. If internal sources are to be believed, WebRTC is going to VoIP to do peer-to-peer swapping and web calling. The biggest advantage is that it can work without any added download or extension requirement in your call center software. 

If the merger happens, users can do direct calling from the website, can do live video streaming, and better web conferencing using a cloud-based virtual phone system.

People will fall in love with calling apps 

The mobile app has entered almost every walk of our lives. Telephony is also not untouched with its charm. The use of VoIP calling apps will increase by two-folds in the approaching time.

VoIP Trends - People will fall in love with calling apps
VoIP Trends – People are gonna like the idea of making phone calls via their internet data. Some of social media apps such as Whatsapp, Messenger, Skype have been showing us glimpse of possibilities of this ground-breaking solution.

And what are the reasons for this?

People can make international calls without any hassles, can share media easily, and can easily operate the apps using any Wi-Fi app. That is why in-app communication is considered as a booming trend in the future. 

The only thing that these calling apps were lacking bit was the integration with other systems. However, it is likely to better and advanced in the approaching time. It is to be said that in the future, users can easily get quick access to their hosted phone system within the Microsoft Office application. They can directly access to Excel files and Outlook emails while doing an in-app conversation. Data migration and transmission would be far smoother. Also, the developers are putting much attention on integrating real-time videos and audios in desktop apps and cloud-space. 

Change is good, and VoIP is becoming better and advanced with cloud-telephony. These trends in VoIP are going to change the face of business communication for once and all. So, stay informed, stay ahead of these VoIP trends.

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Uncategorized

Medical Education: Is Artificial Intelligence The Way Forward?

Artificial intelligence is one of the boons of the 21st century. It is shaping the world as we know it. In the future, it will have even more impact. Leveraging it, medical education the way it is taught can be revolutionized.

The use of artificial intelligence is on track to improve medical accessibility to millions of patients globally. It can reduce medical errors, medical negligence, and provide relief to thousands of overworked doctors in the world. For that, doctors need to be well-versed in AI and know how to use it in medical science.

The Role of Artificial Intelligence in Medical Education

Here are some ways medical education can benefit from AI:

1. As a Data Aggregator

Most medical students are incredibly overworked. AI can help them by acting as a data aggregator by:

  • Eliminating rote learning
  • Promoting application-based learning
  • Promoting a collaboration-based environment
  • Promote critical reasoning skills
  • Helping students focus on the essentials of knowledge

AI in medicine as a data aggregator

2. Clinical Decision Making

With the vast amount of patient data available online, the world is moving towards personalized medicine. In the near future, redundant medical tests, that are common for everyone, will be replaced with tests that are tailor-made for an individual. It will provide better patient care and reduce costs. AI is central to this concept, and students need to know it, to be able to use it. It will help in:

  • Conducting a thorough check of the individual’s blood profile and past diseases, if any
  • Generating genomic profile, that is, an analysis of patient’s genes
  • Clinical decision making
  • Predicting the medicines that the patient should use, based on height, weight, age, sex, and other factors
  • Providing high accuracy of treatment
  • Ensuring high efficiency and lower costs of treatment

Clinical Decision Making

3. Help Physicians Develop Empathy

Physicians are mostly overworked wherever you go. In India itself, there is a current deficit of 6 million doctors and 2 million nurses. As such, doctors cannot really be expected to empathize with patients, even as students. Millions of other lives are dependent on them.

AI can help mold budding physicians from a young age by:

  • Freeing up plenty of their time
  • Helping them devote more hours to patients
  • Helping improve their communication skills
  • Helping them take time to listen and empathize with the patient by fully listening to the patient, and learning about the signs and symptoms

4. Introducing Robotic Surgery Courses

The world’s first telerobotic surgery was performed in India in 2018. The doctors using these advanced technologies never had the opportunity to study them in medical education.

However, the world is undergoing a shift in how medicine is practiced. Robotic and tele-robotic surgery is widely prevalent now and in the future. If students are taught such revolutionary techniques during college, they will come out with a very well-equipped doctor.

Benefits of such courses are:

  • Physicians can perform surgery from anywhere in the world
  • Physical barrier to medical treatment or surgery can be eliminated
  • Millions of lives can be saved
  • Medical accessibility issues can be solved, especially in a country like India
  • Future physicians will learn about prevalent technique and be ready for challenges

They can be prepared with skills necessary to upgrade to higher technology in the near future.AI in Medical Education

5. Learn the Importance of Preventive Care

Medical education is primarily based on reactive treatment. It still focuses almost entirely on what to do after you have a disease.

But what if you, as a doctor, could prevent diseases from happening at all?

And this is where Artificial Intelligence comes into the picture.

With the advances in technology, there has been a rise in activity trackers like Fitbit. Leveraging the power of these, you could instantly connect to your patients and monitor them real-time. And you could identify dispositions towards chronic diseases like diabetes and obesity from a mile away. This activity alone can save millions of dollars. Thus, getting to study specialized courses aimed at taking advantage of such technology is very crucial.Learn the Importance of Preventive Care

6. Centralize Data

Rather than making a patient run from department to department, the world is now moving towards value-based care model.

Here, the patient is the most important part of the treatment, and not the overall cost incurred.

Teaching students how to use Data Science and AI to centralize patient information onto a common platform is something that is of utmost need.

AI can help in this context by:

  • Streamlining patient flow through hospital departments
  • Bringing information about medical test results, diagnostic reports, previous diseases or surgeries, if any, on to the common platform for any physician to readily access
  • Readily providing information regarding the issues plaguing patient
  • Other pertinent details, such as the medicine(s) the patient is taking

All these are crucial information that can be collated and analyzed immediately through the power of AI.

Wrap Up

Exposing the physicians of tomorrow to such technology only helps to hone their skills. Thereby, they get ready for the real world, and the technologies that they will get exposed to. Inclusion of these topics during medical education is the best way to equip them with technological skills that will ultimately shape their future.

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Blockchain Technology Designs & Invention IoT (Internet of Things)

7 Powerful Ways to Integrate Artificial Intelligence (AI) with E-commerce!

Artificial Intelligence or AI is one of the latest technologies that has reshaped almost every industry by streamlining their work processes and providing a plethora of other benefits. The e-commerce industry is not far behind when it comes to incorporating the use of AI in order to provide their customers with a seamless and personalized experience

The simple reason being that today, every industry has realized the fact that they cannot sustain in the present competitive scenario if they do not elevate their technology usage. So, let’s get started and discover how impactful AI has been in the past or can be in the future for the e-commerce industry.

Top AI and E-commerce Statistics

  1. As per a report by Statista, the amount for worldwide revenue from AI in 2018 was a whopping $482 billion, and by 2024, this figure is likely to go beyond $3061 billion
  2. Another study by Statista reported the number of global sales in 2018 of the e-commerce industry to be approximately $2.8 trillion, and by 2021, this figure is likely to surpass $4.88 trillion
  3. According to the Ubisend Report:-
  • 20% of customers are happy to buy a product from the chatbots
  • 40% of customers find the top deals with the help of chatbots
  • In 2014, Google acquired DeepMind (a leading AI company) for $500 million

Top 7 Ways to Integrate AI with E-commerceIntegration of Artificial intelligence in ecommerce

1. Predict Services or Sales

E-commerce business is all about online sales, and anything that can drive sales becomes a top favorite amongst owners. AI’s capability to predict sales after the assessment of massive datasets and understanding the pattern of customer behavior is what makes it extremely beneficial for the e-commerce industry. 

For example, Netflix successfully uses AI to know about customer viewing demands and offer the same through information interpretation and collection automation.

2. Automate Back-Office Processes

Most of the back-office processes comprise of tasks which need manual efforts for the management of data and products, which are error-prone and time-consuming at the same time. Automation is the only solution to reduce this type of unproductive workload and pay attention to the other important tasks. 

Image Recognition technology by AI is used aggressively by the e-commerce owners for categorizing the products. For instance, Pinterest uses this technology to enable its users to look for a particular element in the photo.

3. Re-target Potential Customers

If we go by the stats of Conversica, the sales team is unable to follow 33% of the leads generated by the marketing team. This clearly means that the sales team has missed out on the new opportunities generated for the business. 

This is where the role of AI comes in as it can help you do the groundwork for those missed customers and again offer them products based on the data related to their interests and behaviors, explains a provider of ecommerce catalog management services. This way, you will be able to convert your missed customers into your existing customers.

4. Provide Exceptional Customer Service

Exceptional service can only be provided when you are available for the customers 24/7, and manual efforts to achieve the same appears overwhelming. However, with the help of AI, you can achieve this effortlessly in the form of chatbots who are ready to assist customers 24/7. 

These bots not only eliminate the need for human efforts but also bring down the customer service cost at large, along with assisting the customers with perfection.

5. Offer Trending Personalized Contents

Writing algorithms to predict what the customer wants to see is not as effective as using artificial intelligence to provide personalized content and that too, which is trending. This content will be provided to the customers based on present trending brands, customer requirements, countries, channels, and more. 

Eventually, it is all about optimizing the experience of the customers when they come to shop on your e-commerce website and by offering trending personalized content, you will be in the same league as Amazon who has successfully implemented the use of AI for this.

6. Optimize Recommendations & Searches

One of the major functions of AI is to optimize the recommendations and searches for the customers. Having WooCommerce specialty on your e-commerce site is recommended for this. The traditional search boxes fail to win the hearts of the customers as optimizing the search box and offering recommendations to them after the intelligent analysis is what makes the customers happy, and for this, the use of AI is imperative. 

For instance, Go Find uses AI to recommend similar products to its users by asking to take a picture and share it with them.

7. Differentiate Between Privacy and Personalization

It is a known fact by now that user privacy is very sensitive, and companies should tackle it very carefully. Personalization is something which is appreciated by customers greatly but exposing their privacy is not accepted by them at all. This is the reason brands are trying to strive for honesty, transparency, and security during customer interactions. However, brands cannot lose out on the benefits of personalization. 

So, what is the solution? The solution lies in taking the help of AI for balancing the two aspects. If you provide users something in return for their personal information, they do not mind it. For instance, Google Now uses AI to synchronize search habits, calendar, and e-mails, along with a brief which states all that you will get in exchange for the personal information according to the schedule.

Conclusion

This brings us to the conclusion that Artificial Intelligence is indeed a game-changer in the e-commerce industry. It not only helps in reducing the manual efforts through automation like ecommerce data entry but also provides intelligent insights into customer data in the form of interests and behaviors, which ultimately enables the e-commerce owners to offer personalized solutions to the customers. Advancements in technology have benefitted e-commerce giants like Amazon who have made complete use of AI and if they can do it with AI, so can any other e-commerce store.

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Designs & Invention Disruption

The Use Of Machine Learning In Mobile Apps – Its Impact and Growth Potentials

The continuous technological advancements and digital improvements are constantly giving companies new ways to handle clients and approach new customers by providing better and tailor-made services to them. Nowadays, with machine learning in mobile apps, we have left behind the issue of mass personalization and moved on to individualization. That said, companies are able to custom-made algorithms and machines that can easily read humans and respond to their needs and requests.

Machine learning actually has more to do with artificial intelligence where getting predictions right based on a set of statistical data is viewed as the learning process. The outcome of the predictions is what determines if the data will be taken in by the machine or not.

Machine learning has been used in many fields, the notable one being in mobile apps where its impact is great. Here are some of the many ways in which machine learning is significant in the development and operation of mobile apps.

Impact of Machine Learning in Mobile Apps Development and Growth

Machine learning in mobile apps
The impact of machine learning in mobile apps has greatly improved the quality of in-apps service delivery. It is no longer the issue of mass personalization anymore; it is about individualization.

1. Ensuring Security Protocols Are Maintained

Machine learning is key in ensuring the security and privacy of your personal information in your various mobile applications. This will include learning of the behavior of viruses and Trojan horses and preventing them from getting to your apps. By learning these attacks of viruses and other malware, machine learning is able to acquire its own measures to curb their access or infestations.
This is the same with hackers who may try to get to your information using various combinations of characters to achieve this. With their predictions right the machine will have a hint that after three or more attempts of a breach possibility, it will prevent further attempts, hence having machine learning in mobile apps is a blessing to the user.

2. Result Prediction

This prediction can be seen when you try to google for an item and it brings you suggestions that may interest you according to your previous search histories. Machine learning in mobile apps will help change from having to look at your pattern in preference of different items, it will bring items that you may like in accordance to your previous selection parameters. For example in an e-commerce website, you are searching for home goods, then the search engine will list deals and coupons for home goods or websites offering the goods that you searched for.

3. Relevance in Ads

Ads on your mobile application can at times be too much to the point of becoming a nuisance. This is mostly if the ad has no relevance to you and the ad on display has nothing that you need. With machine learning technology embedded in your mobile apps, it can be able to get you the right ads depending on your search history and also online behavior. This is beneficial to both the advertiser and the viewer. This is because the ad will go to the intended viewer with an interest in the product being marketed.

4. Ease in Customization Of The App

In planning app development, the level of customization should be put into consideration for the ease in usability by the user. Machine learning will make it easy in customizing key app features such as font and display courtesy of the noted down preferences by the user. With machine learning, your app will be able to get you such features for your consideration in a bid to enhance your experience.

5. Helps in Visual And Audio Recognition

Mobile learning, courtesy of its niche in predicting patterns and with many successful bids, is able to detect patterns in visuals and audios and give you the right results. This is key in visual and audio recognition which may be used to search for music, detect faces and are also deployed in mobile app security protocols.

6. Analytics

Machine learning, due to its predictive essence can help in the analytics of different expected outcomes together with their probabilities. This is essential mostly in financial and statistical mobile apps. This will help in giving out clear informative data of many variants and also the odds of happening. This is key mostly in forex trading applications.

In this situation, the machine learning will be courtesy of analysis of previous data fed to it and it will take note of the frequency as well as variables to give you accurate results.

Machine learning, as can be seen, is very advantageous in many aspects of the operation of the mobile app. It really helped in the development of more advanced apps. The development of these apps involves the incorporation of artificial intelligence. There are lots of developers around the world willing to provide their services and bring innovations in the mobile industry. Most of the high tech labs dealing with AI are located in Europe. This means if you want to develop such advanced apps you may have to outsource to Europe some of the services in order to get a good bargain for your company. 

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Disruption

AI Disruption: 5 examples where AI still shows itself 

When people hear the words “artificial intelligence” or “AI”, they usually think about something fantastic, but not many are aware of its usage. In fact, it has been used in our life for many years and had a major impact on it.

AI, of course, is present in our online and any other digital activity. Machine learning helps to improve our social media experience and at the same time can be used for developing new healthcare approaches.

In this article, we will disclose 5 most common examples where artificial intelligence plays an important part.

5 examples of industries where AI disruption still shows itself strong

Artificial Intelligence Tools (AI Tools and AI Disruption Industries)
Artificial intelligence has largely drives many industries behind the scene that many of us could hardly believe. here are large number of artificial intelligence tools that are been integrated into social media lately such as LinkedIn, Facebook and others. It has as well influenced development in the health and wellness industry, same of financial market and some others. It is not stopping anytime soon. Here are five Industries that AI has, and will still continue to disrupt massively in the future.

AI in medicine

Machine learning has a noticeable impact on this field. It is used almost at any stage of medical research and treatment. Collecting information about diseases and various cases allows making more accurate conclusions about patients’ health. Personalized treatment also becomes more accurate thanks to machine learning implementation. The same approach allows faster development of drugs as with algorithms clinical trial can be conducted more effectively.

AI in music

Seems like it is a field too creative to use artificial intelligence? Well, you will be surprised that machine learning has been used by services like Pandora or Amazon Music to customize the user experience.

But it goes further and with the help of algorithms, we can create some tunes. Of course, they will not be masterpieces, but hits – easily! The thing is that machine learning can analyze the structure, balance, harmony of the existing pieces of music and compare them to the human reaction. Trust us, that is how many “nostalgic” or “dancing” hits are done today.

AI in photo editing and design

If you use photo editors or social networks like Instagram, you might know already how AI can improve your experience in this case.

Filters, skin enhancers, color improvers and, of course, face finders – these are all the parts of machine learning approaches. They analyze the picture and offer some changes that in most cases make your photo better. And if you tune the settings, you will make your own input in the algorithm development.

AI in trading

Once trading was drastically changed by computers. Now, artificial intelligence took its turn to change the game. The main advantage here is that machine learning can detect patterns that humans can miss. Companies now seriously rely on AI to manage their financial operations.

AI revolutionizes almost every aspect of trading:

– cryptocurrency trading;

– sentiment analysis;

– forecast and predictions;

– blockchain analysis;

– fundamental analysis.

And this is not the limit. There are many other instances of AI disruption aside the aforementioned.

AI in website building

In this industry, we can witness how intensively the technologies evolve and the process of website building becomes simpler and affordable. The great example of such is Weblium. The AI-powered website builder allows people with little to no knowledge in web design to create a landing page or website in less than an hour. And the results always exceed expectations, since built-in Al prevents common design errors.

Machine learning makes it possible to enhance building processes:

– adjust new elements to the general website style;

– maintain the unity of the fonts, paragraphs and other visual elements;

– detect local and global changes and implement them, etc.

The greatest advantage of AI is that it can be taught and developed to meet clients’ needs.

Wrap Up

Of course, on the current level of ML development, we cannot completely eliminate the human part. We still need doctors and researchers to control the diagnoses and treatments that were given by AI.

But with its help, we can solve multiple issues within a shorter period of time and focus on solving more problems. When it comes to online business, you will see how effective your investments will be as soon as you start using services and tools based on machine learning.

The future is now and we should take advantage of it as much as we can.