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Neural Networks and its Applications

Neural networks are connections between the neurons in the brain, which are responsible for memory, cognition, learning, and intellectual activities.

These neurons receive sensory input and form connections between them, which become stronger with the inputs received over time. These are called human neural networks and which form the basis for Artificial Neural Networks on computers.

Artificial Neural Networks contain artificial neurons, which are called units. Artificial Neural Networks (ANN) replicate this functioning of the human brain to allow computers to analyze data or do complex mathematical calculations.

This technology has a myriad range of applications, from facial recognition to aerospace. In this blog, we will discuss what neural networks are and its applications…

What are Artificial Neural Networks?

Artificial Neural Networks (ANN) are biologically inspired simulations on computers to perform tasks like clustering, pattern recognition, and classification.

An ANN is a collection of connected units, called nodes, which are artificial neurons. These units are very similar to the neurons of the human brain. Every node has a set of inputs, weights, and a bias value.

Source: bianoti.com

Types of Artificial Neural Networks

      Feedforward Neural Network (FNN)

Feedforward Neural Network is the most basic form of Artificial Neural Network in which the data/input travels in a single direction. 

The data enters the ANN through the input layer and exits through the output layer.

Source: stackoverflow.com

      Recurrent Neural Network (RNN)

RNN saves the output of a layer and feeds it back to the input to better predict the outcome of the layer. 

The first layer is similar to the Feedforward Neural Network, and RNN starts once the output of the first layer is computed.

      Convolutional Neural Network(CNN)

A Convolutional Neural Network (CNN) is somewhat similar to a feed-forward neural network. In CNN, the connection between units has weights that determine the influence of one unit on another unit. It has applications in speech processing and computer vision.

Source: kdnuggets.com

      Modular Neural Network

A Modular Neural Network comprises a collection of different neural networks that work independently. The output is achieved without any interaction between them. Each neural network performs a sub-task by obtaining unique inputs as compared to other networks.

      Single Layer or Multilayer Perceptron (MLP)

Neural Networks with two input units, one output unit, and no hidden layers are called single-layer perceptrons. Multilayer Perceptron have more than one hidden layer of neurons, unlike Single Layer Perceptron, which has no hidden layers.

Multilayer Perceptron is also known as deep Feedforward neural networks.

Source: github.com/PetarV-/TikZ

Applications of Neural Networks

1.    Facial Recognition

This application is mostly used for surveillance at public places such as shopping malls, airports and similar. Digital images are compared with human faces by recognition systems. It can also be used for selective entry at offices.

This is done by Convolutional Neural Networks (CNN), which have a database of a large number of pictures. These pictures are further processed for training a neural network. 

Source: bbc.com

 2. Aerospace  

Neural Networks in aerospace engineering are used to model key dynamic simulations, secure control systems, auto-piloting, and diagnose faults. 

As passenger safety is of utmost importance in aircraft, neural network systems built algorithms ensure the accuracy of autopilot. 

3. Healthcare

Convolutional Neural Networks (CNN) are actively employed in the healthcare industry for X-Ray detection, Ultrasound, and CT scans. Medical imaging data retrieved from these tests are analyzed and assessed based on neural network models.

Recurrent Neural Networks (RNN) are being used for the development of voice recognition systems. Generative Neural Networks are used to match the different categories of drugs, which is needed for drug discovery.

Source: sanet.st

4. Sales & Marketing

AI and neural networks are also used in marketing and sales industries. You would have noticed that when you open up an eCommerce site, they suggest products based on your purchases & previous searches. Similarly, cloud kitchens give recommendations based on previous orders.

This is true across all segments, like movies, hospitality, and online bookstores. This is called personalized marketing and is done using artificial neural networks. These networks identify individuals’ likes, dislikes, and purchase histories.

5. Personal Assistants

You would have heard about personal assistants like Alexa, Siri, Cortana, etc. These assistants make use of speech recognition, Natural Language Processing to respond to users’ queries. Natural Language Processing uses artificial neural networks to understand human language, accent, and context. 

6. Stock Market

Predictions in the stock market were difficult to make before Artificial Neural Networks came into existence. Stock Market predictions are made using feedforward Artificial Intelligence algorithms and neural networks. 

Neural networks have shown success in successfully predicting market trends.

Source: hxlpartners.com

7. Weather Forecasting

Weather forecasts made by the Meteorological Department were never so accurate until Artificial Intelligence & neural networks came into the picture.

Multilayer Perceptron (MLP), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) are the neural networks that are used for weather forecasting.

Using Artificial Neural Networks(ANN), climatic conditions can be predicted 15 days in advance. Parameters analyzed include air temperature, wind speed, solar radiation, and relative humidity.

8. Social Media

Artificial Neural Networks(ANN) are used to analyze the behavior of social media users. This is done using Data Collection and Analysis. The findings can be used for promoting products according to their likes and dislikes.  

Multilayer Perceptron(MLP) is used for this application along with different training models, which include Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Squared Error (MSE). 

Source: medium.com

Wrapping Up…

Neural networks function in a way that is very similar to the human brain. As the brain becomes more intelligent as it gathers information, Artificial Neural Networks also perform better over time. 

As we have seen, Neural networks have a wide range of applications. Artificial Neural Networks have simplified traditional algorithms and made Sci-Fi movies closer to reality.

For more information about Neural Networks and its applications, get in touch with us at Zesium.


Victor Ortiz is a Content Marketer with GoodFirms. He likes to read & blog on technology-related topics and is passionate about traveling, exploring new places, and listening to music.

Use of Modern Technologies in Documentaries

As technology makes the world more accessible to us, so too does it open our eyes to the many stories and experiences out there to tell. Documentary filmmakers have been telling these stories for ages, and their platform for producing and presenting these stories has only continued to widen, also due in large part to technology.

It’s only fitting, then, that technology has availed itself to documentarians to help make their filmmaking process more efficient and effective and even improve the quality of the documentaries they create.

Cinema itself was a revolutionary technology in storytelling and journalism at one time. Now, revolutionary technologies like virtual production, volume technology and LED walls, AI, remote editing and storage and real-time rendering have made it even easier to make films that tell those stories more vividly than ever before.

Virtual Production

In early 2022, French documentarians became one of the first in their country to incorporate virtual production techniques into a filmed production with the documentary series 2080.

Appropriately focusing on innovations in modern technology, the show incorporates not only motion capture and CGI technology but virtual effects (VFX) projected on an LED wall rather than a green screen (a virtual production technique known as “volume technology.”)

Virtual production is somewhat of a catch-all phrase for any filmmaking enterprise incorporating at least one virtual or CGI-based element. Many of the other technologies discussed here, in fact, could qualify as or contain an aspect of virtual production.

Among the technologies falling under the canopy of virtual production include those to produce:

●       Performance and volumetric capture

●       Virtual camera outputs, such as pan, tilt heads and master wheels

●       The feel of a handheld camera

Cinematographers can now use simple and convenient drop-down menus to alter lighting and switch between lenses.

Though its applications for documentary filmmakers may only just be emerging, filmgoers can already see elements of virtual production in action in science fiction films—an apt genre for experimenting with new storytelling technologies—like 2013’s Oblivion, which used back-projection techniques to bring high resolution to backdrops containing actual footage rather than green screens. (You can see Oblivion’s masterful use of virtual backgrounds for free on DIRECTV STREAM.)

While it may be easier, certainly, to see how fictional films can incorporate virtual characters, worlds, elements and effects, documentarians can also benefit from this technology.

For example, to explain the workings of a complex engineering or biochemical mechanism, a documentarian can employ CGI. To recreate a setting or scene to convey a critical narrative within the film, a documentarian can create a virtual rendering of that environment and even the characters concerned.

What started as a technology for video game engineering providing an innovative way of manipulating polygons, backgrounds and VFX creations has become an increasingly valuable asset for filmmakers.

Source: mediafactory.org.au

Artificial Intelligence (AI)

Artificial intelligence (AI) is one of the first and foremost modern technologies working its way into film production, as filmmakers are discovering the many ways it can play a major supporting role in the filmmaking process.

Scriptwriting and Analysis

AI makes the task of coming up with new stories that have the potential to wow modern audiences more efficient. AI algorithms can be fed large quantities of film scripts from which to cull and analyze data and apply what they learn to the writing of new scripts.

When it comes to documentaries, this can be incredibly helpful in coming up with effective and compelling narration. The time this use of AI can save filmmakers in finding good stories to tell can ultimately save production money.

Another application of AI for the writing of films is script analysis. Once documentarians compose their footage into a script, they can use AI to analyze that result and identify any weaknesses in its narrative structure or holes in its presentation of the information. It can then ask questions and suggest revisions to improve the script.

Pre-production Planning

AI can help simplify and streamline pre-production by helping automate necessary processes such as schedule planning and location scouting. By helping to efficiently coordinate schedules of talent (interviewees, etc.) crew and location availability, AI can again help save productions time and money.

Source: simbasible.com

Performance Predicting

AI can help productions predict how successful a film may be with audiences and how much revenue it may pull in.

This can be useful for studios deciding whether or not to produce or distribute a particular documentary and how many resources to put behind it. Studios and filmmakers can also use AI to help match a film to its most likely audiences.

Cast Selection

While cast selection may not be as big a factor with documentary filmmakers as with fiction filmmakers, there are still decisions to be made as to what faces and voices to show audiences to help tell their story.

Many documentaries have figures that must appear in the film to present the full story. However, they may also have parts of the story that several personalities may be qualified to convey, such as multiple officers, lawyers or friends of a victim or suspect in a crime documentary or multiple first-hand participants, witnesses or analysts involving a central event. In deciding which of these people to include in the film, AI can turn out to be quite useful.

Movie Promotion

It’s commonplace nowadays for studios to use AI to market their films.

They’ll use AI to analyze a film’s audience base and the popularity of the subject with filmgoers in various locations and demographics to help determine where and how best to promote the film. They may even use AI to help come up with those advertisements.

Source: huffingtonpost.co.uk

Music Composition

Using a technique called reinforcement learning, AI can develop musical patterns based on data it analyzes from other compositions as “inspiration.”

It can also base these musical patterns and their changes throughout a film on the tone or atmosphere of the movie at any given moment. It can even account for factors of the genre.

Algorithmic Video Editing

Using AI to edit films according to a defined set of rules is known as algorithmic editing. Nearly all films in the modern age use this technology to some degree in their editing process.

Some of the ways algorithmic editing can help streamline and improve the editing process of a film include:

●       Organizing footage based on faces, landscapes or other visual identifiers

●       Automatically cutting footage to suit a particular style or narrative flow, such as the flow and balance of interviews with direct footage

●       Optimizing post-production workflow

Audio/Visual Restoration and Recovery

For his acclaimed documentary The Beatles: Get Back, a behind-the-scenes look at the band’s production of the album Let It Be, Peter Jackson used AI in a process called “demixing” to reveal muted conversations in the studio between the bandmates. (Stream The Beatles: Get Back on Disney+.)

Another example of AI’s use in film restoration and enhancement is how it was used to restore the Lumière Brothers’ seminal 1896 documentary short L’arrivée d’un train en gare de La Ciotat (Arrival of a Train at La Ciotat) and then enhance it into 4K at 60fps.

Remote Editing and Storage

Documentarian filmmakers Jim Rota and Dean Gonzalez faced dual difficulties when trying to edit What Drives Us featuring Foo Fighters’ frontman Dave Grohl. COVID forced them to work from home, so they turned to remote editing to get the film completed. But, to remote edit the film, they needed a sufficient means of remotely storing the over 1,000 photographs and hours of B-roll footage and video interviews they compiled, comprising in total of about 54 TB of data.

Not only did they need a reliable remote storage solution to remotely access that data and save their progress working with it; they needed enough throughput with that storage to handle various key editing components, like playback, review and editing and sequencing scenes.

Rota and Gonzalez used an enterprise-grade NAS storage solution from OpenDrives called Blackmagic Design’s DaVinci Resolve 17. It allowed them to use a MacBook Pro for all post-production processes, from compositing many images into a single one to adding effects to correcting color for consistency to mixing sound–all from the same platform.

It also allowed them to transfer video files directly between the camera storage card, a workstation and an editing interface without needing to change the file format. (You can stream What Drives Us on The Coda Collection through Amazon Prime Video.)

Real-Time Rendering

Another outcropping of the video game industry, real-time rendering allows filmmakers to make changes to a digital environment almost instantaneously, avoiding the cumbersome render times that formerly stifled progress on production.

With the ability now to see and adjust how a production’s digital and physical components interact in real-time, they can work quicker and more precisely than ever.

 While not a documentary, this technology can already be seen in films like the sci-fi epic Gods of Mars.

Source: blogs.nvidia.com


These are just some of the newest software technologies documentary filmmakers are using on their projects. Modern tech has also given documentarians a slew of filmmaking hardware innovations and improvements to advance their craft, from high-quality, pocket-sized cameras to drones.

 One day soon, other modern innovations like virtual reality (VR,) augmented reality (AR) and AI voice synthesis and voice cloning will work their way into the documentary filmmaker’s standard toolkit.


Frank Moraes is the editor of the cord-cutter website HotDog.com

How can AI help You to Reach Success in Business Writing

Artificial intelligence is one the rise. This technology is considered one of the most promising ones to solve not only everyday business issues but also deal with global challenges. 

While the opportunities of AI are almost limitless, let’s narrow down its use cases to content writing and find out how AI solutions can help modern writers and businesses create top-notch content for their audience and reach their business goals. 

Source: prdaily.com

Artificial Intelligence in a Nutshell

To better understand how Artificial Intelligence, content writing and digital marketing are aligned, let’s get started with a brief explanation of artificial intelligence as such. 

As the name suggests, AI is a data-driven algorithm programmed to solve certain tasks. Artificial Intelligence is a general concept so it makes more sense to talk about Machine Learning since this is already a more specific technology able to learn the patterns, catch the anomalies, define the trends and even make data-driven predictions.

The role of Artificial Intelligence in business is growing. To date, a lot of companies use AI solutions to automate marketing tasks, predict market trends, automate routines, eliminate human mistakes, analyze customer data, improve safety on the workplace, optimize different business processes and even develop a business growth strategy, being guided by real-time data and market trends predictions. 

AI content writing is one of the applications of this technology in modern digital marketing as well. What’s more, an AI-powered content writer does exist (the program capable of writing the texts from scratch on its own) but most companies still prefer to hire human content specialists. 

The latter, in turn, are welcome to use the whole set of AI-driven tools to improve and simplify their writing process, delivering better results to the business owners. 

Source: analyticsinsight.com

How AI Helps Writers to Create Top-Notch Content

Writing in the future is expected to become fully driven by AI, but to date, there are a lot of applications to use in content writing and digital marketing. 

Below are some of the AI use cases, which create new opportunities for bloggers to make their writing more engaging, streamlined and polished. 

Grammar Check

Yes, you guessed it right. 

Grammarly, one of the most popular tools in modern content writing is fully driven by AI. 

While checking for grammar mistakes and typos is its simplest function, the Premium version opens up access to neural networks algorithms that are capable of catching the context of the article and making data-driven suggestions to improve your writing. While Grammarly isn’t always right, its improvements can be pretty valuable for those who want to be calm about their text clarity, engagement, and correctness. 

In addition to checking for grammar mistakes, AI-driven tools can also help you improve your text readability, get rid of passive voice and complex sentences. For this purpose, you can consider the Hemingway app which is also algorithm-based. 

Source: technology.inquirer.net

Plagiarism Check

Both plagiarism and duplicate content are essential indicators for search engines.

Fortunately, you can deal with these issues with the help of Artificial Intelligence solutions as well. Already familiar and popular plagiarism checkers are ultimately powered by AI  – its data analysis capabilities allow the algorithm to quickly scrap the web and find overlapping pieces of text. 

As for duplicate content, it works in almost the same way but checks the content within the framework of your website only. Read more to find out how to check duplicate content and why this subtask on on-page SEO is essential for your content promotion. 

SEO Research

As always, SEO promotion is still pretty complex. 

In addition to the need to write top-notch content and create useful backlinks, you also have to carefully research the relevant keywords and fill your articles with them. And here is one more use case when AI helps businesses with both content writing and SEO promotion. 

Such tools as Ahrefs, HubSpot, Answer the Public and others are fully data-driven and work with the help of AI. Their data analysis capabilities allow the businesses to get updated information on keywords relevancy, performance, frequency, and other important indicators. 

Source: gospelherald.com

Performance Analysis

In addition to creating the content as such, there is always a need to check its performance. 

There are automated tools that allow for measuring the bounce rate, users’ dwelling time, conversion rate, finding out the source and amount of traffic, evaluating the performance of your backlinks, and much more. 

There are even solutions that allow for tracking real-time user behavior on the website, for example, Hotjar. With the help of this tool, you can get a better idea of what pieces of your content the users interact with best, discover the stumbling blocks in your website design, and develop better tactics to make your website more user-friendly and your content – more valuable and engaging. 


Enriching your content with stunning graphics is a great way to make it more engaging. 

Still, not all business owners have the budget to hire a designer for this purpose. As well as not all of them consider stock photos to be good for their business reputation. Fortunately, there is a solution that leverages the power of AI to create custom photos, videos, and images. 

For example, with the help of Prototypr.io, you can drag and drop picture elements to come up with your own, add or remove backgrounds, use face swapping, and much more. It works like Photoshop but is easier and more affordable to use. 

Source: vecteezy.com


The opportunities of Artificial Intelligence for business can go on and on. When limited to digital marketing and content writing, they open the way to create better content, stay updated on your performance and goals’ achievement, automate routine tasks and find out more insights on how your users behave in response to your marketing tactics.

Choose the AI use case from the one we have reviewed above and get started with unlocking the power of artificial intelligence for your both core and non-core business processes! 

How to Integrate AI for Digital Marketing Success

The business world has continuously embraced the use of technology because of its massive benefits. Artificial Intelligence (AI) has therefore become fundamental in the operation of these businesses. 

Companies that have embraced this technology have reaped big, and the results will continue to skyrocket from stats. 

Dive in to understand how to integrate AI for digital marketing success.

Personalized Content Creation

Content is a cornerstone of any digital marketing company. However, gone are the days when ANY content was king. For you to reach your audience, you have to curate your content to meet your customers’ immediate needs and you can get the best from it if you personalize your content.

Have you subscribed to any company newsletters? If yes, you should have noticed how they address every person by their names and even emphasize the content as if they know you. 

The secret is AI technology. With the use of AI, companies send personalized content to every prospect hence increasing conversions.

Many firms have embraced this technology while sending emails to prospects. 

Email marketing is the best way to reach clients and candidates in real-time. It has also proved to be the best tool for converting prospects into long-term clients. All the company needs is to send regular emails with insights that try to solve client needs. In turn, candidates will seek favor and more solutions, which is how they become warm prospects or even long-term clients. Use email marketing to send industry-specific news, company updates, or just to check in with clients. 

This regular communication with your consumer base will go a long way to converting sales. 

Source: rxdigitialmarketing.com

Using AI Chatbots Services

It is part of the ancient past when representatives answered every customer’s queries. 

Many companies have invested in AI chatbots that solve many customer problems in real-time. 

The chatbots engage prospects immediately when they click the link to your website. Clients trust such sites when they get help on the go.

AI allows the chatbot to gather helpful information from different sources of data. That enables other brands and businesses to communicate with consumers on a personal basis. That is what Under Armour and IBM did when they collaborated. The record learns more about one’s different activities and suggests the best way to perform better. The Under Armour App provides users with advice about nutrition, health, and exercise.

If you invest in chatbot technology, you will save a lot as everything happens, even without your customer care representative. You can start your own drip campaign, marketing automation, and chat service to boost your customer service ROI. Search for quality services online to help you implement this technology. 

Doing this will also reduce the number of customer care representatives, as the bots will do a more significant percentage of the customer care services.

Source: knowledge-era.com

User Experience

Have you ever asked who decides on the ads you see when you open your browser? 

There is a lot of work in the background to arrive at every ad you see on your social media platform when you open eCommerce apps like Amazon

Many companies have significantly invested in AI technology to the extent of knowing your region, your search history, and likes and preferences.

From stats, customers who receive ads that match their interests are likely to purchase them, increasing the conversion rate. 

AI has dramatically enhanced customer experience and an increasingly more significant customer base with little effort. AI technology is able to collect a wide range of user insights that can influence your marketing campaigns and messages. AI can save your company money by collecting this data for you about your customers. 

This data will not only enhance the consumer experience through personalization, but it can help your company create data-driven solutions and tactics to grow your business

Source: in.pinterest.com

Lead Generation

With the help of AI, you can generate more leads for your current website.

The technology extracts and analyzes insights from an extensive database. It matches the data with the other leads hence derives a probable conversion rate for every lead. With the technology, you can first target prospects with a higher conversion rate before going for the others with less conversion. 

Moreover, when you use the correct data and AI technology, you can easily predict customer experience hence adjust accordingly.

Source: pipes.ai

Image Recognition Technology

You will agree that you found your photo target or friend target to a particular image at some point. 

Many platforms invest in image recognition technology to target the right audience, mainly when they use images similar to what the niche leaders post.

For instance, you can decide to make an image similar to your most significant competitor’s bit with minor adjustments. Clients will efficiently prospect for your products. They, too, might remain your prospects if they get what they need. However, please don’t use the technology to dupe customers to your company and fail to get what they want. 

Offer the best services as you utilize image recognition technology.

Source: openthegovernment.org

Bottom Line

AI continues to rock the digital marketing world. 

The technology has helped the firms curate the best content customized to every prospect which in turn generates higher leads and a more personalized experience for the consumer. It has also helped the companies attract many clients with minimum effort. AI is also fundamental customer care assistance as they support candidates to get what they need in real-time. Technology is essential for any business with the vision of remaining at the brim of operations.

How will Artificial Intelligence Aid Business Growth in 2021

Artificial Intelligence (AI) investments among big businesses are on the rise. Currently, the percentage of businesses using AI grew by 270% from 2014-2019. Most of these businesses are large companies, but small to medium-sized businesses are also adopting AI technologies. 

Whether people are aware of it or not, Artificial Intelligence permeates most of the services and applications they are using daily. 

Current AI investments among big companies include the following AI applications

  • Augmented Reality (AR) and Virtual Reality (VR)
  • Autonomous Vehicles
  • Machine Learning
  • Machine Vision
  • Natural language Processing
  • RFID
  • Robotics
  • Touchscreens
  • Voice recognition

AI is also extensively used in the medical industry – for diagnosing and recommending treatment actions for patients. These data-centric business solutions enable medical specialists to give accurate and more personalized recommendations. 

In addition, AI serves a crucial role during the pandemic. It is used for proper screening and predicting the current and future patients, early detection and diagnosis of the infection, developing drugs and vaccines, and reducing healthcare workers’ workload.

Personalization in Business Interactions

Approximately 85 percent of consumer interactions in 2020 were done without the involvement of human beings. Chatbots and other platforms became more dominant as the pandemic raged and they include online sales and delivery, automated retail, and touchless engagements

Many facets of eCommerce are affected by AI today as it quickly detects trends and clusters in consumer behavior, purchase patterns, and other commonly occurring data. In fact, AI now makes it possible to detect millions of such purchases per day, generating a customized experience for a single user.

More than 33 percent of marketing leads are lost due to a lack of follow-up. By effectively retargeting new clients, AI stops this from happening.

With the sales processes moving beyond time-consuming methods, consumers are now influenced by different media types. Using artificial intelligence integrated into CRM systems enables businesses to personalize solutions and communications that target the right consumers at the right time for the proper purpose.

Source: cio.com

AI-Powered Email Marketing

AI has been playing a significant role in email marketing for years. Email marketing generates steep revenues at $38 for every dollar spent.

Since most businesses have moved online, the competition for the market’s attention has become more cutthroat. However, intelligent strategies powered by AI solutions can level the playing field. 

You need to start using data-centric email marketing plugins, allowing you to create unique email marketing strategies that yield the best possible results. If you are already using email marketing, upgrade to AI-powered plugins to stay competitive in 2021

Those who could retain their brick-and-mortar stores start collecting customer email addresses using a POS (Point-of-Sale) system. Just make sure you do all your lead generation in keeping with privacy laws to avoid issues for your company. If you’re exclusively an eCommerce retailer, you can collect email addresses as visitors land or leave your site. 

Modern POS systems and retail platforms can be linked to email marketing apps such as MailChimp. This way, you can create and manage a subscriber list, automate email campaigns, and generate detailed reporting. 

Source: pinterest.com

Cashless Payment Solutions

A more straightforward way to go touchless amid the global crisis is to use cashless payment solutions. More and more consumers now use E-wallet payment platforms and apps.

A Mobile E-wallet helps you keep money and move funds to your bank account by scanning a QR code. It may be linked to a customer’s debit or credit account, depending on the business’s preference. To be vigilant, you can top up or fill just the cash you need on your E-wallet. 

Any aspect of the transaction, including billing to receipts, is digital, regardless of customers’ devices. Cashless payment is also possible for microbusinesses in small communities through online payment apps.

Source: prnewswire.com

Contactless Sales and Shipping 

Contactless delivery is the new normal. 

Drop-off delivery options are now a standard among logistics companies like DoorDash, Postmates, Instacart while eCommerce sites like Amazon, Shopify have long offered this feature. 

Sales and shipping has dramatically increased during the pandemic as people observed social distancing and lockdowns all over. We will continue to see contactless delivery options rise in 2021. 

For instance, self-driving vehicles and robots for grocery and food delivery are emerging around the world. Meituan in China, Walmart in the US, Ocado in Europe, and Rakuten in Japan are just some examples of AI-powered vehicle solutions helping businesses thrive in the pandemic. 

We will see more companies comply with human touch preservation via artificial intelligence-based applications.

Source: istockphoto.com

Business Automation 

The rise of AI technology has led to work automation marking the new-age business revolution. The theme remains constant, from robots working in factories to automated hotel bookings and property technology – incorporating AI systems for business automation. The only difference is the AI applications employed. 

With a growing trend in the automation of routine work, AI is quickly automating several routine business processes.

AI is one of the fastest-growing and popular data-driven technologies being used worldwide. From governments and large organizations to small online businesses, AI is being used by multiple entities across the world to automate routine operations, making way for human resources to focus on high-quality tasks.

Streamlining operations through AI solutions is a smart move for businesses to cope with the demands of a new normal economy. Artificial intelligence statistics from a recent survey show that more than nine in ten top businesses surveyed are already investing in AI technology.

Companies’ growing use of AI shows plenty of benefits, at the top of which is business productivity. 54 percent of business executives claim that AI adoption within their work led to an increase in productivity. Such effective use of AI also helps with better and more accurate decision-making within organizations. 

Source: acom.com

Distributed Teams and Remote Operations

Remote working has been around even before the pandemic. However, the crisis pushed remote working and distributed it into the forefront in 2020. From government offices to private companies, everyone had to adjust and find ways to keep operations ongoing. 

The reason for this is because the pandemic remains to be controlled. 

Another reason is the dramatic decrease in revenues for most companies affected by the lockdowns. 

A third reason is that distributed teams cost less than a full-on, on-site staff. As the economy begins to recover, more and more businesses discovered a remote work setup’s glories mention they will keep these newly-adopted work setup. 

Even employees and freelancers themselves find the remote work setup most suitable for them when preservation of health and safety is critical. Mobile apps to increase productivity at home multiplied to answer the demand for remote working. 

Video conferencing has thus become a norm – Zoom rose rapidly as a videoconferencing platform, outranking Skype, Google Meet, and other messaging apps because of its features that were quickly able to accommodate the exodus of professionals and students coming its way. Although it experienced security and technical issues with the sudden jump of its users, it bounced back real quick and made the app more secure, able to accommodate even large-scale webinars from around the world. 

Many new ventures are emerging in the remote working sector. Startups Bluescape, Eloops, Figma, Slab, and Tandem have all provided 

Visual collaboration platforms are also on the rise, enabling teams to interact, create and share content, monitor projects efficiently, conduct online employee training and run virtual team-building activities. Such examples include startups Bluescape, Slab, Figma, Eloops, and Tandem. 

Micro-SaaS companies in the new normal economy are also increasing, most of which integrate Artificial Intelligence and machine learning solutions to improve modern businesses

Source: mdsny.com


The growing use of AI isn’t just widespread in businesses. As the technology goes mainstream, consumers worldwide have become more receptive and accepting of it.

Businesses need to work on communicating how they’re using AI within their organizations – despite the growing acceptance of AI, many consumers remain wary of how businesses are using the technology. Only 54 percent of consumers claim they trust companies to use the data collected from AI in a way that’s beneficial to consumers. 

To boost small businesses, owners must be open to AI adoption and integration – the increasingly widespread use of AI is boding well for SMEs (small to medium enterprises) because it is becoming more accessible and affordable in many ways. 

If customers are willing to use AI-powered solutions for a better experience, then all the more the businesses should. 

Keep up with consumer demands and maintain their edge amongst their competitors. 

Practical Use of A.I. in Transportation

Artificial Intelligence (AI) is a technology that fuels machines with human intelligence – machines that have AI capabilities can automate manual tasks and learn on the go just like humans. 

Such automation gets repetitive and time-consuming tasks under the AI-powered systems that learn with time and can eventually carry out critical tasks and make decisions on their own. 

Such unique potential drove the transportation businesses to start investing into AI technology to improve revenue and stay ahead of their competitors. 

Transportation industry has just begun to apply AI in critical tasks however the reliability and safety in transport are still under question. Major challenges in transport like safety, capacity issues, environmental pollution, reliability etc. provide a huge opportunity for AI innovation. 

No matter downfalls, AI in transportation is yet to reach 3.5 billion dollars by 2023

Source: techstreetonline.com

How can A.I. help transportation:

Transportation industry faces problems when a system functionality cannot form per predictable patterns which are affected by external elements like traffic, human errors or accidents.

A.I. uses data to predict decisions appropriately and it has been implemented in a variety of ways where some of examples include

  • public safety (e.g. tracking crime data in real time),
  • autonomous vehicles (e.g. self-driven vehicles),
  • pedestrian safety (e.g. tracking pedestrians/cyclists paths to minimize accidents),
  • traffic patterns (e.g. causes of delays, reduction of traffic congestion) and
  • corporate decision making (e.g. accurate prediction methods and forecasts). 
  • etc.

Benefits of AI in transport:

The best fit of AI and transport somehow came naturally as adoption of these technologies can have a massive impact on the entire industry although the application of AI still varies across geographies. 

Increased use of A.I. will ensure reduced labour costs while providing higher profits – fully automated fleets will be there to resolve an issue of long driving hours and breaks.

AI can also have a huge impact on safety and traffic accidents. Driving at night is a great issue and smart unmanned vehicles can significantly improve the problem. Auto-pilots or unmanned vehicles that can operate without a human can help the drivers to snooze without causing any traffic accidents.

Traffic management can also be more effective – AI methods enable us to forecast traffic by using traffic data and details about urban ongoing events as well as suggest alternative routes by automation. 

Complex infrastructures and various elements within cooperation chains can be improved with the help of AI through e.g. optimal route schedule, minimal waiting time, traffic detection in real time for adjusting the routes etc. 

Data analytics in logistics can also help upgrade transportation planning and increase safety in general. 

There are many more benefits to list yet AI is still growing and the benefits will too.  

Source: raconteur.net

Drawbacks of AI in transport:

Although AI can bring a plethora of benefits to any industry, there are also some drawbacks to pay attention to like creating transparency in AI decision making or safety issues within autonomous vehicles. 

One of drawbacks include job flow as it became a major issue for truck or taxi drivers and other industry members. Although social experts tried to explain that job skills can be shifted to other sectors, tensions remain. 

AI implementation can also represent drawbacks as undeveloped countries will face massive challenges in utilizing such solutions as their infrastructure is not capable of providing maintenance.  

Transport companies also face potential AI drawbacks as transportation costs contribute to the company revenue by up to 10%. All existing businesses will need to develop and implement AI technologies to remain competitive within their industry and the high cost of developing, repairing and maintaining the complex machines can be extremely high.

Ethic issues are also under revision – companies bringing AI to transportation will have to take the ethics of AI seriously if they want to win consumers’ trust. 

AI technology still needs significant improvement as it’s still far from a human level of intelligence. 

Source: zfort.com

AI in Transportation

We can already find the examples of AI being used within transportation. As Artificial Intelligence evolves and becomes more mature, it is certain that the number of roles where AI plays a major role will increase.

Some of the examples where AI is common in transport are:

Autonomous Vehicles

Autonomous vehicles are already a reality within transportation. They represent the first step into a new future of autonomous transportation although it seemed quite a futuristic idea in the past.

A.I. uses its processing, control and optimization capabilities to power these driverless vehicles. With autonomous vehicles, real-time data transmission and processing is crucial and any confusion within these processes can cause fatal outcome.

In Tokyo, autonomous taxis have already begun operating but the driver sits in the car for safety reasons to be able to take control of the taxi in case of emergency situations. 

Source: https://asia.nikkei.com/

The USA started to implement autonomous trucks as of 2018 as 65% of goods are carried via trucks globally. It has also been predicted that maintenance and administration costs can be reduced by around 45% with autonomous trucking. 

Waymo company has introduced self-driving minivans and trucks within a certain number of states for testing on public roads.

These types of projects are still in pilot versions while trying to make autonomous vehicles safe for passengers but as the technology evolves, autonomous vehicles will gain more reliability and become much more widespread. 

Passenger Transportation 

The safety of passengers, pedestrians and drivers has always been a number one issue for the transportation industry. 

The use case of AI was the autopilot system which is used in almost every commercial airplane today and it is a vital part of any air travel nowadays.

New York Times reported that only 7 minutes of an average Boeing flight is controlled by humans (takeoffs and landings) while the rest is being handled by an autopilot.

Public transportation will also be hugely affected by A.I. since there have been driverless buses recently transporting passengers with the help of sensors, cameras and GPS. 

Source: interestingengineering.com

A.I. technology can do so much for us – it can reduce the human errors within traffic, monitor the safety regulations compliance, review vehicle maintenance reports and manage transportation in such manner to decrease effects of driving risks in urban areas.

Smartphone Apps

Today, ‘there is an app for everything‘ – it includes AI powered real-time traffic updates through services like Google Maps or Waze

These applications use location data collected from smartphones to be able to analyze traffic conditions within your local area and inform the users better about the traffic. 

These apps may soon face competition in the form of autonomous vehicles as why would you need an app if the car itself already does the same work?

Source: techcrunch.com

Traffic Management

AI can be used to manage traffic systems due to its processing, control and optimization capabilities. In order to make the roads smarter, AI can be applied to traffic management to streamline the traffic. AI prediction ability to recognize the physical or environmental issues that may lead to heavy traffic or congestions is another great benefit. 

Source: interestingengineering.com

Sensors and cameras implemented on the roads collect large amounts of data related to traffic details. Such data is analyzed by big data and AI systems to reveal traffic patterns. 

The relevant insights assist commuters with details on traffic predictions, accidents or road blockages and provide suggestions on the shortest routes to their destinations.  

The example is Siemens Mobility which has tested a prototype A.I. monitoring system through traffic cameras – it alters the traffic lights based on real-time road congestions hence minimizing road congestion. 

This way, AI can reduce redundant traffic, improve road safety and reduce wait times. 

Source: bbc.com

Law Enforcement

Law enforcement is another area where A.I. is not being used to help law officers to identify people drinking or texting while driving, for example. Earlier, this represented an issue for human officers since vehicles move at high speed but A.I. has resolved this issue. 

Now, A.I. can detect quite accurately if a person drinks or texts while driving and sends an alert to any nearby officers to intercept them. 

One of those examples is Motorola Solution which brings AI voice assistants to law enforcement vehicles where police can just state a license plate and the system will look up the information and respond within a few seconds. 

Source: bbc.com

Delay Predictions

Another problem within transportation, especially air transportation, is the delays. As per the research paper by the University of California, Berkeley, flight delays can cost up to 39 million dollars in the USA. 

In order to overcome flight delays costs as well as passengers’ negative experience, AI comes to the air transport for rescue. 

Data analysis and computer vision come to assist and shorten passengers’ waiting time as AI can use its capabilities to predict anything from bad weather to a certain number of technical glitches which may cause flight delays. Computer vision systems can intermittently monitor the aircrafts while AI along with Machine Learning (ML) use and process real time aircraft data, records and weather information. 

Computation can reveal some hidden patterns helping the industry to gain valuable insights on possibilities that may cause delays or cancellations. 

Source: express.co.uk

Drone Taxis

Drones have already been used in delivery service systems but soon they could be used as taxis as well. Unmanned aerial vehicles represent a one-of-the-kind solution in fight against carbon emissions, traffic congestion or expensive infrastructure.

Drones as taxis will allow people to arrive at their destinations much faster while reducing their commuting time to a minimum at the same time. Regarding urban areas, drone taxis can be a real deal for solving the issues like urban planning and urban infrastructure development. 

Some recent examples of drone taxis was a display of an autonomous aerial vehicle in China, where 17 passengers had a chance to experience smart air mobility for the first time. 

A few years ago, Uber took a step forward to make autonomous ‘flying taxis’ a reality by signing a partnership with NASA to develop the software to operate them.  

These use cases indicate that similar future applications are about to be developed.  

Source: interestingengineering.com


Artificial Intelligence (AI) has become more than just a visionary idea – it is a part of our daily lives and we use it each day without even noticing. AI can be found in our mobile apps, in social media feeds or in the way how Grammarly checks our grammar mistakes.

Transportation industry has already used some AI solutions for a while but it won’t be long until the increase of AI within transportation and logistics.

As A.I. is getting more subtle with time, it is a matter of time when we will get to see the exciting future driven by AI!