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Artificial Intelligence

How AI Training Data Can Be A Security Threat To Your Company?



AI training data risk and threat

The race into Artificial Intelligence (AI) flying field is becoming more expeditious with new and more innovative developments across the world. However, such competitive approach also posing a new threat to companies working on such projects.

Every coin has two sides – AI is also brining such risk which needs to understand timely. Actually, I’m talking about the training data that is primarily used in model training and development. Though, there are many security issues with AI-based model development and applications developed using this technology.

But training data is the information you upload into the algorithm to create your AI model is highly vulnerable towards the hackers and fraudsters, if they manage to access that. If such crucial data landed into wrong hands, it can be mischievously manipulated to crash your computer networking system or breach the privacy and security of your company.

Your AI-based application is also equally susceptible to hacks or data leaks, hence you need to protect your data and we have discussed right here what are the major issues you need to consider while working on such AI-based projects.

Are you storing your data at a safe place?

If you are using cloud-based AI services where you upload your labeled data on such online data servers. You don’t know if this cloud is directly under control of your service provider, or do they own the entire stack. Moreover, always remember that maybe your cloud is secured, but not necessary it is used in a secured manner.

As per the global research and advisory firm, Gartner’s prediction up to 2022, at least 65% of cloud security failures will be occurred due to customer’s fault.

Hence, you need to make sure use the secured cloud-based AI services and also need to audit threats and risks that your employees usage may pose to the cloud.

Who possess your training data?

This is a big question – Who owns your training data? Actually, when you use a cloud-based machine learning algorithm to develop an AI-based model, you have to upload your training or testing data into the services algorithm.

Also Read: What is Training and Testing Data in Machine Learning with Types?

Let’s take an example – Suppose you are using an NLP look through your call data which a proprietary data providing a competitive edge is a very sensitive data that you are legally bound to protect from unauthorized users.

Here, you need to make sure you do not permit any rights to your data and that you will own the final model created with that data. So, carefully check the “terms of service”, license agreements and other fine print before signing up for using any cloud-based AI technology.

And if you find anything unfavorable in their “terms of service” or ambiguous you can terminate the service and go with other reliable service providers.

Similarly, you also need to make sure you are not using unmoderated publicly available datasets for your AI or ML training data, as this can open you up to malevolent data source that can seriously poison your application or fail the model.

Also Read: Reasons Why AI and ML Projects Fail Due to Training Data Issues

Do you clean up the data from such servers?

Once your AI model training is completed, it is necessary to delete all vestige from the servers used in training. Finally, you are going to use the AI application and whenever you kick-off your AI project, it’s easy to carry off with the possibilities it opens out.

Usually, managers emphasize speed and innovation, but take your time to understand what is going on behind the scenes. This will definitely help you in long-run in securing your application from mishandling while ensuring the privacy of the customer’s data.

Acquiring the machine learning training data is not difficult but keeping it secured and private during the model development is very important for every company enthusiastic in such developments.

Thus, consider such aspects while working on such projects, especially when you use a cloud-based algorithm to build an AI model and stay ahead in the competitive market without losing your privacy and data safety.

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Artificial Intelligence

What Is Computer Vision In Machine Learning And AI: How It Works?



Computer Vision in AI and ML

Thanks to AI and machine learning, computer vision technology is getting upgraded with improved versions of visualizing making perception through machines reliable. Actually, this is completely related to computer-based visual processing of objects.

What is Computer Vision in Machine Learning and AI?

Computer vision is simply the process of perceiving the images and videos available in the digital formats. In Machine Learning (ML) and AI – Computer vision is used to train the model to recognize certain patterns and store the data into their artificial memory to utilize the same for predicting the results in real-life use.

The main purpose of using computer vision technology in ML and AI is to create a model that can work itself without human intervention. The whole process involves methods of acquiring the data, processing, analyzing and understanding the digital images to utilize the same in the real-world scenario.

How Does Computer Vision Work?

Computer vision in machine learning is used for deep learning to analyze the data sets through annotated images showing an object of interest in an image. It can recognize the patterns to understand the visual data feeding thousands or millions of images that have been labeled for supervised machine learning algorithms training.

This process depends subject to the use of various software techniques and algorithms, that are allowing the computers to recognize the patterns in all the elements that relate to those labels and make the predictions accurately in the future. Computer vision can be only utilized only with image processing through machine learning.

How Computer Vision is Different from Image Processing?

Both are part of the AI technology used while processing the data and creating a model. The difference between computer vision and image processing in computer vision helps to gain high-level understanding from images or videos.

For instance, object recognition, which is the process of identifying the type of objects in an image, is a computer vision problem. In computer vision, you receive an image as input and you can produce an image as output or some other type of information.

Whereas, image processing doesn’t need such a high level of understanding of image. In fact, it is the sub-field of signal processing but also applied to images. For example, if you have noisy or blurred images, then under image processing the deblurring or denoising is done to make the object in the image clearly visible to machines.

The image process task involves filtering, noise removal, edge detection, and color processing. In entire processing, you receive an image as input and produce another image as an output that can be used to train the machine through computer vision.

Also Read: The Main Purpose of Image Annotations is to Develop AI Model

The main difference between computer vision and image processing are the goals (not the methods used). For example, if the goal is to enhance the image quality for later use, which is called image processing. If the goal is to visualize like humans, like object recognition, defect detection or automatic driving, then it is called computer vision.

Application and Role of Computer Vision in AI and ML

The applied science of computer vision is expanding into multiple fields. From AI development to machine learning, it is playing a significant role in helping the machines identify the different types of objects in their natural environment.

From simple home tasks to recognizing human faces, detecting the objects in autonomous vehicles, or combating with enemies in war, computer vision the only technology giving an edge to AI-enabled devices to work efficiently.

The application of computer vision in artificial intelligence is becoming unlimited and now expanded into emerging fields like automotive, healthcare, retail, robotics, agriculture, autonomous flying like drones and manufacturing, etc.

Also Read: What is Training and Testing Data in Machine Learning with Types

Actually, to create the computer vision-based model the labeled data is required for supervised machine learning. And image annotation is the data labeling technique used for creating such labeled images for computer vision.

Many companies providing the data annotation service for computer vision providing the image annotation solution for AI and machine learning.

Rendering the high-quality training data using the best tools and techniques allowing computer vision to help algorithms train the model to perform accurately in real-life use.

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Artificial Intelligence

How Chatbots Can Transform Your Business: AI Chatbot Six Benefits



How Chatbots Can Transform Your Business

AI-enabled chatbot is becoming popular among the companies, curious about their customers to help them all-the-time as per their ease. Actually, such AI automated chat application system comes with multiple benefits, that a business owner can utilize and improve their customer service while growing their business.

As per the Gartner recent reports – by the end of 2020, around 85% of business relationships will be managed by the customer without interacting with humans, which will encourage more demand and adoption of self-help service.

And chatbots are the best self-help applications improving its communication process with more critically implemented natural language processing to learn about human interactions in their native-speaking style to communicate easily.

Read Also: What AI Techniques Are Used In Chatbots: Explained with Examples

In upcoming days, most of the brands including newly emerging business enterprises will use this AI-based technology into their business operations and improve the overall customer relationship experience while generating more revenue.

Hence, here we will learn how a chatbot can help to improve your customer service and transform your business to achieve new goals and reputation in the markets transformed through chatbot benefits.

Six Chatbot Benefits for Business and Customer Service

#1 Round-the-clock Customer Support

The best part of AI-based chatbot is, available all-the-time for the customers to solve their queries as per their needs. As we know there is no need for humans to operate or manage this application, it works itself and can answer the questions asked by the customers related to products or services offered by your company.

Companies serving overseas customers have different time-zones, and customers in working hours contacting their service provider in another country running with sleeping time can be only handled by such automated chatbots.

#2 Multiple Customer Engagements at a Time

Another interesting point of adopting chatbot into your business is – it can handle multiple customers at a time, which is not possible for a person to interact or chat with different people at a time without any response time delay or waiting time.

The multiple customer handling capabilities will not only serve different customers at a time but will also minimize your customer service expenses while improving the customer engagement process in terms of solving the multiple issues quickly.

#3 Reduce Human Errors and Emotional Support

Humans can do mistakes but the machine doesn’t do that until a major bug affects the system which is rare, as such applications are integrated only after full testing. Similarly, chatbots don’t do any mistakes while answering the customer’s questions.

Also Read: What are Chatbots and how they are changing the World of Business?

Identically, unlike humans, chatbots don’t have feelings, so they cannot be influenced by the people asking any kind of emotionally attached questions. The human customer service agent can change their minds or can do favor against the company policy, while chatbots cannot be influenced by such psychological factors.

#4 Cross-platform Accessibility to Customers

In the smartphones and tablets era, people are accessing various services through such gadgets. And chatbots can be accessible through multiple types of platforms and devices making available to customers anywhere as per their ease.

These chatbots can be designed and developed as per the different devices and operating systems that can be integrated with customizing options for instant chat. Chatbots are accessible through desktop PC, laptops and smartphones.

#5 Better Understanding with Data Gathering

When humans in customer service interact with end-users and end their conversation, they don’t look at the chat data, except the concerning factors to solve their queries. While AI-enabled bots can gather chatbots training data to analyze the sentiments of people, learn human speech through NLP and understand them better.

And this kind of crucial data is not only important to understand them and serve with better service, but also help chatbot developers to train their next model with more accurate data sets for better results through automated chatbot system.

#6 Save the Time and Cost of the Company

Last but not the least, if you integrate the chatbot system in your business to provide the automated online help or support system to your customers you will save the cost and time of the company in managing and operating such services.

Human employees can be retained only by paying monthly payouts, but chatbots need a one-time cost in development and execution. Human’s salary needs to be hiked while chatbot needs only updates at a few extra costs which are only if you have subscribed to any third party chatbot service provider to use on your website for support.


AI benefiting humans in different ways, and AI-enabled Chatbots will not only provide you an edge to your business but would also help to serve your customer better. Using such bots if you can get to know what exactly your customers seeking and understand their feelings through sentiment analysis to serve them best.

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Artificial Intelligence

How Do Deepfakes Work And What Are Disadvantages With Advantages?



deepfake advantages and disadvantages

Deepfakes are an AI technology based created realistic fake images or videos of targeted people by swapping their faces another person saying or doing things that are not actually done by them. And people start believing in such fake videos, as it is not recognizable with the normal human eye, it requires in-depth analysis.

How Do Deepfakes Work?

A Deepfake video seems like an original content having the person doing some kind of action or speaking on a topic. And while creating such fake videos, multiple images of the targeted person from different angles are used to superimpose on the original face.

Video: How Deepfake is Created

Images are compromised with faces and other body parts, to make it look original while creating videos, the voice is also cloned with a targeted person using the AI-enabled tools to simplify the process and match the lips moving according to words spoken.

Deepfake videos affect the life of popular personalities in our society. Politicians, actors or actresses, other celebrities and notable personalities from the corporate world. AI and machine learning-based tools are used to generate such content. But with the help of Deepfake detection services, such fake videos can be detected.

Also Read: What is Deepfake: Know Everything About this AI-based Technology

And Deepfake works like creating sensational news stories about popular personalities that people love to watch and also share with others or include in their gossips. And Deepfake porn videos gets more attention and invites more hitting on adult sites increasing online visitors count on such portals.

Disadvantages of Deepfakes

Rather than benefiting anyone, this AI-based technology has disadvantages affecting different groups of our society. Apart from creating fake news and propaganda, deepfake is majorly used for revenge porn to defame notable celebrities.

deepfake disvdantages

As soon as fake videos go viral people believe initially, and keep sharing with others makes the targeted person become embarrassed watching such unusual acts.

Until and unless an official statement of the targeted personality not comes, many people start believing making their life difficult, especially when they are criticized by their fans via social media platforms like FaceBook, Twitter or Instagram.

Advantagesof Deepfakes

Though, it is harmful to the society but it also has few advantages like creating extraordinary attention among the online audience making the web page popular on the search engine, as more number of people start searching on such erotic topics.

And few celebrities who are not known to everyone also become famous overnight, as people start searching reading about them, what they do, what is their profession and more about their personal background and current reputation in the market.

People become more cautious about such news

Another factual advantage of deepfake is, it makes us become aware about such fake things and we should not believe in everything we see around us. Once we find that it is fake we learn and next time when such contents come through similar sources, we take time to believe or do some research to authenticate the news.

Deepfakes Advantages

Though, such benefits are only for the audience, they don’t have any significant advantage to the person who becomes a victim of such misuse of technology. And detecting such fake images or videos timely, only can help acknowledged people to not become a victim of deepfake and if happens should be detected timely to stop further circulation.

Anyway, whatever the impact on different sections of our society, but there are many companies providing deepfake detection services to recognize the fake images or videos and control further circulation for such fake contents.

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