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About Artificial Intelligence and Data Science

Data science, deep learning, and Artificial Intelligence (AI) have all been subject to much research and consideration in the last decade. The current use of these three forms and an expected increase in their future applicability means that they will correlate with each other to form the basis of a smart society.

To understand the differences between the three and how they correlate with each other, it’s imperative to comprehend what they are and how they work towards creating a more technologically advanced society.

Data science, deep learning, and Artificial Intelligence (AI) have all been subject to much research and consideration in the last decade. The current use of these three forms and an expected increase in their future applicability means that they will correlate with each other to form the basis of a smart society.

To understand the differences between the three and how they correlate with each other, it’s imperative to comprehend what they are and how they work towards creating a more technologically advanced society.

Artificial Intelligence

The term “AI” is used so often nowadays that we have a basic understanding of what it means: a computer’s ability to perform tasks such as visual perception, speech recognition, decision-making, and language translation. AI has progressed rapidly over the last few years, but it is still nowhere near matching the vast dimensions of human intelligence. Humans make quick use of all the data around them and can use what they have stored in their minds to make decisions. However, AI does not yet boast such abilities; instead, it is using huge chunks of data to clear its objectives. This ultimately means that AI might require huge chunks of data for doing something as simple as editing text. 

Data Science

Data science is much more than just simple machine learning. Data here may not have been obtained through a machine, and it may not even be for learning purposes. Put, data science tends to cover the whole spectrum of data processing as we know it. Data science is not just related to the statistical aspect of the process, but it feeds the process and derives benefits from it through data engineering. Data engineers and data scientists have a huge role to play in propelling AI forward.

Future Technologies

1. AI in Science and Research

AI is making lots of progress in the scientific sector. Artificial Intelligence can handle large quantities of data and processes it quicker than human minds. This makes it perfect for research where the sources contain high data volumes.

AI is already making breakthroughs in this field. A great example is ‘Eve,’ which is an AI-based robot. It discovered an ingredient of toothpaste that can cure a dangerous disease like Malaria. Imagine a common substance present in an everyday item that is capable of treating Malaria; it’s a significant breakthrough, no doubt. 

Drug discovery is a fast-growing sector, and AI is aiding the researchers considerably in this regard. Biotechnology is another field where researchers are using AI to design microorganisms for industrial applications. Science is witnessing significant changes thanks to AI and ML. Learn more about the benefits of AI.

2. AI in Cyber Security

Cybersecurity is another field that’s benefitting from AI. As organizations are transferring their data to IT networks and cloud, the threat of hackers is becoming more significant. 

One triumphant attack can wreak havoc on an organization. To keep their data and resources secure, organizations are making massive investments in cybersecurity. The future scope of AI in cybersecurity is bright. 

Cognitive AI is an excellent example of this field. It detects and analyses threats, while also providing insights to the analysts for making better-informed decisions. By using Machine Learning algorithms and Deep Learning networks, the AI gets better and more durable over time. This makes it capable of fighting more advanced threats that might develop with them. 

 Many institutions are using AI-based solutions to automate the repetitive processes present in cybersecurity. For example, IBM has IBM Resilient, which is an agnostic and open platform that gives infrastructure and hub for managing security responses. 

Another field is fraud detection. AI can help in detecting frauds and help organizations and people in avoiding scams. For example, Recurrent Neural Networks are capable of detecting fraud in their early stages. They can scan extensive quantities of transactions quickly and classify them according to their trustworthiness. By identifying fraudulent transactions and tendencies, organizations can save a lot of time and resources. It surely lessens the risk of losing money. 

3. AI in Data Analysis

Data analysis can benefit largely from AI and ML. AI algorithms are capable of improving with iterations, and this way, their accuracy, and precision increase accordingly. AI can help data analysts with handling and processing large datasets. 

AI can identify patterns and insights that human eyes can’t notice without putting in a lot of effort. Moreover, it is faster and more scalable at doing so. For example, Google Analytics has Analytics Intelligence, which uses machine learning to help webmasters get insights on their websites faster. 

You can ask Analytics Intelligence a question in simple English, and it would give you a prompt reply. It also provides webmasters with Smart Lists, Smart Goals, Conversion Probability, and other features that help the webmaster in improving the results of their site. 

The scope of AI in data analytics is rising rapidly. Another example of AI applications in this sector is predicting outcomes from data. Such systems use the analytics data to predict results and the appropriate course of action to achieve those results. Learn more about AI applications.

As mentioned earlier, AI systems can handle tons of data and process it much faster than humans. So, they can take customer data and make more accurate predictions of customer behavior, preferences, and other required factors. Helixa.ai is a great example of such an AI application. They use AI to provide insights into customer (or audience) behavior for higher accuracy and better results. Agencies and marketers can use their services to build precise buyer personas and create better-targeted ad campaigns. 

4. AI in Transport

The transport sector has been using AI for decades. Airplanes have been using autopilot to steer them in the air since 1912. An autopilot system controls the trajectory of a plane, but it isn’t restricted to aircraft alone. Ships and spacecraft also use autopilot to help them maintain the correct course. 

Autopilot helps the human operator and assists them in heading in the right direction. A pilot of a modern aircraft usually works for 7 minutes; the autopilot handles most of the steering of the plane. This allows the pilots to focus on other more important areas of the flight, such as the weather and the trajectory of the plane. 

Another area where the future scope of AI is quite broad is driverless cars. Many companies are developing autonomous vehicles, which will rely heavily on AI and ML to operate optimally. Experts believe self-driving cars will bring many long-term and short-term benefits, including lower emissions and enhanced road safety. For example, self-driving cars will be free from human errors, which account for 90% of traffic accidents. Many companies, including Tesla and Uber, are developing these vehicles. 

5. AI in Home 

AI has found a special place in people’s homes in the form of Smart Home Assistants. Amazon Echo and Google Home are popular smart home devices that let you perform various tasks with just voice commands. 

You can order groceries, play music, or even switch on/off the lights in your living room with just a few voice commands. Both of them rely on Voice Recognition technologies, which are a result of Artificial Intelligence and Machine Learning. They constantly learn from the commands of their users to understand them better and become more efficient. 

Smart assistants are also present in mobile phones. Apple’s Siri and Google Assistant are great examples of this sort. They also learn to recognize their users’ voices to interpret them better all the time. And they can perform a plethora of tasks. Microsoft also has a smart assistant, which is called Cortana. 

You can use these smart assistants for various tasks such as:

  • Playing a song
  • Asking a question
  • Buying something online
  • Opening an app

There’s a lot of room left for improvement, but surely, the scope of AI in the smart home sector is booming. 

6. AI in Healthcare

The medical sector is also using this technology for its advantages. AI is helping medical researchers and professionals in numerous ways. 

For example, the Knight Career Institute and Intel have made a collaborative cancer cloud. This cloud takes data from the medical history of cancer (and similar) patients to help doctors in making a better diagnosis. Preventing cancer from moving to higher stages is its most effective treatment at this time. 

We’ve already mentioned how AI is helping researchers in their field too. Apart from finding a cure for cancer, some organizations are using AI to help patients get telemedicine. The UK’s National Health Service uses Google’s DeepMind platform to detect health risks in people through apps. 

Wrong diagnoses are a significant problem in the medical sector. AI can help doctors in avoiding these errors by providing them with relevant databases and recommendations. It can analyze the database of patients with similar symptoms and suggest the treatment that was the most successful in those cases.

Many major organizations, including IBM and Microsoft, are collaborating with medical institutions to solve the various problems present in the healthcare sector. 

AI can also help in reducing medical costs by preventing diseases beforehand and helping doctors in making better diagnoses. BCIs (Brain-computer Interfaces) is another area where the medical sector is utilizing AI. These interfaces help in predicting problems related to speaking or moving that might develop due to problems in the brain. They use AI to help these patients overcome these issues, too, by decoding neural activates.

Job Opportunities

According to a Gartner report, Artificial Intelligence (AI) is estimated to pave way for close to 2.3 million opportunities by the year 2020. And if you look at a report from Indeed, vacancies in the realm of artificial intelligence has doubled over the last three years. A similar report from Indeed also reveals that the most in-demand job roles in artificial intelligence are that of machine learning engineers, software engineers and data scientists.

While the competition in the industry is yet to heat up in the coming months, the current talent pool in the IT industry have already set their eyes on artificial intelligence as an avenue for lucrative paychecks and rewarding career path. Amidst all the commotion that AI will replace redundant job roles with automation and smart devices, we are yet to reach the stage where machines would take over our everyday life. So if you are an AI aspirant looking to land a job in the industry, let us remind you that opportunities are aplenty. This article sheds light on some of the most in-demand jobs in the industry right now.

Data Scientist

By now, we are quite sure you would have understood the roles and responsibilities of data scientists. They are primarily involved in collecting data from multiple touchpoints, analyzing it, interpreting it for inferences and insights and coming up with effective solutions for business concerns. Machine learning and artificial intelligence are integral parts of data science, where techniques from both such as regression, predictive analytics and more are applied for insight generation.

Research Scientist

The role of a research scientist is inter-disciplinary. He or she would go back and forth between working on artificial intelligence and machine learning-based projects. A research scientist would be involved in deep learning, reinforcement learning, natural language processing, computer perception and more. If you intend to become a research scientist, you need to possess skills in parallel computing, distributed computing, algorithms and computer architecture. You can also expect a median salary of over $80,000.

Business Intelligence Developer

A business intelligence developer brings to the table business acumen apart from skills on artificial intelligence and machine learning. He or she is responsible for crunching massive chunks of data for business insights and work on increasing the profits of a company from a myriad of perspectives. From designing and maintaining data for cloud-based platforms to optimizing workflows and processes, business intelligence developers are responsible for carrying company growth on their shoulders.


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Vasireddy Venkatadri Institute of Technology
Nambur (V)
Peda Kakani (Md)
Guntur (Dt)
Andhra Pradesh

9951 023 336
9849 542 336
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