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Artificial Intelligence and Machine Learning: 5 Developing AI and ML Trends to Watch in 2021

  • Riya Kumari
  • Nov 23, 2020
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“AI and its offshoot, machine learning, will be a foundational tool for creating social good as well as business success” -Mark Hurd


Artificial Intelligence or AI and Machine Learning or ML are much trending and also confusing terms nowadays. They both are being used widely in businesses as well as in our daily lives. AI is planning to make robots as intelligent as we humans are so that they can understand and do the work more efficiently and also save time. 


Machine Learning is a major part of Artificial Intelligence and there is one more term Deep Learning which is also a part of AI and subdivision of Machine Learning. Have you ever wondered how these remarkable fields can benefit you or your company? So, here is an answer to your question. 


Enterprises over the world merge AI and ML with organizations to empower quick changes to key cycles like promoting, customer relationships, and the management, creation and conveyance, and many more. Artificial Intelligence and Machine Learning are going to boost a lot in businesses as well as the whole world. In simple words, we can say that AL and ML are helping companies and people in achieving their goals. 


So, in this blog, we will explore the basics of Artificial Intelligence and Machine Learning with some considerable examples. Also, we will see how AI and ML change security's future, five developing AI and ML trends to watch in 2021 and many more such things.


What is Artificial Intelligence?


Artificial Intelligence is a great technology in today's world, so for your clearance let's describe it in very simple language. Artificial Intelligence refers to technology that can prepare machines to think like human beings. It enables machines like robots to copy the action of humans based on their behaviour. Artificial Intelligence is used in almost every field like the healthcare industry, aviation, cartoons and animation, media industry, and many more. This technology in the coming days can convince to be a worldwide success and might similarly be universally implemented.


Consequently, businesses are also boosting a lot because of Artificial Intelligence as it creates the relationship between the clients and business more worthwhile. There is a lot more to learn about AI, it is expanding day by day. We use it everywhere but sometimes we even don't realize it. Google maps, smart cars, autocorrect, smartphones, smart speakers, and there are many more examples of Artificial Intelligence.


Now, let's Catch a Glimpse of Some of the Best AI Android apps


  • Google Assistant

You must be familiar with this term,  Google Assistant as it is the most popular voice-based AI assistant. This app is available on android phones which can do several tasks like it can set alarms, reminders, make a call, and many more. 


  • Replika

This app is basically for people who suffer from mental health problems. So, this AI-based app can help you as when you feel low or want to talk then you can talk to this app. This assures favourable mental health. Also, it has confirmed to be very beneficial in winning the initial phases of depression.


  • Face App

This application has a bunch of extra filters than the regular ones as it can remake the picture to look more wonderful, even modify it into another gender or various hairdos, looks, and so on.


  • Cortana

Earlier, it was launched on windows phones. Though, after the failure of windows based phones, it was shortly accessible for the windows 10 Operating system and it has similar traits as google's assistant.


  • Swiftkey keyboard

While typing you have noticed that your incorrect words automatically correct itself. So, this is the app that modifies the spellings of words as typed. Also, it has numerous themes and various font categories.



What is Machine Learning?


Machine Learning is an application of Artificial Intelligence which assists in enabling systems to consequently remember and upgrade from the understanding without being explicitly customized. It is being utilized in a wide scope of zones like art, science, and finance. We have various algorithms that are used for ML, for example, Decision Tree, Random Forests, and Artificial Neural Networks


ML directs on the headway of computer programs that can get to data and use it to discover all alone. In basic words, we can say that they consistently grow their activity on an errand without being reprogrammed. Thus, there are several live examples present around us such as digital assistants search the web and play music in answer to our voice commands, websites recommend movies and songs based on what we watched or listened to before, and many more. (Related blog: What is Automated Machine Learning (AutoML)?)


Now, moving towards types of learning algorithms in machine learning. Mainly, there are 3 types of learning algorithms in machine learning that are Supervised machine learning algorithms, which makes predictions. Unsupervised machine learning algorithms, it sorts out the data into a gathering of groups. Reinforcement machine learning algorithms, in which we use these calculations to pick an activity.


How AI and ML Change Security's Future?


As we have discussed earlier that AI and ML are expanding very fast in every industry and they are solving the toughest business challenges. IT security is one of the toughest challenges. According to IBM Security, in 2020, the usual price of a data breach is $3.86 million worldwide and $8.64 million in the United States. Accordingly, let’s scan the effect AI and ML can make in securing our companies.


  • It identifies evolving malware and phishing attacks- Malware and phishing attacks are developing more up-to-date. Malware creators are continually delivering new variations, jettisoning their old virus signatures to avoid discovery. So, here Machine Learning can help by consuming the historical list of all known malware in the wild, it can pinpoint natural personal conduct standards, for example, basic record sizes, what is stored in those documents, and string designs tucked inside the code.


  • Augment, don't replace, security personnel- We often hear that, robots will take our jobs, but this is not true. AI will benefit us in making our work more productive and Network security is no different. AI security devices are not something you install and forget about, you need to operate them properly as they are machines. They are machine learning types that must be instructed on millions of data levels.


There are many more points like this such as it can protect your AI from hackers, Join the arms race, ML can pinpoint patterns and shut down malware in real-time, and so on.


What are the 5 Developing AI and ML Trends to Watch in 2021?


As we have seen that in 2020 Artificial Intelligence and Machine Learning has shown their best from intelligent quantum computing systems to smart personal assistants. There is more to see in 2021. Let's have a look at some points-


  1. The growing role of AI and ML in Hyper Automation


AI and ML are the major components of hyper-automation. To be effective, hyper-automation initiative can't depend on static packaged programming. Automated business measures must have the option to adjust to changing conditions and react to startling circumstances. So, this is where AI, ML models, and deep learning technology come into work, along with data produced by the automated system, to permit the system to automatically modify over time and respond to altering company procedures and provisions.



  1. Bringing discipline to AI development through AI engineering


Organizations and associations are coming to comprehend that a vigorous AI engineering procedure will improve, “the performance, scalability, interpretability and reliability of AI models” and deliver “the full value of AI investments,” as per Gartner's rundown of Top Strategic Technology Trends for 2021. Building up a disciplined AI engineering cycle is vital. Artificial intelligence engineering joins components of DataOps, ModelOps, and DevOps and makes AI a piece of the standard DevOps measure, instead of a bunch of particular and separated undertakings, as indicated by Gartner.



  1. The intersection of AI/ML and IoT


The use of AI and ML is progressively entwined with IoT. AI, ML, and deep learning, for instance, are now being utilized to make IoT gadgets and administrations more brilliant and safer. However, the advantages stream the two different ways given that AI and ML require huge volumes of information to work effectively, precisely what organizations of IoT sensors and gadgets give. ( Also blog: How is AI integrated with IoT?)



  1. Increased use of AI for cybersecurity applications


Artificial intelligence and Machine Learning technology is progressively discovering its way into cybersecurity systems for both corporate systems and home security. They can be employed to help distinguish dangers, involving variations of prior dangers.



  1. Persistent ethical questions around AI technology


According to a Washington Post story, numerous IT vendors, including Microsoft, IBM, and Amazon, declared that they would limit the usage of their AI-based facial recognitioquestionslogy by police departments until national laws are restraining the technology’s use. That has put the focus on a scope of ethical questions around the expanding utilization of artificial intelligence technology.





Artificial Intelligence and Machine Learning are making another vision of machine-human joint effort and taking organizations higher than ever. So, after reading the blog you have realized how Artificial Intelligence and Machine Learning are influencing our day to day life. ML helps associations across different mechanical areas to create savvy arrangements dependent on exclusive or open-source calculations or systems that measure information and run complex calculations on cloud and edge.


"Machine learning allows us to build software solutions that exceed human understanding and shows us how AI can innervate every industry." -Steve Jurvetson


Machine Learning models can be constructed, prepared, approved, enhanced, and tried utilizing recent devices and advances. This guarantees quicker dynamic, expanded profitability, business measure mechanization, and quicker abnormality identification for the organizations. Soon we will watch the maximum tasks getting achieved that appear even unthinkable today.

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