In this era of technology, one can not be unaware of it. People in every corner of the globe have started using technology to get their work done. Dependency on machines is increasing with every passing day. To serve better, they also need to be smart enough. They need to be intelligent. However, none can match the excellence of a human brain.
Yet there are developments enough to understand the commands of humans. It may be easy for tech geeks to guess, but for people not so fond of technology, artificial intelligence is the term we are talking about here.
There is rarely any sector that has not adopted this modern solution that helps them serve better. Some reports say that 77% of the world is already using Artificial intelligence in some way. Artificial intelligence has been the talk of the past decade and its roots are ready to go deeper. For those who think AI is just a technology world thing, they are pretty far off. It's being used everywhere. So, in this article, we will be looking at the top five trends in AI that should be eyed upon. But for this, we will begin with a brief description of AI.
“Artificial Intelligence is transforming children’s future. But we must ensure that it upholds their rights..”
-Henrietta H. Fore, Executive Director, UNICEF
Artificial intelligence is a branch of computer science that talks about the intelligent behavior of machines. In simple words, it's like making machines think and work more like humans. AI has been a revolutionary step in the technology world. It has made our lives simpler and it aids humans to achieve complex tasks ‘like a cup of tea’. AI has made things possible which looked like a magical fate to our ancestors.
This use of AI continues and there will be some new developments. So, we will talk about eight such trends in Artificial Intelligence.
Snapdragon 865 Plus - AI- Enabled Chips
AI-Enabled chips are the latest trend in Artificial Intelligence. Their popularity has been continuously increasing. An article by geeksforgeeks said that the spending on such chips will increase by 15 times by the year 2025 when compared to the spending in 2018. This advancement is being acknowledged as a crucial development because these chips will enhance the functioning of smartphones.
Everyone is well aware that reliance on smartphones is continuously increasing and companies are progressively making an effort to fulfill the demands. While some brands have already integrated AI-Enabled chips, they are also being added to the latest smartphones.
These are smartphones that are made intelligent enough to anticipate a command from their owners. In such a scenario, AI required specialized CPUs alongside the main ones, because the primary CPUs are unable to do such tasks with efficiency. So, these AI-Enabled chips make sure that tasks like facial recognition, natural language processing(NLP), computer vision, object detection, etc. occur at a much faster rate.
Many companies are in the manufacturing of such chips. NVIDIA, AMD, Qualcomm are at the top among these.
Qualcomm had announced their AI-Enabled Snapdragon processors that can perform 15 trillion tasks per second with sheer efficiency. In December 2019, Snapdragon 865 was launched while this year they came up with Snapdragon 865 plus which is powering the high range smartphones like Samsung S20 ultra.
"Companies will adopt AI — not just because they can, but because they must,.."
-Ritu Jyoti, program Vice President, Artificial Intelligence, IDC
Artificial Intelligence(AI) and the Internet of Things(IoT), the two massive names in technological innovations, and when we talk about using them together, it's a match made in heaven! The integration of these two advanced technologies makes life even better.
IoT devices work to create a collection of data that are required for actionable insights. On the other hand, the Artificial Intelligence algorithm requires such data before reaching any conclusions. So, don't these two complement each other?
Artificial Intelligence algorithms can work on the data brought by IoT devices to create useful results and then can be passed on to IoT devices to deliver them.
One example to better understand the usefulness of the integration is the Smart Home Devices. These devices have made lives simpler and it’s predicted that 28% of homes in the US will become Smart Homes by the year 2021. Not only households, but businesses also are increasingly adopting smart devices as they are efficient.
Organizations are always looking for alternatives that are less complicated to use yet are capable of doing the work equally well. One such alternative that has emerged in the past few years is Automated Machine Learning. Organizations are more inclined to use AML over using the traditional machine learning models that are way too expensive and complicated. AutoML does not require its user to be an ML tech wizard, however, some ML expertise is required to set additional parameters as needed.
This means that tools like Google Cloud AutoML will become more popular in the future. It is so because they are used to train custom-made and high-quality ML models while even with a minimum machine learning expertise. The companies in the US like BackLocus, Zenefits, Nationstar Mortgage, etc. are already using the AutoML and many more are likely to follow.
AI and Cloud Computing
The concept of Cloud Computing has helped businesses in cutting the cost of infrastructure setup. And when integrated with Artificial Intelligence it becomes even more handy. AI and Cloud Computing together revolutionize the current market and create new methods of improvement. It’s quite evident that AI is the technology of the future but its integration requires experienced employees and enormous infrastructure. This is where Cloud Computing provides immense help.
Companies do not need to worry about massive computing power and access to large data sets, they can still avail the benefits of AI through the cloud. AI, in return, can be used to manage issues in the cloud. Currently, the leaders in the market that incorporate AI into their cloud services are Amazon Web Services(AWS), Google, IBM, Alibaba, Oracle, etc.
With the increased use of technology, security issues reside alongside. CyberSecurity is not a new concept but its integration with AI enhances the functionality. The addition of Artificial Intelligence improves the analysis, understanding, and most importantly prevention of cybercrime. The use of AI becomes more prevalent because cyber attackers are already using it to enhance their attacks. A study by Capgemini Research Institute proves the fact. So, the use of AI in CyberSecurity will provide a more secure environment to work. Moreover, AI allows for a faster response to security breaches.
These chatbots are computer programs that undertake interactions via audio or text. There are many ways through which chatbots are adopted, like marketing, processing, and payments although their biggest plus point is the customer service they enable.
It is believed that in 2020, chatbots will get even more capable of matching human interaction, enabling a considerable section of customer interactions to take place via chatbots. Upon adopting AI and machine learning, chatbots can decipher what a user inquired in prior communications, personalizing the present interaction on the basis of data gained from all prior ones. This renders a much-improved user experience and an enhanced customer satisfaction level while presenting effective communication patterns in comparison to what the human operators offer.
In the month of February 2020, big-box retailer Walmart introduced thousands of robots to its workforce. The purpose of these robots was to help in managing inventory, scrubbing floors, and keeping product shelves in place.
In the near future, we would observe grocery stores that provide a range of automated technologies and only a handful of human assistants for ensuring that everything operates flawlessly for the consumers.
Alongside automated payment systems and robots, biometrics is yet another way offering AI the power of revolutionizing the manner in which retail stores perform. While in the present times the technology is being adopted in the case of mobile phones and for scanning fingerprints yet it has a possibility of being adopted in stores in the future and be used for interpreting one's facial expressions as they observe the varying products and then generate personalized promotions on the basis of the sensors’ observations.
As per a report termed as A Future That Works: Automation, Employment, and Productivity, which is based on a study conducted by McKinsey Global Institute, there is a prediction that almost half of our work duties have the possibility of being executed by a robot by the time that nearly half of our work tasks will be performed by some form of a robot by the time 2055 arrives. RPA may automate any task which could prove to be repetitive or routine.
For instance, Goldman Sachs Group, an American investment bank, that had once employed 600 traders in its New York office, now has the same tasks being executed by merely two human traders and a range of AI tools.
The role of Artificial Intelligence in the transformation of lives is increasing day by day. Companies are already into their adoption. As mentioned above no sector is deprived of AI’s use and it is going to increase further. A report by IDC says that Worldwide Spending on Artificial Intelligence is expected to double in the next four years. It shall reach $110 billion by 2024 from $50.1 billion in 2020. India too is looking to make its economy completely digital and hence continuously working to achieve this. IDC has unveiled the top 10 AI predictions for 2020 and beyond for the Indian market.
This stat is just approval to what we have been saying already. AI is the dominating technology of this decade and will continue to dominate in the coming ones too.
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
6 Major Branches of Artificial Intelligence (AI)READ MORE
Top 10 Big Data TechnologiesREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
7 types of regression techniques you should know in Machine LearningREAD MORE
Deep Learning - Overview, Practical Examples, Popular AlgorithmsREAD MORE
Introduction to Time Series Analysis in Machine learningREAD MORE
What is the OpenAI GPT-3?READ MORE
How Does Linear And Logistic Regression Work In Machine Learning?READ MORE
7 Types of Activation Functions in Neural NetworkREAD MORE