The synergistic relationship of Big data and AI is already changing the way businesses operate, but it is expected to accelerate as AI becomes more accessible. And a lot of companies start ramping up investment in their data science and analytics departments. So let’s look at 5 specific Big data analytics and artificial intelligence trends that businesses will use in 2022 to develop and grow.
What is Big data and artificial intelligence?
Big data refers to inputs and raw materials that artificial intelligence uses to analyze and generate insights and decisions. Therefore, it is an integral part of artificial intelligence. Artificial intelligence differs from traditional analytic programs because it can learn from and react to new information without having to be guided by code. The main goal of AI systems is to not merely identify patterns but to accomplish tasks that humans were previously doing, such as driving or reading X-ray results.
Why does Big data affect artificial intelligence?
Artificial intelligence can not run in a bubble because, just like the human mind, it relies on inputs to develop ideas and solutions. This required input is known as Big data. It refers to large data sets that can be on literally anything, from the life expectancy of mice to the average salary of Finnish people. By programming AI to devour different types of data, it can then effectively come up with solutions and make decisions on a range of different topics.
Why is Big data and artificial intelligence important for businesses?
Big data and artificial intelligence are literally a superpower. By leveraging superhuman computational power, businesses that adopt the technology and AI will be able to not only learn how to meet the needs of their customers more effectively but also perform tasks to a higher standard at quicker speeds through automation. For example, currently, Netflix is using insights generated by Big data to produce and recommend content that you enjoy based on your viewing history. However, in the future, Netflix will be able to produce entire content written by AI that is curated to meet your exact wants.
While Big data and AI are in their infancy stages, they are already being used by a range of different businesses. So let’s now look at 5 trends that will accelerate the Big data and AI world revolution.
Deepfakes and synthetic data
Have you been watching Tom Cruise on TikTok lately? Many people were shocked to find out that the videos were not of the Mission Impossible star at all but resulted from deep fakes or synthetic media. The technology that is used to create deep fakes and other synthetic data is called generative AI as it is able to produce data, images, or videos which are completely fictitious. The most notable use of this form of AI has been in Hollywood, where Martin Scorsese was able to turn back the clock on Robert DeNiro in The Irishman. In the future, you can expect many of your favorite actors to be playing much younger versions of themselves, thanks to the powers of generative AI.
Hollywood and the entertainment industry won’t be the only businesses leveraging generative AI in 2022. Synthetic data is already being used to help train AI and machine learning programs. Synthetic data is preferred most times because it is cheap and does not cause privacy concerns. For example, generative AI can be used to produce fake faces, and these faces can then be studied by AI programs to enhance facial recognition algorithms while avoiding the privacy concerns involved with using real people’s faces.
Big data and artificial intelligence in healthcare have the ability to save millions of lives, and generative AI will play a major role in 2022. Synthetic medical data, such as medical scans, can be used to train machine learning programs to develop the ability to spot rare conditions more accurately and faster than doctors. The use of synthetic data management is incredibly important for identifying rare diseases as due to limited real sample sizes making accurate diagnoses becomes very challenging.
The use of synthetic data in health care is already well underway. For example, in 2018, the Mayo Clinic and the MGH & BWH Center for Clinical Data Science trained AI to spot tumors using fake brain scans. The results were amazing, as the AI that used 90% fake scans could make as accurate diagnoses as the AI that used real scans (Big data increases precision in medicine).
Customer experience powered by AI and Big data analytics
Thanks to AI, companies can now take a large amount of data and use it to provide a superior customer experience. Big data analysis can be used to enhance all aspects from customer service, logistics, marketing, accounting, and more. In 2022 you can expect businesses to continue to make it more enjoyable to shop online due to their ability to leverage new insights uncovered through data analytics.
Here are some of the ways artificial intelligence and Big data will be used in 2022 to enhance the customer experience (many of the top Big data analytics companies are already using these methods):
- Forecast trends – In 2022, expect companies to more accurately predict what, when and how much a consumer will buy. Companies will use this data to create new products and ensure those products are readily available at key times.
- Targeting the right leads – With the use of the technology, companies can filter leads based on their quality which cuts down on the time businesses waste contacting potential buyers who are not a right fit for their products or services.
- Finding the right people and effectively training them – Are you tired of dealing with clueless customer support staff or overly push sales reps? Well, in 2022, you can expect many businesses to enhance their current staff by using it to improve their hiring and training process. For example, companies can analyze all of the customer feedback left for customer support reps and quickly identify key areas that need to be improved (fusion of software development and Big data). Companies can then create training modules based on these problem areas and rapidly improve their customer experience.
- Providing a personalized experience – Expect more and more businesses in 2022 to go down the Netflix, YouTube, and Amazon route and make personal recommendations to you based on your previous activity. It is applicable to many industries, for example, look for Big data and AI in banking.
As companies develop more sophisticated Big data strategies and start implementing AI technologies, the customer experience will continue to improve, and each individual buyer will get to enjoy effortless customized service.
Democratization of artificial intelligence
Now, businesses using Big data and AI rely on data scientists who spend hours preparing the data and then coding the different programs. Thanks to that, businesses are able to leverage the power of Big data analytics machine learning, and artificial intelligence. However, there come a lot of automated machine learning tools, thanks to which the world of AI is being opened up to millions of businesses that need easier and less customized solutions.
Automated machine learning creators have designed their artificial intelligence systems to be used by anyone. The hope is that these tools will allow non-technical subject matter experts whose specialized knowledge in certain fields can be used in combination with AI programs to solve a range of different problems. But it’s crystal clear that simple solutions won’t solve big problems of middle-sized businesses or enterprises. If planning a serious project, think of outsourcing it to AI consultancy specialists, not to simple open-source software. Big business challenges require comprehensive analysis and complex solutions customized to the business’s specific needs.
With automated machine learning such as AI mobile apps, anyone with a problem they need to solve, or an idea they want to test, will be able to leverage AI through non-technical friendly interfaces that require no coding skills. Thanks to these automated machine learning tools, you can expect 2022 to witness a proliferation of AI, which will help many companies make breakthroughs in a wide range of business processes, including product design and development. Game developers are already leveraging early automated machine learning tools to enhance their games, such as coin master spins.
Tiny data revolution
The massive amounts of data that companies are collecting and studying are called Big data. Many of the AI and data technologies used to make decisions and come up with insights are also huge. For example, GPT-3, the most advanced model of the human language, features almost 200 billion parameters.
While large-scale data collection and AI programs are necessary and run perfectly fine when working with cloud-based systems and unlimited capacity, they are not applicable to a whole range of other use cases. This is where small data and lightweight AI systems come into play. Small data allows decisions to be made using small amounts of data in a rapid time when capacity and energy expenditure are limiting factors.
Data science companies are currently using small data in self-driving cars that must make decisions instantly without relying on a centralized server. Self-driving cars don’t have the luxury of waiting hours to come up with a decision on whether to swerve to avoid a collision.
Tiny machine learning is designed to compute at rapid speeds while taking up as little space as possible and is able to run on power-limited hardware. As tiny machine learning becomes more pervasive, you can expect to find it featuring in more and more products in 2022. Don’t be surprised if tiny machine learning pops up in wearables, cars, appliances, and different machinery and medical equipment. Thanks to tiny machine learning technology solutions, a lot of products will be more effective and more useful in 2022.
Synergy of AI with the Internet of Things, 5g and Cloud computing
One big Data analytics trend is the fusion of AI with the Internet of things (IoT), cloud computing, and super-fast networks like 5G. Big data is the oil that is going to allow this new industrial revolution to take place. While currently, these digital technologies work separately from each other in the coming years, they will be combined to create a synergistic effect that will not only transform businesses but the world.
In 2022 AI will play a powerful role in helping Internet of things devices to continue to improve and disconnect from their reliance on human intervention. Smart homes will continue to become more advanced, and we will get ever closer to the future where all home chores and tasks can be automated and transferred to AI-powered devices and systems.
We predicted big data analytics and business innovation in the 5G sphere. AI algorithms will optimize the 5G networks through routing traffic, automating environmental controls in cloud data centers, and ensuring the network runs smoothly. 5G is expected to spur a technical leap forward as ultra-fast network speeds will allow for new types of data transfer and use. 2022 will see Big data machine learning and artificial intelligence usher in a new digital revolution as they allow transformative technologies such as 5G, cloud computing, and the Internet of things to operate effectively and in unison.
2022 is an incredibly exciting year for Big data and AI. You can expect to see more and more businesses adopt these emerging technologies and use them to improve all aspects of their business, from logistics to marketing to product development to customer service. By leveraging all of the incredible data available with the computational miracle of AI, expect many companies to play a key role in ushering in the beginning of a digital revolution in 2022.
Thomas Glare has always been interested in computers. Ever since he was a little kid, he would learn about programming languages, even setting up websites for his friends in primary school for fun. He went on to work as a consultant in a leading cybersecurity firm. On a part-time basis, Thomas likes to write articles about everything to do with cybersecurity for various websites and publications.
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