Many data scientists think Artificial Intelligence is the “electricity” of the 21st century. It is impossible to think of any technology or solution today that doesn’t have a touch of AI and Machine Learning In phoenix. In fact, AI engineers and data analysts are trained in AI and machine learning courses to find newer solutions and capabilities that could help in building a more robust, secured, and environment friendly society, without any kind of human driven biases and ambiguities.
Let us dive into the AI world, and why we think AI is the universally accepted solution that can solve any challenge arising from different situations.
Business models revolve around AI Machine Learning adoption and services
From IT companies to digital marketing agencies, every organization has AI Machine learning at its core. Whether it’s how Airbnb searches through online properties for rental and vacation homes, or how Netflix delivers a high speed recommendation for your weekend movies – Artificial Intelligence seems to be a “best seller” investment for a majority of the modern business models. But wait?
Is it really worth playing the game where everyone is upbeat about using, offering, or innovating the same kinds of solutions? If the recent trends are anything go with, AI systems not only drive better business results but also prepare these businesses and customers from unforeseeable disruptions and slowdowns happening due to myriad reasons – including the ones arising from a global pandemic such as the COVID-19.
There Are More AI Lovers than Haters
When a technology solution provides more answers than the problems it could create, it is bound to become popular. That’s exactly the driving force that assures AI a place in marketing and sales generation. We are living in an era where every activity has a touch of machine intelligence, powered by what we call the “artificial intelligence software.” It has taken decades of hard work in programming, computing, and analytics to build the current generation of AI and machine learning algorithms. With so much happening in the industry that uses AI and machine learning software, it is worth understanding how the technologies are likely to change further in the coming months and years. Not only should business leaders realize the huge potential of these capabilities but also promote and sponsor talent search activities associated with education imparted through AI and machine learning courses.
AI Software is Embedded in 90% of Software based Devices
In 2018, the global market for Artificial Intelligence software was less than 11 billion US dollars. In 2022, the market has blown up by five times, currently placed to generate more than 50 billion US dollars, and the pace of development continues to turn heads. If we go by the recent reports, the AI software market would be close to 130 billion USD, and these would be showcased in the device based economy by virtue of adoption across different industries. Mobile and biometrics devices would be the biggest adoption centers for these technologies, even as scientists and AI engineers look for new ways to innovate new solutions using Natural Language Processing/ Translation, Computer Vision, and Robotic process automation. By 2025, close to 90 percent of all the handheld and hand operated devices would have AI software in them.
AI, Business and Academics – A Unique Conjecture to Streamline Education
The success recipe for any professional aspiring to be an AI engineer lies in how quickly they are able to differentiate between AI and machine learning and prepare for a better future.
It’s true that many online AI and machine learning researchers are offering their training and computing expertise to open source communities which are promoted as the way forward to build a 100% democratized data science environment. This democratized AI world would secure engineering marvels created using AI from falling into evil hands, where AI capabilities such as encryption and deep fakes are used extensively to grow and spread the tentacles of piracy, spoofing, and forgery. Thanks to the global taskforce acting together in unison to bring ethics and bias free AI development to every business model, it has become critical for academicians to work in sync with product engineers, analysts, data compliance officers, and government and non-government regulators.
By coming together, AI engineers, business leaders, and academicians are creating a strong and wider “absorption center” that ensures everyone maintains a strict framework and definition of Machine Learning and Artificial Intelligence with simple and bias free action driven “AI for everyone.”