Artificial intelligence is one of the fastest-growing sectors within the data sciences and information technology space. Coders, engineers and data experts around the world are aiming to acquire some form of technical expertise in the domain of AI and Machine Learning. When answering the question of “What is artificial intelligence?”, it helps to start from its growth potential.
Research from Gartner suggests that the global AI economy can reach $3.9 Trillion by 2022, which is why many firms are hiring AI engineers from this year. Developers from around the world are attending conferences, acquiring certifications and visiting forums to learn more about this technically challenging space.
What is artificial intelligence?
What artificial intelligence essentially is, is a complex focus-area within the greater information technology space, that impacts every major process we use every day. From mobile connectivity to online shopping, AI plays a strong role in every major consumer and business-facing technology protocol.
When asking – what is artificial intelligence, it’s also important to understand it’s roots. The pioneer of the technology, Prof John McCarthy of Stanford, suggests that AI’s goal is to find solutions without confining to biological methods or standard protocols.
Definition of AI
Artificial intelligence leverages the power of cloud computing and machine processing, to deliver faster processing of complex problems. AI is also referred to as machine intelligence and is driven by some of the leading technology companies in the world. It’s designed to resemble human intelligence, across an array of areas such as pattern recognition, forecasting, communication, and planning.
Engineers design code to automatically learn to solve a problem by processing millions of points of approach and finding the best one with minimal intervention. Since these areas of processing are considered more technologically advanced, the domain has been titled as artificial intelligence.
Narrow AI & General AI
There are two types of AI that data scientists should concern themselves with, namely narrow and general AI. When asking – what is artificial intelligence, it’s critical to understand the differences between the two. Narrow AI revolves around chatbot speech recognition, image identification, ID recognition, security code analysis, etc. It has a well-defined scope and is being used by businesses across the world.
General AI is a more overarching form of AI, which is set to fully expand with a few decades from now. General AI can compute new rules of logic and go beyond what we can expect from its computational capabilities.
From a business standpoint, both types of AI systems present unique opportunities across the board. However, narrow AI is a specialized form of AI that focuses on single challenges that need quick answers.
Opportunities within AI
Data from PwC Consulting suggests that AI can directly contribute upwards of $15.7 Trillion to the global economy through the consumer demand and operations efficiencies that it introduces. These machines go beyond standard processing of data and code and focus on finding better ways to find solutions to technically complex problems.
That’s why many of the top firms in the world are investing heavily in the space of artificial intelligence future. Companies like Uber, Facebook, Google, IBM, and Microsoft are using AI every day to enhance their core processes. AI is also being used to design better consumer products, owing to its statistical management prowess in the domain.
Use cases of AI
The possibilities with artificial intelligence are endless, which is why technical engineers should focus on studying under a comprehensive artificial intelligence course. Every industry can be significantly enhanced when artificial intelligence future technologies are introduced.
Many of the top healthcare firms in the world are using AI to process patient data better and analyse EHR (Electronic Health Record) data faster. They’re also helping patients gain access to healthcare much faster than traditional methods.
Financial services firms focus on the computational capabilities of AI to see market trends before they form. They’re able to process hundreds of data points to reach profitable conclusions.
Consumer goods and retail
Consumer goods brands focus on AI to understand consumer demand better. They can then stock up inventory before peak seasons start and promote more popular brands through machine learning.
Research and innovation
AI is leveraged frequently to find new areas of innovative growth within industries. By analysing millions of data sets within the enterprise, companies create new products, solutions and service lines via targeted field projects.
Acquiring technical skills in AI
In India, there is a major demand for adept engineers that have strong capabilities in the domain of AI. This is because artificial intelligence offers significant business opportunities to start-ups, firms and tech giants across geographies. It’s one of the few technology areas that impact your career fundamentally and transforms how recruiters review your profile.
Engineers can also opt for AI resources online, which may provide basic information on the subject area. While there may be no guarantee of success using the information provided, developers can get acquainted with the subject matter via these platforms.
Companies are also urging employees to acquire core skills via artificial intelligence course programs and get hands-on with projects in the domain of AI. They also have in-house supplemental programs through which employees can upskill while working.
Focused AI Certification Programs
A thorough artificial intelligence course allows engineers to work through complex challenges in AI and refine their overall approach within the domain. Many engineers consider artificial intelligence future-ready and see trends in the space before other developers. That’s contributed to the expansion of the domain, and the multi-billion projects that work through AI on a global scale.
Springboard offers a comprehensive AI and Data Science course that can help enhance your skillset, thereby boosting your knowledge base in the area. It’s also uniquely designed to develop your technical prowess in the domain while providing 14 field-tested capstone projects.