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Industry Insights

6 Tech Acronyms You Need to Know: AI and ML and NLP, Oh My!

By Akhila Sriram on October 27, 2021

When it comes to modern life, everything has been turned into acronyms and initialisms. GFI, LOL, OMG, and more litter our everyday speech and writing. But the most acronymized, and rightfully so, is the ever-evolving field of technology. To best capture all of our technology ins easier to manage statements, most tech and digital phrases have become very interchangeable and overused acronyms and initialisms. AI, ML, and NLP are victims of this and have become even more confusing as they seep into every aspect of the digital world, from technology that controls computers and predictively models, to even being used in everyday consumer digital interactions, like chatbots, automated text and email sending, and social media interactions.

We at OSG are guilty of using AI and ML in every other breath, to capture the power behind our technology solutions and communicate that to our audience. But we know not everyone in our audience knows the implications of all of this tech jargon. So this blog is to help break down the current innovations in technology and the future trends coming down the pipeline. And I apologize to my fellow literature nerds out there, but I’m going to use acronym from here on out, even for the initialisms, just for ease of reading.

Tech Acronym #1: AI – Artificial Intelligence

The stuff that sci-fi movie nightmares are based on, artificial intelligence had long been the futuristic technology bogeyman. Technology taking over the world and enslaving or killing off the human population was usually powered by this ambiguous “artificial intelligence.” But as science fiction and current technologies have shown, artificial intelligence is a technology that can be used for good just as easily as becoming world-dominating robots.

According to Britannica, artificial intelligence is “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” This technology has been instrumental in the evolution of computing capabilities, going from computers who need explicit programs made for each action taken, to computers that can process and understand a request and complete it, based on its understanding of the problem at hand. Starting with Alan Turing’s famous thought exercise, asking a computer whether it is a computer, to modern-day technology, when IBM had a Jeopardy!-ready robot that could accurately handle the backwards trivia structure of the famous TV show, artificial intelligence has been changing the world.

The future for AI is difficult to predict, as the lines now between human and machine intelligence are getting more and more difficult to parse, but what science shows is that the more than technology grows, the more than we all can learn and grow as a result.

Tech Acronym #2: ML – Machine Learning

Machine learning is exactly what it sounds like: algorithms that are able to learn and build predictive models based on massive data sets and the trends that lie within that data. Machine learning is a subset of the technology used for artificial intelligence, as the technology used in ML are the machines that can act on their own and learn from their actions to improve at those tasks. Machine learning can look like algorithms that can predict human behavior, like search engines that try to guess the searcher’s need, or recommendation engines behind streaming platforms. Machine learning is also sorting and tagging data and building models based on huge similar datasets, like libraries of images, customer databases, and healthcare research data. By building models that can grow and learn when new data is added, the algorithms can improve themselves without the need for human intervention or training.

Machine learning programs are slowly becoming as ubiquitous as the applications of artificial intelligence, as the Internet of Things and all collections of data get steadily larger and harder to digest. When it comes to all healthcare data for a hospital, machine learning is better able to help physicians understand the health risks that their patients are facing. Containing all of that data and analyzing it with just our human brains has slowly gotten more and more impossible, as the necessary information and knowledge has exponentially increased. Humans are usually the ones making the decisions based on what an ML algorithm suggests, but just that technology has helped us understand our own choices better, as well as making all information a little more accessible and available.

Tech Acronym #3: NLP – Natural Language Processing

Natural language processing goes hand-in-hand with AI and ML, as it takes powerful technology to power truly effective NLP programs. Human communication, in any language, is full of idiosyncrasies specific to each language, like tongue-twisters, slang, vernacular, and idioms that either don’t translate to other languages effectively, or don’t translate between cultures entirely. To best breakdown how language is used in communication, for computers to understand how humans speak and write, programs needed to be created to parse it.

Natural language gives computers the understanding power that only humans had until now, the power to understand text and spoken words. And this technology is hugely valuable for all sorts of businesses: stores that get feedback in text form from its customers, physicians in need of writing notes in an electronic health record (EHR) and that EHR then understanding any actions it needs to take based on the dictation, and just everyday spell-check and autocomplete that helps everyone write their texts faster and faster. By understanding the language, technology is able to help us more and understand our needs in order to make our lives a little more convenient and efficient.

Tech Acronyms #3-6: SaaS, PaaS, and IaaS

When it comes to technology packages, the most commonly used acronyms are SaaS, PaaS, and IaaS, which denote different levels and sizes of technology coming bundled together for businesses to use. These aren’t the only ones used for this purpose, as you might run into Computing-as-a-Service, or CaaS, but these three are the most common.

SaaS – Software-as-a-Service

Software-as-a-Service, such as our feedback platform PxidaX, is a third-party vendor, hosted and handled by that vendor, for use by businesses. Our feedback platform is hosted on our cloud, and runs directly in the web browser for small and medium businesses (SMBs) to gather their customer and employee feedback for visualizing and taking action on that data. SaaS products, as they’re hosted on the cloud and not by the business itself, don’t require IT staff for handling and managing, and don’t require any hardware for the business to acquire to use it for the business.

Other examples of common SaaS products include cloud-based programs like the Google Workspace suite, CRMs like Salesforce or HubSpot, and video/online call platforms like Webex and Zoom. They’re usually used based on a contract or free basis, and come as easy-to-implement and launch software for business to integrate into their current processes. Since they’re accessible from the Internet, they don’t require any extra computing power for the business, other than reliable Internet connections.

PaaS – Platform or Product-as-a-Service

Platform-as-a-Service are softwares that serve as foundations for app development and production. These platforms are scalable, highly available, and, just like SaaS products, are delivered via the Internet. This means PaaS products are managed and maintained by third-party vendors and contracted or engaged from them for use via businesses, which means they can be used with or without implementing extra hardware or computing power. When it comes to our business, our PaaS products include OSG o360, PatientX360, and RetailX360, which are app-based data analysis platforms for businesses to digest and understand their structured and unstructured customer data. These platforms are hosted on our servers, but are available for customer use via the Internet, so they can access their customer data, predictive models, and dashboard visualizations at any time.

IaaS – Infrastructure-as-a-Service

Infrastructure-as-a-Service is the largest and most comprehensive technology packages of the three, encompassing everything that a business needs in terms of technology and computing. IaaS looks like the delivery of all necessary cloud-computing infrastructure for app development, hosting, and deployment, including servers, networking and storage capabilities. The whole data center for a business is hosted on an IaaS product, like with AWS, Microsoft Azure, and the Google Compute Engine. By handling all computing needs, IaaS serves as a foundation for technology company to build all of its functionality on top of.

The Best Acronym for Understanding the Power of Business Technology: OSG

We use the terms AI, ML, and NLP to describe our technology because that’s exactly how we power our data analytics. By taking huge sets of customer data and breaking it down to the trends and key decision-making factors for our clients’ customers, we’re able to provide actionable insights for our clients. Business decisions are difficult to make without the right reasoning and foundational data to back it up, so we make that easier by providing the insights our clients need to take action and improve their businesses. Learn how our technology can help your business today by contacting our experts!