By BRAD CARLSON //
We can’t go long without seeing or hearing something about artificial intelligence these days.
It burst onto the public scene with the launch of OpenAI’s ChatGPT about two years ago – for most, a first exposure to AI. Since then, we’ve all been exposed, sometimes without knowing it.
Those who’ve studied computer science or engineering, however, have known about AI for decades. The term was first used in 1955 by computer scientist John McCarthy in a proposal for a Dartmouth College summer research project; elements of AI have been part of computer science and engineering curricula since the 1960s.
ChatGPT is generative AI, meaning it can create original content by leveraging the plethora of data (a.k.a. “Big Data”) amassed on the Internet since its inception.
Big Data is a term I first heard when working at Symbol Technologies (now Zebra Technologies) in the late 1990s The barcode technologies that Symbol invented were a significant enabler for the collection of data, with billions of point-of-sale transactions occurring daily; all this info was collected by those scanners, providing, among other things, an intense study in consumer habits.
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By the early 2000s, Symbol was a leader of researching Big Data in the retail space, with an eye on improving efficiency and profitability. This put the company at the forefront of many advanced technologies, with CEO Jerome Swartz leading R&D team to develop AI technologies that took decades to refine and deploy.
At the same time, information collected in life sciences and other fields began feeding the lakes of Big Data around the world. Over the past two years, we have seen the culmination of efforts to leverage all this data, helping global industries refine their approach and helping us all be more efficient with routine tasks.
Hundreds of AI tools have been launched since ChatGPT emerged, generating essays, podcasts, images, even software code. It’s not a precise science and it’s prone to making errors, which limits AI’s application to fields where such errors can be tolerated or fixed – but generative AI systems are fascinating and increasingly useful.
As the public-facing use of AI proliferates, it’s important to recognize that AI systems have been in our world for decades, adding value to our complicated lives. These are the AI systems that I studied in college, when artificial intelligence was known as “machine learning.”
Machine learning has been studied heavily since the invention of the digital computer. It’s different but closely related to today’s gen-AI tools, based on a detailed understanding of a certain problem and the creation of a model or algorithm that makes complex, human-like decisions to address it. Machine-learning algorithms are more constrained than gen-AI, and produce more accurate and predictable results.
Raising the bar: Barcode scanners created by Symbol Technologies (now Zebra Technologies) have played a big role in the amassing of Big Data.
Such models are more common today than most people think. They’re found in automobiles, appliances and other widely used products. The next time you enable your adaptive cruise control on the highway, know that there is a machine-learning algorithm – taught to interpret imaging data, distance, velocity, etc. – running in your car’s computer.
Artificial intelligence research and education are alive and well in our own backyard. Stony Brook University recently launched a new Department of New Technology, AI and Society, along with a new AI Innovation Institute. With more than $20 million in research funding, the institute focuses its AI research on areas such as neuroscience, cancer, energy and psychology.
Long Island University, meanwhile, offers undergraduate and graduate degrees in AI, and Farmingdale State College has a new bachelor’s degree program focused on this evolving science.
Brookhaven National Laboratory, Northwell Health’s Feinstein Institutes for Medical Research and Cold Spring Habor Laboratory all have active AI research programs.
Long Island is becoming a hub for AI research, with a distinct focus on healthcare, biotechnology, advanced manufacturing and ethics. The rapid advancement of AI technology will not slow down – fortunately, Long Island is well positioned to benefit from this progress.
Brad Carlson is vice president of technology and business development at Hauppauge-based Intelligent Product Solutions.
