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According to this academic journal, the “year of AI” was declared 43 years ago, back in 1980. AI has been with us for a very long time. Decades ago, an academic thesis on AI ethics was completed, leading to an article written in 1986 for Computer Design Magazine entitled “Artificial Intelligence as a Systems Component”. Two AI-based products were also introduced for the Mac in 1988. Also: AI in 2023: A year of breakthroughs that left no human thing unchangedAnd even then, AI was more than 30 years old. It’s safe to say AI has been around for at least 68 years. We can trace some of the earliest AI activities to Professor John McCarthy of Stanford, MIT, and Dartmouth, who founded SAIL, the Stanford AI Lab in 1955 and invented LISP in 1958. So, by 2023, AI has been around for at least 68 years. And that didn’t count speculative fiction, as Isaac Asimov started to contemplate AI ethics 25 years earlier, in 1940. And yet, it’s hard to argue against calling 2023 the Year of AI. It’s been quite a year. What changed?
AI has been used for a very long time. Whether it’s in expert systems, diagnostic tools, video games, navigation systems, or many other applications, AI has been productively utilized for decades. But it’s never been put to use quite like it has this year. This is the year that true generative AI has come into its own. Up until now, most of the training for AIs has been supervised. By contrast, we’re now in a time of large language models (LLMs), where the pre-training is unsupervised. This process allows the AI to produce astonishingly varied material with a breadth that was impossible before.
This year, true generative AI has come into its own. Significant advancements in processor performance and storage have also contributed to this development. Back in 1986, a hard drive that held 470 megabytes was priced at around $10,000 (roughly $27K today). Today, you can pick up a 20TB internal enterprise NAS hard drive from Amazon for $279. The combination of the cloud, broadband, faster processors, and larger RAM pools make the processing power of LLMs possible.
Generative AI is amazing and has been utilized for diverse tasks this year. But it has a severe accuracy problem, and it has also been tainted by human-produced content, which has led to issues of bias and discrimination. It is also expected to result in job losses as it becomes more sophisticated and companies replace white-collar workers with AI services, starting with entry-level positions. This trend is a cause for concern and warrants further discussion.