Fine Tuning A GPT Model
When we look back on 2024 regarding technology advancements and changes, there is likely one prevalent topic that will continue to pop up: AI. This year has been defined--and perhaps even...
As a self-proclaimed futurist, I’d much rather focus my attention on what’s to come versus dwelling on the past. Not surprisingly, all roads start (and end) with artificial intelligence (AI), and the challengers that will emerge in both the obvious and not-so-obvious arenas will battle for AI supremacy this year.
Having grown up as a nerd in the ’90s, I remember the endless battles between Intel and its rivals—and other nerds bragging about their shiny new Pentium-something processor they’d overclocked to the enth gigahertz.
Well, the chip battles are back, and this time, it’s NVIDIA standing to be challenged, as their GPUs are the engines that power nearly every generative AI service anyone’s talking about.
While hyperscalers like Microsoft have been quick to form strategic partnerships with NVIDIA to ensure they can keep building Azure data centers faster than school children can pump out ChatGPT-produced book reports, even they realize the risk of overreliance on a single manufacturer and have gone so far as to get into the chip game themselves. Expect several other rivals from both the established players and market disruptors to vie for a slice of this trillion-dollar market.
Search engines had to have issued a five-alarm emergency internally when ChatGPT hit the scene in late 2022, and the anxiety only heightened last year as their worst fears began to materialize. Who needs to waste time “Googling” something and poking through a bunch of hyperlinks like it’s 1999 when you can simply open an app, ask it your question like you would a human and have it do the grunt work for you?
While it may be anecdotal, I find myself using traditional search about half as much as I used to, which is a massive problem for Google (which still relies heavily on ad revenue generated via its traditional search functions).
Expect the major players in gen-AI to continue to siphon lucrative search traffic away from Alphabet’s golden goose. Entrants focused exclusively on replacing search may gain traction as well, because who doesn’t want to be the next Google?
Just as quickly as the internet became a useful tool for millions globally, imaginative entrepreneurs and corporate fat cats alike started finding ways to turn bytes into Benjamins.
As the internet has evolved from the early days of chat rooms and dancing hamsters to serving as the backbone of every business, monetization schemes have come and gone. The shift toward leveraging AI to consume, analyze and synthesize content from all corners of the web will require businesses that rely on revenue from traditional advertising, gated content and affiliate marketing to re-think how they convert their click-bait into cash.
While we’ve already seen early signs that big gen-AI players may be willing to pay a few marquee outlets for permission to scrape, train on or reference premium content, there’s still a ton of space for creative capitalists to introduce other methods of converting prose to profits.
Ultimately, consumers will decide with their clicks (or AI convos) whose content is worth paying for and what it’s worth to them. A gap exists for challengers to compete with traditional ad networks and paywall aggregators with disruptive new methods.
One of the not-nearly-discussed-enough topics of the last year is the impact AI will have on every side of the ever-escalating cyber war. While malicious actors are already leveraging both commercial and open-source gen-AI models to do all sorts of nefarious things, from drafting more convincing phishing emails to writing millions of lines of malicious code, cyber professionals are adding equally powerful weapons to their defenses.
With AI-powered capabilities that replace manual threat hunting with synthesizing thousands of events down to the few that actually matter, one of the biggest issues security teams suffer from is being directly addressed by AI—more time and less noise. You can bet your bitcoin that the challengers on both sides of this battle will get even more clever in 2024, and the multi-billion-dollar question is which side moves faster to leverage AI as their weapon of choice. Oh, and we’re in an election year, so don’t expect the (misinformation) campaigns to be left out of this skirmish.
While last year was chock full of marketer-led videos and landing pages explaining how AI was fundamentally changing the way we work, the reality for most tech leaders was they were just trying to figure out how to respond to questions from other execs and board members about their org’s AI strategy. And it really wasn’t their fault. Just about none of them had any additional budget, resources, or practical guidance on what the business expected.
Tools that promised practical business value from gen-AI were mostly out of reach, leaving most IT departments trapped in AI purgatory, where business hopes and dreams went to die.
This year, expect the rubber to meet the road, with many organizations having both a budget for AI and accessible tools like Copilot available for implementation, making 2024 the year where AI goes from a marketing hype machine to a competitive necessity.
Last year was full of reasons to stall on AI strategy; however, this year will prove that smart leaders will leapfrog their slower-to-move competitors by making AI accessible to users in meaningful ways.
If 2023 was the year of talking about AI, 2024 promises to be the year where the doers get to work, with challengers emerging from every corner to stake their claim to the next big wave in how business gets done. Expect major upsets in everything from physical infrastructure to geopolitics to productivity tools. So take a seat and grab your popcorn, because it’s going to be more nail-biting than Elon versus Zuckerburg.
This article was originally published on Forbes.
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