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The Gartner Hype Cycle - Is It Playtime or Naptime for Large Language Models?

published - |written by Joe Peterson
Are we mired in the Trough of Disillusionment?

Are we mired in the Trough of Disillusionment?

Gauging the moods and shifts in the world of LLM technologies like GPT, Bard, and LLaMA

Alright, tech enthusiasts! We're about to embark on a thrilling expedition – a deep dive into the Gartner Hype Cycle and its application to the realm of Large Language Models (LLMs), starring our pals GPTBard, and LLaMA, the open-source brainchild of Meta (you might remember them as Facebook). It's time to weigh anchor and figure out if we're snorkeling in the Trough of Disillusionment or mountain climbing up the Slope of Enlightenment with these tech wonders. Ready? Let's hit it! First things first, for those scratching their heads about the Gartner Hype Cycle – imagine a wild rollercoaster ride that starts with a revolutionary tech "Innovation Trigger". Then, it bolts upward to the "Peak of Inflated Expectations", and hurtles down into the dreaded "Trough of Disillusionment". But fear not! After this tumultuous journey, it gradually climbs the "Slope of Enlightenment" to finally reach the calm "Plateau of Productivity".

hype cycle labeled

Quite a journey, right? Now, let's dissect where our LLM friends currently stand on this exciting tech expedition.

Lately, the whispers among tech circles suggest we could be chilling out in the Trough of Disillusionment. Some voices argue that LLMs, like GPT and its fellow travelers, can come across as "somewhat random and even nonsensical" – not exactly flattering, right? It points to a sense of uncertainty about where these models are heading, a possible hint of disillusionment.

Academics too seem to be playing this tune, while suggesting we apply the Gartner Hype Cycle to make sense of the wild ride LLMs are giving us.

Moreover, there's a growing sentiment that the glitter of LLMs is starting to lose its shine. Some suggest we're witnessing a shift of LLM activity away from third-party platforms. Could this be a sign of the honeymoon phase ending, with tech enthusiasts exploring new frontiers? It's possible.

But wait, let's not drop our sails just yet! There's a strong undercurrent arguing that we're not quite ready for a siesta in the trough.

Making waves against the Trough of Disillusionment are robust forecasts predicting an AI-dominant future. One such prediction suggests that AI could be responsible for generating over 10% of all data within the next few years. This reflects not only sustained interest but potentially a surging tide of investment in AI technologies like GPT and LLaMA.

Various reports are lauding the potential of LLMs, while still being realistic about the hype that invariably comes with it. On top of this, the rising tide of low-code tech solutions is challenging traditional tech norms, signaling continued excitement in AI technologies.

So, where are we really? Are we mired in the Trough of Disillusionment with LLM technologies like GPT, Bard, and Meta's LLaMA? Well, like any good mystery, the plot is filled with twists and turns. The Gartner Hype Cycle provides a valuable roadmap, but it's not a GPS pinpointing the exact location.

What's clear is that LLMs are causing ripples in the tech ocean, and it's a phenomenon that can't be ignored. Regardless of whether we're soaking in the trough or already climbing up the slope, the future trajectory of these AI powerhouses promises to be intriguing. So, all aboard, mateys! It's time to sail into the uncharted waters of LLMs. This journey is far from over!

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