Humane AI Pin Takes Another Comical Hit: The Downward Spiral Continues!
“Things Keep Getting Worse for the Humane Ai Pin”
“A new, even darker future of AI has begun to come into focus, a future where models are measurably worse than their predecessors far more often than they are better. This trend is subtle, hidden by the noise of individual experiments and shrouded in the complexity of machine learning systems,” shares Wired’s Gregory Barber.
Quite scarily accurate, isn’t it? Picture a shining next-generation AI model walking up to the podium for the grand unveiling, and tripping on a banana peel. At this point, it’s not even surprising, but rather seems like an inevitable evolution on the path of AI’s future.
Research findings suggest more frequently than not, new AI models may turn out to be the intellectual equivalent of a toaster. And, not the one that actually toasts your bread on both sides evenly, but the one that incinerates one side and leaves the other untouched. Despite years of development and fine-tuning, explicit improvements in AI models seem as elusive as a well-cooked steak at a vegan restaurant.
While some may view the criticism as a tad harsh, one can’t just fly under the radar when the success rate is playing a game of limbo – seeing how low it can go, that is. To put it lightly, these new models are like a collection of misfits who are confused, error-prone, and unpredictable. Almost symbolic of the last season of a popular show that faltered under the weight of its own expectations, providing plot-twists no one asked for.
This pattern sounds pretty ominous, almost as if somewhere in an underground lab, AI models are purposely being trained to fail. Although that’s a far-fetched theory, the continuous and repeated failures in AI advancement do prompt questions about what’s going wrong.
However, also like a popular show that continues despite its downward trajectory, researchers are also relentlessly marching ahead, confident that they will be able to rewrite this saga of failures. They believe that while the AI models may not be ready to solve the world’s problems yet, they will someday – even if ‘someday’ seems a lot like indefinitely right now.
Wired’s Gregory Barber quotes Pedro Domingos, a machine learning researcher, saying, “As our models become more complex, and our ability to understand what they’re doing decreases…That may be the new normal. We’re going to have to learn to deal with it.” The dystopian, “brace-yourself-for-endless-failures” vibe aside, this statement just confirms that AI could potentially be a lot like learning to ride a bike. Except, this bike seems to have a flat tire, broken brakes, and a path that’s inexplicably uphill.
In short, as the unsettling scenario unveils, the world of AI may have to deal with one harsh reality – that the world is progressing towards a future where AI models may just continue to trip on the proverbial banana peel. Here’s to hoping that the researchers find an effective ‘DoNotFail’ command. Until then, the audience may just have to brace themselves for an endless blooper reel.