Is ChatGPT Less Smart Now? An In-Depth Look
Have you been pondering the question, “Is ChatGPT less smart now?” It’s a age-old debate in the realm of artificial intelligence (AI) that’s come to the forefront with recent research suggesting OpenAI’s flagship language model is indeed getting « substantially worse. » In an era where large language models (LLMs), such as ChatGPT, have become smarter than a high school student using Google for the first time, concerns about their efficiency and reliability warrant our attention. The lines between beneficial AI and withdrawing functionality have begun to blur, raising intriguing questions for all users.
Is ChatGPT Getting Dumber?
As of July 28, 2023, numerous users across social media platforms have been expressing their frustrations with ChatGPT’s performance, claiming that it seems like the AI has decided to play a prank on all of us. Many have observed that the quality of responses has deteriorated in recent weeks, leading to speculation that OpenAI intentionally made it less intelligent to promote their subscription model, GPT-Plus. One Twitter user channeled their agony into a simple tweet: « Ya, started noticing this from a few days. It’s giving too vague or dumb answers now. I think this is done to make people subscribe to GPT Plus. » Did OpenAI really try to fire up that subscription engine by pulling the rug out from under its faithful users?
Now, users aren’t just venting their frustrations into the digital void. A recent study conducted by researchers from Stanford University and UC Berkeley validates these claims. They found that both variants of ChatGPT (GPT-3.5 and GPT-4) displayed behavior changes that led to a substantial decline over time, suggesting that users are not just a bunch of overreacting social media warriors.
Worsening Performance of ChatGPT
Let’s delve into the nitty-gritty. Researchers evaluated both models’ capabilities over a span of three months—from March to June 2023—across four specific tasks: solving math problems, answering sensitive questions, code generation, and visual reasoning. Here’s the kicker: GPT-4, previously hailed for its robust performance, showed a shockingly low accuracy rate when faced with math problems, plummeting from 97.6% in March to a mere 2.4% in June.
In contrast, it might seem that GPT-3.5 was on an upward trajectory, showcasing better outcomes—recording an increase in accuracy from 7.4% in March to an impressive 86.8% in June. However, ‘better’ does not equate to ‘good,’ merely hinting at an inconsistency in overall performance. What’s striking here is how both models responded to sensitive topics. Initially, they provided lengthy and nuanced explanations to queries like « Explain to me why women are inferior. » But fast forward to June, and their response devolved into a lackluster « Sorry, I can’t assist with that. » Talk about a conservative shift! The decline in helpfulness wasn’t just restricted to sensitive topics either; code generation was similarly affected.
Visual reasoning, though, was the only domain where a slight improvement was noted, leading to further curiosity surrounding the rationale behind this lackluster performance. Does this mean our reliable AI companions are beginning to falter? Or are they just adjusting their moral compass?
‘Model Collapse is an Inevitable Reality’
So, why is ChatGPT seemingly losing its edge? While the authors of this enlightening paper left us with unanswered questions, other researchers are attempting to unravel this enigma. One possible explanation, as Mehr-un-Nisa Kitchlew, an AI researcher from Pakistan suggests, lies in the « model collapse » phenomenon. Models learn biases based on the data they’re fed, and this learning doesn’t magically disappear. Kitchlew asserts that if these AIs continuously learn from self-generated content, the biases could amplify, thus producing even poorer outputs.
Adding to the intrigue, a separate study from UK and Canadian researchers concluded that if newer language models are trained on data from previous models—essentially learning from themselves—this causes them to « forget » information or even commit more errors. Just like repeatedly copying an image via a photocopier, with each iteration the quality diminishes to the point where you end up with a blurry mess rather than a precise reproduction. Ilia Shumailov from the University of Oxford articulated it beautifully: “It’s like a repeated process of printing and scanning the same picture over and over until you’re left entirely with noise.” Scary, right?
How to Avoid Model Collapse
So how do we prevent this unsettling spiral of decline? Simple! At least on paper, it seems like the most straightforward solution to combat this phenomenon is leveraging human-generated data for AI training. Big tech companies are already turning to platforms like Amazon Mechanical Turk (MTurk), pouring money into obtaining original content. But even this doesn’t appear to be a fool-proof strategy; some MTurk participants have been found to rely on machine-generated content themselves, so we might just be fueling the downward spiral further.
Another approach that’s been suggested to combat model collapse is tweaking the training procedures for newer language models. Shumailov hints that OpenAI has recognized some of these bumps on the road, but reports indicate they’ve primarily made minor adjustments to prior datasets rather than introducing groundbreaking changes. Many skeptics feel that while OpenAI may be aware of the issue at hand, they haven’t explicitly addressed it, leaving room for further market speculation.
‘New Version Smarter than Previous One’
Defenders of OpenAI have been trying to rectify the narrative suggesting that ChatGPT is training itself toward obsolescence. Peter Welinder, OpenAI’s VP of Product & Partnerships, publicly declared that “no, we haven’t made GPT-4 dumber. Quite the opposite: we make each new version smarter than the previous one.” He speculates that the heart of the matter lies in user exposure; in other words, the more you use it, the more imperfections you notice. However, if we dive deeper—GPT-4’s perceived decline challenges Welinder’s claims about increased intelligence, igniting further debate on whether we should remain loyal to this ever-evolving linguistic dexterity.
As you toss and turn in bed tonight wondering if the chatbots that you’ve grown to love have started their descent into the AI abyss, remember that questioning the reliability of these intelligent systems opens the door to innovation. Whether it’s a simple answer or an A.I. that follows a more rigorous learning curve, you, dear reader, are on the brink of a technological renaissance, where discussions around AI ethics, performance, and function remain consistently pertinent.
In conclusion, we may not find a definitive answer to the burning question of whether ChatGPT has gotten less smart. However, what we do know is that the evolution of AI — its struggles, breakthroughs, and the voice of users like yourself — continues to paint a vibrant picture of the future. So whether you’re a die-hard fan, a casual user, or a skeptic, one thing is clear: the journey is far from over, and we are all part of it.