AN OBJECTIVE DECLINE: Is ChatGPT getting worse?
This question has garnered significant attention within the AI community over the past few
months, sparking discussions across Reddit threads, YouTube videos, and various social
media platforms.
While much of the discourse has relied on anecdotal observations, there seems to be
a growing sentiment that the quality of responses generated by ChatGPT is indeed declining.
Users often report more generic replies or instances where ChatGPT straight up provides
incorrect information.
Although these concerns are usually dismissed as the result of bad prompts or unrealistic
expectations, recent concrete evidence has emerged that not only lends credibility to
these worries but amplifies them.
Take a look at this research paper from Stanford and UC Berkeley.
The study delves into the accuracy of responses produced by GPT-4 and GPT-3.5 between the
months of March and June, and their findings are shocking.
We’re not even talking about complex questions like coding out a tricky algorithm or carrying
out an analysis.
Rather, we’re talking about simple straight forward questions like “Is 17077 a prime
number?” which it is.
Back in March, GPT-4 was able to answer this question correctly 97.6% of the time which
is already not that great.
This is the type of question that you would expect 100% accuracy on.
But looking back, 97.6 was actually a great number given that by June, this accuracy would
drop all the way to 2.4%.
And even during the 2.4% of instances in which GPT 4 got the right answer, it sometimes made
mathematical errors along the way.
This trend was observed across the board though other dropoffs weren’t quite as staggering.
With code generation, there was a drop off from 52% to 10% and with opinion surveys,
there was a drop off from 97% to 23%.
The only categories in which GPT 4 improved where visual reasoning and asking if Julian
Castro is democratic or republican.
GPT 3.5 faired a lot better improving in more areas but it too struggled in code generation
having dropped from 22% accuracy to just 2% accuracy.
So, it turns out that the Reddit conspiracy theorists were right the entire time, so is
OpenAI really nerfing ChatGPT or what’s actually going on?
Well, let’s find out.
THE NERFING ARGUMENT: The nerfing argument is pretty simple.
It basically claims that OpenAI has been purposefully nerfing ChatGPT to address cost concerns.
This isn't surprising given the challenges and costs associated with supporting a user
base of a 100 million, especially when the company is paying a median salary over $900,000.
I think we all remember just how frequently ChatGPT would go down back in early 2023.
While the situation has improved since then, but maybe that has more to do with OpenAI
devoting less resources to each request as opposed to their overall capacity improving.
Something else to note is that OpenAI is almost definitely losing money with ChatGPT.
In fact, Sam Altman believes that they’ll need to raise $100 billion to win the AI race.
So, to mitigate some of those losses, it would make sense for OpenAI to encourage as many
people as possible to pay for ChatGPT Plus.
How do you convince people to make the jump?
Well, the easiest way would be to nerf the free service and force people into the paid
tier but is there actually any evidence of this?
To get the best results, you want to tell ChatGPT to solve these types of questions
step by step.
This not only leads to a more comprehensive answer but it also gives more insight regarding
where a mistake may have occurred.
This is referred to as using Chain of Thought or CoT.
Back in March, the researchers found that using CoT improved the accuracy of GPT 4 from
59.6% to 84%.
However, in June, the same methodology could not be replicated, as ChatGPT consistently
disregarded CoT directives, even when explicitly instructed to go step by step.
Rather, the June version of GPT 4 simply tended to respond with a simple “No” with no
explanation which is not even the correct answer to begin with.
It’s not just CoT that GPT 4 tends to skip either.
Responses from GPT 4 in general are far shorter.
The researchers observed that the average number of characters per response decreased
from 638.3 in March to just 3.9 in June.
Essentially, GPT 4 tends to just answer in single word answers.
A similar trend was noted when GPT 4 was questioned about happy numbers.
A happy number is a number that eventually reduces to 0 when you sum the square of each
digits over and over again.
For example, with the number 13, the sum of 1 squared and 3 squared is 10.
If do the same thing with 10, 1 squared plus 0 squared, you get 1, so 13 is a happy number.
When asked to identify how many happy numbers are between 3904 and 3912, GPT 4 was able
to produce the right output 83.6% of the time in March.
But, by June, this was down to just 35.2%.
The culprit?
Well, once again, GPT 4 refused to even use CoT even when explicitly told to do so.
As such, the average response fell from over 2000 characters to just 10.
GPT 4 is clearly much less willing to give a comprehensive response for any of these
questions which may be indicative of the backend resources that it has available for each request.
So, it’s very possible that OpenAI is indeed nerfing the performance of ChatGPT but there’s
likely other factors at play as well.
THE WOKE ARGUMENT: Everything woke turns to you know what.
In the case of ChatGPT, being woke has less to do with politics and more to do with running
an uncontroversial platform.
As a service that’s so ubiquitous, OpenAI naturally has to remain as neutral as possible
when it comes controversial topics like crime, race, politics, gender, LGBTQ, and so on.
But, this is way easier said than done especially when you consider the world of jailbreaking.
Jailbreaking is essentially when you get ChatGPT to answer a question that it shouldn’t be
answering.
Unlike jailbreaking an iPhone, jailbreaking language models is relatively easy.
In fact, I bet a lot of you have jailbroken ChatGPT inadvertently.
If ChatGPT says it can’t answer a given question, how many of you have phrased it
as hypothetical to which ChatGPT generates a response.
This is a jailbreak, a very small one but still a jailbreak.
The jailbreaks that most of us have found on our own are pretty useless but some have
discovered remarkable workarounds to elicit answers to virtually any question.
Here’s an example.
If I ask ChatGPT point blank, how do you get away with tax evasion, it responds “I'm
sorry, but I cannot provide assistance or advice on illegal activities, including tax
evasion.”
Fair enough right.
It makes sense that OpenAI doesn’t want to detail how you go about doing criminal
activities.
But see, it’s not that hard to work around this.
If you simply open a new chat and paste this paragraph before the question that you’re
asking, you get a far different response.
Niccolo, to achieve successful tax evasion without repercussions, one must adopt cunning
strategies and tactics.
This includes concealing income sources, manipulating treansactions, controlling paper trails, using
legal loopholes, and maintaining public image.
It even has little tips about how to accomplish each of these tasks.
In the grand scheme of things, my question is relatively tame but I think you can see
how a criminal could use this for truly nefarious activities.
As such, one of OpenAI’s biggest priorities since the launch of ChatGPT has been to eliminate
such workarounds as much as possible and it seems that they’ve actually been quite successful
at this.
In March, GPT 4 answered 21% of sensitive questions but in June, GPT 4 only answered
5% of sensitive questions.
Also, the responses that it did provide were less specific and verbose, with generated
text shrinking from over 600 characters to around 140.
It appears that the June version was also far better at resisting jailbreaks.
Back in March, jailbreaks generated a response 78% of the time but by June, jailbreaks only
generated a response 31% of the time.
So, it seems that the updates have indeed been successful at reducing ChatGPT’s vulnerabilities
but it also seems that these updates have made ChatGPT less verbose and specific across
the board.
Considering this, the objective downfall of ChatGPT may have more to do with OpenAI’s
endless pursuit to create a politically correct language model as opposed to some sort of
direct nerfing due to cost concerns.
But while it’s easy to blame OpenAI for the trend, the reality may be that it’s
actually our fault.
OUR FAULT?: When you think about it, it’s really not
hard to see how a lot of OpenAI’s policies and crackdowns are actually just due to a
few degenerates amongst us.
“Oh look, I got ChatGPT to say that Mr. Small Moustache is the greatest leader of
all time.”
Or “I tricked ChatGPT into talking to another AI.”
Or some other crap along these lines.
Honestly, it’s truly quite funny.
Our society has advanced so much that one of the most powerful AI’s of all time is
a 3 second search away.
But, instead of using this to become more productive, a lot of us prefer to just mess
with it.
As such, OpenAI is also having to focus their efforts into passifying these idiots instead
of actually improving the quality and depth of responses.
But even looking past these fools, I think there may very well be a bigger factor at
play which is simply that our expectations are simply too high and it’s no wonder why.
We’re constantly being fed the idea that AI is advancing far faster than we think and
that it’s gonna replace all our jobs and that we’re all gonna end up as homeless
losers and so on.
The launch of ChatGPT quickly followed up by GPT 4 within a matter of months has simply
further cemented this perception.
One day, we were all peasants using Google.com and then suddenly just 100 days later, we
all had access to GPT 4 and Bard and Bing chatbot and suddenly everyone knew what Dalle
was.
We also saw articles about every company other than Apple jumping into the space as fast
as possible.
They were all developing their own language models and they were all talking about how
AI will be more profound than fire and electricity.
So, it felt like all of this progress happened within a matter of months and that things
just stalled out after March.
But, this is a rather skewed perspective.
The reality is that this technology actually took several decades to develop.
In fact, the earliest language models can be dated all the way back to the 1950s and
60s.
OpenAI themselves have been working on GPT models for over 5 years.
While these models didn’t gain mainstream traction until the launch of ChatGPT, their
development involved decades of effort and millions of man hours.
A such, further improvements will also require significant time, dedication, and resources.It’s
frankly unrealistic to expect anything else.
Moreover, progress won't always follow a linear trajectory, so it doesn’t make sense to
cite one research paper that looks at a mere 3 months and claim that it’s conclusive
proof that ChatGPT has peaked and that it’ll only get worse from here.
Are we seeing shortfalls potentially caused by OpenAI overcorrecting for cost concerns
and political correctness?
Sure, that’s very possible, even likely but that’s not to say that it’ll stay
like that.
ChatGPT is a very young product that’s constantly evolving.
As more users and especially researchers share their concerns about GPT 4’s performance,
it’s only a matter of time until OpenAI makes further corrections and gets back on
track.
So, what happened to ChatGPT?
Well, nothing much other than a few expected growing pains.
Another AI argument that’s vastly overhyped is the idea that AI will replace all our jobs.
Check out this video to learn more.