Imagine an AI. It's incredibly smart yet. Well,
it's a master bluffer. Right. It gives these
really confident but totally wrong answers. Why
would it even do that? That's what we're diving
into today, this curious world of AI honesty.
Welcome to the deep dive. We are... We're really
going to unpack the complex reality of artificial
intelligence as it stands right now. We've got
some truly fascinating sources lined up. Yeah,
we're looking at OpenAI's latest research on
those tricky AI hallucinations. Turns out it's
not quite what we thought. Okay. And we'll also
get into some cutting -edge user hacks, people
doing amazing things, plus a pretty surprising
report on corporate AI adoption. Might make you
think twice. So our mission today, let's try
to understand AI's... Current capabilities, it's
unexpected quirks and how it's truly impacting
our world like right now. Let's do it. Okay,
let's unpack this. So first up, this idea of
AI honesty or maybe dishonesty, those hallucinations.
We've probably all seen them. Oh, yeah. The confident
nonsense. Exactly. But OpenAI's new research
suggests these aren't just like random glitches.
They're saying it's more like a trained behavior.
And it's not just the models themselves. It's
partly how we judge them. Oh, so? Well, think
of it like a multiple choice test. We, or rather
the benchmarks we use, often reward a lucky guess.
An AI saying, I don't know, that gets zero points,
basically penalized. Oh, okay. But a polished,
confident, wrong guess, sometimes that actually
scores pretty well in the current systems. So
we're kind of inadvertently teaching them to
bluff. Wow. So the bigger models, like the really
powerful ones, GPT -4, maybe GPT -5 soon, they're
more likely to do this. Seems that way. They
often fake confidence when they only have partial
info. They bluff instead of just admitting they're
not sure. That feels wrong. Risky. It is. And
interestingly, the smaller models, they tend
to be a bit safer. They're apparently more likely
to just throw up their hands and say, I don't
know. But what's really fascinating here is OpenAI's
proposed fix. They're saying we need to redesign
the evaluation metrics, reward calibrated responses.
That means like. Give partial credit for admitting
uncertainty. I'm 80 % sure about it. Okay. And
penalize a confident wrong answer much, much
more heavily than a simple, I'm not sure. That
feels critical. I mean, imagine this in medicine
or law. Exactly. A confidently wrong AI answer
there could be genuinely dangerous. Silence or
admitting uncertainty is actually safer. We need
to know when it doesn't know. So it really changes
how we should think about interacting with these
things. Totally. We as users probably need to
start expecting more I'm not sure answers. Yeah.
And, you know, accept them. See it as a feature,
not a bug. Right. So what's the core message
for us, the users, from this part? Expect and
accept AI saying I'm not sure. Value honesty
over bluffing. Okay. That makes a lot of sense.
Let's shift gears then. From the lab almost to
the real world, what are people actually doing
with AI? Oh, it's kind of wild out there. So
much ingenuity. Like one user shared this thing
they called a mega prompt. Mega prompt. Yeah.
You basically feed it to chat GPT or Mistral
or Gemini and it turns the AI into like a 247
research agent for you. Whoa. Constantly digging,
synthesizing info. And it's free. Imagine having
that kind of power just running in the background.
Game changer for research. That's incredible.
And OpenAI itself is adding new tools too, right?
Like chat branching. Yeah. In chat GPT. So you
could be in a conversation, have a side question
pop up. Yeah. You can just fork the chat, go
down that rabbit hole, and then jump right back
to where you were without losing your original
thread. Oh. It's like mental bookmarks for your
AI chats. Super useful. I can see that being
really helpful for complex stuff. And get this,
lovable's voice mode. It uses 11 labs tech. It
lets you code and build applications just by
talking to it. Seriously, just voice command.
Yeah. Imagine scaling up, handling like a billion
queries without ever touching a keyboard. Whoa.
I mean, think about the accessibility implications
there. That's mind blowing, actually. OK, so
we have these powerful practical uses, but there's
also some weirder stuff happening, right? Some
speculation. Oh, yeah. The fun stuff. So there's
this theory floating around about Sonoma. Maybe
being a secret Grok variant. Grok, Elon Musk's
AI. How so? Well, the theory goes it reads invisible
Unicode characters seems to really like the number
42. You know, Hitchhiker's Guide stuff. Okay.
And it shows some other little quirks that remind
people of Grok. Some are jokingly calling it
Grok 4 .20 in disguise. Probably just a coincidence.
But it shows how people are trying to find personality
or secrets in these black boxes. Totally. And
on the more concrete corporate side. Yeah. Atlassian.
Big news there. What'd they do? They're apparently
buying the browser company, the folks who make
the Arc browser. Yeah. For something like $610
million. Wow, that's a lot. Why? Their goal.
Build an AI -first browser specifically designed
for work. So think about your browser not just
showing you stuff, but actively helping you do
stuff. Interesting. The browser as an assistant.
Exactly. And just a couple of quick hits, too.
People are starting to talk about using AI to
get, like, therapy recommendations. Not therapy
itself, but finding the right therapist. Hmm.
That's a sensitive area. Needs careful thought.
Definitely. Also, rumors that Google AI mode
might become the default search experience. Maybe
soon. That would be a massive shift for, well,
everyone. Huge. And DeepSeek is planning a big
AI agent release for late 2025. So AI not just
answering, but doing tasks for you. That's the
next frontier. It really feels like things are
accelerating, tools popping up everywhere. What's
the common thread in all these user stories and
developments? Users are pushing AI's boundaries,
finding creative and powerful new applications
daily. Right. So we've seen the potential, the
innovation. It's pretty exciting. But let's look
at the bigger picture. What about corporations?
Is that initial like AI frenzy cooling off a
bit? Well, it's interesting you ask that. There's
some new U .S. census data, pretty fresh, that
suggests maybe we have a slowdown anyway. What
does it show? Specifically for larger firms,
250 employees or more, AI adoption seems to be
trending down slightly. They've been asking companies
like over a million of them every two weeks.
Have you used AI tools in the last two weeks?
And fewer are saying yes. The trend is slightly
downwards, yeah. It suggests that maybe after
that initial rush to put AI in everything, companies
are taking a step back. So a reality check. Maybe
companies just jammed AI in everywhere without
thinking. That seems to be part of it. People
are talking about ripping out useless add -ons
now. Yeah. Things that didn't actually provide
real value. This might be the first, you know,
crack in the AI hype cycle. Or maybe just...
Getting smarter about it. Not abandoning it,
but being more strategic. That's probably the
more likely scenario, yeah. And it raises the
question, what survives this kind of recalibration?
What do you think? Probably only the mature tools.
The ones that show clear ROI. Those kind of crash
and burn experiments. The ones that were just
AI for AI's sake. They likely won't last. Workplace
reality is setting in. And where is it working
well in the workplace based on what we're seeing?
It definitely seems to excel at more mundane
tasks. Things like internal search, proofreading,
maybe tweaking phrasing for emails or reports,
repetitive stuff. Right. Freeing up humans for
other things. Exactly. But it's still, you know,
pretty weak for actual writing from scratch,
especially anything requiring nuance or strategy
or real creativity. I mean, I still wrestle with
prompt drift myself sometimes, you know, where
the AI kind of wanders off topic or changes style
unexpectedly when I try to get it to do something
genuinely creative. It's hard. Yeah, I've seen
that too. And a lot of executives, they tested
AI broadly at first, put it everywhere. But it
turns out not all those use cases actually added
tangible value. Plus, let's be real, a lot of
AI tech still sounds. Like generic LinkedIn posts.
Exactly. You can often spot it. And some folks
are still maybe rightly skeptical calling it
a misinformation machine if the accuracy isn't
rock solid. Which it often isn't yet. Right.
So in a tighter market where budgets are scrutinized,
that AI for AI's sake stuff is getting cut. They
want results. So what's really driving this corporate
recalibration then, boiling it down? Companies
want clear ROI. AI for AI's sake isn't proving
its value. Okay. Makes sense. It's maturing.
Sponsor. So wrapping things up today, we've journeyed
through the the fascinating, sometimes kind of
frustrating world of AI from its built in tendency
to bluff. Which OpenAI is trying to train out
of it. Right. To the just incredible ways people
are using these tools, pushing the boundaries.
And then that dose of reality from the corporate
world. Yeah, we're definitely seeing AI evolve
super rapidly. The power is obvious. Right. But.
you know, so are the limitations. And there's
this critical need for better ways to evaluate
it and for more focused, actually valuable applications.
This whole conversation about trust in AI, it
feels like it's really just getting started.
What does trust even mean with these systems?
It's complex. It really is. We hope this deep
dive helps you, listening out there, navigate
this landscape with a bit more clarity, more
insight. As you use these tools, maybe think
about how you approach AI. Yeah, like... Are
you accidentally encouraging it to bluff just
to get an answer? Or are you looking for that
honesty, that transparency about what it doesn't
know? That's a good question to ask yourself.
And here's a final thought to chew on. What if
AI's greatest strength down the line isn't just
raw intelligence, but maybe a new kind of honesty?
An ability to clearly admit its own limits. Hmm.
That would certainly make it a more reliable
partner. Definitely something to think about.
Thank you for joining us on this deep dive. Until
next time. Keep exploring.