Speaker 1: Hello, and welcome back to Thrilling Threads. It is February seventh,
twenty twenty six, and I want you to just take
a second right now wherever you are, and look at
your phone, Look at the screen. Now, look at the
room you're in. Maybe you're on a commute, maybe you're
in a hun office. For the last I don't know,
three or four years we've been talking about artificial intelligence.
Is this thing that is coming like a weather forecast,
you know, predicting a hurricane a week out. We were
always saying when AI does this or if AI does that.
Speaker 2: It was always speculative. It was always about the potential exactly.
Speaker 1: But looking at the date today, I mean we're in
early twenty twenty six. We aren't looking at a crystal
ball anymore. This isn't some distant future. We are living
in the shift. The storm made landfall. The landscape is flooded,
and we're all just learning how to swim in it. Now.
Speaker 2: That is such a good way to put it. That's
the feeling, isn't it. You know? I was looking at
the primary research report we're using for today's show, this
massive analysis of the twenty twenty six landscape and The
thing that really struck me wasn't the tech itself. It
was the normalization, the fact that it's just everywhere. It's
the fact that this year AI is projected to touch
eighty percent of all work.
Speaker 1: Eighty percent. Just pause on that for a second. That's
not just you know, tech bros.
Speaker 2: In Silicon Valley, No, not anymore.
Speaker 1: It's not just coders. That's the barista, the barrister, the
truck driver, the middle school teacher.
Speaker 2: It's ubiquitous and the global market. I mean, it's pushing
past four hundred billion dollars. That figure alone backs it
all up.
Speaker 1: Wow.
Speaker 2: But we need to be really careful with that number.
It's not just money being spent on like chatbot subscriptions.
It represents a fundamental restructuring of the economy. We're seeing
huge capital expenditure moving from hiring people to renting compute.
Speaker 1: From people to compute.
Speaker 2: That is the new normal everyone was talking about. But
it looks, it looks very different than what everyone predicted
back in say, twenty twenty three.
Speaker 1: It really does. Yeah, and that is exactly why we're
here today. We have this comprehensive report. It's going to
be our roadmap for this whole compnversation, and we're going
to pull apart the nine specific trends that are defining
twenty twenty six. And I want to be clear to
you listening, we aren't just going to list off some
cool gadgets. Yeah, we're going to talk about how you
talk to machines, how machines are actually you know, entering
the physical world, and then the really heavy stuff, how
nations are starting to fight over the brains of these machines.
Speaker 2: The geopolitical angle is usually the one people ignore, but frankly,
it's the one that's going to affect your life the
most in the long run.
Speaker 1: Oh for sure, we'll get there, but I have to
tease the number one trend go on. Honestly, when I
saw it on the list, I just laughed, because three
years ago, everybody thought the future belonged to whoever had
the biggest, the smartest AI model.
Speaker 2: The god model, right, the race for the super brain, right.
Speaker 1: And it turns out that might have been a total red.
Speaker 2: Herring, a huge misdirection. But we have to earn that reveal.
Speaker 1: We do we do.
Speaker 2: We have to understand the interface first, how we even
interact with this stuff.
Speaker 1: So let's start there Segment one, the evolution of interaction.
We're covering trends nine, seven, and four here. This is
all about the user experience of well of being alive
in twenty twenty six, and I want to start with
trend number four, Context replaces prompt.
Speaker 2: Engineering RIP prompt engineering.
Speaker 1: Seriously, yeah, I mean, do you remember twenty twenty three
or even most of twenty twenty four?
Speaker 2: Oh? Vividly.
Speaker 1: It felt like you had to be a wizard casting
a spell. Right, You'd open a textbox and type this long,
convoluted thing. Oh yeah, act as a senior marketing executive
with twenty years of experience in SAW sales and write
me a polite but firm email to a client who
is laid on payment using the structure of the Challenger
Celle method.
Speaker 2: And if you missed a comma or phrased it slightly wrong.
Speaker 1: Garbage output total garbage, or it would just hallucinate something
completely useless.
Speaker 2: It was brittle. That's the perfect word for it. The
system was just brittle. You were trying to coax intelligence
out of a system that had almost no short term memory.
Speaker 1: But people were selling courses on this. I remember seeing
them everywhere by my PDF of the fifty magic prompts.
Speaker 2: It was a whole cottage industry, but trend four. I
mean it basically says that industry is dead, gone, and
it died because of a brute force technical leap. The
context window.
Speaker 1: Okay, let's unpack context window, because I think a lot
of people hear that term in their eyes just glaze over. Sure,
what are we actually talking about.
Speaker 2: Think of the context window as the working memory of
the AI. Okay, not what it knows from its training data,
like who George Washington was, but what it knows about
you and this specific conversation right now.
Speaker 1: The immediate short term memory exactly.
Speaker 2: And in the old days, and again we're talking like
eighteen months.
Speaker 1: Ago, which feels like a decade it does.
Speaker 2: Back then, that window was about eight thousand tokens.
Speaker 1: Which translates to what in human terms a few pages
roughly a long essay, maybe a short chapter of a book.
Speaker 2: So if you fed it a fifty page contract, by
the time it got to page fifty, it had technically
forgotten what was on page one. Oh, dropped out of
the memory.
Speaker 1: Buffer, which is completely useless for any real complex work.
Speaker 2: Totally useless, right, But look at the data and the report.
In just eighteen months, that capacity exploded from eight thousand
tokens to over two hundred thousand tokens. Wow, that is
a twenty five hundred percent increase.
Speaker 1: Two hundred thousand tokens. So we aren't talking about an
essay anymore.
Speaker 2: We are not. We are talking about the entire Harry
Potter series, the whole thing, the whole thing. We're talking
about your company's entire chaotic slack history from the last quarter,
every single line of code in a massive software project.
You can now dump all of that into the prompt.
Speaker 1: But hold on a second. Yeah, I have to play
Devil's Advocate here. Yeah, just because I can dump a
library's worth of text into the chat box, Yeah, does
that mean the AI actually understands it or finds the
important parts? I remember reading about the lost in the
middle phenomenon. Yeah, with the AI would remember the start
and the end of a document, but it would kind
of just hallucinate the stuff in the middle. Yeah, is
that still a problem.
Speaker 2: That's a really sharp question, And in twenty twenty four
that was a huge, huge problem. You'd give it one
hundred page legal brief and it would completely miss the
critical loophole on page forty right, But the reasoning capabilities
have really started to catch up with the memory size.
The attention mechanisms that's the part of the AI that
decides what's important, have gotten so much better at needle
in a haystack.
Speaker 1: Retrieval, so it can actually find the key detail in
a see of text.
Speaker 2: It can, so now you don't need to craft a
perfect prompt, you just need to provide the perfect context.
Speaker 1: Ah okay, so the skill shifts. It's not about knowing
how to talk to the robot anymore. It's about knowing
what information to give the robot precisely.
Speaker 2: It's become context dumping. You don't say act as a marketer.
You upload your last fifty marketing campaigns and you just say,
write one like these.
Speaker 1: So the AI derives the style from the data, not
from your description.
Speaker 2: Of the style exactly. It's so much more effective.
Speaker 1: That's a huge relief. I always hated trying to describe
my own writing style. It's like trying to describe your
own face.
Speaker 2: It's impossible, right, And the data totally supports this shift.
The report says context aware, so searches based on uploaded
documents increased by eight hundred and ninety percent in twenty
twenty five alone. Wow, people just stopped asking generic questions
and started asking really specific questions based on their own
uploaded data.
Speaker 1: But okay, this leads to a massive friction point, right, Yeah.
If I have to upload my life context, all my emails,
my project history, my personal preferences, every single time I
open a new tab, that is incredibly annoying. It is
I don't want to reintroduce myself to my own assistant
every single morning.
Speaker 2: And that is the perfect segue into trend number nine,
which is AI becomes persistent and personal. This is the
end of what I call the groundhog Day effect.
Speaker 1: Groundhog Day, great movie, absolutely terrible user experience.
Speaker 2: It's the worst, and it was the default for so long.
You close the tab, the AI basically gets a lobotomy. Yep,
it forgets who you are, what you were talking about, everything.
But the report shows that twenty twenty six is the
year this finally stops. It found that eighty two percent
of users either implicitly or explicitly want an AI that
remembers them across sessions.
Speaker 1: Eighty two percent. That number actually seems high to me. Yeah,
I mean, aren't people terrified of the privacy implications? If
the AI remembers that I was stressed about my mortgage
last Tuesday, and then today I ask it about planning
a vacation, isn't that getting a little too close to
big brother territory?
Speaker 2: It absolutely is, And I don't want to gloss over
the privacy nightmare this could become. It's a huge concern,
but human behavior almost always follows the path of least resistance.
Congeniens almost always beats privacy concerns in the long run.
Speaker 1: That's a depressing thought, but you're probably right.
Speaker 2: Well, think about the utility of it. If the AI
remembers your mortgage stress from last week and then you
ask it for a vacation plan, it might proactively suggest
a more budget friendly itinerate without you even having to say, hey,
by the way, I'm broke.
Speaker 1: It connects the dots for you.
Speaker 2: It connects the dots, and the report notes that personalized
assistance the ones with this long term memory show three
point five times higher engagement than the generic forgetful.
Speaker 1: Ones three and a half times. That's a huge difference.
Speaker 2: It's mats.
Speaker 1: I guess it's because it stops feeling like a tool,
like a calculator, and starts feeling more like a colleague.
Speaker 2: That's the perfect word. A colleague remembers that you hate
early morning meetings. A calculator doesn't care.
Speaker 1: Right.
Speaker 2: Persistent AI means the software builds a model of you
over time. It's kind of it's creating a theory of
mind about its user.
Speaker 1: Which is both incredibly cool and incredibly creepy at the
same time. It is. But okay, let's assume I'm on
board with the AI knowing my soul. How am I
interacting with it? Yeah, because for the last few years,
my thumbs have been doing all the work. I'm just
typing constantly.
Speaker 2: And typing is a bottleneck. It's actually a very low
bandwidth way to communicate. You can speak so much faster
than you can type, and you can show something with
the camera faster than you can describe it in words.
This is trend number seven Site and Sound.
Speaker 1: The stats here are pretty interesting. Fifty five percent of
smartphone users now use voice AI on a weekly.
Speaker 2: Basis, and that's up from what maybe ten percent who
are just using Siri for the rather a few years ago.
Speaker 1: Totally, but this isn't just sirius set a timer for
ten minutes. This is full, long, back and forth conversation.
Speaker 2: It's latency. That was the big unlock in twenty twenty six,
the lag between you speaking and the AI answering. It's gone.
It's instantaneous. It feels like a real phone call.
Speaker 1: Okay.
Speaker 2: But the bigger shift, the one I think is actually
more transformative, is.
Speaker 1: Vision video understanding. The report calls it that.
Speaker 2: Yes, queries for video understanding surged by six hundred and
seventy percent in twenty twenty five.
Speaker 1: Give me a real world example of that, because you know,
I can see using it to identify a bird in
my backyard. But six hundred and seventy percent growth that
implies people using this for actual work.
Speaker 2: Okay. Sure, Imagine you're a junior field technician for a
big telecom company. You're standing in front of this massive,
messy server rack you've never seen.
Speaker 1: Before, okay, a mess of wires.
Speaker 2: A total mess. In the old days, you'd have to
find the right manual, try to read the tiny schematic,
maybe call a senior tech for help, and.
Speaker 1: Hope the senior tech actually picks up the phone. Right.
Speaker 2: Good luck with that, ye, But now you just point
your phone's camera at the rack. The AI sees all
the wires in real time. You say which one of
these is the secondary uplink, and the AI just highlights
it on your screen in ar and says the blue cable,
third from the left.
Speaker 1: So it's not just seeing an image, it's analyzing context
and providing instruction.
Speaker 2: It's understanding the physical world. Humans don't experience the world
in text. We experience it in photons and sound waves.
Trends seven is all about AI finally matching human sensory input.
It makes the AI feel present, present in your physical.
Speaker 1: Reality, which you know, honestly that sets off some alarm
bills for me. Oh so well, if the AI is
present in my physical reality through a camera, the logical
next step is for to actually touch the physical reality
interact with it.
Speaker 2: You're anticipating our next segment perfectly.
Speaker 1: I am. Let's move to segment two, the physical world
and the economy, because we aren't just talking about software anymore,
are we We're talking about hardware.
Speaker 2: Trend number six is humanoid robots, and this is the
one where everyone usually rolls their eyes.
Speaker 1: I am rolling my eyes right now. I've seen the
demos I saw the robots walking like they had a
full diaper. I saw them folding laundry at like one
tenth the speed of a human. Is this actually a
trend for twenty twenty six or is this just hype
for stock prices.
Speaker 2: Look, if you asked me that in twenty twenty four,
I'd have said it was ninety percent hype. Yeah, But
looking at the twenty twenty six data, it's very real.
The market is projected to hit thirty eight billion dollars
by twenty thirty. But that's not the telling stat What
is the competition? In twenty twenty three, there were maybe
what seven major companies in the space. Now there are
twenty three.
Speaker 1: Twenty three, including all the big players, right.
Speaker 2: Tesla is the loudest one. Of course, They plan to
deploy thousands of their Optimist robots in their own factories
by the end of twenty twenty six.
Speaker 1: Thousands. Okay, So let's talk about so wet here. If
I'm a factory worker, should I be terrified?
Speaker 2: I'd say you should be paying attention, for sure. But
the use case right now isn't skilled labor. Okay, it's
not replacing the guy who knows how to well to
a complex joint for memory. It's boring practicality. It's moving
a box from palad A to palette B for eight
hours straight without a break.
Speaker 1: So the backbreaking stuff, the repetitive motion, the.
Speaker 2: Stuff that causes injuries, the stuff that has incredibly high
turnover because nobody wants to do it. The trend is
that AI is finally getting hands, but there is a
massive economic barrier here. Robots are expensive. The compute needed
to run them is expensive, which brings us to the
let's say, the ugly side of the economy. How do
we pay for.
Speaker 1: All of this? Friend number five advertising.
Speaker 2: The monetization reality check.
Speaker 1: This one hurts a little. I think for a while.
We all live in this nice little bubble where AI
was this pure helpful tool.
Speaker 2: We have a fun bubble.
Speaker 1: It was, But the source material says the AI advertising
sector is projected to hit one hundred and seven billion
dollars by twenty twenty eight.
Speaker 2: There's no such thing as a free lunch. We are
burning through just massive amounts of energy and GPU time
to run these huge context windows we love so much.
The big companies open AI, Google anthropic. They need revenue.
They have to pay the bills.
Speaker 1: So what does an AIAD even look like is like
a banner ad at the top of my chat.
Speaker 2: That's the benign version, the safe version, But the dangerous version,
the one the whole industry is grappling with right now,
is recommendation as ad.
Speaker 1: Okay, explain that.
Speaker 2: You ask your persistent AI, the one that knows you, Hey,
I need to book a flight to London and a
hotel for three nights. I want something modern and cool, right.
The AI comes back and says, okay, great, I've booked
you on Virgin Atlantic and put you in the Marriott.
Speaker 1: And my question is, did it choose the Marriott because
it's really the best modern hotel for me, okay? Or
did it choose the marriout because Marriott paid for that
top recommendation slot.
Speaker 2: Exactly, And unlike a Google search where it's as sponsored
in a tiny, tiny.
Speaker 1: Text at the top, which no one reads.
Speaker 2: Right, conversational AI completely blurs that line. It feels like
advice from a trusted friend. And if a friend recommends
a restaurant, you trust them, Yeah, But if you find
out your friend recommended that restaurant because the restaurant paid
them twenty dollars to do it. They're not your friend anymore.
They're a shill.
Speaker 1: And that completely destroys the trust. The whole persistent personal
system thing we just talked about. That whole relationship relies
on me trusting that the AI is working for me. Yes,
If it's actually working for the highest bidder, the entire
relationship breaks. The value is gone.
Speaker 2: It's an incredibly delicate balance. The report says fifty eight
percent of users would accept ads to keep their tools free. Sure,
we've basically been trained by the Internet for the last
twenty five years to trade our attention for free software, right,
But the intimacy of AI, as you said, it makes
that betrayal sting a whole lot more.
Speaker 1: The intimacy of AI. That is a phrase I am
definitely going to be thinking about later tonight. But I
want to shift gears. We've talked about the user, we've
talked about the robots and the ads. Now I want
to look under the hood.
Speaker 2: The engine room.
Speaker 1: The engine room segment three. This covers trends three, two,
and one, and this is where the entire narrative really
flips for me. Let's start with trend three. The technical
divide disappears.
Speaker 2: The democratization of code. This one is huge.
Speaker 1: For thirty years, if you wanted to build software, you
had to speak the language of the machine. You needed
to know C plus Python, JavaScript. If you didn't, you
were just a consumer, or.
Speaker 2: You were the idea guy. And nobody likes the idea guy.
Speaker 1: H the worst. I have an amazing ad idea, I
just need a developer to build it for me for equity.
Speaker 2: The classic trap. Yeah, but just look at twenty twenty five.
The report says forty three percent of all new applications
were built using AI assisted, no code or low code
tools forty three percent. And here's the real kicker, fifty
two percent of so called citizen developers. These are people
with zero formal code and training successfully shipped functional apps.
Speaker 1: Shipped is the key word there. They didn't just build
a prototype, they.
Speaker 2: Launched, They launched. This is the single biggest leveler in
the history of Silicon Valley. Innovation is no longer gated
by your ability to write syntax. It's gated by your
imagination and your understanding of a workflow.
Speaker 1: But I have to be the cynic again. If my
accountant is building apps and my hr rep is building apps,
isn't that a massive security nightmare? We USTI to call
that shadow it.
Speaker 2: Oh it is.
Speaker 1: Just because you can build an app doesn't mean you
know how to properly encrypt a database.
Speaker 2: Oh, it's a gigantic headache for CIOs everywhere. Suddenly you
have five hundred unvetted insecure apps running on your corporate network.
But from a trend perspective, it's unstoppable. The barrier to
entry has completely collapsed. You don't need to be an
architect to build a shed anymore.
Speaker 1: But you still need an architect to build a skyscraper.
Speaker 2: Exactly. Engineers are not obsolete. Role just moves up the stack.
They handled the complex, scalable secure infrastructure. The citizen developers
handled the local specific problems.
Speaker 1: Now, speaking of how these things work, last year twenty
twenty five, there was this massive hype cycle around agents,
autonomous agents.
Speaker 2: To set it and forget it dreams the dream.
Speaker 1: But trend number two is agents versus workflows, and looking
at this report, it seems like the agents they kind
of failed.
Speaker 2: They face planted hard. The report found that sixty seven
percent of companies that deployed fully economous agents scaled them
back within six months.
Speaker 1: Why. I remember seeing the demos. You'd say, go plant
a vacation to Italy, and the agent would browse the web,
use your credit card and book the whole thing. What
went wrong?
Speaker 2: Loops, infinite loops and just wild hallucinations. You'd tell an
agent research this competitor company. It would get ninety percent done.
It would hit a broken link on their website, and
then it would spend five hundred dollars of API credits
just trying to click that one broken link over and
over and over again. It got stuck, or it would
make a decision that was like legally disastrous for the company.
It lacked judgment, it lacked a brake pedal. That's a
great way to put it. It lacked a brake pedal.
So the big pivot, and this is trend too, is
toward human in the loop workflows. The report says eighty
nine percent of successful AI implementations use this model.
Speaker 1: So instead of telling it go do this entire job
by yourself, it's more like, do step one, then show
me the result. Okay, that looks good. Now do step two,
then show me again.
Speaker 2: Exactly, It's a workflow, not an agent. The AI is
the powerful engine but the human is the conductor. It
turns out businesses don't actually want full autonomy. They want accountability. Right.
Speaker 1: If the AI screw something up, you can't fire it.
You need a human who signed off on the work.
Speaker 2: That makes me feel a little bit better about my
own job security.
Speaker 1: Honestly it should. The human in the loop is the
critical safety valve, which brings us.
Speaker 2: To the number one trend, the one we teased at
the very beginning trend. Number one models stuff being the differentiator.
Speaker 1: This is the one that changes the entire business landscape completely.
Speaker 2: Okay, explain this because for years the entire game was
my AI is bigger and smarter than your AI.
Speaker 1: It was a pure arms race. Yeah I have GPT four,
you only have GPT three, so I win. Yeah, but
look at the API pricing. The report notes that since
twenty twenty three, the raw cost of top tier intelligence
has dropped by eighty percent.
Speaker 2: It's just crashing. The price is falling through the floor.
Speaker 1: It's commoditizing. Intelligence is becoming like electricity. You don't care
which power plant your electricity comes from. You just care
that when you flip the switch, the light turns on.
Speaker 2: So if I'm a startup in twenty twenty six. I
can't go to VCS and I have my pitch be
we have a really really smart model. No, they'll laugh
you out of the room because your competitor has access
to the exact same model for pennies. The moat is gone.
If everyone has access to a super genius brain for
next to nothing, then having a super genius brain isn't
special anymore.
Speaker 1: So what is special? If the brain itself is a
cheap commodity, what's the luxury good? What's the differentiator?
Speaker 2: Two things, primarily proprietary data and user experience. If you
have a data set that nobody else on earth has,
like fifty years of specific medical records for a rare disease,
that's a mote, okay. Or if you have a workflow
a user interface that is just delightful and intuitive to use,
that's a mote. But the tech itself, the AI part,
it's just table stakes. Now.
Speaker 1: This is a massive shift. It means the tech war
isn't about the algorithm anymore. It's about the product that's
wrapped around the algorithm.
Speaker 2: It shifts power from the research scientists to the product managers.
Speaker 1: Okay, so we've covered the tech, the users, the business models,
the economy. But we have to zoom out. Now, we
have to look at the map, the literal world map.
H Segment four is the geopolitical landscape trend number eight.
AI as statecraft.
Speaker 2: This is the heavy one. This is the one that
keeps the lights on at the Pentagon and in national
security agencies all over the world.
Speaker 1: We aren't talking about Google versus Microsoft anym. We are
talking about the US versus China, versus Europe versus everyone else.
Speaker 2: AI has officially graduated from a corporate asset to a
national imperative. The number of countries with formal, government funded
national AI strategies has tripled in just a few years.
Speaker 1: Why I mean, is it just national pride? We have
an AI too.
Speaker 2: It started that way, but now it's about economic sovereignty.
Think about it. If the AI models that run your
country's hospitals, your banks, and your school systems are all
hosted on servers in California, do you really control your
own country?
Speaker 1: If the US government decides to turn off the.
Speaker 2: Tab exactly, your economy grinds to a halt. Or what
if the US decides to just peak at all the
data flowing through those servers. So we are seeing this
massive push for sovereign.
Speaker 1: Clouds, sovereign cloud.
Speaker 2: Countries building their own massive data centers on their own soil.
The Middle East is spending tens of billions. Europe is
frantic to build their own compute capacity to catch up.
Speaker 1: And this is a physical thing, right, We're talking about
a race for computer chips.
Speaker 2: It's chips and it's energy. That's the bottleneck. Nobody discusses enough.
These data centers consume terrifying amounts of electricity. We are
literally seeing geopolitical struggles over access to power grids. Who
has the energy to run the brain of the future.
Speaker 1: It feels like the oil wars of the twentieth century,
but for silicon it.
Speaker 2: Is exactly that. We are moving from a tech war
to an economic solientty war that will be defined by
compute power. Where the GPU clusters live, That's where the
future economy lives.
Speaker 1: That is really sobering. It certainly puts my annoyance about
context windows into perspective. We're worrying about our little chatbots
while nations are worrying about the fundamental infrastructure of reality.
Speaker 2: It's all connected, though, isn't it. The little chatbot on
your phone only works because of that massive, energy hungry,
geopolitically sensitive infrastructure.
Speaker 1: Right, it all flows together. So let's try to synthesize this.
We have a lot of ground here. We have. We
went from the death of prompt engineering, all the way
to robots moving boxes, to the commoditization of intelligence, and
finally to global chip wars.
Speaker 2: It's a complex tapestry for sure.
Speaker 1: If you had to pick on one single theme for
twenty twenty six, what would it be.
Speaker 2: Integration?
Speaker 1: Integration.
Speaker 2: Okay, Up until now, AI was a novelty. It was
a destination you went to chat GPT to do a thing.
Right now it's integrated. It's in your phones operating system,
it's in the robot, in the factory, it's in the
national defense strategy. It's no longer a separate layer on
top of everything. It is the infrastructure. It's the concrete
of the digital world.
Speaker 1: And for the listener, you know, trying to navigate this
new world, what's the big personal takeaway?
Speaker 2: I'd say, look at trend three and trend two together. Okay,
the technical barriers are down. You can build things you
never could have before. If you have an idea you
can probably make it a reality, but don't trust the
machine blindly. Keep your hand on the wheel. The human
in the loop is you. You're the one that matters.
Speaker 1: When I have a question, I want to leave everyone
with a final provocation, go for it. If intelligence is
now cheap and abundant, like we said in trend one,
and the technical skills to build things are no longer
a barrier like in trend three, what becomes the most
valuable human skill?
Speaker 2: That is the billion dollar question, isn't it.
Speaker 1: What do we bring to the table? Is it taste?
Is it judgment? Is it empathy? When the machine can
do all the math and write all the code, maybe
the most valuable thing you can do is just be human.
Speaker 2: I think the future belongs to the curators, the people
who have the judgment and the taste to know what
to ask the AI to do, not just how to
ask it.
Speaker 1: I love that the curators, Well, we want to hear
from you. Seriously. Where do you stand on this whole
human in the loop idea? Are you relieved that the
autonomous agents struggled and you're still needed or are you
annoyed because you just wanted the robot to do your
job so you could finally go to the beach.
Speaker 2: I definitely know my answer to that one.
Speaker 1: On the comments. Thanks for joining us on this thread,
keep pulling at it, See you next time.