March 25, 2026 • 31 mins
A $30,000-a-year piece of software has tech and finance bros beefing on LinkedIn. The Bloomberg Terminal has a rabid Wall Street fanbase. So when some tech bros claimed to have vibe-coded a version of the terminal, with one prompt, there were some strong emotions among its finance superfans. Oz talked to Isabelle Bousquette, a tech reporter for The Wall Street Journal, to break down the drama and what it says about the future of software. Then, Isabelle updates us on Nvidia’s massive developer conference last week, the company’s new OpenClaw obsession and why making a claw almost broke her brain.
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Speaker 1 (00:16):
Welcome to Tech Stuff. I'm os Voloshen, and I'm excited
to welcome journalist isabel Busquett to talk about two of
her recent Wall Street Journal stories that caught my attention. First,
there's a battle happening on LinkedIn. It's a real sharks
versus jets, the moment between finance bros And tech bros.
And it's all part of this bigger picture of software
companies being existentially threatened by AI. Then, Isabelle tells us
(00:41):
about last week's GtC, the Massive Developer conference held by
the multi trillion dollar company in video.
Speaker 2 (00:48):
Welcome, Isabelle, Thank you so much for having me.
Speaker 1 (00:50):
Now this is I have to say I admire you
tremendously because you went literally straight from GtC on Tuesday
evening to the Red Eye to the podcast to do this.
Speaker 3 (01:01):
Yeah.
Speaker 2 (01:01):
Yeah, that's right.
Speaker 3 (01:02):
I had a brief little breakfast at home first, but yeah,
fresh from San Jose.
Speaker 1 (01:08):
So you're not a correct engineer, but you're a correct journalist. Yeah.
But I want to ask you what about GtC. But
the piece that caught my attention this week was about Bloomberg,
and I have to confess I used to work this,
so obviously I was particularly intrigued. Yeah, what happened? What
was this throwdown and how did it come about?
Speaker 3 (01:26):
Okay, so I cover enterprise AI, and so for a
while we've been seeing crazy releases, these new models, these
new tools are coming out all the time. It's constant.
So the more these tools come out, the more capable
they are. It starts to raise questions about how fast
they can recreate versions of popular but very expensive software.
(01:50):
So Salesforce is a great example of this. There haven't
been a lot of sort of alternatives in the market,
and so now with a tool like claud code, some
people are saying, oh, we can just sort of code
our own version of Salesforce. So that's sort of the
context of this conversation. There's sort of this existential threat
to software and it's really been hitting some of the
software stocks odd.
Speaker 1 (02:11):
Right, I mean Salesforce at lassion.
Speaker 3 (02:13):
Yeah, the salesforces the workdays of the world, you know,
companies like Legal Zoom.
Speaker 2 (02:18):
There's been like I think, like a trillion.
Speaker 3 (02:20):
Dollars lost in the markets over this, And you can
argue about whether it's justified or not justified, but I
think the idea is like investors are spooked.
Speaker 1 (02:28):
But let's anchor this in Bloomberg. I think most people
listening to this podcast may not know what the Bloomberg
terminal even is. So if you could start with explaining
the Bloomberg terminal and then how it fits into this story,
and then why it kind of went viral on LinkedIn.
Speaker 3 (02:41):
Yeah, Yeah, the Bloomberg terminal is a little bit of
a unique beast. So it's it's it's essentially a computer system.
It's the hardware and software. It came out in nineteen
eighty two, and the interface looks remarkably similar to the
way it looked in nineteen eighty two. Yes, it has
that classic dark background, gold tags, very sort of classic feel.
(03:02):
And this machine is like the lifeblood of financial institutions.
So traders and research teams are on it for hours
and hours a day doing everything they need to do,
from tracking real time prices of commodities stocks and they
can research historical prices, They get news alerts, they can
(03:22):
do all the analysis about the way that you know
certain news is impacting certain prices.
Speaker 2 (03:26):
They can execute trades on it, and.
Speaker 3 (03:29):
One of the most beloved and critical features is called
instant Bloomberg, and it's a chat feature where you can
chat with anyone else who has a Bloomberg terminal. And
because the Bloomberg terminal is sort of so entrenched in
financial institutions, like everybody has it, so anyone who is
a colleague, a competitor, a customer is on there, and
(03:49):
it's sort of created this whole network of a community
that is just like on there all the time. That's
just their operating system.
Speaker 1 (03:57):
It was sort of Select before select Bloomberg Messenger and
also outside your own organization.
Speaker 2 (04:01):
Yeah yeah, yeah you met.
Speaker 1 (04:02):
Their wives there, I mean.
Speaker 3 (04:05):
True, Yeah, there is like a whole dating scene on
instance bloom Yeah. Yeah, people definitely mete their spouses on there,
and yeah, a lot going on.
Speaker 1 (04:15):
So what what was a story you wrote? And because
I saw it on LinkedIn and I saw your story
and I was just delighted. But how did this kind
of come about?
Speaker 3 (04:21):
Okay, so it sort of goes back to what we
were talking about a minute ago, which is that you know,
there's been this constant stream of releases of AI tools,
and every time there's a new AI tool released, there's
this really you know, broad conversation on social media being
like Salesforce is dead, workday is dead. This is the
end of this piece of SaaS software. This is the
(04:42):
end of this piece of SaaS software. So it was
on the heels of the launch of this tool called
Perplexity Computer, which is sort of an agent building system.
And Perplexity Computer comes out and some folks on you know,
social media, on acts on LinkedIn start posting that they
vib coded a version of a Bloomberg terminal in one shot,
(05:03):
so like one one natural language prompt, and they had
a Bloomberg terminal in.
Speaker 2 (05:08):
Front of them.
Speaker 1 (05:09):
By the way, Bloomberg terminals generate I think about ten
billion dollars in revenue a year today.
Speaker 3 (05:13):
Right, It's a massively expensive tool. I mean it costs
thirty thousand a year per seat, per user. The Perplexity
tool costs like twenty four hundred dollars a year. So
the idea that you might be able to get what
you could get on Bloomberg via one shot prompt kind
of a wild idea. It doesn't really stack up theoretically,
but I think it touches on a lot of sort
(05:36):
of sensitive issues that are going on here. What struck
my interest about the conversation was just that, you know,
the visceral reaction from the finance community was so passionate
and energetic and angry, and people were so protective of
the Bloomberg terminal and just responded with such backlash, saying
(05:59):
like you will never replace this, Nothing you can ever
do will ever replace this, you know, questioning people's sanity,
saying the you know, users should be locked up, saying
that so there was a conspiracy theory that like some
of these people were paid by Perplexity to post it,
which Perplexity is said is not true. So the conversation
just kind of like spun out of control from there,
and I just thought it was so fascinating because like
(06:21):
nothing has sort of stirred that visceral reaction the way
that you know, this love of the Bloomberg terminal emerged.
Speaker 1 (06:28):
Do you think the kind of Jets versus Sharks a
West Side Story comparison is apt? I mean, I guess
what I'm asking you really is finance bros were the
acme of professional brohood. Yeah, for twenty years. It's almost
like I'm wondering this is just a hypothesis. It feels
(06:48):
like finance people have essentially been replaced as in the
hierarchy of like where value creation and becoming incredibly rich happens.
That's been kind of happening for a while. But I
like the AI moment in the last couple of years
has really accelerated there. So do you think this is
like a howl in the wind of saying like no, no,
like no tech bros, like we still got us finance bros.
(07:10):
Is that fair or what? Do you think?
Speaker 3 (07:12):
I think, Yeah, that's an interesting idea, Like I do think,
like one common criticism from the tech bro side was that,
you know, the finance people were just they just wanted
to stick their feet in the sand. They were ignorant of,
you know, how important and how critical AI advances were
going to be, that they were stuck in their old ways,
(07:35):
that it was naive of them to think that there's
any piece of software that's irreplaceable. But yeah, I mean,
I think, like what's so interesting about these two groups
is that the people who work in finance just have
this love of Bloomberg, Like it is like it is
like a phantom limb for that. One person I talked
to told me like using his terminal was like crack,
(07:56):
which I was like, okay. And on the other side
of that, like people worship AI.
Speaker 2 (08:03):
So there's this like extreme.
Speaker 3 (08:05):
Like almost religious like passion on both sides, and I think.
Speaker 2 (08:09):
That's sort of the root of why we saw.
Speaker 1 (08:11):
This clash that's so well put. You know, a friend
of mine worked in a scrapyard in France when he
was a teenager. Briefly we told me the other day
that there was an occasion when a guy who was
like a truck driver brought his truck to be scrapped
and he'd driven it for twenty years, and as it
was kind of entering a scrapyard, he just collapsed on
(08:32):
the floor and was screaming like a child in the
fetal position, saying look by to his truck. And we
were talking, my friend and I about this and how like,
as a person in the world, you ultimately spend like
the majority of your waking hours working, whether that's like
driving a truck or on the Bloomberg terminal, And so
that like extreme like nostalgia and personal identification with these tools,
(08:56):
whether it's a truck or a terminal, it's kind of interesting,
but is there something different about the terminal from say salesforce, Like,
what do you really think makes this like such a
rubicun for finance people.
Speaker 2 (09:07):
I mean, it's a good question.
Speaker 3 (09:08):
I think the fact that it's been around so long
and it's had such staying power throughout that period of
time is important. I think the fact that it is
so expensive also is important. You know, when you reach
the point in your career at which you get a
Bloomberg terminal, that's a big deal. That's sort of like
a rite of passage for you, and then you have it,
(09:30):
and it's sort of a status symbol. So I think
it's it's come to represent all these things. But I
also think the reality is that they do love the functionality,
like they just they've sort of come to depend on
that functionality and they couldn't really live without it. And
I think it's easy to be skeptical of, you know,
some sort of flashy new AI coming in and being like, oh,
(09:52):
we can do this, Like I think, you know, the
natural reaction is no, you can't. Bloomberg has been doing
this for decades. This AI tool was invented a couple
weeks ago, Like, what do you people know about this?
Don't try to come in and take away our Bloomberg
terminals and give us some shoddy, cheaper vibe coded replacement
because you're taking away like what we need to do
(10:14):
our jobs?
Speaker 1 (10:16):
And did you experiment with the vibe coded replacement? I mean,
what was the take of people who actually used these
products in terms of how close did the perplexity vibe
coded version get to successfully replicating the Bloomberg functionality.
Speaker 3 (10:30):
Yeah, so I think, to be honest, on both sides,
there's an acknowledgment that whatever you can vibe code in
one shot prompt is not going to be anywhere near
the Bloomberg terminal. Like I think even the tech people
realize how I acknowledge that, And I think they would say, like, oh, yeah,
but it's a great starting point and if you put
in a little more effort and maybe it's not all
(10:51):
vibe coding, maybe some of it's real coding, and maybe
you can't get all the way there, but maybe you
can get close. But these sort of like one shotted
vibe coded demonstrations, it's hard to tell because the people
that post them, you can't sort of go it. They
don't always share the prompt and they don't always share
the experience. They just share like a screen grap and
so a lot of what was being shared is these
(11:13):
tools for like tracking stocks and financial analysis, which people
were right to point out is just one part of Bloomberg.
Like a big question that came up is sort of
like the real time data inputs the Bloomberg gets. Like
Bloomberg has these proprietary data inputs, it gets them faster
than anybody else. It gets more data, one might say,
(11:34):
better data than anybody else. And yes, there is stock
data and commodities data available on the Internet, but it's
maybe not the same breath and depth that Bloomberg gets.
So I think, like no, to answer your question, like
the one shotted, vibeut it apps like don't come close
to what the Bloomberg terminal is. But again, like the
tech people would say, like bo we.
Speaker 2 (11:56):
Can get there.
Speaker 1 (11:57):
You know what I mean, you are another story couple
of weeks ago, meet the company's vibe coding that own CRM.
What's your like medium term perspective? You do you think
software companies are like literally gonna go away or do
you think a new crop of more targeted software companies
will emerge to have less legacy baggage and then probably
(12:17):
be consolidated into selfwaking commorts. Again, like, what do you
think is gonna happen here.
Speaker 2 (12:21):
Yeah, No, it's a good question.
Speaker 3 (12:23):
I mean, like there's been talk of the death of
software for a really really, really really long time, and
it has been resilient and it has stuck around. And
you know, three years ago when Chatchibt first came out,
everyone was like, oh, it's the end of software, like goodbye,
and that I think that hasn't really happened. Although, like
(12:43):
I think there is like if you're a legacy SaaS
company and you can pivot into the modern age and
you can invest really deeply in AI, invest really deeply
an agents, provide that to your customers and sort of
be a value proposition that's you know, not dissimilar from
what they could get from a more AI native startup,
(13:04):
then I think that those companies have a chance of succeeding.
If you're a legacy sasas provider and you kind of
stick your feet in the sand and you just count
on the fact that your customers are sort of locked
into you. They have years alone contracts, it's going to
be really hard for them to exit your platform. Then
maybe you're in a situation where you're getting in trouble
in a few years. But I do like, I think
most of the SaaS companies know they have to pivot,
(13:26):
Like AI is AI is the big thing. AI is here.
Everybody in the software world knows that, and so they're
all sort of jostling to position themselves as the provider
of AI and AI native companies are in a like
you could argue they're in a better position to do that,
but legacy companies have at yeah, big customer bases, more
(13:49):
of an understanding of like what you know, business requirements
and stuff like that.
Speaker 2 (13:53):
So I don't know how it's all going to play out.
Speaker 3 (13:55):
People like compare this sort of AI moment a lot
to like the dawn of the Internet and sort of
like the dot com must and you know, there will
be a lot of new companies that come up and
are great, and there will be other companies that sort
of go on the corner and die and other companies
that survive.
Speaker 1 (14:13):
Yeah, we'll just have to say, Well, the company, which
is in many ways at the very center of all
this is in video when we come back, Isabelle tells
us all about her trip to Invidia's develop a conference
last week, what Jensen Huang has called the super Bowl
of AIM. So before the break. We were talking about
(14:57):
Bloomberg and software and whether AI will eat softwa where,
And I want to talk a bit more about that
in respect to what you learned this week at the
Nvidia conference. Before we get into those specific topics, what
was it like and describe the scene.
Speaker 3 (15:11):
The energy at Nvidia GGC is very unique and it's
kind of electric. It takes over the entire city of
San Jose, thirty thousand people.
Speaker 2 (15:23):
I interviewed the mayor of San.
Speaker 3 (15:25):
Jose last year about this and he was like, the
coffee shops make their entire year's rent in the course
of a couple days. Of course, that means like if
you want to get a cup of coffee, you are
waiting in line for like an hour. You're waiting in
line for an hour for everything to like get into panels,
to get into buildings, to get coffee, to get a
granola bar. It's, you know, like you're out there in
(15:45):
the wilderness, like you have to fight to get like
a sandwich.
Speaker 1 (15:50):
No, the Fortralling Company doesn't provide any free coffee and sandwich.
Speaker 4 (15:53):
This is no.
Speaker 3 (15:54):
I mean it's like it's wild though, I mean it
does like people say, it has this like rock concert
like sort of atmosphere. There's music and there's you know,
in the evening they like bring out shot luges. There's
robots everywhere of every different kind of roy you can imagine.
Because in Video is like really invested in this physical
(16:15):
AI thing.
Speaker 2 (16:16):
They're also really.
Speaker 3 (16:17):
Invested at autonomous driving, so they have like all these
like different cars. Like everything in the city is decked
out in in Vidia signature green and it's sort of
like Disneyland for like the AI industry, Like there's just
so much to do and see and play with and
it's just like a totally different world. Everyone is super
(16:38):
excited about the technology. Everyone is super bullish about it.
So yeah, it's it's sort of like this little like
hype of Vortex.
Speaker 2 (16:45):
It's so easy to get sucked in.
Speaker 1 (16:47):
Well, how do you avoid getting secked in? What the
kind of what were the more critical questions that you
had about what was going on?
Speaker 3 (16:52):
I suppose yeah, yeah, I mean I think like if
you think about Nvidia as a chip company, like there's
sort of been this inflex point in the chip industry,
which is this shift from training to inference, Like for
the last few years, like the bulk of compute has
been used to train these really big, large language models,
(17:13):
and now we're getting to the point where a lot
of compute is being used to run these large language models.
And so in Vidia's chips historically have been really, really
really great.
Speaker 2 (17:24):
At the training.
Speaker 3 (17:25):
Like that is what propelled them to their current valuation.
And I think like there were always questions about what
does it mean for Nvidia in the era of AI
and friends, And in Vidia is an incredibly innovative company
and it comes from the top. Jensen is just an
incredibly curious, innovative person. They have a very flat structure
(17:49):
as a company, not a lot of middle management.
Speaker 2 (17:52):
Jensen and sort of like all the top leaders have
a lot of direct reports.
Speaker 3 (17:55):
There's a lot of autonomy, but there's just this constant
push to just like innovate as fast as you can
and always be on the next thing, and always be
on the next thing, and always be on the next thing.
So they acquired an inference chip startup called Grock recently,
so a lot of the conference was.
Speaker 1 (18:13):
There's nothing to do with Elan's Grock, This is Grock
with Q or other case.
Speaker 3 (18:16):
Yeah, it's incredibly confusing and a weird name to have
twice and what is stream But yeah, so there was
a lot of talk about how they're integrating sort of
like Grock's offerings into in video offerings and you know,
just this this big push to you know, stay on
top of things on the compute side, and then on
the flip side of that, there's also you know, part
(18:38):
of this conference is for Jensen to get out there
and you know, prove that demands for AI workloads is
going to be greater than ever before. And that's what
he says every year, and that's what he has to
go and prove out every year because that's what's sort
of spurring their demand. And so there was a lot
of talk about the software side and what companies are
doing with AI and what they're going to be doing
(19:00):
with AI, and there was a lot of talk about
something called open Claw.
Speaker 1 (19:06):
I want to ask you about them, and particularly how
it relates to the Bloomberg and the software story we're
talking about earlier. Just before we get there, I want
to read a quote from your newsletter. Today's maturity curve
in AI is much higher, and the explosive growth and
improvement of AI coding tools has arguably given a gentic tech.
It's killer app Still, the technology continues to speed far
(19:27):
ahead of business adoption. Talk about that. Why is business
adoption slower than technology development?
Speaker 2 (19:33):
I mean there's a lot of reasons for that. One
is just because technology development is so fast. Silicon Valley
is moving so fast right now with the models are
coming out all the time, they're always better. And then
there's you know, last year, agents were just starting to
become a thing. So I remember being a GtC.
Speaker 3 (19:51):
Last year and everyone was talking about agents, but also
nobody was really using them. There was just this understanding that, like,
agents are going to be the next thing. And it
was this transition from we have chatbots and we can
ask them questions and we can get answers and this
is incredible to Okay, agents are actually going to do
things for us. And I think last year was just
(20:11):
sort of like a buzzword. This year is actually starting
to happen in businesses. But the tech is sort of
chugging along even beyond that too. It's not just agents
that will do a task for you, it's now these
sort of complex groups of agents that are delegating tasks
to each other and can access your documents and files
(20:35):
and business data and run for a really long time
and sort of do these complex workflows and then you know,
report back to you. So it's it's even beyond just
doing tasks to like you know, doing almost like entire jobs.
But I think that's where businesses are still sort of
like the initial agentic deployment point of just like figuring out,
(20:57):
like where do I even like trust this type of
offer to like do a task for me let alone,
like you know, give it access to like my entire
operating system.
Speaker 1 (21:06):
And where does open claw fit into all of this?
Animo Claw which was announced at GtC.
Speaker 3 (21:12):
Open Claw is another thing that just sort of it's
so hard to keep up in this industry.
Speaker 2 (21:18):
Someone was saying the other day.
Speaker 3 (21:19):
Like you have to be fully unemployed to keep up
with anything that's going on in AI, and like I
can really respect that.
Speaker 1 (21:27):
I can relate to that too. I mean I do
this podcast twice a week, but it's just the deluge
of information.
Speaker 3 (21:32):
Wild It's like one day and there's this thing called
open claw, and it's really confusing because open claw is
about creating these things called.
Speaker 1 (21:42):
Clause clause agents. Yeah.
Speaker 3 (21:45):
Yeah, Claws are basically these long running autonomous agents. And
open claw it's it's an open source standard for building
these sort of like complex orchestrations of all these different
age So you can set up a claw to do
something and that claw will like tap a bunch of
series of subagents delegate tasks. You can give it access
(22:08):
to your files. It can do things for you, and
it can do it like continuously over a long period
of time. Like you could do things like summarize all
the news of the week and shoot me an email
every Monday at noon with what's going on, and it
will just sort of keep running and do that. Or
you know, you could set it to do a task
overnight and then come back and it's done in the morning.
(22:29):
So I think like the biggest sort of shift with
open claw is this move from I'm talking to an
agent and I'm prompting an agent and it's giving me
a response, and then I'm giving it a response, and
it's sort of this like real time interaction collaboration versus
with clause, you're really just sort of like sending it
off okay for a while, and then it's coming back
(22:54):
to you later.
Speaker 2 (22:54):
It's like it's asynchronously working with.
Speaker 1 (22:56):
A single natural language prompt or a more complicated promo.
What's the use case of open clure that you've seen
that you find intriguing.
Speaker 3 (23:03):
Yeah, yeah, no, I mean that's a great question, And
that was exactly my question when I was at the
conference and in video had this experience called build a Claw,
which was this tent where everybody got to go inside
and build a claw, and I think like it was
really interesting because I went to go build my own claw,
and I just said to the video exact I was
(23:24):
talking to, I can't think of something that would need
to be a claw that I couldn't just do with
an agent or a chat bot. And it was just
it's this hard conceptual shift that needs to happen. It's
like it's sort of like the same way when chattyb
(23:44):
Tea came out, we would all talk to it the
same way.
Speaker 2 (23:47):
We talked to Google.
Speaker 3 (23:48):
We would just put in a few keywords because that's
the way we were used to interacting with those systems. So
now it's like when we get the opportunity to use
a claw, we're kind of interacting with it the same
way we would do with chatchybet. Like I was with
my editor and he was like, oh, help me plan
a road trip, and it could do that, but it's
like it's capabilities are so far beyond that that again
(24:10):
it's hard to conceptualize, like how to actually do this.
Speaker 1 (24:13):
Do the invideoor exec give you any advice on what
type of clore to build or were the other people
that build? Yeah, I mean I that you came.
Speaker 3 (24:20):
I remember talking to this one marketing leader who said
she had like, you know, a dozen different ideas for
clause and a lot of it is, you know, scanning
information on the internet. So her idea is, you know,
go on social media and read all these news sites
and read all these newsletters and report back to me
(24:41):
every morning.
Speaker 2 (24:42):
What are sort of like.
Speaker 3 (24:43):
The key themes of you know, what we should be
putting our marketing and thought leadership content around, and then
like help us like make sure that whatever we plan
to put out that day is like sort of like
drafted around that. Another example was an Nvidia exec was
telling me that they had this college student come through
and she was job searching, and so she was like
(25:04):
kind of claw helped me, you know, identify jobs to
apply for. And he was like, yes, that's like a
great chop out question. But like take it a step further,
like once it finds the role, then have it like
identify the right skills and then like optimize and tweak
your resume. And she was like, okay, great, and then
in videos, I can then take it a step further
(25:25):
and then give it access to your LinkedIn and then
give it access to your data and like have it
build out these coverlead It's like, have it do these applications.
And so it's like you just have to have that
mindset shift of like always take it a step further.
And I think that's not totally clear to all of
us yet unless you're, like, you know, an AI.
Speaker 2 (25:45):
Super super super user.
Speaker 3 (25:46):
But even since the AI super users that were at
the video conference, I think we're just like having trouble
conceptualizing like the real capabilities of what we can.
Speaker 1 (25:54):
Do with this. Jensen said, this is the new chat moment.
He said that we're having the che cheapy team moment
for robotics, so having one check cheap team.
Speaker 3 (26:05):
He was like he was really really all in on this,
I mean all on open claw.
Speaker 4 (26:11):
Yeah.
Speaker 3 (26:12):
But okay, so here's the thing about open Claw we
haven't talked about, which is that like there's a lot
of security challenges, and I did not find anyone at
the video conference who was comfortable using open claw for
any context in their actual like work slash business. So
when people want to use open claw, a lot of
times they'll go out and get a separate computer and
(26:34):
just run it on that computer, like.
Speaker 1 (26:36):
A clean computers.
Speaker 3 (26:37):
So it's like it's literally just like a separate computer. Yeah,
and just for open claw, because if you have open
claw on your computer where you have all your business
data and you're giving it access to things, it can
really I mean there's been a lot of stories of
open claw deleted all your emails or if you know,
if you have a Claw that's on the internet and
(26:58):
interacting with people, you know, it's not that difficult to
like prompt injected and then open clock can like give
away or credit card details. So there's so many data
concerns about open claw, which is why it is not
enterprise ready.
Speaker 1 (27:11):
And the video are trying to basically with Nemo Claw,
which is their product, create a version of layer on
top of the open source open flaw to make it
business safe.
Speaker 2 (27:21):
Yes, yeah, yeah, that's what they're trying to do.
Speaker 3 (27:23):
I don't know if they're fully there yet I think
there's this is this tack is so new, there's still
so many concerns because a lot could go wrong, clearly,
but I think they're excited about what could go right
and they just sort of want to put it in
that direction.
Speaker 1 (27:38):
The other thing which came up, I think a fabit
was space, right AI and space?
Speaker 4 (27:42):
Yeah?
Speaker 1 (27:43):
Was that? What else kind of surprised you and caught
your eye while you were there on the ground.
Speaker 3 (27:46):
Look, the amount of announcements and video puts out at
GtC is crazy. I mean there was there were more
than a dozen.
Speaker 2 (27:52):
Press releases, Like it's just wild.
Speaker 3 (27:56):
But yeah, I mean computers going into space, that's one
thing you know in videos playing a lot in the
quantum landscape, Like, that's another thing we should be paying
attention to. Autonomous driving is a really big focus, and
I think that caught my eye because you know, in
video they announced a partnership with Uber to sort of
(28:17):
invest in this robotaxi fleet and it's coming to a
bunch of cities around the world in the next couple
of years. And you know, you can imagine a future
where like you drive to work and then while you're
in your office, you send your car out to be
an autonomous uber for the day, and then it drives
back and picks you up.
Speaker 2 (28:37):
So that was another interesting thing.
Speaker 1 (28:40):
Just coming back to the to the beginning of our conversation.
I mean, the kind of open law world you're describing
does sound like a world whereas seems like there will
be serious competitive threats to people paying thirty thousand dollars
a year for Bloomberg.
Speaker 3 (28:54):
Yeah, yeah, I mean you could definitely make that argument.
You know, you could also make the other argument that,
you know, there's a reason Bloomberg costs thirty thousand dollars
and it's incredibly secure and they have spent many, many
years investing in you know, the algorithms that model the
pricing for this, and that I think, you know, you
(29:16):
could build an alternative with open claw and people will
And you know, maybe if you're just sort of like
a less serious retail investor, like that will be great
for you because you're someone who's never going to invest
in a Bloomberg terminal. But if you're like a finance company,
it's hard to imagine you would walk away from like
(29:38):
the security and consistency of something like a Bloomberg terminal
At least in the near future.
Speaker 1 (29:44):
I think brand metters, and I think about on the
legal side, for example, like sure, if you're a finance company,
you could use some you know, legal AI software like
or you could pay Lathan Watkins one thousand dollars an
hour perer because you know you've got Yeah.
Speaker 3 (30:01):
Yeah, And I mean one thing we haven't touched on
either is the fact that, like you know, Bloomberg is
integrating AI. They have AI features of the terminal, and
so I think like that's their push to sort of say,
like this is not a point when you need to
go out and find an alternative, like we are everything
we've always been to you and more and we're worth
that price tag. So yeah, I mean again, there's arguments
(30:22):
on both sides, which is again why it's started up
playing so much angry debate online.
Speaker 1 (30:27):
Isabel, thank you, thanks for coming straight from the Red Eye.
A good luck with the rest of your day. I
gather you're going into the office now to write some
more stories.
Speaker 3 (30:34):
Yeah, yeah, I'm about to. Could I go write some
more Open Claws stories?
Speaker 4 (30:38):
So thanks for having me, h for text stuff.
Speaker 1 (31:02):
I'm as Volosian. This episode was produced by Eliza Dennis
and Melissa Slaughter. It was executive produced by me Julian
Nutter and Kate Osborne for Kaleidoscope and Katrina Norvell for
iHeart Podcasts. The engineer is Charles de Montebello for CDM Studios.
Jack Insley mixed this episode and Kyle murdoch Rodart theme
song and please do rate and review this show wherever
(31:22):
you listen to your podcast
Welcome to Tech Stuff. I'm os Voloshen, and I'm excited
to welcome journalist isabel Busquett to talk about two of
her recent Wall Street Journal stories that caught my attention. First,
there's a battle happening on LinkedIn. It's a real sharks
versus jets, the moment between finance bros And tech bros.
And it's all part of this bigger picture of software
companies being existentially threatened by AI. Then, Isabelle tells us
(00:41):
about last week's GtC, the Massive Developer conference held by
the multi trillion dollar company in video.
Speaker 2 (00:48):
Welcome, Isabelle, Thank you so much for having me.
Speaker 1 (00:50):
Now this is I have to say I admire you
tremendously because you went literally straight from GtC on Tuesday
evening to the Red Eye to the podcast to do this.
Speaker 3 (01:01):
Yeah.
Speaker 2 (01:01):
Yeah, that's right.
Speaker 3 (01:02):
I had a brief little breakfast at home first, but yeah,
fresh from San Jose.
Speaker 1 (01:08):
So you're not a correct engineer, but you're a correct journalist. Yeah.
But I want to ask you what about GtC. But
the piece that caught my attention this week was about Bloomberg,
and I have to confess I used to work this,
so obviously I was particularly intrigued. Yeah, what happened? What
was this throwdown and how did it come about?
Speaker 3 (01:26):
Okay, so I cover enterprise AI, and so for a
while we've been seeing crazy releases, these new models, these
new tools are coming out all the time. It's constant.
So the more these tools come out, the more capable
they are. It starts to raise questions about how fast
they can recreate versions of popular but very expensive software.
(01:50):
So Salesforce is a great example of this. There haven't
been a lot of sort of alternatives in the market,
and so now with a tool like claud code, some
people are saying, oh, we can just sort of code
our own version of Salesforce. So that's sort of the
context of this conversation. There's sort of this existential threat
to software and it's really been hitting some of the
software stocks odd.
Speaker 1 (02:11):
Right, I mean Salesforce at lassion.
Speaker 3 (02:13):
Yeah, the salesforces the workdays of the world, you know,
companies like Legal Zoom.
Speaker 2 (02:18):
There's been like I think, like a trillion.
Speaker 3 (02:20):
Dollars lost in the markets over this, And you can
argue about whether it's justified or not justified, but I
think the idea is like investors are spooked.
Speaker 1 (02:28):
But let's anchor this in Bloomberg. I think most people
listening to this podcast may not know what the Bloomberg
terminal even is. So if you could start with explaining
the Bloomberg terminal and then how it fits into this story,
and then why it kind of went viral on LinkedIn.
Speaker 3 (02:41):
Yeah, Yeah, the Bloomberg terminal is a little bit of
a unique beast. So it's it's it's essentially a computer system.
It's the hardware and software. It came out in nineteen
eighty two, and the interface looks remarkably similar to the
way it looked in nineteen eighty two. Yes, it has
that classic dark background, gold tags, very sort of classic feel.
(03:02):
And this machine is like the lifeblood of financial institutions.
So traders and research teams are on it for hours
and hours a day doing everything they need to do,
from tracking real time prices of commodities stocks and they
can research historical prices, They get news alerts, they can
(03:22):
do all the analysis about the way that you know
certain news is impacting certain prices.
Speaker 2 (03:26):
They can execute trades on it, and.
Speaker 3 (03:29):
One of the most beloved and critical features is called
instant Bloomberg, and it's a chat feature where you can
chat with anyone else who has a Bloomberg terminal. And
because the Bloomberg terminal is sort of so entrenched in
financial institutions, like everybody has it, so anyone who is
a colleague, a competitor, a customer is on there, and
(03:49):
it's sort of created this whole network of a community
that is just like on there all the time. That's
just their operating system.
Speaker 1 (03:57):
It was sort of Select before select Bloomberg Messenger and
also outside your own organization.
Speaker 2 (04:01):
Yeah yeah, yeah you met.
Speaker 1 (04:02):
Their wives there, I mean.
Speaker 3 (04:05):
True, Yeah, there is like a whole dating scene on
instance bloom Yeah. Yeah, people definitely mete their spouses on there,
and yeah, a lot going on.
Speaker 1 (04:15):
So what what was a story you wrote? And because
I saw it on LinkedIn and I saw your story
and I was just delighted. But how did this kind
of come about?
Speaker 3 (04:21):
Okay, so it sort of goes back to what we
were talking about a minute ago, which is that you know,
there's been this constant stream of releases of AI tools,
and every time there's a new AI tool released, there's
this really you know, broad conversation on social media being
like Salesforce is dead, workday is dead. This is the
end of this piece of SaaS software. This is the
(04:42):
end of this piece of SaaS software. So it was
on the heels of the launch of this tool called
Perplexity Computer, which is sort of an agent building system.
And Perplexity Computer comes out and some folks on you know,
social media, on acts on LinkedIn start posting that they
vib coded a version of a Bloomberg terminal in one shot,
(05:03):
so like one one natural language prompt, and they had
a Bloomberg terminal in.
Speaker 2 (05:08):
Front of them.
Speaker 1 (05:09):
By the way, Bloomberg terminals generate I think about ten
billion dollars in revenue a year today.
Speaker 3 (05:13):
Right, It's a massively expensive tool. I mean it costs
thirty thousand a year per seat, per user. The Perplexity
tool costs like twenty four hundred dollars a year. So
the idea that you might be able to get what
you could get on Bloomberg via one shot prompt kind
of a wild idea. It doesn't really stack up theoretically,
but I think it touches on a lot of sort
(05:36):
of sensitive issues that are going on here. What struck
my interest about the conversation was just that, you know,
the visceral reaction from the finance community was so passionate
and energetic and angry, and people were so protective of
the Bloomberg terminal and just responded with such backlash, saying
(05:59):
like you will never replace this, Nothing you can ever
do will ever replace this, you know, questioning people's sanity,
saying the you know, users should be locked up, saying
that so there was a conspiracy theory that like some
of these people were paid by Perplexity to post it,
which Perplexity is said is not true. So the conversation
just kind of like spun out of control from there,
and I just thought it was so fascinating because like
(06:21):
nothing has sort of stirred that visceral reaction the way
that you know, this love of the Bloomberg terminal emerged.
Speaker 1 (06:28):
Do you think the kind of Jets versus Sharks a
West Side Story comparison is apt? I mean, I guess
what I'm asking you really is finance bros were the
acme of professional brohood. Yeah, for twenty years. It's almost
like I'm wondering this is just a hypothesis. It feels
(06:48):
like finance people have essentially been replaced as in the
hierarchy of like where value creation and becoming incredibly rich happens.
That's been kind of happening for a while. But I
like the AI moment in the last couple of years
has really accelerated there. So do you think this is
like a howl in the wind of saying like no, no,
like no tech bros, like we still got us finance bros.
(07:10):
Is that fair or what? Do you think?
Speaker 3 (07:12):
I think, Yeah, that's an interesting idea, Like I do think,
like one common criticism from the tech bro side was that,
you know, the finance people were just they just wanted
to stick their feet in the sand. They were ignorant of,
you know, how important and how critical AI advances were
going to be, that they were stuck in their old ways,
(07:35):
that it was naive of them to think that there's
any piece of software that's irreplaceable. But yeah, I mean,
I think, like what's so interesting about these two groups
is that the people who work in finance just have
this love of Bloomberg, Like it is like it is
like a phantom limb for that. One person I talked
to told me like using his terminal was like crack,
(07:56):
which I was like, okay. And on the other side
of that, like people worship AI.
Speaker 2 (08:03):
So there's this like extreme.
Speaker 3 (08:05):
Like almost religious like passion on both sides, and I think.
Speaker 2 (08:09):
That's sort of the root of why we saw.
Speaker 1 (08:11):
This clash that's so well put. You know, a friend
of mine worked in a scrapyard in France when he
was a teenager. Briefly we told me the other day
that there was an occasion when a guy who was
like a truck driver brought his truck to be scrapped
and he'd driven it for twenty years, and as it
was kind of entering a scrapyard, he just collapsed on
(08:32):
the floor and was screaming like a child in the
fetal position, saying look by to his truck. And we
were talking, my friend and I about this and how like,
as a person in the world, you ultimately spend like
the majority of your waking hours working, whether that's like
driving a truck or on the Bloomberg terminal, And so
that like extreme like nostalgia and personal identification with these tools,
(08:56):
whether it's a truck or a terminal, it's kind of interesting,
but is there something different about the terminal from say salesforce, Like,
what do you really think makes this like such a
rubicun for finance people.
Speaker 2 (09:07):
I mean, it's a good question.
Speaker 3 (09:08):
I think the fact that it's been around so long
and it's had such staying power throughout that period of
time is important. I think the fact that it is
so expensive also is important. You know, when you reach
the point in your career at which you get a
Bloomberg terminal, that's a big deal. That's sort of like
a rite of passage for you, and then you have it,
(09:30):
and it's sort of a status symbol. So I think
it's it's come to represent all these things. But I
also think the reality is that they do love the functionality,
like they just they've sort of come to depend on
that functionality and they couldn't really live without it. And
I think it's easy to be skeptical of, you know,
some sort of flashy new AI coming in and being like, oh,
(09:52):
we can do this, Like I think, you know, the
natural reaction is no, you can't. Bloomberg has been doing
this for decades. This AI tool was invented a couple
weeks ago, Like, what do you people know about this?
Don't try to come in and take away our Bloomberg
terminals and give us some shoddy, cheaper vibe coded replacement
because you're taking away like what we need to do
(10:14):
our jobs?
Speaker 1 (10:16):
And did you experiment with the vibe coded replacement? I mean,
what was the take of people who actually used these
products in terms of how close did the perplexity vibe
coded version get to successfully replicating the Bloomberg functionality.
Speaker 3 (10:30):
Yeah, so I think, to be honest, on both sides,
there's an acknowledgment that whatever you can vibe code in
one shot prompt is not going to be anywhere near
the Bloomberg terminal. Like I think even the tech people
realize how I acknowledge that, And I think they would say, like, oh, yeah,
but it's a great starting point and if you put
in a little more effort and maybe it's not all
(10:51):
vibe coding, maybe some of it's real coding, and maybe
you can't get all the way there, but maybe you
can get close. But these sort of like one shotted
vibe coded demonstrations, it's hard to tell because the people
that post them, you can't sort of go it. They
don't always share the prompt and they don't always share
the experience. They just share like a screen grap and
so a lot of what was being shared is these
(11:13):
tools for like tracking stocks and financial analysis, which people
were right to point out is just one part of Bloomberg.
Like a big question that came up is sort of
like the real time data inputs the Bloomberg gets. Like
Bloomberg has these proprietary data inputs, it gets them faster
than anybody else. It gets more data, one might say,
(11:34):
better data than anybody else. And yes, there is stock
data and commodities data available on the Internet, but it's
maybe not the same breath and depth that Bloomberg gets.
So I think, like no, to answer your question, like
the one shotted, vibeut it apps like don't come close
to what the Bloomberg terminal is. But again, like the
tech people would say, like bo we.
Speaker 2 (11:56):
Can get there.
Speaker 1 (11:57):
You know what I mean, you are another story couple
of weeks ago, meet the company's vibe coding that own CRM.
What's your like medium term perspective? You do you think
software companies are like literally gonna go away or do
you think a new crop of more targeted software companies
will emerge to have less legacy baggage and then probably
(12:17):
be consolidated into selfwaking commorts. Again, like, what do you
think is gonna happen here.
Speaker 2 (12:21):
Yeah, No, it's a good question.
Speaker 3 (12:23):
I mean, like there's been talk of the death of
software for a really really, really really long time, and
it has been resilient and it has stuck around. And
you know, three years ago when Chatchibt first came out,
everyone was like, oh, it's the end of software, like goodbye,
and that I think that hasn't really happened. Although, like
(12:43):
I think there is like if you're a legacy SaaS
company and you can pivot into the modern age and
you can invest really deeply in AI, invest really deeply
an agents, provide that to your customers and sort of
be a value proposition that's you know, not dissimilar from
what they could get from a more AI native startup,
(13:04):
then I think that those companies have a chance of succeeding.
If you're a legacy sasas provider and you kind of
stick your feet in the sand and you just count
on the fact that your customers are sort of locked
into you. They have years alone contracts, it's going to
be really hard for them to exit your platform. Then
maybe you're in a situation where you're getting in trouble
in a few years. But I do like, I think
most of the SaaS companies know they have to pivot,
(13:26):
Like AI is AI is the big thing. AI is here.
Everybody in the software world knows that, and so they're
all sort of jostling to position themselves as the provider
of AI and AI native companies are in a like
you could argue they're in a better position to do that,
but legacy companies have at yeah, big customer bases, more
(13:49):
of an understanding of like what you know, business requirements
and stuff like that.
Speaker 2 (13:53):
So I don't know how it's all going to play out.
Speaker 3 (13:55):
People like compare this sort of AI moment a lot
to like the dawn of the Internet and sort of
like the dot com must and you know, there will
be a lot of new companies that come up and
are great, and there will be other companies that sort
of go on the corner and die and other companies
that survive.
Speaker 1 (14:13):
Yeah, we'll just have to say, Well, the company, which
is in many ways at the very center of all
this is in video when we come back, Isabelle tells
us all about her trip to Invidia's develop a conference
last week, what Jensen Huang has called the super Bowl
of AIM. So before the break. We were talking about
(14:57):
Bloomberg and software and whether AI will eat softwa where,
And I want to talk a bit more about that
in respect to what you learned this week at the
Nvidia conference. Before we get into those specific topics, what
was it like and describe the scene.
Speaker 3 (15:11):
The energy at Nvidia GGC is very unique and it's
kind of electric. It takes over the entire city of
San Jose, thirty thousand people.
Speaker 2 (15:23):
I interviewed the mayor of San.
Speaker 3 (15:25):
Jose last year about this and he was like, the
coffee shops make their entire year's rent in the course
of a couple days. Of course, that means like if
you want to get a cup of coffee, you are
waiting in line for like an hour. You're waiting in
line for an hour for everything to like get into panels,
to get into buildings, to get coffee, to get a
granola bar. It's, you know, like you're out there in
(15:45):
the wilderness, like you have to fight to get like
a sandwich.
Speaker 1 (15:50):
No, the Fortralling Company doesn't provide any free coffee and sandwich.
Speaker 4 (15:53):
This is no.
Speaker 3 (15:54):
I mean it's like it's wild though, I mean it
does like people say, it has this like rock concert
like sort of atmosphere. There's music and there's you know,
in the evening they like bring out shot luges. There's
robots everywhere of every different kind of roy you can imagine.
Because in Video is like really invested in this physical
(16:15):
AI thing.
Speaker 2 (16:16):
They're also really.
Speaker 3 (16:17):
Invested at autonomous driving, so they have like all these
like different cars. Like everything in the city is decked
out in in Vidia signature green and it's sort of
like Disneyland for like the AI industry, Like there's just
so much to do and see and play with and
it's just like a totally different world. Everyone is super
(16:38):
excited about the technology. Everyone is super bullish about it.
So yeah, it's it's sort of like this little like
hype of Vortex.
Speaker 2 (16:45):
It's so easy to get sucked in.
Speaker 1 (16:47):
Well, how do you avoid getting secked in? What the
kind of what were the more critical questions that you
had about what was going on?
Speaker 3 (16:52):
I suppose yeah, yeah, I mean I think like if
you think about Nvidia as a chip company, like there's
sort of been this inflex point in the chip industry,
which is this shift from training to inference, Like for
the last few years, like the bulk of compute has
been used to train these really big, large language models,
(17:13):
and now we're getting to the point where a lot
of compute is being used to run these large language models.
And so in Vidia's chips historically have been really, really
really great.
Speaker 2 (17:24):
At the training.
Speaker 3 (17:25):
Like that is what propelled them to their current valuation.
And I think like there were always questions about what
does it mean for Nvidia in the era of AI
and friends, And in Vidia is an incredibly innovative company
and it comes from the top. Jensen is just an
incredibly curious, innovative person. They have a very flat structure
(17:49):
as a company, not a lot of middle management.
Speaker 2 (17:52):
Jensen and sort of like all the top leaders have
a lot of direct reports.
Speaker 3 (17:55):
There's a lot of autonomy, but there's just this constant
push to just like innovate as fast as you can
and always be on the next thing, and always be
on the next thing, and always be on the next thing.
So they acquired an inference chip startup called Grock recently,
so a lot of the conference was.
Speaker 1 (18:13):
There's nothing to do with Elan's Grock, This is Grock
with Q or other case.
Speaker 3 (18:16):
Yeah, it's incredibly confusing and a weird name to have
twice and what is stream But yeah, so there was
a lot of talk about how they're integrating sort of
like Grock's offerings into in video offerings and you know,
just this this big push to you know, stay on
top of things on the compute side, and then on
the flip side of that, there's also you know, part
(18:38):
of this conference is for Jensen to get out there
and you know, prove that demands for AI workloads is
going to be greater than ever before. And that's what
he says every year, and that's what he has to
go and prove out every year because that's what's sort
of spurring their demand. And so there was a lot
of talk about the software side and what companies are
doing with AI and what they're going to be doing
(19:00):
with AI, and there was a lot of talk about
something called open Claw.
Speaker 1 (19:06):
I want to ask you about them, and particularly how
it relates to the Bloomberg and the software story we're
talking about earlier. Just before we get there, I want
to read a quote from your newsletter. Today's maturity curve
in AI is much higher, and the explosive growth and
improvement of AI coding tools has arguably given a gentic tech.
It's killer app Still, the technology continues to speed far
(19:27):
ahead of business adoption. Talk about that. Why is business
adoption slower than technology development?
Speaker 2 (19:33):
I mean there's a lot of reasons for that. One
is just because technology development is so fast. Silicon Valley
is moving so fast right now with the models are
coming out all the time, they're always better. And then
there's you know, last year, agents were just starting to
become a thing. So I remember being a GtC.
Speaker 3 (19:51):
Last year and everyone was talking about agents, but also
nobody was really using them. There was just this understanding that, like,
agents are going to be the next thing. And it
was this transition from we have chatbots and we can
ask them questions and we can get answers and this
is incredible to Okay, agents are actually going to do
things for us. And I think last year was just
(20:11):
sort of like a buzzword. This year is actually starting
to happen in businesses. But the tech is sort of
chugging along even beyond that too. It's not just agents
that will do a task for you, it's now these
sort of complex groups of agents that are delegating tasks
to each other and can access your documents and files
(20:35):
and business data and run for a really long time
and sort of do these complex workflows and then you know,
report back to you. So it's it's even beyond just
doing tasks to like you know, doing almost like entire jobs.
But I think that's where businesses are still sort of
like the initial agentic deployment point of just like figuring out,
(20:57):
like where do I even like trust this type of
offer to like do a task for me let alone,
like you know, give it access to like my entire
operating system.
Speaker 1 (21:06):
And where does open claw fit into all of this?
Animo Claw which was announced at GtC.
Speaker 3 (21:12):
Open Claw is another thing that just sort of it's
so hard to keep up in this industry.
Speaker 2 (21:18):
Someone was saying the other day.
Speaker 3 (21:19):
Like you have to be fully unemployed to keep up
with anything that's going on in AI, and like I
can really respect that.
Speaker 1 (21:27):
I can relate to that too. I mean I do
this podcast twice a week, but it's just the deluge
of information.
Speaker 3 (21:32):
Wild It's like one day and there's this thing called
open claw, and it's really confusing because open claw is
about creating these things called.
Speaker 1 (21:42):
Clause clause agents. Yeah.
Speaker 3 (21:45):
Yeah, Claws are basically these long running autonomous agents. And
open claw it's it's an open source standard for building
these sort of like complex orchestrations of all these different
age So you can set up a claw to do
something and that claw will like tap a bunch of
series of subagents delegate tasks. You can give it access
(22:08):
to your files. It can do things for you, and
it can do it like continuously over a long period
of time. Like you could do things like summarize all
the news of the week and shoot me an email
every Monday at noon with what's going on, and it
will just sort of keep running and do that. Or
you know, you could set it to do a task
overnight and then come back and it's done in the morning.
(22:29):
So I think like the biggest sort of shift with
open claw is this move from I'm talking to an
agent and I'm prompting an agent and it's giving me
a response, and then I'm giving it a response, and
it's sort of this like real time interaction collaboration versus
with clause, you're really just sort of like sending it
off okay for a while, and then it's coming back
(22:54):
to you later.
Speaker 2 (22:54):
It's like it's asynchronously working with.
Speaker 1 (22:56):
A single natural language prompt or a more complicated promo.
What's the use case of open clure that you've seen
that you find intriguing.
Speaker 3 (23:03):
Yeah, yeah, no, I mean that's a great question, And
that was exactly my question when I was at the
conference and in video had this experience called build a Claw,
which was this tent where everybody got to go inside
and build a claw, and I think like it was
really interesting because I went to go build my own claw,
and I just said to the video exact I was
(23:24):
talking to, I can't think of something that would need
to be a claw that I couldn't just do with
an agent or a chat bot. And it was just
it's this hard conceptual shift that needs to happen. It's
like it's sort of like the same way when chattyb
(23:44):
Tea came out, we would all talk to it the
same way.
Speaker 2 (23:47):
We talked to Google.
Speaker 3 (23:48):
We would just put in a few keywords because that's
the way we were used to interacting with those systems. So
now it's like when we get the opportunity to use
a claw, we're kind of interacting with it the same
way we would do with chatchybet. Like I was with
my editor and he was like, oh, help me plan
a road trip, and it could do that, but it's
like it's capabilities are so far beyond that that again
(24:10):
it's hard to conceptualize, like how to actually do this.
Speaker 1 (24:13):
Do the invideoor exec give you any advice on what
type of clore to build or were the other people
that build? Yeah, I mean I that you came.
Speaker 3 (24:20):
I remember talking to this one marketing leader who said
she had like, you know, a dozen different ideas for
clause and a lot of it is, you know, scanning
information on the internet. So her idea is, you know,
go on social media and read all these news sites
and read all these newsletters and report back to me
(24:41):
every morning.
Speaker 2 (24:42):
What are sort of like.
Speaker 3 (24:43):
The key themes of you know, what we should be
putting our marketing and thought leadership content around, and then
like help us like make sure that whatever we plan
to put out that day is like sort of like
drafted around that. Another example was an Nvidia exec was
telling me that they had this college student come through
and she was job searching, and so she was like
(25:04):
kind of claw helped me, you know, identify jobs to
apply for. And he was like, yes, that's like a
great chop out question. But like take it a step further,
like once it finds the role, then have it like
identify the right skills and then like optimize and tweak
your resume. And she was like, okay, great, and then
in videos, I can then take it a step further
(25:25):
and then give it access to your LinkedIn and then
give it access to your data and like have it
build out these coverlead It's like, have it do these applications.
And so it's like you just have to have that
mindset shift of like always take it a step further.
And I think that's not totally clear to all of
us yet unless you're, like, you know, an AI.
Speaker 2 (25:45):
Super super super user.
Speaker 3 (25:46):
But even since the AI super users that were at
the video conference, I think we're just like having trouble
conceptualizing like the real capabilities of what we can.
Speaker 1 (25:54):
Do with this. Jensen said, this is the new chat moment.
He said that we're having the che cheapy team moment
for robotics, so having one check cheap team.
Speaker 3 (26:05):
He was like he was really really all in on this,
I mean all on open claw.
Speaker 4 (26:11):
Yeah.
Speaker 3 (26:12):
But okay, so here's the thing about open Claw we
haven't talked about, which is that like there's a lot
of security challenges, and I did not find anyone at
the video conference who was comfortable using open claw for
any context in their actual like work slash business. So
when people want to use open claw, a lot of
times they'll go out and get a separate computer and
(26:34):
just run it on that computer, like.
Speaker 1 (26:36):
A clean computers.
Speaker 3 (26:37):
So it's like it's literally just like a separate computer. Yeah,
and just for open claw, because if you have open
claw on your computer where you have all your business
data and you're giving it access to things, it can
really I mean there's been a lot of stories of
open claw deleted all your emails or if you know,
if you have a Claw that's on the internet and
(26:58):
interacting with people, you know, it's not that difficult to
like prompt injected and then open clock can like give
away or credit card details. So there's so many data
concerns about open claw, which is why it is not
enterprise ready.
Speaker 1 (27:11):
And the video are trying to basically with Nemo Claw,
which is their product, create a version of layer on
top of the open source open flaw to make it
business safe.
Speaker 2 (27:21):
Yes, yeah, yeah, that's what they're trying to do.
Speaker 3 (27:23):
I don't know if they're fully there yet I think
there's this is this tack is so new, there's still
so many concerns because a lot could go wrong, clearly,
but I think they're excited about what could go right
and they just sort of want to put it in
that direction.
Speaker 1 (27:38):
The other thing which came up, I think a fabit
was space, right AI and space?
Speaker 4 (27:42):
Yeah?
Speaker 1 (27:43):
Was that? What else kind of surprised you and caught
your eye while you were there on the ground.
Speaker 3 (27:46):
Look, the amount of announcements and video puts out at
GtC is crazy. I mean there was there were more
than a dozen.
Speaker 2 (27:52):
Press releases, Like it's just wild.
Speaker 3 (27:56):
But yeah, I mean computers going into space, that's one
thing you know in videos playing a lot in the
quantum landscape, Like, that's another thing we should be paying
attention to. Autonomous driving is a really big focus, and
I think that caught my eye because you know, in
video they announced a partnership with Uber to sort of
(28:17):
invest in this robotaxi fleet and it's coming to a
bunch of cities around the world in the next couple
of years. And you know, you can imagine a future
where like you drive to work and then while you're
in your office, you send your car out to be
an autonomous uber for the day, and then it drives
back and picks you up.
Speaker 2 (28:37):
So that was another interesting thing.
Speaker 1 (28:40):
Just coming back to the to the beginning of our conversation.
I mean, the kind of open law world you're describing
does sound like a world whereas seems like there will
be serious competitive threats to people paying thirty thousand dollars
a year for Bloomberg.
Speaker 3 (28:54):
Yeah, yeah, I mean you could definitely make that argument.
You know, you could also make the other argument that,
you know, there's a reason Bloomberg costs thirty thousand dollars
and it's incredibly secure and they have spent many, many
years investing in you know, the algorithms that model the
pricing for this, and that I think, you know, you
(29:16):
could build an alternative with open claw and people will
And you know, maybe if you're just sort of like
a less serious retail investor, like that will be great
for you because you're someone who's never going to invest
in a Bloomberg terminal. But if you're like a finance company,
it's hard to imagine you would walk away from like
(29:38):
the security and consistency of something like a Bloomberg terminal
At least in the near future.
Speaker 1 (29:44):
I think brand metters, and I think about on the
legal side, for example, like sure, if you're a finance company,
you could use some you know, legal AI software like
or you could pay Lathan Watkins one thousand dollars an
hour perer because you know you've got Yeah.
Speaker 3 (30:01):
Yeah, And I mean one thing we haven't touched on
either is the fact that, like you know, Bloomberg is
integrating AI. They have AI features of the terminal, and
so I think like that's their push to sort of say,
like this is not a point when you need to
go out and find an alternative, like we are everything
we've always been to you and more and we're worth
that price tag. So yeah, I mean again, there's arguments
(30:22):
on both sides, which is again why it's started up
playing so much angry debate online.
Speaker 1 (30:27):
Isabel, thank you, thanks for coming straight from the Red Eye.
A good luck with the rest of your day. I
gather you're going into the office now to write some
more stories.
Speaker 3 (30:34):
Yeah, yeah, I'm about to. Could I go write some
more Open Claws stories?
Speaker 4 (30:38):
So thanks for having me, h for text stuff.
Speaker 1 (31:02):
I'm as Volosian. This episode was produced by Eliza Dennis
and Melissa Slaughter. It was executive produced by me Julian
Nutter and Kate Osborne for Kaleidoscope and Katrina Norvell for
iHeart Podcasts. The engineer is Charles de Montebello for CDM Studios.
Jack Insley mixed this episode and Kyle murdoch Rodart theme
song and please do rate and review this show wherever
(31:22):
you listen to your podcast
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