Welcome to the AI Chat Podcast. I'm your host,
Jaden Schaefer. Every day I cover cutting -edge
AI news and talk with the leaders behind it,
breaking down what it means for your life and
business. Anthropix Mythos AI is finding Microsoft
bugs faster than Microsoft's engineers can patch
them. Google's SynthID watermark survived 300
edits. but fragmentation might actually make
this completely useless. We'll get into that.
Encore AI just raised $30 million to turn sales
call transcripts into voice agents. This is an
interesting pipeline as far as the data goes.
Writers right now are embracing typos, myself
included, and all of the idiosyncrasies basically
to fight the AI writing that we're seeing everywhere
that has just become, you know, basically a plague
on the entire internet. Sayer is going to acquire
Oasis security for a billion dollars to police
AI agents identities. If you have tasks that
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all the different AI models in one place for
that same price. Let's talk about what's going
on with Anthropix Mythos. They have a... Bug
Hunting AI, and it found 90 critical and 141
different important bugs in Microsoft SharePoint
just in April. And this is basically the problem
here is that it's finding these bugs faster than
Microsoft's engineers can patch them. So Microsoft
shipped 600 fixes on July 14th, and their internal
meetings show that the company was racing a May
31st deadline before hostile governments build
equivalent tools. And I'll also say that this
isn't the only thing. Microsoft SharePoint isn't
the only thing it's been working on. It has found
hundreds of critical bugs in Microsoft. 365,
Microsoft Teams, Microsoft Copilot, all of that
since the beginning of the year. So I think they
have about 300 moderate severity SharePoint flaws
that are still queued for patching. So I mean,
this is kind of a big deal. And on July of this
month, or the 14th of the month, Microsoft released
patches for over 600 bugs, only seven were low
or moderate severity, and one was already being
exploited by hackers in the wild. So I mean,
it literally found something that was actively
being hacked. The Five Eyes Intelligence Alliance
warned in late June last month that the window
for defenders to outpace AI -equipped attackers
would close within months. Internal Microsoft
documents show that it might have already closed,
right, because we already have one exploit being
used. The real danger, I think, is that Mythos
can chain multiple small bugs into working exploits
that humans miss. So Vin Nugent, who's a senior
anthropic advisor and a former NSA AI chief,
said that microsoft's standard triage system
which is patch critical flaws first low severity
last no longer works when ai can weaponize the
bottom of the queue so the race is definitely
on and speed alone might not be enough right
now we also have google's synth id watermark
so basically this is an invisible watermark embedded
on ai generated images primarily from google
but there's some other a bunch of other companies
have kind of all worked together to adopt this
not everybody has i think grok if I'm remembering
correctly, does not do this, but many others
do. So, um, when they were, when they did this,
these AI generated images, um, when it had the
synth ID watermark, apparently it actually survived
300 rounds of compression and resizing and real
testing. And so, and it still was able to detect
that an image was AI generated. So people might
say like, Oh, look, I'm going to, you know, take
this AI generated images image. I'm going to
compress it. I'm going to resize it. I'm going
to, um, zoom in and like, do you, you can. try
to edit it in all sorts of ways. But that watermark
is still detectable, which is really cool. And
that Google says proves that their tech is way
more durable than they were expecting. I think
there's still one big problem. And that's Google's
detector can't read watermarks for open AI runway
or NVIDIA. So I believe if I'm correct, they're
working with meta on this, and maybe a couple
other players. But even though they're using
the exact same technology, OpenAI Runway and
NVIDIA, like the detector doesn't go cross platform,
which is kind of weird. So SynthID is obviously
really impressive. And with those 300 compressed
cycles on both fully AI generated and AI edited
images. It was only breaking after a 20 % border
crop was added on top. That was the only thing
that was killing it. Google limits synth ID verification
to about 10 image checks per day per user, and
they throttle faster lookups on similar images
to block attackers from reverse engineering their
system. It's kind of like when you, when Anthropic
is complaining about everyone going and doing
distillation attacks, right? They're like, everyone's
asking Anthropic questions, getting the answers
and training their AM models on it. Google's
worried that people are going to use the verification
like hey is this was this generated with synth
id to reverse engineer how they're doing i don't
know if that's really a long -term play because
eventually right you're going to get enough data
and figure it out but um for now there it's kind
of a closely guarded secret it feels kind of
like it's going to be like these captchas how
captcha has had to evolve a lot right it used
to just be like really simple letters and then
it got more complicated and then it got turned
into like identify all the bridges in this photo
and you know zoom this uh you know spin the three
model till it lines up in the image. Like there's
all these crazy things that have been invented
for captures. This is kind of what I feel like
synth ID is going to become opening. I runway
and NVIDIA have each built their own versions
of watermarks. Um, but they all have a little
bit different of implementation. That's what
I was saying. Like it doesn't actually go cross
platform. And so there's a bit of a fragmented
landscape right now. And these detectors, they
can only really detect their own watermarks,
not everyone else's watermarks. The thing that
I'm the most curious about, and I don't actually
have a direct answer to this, that, that I I
would be curious, though, is if it's actually
able to, you know, you go to like Google generate
an image, maybe it looks like a great image,
just go to an open source model, give it that
image and say regenerate this. If it would kind
of kill the synth ID on top, and I would guess
that it might actually kill it. So For that reason,
I mean, half the time I'm generating images,
I'm like screenshotting, you know, another image
or another graphic or something that I like out
in the wild. And I'm like, hey, use this as like
an inspiration and change it slightly. And so
that's how I use like chat GPT to generate images
a lot of times. And I'm worried it's going to
be the same thing, which basically makes these
image generating synth ID things useless, because
for a majority of, you know, bad actors out there,
they'll be smart enough to figure that out. And
99 % of people that just use these AI image.
generators in a you know responsible or good
way well it doesn't really matter and so at the
end of the day yeah i'm not sure if it's gonna
make a huge difference if i'm you know being
honest sorry for the pessimism okay encore ai
has just raised 30 million dollars to build voice
agents they're all going to be trained on real
sales calls that have actually closed deals which
is fascinating right because we have all these
data sets i have a friend in particular and he's
got a company and he's got a bunch of sales people
that help close deals for his cleaning company
and what's interesting is he uses go high level
and every single call is recorded for the whole
conversation. So he has transcripts of every
single call. And yeah, he knows which of those
calls actually ended up closing. You can also
even if he wasn't tracking that bit of information
in particular, you could usually just go read
the transcript or have AI read the transcript
and decide which ones were closed. But that is
fascinating, right? It's like determining who
the top sales reps are, which ones are actually
closing, using those transcripts and training
models to be more like those. So fine tuning
models to actually be good at closing deals.
This startup in particular, Encore AI, they're
getting their call recordings and they're mining
all of that to identify what the top performers
say that move customers forward. And so, yeah,
this is... in my mind, really, really smart.
The annual recurring revenue has grown more than
5x since they started and since they did their
seed round, which was about 18 months ago. They
now serve over 40 enterprise customers. Most
of those are financial institutions that they're
servicing right now. This was started in 2022
as ESAIT .io, and then they rebranded to Encore.
Later on, I think one of their advisors recommended
it because ESAIT is not, I don't know, very recognizable.
In any case, they... analyze different customer
interactions stage by stage to find revenue leaks
and friction points. And they feed those insights
into both AI agents and human employees for coaching.
So what's interesting to me is it doesn't just
grab that just like the pure transcript. and
try to copy the whole thing. But it breaks it
into stages. It's like, okay, we're in, you know,
maybe it's like a, I don't know if they do cold
calling, but let's say it's like cold calling.
It's like, you got to get the person to stay
on the phone. And it's like, then you got to
get them to be interested in the product. Then
you got to give them like a hook. Then you got
to like, you know, get rid of any sort of issues
they might have with your product. Then you got
to sell them on the price, right? Like these
are these different stages in the sale that you
got to go through. And so it's breaking the transcripts
down into all of those different pieces to, you
know, identify it that way and kind of break
it into chunks. I think this is so fascinating.
Encore's edge over Salesforce and a bunch of
other CRM giants is that the call recordings
live outside of their platform. So financial
services is, I think, one of the smartest areas
that they could get into for this. Banks right
now and also insurers already record every customer
conversation for compliance. We've all heard
it when we're on the phone and it's like, this
call may be monitored for quality assurance purposes,
right? And so Encore right now is going to be
able to plug into that infrastructure without
forcing a renegotiation of how CRM data gets
handled across every customer deployment. And
if they're able to actually train it on, like,
let's say they go to Chase Bank and they're like,
hey, Chase Bank, you already have all the transcripts.
We're going to use your transcripts. So we understand
how your top salespeople actually convert people.
Right. So and if they can just keep that data
with just Chase Bank and they're not like training
off of that and giving it to, you know, Bank
of America or something. else, that's a really
valuable because Chase Bank gets, you know, the
best their salespeople are able to do. And Bank
of America gets the best their salespeople are
able to do. And they're not worried about that
data or that, you know, confidential information
leaking. I think this is incredible. And so when
you have something like Salesforce, currently
Salesforce and others like that are a little
bit more centralized, and they don't have those
kind of out of the box, you know, custom client
solution. So very cool. Right now, writers and
editors are deliberately breaking conventional
style rules. We're all getting rid of em dashes.
We're all adding typos. Well, I mean, I actually
just naturally have a lot of typos. So that's
just me. My wife always rolls her eyes at me.
But this is actually becoming something that's
more and more popular. And it's kind of funny
because in a weird way with this podcast, I've
always kind of had that same mantra. A lot of
when I first started this podcast. Prior to this,
I actually ran a bunch of 100 % AI generated
scripts and speaker podcasts for a different
startup I had. And I was just doing it for, you
know, lead gen or whatever. And they were kind
of like educational episodes, evergreen content,
not news like this is. But anyways, from the
very beginning, I always knew that this was a
possibility. And I always said, look, I got to
have a real person, myself, my real voice on
this podcast talking because people are going
to want to hear my background, my stories, my
anecdotes. And even to the point where I was.
like pauses and ums and buts and like little
i don't know human things that you put in there
people want to hear that because they know that
this isn't an ai talking to them i for one i
mean even if the voice because the voices used
to be bad and now they're actually really good
like if you use 11 labs v3 the voices are incredible
sometimes i can't tell it's a it's a real um
or it's just an ai if if i'm not careful and
i've had calls i've i've heard music um like
i can detect it but guys i'm serious like i'll
get I'll listen to a song the other day. I added
it to my liked folder. on YouTube Music and realized
probably like five listens in. I'm like, this
is probably AI generated. So anyways, I think
this happens more than we would like to admit.
I mean, this stuff is getting a lot better. But
my mantra has always been like, look, people
are going to want a real human. And this is what's
happening with writers now. They're adding literal
typos and kind of these messy first person stories
to make all of their writing look more unmistakably
human. It's not even just like looking human,
but unmistakable. Like we want people to know
this is human. ChatGPT doesn't output text like
this. It doesn't use all lowercase. So this is
really interesting. One publication in particular
said that they got a thousand pitches in May
and almost all of them were AI generated. Pitchfork's
editorial head has banned AI from review submissions.
That was starting in 2024. And I think that was
like two years ago. But novelists are actively
avoiding a lot of different things. And I mean,
you'll see it on Twitter. It's kind of funny
or an X or whatever, where everyone like finds
em dashes and old literature or they find like
just, you know, funny glitches that Claude always
says, you know, it's not this, it's that right?
Like all those funny things, and they'll screenshot
them from old books. and they're like, oh my
gosh, I can't believe Jane Austen was using AI
to write. So anyways, there's a lot going on
inside of the writing world trying to be more
human. Sierra is a $12 billion data security
company and they're buying Oasis Security for
$1 billion to manage AI agent identities inside
of companies. So right now, basically every company
is putting out all of these different agents
to do work, but they need some tools to track.
who those agents are, and what they have access
to what they're doing. This is a problem that
I think a traditional security software would
be tracking humans. But now that we have these
agents, they also want to track that. And I think
it's interesting, because I've seen some tweets
on x where people were like, they're screenshotting,
I think it was chat GPT, like 5 .6, or whatever.
And It was on cursor. They were using cursor
and they said they were working on a project.
OK, stop for now. Finish this later. And it made
a push after I told it to stop. Why did you do
that? And I was like, oh, I just like was doing
the push. Anyways, these things happen where
these agents, you know, especially if you give
them a task, especially if it's more open ended,
like, hey, just get X, Y, Z thing done. They
do it in their own way. And we don't always know
what made the change, what made the edit, who
did what. And so you can have some of these issues.
Anyways, Oasis was founded in 2022. They raised
one hundred and nine. million. They specialize
in securing non -human identities and they do
it through API, you know, API keys that are logging
into corporate systems without any humans there.
They just raised $600 million, a $12 billion
valuation. And they're now making $150 million
a year in revenue, but they're still not profitable.
They've spent really aggressively. They have
three acquisitions that they just did in quick,
like really close together. This is their third
acquisition in a few months, which is following
them buying Rift and Genie Security. I think
it's interesting when you have a company that's
able to raise so much money. Obviously, they
have a really good team. They have a really good
visionary at the top. But when they make all
these acquisitions, I mean, A, they're smart,
but B, they're growing so fast and they have
so much money, they have the bandwidth to do
it and not to build it from scratch, which is
interesting. There's a huge push right now to
own the non -human identity market before a lot
of these bigger companies like Palo Alto Networks
or Okta are kind of moving into this. And so
that's why I think they're jumping on that. Other
news that happened this week that I just want
to cover the headlines. Google's DeepMind has
just shipped Lyria 3 .5 in flow music with some
better vocals and lyrics. I've talked about Lyria
in the past, not been impressed with it. When
it was first came out, it was like only able
to generate 30 second clips. Then it became,
then it was able to do full songs. And now I
think they're getting better at vocals and lyrics.
So I think this is going to be a big player,
challenging Yudio and Suno and stuff. When it
first came out, it wasn't much to talk about,
but I think Lyria is getting better. I still
like Suno more because they have the entire AI
studio and they have like music covers you can
do. And there's just so much to do with Suno.
But I am excited that the underlying model behind
Google is getting better. Panagram just raised
$9 million to detect AI generated text. It apparently
has 99 % accuracy. It's interesting, you know,
in light of what we were talking about with everyone
using more, I don't know, typos or whatever you
want to call it to seem less AI generated. So
now we have these tools that are really good.
It's interesting because OpenAI in the very early
days. came out, they had their own AI text detector.
And they actually shut the project down because
they said it was too hard to detect AI generated
text. Now, I think we all kind of have AI generated
text detection built into our brains now, where
we're understanding a lot of the phrases that
are used, we're understanding em dashes, but
those things that AI models are going to be able
to get around very easily. I actually have a
whole list of things that AI models frequently
say that annoy me. And whenever I get AI to write
a podcast script or if I get it to go write an
article or I go get it to write a blog post or
content or like basically any work I'm doing
or even like. even websites i very frequently
will say like run through this whole list and
remove every single m dash from the website every
single time that we say x y or z and i just get
it to go like run this kind of audit on my content
now eventually hopefully the models will just
get away from that but uh it is interesting all
this ai generated text detection stuff. I think
I like I hope that it's good, but I'm always
dubious of it because I feel like it's always
a cat and mouse game. Okay, there's funny news.
Martha Stewart has co founded hint, which is
an AI assistant for homeowners. And she has $10
million in funding for this project. So that's
kind of interesting. If you haven't left a review
on the podcast yet, it would help the show out
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But thanks so much for tuning in. I hope you
guys have an incredible day. Make sure to go
check out AI box .ai if you want to get 80 different
AI models all on one platform, and I'll see you
in the next episode.