Welcome to Artificially Intelligent Marketing, a weekly podcast where we stay on top of the
latest trends, tips and tools in the world of marketing AI, helping you get the best
results from your marketing efforts.
Now let's join our hosts, Paul Avery and Martin Broadhurst.
Welcome to episode 14 of Artificially Intelligent Marketing.
I'm getting better at saying that every week.
Martin, I've been practicing in the shower, in the mirror, in the dark, every morning.
Absolutely.
Just getting focused and making sure I can rock it.
How are you, Martin?
For episode 14, are you good?
I'm good.
It's Friday once again and I've had a flaffle for lunch.
That's very exciting.
So, you know, I'm in a good space, you know, mentally, physically, emotionally, just all
of it.
I'm just in a very good place.
That's good.
We need you centered because there's been a lot of AI news this week that we've got to
get through.
So lovely listeners, thanks for joining us again.
We're going to look at our short snippets like we always do, some really good little
bits and pieces in there to cover.
We're going to dive into our chunky main stories, which this week is going to include Apple's
Developer Conference in which we saw the Vision Pro for the first time, virtual reality, augmented
reality headset, but also a ton of other things that involved AI, which they call machine
learning because they have to be different, of course, under the hood.
So we're going to dive into that, which is cool.
There has been a ton of generative image and video news this week.
We've lumped all of that into one big story for us to talk through.
We're going to talk about DeepMind and their announcement around a generalized AI to optimize
computing performance.
And we're going to look at Meta's roadmap in terms of how large language models are
going to be coming to your favorite tools that you already use, like WhatsApp and Messenger.
And the tool of the week this week is going to be Gen2, RunwayML's Gen2, text to video
creator, which is now easily accessible to all.
So with that in mind, let's get straight into our short snippets with some news from AI
startup Kohia raising $270 million to now be valued at $2.1 billion.
We've done quite a lot of guess what?
Another AI company got a ton of cash news, and this is another version of that.
This puts Kohia up in the echelons of Anthropic and OpenAI and several others with very, very
large valuations now based on the amount of cash that they're getting to fuel their large
language model based tools.
Kohia, many of you won't have heard of as much as some of the other companies we just
mentioned, but their technology does underpin some of the writing tools that you might use.
Like I think is it Jasper that uses Kohia?
I think HyperWrite might use Kohia as well.
Yeah, I think a lot of the tools are taking different models from all of the different
providers.
So they're part of the mix.
You'll inadvertently have been using them if you're using any of these tools, I'm sure.
Absolutely.
One of Kohia's things is to try and be somewhat agnostic and allow lots of different tools
to basically leverage it and deploy it how they see fit.
Yeah, they're very much positioning themselves in recent months as being for the enterprise
as well.
That is where they've been doing a lot of their messaging, if nothing else.
Absolutely.
So again, watch that space as we see all of these companies getting ever more money as
private equity and other investment vehicles bet on AI as the next big thing.
Let's hope it doesn't turn out to be too much of a bubble.
In terms of the next short snippet, we're going to talk very briefly about how Mark
Walters from Georgia has decided to sue OpenAI over claims made by ChatGPT that he embezzled
funds, which is absolutely false and it was a hallucination by ChatGPT and it's not real.
So further examples of what happens when ChatGPT makes stuff up and the carnage it can cause.
So that fits in with the story that we mentioned last week, Martin, when a lawyer was using
it for research.
Yeah, the other side of the coin.
I haven't dug too deep into this story, but one could imagine that if you prompted the
tools just right, I reckon I could probably get ChatGPT to make some stuff up about me
potentially and then maybe I can come up with a cool case.
Well, that's the detail that's missing from the story.
I read the report and I've read a couple of them and that's the detail that is ultimately
missing.
What was the conversation thread?
That is the whole essence of it.
I know that it was a question around, I don't have it to hand now, but it was a specific
legal case and this radio host wasn't involved in it at all.
And I think the person went back and asked it to clarify the details and it kind of doubled
down on it as well, which I think made the situation slightly worse.
Right, right.
Cool.
Another short snippet is another funding announcement, so this is Lightmatter that received $154
million in new funding.
This is an interesting one because Lightmatter is developing a form of optical computing,
so it's a mixture of hardware and software that aims to be more efficient, faster and
cheaper but to run AI models quite specifically.
I'm sure there'll be other applications, but the one they're focusing on at the moment
is that.
This is hot on the heels of some of the discussions we've been having, Martin, about how much
energy it takes to run the compute power needed to run these models, how much water is required
to cool the server farms and all that stuff.
So this is a company that's trying to help solve for some of that and obviously convincing
a number of other people with money that it's a goer.
So they're hot on the heels of some of those challenges.
There was a report from Salesforce this week that found that 51% of marketers are using
generative AI at work with the most popular applications being, as you might have expected,
content and copy creation.
But I think this is part of an emerging trend that I'm starting to see when I'm talking
to more and more people in the market that they not only are aware of these tools, but
they've tried them and they're playing with them and they're seeing how they might fit
into their workflows.
Yeah, I saw something else this week that said people are on average using ChatGPT six
times and then going, I'm done with it now.
Yeah.
Which certainly isn't my, I'm using it six times a minute at the moment.
But that was an interesting thought that actually the early adopters are all in on it.
But now as we're starting to see more and more people get familiar with it, they're
using it, but not really diving in with both feet.
That's a good question for me to ask folks because I definitely think the tools are quite
iterative.
They're good at certain things and it's quite hard to get good outputs out of them for other
things.
And I do think you have to have a bit of sticking power in terms of figuring out how you're
going to make them work for you.
So I guess that fits because if you don't have that sticking power, you might be like,
oh, it's pretty useless.
As an example, I've been experimenting, I might have mentioned this before.
I'm using a tool at the moment called Audio Pen, which is pretty cool.
You record a short audio snippet, like I think it's up to three minutes.
So I'm basically using it for idea collection when I'm walking the dog on the stuff at the
moment.
And it doesn't just transcribe it, but it uses probably GPT-4, I don't know, a large
language model to turn it into coherent text.
So if you wanted to share it with someone else or read it yourself later and have it
make sense rather than the rambling that you get when you do a voice note, it's actually
really quite good for that.
But what I found is I really wanted that same thing, but to be able to draft emails for
me, but the email, so I'll record an audio snippet and then I'll push it into chat GPT,
but the emails are never in my voice.
It sounds, they're either way too corporate or if I'm like, hey, could you chatty this
up a bit, it's like, hey dude, some ideas.
So it's like, it goes all the way the other way.
Like I'm either like running, I'm either CEO of like a $25 billion company or I'm running
a surf shack and it doesn't seem to know.
There is no in between, but I think that that's how I see you.
You're a $25 billion CEO that is running a surf shack.
And I'm always like, he just seems poorly primed for either of those positions to be
honest.
I couldn't agree more.
I think it depends on what day I run it.
It knows I'm big time Charlie on a Monday, but I'm down the beach cats and some waves
on a Tuesday.
So that's probably how it's, it's figuring it out.
It's a great example of the voice note, because we spoke about this with Whisper and the Whisper
integration and Zapier.
And I think that's maybe where you can play around with that a little bit.
Try it with Zapier, try the voice note, save it to a Google drive, stick it into, because
that, if you, I guess, if you were to in your prompt, put some examples of your existing
email tone, it would then start to reflect that.
So that would be an interesting one to play with.
We should, we should, we should take this offline and give it a go.
Yeah.
I think definitely there must be some sort of tool or Zapier that you can build that
in essence rhymes at every time on your voice by actually automatically giving it quite
a comprehensive prompt.
And then of course, at some point when Copilot goes live and Bard is integrated into Gmail,
one assumes this won't be a problem at all anyway.
So certainly not a tool I would build to try and commercialize because I think in three
months it would be dead in the water.
But in terms of a quick Zap to create that might do some cool stuff that currently I'm
not able to do, completely agree.
While we're talking about Bard and Copilot and all these things, the other short snippet
this week is that Bard can now execute code as well as write it.
Execute code as well as write it.
Martin, you pick this one up.
Can you elaborate a bit for us on that?
I mean, it's as the story says there, to be honest, it's able to, it's given it more reasoning
capabilities which is just extending its powers really.
I didn't get a great deal more from it than that.
Where is the article?
Google has unveiled a major new update to its AI chatbot, Bard, that significantly improves
its powers of logic and reasoning.
It has a new technique called implicit code execution that enables Bard to detect computational
prompts and run code in the background.
So that's what it's doing and the result is that Bard should theoretically be able to
respond more accurately to mathematical tasks and coding questions as it will have already
tested the outcomes that it proposes.
So in terms of really ramping up its capabilities, I think that's quite a step up.
That does sound interesting, but it's not.
It deploys code in the wild.
It's like, here's some code and by the way, make it so that it will actually run on a
server or as a web app or whatever.
Yeah, correct.
It's just kind of running it in the background and throwing the result back to you.
Cool.
While we're on this topic, because we love a tangent here at artificially intelligent
marketing, as you will know, dear listener, and we appreciate your patience because of
that, I was playing with chatbot, so HubSpot's chat tool this week and I hadn't really gone
back to it for like three or four weeks because basically everything I asked it to do, it
couldn't do.
It kept sort of saying, I know what you want, but I can't do that yet.
Or it went, I don't know what you want and neither of which are responses that were particularly
useful to me.
But they've changed how it works.
So it's not on the old URL anymore.
It's been redeployed in some other way.
I think they're moving into that part where maybe they might be ready to move from alpha
into beta because it just got a ton better.
Interesting.
Like miles.
So I had a new business call this week and I was like, I just wrote in natural language,
tell me about company X and my goodness, it told me how many employees, revenue.
It told me a short summary of a company.
It told me what technologies they were using to underpin their marketing and sales tech
stacks.
It told me that they were on WordPress and all this stuff, all in one output.
That's interesting because that's the content that you get from the AI insights that HubSpot
has been providing anyway for a long time.
So the data enrichments that HubSpot has been providing through HubSpot Insights, they're
obviously integrating that knowledge base and database into Chatspot now.
I've not had to play with it like you.
I kind of left it for a few weeks.
So that's interesting.
I will definitely get into it.
And that was the type of question I was asking it previously and it was saying, I know what
you want, but I can't do it.
I think the other thing is it's the little things that it's adding in.
So it also tells you how many followers they've got online.
It tells you how many locations they've got.
Then there's some handy buttons so you can click SEM summary and it will tell you what
SEO, so organic keywords they rank for, but it will also tell you what paid ads they bid
on.
And that's just by clicking a button.
So you can quite quickly really gather some interesting data on a company just from its
name and quite iteratively.
And so if you had a play with it when the alpha first launched and you were like, crumbs,
it promises loads of cool stuff, but it can't do it.
Go have a play because if my play this week is anything to go with, it has vastly improved,
vastly improved.
So that's pretty cool.
Right.
Let's get into the actual main stories.
Although hopefully those snippets were a few deep dives that were still useful.
And we're getting to story number one.
And this is Apple's Developer Conference, which was real cool.
I'm a bit of a tech nerd.
I know you enjoyed this, Martin.
Tell us, what did you take away from Apple's news and launches this week?
Well, one hot take that I read on Twitter was that Apple is in trouble because they
are not focusing on AI right now.
Really?
It's got an issue.
It was the hottest of hot takes.
I thought, wow.
They've got this machine learning thing.
I don't know what that is, but they've got no AI.
They're not an AI first company.
Yeah.
And it was interesting that they didn't mention AI throughout the keynote once, but I don't
know what the count was for the number of times they said machine learning.
But machine learning is coming to pretty much everything.
I mean, not that it wasn't baked into the whole system anyway, but there's some really
interesting new examples.
One of which that everyone will be, everyone within iOS device will be happy about, particularly
if they're a little bit fruity in their language, will be the new auto correct coming to iOS
17, which is powered by on-device machine learning.
And it actually has a transformer based language model on device capable of not just auto suggest
for a language, but auto suggest for language generation.
So I guess it's going to be similar to auto complete on Gmail and things like that.
So finally, that auto correct that everybody gets when they type in the F word and it switches
it to ducking, well, that will no longer be the case.
I was fascinated here, Martin, by the on-device machine learning because there was, so maybe
we'll get into the headset in a moment and the Vision Pro, but there are a number of
things there where they really touched on protecting user security and information while
they were talking about how it works.
And we've talked previously about how on-device machine learning models might be needed to
help people feel comfortable that their personal data and other things are not being shared
in the cloud and used to train models or accessible by others.
And this is the first time I can remember really a key tech player or software player
talking about how their models are being run locally rather than in the cloud.
Yeah.
And we saw it coming, didn't really, we kind of forecast this with the investment and the
capabilities that were never quite fully tapped in the M chips.
Yeah, yeah, absolutely.
And that was indicative of it.
So we've also got Dictation in iOS 17, getting a new transformer based speech recognition
model.
iPad OS PDF features use machine learning models to identify form fields.
That's pretty neat.
That's pretty cool.
Yeah, I mean, there's loads of these things.
So, airpads.
Where can I get those?
Airpads.
Yeah.
Not sure what that was.
That sounds like some sort of basketball performance enhancing drug, doesn't it?
Or sort of very special trainers.
Can I get me some Nike Airpads, please?
So AirPods adaptive audio features use machine learning to understand your listening preferences
over time, the smartwatch, the Apple watch is getting a smart stack widget to show the
relevant information, journal app on iOS 17 users on device machine learning to provide
personalized suggestions based on photos, locations, music and workouts.
You've got the animated eye display on the aforementioned Apple Vision Pro headset, which
is coming in at a bargain price of $3499 USD.
And that's being created using the most advanced machine learning techniques on an advanced
encoder decoder neural network.
And then the M2 Ultra chip in the Mac Studio and the Mac Pro has been announced and it's
powerful enough to train, this was interesting, to train large transformer models and other
massive machine learning workloads.
As we did discuss previously, right?
They're absolutely leaning into that.
I thought that was a fascinating bit of noise.
Hopefully not noise, but a bit of news.
A bit of noise that the Apple team started making.
Lovely noise.
Yeah, it's funny.
You talk about $3499 for the Vision Pro and there's two camps forming.
One's a massive camp and one's a small camp.
Some people think, wow, that's outrageously expensive and other people are like, that
is not expensive at all.
That is a bargain.
And I started in the expensive camp, but now that I really think about the technology that's
in that headset and what it potentially could replace, it's not a price.
It's not a bargain, but it's potentially really good value when you actually think about it.
Yeah.
I mean, cards on the table, it is expensive, but it's not ludicrous and it's not for everybody.
There was an interesting tweet from Robert Scoble who tweets all sorts of stuff about
AI all the time.
And he put an interesting comment saying that when he was really jealous of Wozniak at Apple
when he got his first color printer way back when and it was wildly unaffordable.
And now you can pick up the same printer for like, or a printer 10 times better, sorry,
or a hundred times better even for like $70.
And that's just the nature of technology.
When things come to the market, when real innovative technology comes to market, it's
expensive and not everybody can have it.
And then the price comes down over time.
That's the nature of it.
So we can all sit here and go, oh, that's so expensive.
But fast forward three or four years and do you know what?
It's probably going to be about 1500 quid.
And that's just where we are.
I did think actually, because you've got the battery pack as well, haven't you?
And the battery pack in additional 1500 or something.
I saw something saying that all in it was somewhere in the region of just over 5000.
We have to buy the battery pack separately.
I did not know that.
That seems unlikely, but I guess it's possible.
Yeah, maybe it was a spare battery.
I don't know.
I saw someone on Twitter saying it and I didn't do a deep dive into it.
It didn't make me sit up and think, okay, if you're at the 5k territory, that is.
That's getting quite insane.
Yeah.
I guess it comes down to the difference between cost and value.
I completely agree.
It's a high cost for most people.
I think my point was more when you look at the technologies in it, it's potentially you
get quite a lot of value for the money, but there's no getting away from it.
It's a high cost, especially when you compare it to other VR headsets on the market and
also similar technologies like high definition 8k TVs or whatever.
I guess we'd need to keep on the AI.
I can't help.
I'm a bit of a VR nerd as well as an AI nerd, so I can't help but get pretty excited about
that stuff.
I did see the...
In fact, I think we might touch on it later, but Zuckerberg's email response basically
going, nah, they're not doing anything that special.
It's fine.
I'd be interested to see how that plays out.
I think there'll be the look and click mechanism of use from the few people who've been using
it.
I get the impression is really very intuitive in terms of you.
Very much so.
Yeah.
You look at something, the eye tracking picks up what you're looking at.
You just touch your fingers together as a click and how intuitive.
Look, one of the things here that we don't know how it's going to play out necessarily
is will this transform a category that struggled to get going?
As marketers, if this starts to become a dominating way of how people interact with content and
information, we're of course going to have to keep that in mind because we're going to
be able to create new experiences, how people interact with their content is going to change.
I think we need to keep it in mind from that perspective.
The key question that it will take probably several years to really unpick is will this
be a leap forward enough to overcome some of the issues of technology until now?
To be honest, seeing someone's eyes through the front of the screen is either going to
work or it's not.
For those that are not aware, the Vision Pro VR headset has a screen on the front of it
in essence that shows the user's eyes under certain conditions.
So that if Martin's using the headset and I walk into the room, it's almost as if an
opaque window on the front of the headset suddenly goes clear and I can see Martin's
eyes as I have a conversation with him.
But of course, I'm not looking at Martin's eyes.
I'm looking at a digital representation of them.
Basically there is a camera on the inside of the headset that's photographing the eyes
so I can see them and I can see where Martin's looking and stuff like that.
I think we're either going to adapt to that type of thing and go, oh yeah, that's kind
of normal.
I like to see where people's eyes are when I have a conversation with them or it's going
to be one of the weirdest experiences we've ever had because we're going to see these
weird floating eyes.
I think it's going to be in that territory of does it fall in the uncanny valley realm
where it's kind of almost right but just a little bit off.
Am I right in saying that it's not quite like a photo of it?
It's almost, it makes a scandia face.
So that's for FaceTime.
So there's like a 3D representation of you for FaceTime that is very uncanny valley.
Not probably better than like a computer game character, but not as good as a CG character
in a movie, probably somewhere in between based on the examples I've seen.
As I understand it, the eyes that you see is a real time video feed of your actual eyes,
but of course they're not your eyes.
It's a display.
It tries to make it look like the device is see through.
It's not see through.
So I think we're either going to adapt to that and it's going to be quite normal and
over time as technology gets thinner and more glass like, probably never glass like, oh
never, 2000 years maybe it's glass like.
I think it's going to be hard to get these things right down with the level of power
and computing that they're trying to do and sensors that they're trying to do into a pair
of glasses.
Although there are AR glasses out there that you can watch TV on that look like normal
glasses and by watch TV I mean a virtual display.
But hey, maybe we'll do an AR VR special, but for now we probably, because I could talk
about this for hours, we probably should get back to the, what were the last bits here
of Apple's developer conference that really stuck out to you?
Anything else that listeners need to know about?
Not a huge amount.
I just think it's interesting that the focus here is on very much on features and applications
of machine learning rather than the tech and the models.
If you contrast that to the recent Google IO event, so the Google Developer Conference
where I think every fourth word was AI, they just didn't talk about that here.
We came away from Google IO hearing about Palm, or should I say Palm 2 and MedPalm and
Music LM and various other models.
Whereas the focus didn't seem like that's what was going on at Apple.
They were more interested in what the features and functionality of their equipment was.
Now obviously they did talk about throughout the conference itself, Core ML and Create
ML, which are models that developers can access to build and extend the functionality of their
apps and they look very cool in and of themselves.
I would actually recommend that people check out the Apple Developer website to see some
of the capabilities because they really are allowing developers quite a lot of power to
extend the functionality of some of their apps.
But yeah, I just thought it was interesting.
They're not talking about, even when they're talking about the transformer model that's
on the device, they're not telling you anything about that model.
They're not telling you if it's an open source one, that they've trained themselves, they're
not making great claims about its capabilities.
They're just saying there's on device machine learning.
Yeah, I mean, again, probably could spend an hour just talking about Apple.
In essence, they've run a closed ship and a closed system and for me there's a reason
they're not using the word AI and that's because everyone else is.
They probably want to see if there's a way they can own machine learning instead.
Do they want to talk about other people's models?
No, I don't want to give credence to other people's models and work.
They probably just want to make everything very Apple centric and hey, they may be in-house
proprietary models that they've built.
But either way, I don't think we'd get to know.
I just want to clarify one thing on that Vision Pro cost that I said, I've just Googled it
and I cannot find any other reference to an additional fee for the battery.
So I think I was led astray with that tweet.
There we go.
That's good to know because that would be a significant bump up in the cost to be able
to not be tethered to a plug socket.
Cool wings.
Let's move on to our next story, which is going to be about the significant amount of
generative video and image news this week.
So we're going to crack through a load of it and then we'll unpick it a bit and talk
about what it means for marketers.
So we'll start with the quick one first because we're going to dive a bit deeper into this
in our tool of the week, but RunwayML has made its Gen2 text to video tool more widely
available.
So we've talked a bit about this on the podcast previously.
It was in a closed beta.
Now in effect, anybody with a RunwayML account can use the tool and we've been playing with
it.
So we'll talk about that later.
We had news that ClipDrop, which is the Stability AI image tool that I think Martin provided
as a tool of the week a few episodes ago, have released a new tool within that suite
called Uncrop, which I think is a great name, which is basically a generative fill tool
for expanding images beyond its borders, a little bit like Adobe Firefly can do, which
we've talked about in previous episodes.
Having had a quick play with it, it's really quick and easy to use.
And for the really tough examples I gave it, I think it may have even done a better job
than Adobe Firefly, if I'm honest.
All testing is required, but it's certainly not a junk tool.
It looks like it could probably do some pretty cool stuff.
While we're talking about images, of course, then we had Adobe Express, which now includes
generative AI tools.
So this is a beta.
As the website says, you can create video marketing and social content, edit photos
and PDFs, make it amazing with all Adobe powers all in one app, including generative AI tools
from Adobe Firefly and easy one click tasks like removing backgrounds.
And a lot of this leans into generative AI, so text to image and text to text effect,
but all baked into Adobe Express, which is a really cool tool for quickly knocking up
banner images for social and little animated gifs and stuff like that.
And so that's pretty cool.
And then the final bit of news here is Adobe Firefly for Enterprises arrived.
So that businesses can leverage that.
I think we've talked previously about some of the, what's the word I'm looking for?
Copyright issues related to using generative AI, especially for image generation because
of what were the tools trained on and was it copyrighted images and will those tools
get in trouble later?
Will users of those tools get in trouble later?
Well, now enterprises can lean into generative AI to create images and amend images.
But one of the most interesting things about this was that businesses can train Firefly
on their brand specific assets.
So this might make it easier to really at scale produce lots of content for your business
if you're able to train it on your brand colors, the typical imagery that you use and all that
good stuff.
So that sounds pretty cool.
But what really caught my eye here, and I will take a breath so we can go a bit deeper
into this together in a minute, Martin, is some of the stuff that's now on the Adobe
Firefly landing page, which includes sketched image and sketched vector creation.
The example that we know will be the best possible version of it that plays on the page
is very cool.
A designer has knocked up some sketch examples for some letters for a logo, highlights them
and asks for some vector based variations and then proceeds to edit them in, I guess
what would be perhaps Adobe Illustrator.
That was pretty cool.
There's an example where you can change the mood, atmosphere or even the weather in a
video through a text prompt.
So describe what you want it to look like and it will change the colors and the settings
to match.
And the example there is some sort of wooden shack in a grassy field in summer that they
then change it to being in winter and then they play the video and the snow falls.
That's a pretty insane example if it turns out that that actually is easy to duplicate
when you have to do it yourself.
And then the last example on the page was high quality 3D renders where you can turn
very simple 3D compositions into photorealistic images.
And the example here is a simple render of a watch that then they give a leather strap
to and different treatments of what the watch face might look like if it was made of like
silver or different types of alloys and all this type of stuff.
And again, very impressive and I should state they are on the coming soon section part of
the site.
It's not that you can get these now, but one assumes they wouldn't be showing us these
examples if they weren't relatively close within the next six to 12 months of being
able to launch those.
So some loads going on at the moment in text to image and text to video and actually some
really cool things that even at the beginning of this a few months ago, I wouldn't have
realised we'd have that power to hand so quickly.
So Martin, what do you think about all of this explosion in text to image and text to
video?
Difficult to know where to start.
There's been so much in there.
I'm going to part runway, uh, Gentoo for a minute because we're going to obviously go
through that one as I'll taller the week, but Clip Drop Uncrop it.
You're right.
It is a great name.
I do love that one.
I've been playing around with it and I like it.
So it throws out four different variations of the uncropped image and it does a really
neat job.
Although I am looking at one that I've created here, which has got the most dreadfully ghoulish
looking AI generated human face on it that I've ever seen.
It's quite scary, but no, it does a good job and this is available for free at the moment.
So if anyone wants to go and play with it, um, get stuck in over there, you don't need
the pro account and it is generating pretty quickly as well.
So there's just so much going on in this space.
I think it's really exciting time to be a creative when I'm demoing this to people at
the moment.
Um, so I did a workshop last week and we were showing people, um, the kind of the similar
capabilities, uh, people really set up and pay attention because things that, for instance,
a workshop that I was doing recently was with some small business owners, uh, kind of business
coaches, consultants, that kind of thing.
They don't necessarily have a team of designers and what on hand all of the time.
So showing them that, Hey, look, you can use this generative fill.
You can expand that image that wasn't quite aligned correctly.
So you couldn't crop it as a square.
Now you can crop it as a square and it works.
It's really useful.
These are just, you don't have to be a designer to figure it out now.
So I love it.
The Firefly examples are really exciting.
The ones that you mentioned there, the vector ones are going to be very, very cool, but
I'm really interested in the enterprise.
That's where things are going to get interesting from a question that always comes back to
me whenever I'm demoing this tech at the moment is can we do it with our brand colors?
Can we do it with our brand assets?
Can we do it with, you know, how much do I need to, can I train it?
This is when people have kind of right at the beginning of their journey.
And now you're going, yeah, yeah, you can.
Okay.
Not immediately.
You've got to sign up and speed to the sales team to get this.
But ultimately this is going to be creating assets that are on brand in seconds with simple
text prompts as it says.
Yeah, I agree.
I think, I mean, there are some tools that promise this, but I've never personally, and
I'm obviously not a designer come across anything that really does it with the type of robustness
that I'm looking for.
But like I create one banner ad or even a print ad.
And then I say, right, I need, you know, 320 by 320.
I need a leaderboard, like the power and the accuracy and the quality of these generated
images at this point, I would trust this tool to go ahead and produce all of the variations
I need to run a campaign across a variety of different platforms, probably at the click
of a button.
And obviously that's not quite here yet, at least not in the Adobe tools as I see them,
but it's can't be far away.
And that just allows you to deploy those campaigns very quickly at scale.
Now plug that into a programmatic ad management tool or Google display network.
Well, now you're now your power to run different messaging variants, subtly different image
variants, but on the same theme, all still in your brand colors.
One assumes you could do even easier at scale.
So there's a load of cool stuff, isn't there, that potentially comes from this in terms
of high quality outputs quickly at scale.
Yeah, and I think that goes to the discussion we were having about Meta's generative AI
tools for advertisers as well.
I think there's going to be quite a lot of overlap, isn't there, with these kinds of
tools.
So yeah, it's just an interesting space to watch at the moment.
I don't do a great deal of design, but I have found that these kinds of functions, particularly
AI, I knock things up in Canva pretty quickly.
But having the magic edit, the magic eraser, having that at your fingertips is, it speeds
up my workflow.
And that's great because quite honestly, I hate any graphic design.
Yeah, I think definitely on the execution front and actually like creating the assets,
I think is a big help.
It has been interesting.
We've been working on a series of creative campaign projects over the last month or two
at Biostrata.
And I personally have been experimenting with some image generation tools to see how they
might support with that.
So Photoshop, generative AI, generative image tools, Mid Journey.
And our team presented some concepts to a client recently in collaboration.
We built a team, a creative team on that, a creative director, scientific copywriter,
brand strategist.
And the ideas that they came up with and the concept, the example concepts, they just blew
away anything I've been able to generate on any tools, honestly.
You get a proper team together who know an audience, know an industry, know how to create
compelling campaign creative.
You have them IDA and then you have them knock something up and then take something through
to final concept.
AI tools are miles away from being able to do that, in my opinion, because what we were
able to generate through that process is just way better.
And in order to try and see what avenues you could go in, I've been playing with Mid Journey
to try and even riff on some of the themes we'd already created, but the ability to really
get what you want out of Mid Journey, and this obviously could be a limitation in our
skill sets and our experience using Mid Journey, it's just you can get cool stuff, but can
you get the thing you want that is very iterative, takes at least in my hands hours and is probably
not the most efficient or effective way to do it.
No, not if you're, you know, if you are a designer, if you're a creative, like I just
don't think like this, but if you are that person, you have something in your mind and
you know what you want to do to get there and you've already got all of those tools
and heuristics that help you get your job done quickly.
You're not sitting there basically at the whim of an AI, typing in a sentence and then
going, let's see what for it comes up with this time.
No, they're all shit.
Like that such an inefficient waste of time.
If you're a creative, you know how to get there.
Agreed.
I think you could probably be inspired by the things that you see, but I don't think
they're going to be the things that you're, that often you're going to produce.
I should caveat.
I've seen some pretty awesome things generated by Mid Journey that are for brands that as
a creative agency, you could use to pitch a brand to get their work.
We've talked about some of them on the, on the podcast previously.
So, so I do think there are certain niche outputs that you're looking for that Mid Journey
is good at that you can use for.
The way a potential game changer might be on this is that sketching tool, right?
Because presumably, I know the example is a logo or, you know, a stylized bee, I think
is one of the examples, but presumably if I have a vision and one of the great creative
directors we've worked with in the past does a lot of sketch work as initial concepts,
but to be able to click a button that then creates a stylized, more polished image based
on that sketch at the click of a button could be really quite interesting.
Right.
Let's jump into story three, Martin.
This is about DeepMind announcing generalized AI to optimize computing performance.
Tell us a bit more about this.
Yeah.
At first glance, you could be forgiven for thinking that this is a bit of a yawn story,
but actually it's, it's quite big.
And I think marketers and AI enthusiasts, generally speaking, should be very interested
in it.
So DeepMind has announced some new applications of its AI models.
So AlphaZero, MuZero and AlphaDev.
And what they've found is that they're able to take these, what are basically general
purpose AI models.
So you might remember AlphaZero was trained to play games and you had AlphaGo and it learned
the game Go and became a world champion and beat the world champion back in 2016.
And that kind of blew away people's kind of expectations for what we can think of the
capabilities of AI.
Now these models have now been put into real world applications and to try to optimize
different computer systems.
And what they've done is basically three big things.
One that they've, they've driven particularly good advances in data center optimization.
So optimizing the hardware within data centers.
Video compression, they've been working on that, which is for a company like Google,
which has YouTube, that's quite impactful.
And they've also discovered faster algorithms for sorting and searching.
So it can seem a bit dry, but please bear with me.
AlphaZero has been used to reduce underutilized hardware at Google's dentists, dentists centers.
I can't speak today.
Dental centers at the dentist, at the dental centers.
You sure that's the tooth?
Is that the whole tooth and nothing but the tooth?
They're getting the drills and saying, yep, this drill isn't used enough.
We're going to make sure it's properly utilized.
Anyway, right back to the real world.
We might get complaints this week, Martin.
We don't actually get complaints.
I might complain.
It's warranted, isn't it?
Bless you, dear listener.
Google's data centers.
So they've been able to reduce underutilized hardware by 19%, which is massive.
So it's improving resource utilization by recognizing tasks as they come into the hardware
and allowing it to make better decisions about what hardware should be used to do a task.
You can...
The kind of visual example I saw of it made me think of...
You remember when you used to have to defrag your hard drive all the time.
All my PC is full, I have to defrag it.
I need to do that with my brain.
But yeah, I do also remember that on the hard drives.
Well, that seems like what this is doing, basically.
It's real time defragging of the data centers is the best way I could describe it.
Then you've got Mu Zero, which DeepMind have been working in collaboration with YouTube.
And this doesn't sound like much, but when you think about this at scale, it's massive.
They've been able to reduce the video bitrate by 4% without impacting visual quality.
So optimizes individual frame compression and how the frames are then grouped.
And it suggests that there is much broader potential applications for video compression.
Video makes up the vast majority of data that we send globally around the internet.
So if you can shave off, if you can compress videos by 4% without losing any issue, well,
without degrading the video quality, that's enormous.
That's a really significant saving on bandwidth and energy.
And then finally, AlphaDev, a version of AlphaZero, has discovered faster sorting and hashing
algorithms enhancing efficiency in sorting short sequences by 70% and longer sequences
by 1.7%.
So hashing efficiency has been approved by 30%, all of which basically says that data
retrieval and searching and sorting of data is going to become more efficient, which,
like I say, bear with me, this is a bit dry.
But it just means that if this gets applied to, if you're an e-commerce store, right,
and you can tap into these models for your store's search engine, you've got maybe hundreds
of thousands or millions of SKUs.
The retrieval is going to increase by, again, it's tiny amounts, it's milliseconds, they're
shaving milliseconds off, but milliseconds count for user experience.
It's going to be using less energy, dramatic reduction in energy.
I saw one industry commentator saying it's going to take like 30% of the amount of energy
to do searching and sorting compared to what it is currently if you were to apply this
mechanism.
So it's something of a dry topic, but I think when we listen to publications from DeepMind,
quite often the application seems somewhat abstract, with the exception of something
like the protein folding, which was obviously pretty massive.
But when it's like, oh, we can train a model to be anyone at chess or at Go, or look at
them, they've applied AlphaGo to this Atari video game and it's just completed it quicker
than any human could ever.
You go, that's super cool.
But now we're starting to see this come into, there's the same technology, the technology
that started off just playing Atari and playing Go, we're now starting to see this come into
real world applications where at a global scale, it can actually make a difference on
both energy efficiency and user experience and more.
Yeah.
Do you know what I thought was cool about this story?
And this is me speaking as a novice in a lot of these topics, is if I understood correctly,
what actually happened was DeepMind asked AI tools to try and solve computer and software
problems that humans had run out of ideas for solving.
And then the algorithms, AlphaDev, was able to actually find new ways of compressing information
or achieving and overcoming these technical issues in ways that humans hadn't thought
of.
So therefore, what other domains are we going to be able to apply AI?
We've run out of ideas to solve this problem.
AI, what would you do?
Because this is the first evidence that I know of, of AI being given a tough problem
where humans are gone that was stumped now.
We've got all the optimization out of this that we can.
What do you think?
Secretly probably thinking, humans have done a good job of this.
There's not going to be any opportunities in there.
AI is not going to find anything.
And then look at the amazing stuff it found.
So I think that will be really interesting to see how that plays out.
Yep.
And I think that's where DeepMind are heading.
And that's why training this, the approach that they've taken with AlphaZero is so interesting
because they've just trained this machine to just, without telling it the rules of the
game, but telling it the objective and then letting it kind of run with that and play
against itself and basically millions and millions of playthroughs of a scenario.
It just finds better strategies.
Really interesting, really powerful approach to problem solving.
Yeah, absolutely mind blowing.
Right for the final story of today, we're going to talk a little bit about Meta's roadmap.
So Mark Zuckerberg has outlined Meta's plans for the future in an all hands meeting this
week, highlighting how AI and the metaverse will align with the company's vision.
Actually they've gone so all in on the metaverse, Martin, but they've been really good at AI.
They've got loads of smart AI people doing loads of great work.
They must've been like, ah, crumbs, we went all in on the metaverse and it was AI that
exploded and we're really good at that.
Yeah and to their credit, they've been really big contributors to the open source community
in AI as well.
So that must be somewhat frustrating.
Yeah, so he's obviously like, right, we're really good at AI.
We're not going to give up the metaverse.
We're going to bring those things together and Meta's going to continue to be a really
successful company.
And then in the in the all hands, they introduced plans for their AI powered assistance across
all meta apps, trying to make these technologies more accessible to users.
And they also revealed that they were working on Project 92, which sounds like an order
to kill all Jedi from the Star Wars universe, to be honest, but there you go, which is a
social app similar to Twitter.
And they've also got plans to improve Instagram's reels to better compete with TikTok.
So it's sort of a galvanizing, we're good at AI, we're still believe in the metaverse.
We realize our competitors are doing all these cool things.
We're doing cool things and we're going to be successful with our cool things.
What was your take on this new story, Mide?
They are bringing the chat GPT Bard, call it what you may like experience to to make
messenger on WhatsApp.
Now this for this to be functional, I'm sure they'll do their own kind of chat GPT Bard
version that you can chat with and they'll call it God knows what they'll call it.
But where I think this will be a kind of game changer for them is by extending this into
businesses.
One of the things that separates Facebook or meta from all of the other tech companies
is the user base for their big chat apps.
Messenger and WhatsApp are massive, the global adoption of these two chat tools is huge for
both consumers and businesses.
Now in certainly in Asia, I know in India, WhatsApp is one of the primary channels of
communicating with companies these days.
We're seeing more and more customer support queries being dealt with on Facebook Messenger
around the world, we're seeing marketing, direct marketing being done through messenger
and through through WhatsApp.
If Facebook or meta can get their language models plugged in to business data, I think
this is going to be an absolute showstopper.
We keep talking about, we've mentioned a few times in recent weeks that increasingly the
differentiator is the UX.
Make it easy for people to use the AI without necessarily having to have, you know, any
technical knowledge or you just just make it easy for me to do it.
That's why chat GPT was an overnight success because it made using AI as simple as using
WhatsApp.
If Facebook can do that with, let's say, enabling companies to connect their customer data,
their CRM, whatever it may be, to Facebook Business Suite, for example, and then given
that everybody can log into apps and services these days with Facebook, you know, sign in
with Facebook, log in with Facebook, Facebook Authenticator, all of that kind of stuff.
If I can log in and then can just fire off a message to a customer support AI in Messenger
and it knows who I am because of all the authentication and it's pulling in data in real time because
it's connected to the relevant database, like chat spot, you know, like we're seeing with
or expecting to see people be able to do with HubSpot's chat spot.
I think that's going to be immensely powerful.
Now, if that's not where they're planning on taking it, Mark, please have the idea and
run with it.
My only concern there would be that over the recent years, every time I try to use Meta's
Business Suite, I find it more and more infuriating every time I have to log in and do even the
most simple task.
So whilst they might want to do this, I think they'll still make it incredibly hard for
businesses to actually be able to implement it.
Usability is key, right?
We talk a lot about UX on the podcast and how the magic at the moment, I think there
is absolute technical wizardry, but that seems to be something that lots of companies have
access to.
It's how wonderfully easy and perhaps almost magic in the background that you can actually
make your tool and that will be what helps a company win.
And I agree.
On the WhatsApp front, there's a number of companies, we talked about the tool I was
trialing where it's basically like an advisor on anything you want, like mindfulness.
It's like, oh, I want to, how can I be calmer in these situations?
You can get advice from this app and here's a business decision I need to make and you
can get advice from this app.
So I think third parties are already leaning into WhatsApp to do that.
And if Facebook can basically gobble up a lot of that before other apps can get in,
it makes sense.
We talked previously on the podcast about where the big companies have their motes.
Well, it may not be the large language models because there's loads of them, there's open
source ones and they're all pretty good now.
But I was doing some Googling while you were talking and according to some research from
last year, about this time last year, WhatsApp had around 2.25 billion monthly users.
And according to another bit of research that would at the time would have made it the world's
most popular messaging app.
That's a fairly chunky moat in terms of having a, you know, 25% of the world's population
give or take, maybe 30% of the world's population using your tool, you know, monetize that.
And of course, I'm sure they're already thinking all of this.
It'd be brilliant, Martin, if me and you were coming up with ideas that their teams of strategists
haven't thought of, I think it's unlikely.
Wouldn't it just, wouldn't it just?
Have that one for free, Mark.
Yeah, like get in touch with the podcast.
We don't mind having you on.
Yeah, we'll make space.
To be honest, he won't stop messaging me on LinkedIn.
And this might be the bit where I have to finally say, all right, Mark, you can come
on.
You'd be very welcome, but we can only give you 15 minutes.
Yeah.
So, so some interesting stuff there.
And I think we should, as marketers, it's what channels we have to reach our audiences.
As you said, a lot of businesses are already using WhatsApp, but what ways might we make
that even better and even easier for our audiences, leveraging the data we have about our products
and services, plus the data that then Meta has about our customers in order to really
provide personalized customer service and product recommendations and all those great
things at scale using a messenger app like WhatsApp, right?
We've got to be imagining what these things might look like, what type of data and systems
and processes we might need internally to take advantage of those opportunities.
Just on that, it would be nice, and I hope the industry heads this way in the near future,
if we saw some standardizations and standardized protocols across the industry to help companies
make their data more accessible to things like AI chat box.
Now, I know that with chat GPT plugins, the idea was basically you would natural language
the connection to your database.
You could basically say, this is our data, this is what it looks like, and off you go,
and it would figure it out yourself.
Maybe that is the way it's going to go, but something akin to website schema markup that
just says exactly what is in your database.
If there was that, that would help us to standardize a connection between, let's say, OpenAI versus
Messenger and WhatsApp, and then some sort of Google chat interface and make our content
easily searchable, crawlable, and accessible to users.
That would be nice, particularly for not enterprise businesses, but large businesses and SMEs
that want to make their customer data accessible via these kinds of chat-based interfaces.
Yeah, I think it's an interesting one.
When's the best time to plant a tree 10 years ago?
When's the second best time to plant a tree today?
If you're a business that's not thinking about your data as an asset, and more importantly,
how that data is structured so you can leverage it as an asset, now is the day to start thinking
about that.
I think the thing that will be really interesting, because I think you're absolutely right, mine,
even similar fields of data in similar systems work very differently.
Anybody who's tried to do a sync between Salesforce and HubSpot will know all the ways it can break
in completely unexpected ways because of what HubSpot calls a contact and Salesforce calls
a contact and the difference between a lead and even difference between an MQL in one
company versus another, things that seem like they should be pretty standard between systems
and between businesses are not.
I wonder if it's kind of a bet.
Do I bet that those with structured data will be able to move faster, monetize their data
through these tools and win, in which case invest time and energy in structuring the
data I already have, because a lot of companies already have a lot of data, or do I bet that
a lot of these companies that are pumping up, I think is it scale.ai one that springs
to mind to basically come in and help extract the insights from your unstructured data to
be able to then build models and stuff on top of them and as they mature, will they
almost be out of the box, AI driven models themselves that can crawl all your disparate
data and figure out how it should connect to other bits of your data and basically turn
unstructured data, instructure data for you without you having to do anything.
That would be the bet, right?
Because if that appears in the next year or two or less, then any effort you put into
structuring your data might be wasted.
So I think it's a difficult one to know how it's going to play out.
One thing is for certain, structured data about your business, about your customers,
about your market that you can leverage in intelligent ways to provide better customer
service, improve your marketing, improve your products.
People have been saying data is the new oil for years and I think we're going to see how
AI tools are going to help get some of that oil out of the ground.
Yeah, although that analogy always just make me think of how bad things are when there's
a leak.
Absolutely.
So after we were about to put the podcast live, we noticed a story that we thought we
should feature.
So here's a little addendum to the big stories this week.
And this big story is about the CRM company Salesforce, who I'm sure many of you will
know, debuting two new generative AI products this week as part of the company's connections
conference.
And those products are called Marketing GPT and Commerce GPT, plugging into Salesforce's
Marketing Cloud and Commerce Cloud products.
So in essence, why is this important?
Well I guess the first thing is they're rolling this out in phases.
So if you are a Salesforce user, you may not have access to these yet, but you hopefully
will in the future.
And in essence, these are kind of cool because what they're going to allow is a number of
different things.
So Marketing Cloud users should be able to put in natural language prompts to query the
data in their Salesforce implementation and identify new audience segments to target.
They could also ask Einstein GPT to write or modify personalized emails, complete with
subject lines and body content for their campaigns.
And they can use typeface within the platform to create contextual visual assets for specific
contacts.
That's pretty powerful and pretty interesting.
In addition to this, there's going to be some other things that can be done that were going
to be valuable for marketers also, including the creation of personalized shopping experiences.
So Marketing GPT uses Data Cloud and Einstein GPT to allow users to not only create dynamic
product descriptions for digital storefronts, but also to have those descriptions translated
into different languages for different target audiences.
So quite interesting stuff actually.
The original article comes to us from VentureBeat, so it's worth Googling.
But yes, Salesforce, maybe I know Einstein has been around for a while, but been a little
bit quiet on the generative AI front.
And it looks like these two products, the Marketing GPT and Einstein GPT could be opening
up some really interesting applications for marketers who use Salesforce that will very
likely make it faster and easier to create content for your customers and prospects,
but also easier to create hyper-personalized content at scale.
So very interesting stuff from Salesforce.
Right, let's get onto the last bit this week because the lovely folks really stuck with
us and we appreciate it.
Let's talk about Gen 2.
So for those that are not aware, there is a really cool web-based tool called RunwayML
that has a whole suite of clever image editing and video editing and image creation and video
creation tools.
And RunwayML made a bit of a splash at the start of the year when they launched Gen 1,
which was a video tool where you could feed an image and it would create a very short
snippet of video based on that image.
Then Gen 2 came along where you could do the same thing, but with a text prompt.
So you just write a simple text prompt, you get, I don't know, what is it, three or four
seconds of video.
So we've been having a play, haven't we Martin?
Because obviously, as marketers, if we can produce high quality video from a simple text
prompt, that opens up a load of creative avenues for us to be able to produce video at scale.
What have your thoughts been with your access to Gen 2?
I've been playing with this for the past day or so, tried out a few different styles.
The first thing that I tried was a prompt which simply said, two British men recording
a podcast in a dimly lit studio with neon lights.
And it's a curious one, I'll be honest, because it can't count as there are three men in the
scene.
It's dimly lit, it does have a kind of aesthetic of a dogly lit studio with some neon lights.
But the three men in the image are all identical.
It's as if three British triplets had recorded this podcast.
That was a bit of a curiosity.
The videos are all, like you say, about four seconds long.
They have some of the strange, I don't even know how you would call it, just objects merging
into one another, like the hand suddenly becomes part of the table and then comes out of the
table again.
What I have found, when I tried more abstract things, so I tried hand drawn animation, so
that was part of the prompt, I said, tractor racing, Grand Prix, line drawn, hand drawn
animation.
And it basically came, just gave me a static image of a tractor, like there was very little
movement in it at all.
Didn't really give me tractor racing.
I was trying something for my toddler, you know.
I found things like animation, it just doesn't really vibe with very well at all.
I haven't had any good results with that.
I've tried three or four variants.
One that I have had a great deal of success with was, so I said a ginger head woman using
her iPhone, stock video, professional video, and that was it.
And it's actually given me a decent clip.
It works quite well.
There's no immediate things that are ghoulish or the artifacts aren't really bad.
Now the file size for all of these images, videos is about three to 400 kilobytes.
So they're really short and basically they're just like little gifs.
And for that purpose, I think if anywhere that you might stick a little gif, so in a
blog post, maybe on something on social, they can be quite useful.
You do have to play around with them a lot and I don't think with the monthly subscription,
you don't get huge amounts of generation credits.
But overall, taking a few words and turning it into an image, when you find the styles
that work, for instance, professional videography, stock video library, and putting that into
the prompt, you can get something that looks pretty decent.
Yeah.
I think my experiences have been the same.
I asked for two fighter jets fighting alien spacecraft over an alien planet and I got
multitude of jet light subjects flying in the sky that weren't really jets.
They were like three jets had all been smashed together to create this strange flying thing.
It didn't work to be honest.
I also asked for a video of Tom Cruise playing basketball and for that, I got a couple of
male figures that look like humans, but none of them look anything like Tom Cruise and
then it didn't animate at all.
Yeah, it's the lack of animation that's interesting and I think they're experiencing this quite
a lot because under each generation, there's a five star rating.
So if you give it a rating and you give it a low rating, it comes up with, it's got like
six options to choose from and one of them is just that it doesn't move.
So it must be one of the common issues that they're facing.
Yeah, I saw that as well and I think soliciting this type of feedback tells me they know this
doesn't work very well yet and they want this type of feedback to improve the models.
My spidey sense tells me that one of the reasons you got better outputs when you tried to talk
about stock videography is the training data.
When I look at my Tom Cruise output, some of that is almost entirely going to be driven
by the training data.
Like it doesn't have a video or anything close to an image of Tom Cruise playing basketball
and so it has literally no hope of producing it.
Whereas I bet if I try to get something that I know there's plenty of stock video out there
for or plenty of stock imagery for, I reckon it would probably do a better job.
So I guess for those marketers out there, as Martin summed it up, you might be able
to get some interesting gifts out of this.
They're going to be very specific use cases that work right now and loads that don't.
You're probably going to have to iterate a lot to get close to something that you like
and then you're probably going to run out of credits.
So it's probably not quite there yet, but like all of these things, we do recommend
you have a play because it's really important to just be informed about what tools are out
there and how they're emerging and how they're developing and which ones are good for what.
Because this space is going to continue to move quickly and I think the best thing marketers
can do is make sure they know how to augment themselves to get more done in less time,
be more creative and all that good stuff.
I have a question for you on this.
Tools like Runway and then companies like Runway, do you think that they are, how do
you think they're going to stack up when Adobe get into this game or Canva or any of the
big players in this space?
What do I think is going to happen?
Do you think they'll just get crushed or what?
Are they just a curiosity at the moment or where's their space in the market?
I think it comes back to users and motes.
So many creatives and even non-creatives have Photoshop installed already, want to do cool
stuff.
The fact that I could just download the beta quite quickly and start playing and it was
good at some things that a lot of other tools are not, made it very accessible.
I want to love Runway.
I love some of the things it can do.
We talked about in the first or second episode of the podcast, we tried to edit the video
for the podcast and the transcript to produce was brilliant.
There was hardly any errors in it, but goodness me, editing the errors out because it was
a web-based app was so slow.
I was like, I don't care if there are errors now.
It's just too painful.
Whereas if I was in Premiere Pro and Adobe, I could make edits very quickly because there's
no real lag in terms of how the tool works, but I made loads more errors in the transcript.
So personally, I think they're going to struggle to maintain applications and tools that they
can keep unique and unless their user experience is awesome and the editing the video user
experience was not awesome and that's why I've been there, they're going to struggle
because they are the ones that have to get us to jump ship.
They have to give us a compelling reason to make this the place where we get that thing
that we need done to this image or this video.
Like I said, unless they can come up with something that other tools can't do and I
think the evidence so far is that the major companies are not struggling to replicate
what other people can build.
That's how it is so far.
Then they have to be absolutely incredible in terms of usability and let's not forget,
Adobe's had decades to improve the usability of its tools and in essence, it's trained
people to use its tools by having people just have to use the left side, but where do I
go for the lasso?
It's on the left side where it's a fourth down.
We know how all of that works.
So personally, I probably wouldn't be, and this is not investment advice because we are
not in that business, but personally, I probably wouldn't be investing in them because I think
it's going to be hard for them.
Yeah, I do at the moment.
I find it a curiosity and something that's fun to watch develop, but so far just seeing
where the... because they are pushing boundaries.
That's the interesting thing with them and that's what I like about them.
I really respect them from that perspective, is the usability and again, it just comes
back to every third or fourth time we've mentioned it today, is having the right UX and the right
usability that makes people go, yes, this is so seamless and frictionless and really
makes my life a breeze.
At the moment, it's like, oh, this is an interesting curiosity.
I can make something that isn't quite a very convincing stock image.
See, you raised such a really important point though, because I think the ecosystem as it
stands right now is critical because I do think that Runway do loads of the cool stuff
and they launch it really early.
You could argue before ChatGPT went nuclear, that was kind of a... we're a small... at
the time, in terms of the mindset, we're an agile, small brand.
We Google, we're like, we don't want to launch anything or release anything before it's ready,
which how much longer would we have waited for these tools if ChatGPT hadn't come out
and open out and just gone, look, let's just get it out.
Let's just ship.
Runway's attitude to its tools is ship, ship, ship, ship, ship and we get to play with innovative
stuff.
Therefore, we shouldn't probably be too down or critical of things when like Gen 2 and
they're not really working as well as we'd all like, but it's because they're getting
out there so we can play with them.
So if the ecosystem is boiled down to Adobe, Microsoft and Google, that is not going to
be good, I would argue, for the actual innovation and the emergence of awesome new tools for
us to play with.
So let's hope that they do do reasonably well because we need them around.
Yeah, I do want to see them thrive, but I just want to see the use cases beyond interest
and curiosity at the moment, which is currently where I feel like it is.
Agreed.
Right.
So that will sign off.
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Right.
Thanks, Martin.
It's for bye.
Bye.
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