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 26 of Artificially Intelligent Marketing.
We are here to bring you all the news that you need to know about if you're a marketer
interested in the power of AI.
As usual, I am joined by my very good friend, Martin Broadhurst.
Martin, how are you today?
The jet lag from post-inbound has finally subsided, but I'm good.
Yeah, Friday afternoon, lots of news to get through this week.
It's been an absolute bummer week in terms of AI.
And we were saying on the WhatsApp earlier this week that it felt like a relatively slow
week actually earlier on in the week.
Once we gathered all the stories up and we realized how much we had to get through, we
were glad that we didn't have an interview to go live with this week because we honestly
wouldn't have had the time.
So with that in mind, we should probably quit the preamble and get into the productive discussions.
So Martin, why don't you take us through our first story this week?
This one's a story that's been bubbling under the surface for a couple of weeks now, but
Google is gearing up to launch Gemini, its own suite of conversational AI software.
And this is big because it's actually intended to take on GPT-4, but aims to be a real formidable
contender in the generative AI market.
Currently, Google is allowing a select group of companies to test an early version, offering
functionalities that range from chatbots to text summarization and, of course, text generation.
Gemini has broader applications too, so it can assist software engineers with writing
code and generating images as well.
It is rumored to be, or expected to be at least, a multimodal model.
So all of this is going to be delivered through Google's Cloud Vertex AI service.
And the new suite is part of the overall Google strategy to really catch up in the AI realm,
which obviously OpenAI has taken quite a lead ahead of Google in this area.
So Gemini opens up all sorts of possibilities for enhanced customer engagement through chatbots
and content generation as well.
I think it's an exciting space or an exciting story because there was talk of it coming
out in December.
Now it sounds like it's being brought forward.
I think it was initially reported in, we picked it up on, in Reuters.
So it could be coming out very soon.
It would make sense that they would do that alongside Google's Duet AI launch, which has
obviously just come to market.
Rumors are that Meta are entering this space as well.
So Meta is also supposed to be working on a new model that will match or supersede GPT-4.
There was the release of Falcon, which was the 180 billion parameter open source model.
That was the past week or two.
So if you look at this in the round, it would make sense that Google would want to push
ahead with the launch of Gemini and get this out to the market quickly.
Yeah, we're going to look at Google Duet in a bit more detail later, but Bard and other
large language models from Google have lagged behind in terms of the qualities of the outputs
of Claude, ChachiPT, arguably even Llama2.
So they do need to try and be ahead of the pack in terms of pushing the envelope for
the next step, don't they?
So I guess one question that we might consider in mind is, does this feel like a too late
an entry for Google bringing Gemini here?
You know, was it a good idea because they could see how competitors would position themselves
and how tools would be used?
Or do we think this is a misstep being laid to market with their most powerful models?
Yeah, very good question.
I think it all depends on the model, right, and how they bring it to market.
There's a lot of hype and in certain places.
So I saw one Reddit discussion thread that someone did a thought experiment based on
the amount of data that Google has available through all of its, well, through every channel
that it has access to, right?
And they said based on their kind of mental maths of this model, it could be, if they
were to utilise all of that, it could be five times the size of GPT-4.
Now, I don't think Gemini is going to be five times the size of GPT-4.
The compute power would just be like crazy.
But they have the capabilities to create a model and train a model that is bigger than
GPT-4.
So if it is, if they bring something to market and they can deploy it in a way that is accessible,
easy to use, I think it's a real strong play.
If however they play it safe and take the somewhat cautionary approach that they've
taken today, I think Microsoft and OpenAI will continue to steal a march on them.
An interesting observation I saw from the past couple of weeks is that Kassi Kasikov,
the chief decision scientist at Google, she left Google this week and she did a keynote
at MAKON back in July where she spoke about all AI models are built upon the decisions
of people.
And there was insinuation in some of the articles that were published about her departure that
she didn't agree with some of the decisions that Google leadership were making in terms
of how they're going to deploy AI in the future and what they're going to do with it next.
So maybe Google's more reserved approach and more cautious approach is going to be
thrown out of the, I think they're going to put in the bin, get rid of that, because they
need to be more competitive.
And they've seen how disruptive OpenAI has been by giving people access to the models
just like, there you go.
And there's a competitive advantage to just letting people have out it with the models
themselves.
Yeah, I think it's going to be interesting.
You and I have been playing with Google Duet in the 14 day free trial with limited success,
let's say.
That's polite.
You had a take home.
Yeah.
What was your take home about what's going to happen with your Google Duet account when
your trial ends?
Yeah.
So my trial ends in about 24 hours and I'm categorically not renewing that trial.
It's not a product that is worth paying close to what they're trying to charge for at the
moment to the extent that today when I was in a Google Doc and I thought, oh, now that
I've got this Google Doc open, I'll just use the built in, you know, barred text generator
to knock something up for me.
I couldn't find out how to do it.
I couldn't see it on the interface to do the damn thing I wanted to do.
The outputs aren't great in the Gmail composer.
I think they're very meh.
It feels like using GPT-3, which, you know, is fine, but I can probably write a better
email myself.
Everything doesn't need to have this exaggerated tone to it.
I don't know.
I just, the whole thing, I've totally been unimpressed by it.
And until they work out how to deliver on the promise that they showed us in the preview
trailer, this is not a product that is worth investing in at this moment in time.
Yeah.
I mean, we talked in the last episode or a couple of episodes ago about feeling like
they rushed this to market as a half-baked tool.
And I think our tests and the tests of other people that we know would confirm that, right?
The Google Slides integration with it, pretty sucky at the moment.
You could basically just generate images with it, which you could probably get better images
out of Mid-Journey or even PipDrop, right?
On stable stability AI models.
The Gmail is really hard to get anything usable out of.
I would agree with you.
I just don't, it doesn't do what I want it to do.
I want it to know the emails of the thread.
They're already in the thread and then make a sensible recommendation on what the next
email should be.
I want it to know what my email style is and draft things in my style.
That seems to have the whole point of having a generative AI tool baked into where all
your other data sits that the systems know about you.
And none of that's here yet.
The Google Sheets integration to come up with project plan type stuff, very interesting.
Not really that usable on a day-to-day basis.
Kind of interesting, not commercially usable.
Then we can analyze data and other stuff with it.
Yeah, that'll be cool.
So yeah, I'm with you.
If you're thinking about trialing it, maybe do, but I wouldn't pay for it.
I think the other thing is when this Gemini tool comes out, let's say it now gets baked
in to, it's much better.
Maybe it's better than GPT-4 and it's powering Google Duet.
Well, now you've got to go back and trial it again, right?
Because realistically that could be a leap forward in performance.
The other thing is Google has promised things in a number of areas, including the trailer
you mentioned, that there's going to be greater functionality to this.
So we're not recommending you take your eye off of Google or Google Duet and you now put
it to one side and say, that doesn't work for me.
I need a different tool because it's probably going to evolve quite quickly.
But as it stands, yeah, not something to pay for.
Right, let's get into our next story then.
So next story is really interesting one.
The Vanity AI has entered the audio generation market with stable audio, which is a diffusion
model that allows for fine-tune control over generated audio.
So if you go to the stable audio website, you can use it to produce audio files that
have been built based on prompts, text-based prompts that you give them, where you explain
the type of music that you want, how long you want the music to play for, et cetera,
et cetera.
It's really quite impressive in terms of its ability to render high-quality audio pretty
quickly for you to play with it like you would play with mid-journey for images.
You can imagine the stable audio has a range of applications for marketing, from generating
customized background music for your videos, to creating audio cues for live events, to
jingles and other use cases.
And as it stands, its licensing model also encourages you to use it for commercial use
if you are a pro user who's paying, I think it's about $12 a month to access the tool
and you can download things as MP3s, et cetera, et cetera, et cetera.
There are actually, as it stands, three subscription tiers depending on what you need.
There's a free version so you can go play with it.
There's the professional and then there's the enterprise.
So with free, you can generate up to 20 tracks of 45 seconds each per month for non-commercial
use.
And then if you're going to likely be a bit more of a power user, the pro plan will give
you 500 tracks with 90 second duration each.
And importantly, you can use these in commercial projects.
If you've got larger scale and more specialized needs, that's where the enterprise plan comes
in for you to basically negotiate with Stable Audio and the team there for what you need.
Now you've been having a bit of a play with this, haven't you, Martin?
And you've generated some little audio snippets.
So we're going to hear them on the podcast.
Tell us what you've been up to.
Martin So yeah, so they've put a really good guide
together on the Stable Audio website to explain what information went into the training model
and what makes a good prompt really.
So I took some of that content and I put it into ChatGPT and said, hey, there's this new
model.
This is what it's about.
Can you help me create some prompts?
And it did.
So I asked ChatGPT to give me a prompt for Stable Audio that would create an introduction
track or this hodcast.
And here it is.
So that's pretty cool.
Quite electronic, but like very melodic.
If I heard that at the beginning of a podcast, I think it wouldn't strike me to think, oh,
where did they get that terrible sample from?
Or, it sounds awful.
And it even has that little sort of ending, right?
It's the right type of length that you would want.
And it ends with that feeling, which then you can lead into speech.
So that was pretty interesting.
It was very electronic though.
Did you really push for electronic music in your prompt?
Well, the prompt that was input ended up having that in it as a style.
And I think that came from the context given to ChatGPT in the first place about this being
a podcast about AI.
So it's taken that as a kind of reference point and then put that into the Stable Audio
prompt.
Interesting.
Listening to it on my headphones, I noticed I've done quite a lot of music production
over the years in tools like Ableton Live and producing music tracks.
And I did notice listening to it in a decent set of headphones, quite a muddy bass area.
So I can imagine that proper audio files and music producers with much more talent and
knowledge than me would probably have quite a bit to say, I think, about the audio mix.
Like it's not professionally mixed audio.
And to professionally mix audio, you need each of the parts of the audio split out,
which of course you don't really get here.
So I think that could be a bit of pushback from professional communities.
But checking it on our podcast, for example, is something that we're able to craft using
AI would probably be quite a fun thing to do.
But I can imagine there'll be some pushback in those types of cores.
Yeah, absolutely.
And believe me, when I asked it to create a lullaby with loops and soft, gentle sounds
for a baby or a toddler, it was discordant.
It was the lullaby of nightmares.
It was not the sort of thing that you would want to be playing as you put your child to
sleep.
I did try some other techniques with it, though.
I thought, well, if we're creating a podcast intro, I would quite like a bit of audio branding.
So I again asked ChatGPT to give us a prompt that would enable us to get something like
the Netflix Tudum or the Intel Dun Dun Dun Dun audio branding, audio snippet, whatever
you want to call it for the podcast.
And you can listen to the output here.
So that's pretty cool.
Again, it's like it's understood what you were looking for.
It did produce like 30 seconds of audio.
It knew it needed to be a little snippet.
It's interesting in that it's somewhat close to the podcast intro.
Did you specifically say use bits of the same prompt to try and make sure they'd be the
same?
No, not at all.
They were completely separate, actually.
So the fact that it's gone down that path of itself is an interesting observation.
That's quite fun.
Maybe we'll have to try and work both those into the actual podcast over time.
I don't know.
That would be interesting.
If you did a third one, then you might.
What was your third little experiment?
Yeah.
So I thought I'd try something completely off-piste from just related to the podcast
and I asked it to create a background score that we could use in a sales presentation
if I was pitching in HubSpot to a client.
Well, so that's pretty good as well.
It has a different feel to the first two, so I definitely think you'd use the prompt
in a different way.
What were your feelings on that?
Would you use that?
I mean, I'm not sure I would actually use that just from a practical perspective.
I'm not sure where I would play it, but I liked it.
I did actually think that you...
I could imagine a scenario where that was playing in a video or something and it wouldn't
offend me.
I wouldn't think it was out of place in exactly that setting.
Yeah.
I love those.
Thanks for having a play with that, Martin, and sharing those with all of us.
I had a play with the system.
I didn't generate anything, but I listened to some examples on the side that other people
have generated and I did feel like everything either felt a bit artificial, which I guess
you would expect, but given that it was trained on audio, it should be able to replicate that
audio, but everything felt a bit robotic or a bit electronica as a genre to me.
Even the audio snippets I tried to look at that were supposed to be quite guitar type
music, like a Nirvana style, but everything just felt a bit electronica.
So I don't know if that's because of the training data set or whatever, but yeah, it strikes
me that we're having a conversation about the musical equivalent of Dourley 2.
It's like, oh, it's kind of cool, but by the way, it can't do hands.
Sometimes faces looks like gould.
It doesn't know what this is.
So it's like, it does some cool stuff really well.
It clearly has some problems, but the tools are learning to get better from here.
Yeah.
And you've got to just look at the rapid development of the stable diffusion model from when we
first saw it, the big model that they recently released.
Absolutely.
Right.
Let's move on to our next story, Martin.
This is something of an AI fiasco coming to us from Microsoft.
Microsoft's MSN news platform recently stirred controversy by publishing an ill-conceived
and presumably AI generated article that tarnished the reputation of recently deceased NBA player
Brandon Hunter.
Labeled as useless in the article's headline.
I shouldn't laugh.
It's terrible.
It labeled him as useless in the headline.
And then the rest of the article was just incoherent text.
And obviously there was a big backlash from the public on this and lots of people, rightly
so started questioning the use of AI in journalism and the ethics of doing this, particularly
the delicate matters like obituaries.
The idea that this went out is just mind blowing to me.
And this isn't the first time either.
This is not an isolated incident with MSN.
They previously published a questionable article with bizarre travel advice about Ottawa.
And this really looks like a trend that's taken off after MSN laid off a lot of its
human journalism team in 2020 and replaced them with an AI slash human hybrid publishing
and content production system, which doesn't appear to be going swimmingly.
So yeah, with questionable articles, low engagement, and what can only be described as a loss of
editorial integrity, this shift towards automation appears to be backfiring.
So yeah, just an interesting observation and something there about the risks of, well,
the lack of human in the loop.
We've talked about it a lot, right?
While you're out inbound, there was a story last week I mentioned on the podcast about
Gizmodo laying off its Gizmodo en Espanol, their Spanish language website, and that sometimes
the translated articles would just switch to English halfway through.
And I think in this pursuit of scalability through what is perceived to be smart automation,
you remove that human in the loop and you're asking for trouble.
We are nowhere near the point where AI generated content, apps, even at scale, can be just
trusted to just go out.
So you're going to try and scale it, Brian.
You can scale initial production and initial draft.
You've got to have editors checking everything.
Otherwise, you're going to have mishaps like this.
Of course, that's critical for brands, sorry for publishers, but it's also going to be
critical for brands, right?
The notion that somebody hasn't just cast their eye over this before it's gone out.
In the most cursory sense, just a single read through of the article just to say is not
even fact checking, but just calling somebody useless in the headline of an obituary.
I mean, come on, there's some real basics that are overlooked there.
I think that's one of the great dangers that we're going to face over the next six to 12
months as more and more companies look at how they're going to implement AI.
There's going to be a lot of it to boost efficiency and productivity, let's be honest, and having
overconfidence in their belief to automate things in a smart way and requires less human
oversight than is really needed.
I think that's going to be true of every piece of content you could possibly create with
AI support, but you should really also be building.
If you're going to do it, and please don't do it, but if you are going to do it, at least
have some sort of risk profile, right?
Have someone check your obituaries, have someone check content that's more likely to give you
issues around sensitivities, and honestly, for goodness sake, human in the loop, get
your human editors involved because we know that AI's hallucinate, they talk rubbish,
and they're going to produce a best case useless content, worst case offensive content, and
you've got to be releasing that stuff.
Right, next story is from Amazon.
Amazon continues to step up its AI game, but this time it's not for shoppers, it's for
sellers.
So the online giant has launched a set of generative AI tools, and the aim of these
tools is to simplify the process of listing products.
So if you are dropshipping or working in e-commerce and you're using Amazon to sell products,
this is for you.
These new capabilities, essentially, they'll take a brief description from you as the seller,
and then use that to generate complete product titles, bullet points about products, descriptions,
et cetera, et cetera.
With a foundation in large language models, Amazon's generative AI promises to produce
high quality content that not only makes listing easier for sellers, but hopefully also enhances
the shopping experience for customers by ensuring that all products have richer, more comprehensive
product information.
If you are in the e-commerce sector, then we would predict that Amazon's latest innovation
could be a real time saving for you.
But significantly given our last story, also how important it is to make sure that you
are checking the automated descriptions and information that you're getting to make sure
that the information is accurate.
There's also going to be question marks.
We think about how to maintain brand style and brand tone if you're handling over content
generation to generative AI, which we would predict is going to produce a bunch of product
descriptions that all begin to basically sound the same.
If effective marketing is about differentiation, then the last thing that you want is for your
content to sound the same, even when it's things like product descriptions.
So yes, I think it's going to end up saving people a lot of time, but again, it's got to
be used with honor.
What do you think this means for the specialist copywriting services out there?
Do you think they're facing a real existential threat?
It's a good question.
I think if your main services revolve around e-commerce, product listings at scale, then
A, if you're not experimenting with this technology already, then you probably should be because
I'm sure that you are best positioned to figure out where its strengths and weaknesses are
going to be and perhaps how to scale your operations and be more efficient.
But human in the loop is critical.
I think if many companies think they can replace you with this AI, they're going to drift into
the muddy gray middle of everything that sounds the same.
And there are going to be certain products potentially where that's appropriate because
1% of people read the product description anyway, maybe.
But I think for those products where you really want to make sure that your content helps
convince customers on Amazon to buy your product and not one of the competitive products, I
think you're going to struggle to be a good, talented e-commerce copywriter.
That being said, I haven't seen many of the outputs.
Maybe they're using a lot of the writing frameworks and creativity in their ability to pitch products
and write compelling product descriptions that humans would use.
But somehow based on the outputs I've seen from other large language models, I would
doubt that they're going to be better than the true experts.
They'll be better than, if I'm honest, poor copywriters and average copywriters, but they
won't be better than the experts.
I wouldn't say.
What are your thoughts?
Likewise, if you are a copywriter and you're not playing with these tools already, then
the whole thing is an existential threat to you.
You've got to be looking at these tools to enhance what you're doing.
I'm honestly interested from a consumer side as well, the impact of this, because there's
loads of times that I've been on Amazon and looked at a product, a generic product, something
that is some generic label product and the description is terrible.
And it could just be that it's just badly worded English.
It's been written by someone where it isn't their first language and you get this description
and you're like, I don't really know what this means.
If we can get from a consumer perspective, just those kinds of descriptions tidied up
a little bit.
I don't need a crafted copywriter to come in and write this great thing that tells me
how good this de-bobbler is that I'm buying for a few quid on Amazon.
I just needed to tell me some basics.
Then great, I'm all for it.
I'm delighted to see Amazon integrating this technology into their core products offering.
Yeah, and I think there's an element of risk and reward.
If I'm a dropshipper or I'm working in e-commerce and I'm selling 10,000 products on Amazon
and I'm running a lean ship, I haven't got the bandwidth to hand write and hand check
all of the descriptions for all the products, especially when we get into translations as
well.
I think there's an element of if sometimes the product descriptions are inaccurate or
not very good, but they're on average better than nothing, I might take that risk because
I might feel like, well, for 9,500 of the products, it worked really well and it's helping
to sell more of them.
For 500, maybe it got something wrong or the translation wasn't quite right or whatever.
I do think it's a continuum.
I know we've just talked about how you got to check everything and I think there's a
number of different business cases where that is absolutely true, but it's going to come
down to risk and reward, how much time and effort you're going to invest in certain things
versus the improvement in results that you're going to get, and then as a business, just
making the decision that's appropriate for you.
Next story is from our friends at GoCharlie who we've had on the podcast in the past.
So for those that don't know, they are a multimodal generative AI tool for marketers and they
have just bagged $2 million in seed funding.
The investment aims to accelerate the company's mission of becoming the trusted partner for
enterprise customers in the AI enabled marketing space.
Recent guest and GoCharlie's CRO, Brennan Woodratt, told Axios that GoCharlie is making
strides in creating a large language model purpose built for marketers.
The new tool aims to deliver personalized content for brands across multiple platforms,
ensuring a consistent brand voice.
Investors like Goodwater Capital and SRI International are throwing their weight behind GoCharlie,
particularly valuing the startup's technical priorities and IP creation.
In the pipeline, GoCharlie is eyeing a larger funding round next year and they're also
on the lookout for potential M&A targets.
Woodruff expects that by then they'll have some large enterprise deals sealed, making
their company eye on.
And they've really made some significant changes to the tool, haven't they, Myron?
And I know you're a fan of GoCharlie.
So what have you seen and what are your thoughts?
Well following our conversation with Brennan a few weeks ago, they've actually launched
their AI agent, which he teased on the episode.
And it's pretty cool.
I must admit, I've really enjoyed having a play with it.
So it can do things like you can stick some URLs in it and ask it to write some tweets
or turn it into a blog post or something like that, you know, write a thought leadership
piece based on three articles that you found out elsewhere.
But where it really made me go, oh, actually, I really like that, is on Silly Little Things.
You can say to it, create a meme about the difficulties and the ironies of promoting
a podcast about AI and marketing.
And it will come back having used a meme image template and it's written a meme using the
right template, making something quite funny about the thing that you've just said.
It can create GIFs.
So you can tell it to go off and create little GIFs.
It will do campaign planning for you.
Now don't get me wrong, this is not the finished product, right?
There's more work to come on this, absolutely.
But seeing it one week after launch and having a play with it, it could do some things that
were more advanced than I was expecting, to be completely honest.
That's quite cool.
What's the quality of the GIFs like?
So I've only tried it for a couple and it tends to kind of make an image.
They're like slides, so it's almost like it's just flicking between slides on a...
So static images.
Static images, yeah, yeah.
But the kind of thing that you might use for display advertising or something like that.
But the memes, it fully understands the different types of memes that are out there.
I asked it to create one and it used the Spider-Man pointing at each other meme and it used it
in the right context.
I've seen some other examples where it's used, well, other meme templates and it's used them
well.
So yeah, that was pretty cool.
That sounds like quite fun to play with, actually.
That's interesting because I think the other thing with these tools is you might get something
that you can consider production ready.
Like I'm going to provide this on my social profile right now, but it might also just
give you new ideas that you're like, oh yeah, that's a funny way of using the Spider-Man
meme.
But I wouldn't phrase the text quite like that.
And then you as a human, I assume, can go in and then tweet the text to get what you
actually wanted in the first place.
Yeah, so the actual interface for it, I think you'd be better off saying you'd actually
tell it, put this text with the Spider-Man meme and it would go off and do that for you.
Right.
Because there's no way of actually editing the physical meme itself.
But because it's entirely driven through this single prompt interface.
Right.
So that's both useful and maybe if we can edit the memes ourselves, Brennan and Ting,
that might also be quite a fast and helpful and useful way to do that in the future.
I think the way that it's doing it at the moment is the agent is using the API for a
meme generator website.
Right.
I think, I don't know, that's my assumption.
We'd have to get a product like that.
As long as it understands your prompt correctly then, one assumes you're going to get the
type of output you want.
And it's almost like you're asking a, we always call AI an alien intern, don't we?
It's like you're asking an alien intern.
No, I don't want that text.
Go and swap it for this.
Yeah.
Cool.
Interesting stuff.
So if you haven't played with Go Charlie, and it is a pretty cool tool, it's even cooler
than it was before.
So go and have a play.
Right.
Next story.
Yeah, speaking of generative AI, one of the other players who was making waves a few weeks
ago has made an even bigger splash and that is Adobe's Firefly.
They've launched it properly.
It's finally out of beta.
So the tool is now widely available across the entire suite of products, across all of
Creative Cloud, Express and Experience Cloud.
It brings features like Photoshop's generative fill, Illustrator's vector recoloring, and
Express's text to image effects to the wider user base of Creative Cloud products.
So yeah, and now it comes with a commercial license, which is something that people were
hoping to see as well.
Firefly for Enterprise caters for businesses directly, offering a commercially safe environment
by using Adobe stock and public domain content for training.
And obviously that's been a big concern for a lot of users of any generative AI, particularly
in the image space.
Its generative AI capabilities offer a way for businesses to create brand specific content
rapidly and safety.
That even, and this is a really neat tool, provided this content credential, which is
a digital label that showcases essential metadata, which is a big step in supporting the responsible
use of AI generated content.
Effectively, it's a kind of metadata watermark to say how AI was used in the production of
any particular asset.
Yeah.
I mean, we've talked a lot about this tool and I think it's nice that you can use it
now without having to like go download Photoshop, the beta version.
Like that was going to be a bit painful for some people to like, I can't be bothered,
but now this is going to be right there in the tools that you use every day.
They are going to be increasing the price of the software.
So if you're like a Adobe Creative Cloud subscriber, you're going to pay a little bit more for
this.
I don't think it's huge.
You can get it out by like two or two to $5 a month on average, but they'll be increasing
the cost and you can use this on the web.
I think there's going to be like an Adobe Firefly website that you can actually go access
some of the tool without having to be a subscriber, but you're going to pay for credits in essence
a little bit like you do for a lot of the other image generation tools.
I think it's interesting, A, this is cool, but we've talked a lot about Firefly.
Maybe let's talk a bit about pricing, right?
Because they've introduced this now without beta.
If you want to continue to use it, your subscription is going to go up.
One assumes your subscription is going up when you use it on the wall.
That's a potential flash point for customers.
And we talked last week about Zoom introducing AI features, but without changing the subscription
price, and we also said today that we wouldn't pay the additional fee to access Google Do
it, but I continued to test it honestly if it was part of my ongoing subscription.
So what do you think is going to happen?
How's this pricing wall going to play out?
Do we think everybody's going to try and increase their subscription fees to cover the AI parts
of their tools?
Is it going to be a competitive advantage to not do that?
What do you think is going to happen?
The compute power suggests that the economics require people to be paying.
There's a certain point, maybe you give away a few users a month.
Stable Audio, for instance, are giving 20 generations of audio away to the free users
every month.
So I think it makes sense for companies to keep this a free tier option where you get
to sample it, because at some point the cost of compute is going to come down and the capabilities
of these products is going to go up to the point where it just makes sense to absolutely
increase your subscription.
You'll see the value at a certain point.
With Do it AI, the time is not in half.
With the Spirefly tools coming out across the Creative Cloud, I don't live in this suite.
This is not my world at all, but from what I've seen of it and the commentary I've seen,
this actually feels kind of production ready in a lot of instances.
So for that low price point, you know, we're not talking an extra $30 a month like we are
with Duet.
If it's in there, $5, $10 a month, and it's going to enable me to be considerably more
efficient and effective, then I'll pay that.
Is that classic, oh, it's a cup of coffee or it's a pint of beer, whatever your standard
value metric is?
Yeah, I think that's the critical piece.
Shouldn't keep battering Duet, but we're going to keep battering anyway, because it just
doesn't help enough.
It's kind of like an interesting oddity almost, like in terms of its power of use, and it
just makes me want to go back to ChatGPT4 or Claude, honestly, whenever I use it.
So that's why by definition, you wouldn't pay for it.
But I think the dream is we'll pay more for AI tools that genuinely save us quite a bit
of time or that allow us to do creative things that we couldn't do before.
Then there's a value prop, right?
The great belief around selling marketing automation systems is to be able to make a
case for, would you spend $100 extra a month if I saved you 20 hours?
Well, of course you would, and so would your employer, because your salary for those 20
hours is a hell of a lot more than the cost of this marketing automation system.
And I think that's where these tools need to find their space to justify how much you
pay for them.
I mentioned Loom last week.
The AI elements of that are interesting and kind of useful.
Like I'd like not having to write the title of the video on average, Loom got that right.
But often the description was like error strewn and the chapter markers are not necessarily
the chapter markers I would have used.
And so it doesn't save me much time and actually introduces a source of error.
Hence not going to pay for that as an additional, but I'll use it if it's there in terms of
what I'm already paying.
So I think the key here then is utility, isn't it?
If you've got genuine utility, we'll pay for it.
If it's kind of cool, but half-faked, I don't think we're going to.
My next story, it's Coca-Cola.
So Coca-Cola is tempting us with an intriguing proposition.
I don't know if Mr. Saul this story this week, they've released a limited edition drink called
Y3000 that's been developed for a unique blend of AI and human insights.
Coca-Cola has not been upfront about the actual flavor profile for Y3000, as you would probably
imagine.
There's a rumor that there's only ever like six people in the world alive who know the
recipe for Coca-Cola.
Is that, I don't know if that's true or not.
And they're never allowed to travel in the same vehicle at the same time.
Yeah.
So a subset of those, they know the recipe for Y3000 as one assumes so do OpenAI at this
point and are using it to further train their model perhaps, who knows.
So this is a pretty interesting one because Coca-Cola are like tapping into advanced technology
to help further develop their product.
Martin and I often talk about on this show, we really lean into promotions, marketing
and communications.
And if we actually think more broadly in terms of the four P's or the seven P's or the 26
P's of marketing, products are an important part of that.
And this is a great example of AI being used to enhance a product.
At the same time, they used AI to help create the artwork for the can and all this other
stuff.
So really, really interesting use of AI in a number of different areas.
And for marketers, it's kind of like an interesting lesson in the power of using technology as
part of developing your products and then telling the story around those products.
Coca-Cola, of course, are using this to create an even wider story around taste the future,
why 3000 is this is what Coca-Cola could taste like in the year 3000 because AI is developing
all the products in the world and all that good stuff.
I guess the question here, Martin, is this kind of like a marketing gimmick or do we
think we're going to see AI being used more in combined product development and promotion?
In the short term, yes, marketing gimmick and I am all for it.
I am leaning into this marketing gimmick and we are sat here promoting it on the show.
They've made a bit of a story on it.
Yeah, I love it.
And I like to see these stories.
I want to see brands doing cool stuff with their product development using AI.
In the longer term, yeah, absolutely.
I think it will be because all of us are going to be using AI tools all of the time.
So it's going to be part of the product manager's toolkit.
I don't think it's going to make a splash in terms of a story like this one, Will, but
we're going to see AI as part of the product development process because it's good at ideation.
It's good at helping come up with ways around.
It is quite creative, much as people don't think it is creative, it is quite creative.
So it can be used in brainstorming sessions.
So yes, AI for product development is absolutely something we're going to have more of in the
future.
Yeah, if I reflect on this and I'm a product manager, I'm probably like, if you're a product
manager and you're listening to this, I think it's a very interesting thought experiment
to think about how can I leverage AI and the hype train around AI to bake AI in a cool
and interesting way into my product and then tell an interesting story about it.
At the same time, how can I do that in a way that genuinely is interesting and doesn't
seem shoehorned?
Because I think you can also get this massively wrong and it's another case of, oh, guess
what, another AI first product.
My shoe allows me to jump further and faster and I'm better at basketball because it's
got AI in it.
Oh, guess what, this chewing gum lasts 5% longer when I stick it on the bedpost overnight
because it's got AI in it.
Like at some point, that's just going to become too much.
But what Coca-Cola have done here is they've made it all feel relevant.
Like it was not just a PR stunt, but that actually it was quite a cool and interesting
thing to try with their product.
And then they thought, oh, we can tell a brand story around this and we can actually make
AI and generative AI part of the marketing promotion strategy, help them create some
of the content and all those types of things.
So maybe a good thought experiment for the product managers out there.
And if you're more of a marketing communications pro, book in a meeting with one of the product
managers, get ChatGPT open and just start brainstorming between the three of you how
you might leverage this boom in AI to enhance your products and tell great stories about.
Right, next story, Martin.
EY, formerly Ernst & Young has announced a massive, is massive, $1.4 billion investment
into AI technologies.
And they're taking aim at the burgeoning market for AI embedded consulting services.
So this initiative places EY in direct competition with other consulting giants like KPMG and
Accenture, all of whom are investing heavily in AI as the next frontier for business growth.
The newly unveiled EY.AI platform, I said that with no complication, definitely didn't
trip over it, absolutely nailed it.
Chef's kiss.
He knew.
EY.AI, you can't do it twice in a row.
That's just ridiculous.
The new platform comes with AI infused versions of EY's existing product suite, including
EY Fabric, which is a data management tool already being used by their 60,000 clients.
So their intent is clear and it's really to integrate AI into every facet of their business
operations.
Apparently they're also looking to release their own large language model called EY.AIEYQ.
Get the brand team on that.
But there's a lot of work to do there on the front.
You've done spectacularly, Martin, to keep getting that right.
It's 5.30 PM on a Friday.
We should arguably be in the pub and you're trying to get your head around that.
EY, you've got to help us out.
We need a snappy name for that.
We'll ask TrackGPT for some snappy names and we'll email them over.
Yeah.
So this sounds like it's going to be used for an internal tool for EY staff, but who
knows, maybe this will be rolled out to their customers.
No news on that at the moment.
They've secured an early access partnership with OpenAI's capabilities through Microsoft
Azure, including GPT-3 and GPT-4, and they formed some partnerships with tech giants
like Dell, SAP, and Thomson Reuters.
I think what we're seeing here is just another step by all of the big consultancies to jump
onto the AI hype train.
Deloitte have done it, McKinsey are doing it.
We've seen their KPMG and Accenture are doing it.
It's becoming integral and big companies are clearly going to these consultancies saying,
hey, we need help in this space.
So they've got to be making a lot of noise saying, we know what we're talking about.
Look at these investments that we're making.
We're on it.
You can trust us.
We're ahead of the game.
I agree.
I think there's a question here, right, which is, is AI embedded consultancy service, is
that the norm pretty much from here on out?
I mean, what do you think about that, Ryan?
Well, I think it is because AI is going to be baked into everything.
So you've got to speak that language.
You've got to know and understand what AI is in the same way that these big companies
for the past decade or so, the buzzword has been digital transformation.
That's what they've been doing.
Deloitte Digital has had loads of thought leadership pieces on this.
You go on the McKinsey website and it's talking about how digital supports growth.
It's going to shift from digital to AI.
That's what we're about to see.
Absolutely.
In fact, what an opportunity for us to talk about our AI transformation services offered
by the team at Heart's Officially Intelligent Marketing to help you bring AI to your organization.
It weren't called AI transformation services.
We were just offering training and consultancy, but I like that, Mahin, and I think we should
TM it.
It's probably been TN'd already and bought it on the website anyway.
I agree with you.
There's a number of aspects to this.
I can imagine a future honestly where you can pay to access a McKinsey bot that is your
first call for questions about your business and you can get a form of guidance through
the bot and you subscribe to it.
But as we know, digital transformation, implementations of CRMs, implementing AI in your business,
it's not just about having experts help you know what to do.
It's the change management and the training that comes with actually embedding that in
your organization, which I think the humans at McKinsey and at EY and people like ourselves
are going to be doing for quite a while because bots are not going to be able to do that because
that's going to be about working with people and bringing people along on the journey,
inspiring them about what's possible, enabling them through training, etc.
Right, last story this week, we are talking MailChimp.
So MailChimp, which was acquired by Intuit not that long ago for crazily large money,
is bringing AI to its suite of tools.
So it's basically baking in Intuit Assist, which is a AI chatbot style tool that Intuit
has obviously been developing, but now it's going to be made available if you are a subscriber
to and user of MailChimp.
Why is this interesting?
Because it's bringing some of that power to small and mid-sized businesses, right?
MailChimp has always been a fantastic tool for smaller companies to use if they didn't
have the budget to invest in more expensive tools like, let's say, Salesforce and the
higher tier options of a product like HubSpot.
So that's kind of the goal here.
They want to be able to bring generative AI to help those SMBs be more efficient.
And the tool promises to enhance marketing journeys, help customers better understand
customer desires, and provide a host of features from connected e-commerce integration to inline
email editing.
Intuit Assist is geared to help businesses generate content, tailor their marketing strategies
and quickly learn from their campaigns, and offers capabilities like real-time content
generation for new product campaigns and even multilingual copy translation.
This tool is integrated seamlessly into the MailChimp ecosystem, so it should be pretty
easy for small businesses to use without having to break the bank.
So this is really cool because it's bringing really significant generative AI power to
smaller businesses and making it much easier for them to leverage.
What do you think, Mark?
Do you think that MailChimp's Intuit Assist is going to democratize access to AI in the
SMB space, or is it not just about having access to technologies, training and understanding
what the tools and stuff can do, still going to be a bit of a barrier, do you think?
This story really caught my eye because I'm a QuickBooks user, and Intuit Assist has also
been integrated into QuickBooks.
And apparently that is allowing QuickBooks users to automate tasks like drafting invoices
and drafting invoice reminders and managing reports and all sorts of things like personalized
recommendations and helping on a bunch of tasks that as a small business owner, you
just get swamped under or you might push under the carpet and forget about.
So as a QuickBooks user, I was quite excited to see that it's being rolled out to that
as well.
I think it is going to be a big benefit to smaller mid-sized business owners.
In the same way that HubSpot is baking in the generative AI tech and just making it
really easy to use in the tools that you're already using every day, it sounds like that's
what's going to happen with MailChimp.
So I'm expecting, and the devil is in the detail, the detail here being the user experience,
how do they build it into the workflow?
If I'm creating an email marketing campaign, does the generative AI do the whole thing
for me in like a wizard based editor or are they adding in a tool that will write me a
smart subject line where I'm typically writing the subject line?
How does it work?
I think it's going to be a big benefit to people looking to, well, anyone that doesn't
know how to use AI and is interested in it, having this capability baked into that platform
is going to obviously increase AI adoption.
Yeah, it strikes me that the race to embed AI in all of the tools we already use is on.
I think that will fizzle out quite quickly.
It could become table stakes reasonably quickly that you expect some sort of support agent
to be able to do things for you based on natural language prompts to help you create content,
to answer questions about your data and help you do data analysis, to smart automate certain
tasks.
And then user experience becomes key, right?
Who makes that the easiest to do?
Assuming that the underlying technology, the large language models that power this ability
to understand natural language and take action based on it that these bots will have is basically
the same, right?
If that's always the same, then it's about user experience and how easy they are to use
and having them in the place where you already do stuff you already do, like Mailchimp.
If you're a Mailchimp user or Microsoft Word or HubSpot or any other platform that you've
got.
So it might be interesting for us to look back at the end of 2024 when every piece of
software's little chat icon that everybody has in the bottom right that basically will
help you answer simple questions or sends a message to a human in customer support is
in essence not that at all anymore.
It's a LLM powered conversational agent that doesn't involve any humans that helps you
do a heck of a lot more in the software that you're using than you were able to do before
all powered in an interface that's kind of similar to the kind of chat, web chat interfaces
that we already use today, but just powered in a different way.
Yeah, and before the end of 2024, I'd say by the end of 2023, saying that your software
product has AI capabilities is going to be so passe, it's like saying that you've got
a website.
Absolutely.
So there you have it folks, that's what's been going on in the world of AI this week.
As you know, we deliberately focus on all the stories that we think are going to be
the most important for marketers.
So there's been a bunch of stories this week like all the key industry bots have been meeting,
having important meetings in Washington about the ethics of AI and all that good stuff.
It's not that that stuff's not important or we recognize it's important, but we do like
to focus as much as we can on the practical aspects of AI that are going to be impacting
the workflows of marketers and small business owners across the world.
If you like this podcast, then please subscribe.
If you really like it, tell your friends about it, especially if you think they find it interesting
or they would benefit.
Thanks as always for your time, Martin.
I will look forward to catching up with you next week.
Speak to you next week, Paul.