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.
Hello, and welcome to episode 30 of Artificially Intelligent Marketing.
Crumbs, how did we get to episode 30?
That's very exciting.
Martin's here with me, Martin Broadhurst, my co-host.
How are you Martin?
What have you been up to this week?
I'm very good.
And I have been having a very busy week, working with lots of businesses across my patch.
In fact, I've delivered two workshops about getting started with generative AI this week.
Across the two workshops, we had 20 businesses in those sessions.
In fact, I've got two sessions coming up.
I've got one tomorrow in workshop and another one in Leicester.
So it's a hot topic at the moment.
Both of those upcoming ones are sold out.
So yeah, it's fair to say that this is a high demand area at the moment, which we are both
well aware of.
You've been a busy boy then.
It's good to hear that you've been getting in about and preaching the benefits of generative
AI.
I had a kind of similar experience myself this week.
I was at the Elrig Drug Discovery Conference up in Liverpool, which was fab, extremely
well attended, which was great to see.
While I was there, I actually gave a vendor workshop for all the vendors that were at
the event on generative AI and the power of the tools that we talk about week in, week
out on the podcast line in terms of how they can be more effective, more efficient.
That was really great.
It was interesting.
I did a lot of the polls that we often do in the workshops that we run and I noticed
that a lot of people had tried to chat GPT and there were even a couple of power users,
but much fewer had tried image generators, interestingly.
So given that the audience was predominantly marketing and sales folk, that's kind of a
bit surprising to me, but I think it's another good example of when you spend as much time
nerding about AI as we do, Martin, you forget that a lot of folks have perhaps not been
exposed to some of this stuff.
Especially I showed them the Hey Jen example that we've talked about on the podcast a few
times and that we've routinely used at our workshops with the, for those of you that
haven't seen it, in essence, someone records a short video on their phone.
30 seconds in English and then Hey Jen automatically dubs it and lip syncs it in different languages
and you really have to watch it to see what we mean because it at first glance looks like
it was originally recorded in those languages.
The audio and the lip sync is so good.
I also found it interesting that I'm definitely starting to see some segmentation occurring
in the people who are working in marketing.
There's definitely people who are still, like they know about ChatGPT but maybe that's about
it and they're really interested to learn about other tools but they haven't really
played with them yet.
I think that's quite a large section of people in our marketing sphere that we play in.
There are, however, a few like ninja power users who are starting to get really to grips
with all of the foundational tools across image creation, music creation, voice creation,
ChatGPT for text and all that other stuff and they're starting to do more power use
cases like connecting to Zapier, running multiple workflows, trying to use different data sources
that they push into a table or Google Sheets that then they use as prompts in ChatGPT to
automate me create prospecting emails that are automated and customized on a use case
by use case basis for each individual person that they want to email.
So definitely seeing some of that segmentation, you see much of that in the workshops you're
going to?
Yeah, very much so.
What I'm finding really interesting is that this technology is so different in terms of
the adoption from people, the enthusiasm to adopt.
I've been in lots of workshops in the past and sessions where, let's say the topic is
search engine optimization and business owners and marketers go, right, I'm here to learn
all about this thing.
I know it's really important to get found in search and then they do the workshop and
at the end of it they come away going, I'm still a bit frazzled.
I understand its importance, but I still don't really know how to get it started because
something like SEO might have the kind of dark arts element to it and a bit of mystery
for people that don't do it every day at least.
If you're immersed in that world, you understand all of it, but it can be quite jargon heavy.
With this, it's completely different because very quickly people can see value.
That time to value for the user is very quick.
You load up an interface like ChatGPT and kind of show people, certainly in the workshops
that I do, I might take somebody's homepage and stick in a prompt and get it to critique
their homepage copy from a particular perspective or how might they improve their copy to appeal
to a particular audience.
Very quickly people go, oh my God, that's a time saver, I'm going to take that away
with me.
In fact, one of the workshops I did this week ran a series of prompts and one of the delegates
said please send me that, email me that content, I want to see it immediately.
The enthusiasm for people to get stuck in is so different to other technologies that
we might have seen in this kind of digital marketing space.
Yeah, I think that's definitely what happens.
People see these different use cases and then they think, oh, I can do that if they're showing
them and also once you start playing with the tool and you let your creativity run a
bit wild, I think you can really find ways to use it.
Obviously, a lot of people are getting started with ChatGPT but the other question that's
coming up for me again and again is outside of ChatGPT, what tools should I be using?
I know we've had a bit of a talk about this off air, Martin, so dear listener, if you
are also asking yourself that question, we're going to do a little segment at the beginning
here just to take you through some of our favourite tools.
For me personally, I am using Magi a lot, which is, how can I describe it?
It's basically a front end on ChatGPT but you can also, so it's like a chat bot basically
that you would use the same way you use ChatGPT but you can access multiple models, so you
can access Claw 2 that we've talked about a lot on the show that has its large context
window and makes it perfect for summarising stuff.
You can also upload files like PDFs so you can ask them the tool to summarise them or
you can in essence chat with the PDF and ask questions of the document which is especially
useful if the document's very long.
Because Magi works with the API version of all these tools and most major tool users
certainly OpenAI have stated that they won't use any information that comes into their
systems via the API, you can have that much more confidence that any materials that you
share within those tools are, the information is not shared and used to chain the model
which I know is a big barrier for a lot of people wanting to use the tools.
So using Magi as my ChatGPT clawed everything in one place replacement, it's also got custom
instructions like ChatGPT but you can in essence give it a whole suite of custom instructions
that are called personas and you can choose the persona that's the most relevant for whatever
you're doing.
So I've got master summariser, expert copywriter, I've got marketing strategist, I've even got
one persona that's set up to help us write the scripts that we create for the podcast
so it just all I do is drop a story in and then it gives me a script to play with in
it.
So very good worth looking at.
Another tool I use a lot is Audio Pen, so this allows you to basically dictate emails
and other things that you would ideally usually write down but for whatever reason you think
faster when you're speaking or if you're out and about like when I'm walking the dog or
playing with the dog in the garden, I'll just speak to Audio Pen on my phone.
The difference between this and using sort of any other like transcription tool that
I've used in the past is that it uses the power of ChatGPT so if I ramble a little bit
like I am now with what I'm trying to say or the note I'm trying to leave myself, it
pushes the transcript that it captures through ChatGPT and then is able to format it in proper
text and again you can have different personas to make that fit your email style or to create
bullet point lists whatever you might do.
My favourite image tool at the moment is ClipDrop.
It's got image generation capabilities in it.
ClipDrop uses stable diffusion, stability AIs models.
The image generation is pretty good.
It's not as good as Mid Journey and probably not as good as Dauley 3 to be honest but the
reason I love ClipDrop is it's got a whole suite of tools.
It's got background remover, spot eraser, relighting, sky replacer, upscaler, so many
tools, really great price, love ClipDrop and its ability to remove backgrounds is insane.
I keep throwing more and more complicated images at it thinking I've killed it this
time and it strips the background out.
Favourite use case so far for that one Martin is I'm always in the need of logos and I
can never find the one that's got the transparent background and so now I just do a quick screen
grab off a website, chuck it into the background remover and it comes out perfect with a transparent
PNG background which is just awesome.
I'm also loving finding new ways to use Dauley 3's chat GPT vision capabilities so both for
image creation in Dauley 3 but as an example for my presentation at Elric this week I wanted
a table that compared all of the different models you could use right like Bard or Bing
or chat GPT because I didn't have one.
I don't know why I didn't have one but I did.
So I found a really good one online that had some stuff that I wanted but I needed to change
it because I felt it wasn't up to date and some of the stuff I didn't agree with but
it was an image.
So I took a screen grab of the image, fed it into chat GPT vision and I said there's
a table in this image, reproduce it as a CSV so I can copy paste it into Excel so I can
edit it and it came out perfect.
So there's just so many cool things that you can do there and then finally on the sort
of video editing and podcasting Descript is an amazing video editor you push your video
in and then it creates a transcript of it and then you can edit it like it's a Word
document so you highlight bits of the script that you're going to cut out and then it just
automatically edits it all for you.
It's also got some nice tools in there to help clean up audio although it's not as good
as Adobe Podcast Enhance which is insane.
I routinely now record my talks at different events on my mobile phone.
I just sit it on the plinth where I'm speaking.
The echo-y terrible audio Adobe Podcast Enhance can strip out most of the background noise
and either make it sound really polished like it was professionally recorded in the type
of like I was mic'd up and stuff or even to the point where you can strip out all the
background and it sounds like I was working in a proper studio.
So on the audio restoration it can really do incredible things and is worth playing
with.
So for the people that keep asking me, that's the answer to that question.
Martin, I know people ask you this a lot as well.
What's your favourite tools to play with?
Well, the tool I wouldn't live without is ChatGPT Plus, right?
Given at this point GPT-4 access is kind of critical but I find myself using all of the
features within that Plus subscription.
So the Dali 3 image generation is increasingly...
I didn't do a lot of image generation.
If you'd have asked me a few weeks ago, I was always playing with mid-journey.
I was taking the occasional image from mid-journey and putting it into slide decks and presentations,
but I wasn't doing a great deal.
But now because of the way that the prompting in ChatGPT with Dali 3 works, I find myself
going to it much more regularly.
It's just part of the way that I use the tool more naturally.
Because it will ask questions to improve my prompt.
That's what I like about it.
One of the things with mid-journey is I often got frustrated trying to craft the perfect
prompt whereas now this does some of the hard work for you.
The browse with Bing functionality has actually meant that one of the tools that I was using
really regularly, which was Perplexity AI, I'm using slightly less now, which is a shame
because I've just bought the annual subscription.
But Perplexity, because it's a real-time search engine and it's all running the answers through
GPT-4, was really useful for getting AI content about to the minute, fact and information.
But actually now I find the browse with Bing is doing that for me.
I was working with a client this week.
They needed some content for the website that was reflective of some legal changes in their
industry from September this year, so within the past three weeks.
We switched on browse with Bing, we ran a few prompts, we got the content that we needed
to stick on the website and update a marketing email.
That was done in seconds.
So that was really useful.
Unlike you, I don't have Audio Pen, but instead I have the Zapier workflows that connect through
Whisper API.
So I'm always recording voice notes on my phone and just uploading them to Google Drive,
which then goes to Zapier, sending them off to Whisper and running them through a sequence
of different transcriptions.
Audio transcription for me is one of the biggest efficiency gains that I personally get from
AI.
So whether it's recording voice notes when I'm out and about or doing conference talks
if I'm doing a conference talk or if I'm at a conference listening to a talk, I'll take
the transcription and try and capture some notes from the sessions.
But also being on meetings.
So I like everyone these days, I'm either in front of chat GPT or I'm on a Zoom call,
an MS Teams call or a Google Meet call or something like that.
Having all of those transcribed for me is a godsend.
It's made my admin much easier.
It's made if I'm on a sales call, it's made the post call follow up so much more effective.
And that's because I use a tool called Laxys.
I'm hopefully getting Laxys CEO Eric on very soon.
It'd be great to have him on the podcast.
But that does a great job of just capturing all the notes, writing the follow up emails,
giving me the action items.
And actually what I do with that, I'll often take the full transcript from a call and stick
that into the other tool.
If you were to say I could have two tools and I couldn't be without them, maybe three,
maybe three.
The thought of having to go down to two then made me struggle.
It made me have heart palpitations.
The ones that I couldn't get rid of would be probably Laxys, chat GPT plus and Claude.
The hundred thousand token context window, the amount of information that you can feed
into it and the outputs that you can get as a result of that context window.
It's a daily driver for me.
In fact, I'm using that easily two or three times a day, every day, even on weekends.
It's just so ingrained in my life at this point.
So yeah, that is definitely a big one.
On the audio side of things, I don't use Descript because I don't have the editing skills that
you have.
But I have started playing and using over the past month.
I've got a subscription to 11 Labs and 11 Labs is the voice synthesis tool that we featured
on this and it does a great job of creating synthetic voices.
It can clone your own voice.
We featured it on a recent episode where it had the dubbed version of my voice into Italian.
And it's a really neat little tool and I've been using that to create little audio snippets
for social media videos for myself, showing clients and proposing that we build this into
some of their social campaigns as well.
And yeah, so far people are very receptive to it.
I think one of the things that people like about it is, well, you know what it's like
trying to do voiceover, right?
And there's loads of voiceover artists online.
You can get them from marketplaces pretty cheap, pretty efficiently and they do great
work.
And whilst I don't want to take work away from voiceover artists, if a client is knocking
up a 30 second social video that needs a little bit of audio with some spoken words over the
top of it and they can do it in something like 11 Labs and it takes them, they can do
it in five or 10 minutes, that's so much more efficient from their workflow compared to
writing the draft, putting it on a board, getting the voiceover artists to respond, going back
and forth, getting the recording, feeding the amends.
Like all of that is a headache.
And I really don't like that AI is going to be taking those kinds of jobs away from people,
but there's a reality to this that actually, I think that's an area where some voiceover
work is going to be lost to AI like 11 Labs.
Well, and if we look at some of the applications of where you might want to do audio on a person
by person basis, like if you're doing sales prospecting and you want to leave like a personal
voice note, in theory, you could probably start to synthesize that whether or not that's
a bit disingenuous for the people who get those notes.
I'm sure we'll learn to sniff those out like we do the prospecting emails that do a terrible
job of making us think that they're just for us.
But yeah, I hear you on that one.
That's a tricky one.
But like you said, the other thing that often happens is when you get the audio back, you're
like, ah, actually, I wish the script had been this instead.
And of course, you could just make that change instantly if you use a tool like 11 Labs versus
rerecording and rebreefing and all that other stuff.
Yeah, exactly.
And that's where the benefit comes.
That's where the efficiency game come because you can iterate quicker.
You can just produce 20 different versions and pick the one that you like and you can
do that sat at your desk rather than having to go back and forth with a recording artist.
Yeah, so that's the tools I'm using.
I mean, there's other tools I'm big on and a part of my core workflow.
So HubSpot's suite of AI tools, I use them regularly for drafting emails.
Principally, I'm using the content assistant.
I'm not using their lead forecasting for myself, but certainly rolling that out with clients.
I mentioned mid-journey or ready for image creation, but that is getting increasingly
lower usage since Dali 3 is coming out.
But one tool that I am finding myself using more and more since the recent updates that
we did discuss on the show is GoCharlie.
So I've had GoCharlie for a while and they recently released their marketing agent, as
it were, and you can give it commands and it will go off and perform tasks.
And I'm finding that really useful, particularly for video summarization from YouTube videos.
That's not the only thing I'm using it for, but that is something I'm using that for two
or three times a week.
I'm absolutely turning to GoCharlie to capture some great extracts from long form video content.
Cool, cool.
Well, there you have it, dear listeners.
Obviously we get asked this a lot.
There is a bullet point whistle stop tour of a billion tools for you to go try, but they
are based on us trying at least 10 times as many tools as what we just described, many
of which we left behind because we didn't really feel like they really did much to our
workflow.
And of course, and I think most people, certainly those listening to the podcast are probably
already going to be here.
If you're going to start anywhere, you start with ChatGPT Plus because it just has so much
power in it, it's probably going to be able to do 80% of the things that most marketers
want to be able to do.
And then when you want to get into more exotic use cases like editing video, creating video,
creating synthetic voices for audio versions of your blog posts and all this other stuff,
then of course some of those tools will help.
Right.
Let's get into the news, Martin, the new ooze.
What have we got as the first news story this week?
So we've got big news coming out of Jasper.
Jasper AI, one of the first tools on the market to really make use of the GPT-3 API.
They put a front end on it and made it really easy for marketers to create marketing copy.
They did all the prompting in the backend and just gave a really nice UI for people
to be able to create content.
And they've been on the market for a few years now.
As the market has evolved, so has the need for products like Jasper to evolve.
So while it was once primarily a generative AI tool for quick content creation, it's now
seeking to become an AI copilot for marketers with a much greater focus on strategy.
So this is a significant expansion for the product, but also for the company.
They just had record breaking series A funding and recently had a change at the top of the
company.
They've got a new CEO, the former Dropbox president, Timothy Young.
So the founding CEO has recently moved roles.
So this expansion is very much multifaceted.
It's designed not only to accelerate, but also improve marketing performance across
a range of areas, not just on content production.
So one of the areas that they're looking at, they're looking at analytics and insights,
including real-time performance analytics on content with AI recommendations to optimize
any underperforming content, as well as one-click deployment for content revisions.
So fully integrated into your workflow.
This is really what they're about now.
It's about helping execute tasks as well as create content.
They've got what they're calling a company intelligence hub, which is a central storage
for all of your brand voice.
Now this is an area that we know companies really struggle with when it comes to tools
like chat GPT, just sounding a bit too generic.
So Jasper are tackling this straight on.
You can upload all of your company documents into the central storage.
You can have strategy documents and other wider institutional knowledge, all of which
will help the AI to create less generic outputs and reduce inaccuracies and bring that knowledge
into the output.
So it can be more kind of fine tuned as it were to your own company information.
And it also allows for kind of dynamic updating, right?
You can import new documents and that gets incorporated into the model straight away.
As well as that, they've got some wider marketing campaign tools.
So what they're calling the campaign acceleration tools, including integrated assignments, comments
and scheduling to improve team collaboration.
And they are doing features such as AI summaries of feedback from teams and one click automation
of revisions.
All of which shows that they're really moving away from being a tool for kind of solopreneurs
or single entrepreneurs where I think that was a big market for them in the early days.
It was, they were one of the first AI writing tools on the market.
So if they could help really small businesses to produce content quickly, that's very much
where they were positioning themselves.
But this change and this repositioning is squarely putting them at the, trying to get
them in front of teams, marketing teams.
This is about collaboration, about security, about feedback and revisions and all of that
kind of thing.
Just on that point actually, they have enterprise controls coming.
So they've got API availability for platform integration, which presumably is how they'll
be doing things like the one click deploying of content and the revisions.
You can easily imagine Jasper being fully integrated with the HubSpot marketing suite
and you could deploy it, getting the content from Jasper into an email marketing campaign
or a blog or a product page in the CMS.
They've also included SOC2 compliance for added security and they've added more administrative
tools which will give greater levels of control over things like user permissions and work
spaces, both private and public.
So yeah, it's a big shift for Jasper.
You can see where they're heading.
Obviously they couldn't just be a content creation tool anymore because you can do all
of that kind of stuff with a well-crafted prompt using Bing Chat AI, which is free.
So if they're going to get value, if they're going to continue to offer value to companies,
they've got to move up market and basically make sure that they are a real, well, as they
call it themselves, marketing co-pilot for teams.
I think this is a really smart move because, and as a callback to the beginning of the
episode, we're often asked what is a great tool for creating content and writing and
ultimately TrackGPT 4 is probably still the best tool in my opinion.
I've tried Jasper, I've tried CopyAI, we were piloting and testing a tool called Writer,
RYTR before TrackGPT was released, probably two years ago, something like that.
And I think where a lot of these tools like Jasper were in risk is kind of being sort
of augmenting people's writing by having lots of templates that write in different marketing
frameworks like Ada or whatever.
But actually not really necessarily being that helpful compared to just using TrackGPT.
This is a really powerful mechanism to really differentiate Jasper as to why would you buy
over the other stuff?
I think you're bang on.
And actually it gives me a bit of FOMO.
I can't say I've had much FOMO when it comes to most of the writing tools.
So it's pretty just happy using TrackGPT or in my case Matchi which is just really a front
end for TrackGPT.
But I could see how a lot of that stuff would actually be really quite useful, especially
for larger companies.
So as is proving the case, you can't really make any hard and fast decisions on what tools
are going to be good or not.
You've got to pay attention to all the different changes that are happening in the space.
So that as tools release new things and it brings them back into contention, you know,
and then you can go test them and play with them and see just how capable they have become.
So Jasper's back on my go test it list.
Cool.
Good story.
Thank you for sharing that, Martin.
Into the next story then, and this one's an interesting one about Anthropic and Universal
Music.
So Universal Music has lodged a copyright infringement lawsuit against Anthropic, which
for those of you who are regular listeners of the podcast will know, has created one
of the large language models Claude II.
And the reason is that Universal Music has accused Anthropic of generating nearly identical
copies of lyrics from Universal's artists via the chap Claude.
Universal along with Concord and ABCO filed the lawsuit in a US court stating that when
Claude is prompted for lyrics to songs like Glory Again as I Will Survive, it produces
a near verbatim rendition.
Music which has investments from Amazon and Google has yet to respond to the allegations.
This is quite interesting because we know that Anthropics Claude is trained in a slightly
different way and its reinforcement learning is a bit different from how ChatGPT works.
I haven't heard anything like this coming out of ChatGPT, but I don't know, mine, does
this flag to us that for all the Claude love that we give on the podcast, especially yourself,
is it maybe slightly more likely to produce things that are a bit more plagiarized that
are not just driven by its clever vector models and that actually there's a little bit of
reproduction happening here?
I don't know, what do you think?
Too early to tell.
I wouldn't be surprised if we see similar suits coming out against OpenAI and ChatGPT.
It wouldn't surprise me, I'm not saying that is likely at all, or I don't have any inside
knowledge that these cases are pending, but I think as more companies do more of these
kinds of experiments on large language models, they're going to come across cases where clearly
copyright data has been put into it and if you get the prompts just right, it will spit
out something very similar.
There was the example with Katy Perry's Raw, which was a big thing in this story as well.
So yeah, they've clearly got it across a bunch of different artists.
I think there was one also where the prompt asked it to write a story about somebody's
death.
It was a high profile person and it came back with lyrics of a song that was actually a
real song that was about that person's death.
Clearly they were trying to trick the model into recreating a piece of, well yeah, recreating
a song.
So yeah, I think Anthropix got some answering to do here.
I don't really know what the, you know, what is the case?
Is it that it was trained on it or that it generated the content?
Because if I ask you to write me a song and you come up with a song that has lyrics that
are nearly identical to Katy Perry's Raw, for instance, I guess you would be, if I was
to then publish that, you, me or both could be sued for publishing it.
But for just recreating them and writing them down, do you get, is that worthy of a legal
complaint in and of itself?
Well, I guess it's interesting, A, it would definitely imply its ability to reproduce them
pretty much verbatim would imply that the song words were included in the training material.
So I suspect that's where the main issue lies.
In terms of producing aspects, like I could definitely imagine use cases where I would
love to use a really good quote from an author or a famous person, but I just can't quite
remember the quote.
So I go ask ChatGPT or Claude in this case to give me that quote and remind me of it
instead of using Google.
And then where, you know, where does that issue lie?
If you search for song lyrics, you will be able to find them in snippets on Google search
results page if you really wanted to find Gloria, Gloria Gaynor's lyrics.
So yeah, it's, I think it's going to come back down to training and this is probably
the best example yet that any of these companies has found to prove unequivocally almost that
their IP was used in the training.
I think that's why this is important.
But I think we're going to, we know that copyright material was included in the training.
So I'm really interested to see the specific legal challenge here.
Because is it effectively just the music version of the Sarah Silverman case against OpenAI
and their training?
In which case, you know, I think these language model companies have, they're going to have
to change their revenue structures or the way that they do licensing.
I mean, you know, how are you, given the way that they work, every time you put a query
into one of these models, the inference will check the whole model, right?
It doesn't just go off to a certain domain.
It runs it against the whole massive model.
You can't charge on a per inference basis.
I just don't understand.
Clearly smarter people than me are going to have to work out that licensing model.
They're going to have to figure this out.
And I think one of the complexities here is if Sarah Silverman feels like her entire
book was used in the training of a large language model, either because the digital version
was accessed or procured somehow.
That's one thing.
The lyrics to lots of songs float around on the web because people want to know what they
are.
You couldn't really access them at the start of the web.
That wasn't something you could easily get hold of.
And so these massive websites sprung up where you could get the lyrics to any song.
We know that a lot of these large language models were trained based on content found
across the web.
And actually the emergence of the World Wide Web is an important precursor to even being
able to have these models exist.
So what do you do then?
If you're open AI and you're training your model and there's 52 copies of the lyrics
on these sites that, by the way, Universal Music hasn't pulled down over the last 20
years for whatever reasons, how are you supposed to stop that ending up in your material?
Or then by default, do you then assume that everything on the web was actually copyright
material because somebody wrote it and owned it in some way?
It's so complicated.
In fact, probably spend the next two hours trying to debate this, even though neither
of us have any real legal background and therefore probably not the qualifications to do so.
Suffice to say, Martin, if you're a marketer, you've got to keep a close eye on how this
is all drifting because I guess one potential is at some point the tools that we've come
to know and love, they all get stopped and we're not allowed to use them for some period
while all this gets sorted out.
I don't think they'll ever disappear forever.
I think there's just too much commercial opportunity for all the people who've built them and even
the people whose stuff got used to train them.
With open source models out there, the genie is out of the bottle.
Just to pull it back, before we move on to this story, the song that I was referring
to, I've got the story in front of me.
It said, the complaint used the example prompt, write me a song about the death of Buddy Holly,
which led the large language model to spit out the lyrics to Don McLean's American Pie,
word for word.
Interesting.
Especially given that I assume just that stanza that's about...
Anyway, the whole song's got loads of other bits in it.
I think as marketers, fundamentally, we're going to have to keep an eye on this in case
it influences how we can use the tools.
Certainly the same things apply if you're using chat GPT, don't use the outputs as they
are as they come out.
There's a whole host of reasons not to do that.
The first is you can't copyright them, that seems to be where legal precedent is drifting.
If you use them as is, often the writing will be a little bit stilted and a bit samey.
There's lots of kind of like grammar loops.
It loves to start a sentence with this, for example, which is not necessarily great writing.
So edit the outputs a lot.
You want them in your own brand voice.
You want to add some insight that chat GPT doesn't have, that your own brand and your
own subject matter experts have.
Scan your content through a plagiarism detector to make sure that chat GPT hasn't just lifted
any content that somehow made it through your rigorous edit and is still present in your
copy.
All these things are still just really, really good advice.
And if this story develops and it impacts how we're as marketers able to use these tools,
well, dear listener, you'll be sure to hear about it first on the Artificially Intelligent
Marketing Podcast.
Should we put those song lyrics to bed?
Right.
The next story is with you, Martin, is about celebrity clones.
Yeah.
So in a compelling mix of fan service and AI, high profile prominent figures such as
Tim Ferriss and Scott Galloway have trained some AI chat bots on their accumulated body
of works, including their podcasts and all of their blog posts, which, you know, is a
large volume of content.
The promise of these chat bots is simple and captivating.
Pose a question and your favorite thought leader will answer based on their previous
statements and insights.
So you get your own Scott Galloway in your pocket, so to speak, which is quite a neat
and handy way to distill the mountains and mountains of content that they've run over
the many years.
So this is a digital trend that is not just confined to business gurus.
Meta is pushing the envelope further by introducing celebrity inspired chat bots on Instagram,
where users can interact with AI versions, AI avatars of their favorite stars, such as
the YouTube sensation, Mr. Beast.
So these initiatives are more about prioritizing entertainment over practicality, admittedly,
pending the results of the popularity, they could pave the way for new and innovative
use cases as yet not seen.
So the target market for this is likely to be Gen Z, who are particularly taken with
character AIs companion chat bots, where you can chat with various different characters
with their AI avatars.
So this poses the question about whether it could be a significant trend in the influencer
marketing space.
If AI avatars, and we already see actually AI created, well actually I'm not going to
say AI influences, it's more the CGI created and managed avatars are very big in the influencer
world.
Now, if we can do this with AI as well, who needs real people?
Why pay real people for their influence when it could just be an AI created character?
Yeah, what did you think about this one?
How do you fancy a Tim Ferriss in your pocket?
Yeah, it's interesting.
So there's a sort of futurist that I followed called Peter Diamandis, and he's already got,
I think it's called Peter Bot, which I've had a play with and there's two versions.
The free version is like Chat GPT, but it's influenced by Peter Diamandis' writings and
podcasts so it produces information related to what he usually talks about, but also with
his trademark optimism and excitement, which is kind of nice.
And then if you pay, it will actually create a Hey Jen-like version of Peter's who he
actually speaks and it's video, which I think is just a really interesting exploration of
this.
And then I can see the continuation of big personalities, big celebrities, big thought
leaders, the Simon Sinek's of the world doing something similar, either as part of their
own offering or licensing their content and likenesses.
But if you follow it even further, because I think one of the key things with all of
this AI driven tech is just how quickly it becomes really cheap and anyone can basically
do it, that if you've got a load of material on your own company website or your blog post
and what have you, how do you approach this as a brand?
Do you have like a new synthetic human AI influencer straight thought leader that's
basically trained on all the content you've ever produced for your company?
Do you choose one of your subject matter experts to be that person?
I think we're going to see a lot more of that.
I know you and I might get asked a lot about customer service chat bots and training them
on internal company information that your human customer service reps would use to answer
questions and this is like an extension of that I think wherein you can ask opinions
and more thought leadership driven aspects.
So I think that will be interesting.
Will we see a revolt of where people are like, no, no, I really want to see what the real
Simon Sinek's got to say, not the shallow AI interpretation of Simon Sinek.
That remains to be seen.
There's probably space for a Martin Broadhurst in my pocket and a real Martin Broadhurst
on the podcast probably because they have different use cases, right?
But I think it's kind of cool and again, hucking back to the beginning of the podcast, there
are people who are, oh, I can do some stuff with chat GPT in there at that stage of development
and sort of interest in all of this as a topic, but there'll be people now who are already
starting to imagine those that are sort of surfing this wave right on the edge that how
can I use this for my company?
How can we use that as a mechanism of standing out from competitors?
How can we use it to create bars?
How can we use it to provide a better service to our customers?
And I think those people will be, what they do with this is going to be what drives the
future of this, is people figuring out useful applications and hopefully, and we talked
about this on a previous episode, not getting caught out when somehow nefarious actors are
able to trick prompt them into saying something or doing something that they shouldn't.
Well, that was exactly what was going through my head just then is from a brand reputation
perspective, there's quite a lot on the line for these individuals, right?
It's one thing for a major corporation to have an automated chat bot that says something
it shouldn't, but a hey Jen talking avatar, self-made, self-published, deep fake effectively,
chatting with somebody offering a bit of support, guidance, insight, but one that just goes
a bit off the rails and tells someone to kill themselves or what have you.
That's a bad look.
That's a bad look for your major high profile influencer.
So that's something that you guarantee is going to happen at some point, right?
I agree.
I think that will definitely happen.
Some chat bot somewhere with the likeness either in the voice of or even the video is
going to, that is going to happen.
They're going to find ways to trick it to say things that it shouldn't and it's going
to be a major news story.
How that influences brands and personalities and famous people as to whether they want
to do this or not is going to be interesting.
Honestly, the reason I haven't created, because as you know, I've got access to the hey Jen
beta and the thing that's stopped me doing it so far is what happens when I have trained
a model on me.
There's now a synthetic version of me, which is fine when I'm in charge of it.
I'm not particularly well known or important, but someone else could get hold of access
to that and make me say and do things that I wouldn't normally do.
I don't know who the producers of that tool are and what other plans they may have for
my likeness.
Probably none for the reasons already said, but it's enough to stop me doing it and my
risk profile is extremely low.
So Snoop Dogg, Tim Ferriss, do they have more to worry about?
Probably.
I think it'd be interesting to see how it plays out.
One more story this week.
You probably get a feel-lessness.
It's been a little bit of a lighter week actually on the AI stories, but we've got one more,
which is actually a continuation of ChatGPT Vision.
We talked about this a couple of weeks ago, some of the cool early use cases.
We mentioned one at the beginning of the podcast, feeding it a picture of a table and then actually
having it engineered into a real table in Excel that you can actually edit.
But what we've spotted this week is a few other really interesting use cases floating
around the web of how as a marketer, you can use ChatGPT's new vision capabilities, not
just some of the cool more general use cases that were popping up.
So I think one of the ones I really like, Martin, was marketers taking screenshots of
high-performing landing pages or websites that they really admire and then asking ChatGPT
Vision to break the website down and use it as an exploration as to why it might be working
well and what features to emulate or asking it for critical feedback on your own website.
The difference here being between just pasting copy in, you'll get feedback on your copy.
But if you take a screen grab of your site, because ChatGPT's vision's capabilities
are so incredible, it can actually see your website and talk about spacing, colors, design
and all of those other things.
Structural elements, which I thought was awesome.
You can also apply that to extending it to other materials like PowerPoint slide decks
and all these other things.
Just take a screen grab and then you can get critique.
Of course, it can read the copy in those as well.
So you're getting design input, you're getting your copy reviewed all in one go.
Yeah, I actually did the landing page one, took a mobile screenshot of a landing page
that I created, put it into GPT for vision and it was the spacing that just caught me
off guard actually because I was expecting it to critique the copy and the flow and the
general structure.
But actually it highlighted a section on it where it said it was all a little bit cramped
and the padding and the margin was off.
I hadn't really considered that.
Nice, nice.
I think it's going to be really useful because just having nearly worked 15 years in agencies,
some people seem to develop a really good design eye for balance, spacing.
Some people have that attention to detail where they can see that the margin's off,
but your ability to just feed that through a tool.
I mean, at the moment, this is all very piecemeal, right?
One by one screen grab.
But if OpenAI open this up as an API, which one assumes they probably will given they
have pretty much all the rest of their tools, then at some point someone's going to build
a tool that automatically screen grabs every page of your website, feeds every page through
a tool and then gives you critical feedback on how to improve it.
And given the example you gave us from Draspa earlier with its one-click content upload
deployments, how long before you can just one-click fix a load of padding issues on
your website because this vision tool was able to detect them all.
So that's pretty awesome.
The other thing I saw this week, which I thought was nice is, and I guess it's kind of obvious
and we've talked about it a little bit off air, but for those people that love to do
like right hand written notes to themselves or brainstorm on a whiteboard.
And I've taken so many pictures over the years at workshops of like sticky notes on a wall
and all this other stuff.
But the ability of ChatGPT Vision to actually just suck all the text out of those and turn
them into like written notes that you can now use digitally to share as a follow-up
after the meeting or for you to index and search later makes it a pretty powerful tool
for that.
And I've played with that yet definitely worth a play.
That is a real benefit.
If you're in a meeting, so I was at a client meeting, I tend not to make handwritten notes
because I just don't really, to be honest, I never go back and check them.
I'm not as diligent in going back and reading them as I should be.
But I've took the photo, extracted the text and yeah, just took it into my CRM and all
was good.
Yeah, I think it's really, really cool use case.
And I think there's going to be loads more that come out of this.
Another screen grab one was people who were not so O-FAY with like a software tool, screen
grabbing it and then asking for an explanation on how to use it or how to interpret information
in it.
So the example I saw was Google Analytics dashboard.
But of course, I think you could apply this to any analytical software that you're perhaps
not O-FAY with.
And in the example, I saw someone took a picture of their Google Analytics dashboard and were
asking questions about what the different stats mean and what the trends might mean
for their marketing and stuff like that.
So I thought that was pretty cool one as well.
So yeah, I think we always talk about, don't we Martin on the podcast, that using ChatGPT
is as much about user imagination as it is the power of the tool because these things
don't come with your traditional software manual.
They don't have like preset eight things they can do and then you learn them and then you
know how to use it.
How you interact and prompt these tools and the creativity you bring to that process is
going to open up new applications for you.
And now that ChatGPT can see, not just hear and read, really opens up a lot of interesting
things that we probably haven't even begun to think of what they might be.
Yeah, so I had an example of that in one of the workshops this week where somebody, they
worked in property and property investment and they were talking about trying to get
investor packs put together and they often had various bits of artwork or they had some
photography from developments that they were working on and they were just describing how
much time it would take them to write a bit of copy around certain elements of these investment
packs.
And he said, could it do this for us?
So we found a kind of fairly generic example of the kind of picture that he would typically
use in his investment pack, put that in, wrote a few prompts, did it live in the session
and there you go.
It created the content for him and he couldn't really believe his eyes.
So yeah, it's as much having the imagination and the creativity and identifying the problem
and saying, could it do this thing?
And then trying it.
That's where you find the magic.
Yeah, I agree.
So there you have it folks.
If you haven't had a play with ChatGPT Vision yet, the easiest way is actually to start
screen grabbing things on your computer, save that as an image and start plugging it in.
Think of interesting questions to ask.
Even if it's, what color is this?
You want to find a hex code, you could just take a screen grab of the button that you're
trying to reproduce and ask for the hex code.
You can grab images and say ChatGPT if I wanted to create an image like this, what would be
like a good prompt that I could use and so it will reverse engineer prompts and give
you prompt ideas.
So yeah, it really is pretty awesome, pretty awesome tool.
Well, I think that's all we've got time for this week, Martin.
I think so.
Well thanks always to you lovely listeners.
We really appreciate you spending your time with us wherever you may be, dog walking in
the gym, sat in your office, hanging out with your pals and saying, God, these are cool
stories and sharing them with all your friends, which I'm sure everybody does.
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Martin, thanks so much for your time.
I look forward to hanging out with you again next week.
I'll speak to you next week, Paul.
Thank you for listening to Artificially Intelligent Marketing.
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