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 Artificially Intelligent Marketing, Episode 12.
Very exciting stuff, we're glad to have you here today.
We're going to do our usuals, it's going to be a bunch of schnort, schnort?
Bunch of schnort.
We're going to have a bunch of schnort and then see where it goes from there.
I'm looking forward to this one.
How about it, don't.
Now we've got a difficult decision, do we leave this in or do we?
I think the listeners appreciate this.
Right, I'm just going to pretend as if we cut it, even though I know you're not going
to let me cut it.
Welcome everyone, this week we're going to have what we always have, short snippets.
They're going to be great.
We're going to have a bunch of main stories as well, which is going to include some info
about Anthropic raising a bunch of cash to build some next gen AI assistance.
We're going to look at Microsoft's copilot coming to Windows 11, pretty exciting stuff.
We're going to look at Google working with Europe on a stopgap AI pact.
I swear Martin, you've written these notes to make me trip up while I try and read them.
But I'm going to crack on regardless.
We're going to look at the Photoshop generative AI beta launch this week, which is easy for
folks to access if they have a subscription to Photoshop and Adobe Creative Cloud.
And we're going to look at how Google has added generative AI to ads and product photos.
And then finally, we're going to look at tool of the week, which is going to be Zapier.
Right.
Just a few bits there to get through.
Yes, but it will all be worth it because there's loads of deep insights in there, Martin.
So I think it's going to be a blooming good time.
Let's start with those short snippets first, shall we?
The first one is that news actually today, we're recording this on Friday, 26th of May,
is that OpenAI could leave the EU if the new AI rules, which we've been talking about before
on the podcast, are passed.
Sam Altman, who is CEO of OpenAI said, either we'll be able to solve for these requirements
or not.
If we can comply, we will.
And if we can't, well, we'll cease operating.
We will try, but there are technical limits to what's possible.
That could be quite interesting for users of tools that require OpenAI as the element
that underpins the tools, or if indeed you're using ChatGPT itself and you're based in the
EU.
This could open up opportunities though, if other, if certainly OpenAI and maybe other
US based firms could open up opportunities for AI firms based in Europe and that are
US, sorry, EU compliant to gain some market traction by dominating in the EU first.
So I doubt we'd get that far, if I'm honest, but it'd be interesting to see how this opens
up.
Next short snippet is A16Z released its AI cannon this week.
You probably saw some posts, there's plenty of posts on social about this.
It is a mega AI resource with loads of information about how AI works, the different types of
models, there's market analysis in there.
It is a real one stop location for all things AI.
So if until this point, haven't really been following much of what's going on, but you're
like crumbs, I really need to do a deep dive.
Go to that webpage, it's got everything you need and we'll pop it in the show notes, won't
we Martin?
Yeah, it's got some fantastic sections in it from a nice gentle introduction through
to the kind of foundational learning, even kind of going to the real fundamentals.
I'd recommend people check out the Word to VEC explainer, which is the absolute basic
building block of large language models.
I think if you can get your head around that, then you're a long way to understanding how
these things work.
So yeah, great resource.
Agreed.
Spend Friday night reading all of that.
Spend a night impress your friends at the pub.
I think that will be both.
If there's one thing I've learned in recent weeks, people love hearing someone more on
about AI in a pub.
But no, but listen, vector databases, listen.
Vector embeddings.
Yes.
The way that cat and dog are close to each other in a way that cat and house are not.
I'm pretty sure this was part of the original version of how to win friends and influence
people and of course it wasn't, but maybe we should update it.
We could probably get AI to update it, but that's a different topic we're discussing
in the pub.
Apologies listeners for the digression.
Back into the short snippets.
Nvidia's stock price went boom shakalaka after greater than expected earnings.
Presumably everyone and their nan are buying GPUs to run generative AI models on and that's
what's boosted that.
We've also previously reported on how many large players are investing in developing
their own chips.
So whether or not this progresses and Nvidia's stock price continues to go shooting up because
their revenues go shooting up or whether most of these companies end up developing their
own chips, who knows?
But for now, if you own stock in Nvidia, you're doing rather nicely.
We don't, we're not experts in the financial markets and we don't offer any investment
advice.
A quick disclaimer there.
Next bit of news is free users of ChatGPT can now access the ability to browse the web
or use the web browser plugin, I should say.
So even if you're a free user, now it will actually access up to date content through
that plugin.
It's powered by and branded as Bing.
So I guess that's part of the trade off there in terms of being able to get to access it.
And then you were looking at a story about water.
What's this water story, Martin, tell us.
Yeah, so it turns out there's quite a bit of energy and water consumption involved in
using these large language models.
There was a piece of research published this week, we'll link you to the paper.
It says ChatGPT may have used 255 million liters of water in a single month.
Yeah, so it has not only massive energy consumption, but the water used to call the data centers
is also enormous.
So in April, ChatGPT reportedly had 1.7 billion visitors who each made an average of six queries.
So that's a total of 10 billion, just over 10 billion queries in April.
And it's thought that it consumes 0.025 liters of water per query, which gives you that 255
million liters of water.
And for comparison, the average American family uses 40,000 liters in a month.
So it's quite a lot.
Interestingly I was at a workshop while I was delivering a workshop on using ChatGPT
this week and mentioned this figure.
And in the room there was, I would call it at best, a kind of disinterested shrug.
Ambivalence.
Absolute ambivalence, yeah, totally.
People just felt that...
And people actually started getting into the technical discussion about how watering data
centers is probably on a closed loop system.
So what's the problem?
And I backed out at that point.
I had no idea.
That's above my pay grade or knowledge, I have to say.
One thing I do remember a while back is having a discussion with a potential client, a buyer
straight back in the day who had data servers and stuff all based in Northern Iceland, where
it's proper cold most of the time.
It seemed like quite a clever way to keep your massive server farms cold and pulling
in cold air from outside.
Which is pretty cool.
Anyway, another digression.
It's already been an episode of digressions.
People just hitting stop, pause, unsubscribe.
Don't do it.
I promise there's fantastic insights, even greater insights than what you've had already.
Actually coming after this.
And actually we're going to get there now because we're going to launch into our first
big story of the week, which is Anthropic raising $450 million to build next gen AI
assistance.
Martin, you spied this.
Tell us what you found and why it's interesting for marketers.
We've spoken about Claude in recent weeks.
This is a continuation of our interest in this story.
So Anthropic are doing a really good job of raising their profile and fundraising.
So 450 million raised in series C funding.
It's thought that it values Anthropic at over 4.1 billion and there are some interesting
venture groups backing them.
So Google, Salesforce and Zoom are all in on this round.
So Anthropic is aiming to build next gen AI systems focused principally on safety, reliability
and honesty, which is through their Claude Bay system, which is a constitutional AI designed
to be helpful, not harmful and honest.
So another interesting point that came from this is that Zoom have also announced a partnership
with Anthropic to build customer facing AI products principally focused on reliability,
productivity and safety following a similar tie up with Google.
All of this gives Anthropic a good position in the market in terms of being able to compete
against the likes of OpenAI.
They're clearly getting access to some big players.
The models are going to be finding some interesting use cases amongst tech stacks that we all
know and use every day.
The real differentiator for Anthropic at the moment is, as we have mentioned previously,
that 100,000 token context window.
So your prompts can be properly long, like novel length long.
Apparently according to the story, Anthropic plans to build an even larger next gen model,
which they say requires 10 to the 25 flops of power.
So that will require one billion pound funding in the next 18 months.
So that's not a cheap endeavor.
Apparently hoping to raise five billion over the next two years to expand its products.
So really they're properly going up against it.
Anthropocare are getting deep pockets in order to be able to compete with OpenAI, who themselves
had 10 billion pound of investment from Microsoft.
Yeah, it's an interesting one because I think it shows that as marketers, we're going to
probably end up with tools as we've talked about on the podcast before, that are driven
by different large language models, which is probably good given that it hasn't really
happened for a while, but in the early days of chat GPT, when it went down a few times
and people were like, oh, I got a thing for myself, which was obviously extremely challenging
for the couple of hours that it was down for people who were heavy users.
But we've also touched on how different models appear to have different strengths.
So actually seeing that we're going to have this slightly more diverse ecosystem than
perhaps we might have imagined when it was looking in the early days, like it was already
an OpenAI takes all game, probably a good thing for us in terms of diversity of tools
that can do different stuff for different applications, strengths and weaknesses.
Most definitely.
And having a system that is fundamentally designed to be different from something like
GPT-4, which is the RLHF model, the reinforcement learning through human feedback model, having
that constitutional framework gives it a real differentiator.
And it's nice to see these on the market because a lot of the models are RLHF.
So yeah, it's a good look to Anthropic.
I'm really enjoying using Claude at the moment.
It's probably my go-to model, even though chat GPT at the moment is expanding with lots
of the plugins.
The real-time connected nature to the web is interesting, of course, being able to browse
the web with GPT-4 is cool, but it's incredibly slow.
I actually find that I can go online, find an article, copy and paste it, stick it into
Claude and say, give me the key facts quicker.
And I don't have to worry about character length because, as I've mentioned already,
you can stick a novel in there.
Yeah.
My jealous green eyes are gleaming now.
And in fact, with the variety of easy image manipulation tools available now, I could
probably take a screen grab and mark it up pretty quickly and easily at this point, but
get onto Photoshop later.
I did see a Twitter, I think it was on Twitter, it might have been LinkedIn, conversation
about how the real power of generative AI might turn out to be content summarization,
not content generation, which I think is really interesting.
We've talked previously about this concept that someone might write a long memo or email
that then gets summarized down by an AI for someone to quickly absorb.
They maybe dictate or write a fairly long response that then gets summarized down.
And actually the real gatekeepers of what information makes it through and what doesn't
might actually be the AI summarizing tools.
But I am jealous of you having access to Claude for that summarization reason because it does
look pretty powerful for that.
On that point about summarization, if anybody hasn't read Wired's article about how they
plan to use generative AI, I highly recommend they check it out.
They published it a few months ago.
I think we might have even mentioned it on a previous episode.
But it mentions in there about they will not use generative AI or large language models
to do any editing.
And they say because it's always a judgment call and what stays and what goes, what is
important and what isn't is going to be different for different people.
So a robot is just a different agent in that aspect.
It's always going to be left to a human to make those calls.
Interesting.
Yeah, I agree.
And I think we may have even talked previously about the dangers of letting a single AI agent
make the call on what gets into the summary and what doesn't.
I think we talked previously about you and I read a book, Martin, and we're going to
take different things away from it because of our context, our experience, our background,
our particular interests, why we read the book, what particular sections we focused
on the most.
And yes, but certainly it's good to have all those different tools.
And I think it's going to be a watch this space as the Anthropic continues to expand
and evolve its offering in this market.
Right, next, let's talk about Microsoft's announcing Windows Copilot, an AI personal
assistant for Windows 11.
So another previous episode callback here, but Martin, we've talked previously about
the edge sidebar and making the transition from Chrome to Edge.
And honestly, I wouldn't look back at this point.
I'm really glad I did it.
I'm absolutely in and out of that sidebar, having Bing available to push content into
to quickly summarize or to more widely search is actually proving really useful.
But of course, Windows and Microsoft, they want to take that a bit further.
So with Windows Copilot, Windows 11 will effectively have a centralized AI assistant that you can
tap into at any point.
So it's the equivalent of the Bing sidebar in Edge, but having that basically in every
app that you're using across Windows and actually basically having it as you're using Windows,
whichever platforms you're working in.
So that in itself is pretty interesting and powerful because we've talked about the where
are the moats for different companies and which products should a market to buy and
invest their time and money and training resource and energy in.
And ultimately, because so many users already use Google Apps or Microsoft Office, there's
an argument to say, wait until this power comes to those because your team is already
using them, etc, etc, etc.
This is an area where Microsoft even has one up on Google, right?
Because so many people use Windows as their operating environment.
And yes, I appreciate Chromebooks and stuff running on Android and also mobile devices.
But for most people in the work environment, still using laptops of some variety, appreciate
Mac users out there as well.
But yes, having that power baked into not just Microsoft Office, but Windows itself
is pretty interesting.
There's also the sort of co-announcement that goes along with this is extending chat plugins
to work in Windows.
So in essence, you can start to imagine this plugin app ecosystem that we talked about
previously for chat GPT opening up so that people can augment your chat experience within
Windows with a whole host of plugins.
So potentially it could become very powerful tool indeed.
And maybe even another play by Microsoft to see if they can control which tool do you
turn to first, right?
Like if you just got your co-pilot sidebar always open in Windows, well then every search
that you do of your own files, of the web, of your own data, maybe generative text creation,
image creation might all start in there.
And of course, if they control that, then they control the ecosystem one, assume.
So pretty interesting stuff here and be interested in see what that looks like when it starts
to roll out.
I demoed this to the group that I was talking about yesterday, or I showed them the video
trailer from the announcement.
And this comes off the back of having done a previous session with the same group where
we'd looked at the co-pilot demo as well.
And one of the questions from people in the room was, which one do we go to for what?
And do they talk to each other?
Is Windows co-pilot going to be the same as the Office co-pilot?
Because the demo talks about being able to interrogate your files, you can drag and drop
a PDF into it and then take content from that and put it into a different document format.
So I think making sure that they get this right and it isn't a jarring, confusing experience
where co-pilot for Windows can do one thing and Office can do another thing.
I think they need to get almost like a Microsoft co-pilot the end.
This is one assistant that works across the suite of tools.
Because at the moment, the demo makes it look like, well, we've got GitHub co-pilot and
we've got Windows co-pilot and we've got Office 365 co-pilot and I just hope they make it
a uniform experience.
You've said previously that because a lot of these large language models have similar
strengths and weaknesses, that this could end up being a battle of UX, right?
And having a high quality user experience and solving for the problem you just mentioned
is a big part of that.
I very much hope it's a sidebar that takes up a little bit of screen real estate at all
times honestly, whereby it knows what window I have open.
It knows I'm in...
Context aware.
Yeah, it's context aware.
It knows that I'm in Word and so there's certain things it's going to do in Word.
And actually if I'm not in Word and I'm like, oh, I need you to summarize this in a document,
then it just does it, pushes it straight into a Word doc and then it's context aware enough
to say, hey, what else do you want to do with this?
Now we're in Word together because I know as well as you know, Paul.
Crumbs, could you imagine the conversations I'm going to have with AI, knowing some of
my communication limitations.
So yeah, I'm in agreement with you.
I think that could be the thing that makes it a winner or a loser because if it's hard
to use or confusing, people are going to get annoyed, aren't they?
They will.
So a general observation about these AI assistants at the kind of system level or both the OS
and I guess at the kind of suite level, so Office 365 Copilot as well.
They talked about something in the Office 365 Copilot demo where they said most users
of PowerPoint are using 10% of the functionality that it actually has.
And using Copilot will enable people to unlock all of this additional functionality that
is baked into the software.
And I think that's probably the case with operating systems as well.
You get into a habit, you know how to do certain things.
If you're not somebody who is confident in a PC, so you sit down, you turn it on, you
do your work and you would never dare venture into the control panel even, this is going
to make your interactions with your computer much easier, one would hope.
So I think that's going to be positive because we sit at these machines all the time and
barely scratch the surface.
We get into routines of doing what we know and if we can start to get the full potential
of the tools that we have at our disposal already out of it through these assistants
then yay.
I completely agree.
When we talked about the code interpreter plugin for Chatch GPT and its ability to analyze
data, uncover trends, report on those trends, write paper abstracts and things like that,
we talked about how it's critical that you have an informed human there to know what
is an interesting trend or to ask great questions of the data.
But what I would really love is what you described and then up to the next level again, which
is when I'm in Excel that the Co-Pilot tool has enough insights into what I'm doing and
how I work to actually be able to say, hey do you know that thing you're doing, I could
build you a macro to do that, you don't have to do it by brute force and just manually
like what you are and then I go, oh that sounds amazing and we go yeah no worries I'll create
the macro for you and all you've got to do is press that red button at the top, well
maybe not it'll be like oh I've started the macro, tell me what next CSV you want to feed
into it or whatever because that would be the cool part because the extra part of that
is you don't know what you don't know sometimes do in terms of you don't use that 90% sometimes
because it's hard to technically do but sometimes because you don't even know it can do it.
Yeah absolutely, particularly with the Microsoft suite.
It's actually why I use Google Workspace a lot of the time because I always think Google
Workspace all of their suite of tools they're not as capable as the Office suite but they're
more than capable enough for what I typically need.
Agreed right we better move on to the next story before we run out of time Martin so
let's go to Google to work with you upon the Stopgap AI pact, thanks again for that.
Tell us Martin what you saw here this week.
So a bit of a follow-up to the story that we've been following over a number of weeks
which is the AI act coming in from the EU and following on from the Sam Altman comments
in the short snippets easy for me to say.
So this story basically what's happened is the EU Commission or the European Commission
and Google have come together and there will be some sort of Stopgap AI pact as you mentioned
in the headline but the story will involve all major companies working on AI both in
Europe and outside of Europe that is the goal at least because the AI act is due to come
in in two years time from sign off or implementation.
There's going to be this two year period where AI companies are not going to have to do anything
and regulators are a bit like oh actually the pace of change in this space is so rapid
that two years with nothing is a bit scary.
So the goal of this AI pact is to mitigate the gravest risks associated with this rapidly
evolving technology until proper legislation is put in place.
EU Commissioner Thierry Breton said Sundar Pichai and I have agreed that we cannot afford
to wait until AI regulation actually becomes applicable and to work together with all AI
partners to develop an AI pact on a voluntary basis ahead of the legal deadline.
I've already I already have a common vision of what could be put in place in anticipation
and which could allow us to give some elements of protection which suggests that this pact
will aim to establish some basic rules or guidelines around AI.
However this will be voluntary so this will not be enforceable and this is going to be
pretty much a good faith deal between the likes of Google, Microsoft, OpenAI and the
EU.
But it should help establish or I think the goal of this is maybe that it helps to establish
a framework for responsible AI development in the future.
In the coverage of this story not much detail is given.
When I say not much no detail is given.
Zero!
Absolutely no detail at all and this is covered by Reuters and a bunch of other reputable
sources.
So we don't know what this pact involves but Breton has mentioned the possibility of
labelling AI systems which would probably be some sort of categorisation based on levels
of risk, transparency and other attributes that we already know are important and are
kind of covered in the AI act.
The AI act is going to be a very risk-based human centric piece of legislation and regulation
and so it would make sense that they're having those conversations in anticipation of the
legislation coming in down the line.
I also read something this week, I can't remember the source for it but it suggested that people
wouldn't be surprised if the AI act gets watered down slightly in terms of requirements for
transparency because explainability at the moment is still such a technically challenging
problem.
I think this comes to the point that Sam Altman said in terms of leaving the EU that if the
requirements were such that they just couldn't meet them due to technical reasons then they
would leave.
As you said when you were reporting on that Paul, you don't think it would come to that.
I am not entirely sure it would either.
I think the regulators will work.
Fragmatically, there'll be more focus on, or in my opinion, the EU will be more focused
on the rights of individuals rather than concerns related to copyright or something like that.
Yeah, it'd be interesting to see that play out and neither of us are lawyers or legal
professionals.
Lots of caveats in today's episode.
But yeah, I think you're right.
When you frame it like that and you look at how Sam Altman phrased his comments, it sounds
like they put more than a reasonable amount of effort to try and meet whatever the stipulations
were.
One would have to assume that any other producer of large language models might also struggle
to meet those stipulations on transparency and explainability.
I think maybe the critical one for OpenAI is they didn't really tell us much about GPT
course training dataset and needing to be able to provide full access and insight into
what that dataset was might be one of the kickers for them at least.
Yeah, and you would think that this could be overcome by having some sort of auditing
mechanism which allows for commercial sensitivities where they are scrutinizable by those that
need to scrutinize the public bodies but not necessarily made publicly available for all
and sundry to see and interrogate.
That doesn't seem like it's beyond the capabilities of man to figure this out.
No, and not our responsibility either, thankfully, Martin.
But yeah, I think it'd be interesting for marketers to keep an eye on how all of this
plays out because again, as we are all starting to think about how we can leverage AI and
different aspects of our business and our marketing processes to increase creativity,
improve efficiency, then understanding what types of frameworks are going to limit what
types of tools before you make investments in building this into your business.
It's just good to know where it's going to go.
Yeah, very much so, which I think, sorry, I cut you off there, but that leads us neatly
into the next story and a model which is very rooted in transparency and responsible usage
and respect for its community.
I think if you read the rules around this next story, you'll see that the Photoshop
are doing a lot to, sorry, I've completely balls that up, not Photoshop, Adobe have done
a lot to respect creators.
So with that in mind, Paul, what were you going to say?
Because I cut you off.
That's a bit of a ramble.
Welcome listeners to my mind.
We promise as much as we wish we hadn't done this to ourselves, we're not going to cut
any of the mistakes because as we've talked about, the human authenticity of this content
is absolutely critical so that you know that we're not bots.
Although would bots deliberately make those mistakes and then leave them in?
Oh dear listener, we'll leave you to chew on that.
But yeah, let's make a segue and then take this into our next story, which is Photoshop's
generative AI beta, which has been launched.
We do have an Adobe account here at Biostratus where I was able to have a play with it.
It was surprisingly easy to access, although you had to update Photoshop and then you had
to opt into the beta and then you had to update the beta part of Photoshop and then you had
to update Photoshop again.
It wasn't an easy process to get hold of it, but we were able to and we've had a play with
it.
Now, what is this?
So Photoshop has introduced this new feature called generative fill.
It basically allows users to access the Firefly tool that they've had in beta as like a separate
standalone and some of the power of that directly in Photoshop when they're working in their
normal image workflow.
Using generative fill, people can use natural language to guide Photoshop in creating aspects
of an image.
So what can they create?
They can add elements, they can replace parts of an image, they can expand past the edges
of an image or, you know, basically at the top or just make an image bigger and it sort
of auto fills in a very contextually aware way.
There's loads of good stuff that you can do.
I've been playing with it this week.
I've had a couple of my very good friends having a play with it as well.
Emile Lampreck, who we've had on the podcast before and also Andrew Muir, props to you
guys for having a proper WhatsApp bash of us just sharing the different images and what
worked well and what didn't.
And at first, I've got to admit, I wasn't super impressed because I tried some things
and it just did a very poor job of it.
So there's some skill to figuring out how to use the prompt, like unlike, say, Mid Journey
or Chat GPT, if you're overly instructional, in my experience at least, it pushes the instruction
into the output.
So I made a picture of a horse and then I said, add a tattoo of a lion, but then it
put a person adding the tattoo onto the lion and I just wanted the tattoo.
So when I said add, it included a person, a tattoo artist, not the tattoo.
Anyway, did you manage to fix that and maybe just put lion tattoo?
And that's exactly what I did.
And that's exactly what then worked pretty poorly, honestly, but that was one of my early
attempts.
Some of the things that we found...
It's difficult to tattoo hair.
Do you think this was the...
Hey, I just thought this is an absurd request.
I refuse.
It's a stupid idea.
Yeah.
I mean, it was a stupid idea and it didn't work very well.
With more playing between Emil, Andrew and myself, we got it to do some pretty cool stuff.
So Andrew spent some time extracting Emil and I from other images with the Context-Aware
Select tool, which is awesome.
It's kind of like, you know, we looked at that segmentation model from Meta that was
really powerful for just...
You click on a thing and it knows in a smart way where the boundaries are.
The sort of magnetic lasso is going to die a death because you can just click on a person
and it very intelligently selects them and then you can remove the background really
quickly and then chuck other backgrounds in.
So Andrew had poor Emil was being attacked by the Loch Ness Monster, a bear.
At one point we were trying to see if we could get Ridley Scott's alien in there.
Basically both Emil and I and Andrew's images were under siege by all these different characters.
And in many cases, we're actually able to get some really quite good effects.
Obviously didn't necessarily look real.
But the bear, for example, was completely in the context of the background, even though
the area where the bear was inserted wasn't in the original image.
Photoshop had to create the background and then put the bear in it.
And it got it sort of on the ground, if you know what I mean, like stood in the right
place.
It was pretty cool.
In fact, the Context-Aware Expansion, so taking like a four by three image and expanding it
to 16.9, like you would do, say for a blog post, Eder, or maybe when you're fiddling
with images for different formats on social or different ad formats.
That was also surprisingly good.
Emil ran an incredibly complex requirement where the centralized image to expand out
was going to be really difficult and it did a really good job.
So I think if you're a marketer, you should know about this because it's going to bring
the power to you that usually would have required some significant design expertise.
I think if you're a designer, you could probably use this to speed up your workflow significantly
and it's absolutely worth having a play with.
This came hot on the heels of a research paper about a tool called Dragon, Dragon, Dragon,
I think it's Dragon, that came out of the Max Planck Institute.
It's not publicly available yet.
It was a paper.
You've probably seen it on social media if you've clicked on anything AI related in the
last few months because I've seen it in many different places.
The demo video is pretty impressive.
It shows an image editor a bit like Photoshop, but where you can drag around and it will
contextually aware edit the image.
So an example was you could close and open the eyes of a cat and it looked at every stage
basically real.
You could open a lion's mouth and turn their head and it was contextually aware enough
to again make it look like that's how the original image had been captured.
There was a resizing of a car where you could change the size of the wheels or the trunk
and actually the image would adjust, like the wheel arches would move to accommodate
the new larger wheels.
Like pretty cool.
You could adjust a person's clothing like the lengths of their sleeves or a skirt or
trousers and things like that and it would again contextually aware and it was able to
do that with really surprising fidelity and make it look real.
So loads of really interesting image adjustment news this week, which of course is absolutely
critical for marketers in a huge amount of areas in which they work.
Yeah, and it's amazing to see the development in this area.
I was showing off the Canva Magic Edit, Magic Eraser feature, which is basically in-painting
much like the tools that you've been describing with Photoshop.
Although the Photoshop ones obviously have a wider suite attached to them, but yeah,
it's cool.
These are readily available to anybody to use and you really don't need to be a particularly
skilled designer, artist, illustrator to be able to get something that looks pretty decent.
The democratization of design, eh?
Absolutely.
And I still think the demo videos always show you the very best possible examples.
I had an image that I used in one of our blogs last week of a little bit of satire.
It was robots sitting in the Houses of Parliament writing up the AI Act, but doing it with paper
and pen, which I just felt was apt in terms of how government institutions might use AI
to increase efficiency in some areas and then still make everything work with pen and paper,
but I digress.
When I tried to swap that pen for a feather quill, it just looked like I'd use an image
stamp like it was not contextually aware at all.
I tried to put a hat on one of the robots.
Awful, didn't work at all.
But if you watch the demo video, it's contextually aware enough, at least in certain cases, to
figure out what the light source is and show light bouncing and reflections in rivers and
stuff like that with a decent level of accuracy that again, I think you can get, but you've
really got to get the prompt right, make the selection be just in the right place, try
different prompts, and I think some images are just going to work better than others.
So yeah, great power.
I think there's cool stuff that we can do, still frustrating enough at the moment to
maybe drive you a bit mad if you've got a particular vision in your head of how it should
look.
I still think it's hard to get that.
That reminds me that I was playing with Firefly this week with the text to effect or the text
effect tool.
I know that you'd said that was somewhat frustrating when we had that conversation.
It can't quite do certain textures.
This week I tried to get a text effect with Donna Kebab and didn't work very well.
If anything, the reason my critique of it was that it was putting in a Sheik Kebab,
which that's so wrong.
It's a million miles away, idiot AI.
I mean, there's a support ticket there.
Get on there.
Right.
Let's move on to our last main story of the week, which is on a similar vein actually,
Google adds generative AI to ads and image assets.
Myan, do you want to tell us about this one briefly?
Yeah.
So a very practical use case, kind of obvious that Google would launch this.
It's going to help people create ads in the AdWords platform.
So they're bringing generative AI to the AdWords platform to simply add, basically you simply
add your preferred landing page from your website and then using the text and the context
from the landing page, Google will then create your ads.
So it will generate relevant keywords, headlines, descriptions, images, and basically pull in
any other assets and using their huge amounts of knowledge about what is effective in terms
of headlines and copywriting and what have you, they suggest that these will be rather
effective combinations of ad creatives.
Maybe you can review and edit these if you wanted to say something different, if you're
not happy with it.
But yeah, you can now get AI to put together your campaign.
Now of course, you've still got to have a landing page that you create.
You've got to have a page that gives good context and has a compelling offer in order
to get the conversions.
But then once you transfer that over to AdWords, you'll be good to go.
Yeah.
Interesting.
I think we've talked a little bit about programmatic and advertising recently.
We've talked a bit about AI enabled ad management and sort of auto creation of ad text and stuff
like that.
Keyword selection, automatic bidding and all of that stuff.
So this obviously fits in line with that conversation and will certainly speed up workflows.
When I saw this, I'm a member of a number of direct response marketing Facebook groups
which is kind of very different to the B2B world that I usually play in.
It's very much consumer oriented, a lot of it's informational products.
But I find it fascinating to see some of the conversations because it's a lot of it's
proper old school, emotive, emotion based, persuasive copywriting.
The type of which has fallen out of a lot of marketing over the years, certainly in
B2B or technical industries like the life sciences where despite our best efforts, everything
ends up very feature driven and first order benefits.
If you're lucky, never second order benefits or what it feels like to finally get a nature
paper or to be able to unlock a new research application that wasn't possible before.
When I read those, I really get a sense for the world class copywriters in the world who
understand human psychology, understand what motivates people, understand true persuasion,
write copy and structure landing pages and add copy and stuff in with real skill.
And I'm not saying that AI couldn't learn to do that if trained on enough examples,
but my fear with this would be it's a great way to get ads up quickly.
Is it a great way to get the best convert in ads?
Is it the best way to get the best results long term?
I don't know.
I think that the world class copywriters of the world would say no.
And certainly a bunch of stuff that I've been able to get out of generative tools like chat
GPT is not bad.
And if you tell it to think in a certain way and use a particular marketing framework like
Ada or what have you, it can do a decent job, but nothing compared to some of these really
gifted direct response marketing copywriters.
So yeah, I think that would be the one caveat I would put on it.
Yeah, a reasonable concern.
And well, I guess we'll have to wait and see.
What ultimately Google and Meta as well are also getting into the generative AI assistant
for ad creation.
I guess the good thing or the thing that they have versus a copywriter is a really good
copywriter can spend time crafting say one, two, three, maybe a handful of variants.
These tools, if you kind of hand them over, presumably we'll be able to multivariant test
different combinations, different phrases at scale automatically and find combinations
that quite frankly, the human just wouldn't have, you know, take them days, weeks, months
to do.
I'd agree.
I think if you've got a large enough budget and a large enough audience in terms of search
volume around those keywords, it's really funny because in the live science, there's
a lot of the keywords that we deal with a quite low search volume and we have to apply
very specific strategies and tactics around that, which this wouldn't work for, right?
Potentially.
I also think to your point, if you're able to produce those, there's nothing to stop
an expert reviewing them and then choosing which they think is going to be the best based
on their experience.
So again, experts human in the loop augmented to do this at scale and speed is probably
going to end up being the way forward at least to begin with.
So from that perspective, I think it makes a lot of sense.
And ultimately, if the main play here outside of, I think your very good point about being
able to split test and find out what works the best.
But if outside of that, the main players speed and efficiency, well, what does that do?
It means that there's ever more campaigns being running, loads more ads, loads more
spend all the things that Google wants.
But as an advertiser is not necessarily what I want because now there's more competition
and click costs go up.
I'm under even more pressure now to get the best cost per click, the best click through
rates, the best conversion rate.
And now we're back to having a really strong value proposition, effective messaging that's
laser targeted on the interests of your customers, which is usually best done through primary
research, which of course, AIs can't do yet.
And then probably that's where the benefit of world class copywriting to really make
sure that your landing pages and ads and things stand out.
So it could end up being like quite a weird cycle in some ways.
Yeah, no, a hundred percent.
Right.
Talking of weird cycles.
No, there is no weird cycle to link onto.
Talking of all good things, marketing, automation and cool generative AI and other tools.
We have been playing, having with Zapier, Martin.
So that's going to be our tool of the week this week and some of the cool stuff we've
been doing with it.
I know we've had both some experiences this week.
Why don't you tell us what you've been up to, Martin?
I finally connected my OpenAI API, a key with Zapier and started just playing around with
a few multi-step zaps.
So if people aren't playing with Zapier already to automate standard marketing tasks in their
day-to-day lives, then they absolutely should get on it.
But the first thing I noticed when I looked at what you can do with the OpenAI actions
and the triggers, I noticed that it has access to the Whisper API, which is the speech to
text transcription tool.
Now that's something that I've not been able to play with.
I'm not a coder.
I don't know how to actually build on the API itself.
This gave me a no-code solution for doing that.
So what I did was I made a zap that starts off by monitoring a Google Drive folder.
Every time a new file goes into there, it will upload that file to the Whisper API.
So I will save a voice note from my phone into my Google Drive folder.
It then puts that into Whisper and takes the transcript.
I've then created a ChatGPT prompt, which inserts the transcript into ChatGPT, grabs
the response from ChatGPT, which is a blog post based around the audio recording that
I transcribed.
That then spits that out into a Google Doc and saves it in a separate folder.
So by recording a very short voice note, uploading that to Google Drive, I get a blog post created.
I did this in a live demo with a group this week, a two-minute, five-question interview
with a cybersecurity specialist.
We went back and forth.
I asked them some very simple questions.
At the end of it, we had a very neat 500-word blog post created, which with very light touch
editing and a little bit of expansion on some of the points, we could have easily got to
750, 1,000 words long that covered some of the big issues in the industry.
All in all, I think we could have had a blog post created and written with two minutes
worth of recording, a minute's worth of uploading to Google Drive, and then maybe 20 minutes
of relatively light editing.
Yeah.
I love that use case, Martin.
I think what I love about Zapier is providing us with the tools to be able to come up with
cool applications for ourselves without having to code.
Because what you did there is absolute genius, and then Zapier makes that easy by connecting
all the different tools together.
This week, I was on a webinar called How Zapier's Go-to-Market Leaders Are Using AI.
There was just a real bunch of interesting use cases in that webinar.
I recommend Googling it and get me on to it.
Maybe we can even include the link in the show notes, I'm not sure.
I'm watching it because I think it will really open your mind to what's possible.
A huge amount of what they're doing is very Slack oriented.
They'll have it so that, for example, for their sales team, they will be able to ask
for information on a particular customer from a Slack bot that then through a mixture of
tools in the backend and different data sources it's connect to understands natural language
questions about the customer.
Surfaces information about their business, if it's B2B, also reports information back
from the CRM on different parts of, in this case, the software that they've used recently
and all those types of things, and actually just gives them that little customer summary
ready to go into the sales meeting.
But it's all done sort of automagically, but through natural language bot interface.
It's almost like having a sales assistant that you're like, right, I've got to speak
to Bob from Acme Co.
Tell me about Bob and then the chat bot just explains it all to you, which I just thought
was really interesting.
I saw a similar one that someone had done using HubSpot.
Oh really?
Yeah.
So because you can connect HubSpot with Zapier, this was on LinkedIn, someone shared this,
and it was a sales outreach email and they said, really neat because the amount of data
that you can extract from HubSpot in Zapier, all of the fields are basically available.
So every time a new lead was generated, you can have that go into the contact, extract
all of the relevant information.
And they pulled through in this prompt, they had, I think it was about 20 fields.
So they had the basics of first name, last name, email address, job title, et cetera.
But because HubSpot has HubSpot Insights, which is automatically populated data about the
company of someone who's been on your website and filled out a form, it was able to extract
all of that information as well.
So this was what the company is, what the kind of annual revenue is, the kind of estimated
annual revenue, number of employees, the city that it's based in, kind of one paragraph
description of the industry that it's in, its website domain, all of that kind of stuff
goes into the prompt.
And then it said, oh yeah, what page they submitted the form on.
So it was contextually aware about what the context of their form submission was.
So maybe it was a webinar or white paper or something.
And then got it to wrote a sales email, pushed that through into a follow-up email, pushed
that into Gmail and send it.
That's awesome.
It was, I watched it and I thought that is super impressive.
Like it's obvious when you see it, but it worked really neatly.
That makes sense.
I wonder if I'm not a big Zapier user yet.
I've had an account for many years.
Obviously this has prompted me to play with it quite a bit more after we were talking
about it through the WeMind, but can you link LinkedIn sales navigator?
Basically link everything to Zapier pretty much, kind of, because then you could pull
things on an individual into that, not just their company, right?
Yeah, good question.
I don't know why not.
Be worth having a quick Google.
It looks like there is an integration.
Oh no, LinkedIn sales navigator has not yet built an integration on Zapier.
Boo right.
We'd love that please.
That would be pretty awesome.
Another thing that was in the webinar that was pretty cool was they'd noticed that GPT
based tools are really good at summarizing sales calls, but also classifying them.
What were the main features?
Because obviously Zapier's team sells software.
What were the main features that the lead was interested in?
What were the objections that they came up with?
And then building a classification mechanism for GPT to draw upon to then auto classify
those.
Which again, if you're doing all of these things at the scale that some of these enterprise
companies would be, there's probably loads of insights you could pull from having that
quick summary of that type of information, which I thought was really interesting.
So I think if you're not using Zapier to explore some of this stuff yet, you really should
be.
That's certainly how I feel.
And Martin, your stories are even more inspiring.
I guess in some cases, you're going to need to have API access to some of these tools
to enable this, right?
The OpenAI example, the chat GPT example you gave, that wasn't chat GPT.
That was access to GPT-4 API, one assumes, to be able to do that.
Yeah.
So actually I don't have GPT-4 API access.
That just came from going into platform.openai.com, making sure I could generate an API key.
And I created a chat GPT API key, which is limited to chat GPT 3.5 or 3.5 turbo.
Right.
Okay.
But yeah, but you need API access.
Yeah, yeah.
The standard account won't do it.
You do need to create a developer account.
Cool.
The other thing that's worth looking at is Zapier have now got this new interfaces tool,
which is in beta, which promises to allow you to build forms, web pages, and basic apps.
No coding required, but where you can connect to GPT-based models like GPT 3.5.
So in essence, it has an element of chat bot builder about it, but this is the underlying
tool that they're using for a lot of the use cases we've been describing, because that's
how they end up basically then this lives in Slack, but its ability to draw on all your
other data sources through all your other Zapier connections is where the power is.
So a lot of the ones we talked about were actually internal Zapier tools, right?
Being used internally by their teams, but one assumes you can actually create customer
portals or bots on your website that could perform similar actions, but low stroke, no
code, because you're just doing it through Zapier instead of having to figure out yourself
how to connect different tools and move data from one tool to the next tool and all that
other stuff.
So in some ways, having access to generative AI is like a massive accelerator for all those
Zapier data connections that you set up over the years, but don't really bother to build
many Zapier apps for anymore, if that's just me.
Cool.
Well, hopefully that was a useful episode for everyone.
If you enjoyed, please subscribe, share it with your marketing friends.
If there's things you'd love us to cover on the podcast that we don't, hit us up on the
Twitters, connect with us and chat with us on LinkedIn.
If there's things that we talk about that you're like, nah, I actually think that bit
of the podcast boring.
Well, we want to hear that as well, right?
Because all feedback is very welcome.
If you want to come on as an interviewee, because you've got something interesting to
say, maybe you've been piloting some cool AI driven applications of your own, maybe
even into Zapier or other tools.
We'd love to hear about those as well, so please do get in touch with us.
Anything to share before we sign out, Martin?
Just the email address, actually.
People can email us their correspondence, hello at artificiallyintelligentmarketing.com.
And a human will respond.
Maybe.
It might just have to be as Zapier into action and we'll set up a really complex bot to do
that.
Cool, thanks for sharing that, Martin, and thank you for sharing your time today.
Lovely to hang out with you as always.
Yes, I'm looking forward to the next one.
Me too.
Have a good weekend, buddy.
Speak later.
Bye.
Thank you for listening to Artificially Intelligent Marketing.
To stay on top of the latest trends, tips, and tools in the world of marketing AI, be
sure to subscribe.
We look forward to seeing you again next week.