Welcome to Artificially Intelligent Marketing, a weekly podcast where we stay on top of the
latest trends, tips, and tools in the world of marketing AI, helping you get the best
results from your marketing efforts.
Now let's join our hosts, Paul Avery and Martin Broadhurst.
Welcome to episode 10 of Artificially Intelligent Marketing.
We're glad to have you here where myself and my good friend Martin Broadhurst.
Hi there, Martin.
Hello, Paul.
10 episodes.
Wow, we've done well.
We stuck at it.
Woop, woop.
The audience are like, oh God, they stuck at it.
But hey, you're still here too.
We love you for it.
We're going to be diving into this week's very cool AI news and interesting topics with
all of the lowdown on what it means for marketers and what they need to know.
This is a chunky one this week, isn't it, Martin?
We have a bunch of really interesting stories and a ton of short snippets.
So this week for the bigger stories, we're going to focus on Google's I.O. conference,
which was full of a ton of updates, many of them related to AI.
And I read a few things online implying that Google had gone from massively behind the
curve to suddenly in front of the curve.
So maybe we can get into detail about whether that's hyperbole or if it's a fair reflection,
Martin.
We're also going to talk a little bit about Anthropix, LLM Claude, which they've expanded
the capabilities of and Martin's been playing with that.
So I think it'll be interesting to go into that.
We're going to talk about Meta's announcement of their new generative AI tools for advertisers.
We're going to talk about Stability AI's new text animation tool.
And we're going to talk about some news from Microsoft about the chatbot ads are coming.
So they're going to be like the sort of main stories of the week.
And then in terms of the tools of the week, I've been lucky enough to get onto the Firefly
how to be Firefly beta.
And I've been having a little play with that and I'll share my experiences in terms of
the short snippets, the things we're going to very briefly mention, but we won't have
time to get into detail on.
Take a deep breath because there's a lot here.
There was this week an article in Bloomberg reporting that BuzzFeed readers spend 40 percent
more time on AI generated quizzes compared to the traditional ones that have been created
by humans.
I haven't been able to go into this story in depth, but it'd be really interesting to
know what has driven that.
So I think that's one we'll probably follow up on.
I'd actually forgotten BuzzFeed was still a thing.
Well there you go.
And here we are.
There we are.
There you are.
So I think that's that could be interesting.
And there's a number of ways I could imagine AI can use insights about the successes of
previous quizzes to be able to optimize quizzes for humans in a way that us poor humans have
to somewhat follow our experience and gut as opposed to data gleaned from a million
other quizzes, which they would perhaps be able to do.
There was a research report where OpenAI used GPT-4 to try and understand how GPT works.
If that's making your brain hurt a bit, you're not the only one.
In essence, there's a lot of discussion about how large language models, especially the
most new ones, the largest ones built on a trillion parameters, that we don't really
know how they work.
We know the fundamentals, but we can't explain after the fact how they generated a particular
output.
And so what OpenAI tried to do is try to use GPT-4 to try and make some predictions about
what a particular model would output at scale and got particularly close in a number of
areas.
So I think there was limitations in the research, but it could help us to identify how the models
behave, which could become important when we're thinking about things like safety and
alignment issues, which we've talked about before.
Yeah, explainability is going to be so important in this area going forward.
And I think a lot of that you'll see only becoming more important with the expectations
of regulators.
Absolutely.
So you can see why they commissioned this research.
Obviously explaining how GPT-2 works compared to GPT-4 is going to be a lot easier given
the size of the training data set and how the model works and all that other stuff.
But there you go.
Wendy's in the US is working on an AI chat bot that's being developed in collaboration
with Google to service customers at its drive-throughs, which is quite interesting.
I mean, we've seen a lot of automation in the fast food space over the last couple of
years as it is.
And here's another potential job within the fast food industry that we might see supplanted
very human no longer manages that interaction, but a chat bot does instead.
Interesting.
We've got mid journey 5.1 is already here and producing much higher quality images,
especially when you're working with shorter prompts.
And I don't know about you, Mime, but I'm playing with lots of different image generation
tools at the moment, but it's hard to look beyond mid journey in terms of just quality
of output.
Yeah.
I was looking at a comparison of mid journey 3 to mid journey 5.1, same prompt and just
looking at the outputs.
And it's, I mean, you would have thought there was five, six, seven years worth of research
difference between them.
Add it barely 12 months.
Yeah, that's kind of insane.
So I think mid journey is proving at least for us, the tool of choice that we are playing
with at the moment, because it seems to be the most capable when it comes to producing
really quality polished outputs.
There was a leaked memo.
In fact, this is after we launched the podcast about an hour after we went live last week.
There's old news now, seven days behind, old news about a leaked memo from Google where
an internal employee, supposedly an internal employee, we should say, questions the ability
of large companies like Google and OpenAI to be able to innovate and differentiate their
products faster than those working on open source alternatives.
For a huge amount of reasons, not least just innovative ideas and bandwidth and the number
of people that can tinker with open source tools and take them forward.
They gave some specific examples in there, didn't they, about being able to run the open
source models on smartphones already, albeit very slowly at five tokens per minute.
But just talking about the level of optimization that you can get when you take an open source
model and fine tune it and optimize it to these specific use cases.
And the language that they used in the memo as well, it's quite interesting how they said,
we do not have a moat when it comes to AI and nor does OpenAI.
However, I have thoughts which will come onto in the Google I.O. story.
Yeah, yeah.
I don't quite agree with that moat statement because I think having an installed user base
using Google apps or Microsoft based apps and hundreds of millions is a fairly significant
moat.
Yeah, that moat seems quite wide.
Yeah.
I think there's a commercial moat there that just may not be an innovation moat and product
development moat.
And the point you made is a really good one, Martin, in terms of open source tinkerers finding
ways to train models at a vastly reduced cost and much faster than some of the models that
are coming out of the bigger players.
But actually without any real dropping quality in the output of the large language models,
like a chat bot that's been trained on far less data for $500 over the space of a week
performs not that far off GPT-4.
And I think that's a major thing that came up in that.
If you're interested, find that memo online.
It's absolutely full of zingers in terms of, I think, insights into what it's like to be
on the inside of developing these models and how the Ecosystem is looking.
So I think, yeah, definitely worth looking into that.
And then the last one is actually just a silly thing.
What I say is a silly thing, it could well be real.
I learned this week that someone's building an app where they're trying to train the model,
a text to bark model, so that you can talk to your dog.
I know that sounds insane.
The website looks like really professional, like it's not an April Fools joke, which is
what I first thought it must be, something like that.
I've signed up.
I have a little puppy, a little Whippet, so I'll be attempting to hold deep conversations
about large language models with my Whippet.
They must be barking mad, aren't they?
Fine.
Boom, boom.
Yeah, you've got to think they're barking up the wrong tree with that one.
It certainly gives one pause for thought, I would say.
Oh, we could go all week, but we won't.
We absolutely should not.
There is too much news there.
Unsubscribed.
Sorry about that.
No more puns for the rest of the session, we promise.
Right, so that's your short snippets.
Let's get into these big old chunky stories.
Martin, tell us about the Google I.O. conference.
Google I.O., the annual conference where Google announces all things new for the next 12 months
in Google land, really.
It covers everything from search to hardware to Chrome.
You name it, they are talking about it.
This year, the theme was very squarely AI.
In fact, I saw one AI word count that said in the keynote, they used the term AI 140
times throughout the keynote.
So it featured front and center.
A few headline pieces.
One was that Palm II, their large language model, their foundational large language model,
has been basically baked in to the, or is going to be baked into all the Google products
coming soon.
If you're using Bard, that had a major upgrade on the day of the event.
So they took it from Palm to Palm II.
And in the coming weeks and months, we can expect Bard to become multimodal with image
generation capabilities.
They also upgraded the code abilities of Bard as well.
So a couple of details about the Palm II model.
It's a 540 billion parameter model.
It uses a compute optimal scaling, which means it scales the model size and the training
data set size in proportion to each other, which makes Palm II smaller and more efficient
than Palm I.
It's also used in some of their state of the art domain specific large language models,
such as MedPalm II and SecPalm II.
And that just a few, they mentioned a few interesting things on MedPalm.
So MedPalm is the medical LLM, the kind of domain specific, in the medical domain, should
I say.
And they said that MedPalm II is the first large language model to perform at an expert
test taker level on the MedQA data set of the US medical licensing examination, reaching
85% plus accuracy.
And it's the first ARA system to reach a passing score on a couple of other exams.
So the NED MCQA data set and the NEAT medical examination question scoring 72.3%.
In fact, the BBC had an article covering this story saying, meet MedPalm II, the AI to replace
your GP, which I thought was an interesting headline.
But it goes to show that it's creeping into that mainstream worldview that this is coming.
This is potentially down the track.
Clearly, it's not going to replace the GP, but these tools are going to be used in diagnostics
at some point soon.
We've spoke about it before.
But yeah, the main takeaway here was that Palm II is being baked into all of the products.
So you're going to see this being rolled out into search, into Google Workspace, Gmail,
and more.
There are a couple of other cool demos as well.
I don't know if you managed to catch any of this, but the Google Maps fly through the
city.
That was a very cool demo.
Basically, they had...
When you do directions on Google Maps, and normally we get this top down view with a
blue line, well now you will get a 3D rendered map view flying through the city streets with
real time weather updates or weather simulations built into that model as well, all generated
through AI imaging of the big cities.
Now that's going to be rolled out across New York, LA, London, Tokyo, etc., all the big
cities in the coming months.
That looked very cool.
They've also got something about video translation, lip-sync.
So it dubs videos for international markets and it does the lip-syncing in time with it
as well.
That one obviously causes people to prickle a little bit because of the potential for
deep fake issues with that one.
They did say that they're only releasing that technology to select partners.
So you can imagine that being rolled out to the likes of Khan Academy, Coursera, those
kinds of institutions.
Do you know the example I saw?
I saw this a while ago.
I don't know if it was Google's technology, a different one, and I don't know what the
movie was.
It was the one where two characters get stuck at the top of a very tall pole and they're
going to fall off.
It's like a drama over 90 minutes.
It was in the cinemas, so it's probably a famous movie and I'm probably doing a terrible
job of explaining it.
But the example I saw, they overdubbed it with a Spanish voice and lip-synced it.
It's a US film with US actors in it and it looked like it had originally been recorded
in Spanish.
Same actors, just their lips moving in perfect time to perfect Spanish.
I assume the Spanish was delivered by voice actors, but the lip-syncing was done by AI
and it looked incredible.
Yeah, yeah.
The example that they showed in the demo the other day was very solid as well.
So this is going to be an interesting one to see how.
I want to see who they give it to.
Who is this technology being deployed to?
Because they're clearly not going to make this available to everyone.
They were very big on safety.
That's one of the big messages that came through throughout on the keynote is that Google is
taking AI safety and responsibility very seriously.
They want to reassure you that that is all in hand.
I would think the artificially intelligent marketing podcasts are probably pretty high
on their list of priorities in getting the video version of this lip-synced in another
40 languages and helping us bring this to the world.
Well, if anything, you say them helping us bring it to the world, if anything, we'd be
helping them bring their model to the world.
I think that's how they should see it.
What a watertight argument.
Absolutely.
We'll get on the old emails and we'll get that all over to them.
Sundar, please give us access.
In fact, just give us access, not please.
No please.
For your own good.
That's quite enough nonsense.
There was a few other cool things around this, wasn't there?
Like this generative AI everywhere concept.
Tell us about that, Mark.
So this is basically the palm to being deployed in every aspect of the Google interface.
In the demo, they showed search, Gmail, they talked about...
So they had a Google Sheets example where you were in Google Sheets and you could just
ask it to... if you were a dog walker and you needed to manage your dog walking clients,
you could just say, create a table to help me manage my dog walking clients.
And it would then in Sheets create a table with columns such as client name, dog's name,
speed, frequency of walks, cost per hour, all that just done for you in an instant because
they had trained this on millions of spreadsheets.
So it just knows and it can do that.
So that was pretty cool.
Although I did see some responses of people on Reddit saying, oh no, now they're going...
I think they actually, the term that they used in the demo was we're going to free you
up from having to create all of these spreadsheets and people will say, creating spreadsheets
is the only thing about my job that I enjoy.
Yeah, I think also the downloads, the content marketing offers behind landing pages and
forms of get your template, that kind of puts the sword to those as well.
In terms of the example, I think I'd have full buy into that if there was an extra column
that plugged in via API to the text bark tool so that I could explain the itinerary to the
dogs I was walking.
That tool is called Sarama by the way, S-A-R-A-M-A for those that want to go Google it.
I promise you it looks real.
But yes, it's cool to see that.
And yeah, like we were saying right at the beginning of the podcast, Google going from
being quite far behind and everybody waiting for copilot to announcing all of this stuff.
And I've had BARD through my personal Gmail account for a while, but now I've been able
to get BARD through my Bystrata Google Apps account.
And there was a how to online from Google, how to get early access to a number of these
features.
I'm actually expecting to start to see BARD popping up to help me write emails and summarize
text and rewrite text in documents fairly quickly.
Whereas I haven't seen, I know you've got one bit of information that maybe goes against
this, but I haven't seen a huge amount of movement on the Microsoft side as it relates
to copilot making it into people's hands.
Google Labs is being, they did announce this, that Google Labs is where you need to head
to to sign up for early access to these things.
They're going to have write it for me in Gmail.
So where we've seen autocomplete on sentences in recent years, it's now going to have a
full write it for me and with a text expander and a tone changer and all of that kind of
stuff baked in.
One thing about the generative AI everywhere, if we look at the fundamental model of what
powers the Google enterprises is ads and search.
And that was very revealing.
They showed a, if in fact, if you go onto the Google website, you can see generative
AI in search and there is a GIF that shows generative AI implemented into Google shopping.
And on the example, there is a search query, someone saying that the search query is words
to the effect of an ideal commuter bike for a five mile ride with hills.
Now typically that result would normally, it would have brought up some Google shopping
results and then some blog posts with best bikes, best commuter bikes and all of that
kind of thing.
There might have been a featured snippet at the top of that that had an excerpt from one
of these blogs.
If you watch this GIF show the generative AI, what happens is you do the search and
then the shopping results come up.
So you get your ads, they're still getting the ad money in there.
And then beneath that, a full screen takeover, it pushes the organic completely off screen
and comes up with a generative AI, like, you know, barred style response detailing different
models of bike, bringing in images of the bikes with some ads in the side unit as well
of the response.
Organics gone.
Like there is, because then beneath that, it's encouraging you to ask follow on questions.
It's giving you suggested questions to follow on.
The organic results are quite literally pushed down the screen like, bye, you were ranking
number one for this and now you're not even visible.
Yeah I think it's, that could end up being fascinating.
I was found it interesting where the barred style response was also providing advice on
how to make a decision for the type of bike based on different use cases and what's important
to you and stuff like that.
I saw mixed reaction to this.
I saw some people online who were kind of excited because I think it still includes
references for example, where relevant and that type of thing.
But yeah, in terms of just getting pushed below the fold quite far into an experience
that the searcher can continue on in the chat style interface is obviously a bit scary for
SEOs and content marketers.
I think the other factor there is we don't know how these models produce the outputs
they produce, right?
Nor does Google presumably or any of the other developers, hence the paper we talked about
with GPT-4 trying to figure out how GPT-2 works.
SEO has always been about reverse engineering what you think you needed to do to please
the Google gods to get your content to rank first.
How are you going to run those tests now?
How are you going to figure out how to get your content even if you can get mentioned
in those barred style conversational responses?
Yeah, I mean, it's going to be fascinating to see how that plays out, but you would think
that that's just not going to happen and you have to hope people scroll down to the organics.
They gave one other insight into the scale of Google shopping actually.
They said there are 1.8 billion updates to the Google shopping inventory every hour.
Yikes.
And if you think about this is plugged into the new LLM and the generative results, yeah,
how are you going to game that from organic?
It sounds like if they're showing ads above the chat response and within the chat response,
I think they're thinking, well, we found a way to not destroy our ad based business model.
We just found a way to squeeze ads into as many aspects of the conversational style barred
response as we could.
So if we want to get our brands and our links up into that conversational space, we got
to pay for it.
I think that was certainly the message that I was getting from that.
SEOs everywhere wondering how is this going to change things.
Yeah.
So what's your key takeaway from this, do you think?
My big takeaway was that this is all about UX.
This is about making AI just accessible wherever you are.
And whilst if you've been in this, you know, if you got excited about chat GPT from November
onwards and went, oh, AI, this is exciting.
There was still a huge swathe of people that haven't seen it or played with it or given
it much thought.
This is about making AI accessible to absolutely everyone.
Not everybody wants to or has any kind of real need to be a prompt engineer.
I was working the other day showing my wife how I was doing something with chat GPT and
she just observed the way that I wrote a prompt and how detailed it was and how how thrifted
it was.
And she was like, you've got to understand that you clearly think differently.
And when you've played with these things, you do, you can see a good prompter and that
they understand how to put all of the context in there.
People don't have time for that.
The rest of the society, getting about your jobs and doing things, you don't want to be
building these long, complicated, crafted prompts.
You just want a thing in the Google Sheets now to do a thing for you.
You want whatever tool you're using, you want it to be there to be easy to be seamless.
And I think that is where Google have really pushed the envelope here.
If it lives up to the promise, this is looking like a fairly seamless integration.
Obviously there's a difference between the shiny marketing pitch to the lived reality.
But this is about just making generative AI everywhere.
And it's a UX play and I can see that this could be a very strong one.
I completely agree.
I was asked this week when we can expect to see generative AI and other AI, I guess mostly
generative AI tools in common use in workplaces.
And for me, and this was before the Google IO conference, I said it's when it's baked
into tools that people use every day already and it's just there.
I said that would drive adoption very quickly.
And when CoPilot gets properly launched and we've got it in Word and PowerPoint and Excel
and it will be interesting to see how fast we get this Palm2 driven tools.
They're not calling it BARD, are they?
I think they're calling it something else internally.
I can't remember what they're calling it.
When we see that in Sheets and Slides and Docs and Gmail, that's what will drive, I
think will go very, very quickly from the old adoption curve.
We'll go very quickly from the early adopters, which I think is people, many of which probably
who listen to this podcast playing with Mid Journey and playing with Writer and Jasper
and HyperWrite, these are the tools to get a feel for the landscape and see what they
like.
I think you go racing into the early majority once you put those tools in things that people
use day in, day out already, which I think for most people is Microsoft and Google Apps.
Yeah, absolutely.
And it will be the point when you don't even notice that you're using AI.
That'll be when you've got true takeoff.
Agreed.
So I think the next couple of months on that front are going to be fascinating because
I think that point is probably going to come, I want to say faster than I thought.
I was so excited about the copilot video and they made it sound like it was polished enough
to launch pretty much straight away and then we've not really seen much, have we?
There are interesting developments with Bing and the edge sidebar, which does give me hope
that they are making a lot of progress.
But yes, I think in the next couple of months, copilot in Microsoft and Google's equivalent
in Slides and Docs and all that stuff and Gmail is going to be the accelerator for mass
adoption, I think.
Rightio.
That's a long story, but it required it because there was so much there to go through.
Let's get through the others fairly quickly if we can.
We spent the lovely people's time who are listening to our podcast.
Let's chat.
Anthropic expanding Claude.
So for those that are not aware, Anthropic is somewhat of a competitor, I guess, to OpenAI
and other large language model developers.
They have created a tool called Claude, which can be interacted with in different ways,
but in essence has a chatbot just like chat GPT.
And what's really interesting here is that they have upgraded the chatbot to allow it
to process up to, I think it's 100,000 tokens, which translate to about 75,000 words of context,
which is three times more than OpenAI's max, which is also only in beta, that maximum context.
And only through the API.
So you can't actually easily access it.
This is a game changer for a lot of applications because it means that the AI can quickly digest
and summarize, reference and analyze large volumes of information.
I think I read somewhere online, was it the great Gatsby book that they pushed into the
tool, changed one sentence and asked it to find it.
And it was able to figure out which sentence had been changed.
So that was one example.
I saw someone else had asked it to analyze an 85 page Netflix corporate, Netflix corporate
filing highlighting all the important stuff for investors and creating tables from balance
sheets and providing analysis of marketing positioning and stuff like that, which I think
is, is really interesting.
This is another big upgrade in terms of competing with OpenAI and honestly offering something
better than OpenAI.
I was reading in one of the newsletters I subscribed to the, at this point is probably
going to help perform several chat with your PDF and chat with your Word document tools
that we'd previously mentioned on the podcast, just because of the sheer amount of information
you can give it in one go.
So yeah, I think you've been playing with this this week, haven't you Martin, since
it was released?
What was your thoughts on it?
Very impressed.
And it is a game changer.
The ability to just throw huge volumes of text, ultimately it's about a novel.
So a typical novel is about 70 to 100,000 words.
So you can stick an entire novel in there and then just start having a chat with it.
It's fantastic.
A simple workflow that we have on this podcast, I think we might have even mentioned it when
we were talking about the co-hair summarization tool that they announced a few weeks back,
taking a transcript from a podcast, a podcast that sometimes runs over an hour, because
some people just don't shut up.
So taking a transcript for a full show like that, there's a lot of words.
And if you try and put that into chat GPT, you're not getting close.
Like it's just, you have to chop it up into so many small bits.
Whereas what I did was gave Claude an example of the way that we format our show notes from
previous episodes.
I said, this is how we format them.
I want to give you a transcript and then can you turn that into show notes?
And I did that for the last episode that we recorded, chucked in the whole transcript
and hit go.
And it produced show notes that were surprisingly similar to the actual show notes from last
week's episode.
The headlines were actually identical, which I found really quite surprising to have got
that much accuracy, but yeah, absolutely totally usable.
And then I stuck in another transcript and it did it again.
And yeah, that much context is, in terms of if you're looking for a differentiator against
something like GPT-4, massive amounts of context will do it.
Absolutely.
I think that's probably where the next battle in the war of the generative AI companies
may be fought is actually in contextual understanding and the ability to deal with large amounts
of information.
We developed a process here at Biostrat of some of the podcasts and audio and webinars
and things that we do where we generate the transcript, which is often a good 10, 15,
20,000 words for an hour.
You'd be surprised how much nonsense we can talk on this podcast especially, but when
people are speaking quickly, any transcript is usually a lot of content.
And we got to the point where we had to split it and chunk it and you had to give Chachie
PT maybe five, six, eight, 10 sections.
You had to split that.
And that's kind of manual.
And there's always the danger that Chachie PT forgets what one of the first sections
was about and all this other stuff.
So the ability, not any of the speed and efficiency, but probably the quality of the output to
just be able to dump that whole transcript in, it really will...
I can't wait to get a hold of it.
I've now put myself on the wait list.
I know you've had it for a while, Martin.
Maybe you can have a word for me.
You know, ask Claus.
Hi, friend Paul, please.
But yeah, if you're developing content like webinars, podcasts, the ability to now turn
that into text-based content like blog posts or eBooks has to be so much faster and easier
now, I would have thought.
Very much so.
And just on the point about taking contextual content, we spoke the other week about embeddings
and fine tuning and putting huge amounts of data and then training your own model on top
of any of the existing, you know, GPT-4s or whatever.
And these are complicated processes.
And for many SMEs in particular, you don't have huge, huge, huge enterprise levels of
knowledge base and documentation, but you do have maybe a novels of content.
And now you can just stick that in a prompt.
You don't need to create vector embeddings and databases and integrations.
Just stick it all in a prompt and be like, there you go.
That's our business handbook or our, all of our blog posts from the past 12 months, use
that as context and help me produce more.
Could you imagine that?
Give it sort of a hundred or blog posts, might end up being slightly too many, but, and then
say, which of these could be pulled together to make a summarized, insightful eBook on
that particular topic, right?
Give me infographic ideas based on the data that you find in these different blog posts.
Yeah.
I mean, you could do so much cool stuff.
Right. In the interest of time, because I think we could go into so much detail on that
one, we will crack on.
Let's talk Stability AI and the text to animation tool it launched, right?
Stability AI has launched Stable Animation SDK.
So this is a tool designed for artists and developers to implement the most advanced
stable diffusion models to create animations.
And there's a number of ways that users can create animations so they can do through prompts
without images, so text based prompts, or they can add a source image and use it as
the kind of seed input, or they can use a source video.
So you can also have text input plus an initial image input.
So the user will provide the initial image that acts as a starting point for the animation
and the text prompt is then used to basically guide the end result.
And all of this has been made available for developers to integrate into their products,
their platforms, what have you, via this new SDK.
So that's just, again, making it really accessible, stable diffusion.
So my understanding is that this is actually now, is this open source?
I'm not sure.
Is the underlying model open source?
I don't know if you can access it.
So I did dive a bit deep into this.
Certainly you can't access it via a web app yet.
So it's not going to be easy for your average marketer, if I take myself as an average marketer
to get involved with playing with it.
As I understand it at the moment, you have to download the necessary files and install
the SDK using Python and you have to have a bit of coding experience to be able to use
it at the moment, I think.
Yes, I'm just looking at the model so it's all API driven pricing based on the size of
the image.
So dimension and image, that's 512 pixels by 512 pixels.
The credit cost per operation will be 0.058 cents and the credit cost per resample operation,
so 3D rendering mode, which sounds pretty cool, is 0.17 cents.
My take home on the pricing just looking at it was we've had a chat off air about how
these models work to generate video versus text and it's certainly more complicated than
what I'm about to say.
But in essence, if a static image is a frame and an animation is operating at 20, 24, 30
frames a second, in essence these tools are just creating many more images and stringing
them together to create moving images, i.e. video and animation.
So it's probably going to eat up many more credits and cost much more to create these
short animations than it would when you are creating static images.
The cost of those generations for the different tools you might use like Dream Studio or whatever
has been dropping all the time, so I don't think it's going to be prohibitively expensive
for anyone if I'm honest, but it probably will cost 25 times as much, give or take,
one would imagine if you're creating a couple of seconds worth of video and actually doing
it at 24 frames a second or whatever it may be.
The actual outputs themselves, they look pretty, you know, at the moment pretty raw, aren't
they?
Yeah.
It's probably fair to say.
Bit glitchy.
Bit, yeah, just a bit, a little bit janky.
The transitions aren't super smooth at the moment, much like we mentioned in last week's
episode with the anime trailer and the vehicle that's driving along the road and then suddenly
becomes the road.
It's kind of got that sly vibe to it.
But again, this is all day one.
If you look at, you know, what we said about mid-journey earlier on, just fast forward
12 months of where this is going to be, yeah, and the acceleration in this area is going
to be huge.
That's important to remember because we were like, oh, look at their hands.
The hands look terrible and they've got 52 fingers and oh, look at the faces.
They look like ghouls.
And now of course we've got the Pope in his pimps.
Balenciaga coat.
Yeah, in his jacket looking like the boss.
So yeah, I think you're right.
I think we can expect to see that improve quite quickly.
I think for marketers using it now, providing they can get it set up, you could probably
create some interesting glitchy style things to play with and get attention with online.
But yeah, we're not a production ready yet.
But as Martin says, probably won't be that long until we see the develops we need to
actually get that quality.
So yes, worth digging that one out and having a look.
Right, next news is Meta announces generative AI for advertisers.
So Meta has unveiled a new product called AI Sandbox, which is aimed at streamlining
the process of creating ad creatives for advertisers.
The Sandbox provides three key functions.
It can generate several versions of ad text.
It can create a diverse range of creative assets for campaigns.
And it includes a cropping tool for tailoring visuals for different sizes and formats, depending
on where you're using it within the meta sphere, if you like, of across Facebook and all these
other tools.
We are not able to fully explore it yet and tell you what it can do because it's not launched
yet.
It's not how you can actually access it.
But it certainly sounds like an interesting development for marketers.
You could imagine a number of benefits that are going to come from this.
I mean, off the top of our heads, you know, efficiency, because if you can use the AI
Sandbox, you can significantly streamline the ad creation process and come up with multiple
ad copy variations, diverse campaign assets and stuff.
And it'll probably do that all quite quickly or within the Meta ads interface itself.
Right.
You can imagine improvements in creativity if you've got a bit of writers or creative
block a little bit like how people are already using Mid Journey and Chat GPT to just give
some ideas to get your own ideas going.
So you might not use the outputs that the AI Sandbox produces, but it might just get
your thought process going.
I think you can definitely imagine some real time adaptation and performance improvements
of your ads over time, right?
Because if the AI driven system is gathering data on what text and creative is working
best for your brand or for different product times, different audiences, different messages,
all that stuff, it could auto adjust the creative and copy running ongoing experiments to improve
results on an ongoing basis.
Right.
Which I think there are tools, fairly sophisticated, expensive tools that are offering to do that
across different platforms.
But this would be all within the Meta ads interface itself, which would bring it to
many more people.
Right.
Yeah.
I have thoughts on that.
So, when you read the press release for this, the technology and the implementation, again,
it's a kind of UI player.
We've got some cool tech and we've made it really easy for advertisers to do background
generation and testing of different creatives and what have you.
Just reading some of the detail, they talk a bit about this Advantage Plus, which is
basically AI ML powered optimization of your campaigns.
I don't know if you ever speak to any Google AdWords specialists who talk about Performance
Max.
So, Performance Max is Google's answer to, well, it's not answers, Google's product that
says basically let us deal with your campaigns.
Give us budget and we will deploy ads across all of our ad units and they will be brilliant.
Trust us, our machine learning algorithms know what they're doing.
If you speak to any AdWords specialist who has been doing this in the industry for many
years, they will tell you, do not turn on Performance Max.
This is Google putting your ads in sub-optimized ad units, focus on tightly targeted keywords
with high search intent, all of that kind of stuff.
Be careful of turning on Performance Max because Google will spend your search intent money
on keywords that you have no interest in bidding on.
My concern with something like this Advantage Plus, just reading the press release makes
me think, okay, this is Meta trying to sell ad units that if you go in and optimize your
campaign, you know what you're doing.
I'm a reasonably confident advertiser on Meta for instance.
I'm not brilliant, but I kind of know my way around the system.
I know what ad units I will and won't buy for instance.
Advantage Plus will just start putting your ads anywhere that they want to sell an ad
based on and they will use this AI creative editor to make the ads work in that ad space.
It makes it sound like, oh yeah, we're really doing you a favor.
Whereas really what they're saying is, oh, we'll make your creative fit to that ad unit
that you had no intention of ever buying so they can sell more inventory.
Maybe I'm being cynical, Paul, but...
I think we're going to try and make this one of our shorter episodes and it's not, unfortunately.
There's a lot of good discussion points to be had.
I am not a Google Ads expert, but I know enough to be dangerous.
As you said, I do have those conversations.
I am extremely cool as many people in the world and those listening to the podcast will
know and a lot of my friends are Google Ads specialists.
I've had this discussion a number of times and I think my experience has been in the
early days, avoid switching on the automation.
Google just wants to spend more of your money.
But my impression from a lot of the people I've spoken to is as the algorithms have got
better, as long as you've manually run the program for enough time to give it the algorithm
an opportunity to train on your particular ad set and your keywords that you're bidding
on, so it can actually learn a bit about who the best people are to target.
Then you adjust it for things like cost per conversion based bidding.
You can actually do better than micromanaging the cost per click bidding and using single
keyword ad groups and all this other stuff that Google Ads specialists used to do in
the past.
There's actually a book on this, it's very interesting, by a guy called Patrick Gilbert
called Join or Die, Digital Advertising in the Age of Automation, where he actually makes,
he's a Google Ads expert, an argument for why now is the time to actually turn over
the reins to the algorithms to optimize your campaigns for you.
Super controversial.
I can certainly imagine how your Google Ads specialists wouldn't want that to be common
knowledge or to be the common belief because I guess in theory it might mean that they
feel or that their clients feel that they're no longer needed.
I don't think that's true.
I think it's exactly like when you were using ChatGPT, you need an expert monitoring things
to make sure that nothing untoward happens.
When you're using Google Ads, untoward means accidentally spending thousands or tens of
thousands of pounds by accident on something that produces absolutely nothing.
So expert in the loop is actually critical.
But yeah, my impression had been that we're starting to reach a tipping point in terms
of people's attitudes on that.
If you're listening to this and you're a Google Ads specialist and you've got an opinion,
hit us up on the Twitter's.
Our Twitter had the line, never remember E is Martin.
Aim podcal, no God.
Now normally people who run podcasts would cut this, but we're not going.
No, no.
Cool.
That's how we like it.
I can tell you with certainty actually, never in doubt it's Aim or AI Marketing Pod.
It's at AI Marketing Pod.
There we go.
There you go.
AI Marketing Pod.
We'd love to hear what you've got to say.
And if you want to come on as an interviewer on the podcast, we'd love to get you on messages
on the Twitter's, on the LinkedIn's.
We'd love to hear your opinion.
So yeah, I think that's very interesting, Martin, because for me, we've heard a lot
this phrase, AI won't replace people, person X, but people who use AI will replace people.
But this is one of those examples where it could almost become quite quantifiable because
you could imagine that if this works as intended, our previous discussion completely accepted,
the companies that are able to rapidly iterate automatically to improve their ad copy and
ad created to drive conversions and sales are going to very quickly pour more money
into that system.
A, they're going to out compete the people who don't use the tools.
And then when everybody's using the tools and everybody's pouring money into the system,
all the cost per clicks and all the other costs are going to go up and putting more
pressure on the system.
Meta's very happy that everybody's pouring money in and happy to spend more.
But at some point, one assumes they're going to saturate the audiences through this.
And we're going to end up seeing so many ad variations and ads in our feeds that it could
really pee us all off.
So it'd be very interesting to see what the second order consequences of this would be.
Yeah.
Cool.
Right.
In the interest of speed, we'll rattle on.
We've got a couple of extra things to chat through.
While we're talking about ads, let's talk about chat bot ads are coming.
So Microsoft this week has indicated that advertisements delivered by AI chat bots are
on the horizon, potentially changing the landscape of search advertising.
This is not dissimilar to what we touched on briefly in terms of what Martin told us
in terms of Google search and ads showing up in the actual conversational area.
I think this is what Microsoft is planning to do on its own platforms.
But also interestingly, with partners who have AI chat bots on their own websites, a
little bit like Google Display Network or, you know, Display Network advertising, but
for chat bots.
I would imagine that for most marketers, they're going to be wanting to use this to expand
their reach once it sort of makes its way into different chat bots across the web.
But it also got me thinking that as a publisher, I could imagine that if I had a big repository
of content on my website, you know, what springs to mind for me is the natures and the sciences
and the cells of the life science world, which have all this incredible peer review research
articles that you could query and ask questions of via a chat bot.
But as a publisher, monetizing that by introducing ads, relevant ads in the chat bot experience
would be quite relevant.
And then, at least in our market, I can imagine that being of interest to life science marketers,
marketing instruments, reagents, tools that perhaps were used in those research papers
to ensure that their products or their content is also shown in amongst that chat bot interface.
So this is quite early days on this.
If I've understood it rightly, there's no screen grabs or anything out there that shows
you what this would look like.
But it is a Microsoft press release.
It is real.
This is what they're planning to do.
And as they say in a quote, we're ready to engage to discuss chat experiences, whether
they need both algorithmic organic results and ads monetization or ads monetization only.
We're listening to feedback from our partners as we continue to learn and evolve our offerings.
So let's see how this plays out.
Ads in chat bots and how different companies leverage that on their own chat bots and then
how people bid and buy space in those chat bots.
Yeah, got to find a good use case to have a chat bot on your website in the first place
and then say time to monetize.
Yeah, yeah, I think you've got to be a publisher with the reams of insightful information or
information and content that that chat bot can draw upon, which is why I think it will
end up being a publisher play.
But obviously if there are publishers, niche publishers or broad spectrum publishers who
reach your audience and they introduce these chat bots, there's an arbitrage opportunity
there if you get in early and you can negotiate those deals with those publishers and be the
first that's shown in their chat bot experience.
Because I can imagine that people are going to want to play with it and see how useful
it is compared to trawling through archives of articles or just leading into Google search
or whatever.
So it could be interesting.
We'll see how that one plays out.
Rightio, last bit is tool of the week.
I mentioned this at the beginning.
I was able to get access to Adobe Firefly.
Now you imagine, you could imagine, but hopefully you'll remember, mine and I were super excited
about this after watching the demo video, which was really, really impressive.
And I have now got access within Adobe Firefly.
There are a bunch of tools that you can get access to from being part of the beta.
You can get their text to image, which is honestly not really very different from any
of the other mid journeys and Duallys and other things that are out there.
There is the recolor vector tool, which I haven't played with much, but I can talk to,
is fairly novel and not offered by most of the other tools, certainly tools I've played
with.
And then there's their text effects where you give it a word and then it stylizes the
text.
And I think the things we were most excited in the demo video was things like having the
biostrata logo made out of dripping chocolate or fire and this type of stuff.
So text to image, pretty powerful.
Make some really interesting images.
I think where it lacks finesse potentially, or not finesse actually, because the images
look good, it's more the scope of what you can do with it is it's trained on images owned
by Adobe.
So that's great if you're a large company and you're concerned there's going to be copyright
issues down the line if you're using a stability AI or if you're using mid journey.
But I think it also does limit it.
And I saw an example online, which I also ran myself, of trying to create images of
popular characters or famous people.
You just can't do it because Adobe's image set doesn't know who they are.
So I tried to create an image of Deadpool.
I saw this example online of how mid journey will create an image of Deadpool sat on a
car, but of course Deadpool being a Fox Disney character at this point, Marvel Disney character.
Adobe creates something that looks a bit like Deadpool, but it's clearly not.
So I think that it's the text to image cool, it has some real nice finesse to it produces
really high quality images, but there's stuff that it can't do that other open source tools
can for good or ill.
On the text image front, this was the one I was the most excited about because it looks
so cool.
The text effects.
Yeah, yeah, text effects.
Sorry, I've not described that correctly.
You give it a word and you say, make this word out of dripping paint or balloons or
something like that.
It is powerful.
It creates some really interesting effects, but it runs into limitations extremely quickly.
And what I mean by that is in the example that I was using it for, I gave it the word
biostrata, which is the name of our marketing agency.
And because we work in the life sciences, I said biostrata made out of cell culture
cells and it kind of gave me something that looked kind of biological, but there was no
obvious cells.
It looked a little bit like it had tried to make it out of a graphic artist representation
of the organelles inside cells like mitochondria and nuclei and Golgi apparatus and that type
of stuff.
But none of them really looked accurate.
So it looked like a designer who didn't understand science had created it.
Right.
And I couldn't use that then for obvious reasons.
So then I was like, oh, okay, well, let's try DNA.
I pretty much got the same output as when I said cells.
Oh, it's almost like the backend is like grouping all of this into biology and then doing what
it thinks biology looks like.
I tried chemistry and it looked a bit different.
And in a few places, there were things that looked a little bit like conical flasks and
stuff.
There were a little bit of like biology type structures in there that look a bit like neurons.
I tried neurons, didn't really look like neurons.
It just looked like biology.
So very cool.
You can get some really cool effects, but your ability to really explore a creative
space, at least in the tool as it is, in my experience is limited.
I would imagine that if you keep it to kind of fairly, like the example that they gave
was that they've done like food styling, didn't they?
And like skyscraper, was it landscape, cityscape kind of images.
But yeah, where you start getting into quite technical things there, it is just falling
flat and clearly not many cell culture images in the older stock library of Adobe.
Well, and so herein lies the rub, because there are.
And it could have used, I think I tried at one point, use microscopy images, basically
got the same thing again.
It's like in an attempt to create this usable tool, it's almost like the large language
model that underpins understanding the prompt, groups, related terms to generate an output
that looks a bit biological, but isn't actually the thing you asked for.
And that could be just because it's a demo, really, because it's a beta, and maybe that
will improve.
But I would say you can do some cool stuff with it.
You can probably get some inspiration from it, but you can't just imagine to your heart's
desire and get what you want.
And if we look at the recolor vectors tool, there's similar limitations there.
So for example, when you try and recolor the vectors, you can't give it a hex code and
tell it what color you want, as far as I can tell.
There are 18 different color palettes, colors across the palette, white, black, a neon green,
blue, but you can't give it your color.
So if I wanted to recolor a particular vector in Biosstratus brand colors, that option is
not available right now.
I have to recolor it in the colors that are made available here.
So again, implications of power with limitations that fundamentally probably wouldn't make
it usable for a graphic designer delivering on a client brief, for example.
So cool power, wonderful demo.
Probably if you're a professional designer, it's not going to be able to do what you need
it to do just yet, is what I would say.
In terms of actually using the tool, if people wanted to sign up for it, how do you interface
with it?
Is it through a web application?
Is it a plugin in Photoshop?
Pass on the Photoshop.
I haven't actually opened up Photoshop to see if I can now access it through the fact that
I'm on the beta.
I'm using the web app, which is firefly.adaby.com.
You'll have to sign up for the beta waiting list.
And then you access it all through a web app similar to the dream studio and clip drop.
And those types of tools.
Cool.
So that was your tool of the week.
Thank you so much for joining us here.
Please subscribe if you enjoyed this, share it with your marketing friends if you found
it useful.
Maybe they will too.
Martin, love hanging out with you.
Thanks for your time today.
I'll catch you next week.
Yeah.
See you next week.
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Oh, what a top tip.
Nice one, Martin.
Have a good weekend.
Speak to you next week.
Cheers.
See you later.
Bye.
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