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 13 of Artificially Intelligent Marketing.
Lucky number 13, Martin, what are your thoughts on that?
I think something's going to go horribly wrong.
Let's hope not.
I think maybe it'll be the best episode ever.
So that's what I'm aiming for.
What have we got for you all lovely people this week?
Well, we've got a few short snippets as usual.
We've got a series of main stories that we're going to cover today, including HubSpot rolling
out campaign assistant.
We're going to look at an attorney in the US who used ChatGPT to build a brief that
was then full of junk, unfortunately, because ChatGPT made a load of stuff up and there
was a big hullabaloo.
We're going to talk about that.
We're going to talk about a sneak peek into the future of OpenAI from Sam Altman.
And we're going to talk about a new paper that was released this week where OpenAI trained
the model based on its reasoning, not its outcome.
We'll talk about a little bit about that later.
And we're also going to lean into our tool of the week this week, which is Recraft AI.
Right.
Let's get them short snippets done first, Martin, because they're quickies this week.
Some of you lovely folks might have seen that Microsoft is rolling out Intelligent Recap
for Teams meetings.
So in essence, Intelligent Recap is bringing a number of the features that a couple of
other tools already have like Tactique and Otter in terms of doing things like smart meeting
summaries, capturing the actions and that type of stuff.
So if you're a Microsoft Teams user, and especially if you're already a premium user, go check
that out.
I'm not, so I haven't been able to play with it, but you definitely should because I bet
it can save you and your team some time.
Then we had a fairly interesting and cool life science company called Benchside that
raised $95 million to help build out, further build out.
It's AI drug discovery platform.
I haven't had a chance to dig into this too much yet, Martin, but it looks really cool.
Like they're collating biological data from across a wide range of sources and using machine
learning and visual recognition to basically make that information searchable and for you
to be able to draw links between, I don't know, different disease states, different
drug trials from the past and that type of stuff.
So yeah, I haven't dug in too deep to say for sure, but it looks kind of interesting
and I will be looking into that in a bit more detail.
And then the last short snippet is the launch of Nvidia's generative AI service, Nvidia
ACE, which is for game developers.
This was pretty cool because one of the demos was trying to use low latency natural language
generation to have non-playable characters interact with you in a less formulaic way.
So you can imagine you're playing a game and you're playing it through for the stick
time and rather than being able to predict what that character says when you walk up
to them, you no longer can with this type of technology because they'll automatically
adapt to the different things that you might say to them.
You're smiling.
I saw the demo and it was a player walking up to someone, there was an NPC behind the
bar and there was the conversation that took place.
It just looked cool.
I just immediately imagine how much an open world game is going to be expanded by that.
I mean, yeah, incredible really.
We've got supposedly, we've got Apple's VR AR headset announcement next week as well.
So that'll be quite interesting to see how much that leaps the industry forward because
that would be the other bit of technology to plug into your vision there, Martin, wouldn't
it, for maybe being fully immersed and able to not physically, but walk up to the bar
in VR and have that conversation would be pretty cool.
Yeah.
I think the VR games just haven't quite tipped over yet into the mainstream.
There's still something holding people back, but if any company can make it mainstream,
let's be honest, I think our money would be on Apple to do so.
That's what I'm kind of hoping for, if I'm honest.
I've had a Quest 2 since probably the start of the pandemic, so not long after they came
out.
And I really like it.
I think it's a cool piece of tech.
There's a boxing simulator, which is surprisingly fun to play.
There's a golfing simulator, which is awesome.
Playing table tennis in VR basically got me through the pandemic in some respects.
So I think there's loads of niche cases that are really enjoyable, but you're right, if
Apple can bring it to the mainstream, that would be kind of cool.
And when I saw this story, I couldn't help but think with my marketing head, if we can
create NPCs that can be that dynamic and with things like Unreal Engine 5.2 and really significant
improvements in graphics, does this change how things like bots, customer service bots
and sales bots on websites might operate?
Because it might be more like a virtual video call, the bots on those websites rather than
a little chat window, and we might be able to have fairly dynamic interactions with them
a little bit like you would with NPCs.
So if they can develop and enhance and figure out how to make the technology work in games,
we might see it filtering to customer service, sales and marketing.
There's a thought.
Right, let's get into our big old stories for this week.
And we're going to start for number one, which is that HubSpot rolls out Campaign Assistant,
their free AI marketing asset creator.
Has been having a little look at this, Martin, tell us more about it.
This was in beta and actually it still is in beta, but they've opened it up that anybody
can access it now.
And this is a generative AI tool from HubSpot that will generate copy for landing pages,
emails or Google ads.
And it's quite a nice interface.
You just answer a few questions.
It literally has a little box that tells you to describe what it is that you want to promote
or that you're offering.
And then it will ask about the tone and the style so you can select three boxes and pretty
much that's it.
And then it will spit out a result.
It's a hundred percent free to use.
It doesn't look like they're making any restrictions on this at all.
You do need a HubSpot account.
So when you go along to the Campaign Assistant, if you don't have a HubSpot login, you will
be asked to sign up to the tool, at which point you will then be part of that ecosystem.
But yeah, I thought the fact that it is completely free to use is pretty generous.
The outputs are really good.
I thought when I used it myself, I wasn't sure whether they've maybe in their system
prompt in the way that they've configured it, whether they've given it quite tight specification
and examples with fine tuning.
I suspect that they have, but you can actually see the user input as the prompt.
So when you generate the output, you see the input that it gives you.
So it just takes the text that you put in the boxes and puts that as a user prompt as
if you've spoke to ChatGPT and you get the answer out from the agent.
Right.
But I did come across a little frustration at the moment with it.
And that's basically, it's kind of a standalone tool.
So it isn't fully integrated into the wider HubSpot suite.
So if you are a HubSpot user already, just be aware that this isn't like you're going
to go into the email section, create a new email, and then within that space, you're
going to be able to generate some text and just populate it into your campaign.
It's standalone.
You just have to copy the text and then paste it into your campaign.
And actually what I found quite frustrating in my use case of it when I was testing it
is I copied the text to add it into a campaign, I dropped it in, and actually the text didn't
add the kind of formatting.
So the markup was included in the copy, if that makes...
So it said headline and then said the headline and it said paragraph one and then added paragraph
one.
So just adding it into the actual content editor within the email interface was just
a bit clunky.
You just had to edit that.
But other than that, I mean, bearing in mind, this is a beta product and it's completely
free and looks like it's going to remain free for everyone.
I think they've done a really solid job.
Yeah, that's awesome.
I had a bit of a play with this in the beta.
I think I was using it to come up with outlines and copy for blog posts, just a couple of
experiments.
And certainly my feeling at the time was, and I think this maybe was pre-GPT4, I can't
remember, but my feeling at the time was I'm a bit surprised at the high quality of both
the outlines and the content I was getting in terms of how informed it was on the topics.
Now, of course, I was testing marketing-based topics for the Byastrata blog and you would
hope that generative tools would know a bit about marketing given their hubspots.
So I don't know whether they've trained their tools on data they've got or other sources.
But at the time, I remember thinking, this is better than I'm currently getting out of
say ChatGPT or other tools.
So that was quite good.
Did you have any experiences where you could sort of ascertain how good is the information
that this is producing?
How well written is it or anything like that?
Now I thought that it did stay quite close to the style.
In a couple of instances, for instance, I actually tried to create a marketing email
promoting the podcast.
And in the input text where I described what I was promoting, I explained the podcast and
I said, I present it with you and I said that this is Paul Avery, CEO of Byastrata.
And then when it wrote the actual copy, it kind of got confused because it was attached
to my company's HubSpot portal.
So it talked about it being from my company, but then talked about our CEO, Paul Avery,
CEO of Byastrata.
So it just kind of got a bit lost with those kind of little minor details.
But other than that, I actually thought the way that it structured the email, so it had
appropriate paragraph length, it had sub headers, it didn't...
Yeah, I thought it did a really good job.
It is powered by OpenAI.
It does have a disclaimer on it saying you have to basically be aware that you're kind
of sending data to them and not to share any sensitive information.
It does explicitly say that in the input prompt.
That's probably useful to know.
Thanks, Martin.
So there you have it.
If you're a HubSpot user or you're in the habit of coming up with business ideas and
throwing up a landing page in HubSpot to see if you can get anybody to sign up or anybody
interested, you can now set up a free HubSpot account and start playing with some of those
tools.
For people that have never used any generative AI, this campaign assistant just makes it
dead simple.
And the fact that it's free is a lovely bonus.
Agreed.
So there you are, people.
Go and have a play.
Let's move on to story number two, Martin.
So this is an interesting one and we're using this as a launchpad for a wider discussion
on the pros and cons and risks and rewards of using generative AI tools.
So I'd be very surprised if anybody hasn't seen this news item now because it blew up
across many different news networks outside of the fact that it was just AI.
But attorney Stephen Schwartz in the States submitted a brief as part of a lawsuit against
Avianca, a Colombian airline, and used ChatGPT to generate the brief.
I've got the SuperWidey report, but I've got the New York Times article here in front
of me at the moment saying that it was a 10-page brief that cited more than a half a dozen
relevant court decisions, but unfortunately, none of them were real.
It's so stupid.
It's just such as, I can't believe you did it.
It's kind of crazy.
So a couple of things here just to let you know that just so that we all realize how
fallible we are and how easily this could happen, right?
So Mr. Schwartz, according to the New York Times, has practiced law in New York for three
decades.
This is not an intern or someone fresh out of grad school.
This is someone who has been playing this game for a very long time and I'm sure understands
the importance of verifiable sources, right?
And in fairness to Mr. Schwartz, he also threw himself, as the New York Times says, on the
mercy of the court on Thursday saying that he used the Artificial Intelligence Program
to do his legal research, in quotes, a source that has revealed itself to be unreliable,
no SH1T, Sherlock.
So I think this just goes to show just how easily you can end up if you just leverage
the stuff that these models push out as fact, you can get yourself into a sticky situation
pretty quickly.
Who could have predicted that that would happen?
It's so stupid, it kind of makes my brain hurt.
But fair play to him for holding his hands up and saying, yep, you caught me.
Can you imagine being the opposition legal team in that instance and you're spending
one at a time crawling and trawling all of the court documents and case law and going,
we just can't find it.
Has he just made it up?
That would be strategic though, wouldn't it?
It's like, I need to keep them busy while I figure out my real argument.
Here, go look up these sources that sound plausible but are not real.
And then that moment when his client must have found out in the courtroom, I'm sorry,
you did what?
I'm paying you how many dollars an hour and you just, oh my dear Lord.
Yeah, so it does go to show that anybody can be duped.
And it goes back to that point about when ChatGPT was first launched, people were saying
that ChatGPT is a bull.
It tells BS.
It's convincing and you read it and you think it's real.
I had an incident recently where I was testing the plugin, the new browsing plugin in ChatGPT
and it was after the Sam Altman Senate hearing.
And one of the clips that I turned or one of the bits of the conversation I wanted to
kind of dial into was about nutritional labeling for AI systems and I asked ChatGPT to explain
this a bit more and I thought, well, it's been mentioned at this hearing so it must
be a topic that a few people have written about.
And it came back to me and said, what you're referring to with nutrition labeling is actually
model cards and model cards were created by Google and they're a way of explaining what
an AI model does, blah, blah, blah, blah, blah.
And I just knew that wasn't true.
But if I didn't know that I would have just taken it as red because actually it sounded
plausible and if you're someone that doesn't follow these things closely.
So I had to say to it, I kind of gave it a telling off and said, no, that's just not
right.
This is a very new concept, but actually what was interesting upon telling it off and telling
it to try again, it must have refined its kind of search parameters because it ended
up coming back saying, oh, this concept was mentioned at this Senate hearing early this
week.
I can't find any other information about it.
This must be a new concept and therefore just kind of watch this space.
It's so interesting, isn't it, that you...
Because I've seen people chastise chat GPT for being wrong and then it's like, oh no,
you're right.
I'm wrong.
Thanks for letting me know.
And it's like, well, if you knew, why did you do it?
And that's because it doesn't know because using the word no is a misnomer.
It's not a correct use of a term here because it's just based on its probability of what
it thinks the next term should be.
Even if it can browse the web, there's going to be this issue is going to be in the system.
In the case of Mr. Schwartz, according to the New York Times article, he told the judge,
Judge Castell, that he asked the program to verify the cases were real and it said yes.
Right?
Well, that's due diligence.
I'm sure you pay them big money for.
So I think in summary, and this kind of reiterates, but it's a perfect real life example of things
that we said on this podcast several times, many times at this point, which is having
an expert in the loop to verify the information that's coming out of these tools is absolutely
critical.
Otherwise, you will make yourself and or your company look like fools and you either need
to understand the topics that you're prompting it about so that you can provide that critical
thinking and analysis to what comes out.
Or you need to be prepared to do rigorous due diligence on quite a lot of stuff that's
coming through from them, but certainly anything that you think sounds a bit dubious.
Yeah.
Right.
Let us move on to the next story then, which in this case is a little perhaps a little
bit of insight into where open AI is going, where GPTs are going.
So this comes from humanloop.com where Raza Habib has documented an interview with Sam
Altman, the CEO of OpenAI and a number of other developers to talk about where OpenAI
is going.
And this article is fascinating because it's got loads of like juicy bits in it.
So we're going to pull some out here, aren't we, Martin, in real time based on the things
that we found the most interesting.
So where do you want to start?
I think start at the top.
So the OpenAI heavily GPT, sorry, GPT, GPU limited at present, which is not a massive
surprise.
We know that the amount of compute power required for these large language models is massive.
It actually links back to what could have been one of the short snippets this week,
which is Nvidia, developers of GPU technology, just about.
I'm not sure if they quite broke the trillion dollar mark this week, but their investors
clearly see a lot of opportunity for them in the AI space at the moment.
So their valuation went through the roof.
But yeah, GPU capacity is what is delaying the short term plans of OpenAI at the moment.
And apparently Sam acknowledged their concern and explained that most of the issue was the
result of GPU shortages, specifically around frustrations that users have when it comes
to the speed of GPT-4 because people get a bit frustrated with that.
But also some of the functionality that was teased when they announced GPT-4, the launch
event and Greg Brockman did the demo with turning the pencil sketch and a notebook into
a real working website.
That multimodality is not coming anytime soon based on what this report says.
We're not going to see that until 2024 simply because they need more GPUs to come online.
Slightly frustrating because there's a couple of projects I've been approached about recently
that would utilize that capability quite beautifully.
But yeah, we must wait.
Who would have thought that GPU access would end up slowing a lot of this stuff down versus
the scramble for regulation if indeed, I mean, this is just one data point, but if indeed
that is proving a major bottleneck, that's quite interesting.
The other thing that we're seeing in the world of open source is people finding clever ways
to make these large language models be able to produce high quality outputs, but without
anywhere near the amount of compute power required, smaller models, fewer parameters
and all those types of things.
So I think it goes to show that there is a number of pressures to try, well, we talked
about water use last week, but costs and all these other factors to actually try and figure
out how to get these models, these tools that we're using to operate without quite so much
compute power required.
So I think we'll see that as well.
Yeah, and attached to that compute power kind of restriction at the moment is also something
that was teased or spoke about when GPT-4 was launched, which was the context window.
So GPT-4 was announced and it had an 8K context window and a 32K context window, but the rollout
of the 32K context via the API has been incredibly slow.
I don't know anyone actually that has got access to that, but they are saying that higher
context windows, as high as 1 million tokens, we've spoken at length on this podcast in
recent weeks about Anthropix 100K context window in Claude, a million tokens, that's
750,000 words.
Only 1 million token context windows are plausible in the near future.
That makes me salivate, but also makes me realise that you would absolutely burn through
cash using that API.
Well, yeah, unless they can get it down.
One of the things in this article that they mentioned that Sam focused on is a cheaper
and faster GPT-4 is more important to them right now than say GPT-5 to try and drive
the cost of these things down so that certainly in terms of API use, they keep the price down
because as you mentioned, 1 million tokens would burn cash.
You'd have to charge quite a lot to offer that as a service.
We were speaking off air, what could you do with a million tokens?
We were like, oh, you could throw the text of 10 marketing books in and from there, ask
it what do these books agree about?
What do they disagree about?
What are the key contention points?
What are the key discussion points?
Imagine doing that with religious text, crumbs, that would be an interesting one, right?
Although probably, I don't know, maybe a lot of religious texts might really stretch the
context window a bit but I think there's a lot of interesting stuff that could come out
the back of that.
Yeah, massively.
I mean, like I say, it gets my juices going.
Yeah, that'd be cool.
I think some other things that Sam talked about that they were aiming for for this year
is what's called in this article a stateful API.
In other words, when you call the API today, you have to keep passing through the same
conversation history and pay for those tokens and in the future, they're hoping for a version
of the API that remembers the conversation history.
These are all things that will just make it easier for people to build tools on top of
it that make for a much more natural conversation style where you can sort of say to whatever
tool you're using, hey, you remember that thing we were talking about last week?
And it'll go, yeah, yeah, do you mean this thing?
Well, yeah, yeah, cool.
I want to go back to that without having to like scroll through a load of chat histories
and obviously ideally connect those chat histories together, I guess.
When you look at the expense of GPT-4 in terms of the cost per token, I think a thousand
tokens is like three cents as an input prompt and six cents on the output.
That's really expensive compared to what we've seen on GPT-3 and 3.5.
So bringing those costs down, if you imagine that chat window, if you've got a long conversation
and every time you called the API, you're pushing all of that through, it does soon
start to rack up.
So I can see why that's going to be a priority for them.
Yeah, I'd agree.
I think the last thing we'll pull from this article that we found interesting, Martin,
was the concept of plugins within ChatGPT not having product market fit yet.
So the article says that the usage of plugins other than browsing doesn't have product market
fit yet.
And he suggested that a lot of people thought they wanted their apps to be inside ChatGPT,
but what they really wanted was ChatGPT inside their apps.
And when you think about how people are using a lot of apps at the moment, that makes sense.
It's almost like ChatGPT is an enabling technology inside of you trying to do something else.
Right?
Even just the HubSpot platform that you talked about at the beginning of this episode was
around a goal.
Like I want to write a landing page, I want to write an email, I want to interrogate my
database of contacts to know who lives in the Cambridge area because I'm going out and
about and I want to go meet with some of them.
That context is key.
And so I think this fits in with some of our experience, this somewhat frustrating experience
is trying to use the plugin library because some of them don't really work very well or
have very specific use cases and other of these types of things.
So it's not necessarily a surprise to hear Sam Altman say that, but I think maybe it
shows you that the whole OpenAI is going to dominate the world by having like the app
marketplace for ChatGPT apps maybe is not the way it's going to go.
Yeah, I'm not sold on the plugins yet.
I haven't found a killer app.
I think the browsing plugin is kind of slow.
Ask your PDF one is pretty good.
And I think there's a video insights one, which does a pretty decent job of pulling
out some insights from YouTube videos and whatnot.
But for the most part, there's actually quite a lot of trash.
I'd agree.
I think the best ones, not entirely, but some of the best ones for me are the ones that
they were really good tools before you could just easily access them in ChatGPT.
So we've featured Ask My PDF on one of the early episodes of the podcast.
That's a pretty cool tool.
And what this just means is I don't have to go to that tool.
I can just access it directly within ChatGPT.
I think there's some cool things you can probably do with Zapier, but sometimes it's maybe just
easier to just copy paste stuff yourself.
Right?
So you can ask ChatGPT to write an email for you based on a brief, and then you can push
it through Zapier into Gmail, or you just copy paste it, right?
Which is pretty fast and easy.
So I'm not super surprised to hear this because I think it fits with our experience, doesn't
it?
Yeah, absolutely.
And the Zapier one is a good example, actually, because I really like the Zapier integration
when I'm doing it through Zapier, not when I'm doing it through ChatGPT.
Yeah.
So I'm usually building multi-step processes in Zapier, and that's where the power is.
I'm like, get this piece of data from here and here, interpret it like this, push it
here, and then do that, which is, at least as I understand it, from my tests beyond the
scope of ChatGPT.
Although I'm sure there's some pretty cool stuff that I haven't been able to do with
it.
Right.
We're going to move on in the interest of time, Martin.
We're going to move on to our last story today, which is a research paper that came out this
week.
We'll only touch on this briefly, where OpenAI had trained a model using human reinforcement-based
learning, but rather than training it by feeding back when it got the right outcome, they actually
molded how it worked based on the reasoning that it took.
So here's a quote from the OpenAI website.
We've trained a model to achieve a new state of the art in mathematical problem solving
by rewarding each correct step of reasoning, process supervision, instead of simply rewarding
the correct final answer, outcome supervision.
In addition to boosting performance relative to outcome supervision, process supervision
also has an important alignment benefit.
It directly trains the model to produce a chain of thought that is endorsed by humans.
I saw this story and we're enthusiasts, we're not machine learning experts, but a lot of
the problems that come up in some of the discussions that we've had over time is, well, ChatGPT
and large language models, they don't think, they just get to an outcome, but in a very
different way from how humans do because it's all based on complex neural architecture,
based on probability matrices and determination parameters and all these other things, and
they don't, in inverted commas, think like us.
But this sounds to me like they're trying to help the models think like us.
They're trying to teach them logical reasoning and things like that, which I can imagine
would be really beneficial in some instances in terms of getting better outcomes, but also,
we've also talked about OpenAI and other large language model developers and providers can't
often describe or explain how the tool got the results.
But that might be easier if you've actually trained things for things to think in a certain
way or to process information in a certain way.
So I just thought that was a cool paper.
Any thoughts on this, Martin?
Yeah, well, chain of thought prompting has been shown to improve outputs for a while
now.
And I think it's really interesting that they're doubling down on the reinforcement learning
of that.
So to improve that as a methodology for coming up with outputs as well.
So yeah, I saw this, they were big on it, OpenAI published it, and Greg Bruckman was
tweeting all about it.
And like you say, this is kind of beyond our area of expertise in terms of machine learning
development.
But yeah, cool to see them doing reinforcement learning in different domains or different
areas.
Absolutely.
And I think as a marketer, if there are particular use cases that these tools are not good at
or untrustworthy in, this might help to see some improvements in terms of improving their
logical reasoning, rather than just potentially regurgitating a remix of information that is
in the training data that helped train the weights in the model to produce a specific
output.
Just as a general note as well, listeners, if they haven't tried chain of thought prompting,
add that into the prompt.
So ask it, if you're asking it to kind of do some planning or come up with a strategy
or do a piece of maths, try saying to it, show your working and show the steps to get
to the output and it will improve the response that you get.
Interesting.
Thanks for sharing that, Martin.
I'm going to have a little play with that.
Right.
Last but not least, let's look at our tool of the week.
It's a quickie because we've not dug into using it too much, but it's been a question
that I've been asked a number of times recently and so it might just be worth flagging in
case people want to go and play with it.
So the tool itself is called recraft.ai and it's another image generation tool, but it's
an image generation tool with a difference.
And the reason it's different is because it produces vector-based images.
So far, when you're using stable diffusion-based models, you get gorgeous images, but they
are JPEGs, PNGs.
They are like your photographs that you would take.
As such, they are limited in terms of their resolution and a number of other factors.
You can't easily change color of specific elements and all those good bits.
What you really want, if you want to be able to scale images infinitely or to be able to
easily change colors and move bits of images around, is to have them as vectors.
And for most marketers, their exposure to vectors is mostly going to be things like
logos, icons, some sort of fairly simplistic, I would have thought compared to photographs,
graphics.
And what recraft.ai allows you to do is it allows you to provide a natural language prompt
like you would for mid-journey or any other similar tool.
But what you can do is produce vectors like icons, colored icons, just like text-based
outlines.
You can ask it to do all of the things that you would imagine, like I was playing with
it trying to create different icons that you might use on a website.
And once it produces them, you can actually go in and edit bits of that vector.
So you can change the colors and things like that, which was pretty cool.
When I tried to get creative and I really tried to get outside of what would be a standard
icon, it did struggle.
So for example, I asked it, six people holding hands in a circle icon to form the shape of
a light bulb.
And it just had no chance.
It did not do well at all, but it did try.
And so I think that for those people who had been trying to get those icon style outputs,
this might be a tool to play with and go and give a try to.
Yeah, I'll definitely check that one out.
It's also one that we're expecting to see as a piece of functionality in Firefly.
If you look at Firefly coming soon, it's one of the tools there, text to vector.
Yeah, because when we were having a play with Firefly, you could do some cool stuff with
their vector tool in the beta, but it was kind of limited.
And I do think when they roll that out into Photoshop, I'm expecting we'll see a huge
amount of extra power, because when you can actually edit those vectors in Adobe Illustrator
and do some of the things I'm talking about here, I think it will be cool.
So if I was going to be brutally honest, I'd say Recraft AI is free at the moment.
You can just create a login and go and have a play with it.
Maybe get some of the stuff that you want.
When this comes to Adobe Suite and you can do this in Illustrator, I think it's probably
going to fit most people's workflows a bit better.
Yeah, that sounds like a fair shout.
But definitely worth a play.
And I was impressed at how easy to use it is.
When you ask for your icon, it's a little bit like Mid Journey.
It gives you four or five options and then you can recraft, which is basically, I didn't
like the ones I got, go and have another go.
And yeah, I think certainly for graphic designers, I'd be having a play and see if it can speed
up your workflow.
And for small marketing teams, solo marketers that want to see if they can just produce
some novel icons quickly without having to go out to a designer, maybe it will help you
get some of the way that you need to go.
I haven't played with it enough to say how reliable the output is, but I think it's worth
having a play with.
Right, I think we'll leave it there, shall we, Martin, for another week?
Yeah, I think so.
I can just leave now and go and be sad about the series succession having come to an end.
I've been really enjoying that in recent weeks, but I have to find something new to watch
now.
Do you know, if it's not Derby County bringing you down now as its succession, have you seen
For All Mankind on the Apple TVs?
I have not.
I didn't think I was going to like it.
This is not what this podcast is about, apologies everyone, but it's an alternate history as
if the Russians got to the moon first and the space race that kicked off.
So it starts off at a point in time that's the same, if you like, as our history and
then it quickly diverges and then goes through time.
I'm only like six episodes in, but it's been really fascinating.
That's worth having a little look at.
And what's that called?
It's called For All Mankind, I think.
For All Mankind.
Cool, I'll check it out.
Right then, thanks always, Martin, for your time.
Always lovely and I will catch you next week.
Yeah, see you next week.
Thanks for listening, everyone.
Follow us, aim marketing pod on Twitter and head to the website artificiallyintelligentmarketing.com
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Yeah, that about sums it up for me.
Right, have a lovely weekend, everyone.
Cheers, bye.
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