Welcome to Artificially Intelligent Marketing, a weekly podcast where we stay on top of the
latest trends, tips and tools in the world of marketing AI, helping you get the best
results from your marketing efforts. Now let's join our hosts, Paul Avery and Martin Broadhurst.
Hello everyone, welcome to Artificially Intelligent Marketing, a podcast for marketers looking
to use AI to help them be more efficient, more effective as marketers really. I'm joined
today by my very good friend Martin. Martin, how are you?
I'm very well, just trying to keep my head above water with all of the AI news going
on in the world at the moment. I feel like I am drowning in it.
I think we broke WhatsApp this week, or at least you broke my fingers trying to reply
to your WhatsApps. Yeah, crazy deluge. Some of the stories that we're going to be featuring
today were released a handful of hours ago, and it feels like at this point you'd need
to do a new podcast episode every day to try and keep up with all of these bits and pieces.
But you've had a good week overall.
Yeah, definitely. Excited for tomorrow actually. I'm doing my first AI marketing presentation
seminar, call it what you will, conference, first one of 2023. So I'm looking forward
to that. That's at Thrive Park in Derby, a digital marketing conference and expo.
Yeah, looking forward to it. Good stuff. Sounds exciting. First for me this week as well,
not work related, I took my little puppy to puppy training for the first time today. Little
Pippin was learning to sit and down and stand and recall and mostly did a real good job.
He's a whippet, so he's a little bit scared of all the other dogs at the moment, but he's
very, very sweet and it was lots and lots of fun.
So Pippin, lovely name as well.
Pippin, he's had four or five names during his life, none of which he responded to. He
was like, I'm not interested in that. Pippin, he's quite happy with. I love the Lord of
the Rings, so I'm quite happy to go down that route. And Scotty Pippin was one of my favourite
basketball players from back in the day when I was young. So it all just fit together.
Right, let's get through this inane-ness and into the stuff that all of you lovely people
are here to hear about. Let's talk about what's been happening in the world of marketing and
AI and this week we got a lot.
As you can see, GPT-4, as predicted last week, did come out. It came out even earlier than
we thought it was going to. And so we've got some great info to go into on that.
As well as that, Google provided an announcement of what they are planning to do by baking
AI into all of their work-based tools. And then Microsoft as well coming in with Copilot
a few hours ago. So we're going to go into those. We're also going to talk about a couple
of tools we've been playing with. One called DID, which is quite fun and maybe could show
the future of website chat. We'll look at that later. And then of course we'll have
our tool of the week, which we're going to not tell you what it is until we get to it
because we're that excited to show you some of the stuff that we've been playing with.
So let's go into story one. GPT-4, it's alive. It's alive.
Right. You've been playing, Martin. Tell us, tell us, tell everyone what's going on first.
Why, why GPT-4, 3, 3, 4, 5, track GPT? Tell us what GPT-4 is.
The latest iteration of the general processing transformer, large language model of open
AI. Have I got GPT? Have I got the words right there? I don't know. Anyway, it's the new
iteration of the engine really that powers the interfaces like chat GPT. So GPT-4 widely
anticipated. People have been talking about the number of parameters, basically how powerful
it is going from 175 billion to a trillion, a hundred trillion. And it's come out now
and open AI. I haven't told us how big it is. So that was a really interesting observation
when they announced it straight off the bat. It was a very different tone in their announcement.
It was much more, we've done this cool thing and this is what we've done to it and this
is what it can do, but we're not going to tell you how we've done it.
No secrets, no secrets revealed. And there's been a little bit of angst on the Twitter
spheres about that. Yeah. Open AI not being quite as open perhaps as they used to be.
Really not. It's like Google's don't be evil motto. All of a sudden, they just pivot away
from that. Previously we were an open AI research company. We're going to share. We want artificial
general intelligence. And then all of a sudden, oh, actually no, sorry. We're going to be
a profit based company, but we're going to put a profit cap on it. It's a hundred times.
So if we invest a billion, can we make a hundred billion?
That's it. But we're just going to cap it there.
Just that's it. That's enough. We know our limits.
Just the GDP of a small country. We just cap it there though. And then we'll go buy a country.
It's all good.
We use AI to take over. And I think actually that's something that they could probably
do. GPT-4 is pretty powerful. It's quite impressive. The announcement, one of the first things
that they said is that it's multimodal. So we discussed this last week. What does that
actually mean? Is it going to input? Are you going to be able to input video and text and
it output video and text? Well, it's, it's an input multimodal. Input multimodal. You
can use this for you to say. You can input images along with the text based prompt. And
what's incredibly powerful about this is that it has some incredible capabilities to understand
those images that you put in. The outputs are all text based. So there's still no integration
with the likes of Dali or any video capabilities or anything like that. Sure. That will come
in GPT-5 or something like that. But for now, text based. And that's really quite powerful.
Some great examples. I'm sure you've seen a few of them. The chicken nugget tray was
a brilliant one.
Didn't you see that? Tell us that. I didn't see that.
So the chicken nugget tray was a baking tray with chicken nuggets laid out in a kind of
map of the world. Chicken nuggets, you've got the making of North America and South
America and Antarctica and all the rest of it. And it's asked to explain why this, basically
explain this mean photo. And it does. It explains it and says, this is funny because it's, oh,
I think the mean picture across the top said the beauty of Earth from space. Looking at
the magnificent sense of Earth from space. But it explains it in really great detail.
It says, you know, it sets you at the bottom of the, in the description, it says, it sets
you up thinking that it's going to be this great, profound, beautiful image. And actually
it's just something mundane and chicken nuggets. So it knows, it gets context. It has much
more relevancy and an appreciation of the world. Another example, a photo of someone
holding balloons on helium and helium filled balloons on string. And the prompt said, what
would happen if the string was cut? And it said the balloons would fly away.
So not just able to interpret accurately what the image is, but also to bring logic into
inferring next stages in a story, for example. That's quite impressive. I think my favourite
was the one, there's been riffing on this, but my favourite was probably the one that
was in the demo, the development demo that was shown on YouTube shortly after the news,
where the person presenting had drawn a sketch for a simple website. They wanted to build
a joke website, took a picture of the sketch, fed it into GPT for, and said, give me the
code that I would need to actually code this website. GPT spits out the HTML. You render
the HTML and you get this website with this joke website and even has clickable buttons
to reveal, you know, JavaScript clickable buttons to reveal the punchlines to the jokes.
The hand drawn script, I mean, it was better than I could do, but it wasn't great, right?
And somehow it was the people talk about low fidelity wireframes. It was the lowest of low
fidelity wireframes. It was a box with, so in the text, you could barely, the text was
barely legible. It had, what I thought was really impressive as well actually was, hint,
text, the text that he'd written, he put in brackets where that was kind of placeholder
text and he had understood that was placeholder text and inserted it and replaced it with
real text. It was, yeah, that was...
Assuming that's all real, right? And it's not been manufactured. That was pretty cool,
right?
Yeah, totally. That was like all of a sudden you went, holy, holy cow, that is quite something.
So what else does it have? It's multimodal. It can, it has this enhanced reasoning that
like we said a moment ago with the example with the balloons. If you can actually access
this model through ChatGPT plus at the moment. So I've been playing around with it and it's
quite interesting the kind of subtleties, because it's also billed as being more concise
and having played with it quite a bit, it will output quite a lot, but it is more concise.
It gets to the point in each section. So if you ask it to write a blog, it's less, and
not that GPT-3 was particularly waffly, but the writing's tighter. Yeah, it's more succinct,
it's more to the point. It's more on point as well actually. I think it's, yeah, it's
really quite surprising that. They talk about it having improved safety and alignment, but
don't really go much more in into how that is. And that's a point of contention for some
people. Again, private company, why do they get to set the rules on what is allowed? What
is harmful content? What is not harmful content? I'm sure that will all come out of the wash
now in the wash over the next few months, then years as more people get involved in
that discourse. I'm not too concerned personally there. I think OpenAI tended to be quite,
responsible in the way that they've put the models out there and they've been quite quick
to adapt. I think we saw that with ChatGPT when it was released. But one of the most
interesting elements of this, other than the multimodal, for me is the longer input text.
We've taken it from being able to handle with ChatGPT about 3000 words, and it's suddenly
gone up to 25,000. So the amount of data you can add into a prompt has just shot through
the roof. It's really quite significant. And that opens up the doors for much more, in
terms of practical applications as marketers or content marketers, you have being able
to take transcripts of podcasts like ours and just stick them in and get your show summaries
done in a click. You're not having to break it up into smaller pieces. If you're doing
research that is going to enable you to put whole documents in there and find key takeaways.
There's a myriad of use cases for this, but I think that one is really, really quite exciting.
Yeah, I'd agree. I've been having quite a play as well. I got a really good book outline
out of it. I'm not going to share what the book's about because I actually think I might
see if I can produce it really quickly as an example and maybe talk about it next week's
podcast or the podcast after. But I gave it a really challenging book concept, without
giving too much away, based on things like the hero's journey. And it did a really, really
good job of taking something super abstract and somehow squeezing that into a hero's journey
character arc, which I was really impressed about. I started to get it to write it. And
by chapter four, it had kind of forgotten what it had written about in chapter one.
So it knew the characters still, but it wasn't consistent with some of the things that had
happened to the character in chapter one. And the chapters, I call them chapters, they
were like 800 words max, right? Like this was not a book. So I think the strategy you'd
have to go through and I saw someone, I can't remember who it was, had written a whole book
of 250 pages and it required 2000 prompts. And that doesn't surprise me because I think
if you really want to produce that type of long form content and have it be coherent,
you're almost, say you want to produce a book chapter, you're really iteratively prompting
every section. And maybe even, I think, giving it, either it should remember giving it a
bit of context for each section or for each chapter so it doesn't forget what it's supposed
to be writing about. But I was pretty impressed compared to when I ran the same test with
GPT-3, like GPT-3's, ChatGPT, the original version, the book concept didn't work. It
just couldn't interpret what I meant. I also really loved, and I thought was a great demonstration,
Paul Reutzer from the Marketing AI Institute showed a post on LinkedIn where he asked GPT-3
driven ChatGPT or GPT-3.5 to give him an out of office, a creative out of office, like a
humorous out of office. And then he asked GPT-4 to do it and the difference is night
and day. And I found this myself even when prompting ChatGPT to be like really creative.
I had it right in social media posts where the prompt was, be so creative and persuasive
you offend me. Like I was asking you to be provocative. I wanted it to say things like,
you're a shit marketer and you don't know what you're doing. And if you don't read this
blog post, your career will be over forever. And I could never get it to get anywhere near
that provocative or creative. But this, and I should say Paul Reutzer is not angry and
aggressive, but it is a great example of the difference because whether you like the output
from GPT-4 or not, it is incredibly creative. It's like, hi Earthlings, I'm away speaking
with robots at AI conferences. Like it is really, really, really creative, which I just
couldn't get out of GPT-3. So yeah, as content marketers, this is a massive upgrade, I think
for a variety of different reasons in terms of its reasoning ability. It's almost like
knowledge of topics and ability to speak about them. The fact it's more concise, the fact
that it really understands the prompts that you give it better than the old model did.
So much cool stuff there. If you're a marketer or you work in content marketing and you've
played with chat GPT, you need to play with chat GPT-4 because I think you will see a
big difference. And if you're a content marketer and you haven't played with either yet, you're
going to be obsolete pretty quick if you don't start to learn how to manipulate these tools
to get a decent first draft out. Don't get me wrong, I still think heavy editing is required.
I still think if you want things with genuine novel insight, you as the human have to bring
the insight to the party. But yes, these things are getting crazy powerful very quickly.
And that's coming through in the benchmarks that they're showing. The capabilities of
chat GPT or GPT-3.5, I think it could, in terms of one of the big domain areas was law. And in
America, passing the bar is the kind of big example. Everyone's just passing the bar. Can
it pass the bar? And I believe chat GPT or GPT-3 had about a 10% pass rate.
I think it was able to, against humans, it was in the bottom 10% of scores.
Oh, she was right. Yeah, I wasn't sure of the... Whereas this is now in the top 90%.
Yeah, it's scores in the top 90%.
Which is, you know, that's quite incredible. And it doesn't say so many domains as well.
I saw some in the life sciences. One of the examples that somebody put on Twitter was about,
we were talking about bio GPT in last week's episode, talking about the drug discovery
capabilities or the drug interaction capabilities of GPT-4 that people have been playing with. I was
like, wow, that's, you know, it's not trained on this, but it's capable of doing it. Well done.
Yeah. I mean, it must be sucking that out of some training material somewhere. I think the exam
thing is interesting. And I honestly haven't probed how they do it deep enough to say,
but one criticism would be training something to take a specific test is potentially quite easy.
Right. Even humans know how to gain certain tests to get a good mark in, you know, for some tests.
Right. So in some areas, I'm not super surprised, but it was the massive jump for some of the,
like you were saying, like for the bar exam, GPT-3 sucked at some, like it was at 0% for a
couple of the tests. And if you look out there, lovely listeners, you'll find there's a bar chart
floating around the interwebs that shows, I don't know, 20 odd tests where GPT-3 scores,
where GPT-4 scores. And it really is those ones where GPT-3 sucked, but GPT-4 is like way better
than most humans, not just better than GPT-3. I actually had an issue this week, a consumer
rights issue, shall we say. And I thought, I don't know how to tackle this one. And I just thought,
you know what, I'm going to throw it into GPT-4 and see what it says. And I kind of set it with
that you are an expert in UK consumer law with domain expertise in this particular area.
And I kind of explained the situation, bullet pointed key points, tried to keep it as
fact-based as possible and ask it to give me advice and then write a letter to the company
that I was engaging with and then provide me with kind of next steps strategy. That was fascinating.
First off, the letter that it wrote, it had the address of the company on the letter. I told it
the name of the company and that it was in Derby and it put the company's full address, their real
address on there. So that's a thing that it can do. Because it can't access the internet still,
right? No, but it's obviously got within its corpus of training data, lots of business directories
and things like that. So it'd be worth sticking Biosrata in and seeing. I'm about to ask it
what the address is. Yeah. And then, so in the strategy actually, in the kind of like,
what should I do? It gave six potential kind of next steps, but in each one, it gave like how
likely that is to get me the resolution that I was after. So it was said, you know, there's this
breach of contract, there's miss selling, you could raise a complaint with the FCA, you could
do this, you could do that. But it gave a detailed kind of explanation. The last one, for instance,
it said, you could take legal action through a legal professional, but this could get expensive
and so on. I think that was a really obvious kind of answer. But the ones earlier were quite
specific and nuanced, I would say. I guess your only danger there is we know that
Chachi Bti can churn out absolute junk that's completely incorrect. So I can imagine a use case
for this. The danger for you as a consumer is you still need someone with a legal background to
check that and make sure it's not nonsense, I guess. But at least it arms you with the right
things to go speak to about with an expert. Yeah, 100%. And again, it's always that kind of
human in the loop element to it. What I would say is that I did check some of the details,
because I thought, is that right? And it gave reference to Consumer Rights Act 2015 and pulled
out relevant sections of it. And that was quite powerful. And what it gave me was, I would say,
a starting point, a far better jumping off point that I would have got doing my own research.
They saved me a hell of a lot of time. And potentially, I can imagine a scenario where
I go to a solicitor and say, you know, this is my current situation, this is my understanding of it.
And you save yourself a £600 bill just by not having to spend the first hour explaining everything.
Yeah, agreed. Pretty cool. Right. I think we've probably whacked Lirico enough on GPT-4 scene as
we've got a ton more of other stuff to give. Let's talk about Copilot, which came out a handful of
hours ago. So take us through it, Martin, why it's important for marketers. Well, the productivity
suite that we all use, we all know, we all love, we used to have Clippy in Microsoft Word, but now
we have Copilot. And Copilot definitely feels like Clippy on steroids. Clippy has evolved,
taken new form and is now making our lives much easier. Before we get into the detail of it,
I just want to say one thing. In the promotional video, there was a two minute promotional video,
and then there was the longer kind of keynote session. In that session, Jared Spataro,
the corporate vice president, modern work and business applications at Microsoft,
he said at one point, at best work not only feeds our families, it feeds our souls.
And at that point I felt what I thought was my soul leaving my body. It was a little bit of vomit
in my mouth. I just, I can see he's doing it to you now, just remembering the event.
So I couldn't, I couldn't hack it. I said, no, don't say that. That's awful. Anyway, enough of
the cringe. Copilot looks pretty cool. Yeah. So they've baked GPT-4 and large language. It looks
like they might be introducing, I'm guessing some of their own as well. I'm not sure. I've not read
that they have done specifically, but I wouldn't be surprised. Well, this is off the presses as
well. So we'll probably learn more in the next couple of days. Yeah. This came out literally
six, five, five, six hours ago. So trying to get ahead around it all very quickly.
It's baked into the whole ecosystem. So Word, Outlook, Excel, all of it has it baked into it.
And what's interesting is it all works together. I thought the presentation that they did was
incredibly powerful. So in short, they'd say that it works with all of the apps. It turns natural
language prompts into productivity actions, unleashes creativity, unlocks productivity,
and up-level skills. So what can it do? Well, it generates content, automate tasks, and provides
relevant data and insights. It's enterprise ready as well. So they say that it protects the tenant,
the group, and the individual data. So it's very secure. It's designed to be rolled out at enterprise
level. There's not going to be any data leakage. It's all contained within your instance, within
your license. So this is clear, because people have been super worried in larger companies about
putting things into chat GPT. Like let's say I want some help editing a press release for an
upcoming product that's going to change the world. Well, clearly that's important commercially
sensitive news. I can't copy and paste the press release into chat GPT. I don't know where that's
going or who's seeing that. So incredible sensitivity and risk aversion for larger companies.
I've heard stories of chat GPT has even been blocked in a lot of companies because they're
like, we don't know where the data goes. We don't know who can see the information. None of you are
allowed to use it. So the fact that then Microsoft can do this within their privacy frameworks that
they're ideally, and I guess would have to be held accountable to, frameworks that probably most of
us were already signed up to even in large enterprise should open the door for those companies that
didn't feel comfortable having their employees use tools where they didn't know where their data was
going. I guess the only thing would be, you know, you use a Jasper or a copy.ai or a writer, which
all rely on open AI. Microsoft also relies on open AI. So yes, there's all these privacy things in
place, but where does the data really go? Are they still going to use it to train further models and
all this stuff? Well, Microsoft actually have access to the code, don't they? They have the
model themselves. Nobody else has access to that's their $10 billion deal. Right. Everyone else can
access it through the API. Microsoft has the thing itself. So it's enclosed. Right. I didn't realize
that. That helps answer that question. Thank you, Mark. I'm glad you're here. Of my pleasure.
Come back anytime. So what else do they talk about? It's integrated into all of the apps in a way
that gives this consistent user experience. And they've said that it's built on responsibility
with AI principles and ethical AI standards kind of at the heart of it, which you would expect them
to say. It does look smart. I thought the demo was great. You also saw the same demo as me. There's
a particular example halfway through the presentation where they take you through
the process, your graduation of the presenter's daughter. She's graduating and it takes you
through sending the invites through to the creation of the presentation that you would
have playing at the party with embarrassing photos and all of that kind of thing. I thought that was
incredibly powerful. I need to stop saying incredibly. That's just how I feel about it at
the moment. What was quite smart was in the chat conversation, it understood the context. So you
could say, send the email invite for daughter's 16th birthday party to family and friends. And
it would draft the email invite, but taking in context from other emails like the venue booking
confirmation email. So it would integrate the party time and date and location into the
message. That is so cool. And they give a business example as well, didn't they, where you're
emailing a colleague and assuming you've got all of your documents on your SharePoint, you can
associate a document with that email, but have Copilot automatically pull the context from that
document to fill the email. So it might be that you need to send over the actions from a call,
but that's easily pulled from the transcription in Teams. It's already been done in the
Teams. It's already been saved. And by the way, if you need to flag to them that they should go and
have a look at the PowerPoint decks, describing the value proposition of the new product,
oh, please Copilot, can you pull out the benefits features and proof points out of the deck and
just add them as bullets in the email? Yeah, cool. No problem. It goes into the deck, knows
semantically what important bits it should pull out, pops them in the email as well.
Like it's kind of mad when you think about the sheer range of possibilities for how much faster
you can do things. One of the points that there's a nice little quote I thought that describes
my experience of using PowerPoint. And the presenter, she said, the average user uses 10%
of PowerPoint. Copilot unlocks the other 90%. And I thought, yes, it's the same with all of
them work for a soft suite. There's so much power in it, but I just scratched the surface of it.
And this is the same with nearly everybody that I know. Just, it can do so much, but you just do
the same thing time and again. The presentation example where it pulled in images automatically
from a folder and then created the deck and you edit the text, that it automatically created
a few tweaks and it would make its auto. And it looked beautiful. Let's be honest. It didn't
even look like a junk presentation. Whatever template it pulled from, I don't know if it uses
branded templates on your SharePoint or if they're built into PowerPoint already, but it looked
mustard. It did with, with animations that didn't look cheesy with transitions that didn't look
cheesy. It looked modern contemporary. It looked smart. How much time in agencies and marketing
departments and design departments, how much time is spent putting together the PowerPoint?
I'm working on a deck, right? The content's there. The content's there in somebody's head
in other documents, in other areas, there was meeting notes, there's this, that, the other.
Someone has to go and sit and create that deck. People will spend hours pulling a deck together.
If that can now be done in minutes, you know, relative, relatively speaking, you know,
10, 15 minutes rather than three hours or something, that's a huge time table. It's an instance.
Yeah. In the life science industry, we, because we deal with such technical and complex subject
matter and the products that we're talking about, showing the applications of talking about the
benefits features applications and all that good stuff. It's usually very complicated. And the
subject matter experts are usually working with the PhD scientists, very detail oriented people
who can, who love the wizardry of the technology that they've built or that they're using and go
into a great amount of detail. It'll be like I'm doing now. Can you tell my next scientists as well?
Because of that, their PowerPoints can massively suffer, right? Like 52 bullets on a page,
basically inviting people to read full prose on slides. But now if there's, it's almost like
there's a magic button that you can press that's going to distill all that key information into
something that's going to be much more digestible for people to, you know, to,
to be presenting, they will focus on you, the presenter.
Exactly. But that, that, as you said rightly is at the moment, you know, the domain of the
marketing department, the domain of the agency, there is absolutely a number of important skills
required to go from dense technical output. Because to be honest, there's, there's reasons
the subject matter experts think and act like that. It's because the majority of their job requires
them to be like that. Right? On the, on the few occasions they have to create a PowerPoint,
this is what you get. And you know, they're not, most subject matter experts don't create enough
PowerPoints to even warrant spending an hours and hours and hours of training to try and be a good
graphic designer or content summarizer or value proposition created. It's just not a good use of
their time, but that used to be the marketing department. And now is it potentially a button?
Who knows? I think until we get to play with it and really see how good it is at extracting key
information and associating appropriate visuals and all that stuff, we have to wait and see,
but it's certainly a step in that direction. Yeah. Huge potential that I did like during the
presentation. They were very heavy on, this is a starting point is that it's designed to give you
a starting point. This is about augmenting human work and not replacing human work.
They were very big on that. And I think that really comes across in the way that the UI of the tool
is as well. Well, still very much in control. This is not, you know, going to replace you,
but it's going to allow you to get stuff on a page quicker. Yeah, I agree. Co-pilot's a good name.
Member of our team, Tom, very smart guy. We, when we started talking about AI and supporting tools,
you know, back when we began testing them, he said, we're going to all have to become very
good pilots. And I just really thought that was a great way of phrasing it because you look at a
modern plane, it can do a lot of things automatically, but there's so many edge case scenarios where you
need the human in the loop. And I don't even think the AIs that we're going to be using for a lot of
these creative use cases are anywhere near as good as the automation in aeroplanes, to be honest,
because I think there's way more edge cases in real life and across all these complex domains that
the AIs are trying to help us with, at least in the marketing industry. So co-pilot is a good word
because we are the pilot and we can get help and we could be more efficient, more effective.
I think, again, it would be great for getting things going. And in the example that you described
in that Microsoft presentation, the raw text that's put in that PowerPoint, the lady who
presents, I can't remember her name, she edits it, right? It's not in her voice. She's like, no,
I wouldn't say that like that. So she edits it. And that's exactly how I expect it to be for some
time, if not forever, because at least at the moment, they don't know what's in our heads,
right? Although if our story from last week where you're an MRI and everything is what you see,
and maybe not so, but yeah, co-pilot is a good name. I think that's how we should all be looking
at it for sure. And I can't wait to get my hands on it. So on that note, Google announced their
own generative AI being baked into Google workspace. But the way that I've just described it to you
is Google has announced his own generative AI in the workspace. I haven't said Google copilot
or whatever. Have they missed a trick? 100%. Trying to get your head around exactly what
Google's product AI infusion is going to look like is hard because from the news announcements,
they don't go into any detail. And Microsoft are way ahead. I think this is Google's attempt to go,
we've got one. We're going to do it. We better tell you so that you think we're still cool.
And holy moly, right team, we need to do it on the same day that GPT-4 is announced and we're
going to launch it a few hours early. Quick, get that two minute promo video done.
You make a massively good point because I was talking about this with some of the team today
after copilot was announced. You can't as an enterprise not access the power of this.
Like if you're on Google apps, if Google don't give you this within three months of Microsoft
bringing it out, even if you've got a two or three year subscription to Google still going,
it's worth binning that off and just transitioning everything over to Microsoft because the sheer
time savings and efficiencies and productivity gains you'll get from having AI embedded into all
your tools and connected to all your data. So Google are now, you know, there's a fair amount
of, you know, there's a fuse burning, mission impossible style, bum, bum, bum, bum, right?
And it is getting quite close to the bit where everything goes boom and they really,
really need to get to the party quickly. They do. And it does look like their promo
video addresses much of the similar things that we've talked about. In fact, on the,
on the example that they give, they have AI baked into the Gmail system. You've come to a threaded
email conversation, laid lots of emails in that thread. It then summarises that thread for you.
It turns the summary into a campaign brief. It's all about marketing campaign. It turns it into
a campaign brief in a Google doc, turns the campaign brief into a slide deck in Google slides.
And it's that, you know, look how smooth this whole process is. But all you see is that that
two minute video, the equivalent of the one that, but it didn't get, it didn't get me excited.
And it, and it lacked the polish and it didn't, it didn't have this feel of something
transformational was coming. Now you and I nerd out about this a lot and have done for a long time,
but I thought Microsoft approach really got people excited. And as much as it was a feeds our families
and feeds our souls a little bit cringe worthy at time. And these things made an event of it.
They tried to make it more exciting. So yeah, Google, you need to start exciting us. Yeah,
very much so. Right. We, this is going to be one of our longer episodes, but there's been loads of
good stuff to talk about. Let's look at a couple of quick things. Just that we saw this week and
we didn't want to make it all enterprise level baked in AI tools. Did we mind? So very quickly,
we were playing with a couple of tools. Let's talk about a depth first. There was a,
a company that got $350 million in funding this week called a depth that is a generative AI that
takes natural language input and turns it into action. So this is a bit different from what we've
been talking about so far. It's almost like it is being designed to be able to operate all the tools
you already use for you. So that when you ask things of it in natural language, it can go do
them. So some of the examples that are given on the website are things like, set a reminder for me
to email this person, find me a refrigerator for under a thousand dollars, add a new column to this
spreadsheet show in this, add this person to Salesforce and give me a reminder to follow up
with them with the presentation. So in essence, multimodal, but in a different sense, like
multi ability to go access all the tools you already use, click buttons, take actions, etc,
etc. So obviously that's a fairly big bet by the folks that have just chucked all that cash into
a debt. Yeah. Text to action as a, as a generative AI, pretty cool. So that'll be fun. Yeah. I can
imagine, you know, sending a text message and all of a sudden my Excel reports are done and, you know,
when you start thinking about these things working together, that your mind just kind of blows a
little bit, you know, writing a prompt to adapt that then speaks to copilot, copilot goes off.
Does this thing for you? I don't, I think we'll write in a lot of instances, like if you're in a
busy office, but honestly, we're going to be speaking to these tools. Yeah. That's a fair point
really. It's computer from Star Trek. That's where we're headed. Maybe not with the sort of super
all encompassing powers that are envisageable by where most people think of AGI, but with enough
power, certainly for marketers and sales folk to be instructing their software platforms to go do
things for them that usually would have required loads of manual input. A click, click, click,
scroll, click, copy, paste, click, scroll becomes, Hey, do this please. And it's done. So yeah,
that's pretty cool. The other thing was we were playing with a tool called DID this week.
Imagine like a near human looking avatar with a near human sounding voice that basically acts
like GPT. So when we say near human and near voices and look, it's kind of like uncanny valley style,
like looks human, not quite sounds pretty human, but still a tiny bit robotic. But you can ask it
questions and through, you know, natural language prompt, and rather than spitting out text, it
speaks to you. So you could absolutely as a marketer, imagine that replacing a chatbot on
your website, or even if you're in customer service, you know, a video customer service rep,
even on the website or almost hosting some sort of video call with a customer. But the customer
service rep is this animated avatar that looks kind of human like and speaks like a human. I mean,
that's kind of mind blowing as well. And I know there's, we've talked about it before, there's
quite a few companies out there trying to do similar things, but this was by far the easiest
one I've played with. Like I literally logged in, signed up, started giving it prompts and having
conversation with it. Very different setup to a lot of the other AI avatar tools that I've used or
seen. Synesthesia, I think is one of the big ones in this. Yeah, and I think so, Bill. I haven't
seen that they're integrating anything with chat GPT or any chat based AI, but it's the next logical
step for them. And obviously it's happening within this space. I'm fascinated to know what the
consumer response is going to be. When these are rolled out, how people are quite happy using
chatbots and kind of live chat agents. They're always quite clogged on here, those, but as those
get more powerful with chat GPT, they're going to be quite useful and functional. Slapperface
on it. And how are people going to interact? Are people going to hate to it? Are people going to
have emotional response? No, I have. What do we do when we fall in love? Yeah, I fell in love with
the chat agent on my Eon meter reading website. Oh yeah, I love my latest iPhone. No, I really
love the fire. Right. Moving quickly on. Tool of the week, Stakey, is still GPT-4 with a comfortable
circle. It is GPT-4. So I wanted to play around with this. There's some people that have been
doing some cool projects on there. Someone made a playable version of Pong, the classic video game.
And I thought, well, wouldn't it be good if we could get the Artificially Intelligent Marketing
podcast to maybe have a new look and feel on the website, maybe create a whole website. Now, the
thing I want to stress about this is we started recording this. I think we jumped on the Zoom call
at 8.30 PM. I started this at seven minutes past eight. Okay. So you had 20 odd minutes to get,
to do what you've been doing. 23 minutes to get this to the point that it is at. And I'm just
going to share this screen now. So for those of you listening, you don't get the benefit of this,
but if you can find the video, you'll see it. But this is the first time Paul has seen it. So
there you go.
Ooh. So wait a minute. Take us through the process for how you did this.
So this is a three-page website. This is, and it works. All of these pages are actual pages. You'll
see we've got the home page, the about page, and the contact us page. Contact us page has got a
form on it. At the bottom, we've got a newsletter signup with stay up to date, Lotus, episode,
news, and events. It's got a form with an API connection. This doesn't actually work because
I haven't put the API key for the email marketing platform. But once I drop in the API key, this
will be connected to Send in Bloom email marketing platform. And you can see it's got a home page.
It's written all of the texts. It's got three buttons that link you out to listen on Apple
podcasts, listen on Spotify, listen on Amazon music. It's got copyright notices and privacy
policy.
Whoa, whoa, whoa, whoa. Right. Okay. Tell us what you did.
Yeah. So what I did, the starting point for this was I actually asked it. I said,
you're a world-class prompt engineer.
We're just talking to yourself there, Martin. What did you say to chat GPT?
To chat GPT, you're a world-class prompt engineer. This is GPT for remember. So
world-class prompt engineer and website developer. Write a prompt for chat GPT to write a website.
So I actually ended up writing this very, very detailed brief, a full written brief with,
you know, it was a very comprehensive brief. I thought it was very solid. I then took that
brief and then popped it into a new chat and said, you're a world-class website developer. Your code
is neat, tidy, minimal, et cetera. You've been asked to design and develop a website following
this brief. And then I asked it to create that website. The interesting thing was its first
response was to almost like write an email to me or write a long response to me saying,
I've written your website. I've created your website. This is what I've done.
It was the account manager. I like it.
Absolutely. It was going, it's this secure. I've added this to the page. And I was like, no, no,
no. I need the files to upload to the server. Send me each of the files now. And then it started
writing the files. So what I ended up getting was three HTML files for the pages. I got,
I think it was two JavaScript files and one CSS file. And I've taken those and opened them in the
browser. Really? I mean, it really is that, that's basically one of them. There were some additional
tweaks. So the logo is actually the hosted logo from our website. So I had to go back and tell it
where to source that from. So I've given it the address for the image.
Couple of other little things that I, what else did I need to change? I tried to get it to put some
animation into the text and stuff. Couldn't quite get that working within 20 minutes.
Oh, well that's highly disappointing. What a waste of 20 minutes that you only built a website from
scratch. Code and design. I mean, that's, I mean, yeah, for 20 minutes work, it wrote all,
yeah, that's it. It wrote all of the text. What? That's not even pulled off our existing website.
No, this was, this was text I have to write all of the text. Everything was created by it.
I didn't do anything other than tell it the name was it. It does make me sound way better than I
really am. I just saw that. So yeah, now, now I understand. That's just a really good example
of its ability to produce junk. Yeah, exactly. I mean, this says that you serve as the chief
marketing for a leading tech company. I do. Artificially intelligent marketing. Currently
a podcast. Soon to be a tech company. We're all tech companies these days. Isn't that right?
Well, I think we have to be. Yeah, that's what I thought. I would play around with the tour
this week. It's, what's interesting actually is I stuck the same prompt into GPT, into chat GPT
with GPT 3.5. Yeah. And it was just like old model. It just went, nope. It said, as a, you know,
AI large language model, I cannot create this, but I can tell you the steps that you would need to do.
Now I know it can create that or it can create web pages because at my presentation tomorrow,
I'm showing an interactive functional game of Noughts and Crosses that chat GPT made for me
and did a pretty good job of. Using the old model. Using the old model. Yeah, correct. And it did
that and I managed to edit it to get a logo and a button added in there with some different
and states on the bottom and stuff. But yeah, this is a level beyond that. This is multiple pages
created. This is design text. It's kind of crazy. Right, Mark, as we said at the beginning, if you're
not playing with these tools, get playing. GPT 4, get playing because, and be creative, start
Googling around, get on the Twitters and figure out who's playing with this stuff. Cause you'll
be inspired by the examples that you see. Not only can it generate text outputs, it can generate
code. It can do sums. I saw in the demo, its ability to reason through someone's tax return.
Get creative. So an example was really smart. Oh yeah. It was mind blowing. Like do my tax return
for me and break out the logic that you needed to go through. And it even like sucked in some important
and ledger changes that were important for a particular time period. And anyway, search that
as well. But yes, play with it, challenge it, challenge yourself. Look for examples online
of where people are doing really out there things with this because you probably do pretty cool
things. I mean, people are using it to create apps at the moment. There's been a lot of that.
Somebody created an app that suggests five new movies to you every day that you should watch.
And they did that in like a half an hour or something crazy. Like if in terms of unleashing
creativity and allowing you to finally come up with ideas for things that you wanted to do,
but lacked technical skills in specific domains, this opens up a lot of doors. We should say mine,
to go from raw HTML and JavaScript to what you then put together. It's not super challenging,
but you need to know what you're doing, right? You can't just like paste HTML into your
web browser bar at the top and now you've got a web page, right? There's still things that you
need to know how to do, but they're not the hard things that quite easily learn.
Yeah. And if you know your way, a little bit of knowledge, you can get a long way. And actually,
if you don't know, you can ask it to explain it to you. That's the thing I think, honestly,
that's the thing that I think is really remarkable because if you come at it completely,
admittedly, I couldn't do it in 21 minutes like I did with this or 23 minutes, whatever it was,
to create this website, but I'm very confident now I could create a Chrome extension from scratch.
If you were to ask me right now to create a Chrome extension, I wouldn't have a clue,
wouldn't know. I'm not a coder, not a developer. I wouldn't know where to start, but I reckon that
within a few hours with GPT-4, I could have a fully functional one up and running.
Well, you know what you've just done there. Martin, will you please create a Chrome extension for us
so that we can show the folks next week?
That's a challenge accepted.
Martin's like crap. But yes.
As if I've not got busy enough with the toddler.
Just don't go watch Davie County. Don't goof yourself anyway. We've already talked about this
before. So there's like three or four hours backing up. Oh, I'm going to have to do this.
Three or four hours backing up. Or take your laptop and just, that would be even better.
I was watching Davie County. They were three-nil down again.
So I created this Chrome extension and accidentally commercialized it over the
next two weeks and made $2 million. That would be pretty cool, wouldn't it?
We are playing Fleetwood Town this weekend. So being three-nil down could happen.
It would be better off listening to Fleetwood Mac.
And with that, I think we'll end the podcast. I think we've probably talked
quite enough nonsense for one week. Thank you so much everybody for joining us again.
We really, really appreciate it. Hopefully you found this valuable. If you did, subscribe.
And if you did share it with your pals in marketing land. We're getting loads of downloads.
We're loving it, but we'd love more. So please do share this far in mind if you think it's valuable.
Other than that, we will see you all next week. Martin, thank you for your time as always.
I'll see you next week, my friend. See you next week.
Cheers. 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,
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