Welcome to Artificially Intelligent Marketing, a weekly podcast where we stay on top of the
latest trends, tips and tools in the world of marketing AI, helping you get the best
results from your marketing efforts.
Now let's join our hosts, Paul Avery and Martin Broadhurst.
Welcome to Artificially Intelligent Marketing.
Here we are for episode 17.
Thank you for joining us.
I'm here with my good friend Martin.
Martin, how are you and what have you been up to this week?
I am bright and breezy today.
This week I have been preaching from the good book Generative AI.
I was at a digital marketing conference over in Leicester, about 300 people in the room
and I was doing a session about how to basically prepare for a future powered by AI when it
comes to your marketing, all of these new AI tools and what should people know?
A couple of interesting things from that talk, Paul.
First one was that at the same conference last year, I asked people how many people
had used AI.
About 10% of the people put their hand up last year.
This year, I would say 95% of the room had done.
It was overwhelmingly a sea of hands went up.
The vast majority chat GPT and specifically the free version of chat GPT.
So not many people get in their hands on GPT-4 just yet.
But the other thing that came out of that conference was a little bit of presentation
magic, Paul.
What I decided to do with the talk was I wanted to incorporate some audience interaction.
So the start of the talk, I was going through a few stats about where the state of AI at
the moment and the McKinsey report that said about four trillion being added to the global
GDP from Generative AI.
But I also asked people in the audience who had used chat GPT and what their use cases
were.
The members in the audience told me their name, told me where the business was.
I made sure to repeat this very loud for the rest of the room.
So I would say, this is Mohammed and you're a graphic designer and you've been using it
to create press releases and how has that been?
He told me the good and the bad.
I did that with another audience member as well.
As the talk went on, I got to the end of the session and nobody in the room saw this coming.
I said, you really want to experiment with these tools, particularly trying out something
like chat GPT with Zapier now, obviously we've played about with the great open AI and Zapier
integration, which gives you access to whisper the audio transcription tool.
So what I'd done is I'd pre-loaded a file in Google Drive to when a new file goes into
that drive, goes into whisper and a sequence of steps occurs.
Long story short, taking the audio clip, transcribing that, turning the transcription into a blog
post and publishing it in real time on medium.com on a medium blog with an image created from
Dali again, that's taken from the audio prompt as well.
When I did it, I had no idea if it was going to work.
The night before I tested it and it failed and I tested it three or four times before
and it had worked, but this one time it had failed on me.
I thought, oh dear, this is bad.
There was no one in the audience that knew that I was doing, so none of the tech team
could give me a kind of thumbs up to tell me that it had worked.
There was going to be a big reveal.
Anyway, so I said at the end, I said, oh, and you can even, I said to the audience,
you can even use this to write and publish a blog post without even touching a keyboard.
I got my medium blog up and fortunately for me, there was a blog.
So I thought that great take, hurdle number one overcome.
Started reading through it and no one really understood the kind of relevance of this.
It all seemed a bit generic until I got to two paragraphs where it mentioned the business
owners I'd spoken to it had their names, the company they were from and their use cases.
When I read that out, there was an audible gasp in the room as people were like, how
has he done that?
That is magic.
So yeah, that was deeply satisfying.
As someone who's done a little bit of standup comedy in years gone by, great when you can
get a laugh from an audience, but getting an audible gasp as people were just shocked
was a good moment.
That is awesome.
So you recorded audio while you were speaking, stopped the audio at some point through it
and then that triggered the rest of the workflow while you just finished your talk and then
went back to it at the end and it was all written as a blog post for you.
Yeah.
And then that was the most nerdy thing because I had it recording in my pocket and then I
went over to the lectern, had to kind of sneak out my phone on the lectern, put it in front
of me and I had to press stop, upload to Google Drive.
I knew that it was only four clicks and it was fairly straightforward.
I drilled it a few times, but you know, 5G could have dropped, like the signal in the
room could have been terrible and it might not have uploaded the file.
And there were any number of things that could have gone wrong and I could have looked like
a bit of a muck at the end, but fortunately I didn't.
I love that.
Great story.
I was at Vistage this week.
I think I was probably one of the more exciting things that happened to me this week.
I'm a member of Vistage, which is like a CEO, peer learning network.
It's been hugely valuable to our business and certainly my own personal development.
So if you're a managing director or a CEO out there who is looking for support and places
to balance ideas off and training, I'd highly recommend Vistage.
But I was at their conference, their yearly conference in London and saw a great talk
from Fireside Chat with Stephen Bartlett of Diary of a CEO fame among other things and
Dragon's Den.
That was really interesting.
But the thing that really caught my eye from an AI perspective was I went to a breakout
talk about AI.
Probably the most important and interesting thing for me from the talk was a couple of
polls that the speaker ran live during the session and there was probably, I don't know,
80, 90 people in the room and the most overwhelming thing stopping people getting started with
AI was a lack of access to training and also the lack of skills and people in the business
who actually know how to leverage AI for the good of the business, which I think we've
touched upon briefly on different episodes of the podcast, Martin, but it really drilled
it home to me that people are starting to become aware of this, right?
You've got your 10% aware of it and have played with it to 95 over the last year or so.
But now they're trying to figure out how do we get started?
And of course, it made me realize how remiss of us, Martin, how remiss of us that we offer
AI training and AI consultancy for businesses in order for them to get started with AI.
But we never mentioned it on the podcast because we're spending all of our time diving into
the details and all the nitty gritty bits that we love to talk about.
But yes, I think that's where businesses are, they're ready to get started, but they don't
know where to start and they're looking for training and help.
So if you visit artificiallyintelligentmarketing.com, we're going to add a few more details about
the services we can offer around that for those of you that are interested.
Meanwhile, I had a fantastic day out of Vistage and got to learn loads of great stuff.
So it was loads of fun for me.
Well, that's always a good bonus and good to see lots of people engaged in the topic
of AI.
Clearly people are wanting to know a lot more.
So yeah, always happy to help on that front, aren't we?
Absolutely.
In the interest of helping, let's get into this week's stories.
So the main stories this week, we're going to touch on Microsoft bringing AI shopping
tools to Bing and Edge.
We're going to look at how AI generated tweets might be more convincing than real people,
according to some recent research.
We're going to look at KPMG's report on the productivity boost from generative AI and how
it can add 31 billion pounds to the UK economy and UK GDP.
We're going to look at a little story around the fact that OpenAI has reported the planning
to turn chat GPT into a super smart personal assistant for work.
We're going to get into those.
We're also going to have a look at tool of the week this week, Storybird, and Martin's
going to tell us about that.
And of course, we've got our short snippets.
So let's get into those snippets first and foremost.
So the first one is that OpenAI is opening its first expansion office and it's going
to be here in the UK in London.
So welcome to the OpenAI team.
Hit us up if you want to be on the podcast or you fancy a coffee.
We also have Demis Hsabis, Google DeepMind CEO, saying that its next algorithm will eclipse
chat GPT.
So there was an interview with Wired Magazine where he mentioned Google working on a sort
of combined technology where they're going to improve the LLM with some of the techniques
used in AlphaGo to give their new system Gemini abilities to do things such as planning and
solving complex problems.
So that's quite interesting and they were brave enough to come out and say it's going
to be much better than GPT-4.
So watch that with bated breath.
I am very excited by that.
I just have a lot of faith in Hsabis and the DeepMind team.
I just love what they've done and their approach that they've taken with AlphaGo and AlphaZero.
I'm excited to see what comes of that combination with LLMs.
I think everyone in the industry recognizes the track record and the deep amount of expertise
in this area within Google and if they're going to come out and say that, I think we
have to take them very seriously.
I've not been able to find any mention on timeline for that in terms of us actually
seeing it in action, but yes, I'd be really excited to see when that comes out.
Another short snippet, you might remember that we spoke on the podcast about DRAGAN, which
was a research paper showing how you could track bits of images and the algorithm would
be able to adjust them to make them look real.
So I think the examples we gave were turning a lion's head, extending a model's shorts
into trousers and adjusting a car features and then the rest of the car adjusts around
it.
Well, you can access this on Huggingface.
You can both access the source code and there is a demo and I had a little play with the
demo, Martin.
I have to say by and large, it lived up to the videos in the research paper, which was
quite amazing.
There's a model and I took the poor model and I moved the model's right arm right out
and I had the model's head turn around to the right quite far, almost to the point where
it probably would have broken a human's neck and it did a reasonably good job of making
it look like a real representation of what that would look like if the image had been
captured like that.
So that was pretty cool.
I recommend going and having a play with that and it'll be interesting to see how quickly
this type of technology can be baked into commercial products.
One has to assume Adobe Photoshop's AI beta is going to get an update at some point if
they can develop similar technologies, right?
There was another cool story, this is from one close to my heart from in the life sciences,
Martin, from Insilico Medicine.
So Insilico is a member of the Nvidia Inception sort of group and we talked a little bit about
how Nvidia had invested in and was working with companies to leverage large language
models and other AI-based tools to help drive business growth.
In this case, pretty cool because Insilico is entering phase two clinical trials for
a drug candidate that they discovered using their AI platform, which is to treat idiopathic
pulmonary fibrosis.
But why is this really interesting is according to Nvidia, doing this the traditional way
would have cost more than $400 million and taken up to six years, but using generative
AI, Insilico was able to do it in one-tenth of the cost and one-third of the time, reaching
that first phase of clinical trials just two and a half years after beginning the project.
Here in the life sciences, it's very well recognized that going from an initial idea
to getting a drug to market takes way too long and costs way too much.
So this is again, more evidence the power of AI in the life sciences especially.
Good to see a real world example of that because it's one of those ones where we hear about
the promise of this.
So actually seeing a kind of tangible project saying, yeah, we're doing this, this is moving
and this is the result and the impact.
That's great to see.
Yeah, very exciting stuff.
Looking forward to seeing more such examples I think over the next two or three years here.
We talked a little bit about Mid Journey's update last week but since then I've been
having a play and seen quite a few examples online, I don't know if you've seen them
or not but people have been getting some amazingly interesting effects with this new zoom tool,
basically creating like infinite zoom outs and then combining them in that Adobe After
Effects to create these videos where they start with an image and they zoom out and
out and out and out and half the time the tool does just a really good job of applying
proper context and some of the times it goes absolutely loopy and like puts an image inside
a photo frame inside a painting and it's kind of mad.
Have you seen any of these?
Yeah, I watched one this morning actually and it was a plane that had crashed in a landscape
and it zoomed out and in the journey that it zooms out, it must zoom out like it must
be like the equivalent to two miles away and you end up in this cabin almost with a pilot
or someone looking out over the landscape where there's basically just been multiple
plane crashes.
Yeah, they're really impressive.
The Mid Journey updates that came out recently with 5.2, I've been playing with some of the
other ones, have you tried the shorten capability?
No, not yet.
Tell us about that.
So, shorten is where you take your existing prompt and you ask it to shorten it and what
it does is it basically cuts out bits of text that it doesn't think are relevant and it's
not going to help get you any better output and it gives you four options and it does
aggressively shorten it.
The first one is slightly shortened and the last one is basically like hardcore, we've
reduced this to the core words that it could be.
But it is insightful when you see what words do and do not make a difference and I think
if you want to become a better prompter in Mid Journey, using this shortened capability
will help you understand which adjectives to include or not include or how to maybe
structure your sentence so that the primary topic and primary focuses are in the prompt.
Yeah, I think that's a really good point.
I'm definitely going to be playing with that because it is hard to know and what you end
up doing is you get into a pattern where you include certain terms of phrase because you
think you need them.
Like I don't know, I see a lot of prompts and I now do this myself that write like photorealistic,
8K, super resolution and all these other things because you think you need it to get the best
output.
It'd be interesting to see if they basically all get stripped out or you only need like
one turn of phrase like 8K to suggest that you want it to appear really high resolution.
The other thing came up as I was having a discussion on LinkedIn, I can't remember if
we've mentioned this on the podcast, there's a lot more tools and prompts in Mid Journey
than I think a lot of people realize.
A lot of people are using Imagine, which is the one that you use to generate an image,
but my favorite is to use Describe and then feed it an image that I think is really cool
and then it reverse engineers what type of prompt would give you an image like that and
it gives you, I think, four prompt ideas, which is absolutely fantastic for then taking
that original image idea and then twisting it as you see fit, so to give you something
completely novel.
So I don't know if you've seen famous actors as fruit or something and you've seen like,
I don't know, Leonardo DiCaprio morphed into some sort of pineapple, I don't know, I haven't
seen, I don't even know what would happen if you enter that prompt, please enter that
prompt and then tweet us and so we can see it.
But then if you wanted to do exactly the same thing and turn a bunch of other famous people
into fruit, just feed it the image and it will give you like the bare bones of what
you needed and then you could just swap the fruit out and you could swap the famous person
out and then you can get a whole series of images.
Are you doing this for us in real time, Martin, so we can see what that looks like?
Oh crumbs.
Okay, well now at least we've got an image for this episode of the podcast.
So yeah, mid-journey, cool, go play with it.
There's loads of extra power there now.
What else have we seen this week?
We've seen GPT Author.
So I don't know if people have seen this, but this has been released on GitHub and according
to GitHub, this is a project that utilizes a chain of GPT-4 and stable diffusion API
calls to generate an original fantasy novel.
Readers can provide an initial prompt and enter how many chapters they'd like it to
be and the AI then generates an entire novel outputting an EPUB file compatible with ebook
readers, and that you can create a 15-chapter novel for as little as $4 and it will be written
in just a few minutes.
That's kind of a bit mind-blowing.
It's not out of the realms of what you might expect given what we know the tools can do,
but the fact that someone's now made that tool available as an open source on GitHub
for people to go play with, I can imagine an explosion now of book generators, one assumes,
Martin.
What are your thoughts on that one?
Well, how long till the Booker Prize is won by an AI and the author has to complete much
like the Sony photography award recently?
That will be interesting to see.
That is the danger and one assumes you can currently ask ChatGPT4 to write in the style
of famous poets and authors and social media gurus.
One assumes you could start cranking out novels based on existing authors' works that you
really liked and then that gets muddy.
It's like, oh, what would have happened if Michael Crichton had written Jurassic Park
3 instead of all of the series of movies that we eventually got?
Well, now we can pump it into the tool and see what we get.
I think it'd be really interesting to see how that all shakes out.
Then the last little snippet is actually an update on a story that we've already featured,
but I think maybe it's interesting to revisit, which is this concept that Amazon is building
a large language model marketplace as part of its sort of bedrock solution for its AWS
customers.
We've talked about this before, but I think the reason this is especially interesting
to hear this come up is I've also heard recently that OpenAI are thinking about doing something
similar and also I think as marketers get to grip with the base level capabilities of
an OpenAI chat-chibi-tea type tool for simple content generation, I'm meeting lots of business
owners and marketers who wish that they had access to an LLM that understands their own
business and their own content and their own internal information better to be able to
produce things that are more customized to them, either as an internal knowledge product
so that you almost have an Ask Jeeves, but for internal stuff.
It's like, oh, who do I go to to find this out?
What document contains information on this technical aspect of this product or whatever
it may be?
Also things like obviously driving more company-specific content production for content marketing,
which I think is a common use case already.
The concept of creating customer service chat bots that are really well-trained on all your
own service materials.
I'm getting asked more and more, how would I go about doing this?
One assumes that therefore this marketplace from Amazon could make that easier.
If you're a product manager or a marketer, you probably need to keep an eye on this space
as it becomes easier and easier to develop large language models on your own information
for marketing, sales, and customer support use cases without all of the technical complexity
that would go into it.
So I think that's going to be interesting to see how that evolves.
Yeah, I agree.
I think the one thing with all of that, because I'm getting a lot of people asking me as well
about this, how do you create these kind of knowledge bases?
And to a certain extent, I think the co-pilots of this world, when all of your documentation
can be read by co-pilot, certainly for an internal knowledge base for employees.
I think I'm expecting Microsoft or Google Workspace AI to do a lot of the heavy lifting
there.
So obviously, if you need a customer facing one, I think there's going to be lots of solutions
coming forward.
But yeah, interesting proposition from Amazon there.
Yeah, and maybe I'm being overly optimistic, but I'm kind of disappointed that we haven't...
I know that there are beaters and that some people have some access to Windows co-pilot
and others have access to some of the Google's palm models in Google Docs and Gmail.
But I was expecting, straight hoping for a slightly wider rollout of those tools by now.
And we haven't seen it yet.
So they're built because they've beaten them, but they're not rolling them out that quickly.
So what can we read into that?
Is it, do we think it's technical infrastructure that's going to slow that down?
Because obviously, there's a lot of compute power that's going to be needed to fuel that.
Is it the tools don't perform that well in the hands of real people doing real use cases?
And so actually figuring that out and ironing out the kinks of slowing things down?
I don't know.
What do you think?
Is this timeline...
Am I being overly optimistic?
Is everything playing out as well as you might expect?
Or do you think we should maybe have this by now?
I thought we'd have it in autumn, to be honest.
When they announced it, I think you've touched on a few things.
The compute power, turning this on overnight and giving this to the world, everyone with
Windows 11 or what have you.
A few things might fall over.
But also, I mean, early testing, I've seen a few headlines and a few tweets.
People aren't blown away with it so far.
So maybe it's just a case of, do you know what?
This is just going to take a lot more testing, a lot more real world, get it in the hands
of users that are going to break things.
That would make sense.
We know these thick tools are prone to hallucination and you have to very precisely brief them
currently to get exactly what you want.
Yeah, I think that will make sense.
Right.
Let's move on to our main stories for the week and let's start with Microsoft bringing
AI shopping tools to Bing and Edge.
So you spotted this.
What were your thoughts on this?
Yeah, so Microsoft have announced a new AI powered shopping tool for Bing and Bing AI
chatbot, which is available in the Edge sidebar browser.
So this new tool set includes an automatic buying guide generator, which uses Bing's
GPT powered AI to aggregate and list product specs for comparison and purchasing.
So as part of this, the buying guide will pull in content from a bunch of different
websites.
At the moment, I believe it's only available in the US, but worldwide rollout is coming
soon.
Couple of interesting points from the buying guide that it generates.
It has AI generated review summaries, so it's taking lots of reviews and then summarizing
them all to give you the good, the bad, the highlights and what have you.
There's another feature that I thought was particularly interesting and you can see here
how AI is being monetized and that's the price match tool.
So what they're doing is that they're putting in a price match tool that helps users to
request a price match from retailers.
Now it's expected or it's thought that Microsoft are getting an affiliate fee, they're getting
some commission on the sales through these buyer's guides.
So that's how they're going to actually monetize this as a strategy.
But yeah, I thought it was a really small use case and definitely one for e-commerce
companies to be aware of in terms of how do you get your products into these buyer's guides.
On the one hand, I think this is good for consumers and to an extent good for product
marketers and resellers.
But if you're a publisher, how many, if I think about last time I bought a bit of tech,
in fact the last bit of tech that I bought was my PC, I think I've mentioned it recently,
I bought my new PC.
How many blog posts, how many articles did I read on the likes of TechRadar, on the likes
of Tom's Guide, on all of these...
The Net and all these other platforms with the 10 best laptops of 2023 style thing, yeah.
Yeah, all of that.
They are going to be sitting up and going, ooh, Bing is coming for our, he's going to
eat our lunch.
Yeah, it's interesting.
I mean, obviously there's the impact on e-commerce stores and how can you get into these sort
of automated buying guides, if you like.
But I saw a post on LinkedIn this week, slightly tangential but related, about the best tools
for SEO were writing listicles and how-to guides.
That may still be accurate today, I don't think it'll be accurate for very long.
And personally, I probably wouldn't invest a huge amount of time and energy in those
because I think they're going to be asserted by generative AI.
That basically gives people that type of information naturally in the response that you get from
the tool.
Yeah, you already see that coming in the examples of Google's search generative experience,
their listicles being written.
You even see listicles that are listing websites without actually linking to the website, which
is crazy to me.
I have to think that they'll do slightly more for publishers rather than just eating all
of their content and regurgitating it.
But yeah, I think if you're in that game, you feel like it's not diversifying how you
create content.
Yeah, I think where my head starts to melt is these tools have been trained on and one
assumes will continue to be trained on whatever content they can get their hands on, which
means the web.
But if we all now stop developing content in emerging areas, let's all decide, oh,
listicles, how-to's, the common go-to type of content is not worth doing now because
you won't get ranked or people won't click on your stuff because it will just be in a
generative search result.
Well, a new area in science emerges or a new technique, which happens a lot.
The tool can't write a how-to.
It's got nothing to absorb and to crawl and to learn from.
So does that mean that how-to's and listicles can continue but you have to stay right at
the cutting edge of material producing information that's going to be things that you know the
tools haven't been trained on yet because it's so new?
So do we end up with a window of opportunity on the how-to's and the listicles and what
have you until just enough content has been generated that now the chat-tipities of the
world have now been trained on it and they can regurgitate it too?
What do you think about that?
Yeah, well, I think that's the case for a lot of companies as it is.
Anyway, a good example from my own blog is that I was ranking really well with a blog
that was the best text to image, well, the best AI text to image generators and I was
updating this monthly up until about September, October last year and I was getting a good
amount of traffic from that because it was first mover advantage.
There wasn't many people talking about it and you could get a lot of traffic through
that but now everyone's written that blog post has been copied, there's probably 20
different versions of it on the likes of TechRadar or what have you.
So trying to outrank those is just too difficult now but I think what's changing is who the
big competitor is, no longer is it the big publishing houses, you know, not HubSpot writing
the blog and me going, there's no way I'm going to outrank HubSpot.
Now it's, well, I'm not trying to outrank, I just don't want Google to rewrite my article
and present it as its own work which it inevitably will do.
Yeah, of a fall, of a fall.
When I was out and about this week, I had someone describe chat-tipity and other tools
as regurgitating the information in their training data which is not strictly true,
is it?
It's probability-based engineering.
But certainly using you as inspiration and a ton of other people, Martin, to produce
some content that you used to get a lot of commercial value out of and then you'll quickly
get zero.
I don't know if you follow Lily Ray on Twitter, she's an SEO influencer.
She's been following the Google SGE process and doing lots of tweets about it and she's
actually found examples where search generative experience is just copying blocks of text
verbatim.
It isn't rewriting it there and it is just, it is presenting it as its own and it's very
clearly a paragraph of text written elsewhere.
Wow.
So we've actually got this blurred line between the models understanding how to communicate
as humans from their large training data sets and then of course, because Google has access
to all the world's information indexed as part of its search algorithm, actually then
going and grabbing chunks of text and then just pasting them in amongst its natural LLM
put.
Yep.
And not giving credit.
So it's like a featured snippet, except you don't even get the link and the referral.
They've just taken your text without giving you the signposting.
Oh, the world is so very gray at the moment.
Right.
With that in mind, let's move on to our next story, which is kind of similar to what we've
been talking about really.
So story number two here is that AI generated tweets might be more convincing than real
people according to some recent research.
So we saw this story on The Verge and in this report, a recent study found that people trust
AI generated tweets, in this case, those written by GPT-3, more than those written by humans.
So the research involved a survey where people were asked to identify the source of a tweet
and determine its validity and some of the tweets were from humans and some of the tweets
were created by GPT-3.
The tweets focused on various scientific topics, including vaccines and climate change.
So also, you know, potentially quite controversial topics.
And it involved 697 participants in the UK, Australia, Canada, the US and Ireland, and
they covered 11 different topics, including topics where the content of the tweets was
correct, but some that was deliberately inaccurate.
And the results show that people struggled to distinguish between human written and GPT-3
written tweets and were more likely to accept both accurate and inaccurate information if
it was written by the AI.
So Giovanni Spitali, the study's lead author, was very keen to emphasize that the technology
itself isn't good or evil, but it's just amplifying human intentions.
And that the study itself, which is in science advances, concluded that GPT-3 generated content
was indistinguishable from organic content.
Research suggests that improving training data sets could prevent the misuse of these
tools for disinformation, noting that GPT-3 resisted generating false content about vaccines
and autism, potentially due to the amount of debunking information in the training data
set, and that ultimately Spitali advocates for fostering critical thinking skills as
the most effective long-term strategy for countering disinformation.
So a fascinating story, because we're not even talking GPT-4 here, we're talking its
predecessor.
Tweets are not exactly the longest form content in the world, so probably reasonably easy
for it to do a half decent job in the character limits that you find on Twitter.
But the idea that people just really couldn't tell the difference is further evidence that
if you wanted to create lots of Twitter content at scale using bots for things like disinformation
campaigns, your average person's probably not going to be able to tell truth from fact.
What are your thoughts about this story, Mike?
I like the conclusion certainly about fostering critical thinking skills.
I think this is good advice in the round, where it doesn't necessarily need to be in
the context of disinformation and AI.
It actually brought to mind the story from a few weeks ago where the research paper was
about the email responses from doctors or GPT-4, or I can't remember which one it was.
I think it was 3.5 for a method.
The AI was more empathetic and that kind of thing.
It just reminded me of that.
I think we shouldn't be surprised when people are taken in by AI written content anymore.
Yeah.
I think basically the verdict's in on that, which is in a lot of use cases, we can't really
tell the difference.
It's funny, I've had a number of conversations this week about what does AI do for education
and how things are changing.
I think a lot of the frustrations with the education system, both from people in it outside
of it, I'm not an expert in this, and mostly just repurposing conversations I've had and
things that I've heard is having schooling moving as far away from learning to remember
versus learning to think and critically analyze and question and be curious and seek sources,
which I realize is a big part of how schooling already works.
Really going in all in on that is probably going to be critical because when you've got
tools that can surface, I mean we've had this with the web really for years, but it's even
easier now to go to a chat GPT and ask questions.
But needing to be able to think about how to assess what you've been told and double
check the sources is going to be critical because, and it's going to be exhausting for
us as humans honestly, having to validate everything that you see online because it
could have been created by a bot that got it wrong or it could have been created by
a bot as part of a deliberate misinformation program.
We need to teach people and kids especially how to do that, but I also think the cognitive
load that's going to place on humans to do that due diligence is going to be a lot.
So I guess what we'll see is an emergence of bots that help us understand the outputs
of bots and do that due diligence for us, but then who controls the bots and influences
and trains the bots that do the due diligence, right, and it all just turns into this crazy
ongoing confusing never-ending infinite paradox of gray.
So yeah, interesting story and I do start to worry a bit about disinformation and the
ability to create this type of content at scale.
Yeah, absolutely.
And it's right to, when it's so easy to create content and the rewards are as high as they
are then, and this goes from SEO through to trying to orchestrate a coup.
It's easy to do, so you have to assume that people's thirst for reward will lead them
down that path.
I couldn't agree more, Martin, than with that.
Next story.
So story number three this week is a KPMG report.
Productivity boosts from generative AI could add 31 billion pounds of GDP to the UK economy.
So you saw this story, Martin, tell us a bit more about this.
It's another report coming out from the big consultancies after we heard McKinsey's report
on generative AI recently and Morgan Stanley's report.
So yeah, this one's focusing specifically on the UK and as you said, they're saying
that generative AI could contribute an additional 31 billion to the UK's GDP annually, which
equates to a 1.2% boost in productivity.
If you know anything about UK productivity over recent years, you would know that being
able to get a 1.2% boost would be seized upon as a great opportunity because quite frankly,
we've had terrible productivity growth in recent years.
So on average, about 2.5% of tasks could be performed by generative AI, impacting 40%
of jobs in some capacity.
This figure is lower than the open AI research that they conducted into the US jobs market.
I imagine that they're fairly similar in terms of makeup of jobs.
Maybe the answer lies somewhere in the middle or KPMG haven't really grasped the full capabilities
of generative AI and the potential impact of a multimodal system like GPT-4, which the
image inputs haven't really come to market yet.
So we're maybe not accounting for that.
Anyway, so it says while 10% of jobs could see significant effects, now that is where
over 5% of the tasks are impacted, 60% of jobs may see minimal to no direct impact from
generative AI.
It goes on to look at which areas are most affected.
So they say creative occupations, text-based AI could automate 43% of tasks for authors,
writers, and translators.
Graphic designers could see 15% of tasks automated.
Whereas jobs in retail, customer services, hospitality, construction, and manufacturing
are among the 60% of occupations expected to see almost no impact.
Which does chime with the open AI report in terms of what jobs are not going to be impacted.
It did tend to be that more manual.
You did see it was the trades weren't going to be impacted.
The one that stands out to me in here that I don't buy, in fact there's two of them,
retail to a certain extent, because I think generative AI will have a role to play in
that.
But customer services.
I'm surprised by that.
Yeah, that doesn't make sense to me.
While you were telling us about that story, I was really, those were the two for me.
And I think without diving deep into the report, I want to be careful about what I say because
I don't know the details of the report.
But for me, it doesn't take a huge amount of imagination to see how the combination
of synthetic video, synthetic voice, and generative AI, which is not really a future tech.
If you look at companies like Synthesia and a bunch of other companies that are creating
synthetic humans, I think MetaHuman is another platform that you can create really realistic
looking people with really realistic sounding voices and they're getting better.
If you think about where that technology even was 12 months ago, the people look more realistic
than ever and less uncanny valley.
And the voices have that natural intonation to speech about that's more like how real
people talk with ums and ahs and pauses and all of that stuff too.
It's hard for me not to imagine a time where even if I go into a store, I would look from
advice from someone, you know, we're buying from self-service checkouts.
We've adopted those when into my local co-op supermarket the other day and there's six
self-service checkouts and there's only one human checkout and most of the people who
are in a rush go straight to the self-service because hey, boom, I'm in, I'm out.
Why not self-service tablets where you can have a full-on conversation with someone?
I think that's coming.
So, and of course you can imagine that in an in-person retail setting and in an in-person
customer service setting.
Why am I not having that conversation at the front desk of a hotel?
I think we could well, right?
I'm not sure that's going to be a human.
How many years that's going to take, I'm not sure.
So yeah, I'm like you, I'm a bit surprised by those two.
The report goes on to say that in order for us to actually realize these productivity
gains, there are changes in work practices, we're going to need to enhance skills and
it's going to require significant digital investment.
These are the prerequisites for actually turning these productivity gains into reality.
And it goes on to say that while widespread job losses aren't expected, skills mismatches
may occur in the short term as the labor market adjusts.
And yeah, that definitely feels right to me.
I think there's going to be some catching up to do as we started out with this session,
people are thirsty for training in this domain.
When people see what it can do and they immerse themselves in it, they're really surprised
and if they've got a brain that can kind of, you know, it's a creative thinker and think
outside of tell it to do this and it will do this, but they can go, oh, what about if
I...
I mean, this is one of the things that I find when I'm doing the training sessions on chat
GPT, right?
People will say to me, could it do this?
And I'm always like, we'll just try it.
Just give it a go.
Like don't ask me if it can do it.
Like just get stuck in.
And I think if you're someone that's a bit of a tinkerer or is prepared to kind of poke
things and see how it responds and reacts, you'll immerse yourself in it.
But I think there's a lot of people that don't have that inquisitiveness.
So they do need a lot of, they are going to need training and that's where employers need
to start investing.
I think you're absolutely right.
I think there's also going to be a group of people who they don't have time to figure
out how to make it work well for them.
They want someone to just shortcut that process for them.
Who's had a play, learn all the things, learn the shortcuts, learn the holes and can basically
just prime them in a two or three hour session.
This is how to be productive right away.
Don't spend two, three weeks trying to figure it out or months, maybe in some cases, how
to figure it out yourself.
So I think I'm going to see a lot of that.
I think the other thing I took from this story, sort of big picture style, again, coming back
to my experience at Vistage this week, we had a great session from Roger Martin Fagg
who's sort of Vistage's economist in residence, I guess, if you like, who often has some very
interesting and sometimes quite provocative views.
He's been speaking for several years about the resource gap in the UK, the labor gap.
Obviously, we're thinking in terms of job losses potentially driven by AI, but within
the Vistage community, we've been talking for several years now about declining birth
rates in the UK over the last 20 to 30 years, a number of people taking early retirement
during or just after the pandemic and that gap in terms of enough people to do a lot
of the jobs.
We've got a very services driven and in some cases, knowledge worker based driven economy
in the UK now.
And where are we going to get our productivity gains if we don't have enough people to do
those jobs?
And I think more and more, there's a hope that AI is going to help enhance the productivity
certainly in economies like the UK's where there is that big labor shortage.
So when you look at it through that lens, it's actually maybe quite exciting and something
to embrace, especially here in the UK, is something that maybe we need to try and find
ways to supercharge our economy, which let's be honest, is struggling when you use a number
of different metrics and you look at growth and inflation in other Western countries.
It's not looking great for the UK at the moment.
So honestly, it may be that stuff like generative AI is going to be needed to help boost our
economy and get it where it needs to be.
That said, we're not the only country that has generative AI.
So that is all relative, isn't it?
If we get a 1.2% boost, you can assume that all other countries are going to get a similar
kind of boost.
Countries that have a similar economic and labor market landscape as ours, which many
Western economies do.
So it's not like we're going to be catching up on companies, sorry, countries that we're
slipping behind.
Okay.
Let's get ourselves into story number four.
I think we're on number four, which is that OpenAI is reportedly planning to turn chat
GPT into a super smart personal assistant for work.
So we won't hover on this too long because it won't be mind blowing to a number of you
that listen to the podcast, but there's a few things in here that might be interested.
So it was reported this week in the Decoder that OpenAI's latest business plans were revealed
in an exclusive by The Information, citing Sam Altman, OpenAI CEO and two insiders.
The business version of chat GPT could be equipped with in-depth knowledge of individual
employees and their workplaces, providing personal assistance tasks such as drafting
emails or documents in an employee's unique style and incorporating the latest business
data.
So why is this interesting for marketers?
Today, we're expecting to have this power through Windows Co-Pilot and Google's Bard
or their large language model or however that then is branded and manifests itself.
But we talked at the beginning of the podcast that this is taking its time to get into the
hands of a lot of people.
So is there an opportunity here for OpenAI to sidestep that process and put a more informed
version of chat GPT in our hands, especially because a lot of people I speak with have
been using it for creating blog posts and social posts and marketing-driven content
creation, which I think is great.
But whenever you try and use it to create emails and stuff in your voice, it's a bit
more of a painful process.
And this would be a welcome addition for a lot of other use cases within businesses outside
of writing blog posts, et cetera.
So I think it will be interesting to see.
Now that might trigger a race, which the whole generative AI field feels like a race that
OpenAI bribed the status gun to go off early and everyone else is like, oh, sprint.
And everybody's running after it.
I think if OpenAI are able to release or find a way to empower chat GPT to absorb company
information and write in your own style and all these other things that we expect Windows
Copilot, et cetera, to do, we might ironically then just get access to those tools earlier,
which I still think given the fact that we baked into all the other tools we use are
going to probably be easier to use and better.
But again, we might thank OpenAI for triggering faster and easier access to them if indeed
this turns out to be true.
What are your thoughts on this, Mark?
OpenAI and Microsoft are sure rubbing up against each other quite a lot, aren't they?
This is the dynamic that I'm really curious about.
They seem to be partners, but at the same time, absolute competitors and rivals in certain
domains.
Similarly, I read a report recently that OpenAI didn't want Bing AI to be published quite
as fast as it was with chat GPT and GPT-4 powering it.
I think they wanted a few more guardrails.
This made me think of Pi, which I know that you've been playing with.
I've still not had a go with Pi.
I think it's because it's on iOS only at the moment.
I think you can use it through the web interface.
Oh, you can get it on WhatsApp, SMS, I think even Facebook Messenger.
Can you?
All right.
I need to have a dig in with that then and have a play.
Am I right in thinking that these sound like similar tools or have I misunderstood Pi?
I think my experiences with Pi is that it wants to be an assistant that remembers a
lot of the things that you tell it and gets to know you better.
Can I ask it to write me an email and send it?
No, not as far as I haven't really tried, but then some of the more basic tasks I've
asked it of.
It's struggled a bit.
I think definitely there is a race to create an AI customized to be your personal assistant
based on you.
Whether there ends up being a blur between one assistant that helps you with work and
play and personal life and all those other things, or whether or not you end up with
multiple different assistants, I'm not sure.
Definitely there's a lot of companies and a lot of money betting on personal assistants
of some sort.
As a slight aside that is probably related, I'd mostly been asking Pi things like, oh,
I want to have this difficult conversation.
What would be a good way to go about it?
Almost like personal coachy type stuff.
I think it'd been doing a reasonably good job.
It's a little bit annoying in that it ends every conversation element, every bit of chat
with another question to the point where you're like, look, I really want to stop talking
to you now.
It's like it's almost trying to addict you to it, but it doesn't really work.
It's just a noise.
There's some feedback from the developers.
This week, I actually asked it something a bit more businessy.
I asked it to try and write me a blog post because I heard on a podcast with one of the
co-founders that it was on par with GPT-4 with a lot of stuff.
I thought, I'm not sure if that's been my experience.
I started to play with it.
Writing a blog post with it was a nightmare circular conversation because it just wants
to keep asking questions.
You'll say, look, give me an outline for a blog post on this.
It's like, okay, well, here's some things that we could include.
Do you think these are good?
I'm like, yes.
Okay.
What about this?
Do you think this is good?
Yeah, yeah.
Okay.
I'm like, can I just have the outline please?
They're like, yeah.
Okay.
What about this question?
I'm like, oh, no.
I just gave up.
Based on that very limited experience, I think we're going to see a bit of a horses for courses
here and there's going to be a bunch of different AIs that do different things for us.
Whether or not they get really good at understanding us over time and their use cases and applicability
expands and then one particular bot takes over, I don't know.
But yeah, that's been my experience.
Right.
Okay.
Interesting to hear that reflection.
If OpenAI's proposed assistant does the things that it's saying it's going to do, I'm excited
for it.
They're a company that I think so far are delivering on their promises.
Well, I say delivering on their promises.
They're not delivering GPT for API access to me yet.
Not that they did promise, but I did fill out that early access request some time ago.
So chop, chop Sam.
I'm sure he's personally signing off on the...
I filled that form in five times.
I'm thinking if I just become really annoying, I'm going to try and crash whatever server,
whatever system they're running on, which is...
In fact, I'm going to ask chat GPT, how can I convince them?
What should I tell them to get GPT for API access?
And if they don't give it to me, how can I bring their system down?
I wonder if it would give me that advice.
They're going to have to upgrade their compute capabilities just to handle your forms of
missions.
Absolutely.
Yeah.
It's bot on bot action.
Right.
With that, a little nugget.
Let's move on to our tool of the week and we're nearly done.
Thanks for bearing with us listeners.
We're going to talk about Storybird.
So you've been playing with Storybird, Martin.
What's been going on?
Storybird is a neat idea that I'm sure lots of people have had when they thought about
the possibilities of stories being able to be written by AI coupled with images being
able to be created by AI.
So your Dali, your stable diffusion type images, wouldn't it be great if you could just write
a prompt and then it would turn that prompt into a story that you can then get images
created for you.
Just laid out all of the text and the pages and then you could have that printed and you
could give one of your loved ones, maybe a child in your life, you could give them a
personalized story.
And that's what Storybird promises, create personalized stories using AI.
The way that it works is you start off with a thousand character prompt.
So you've got to write a summary of the story and the more detail you give it, as is the
way with these things, the more detail you give it, the better the output is.
So if you're quite tight with your, if there's characters, you can just put in brackets next
to their name, a few traits for them, you might say, strong or scared or courageous
or whatever.
And it will incorporate that into the story.
Does it work?
Yeah, it does.
It does work.
It's a story I put in a story for my lad about tractors and it gave me a story and the story
was fine.
That's what I would say.
I don't think the storytelling-
It was fine.
I wasn't blown away with the quality of the output.
I only did try the one story and I felt like my prompt had enough detail in it to have
a more, well, just to have more drama.
Drama is probably the wrong word.
I mean, it was a story about tractors looking for a plow with some pigs and sheep and goats,
but just something that was slightly more engaging.
I think the biggest issue that they've got at the moment and they do address this directly
in the tool itself is that due to the way that images are created using just diffusion
tools, the images aren't consistent of the characters.
So the tractor in my story, it created as a green tractor, but every time the green
tractor appeared, it was a completely different style of tractor.
So there's no consistency throughout the story and that's something that they said they're
working on and it's understandable that that isn't quite there yet.
Once you've created your story, if you're happy with it and you can regenerate the images,
so it gives you the text, gives you the image, you can change each of those elements as you
see fit.
Once you're happy with outputs that you've got, you can then actually order the book
to be printed on demand via Amazon for about $26 and it will be printed and shipped to
you.
So it's a really novel idea.
The interface is very, very easy to use.
It's designed to be kind of idiot proof and I did demonstrate that quite effectively.
Yeah, it works.
What I like is someone putting together a very nice UX, UI to do something that lots
of people have said would be a cool idea to do, which is create personalized AI generated
storybooks, but it does need to work on making those stories slightly more interesting.
Yeah, so interesting concept.
I think when I think about it as a marketer, a great way to communicate is to tell stories.
I think some of my favorite business books are not dry textbooks.
They are business fables like Five Dysfunctions of a Teen by Patrick Lencioni.
Basically anything that brings the message of trying to get home to life with real characters
and in a story.
I could definitely imagine not this tool because I think for obvious reasons it's targeted
at a very specific demographic.
If we say on their homepage, empowering young writers to create unique stories with amazing
illustrations, there's a very specific target market here.
But how would sales folk and marketing folk can we storeify the messages we're sharing
about our products?
Maybe there'll be an AI for that.
Thinking even further, I was giving a workshop, a webinar about ways to make your budget go
further in an economic downturn and how it's five times more expensive to generate a new
customer than it is to keep and grow an existing customer and how can you delight your customers.
We talked a lot in that webinar about how to delight people but at scale.
For example, you can generate handwritten notes using tools like handwritten, but it's
done in an automated fashion.
You could imagine creating interesting bits of content for existing customers or new prospects
at scale with images and text that are created by an AI based on a story scaffold that you
give it, which might be the challenge.
Start with the protagonist, which is your customer at the beginning, and then what happens
is they're on their journey with you and your business as the guide and how they come out
the other end as a successful hero, perhaps incorporating specific things that end up
in your CRM about their particular challenges or business or use case or whatever.
So actually, it doesn't take a huge amount of imagination to try and start thinking about
how these tools could be used in a business context.
No, quite.
It's just, again, I've said it before, stick a nice UI on it, make it functional for people
and you've got yourself a nice product.
Absolutely.
Another thing we say a lot on this podcast is these tools are as bad as they're ever
going to get.
They're only going to get better from here.
So if they suck a bit at A, B or C, they're probably going to get better.
And what's interesting about having so much access to the APIs of a lot of these products
and including companies like Meta making so much stuff open source, I think they're learning
huge amounts about how people want to use them, how businesses want to use them, where
it goes wrong.
I mean, if you are StableDiffusion, sorry, Stability.ai or if you're developing Mid Journey,
you must know that unleashing a commercial application of your business is the ability
to keep subjects in images the same across image sets.
And I know you can use the seed tool for that.
So there is some control.
But the image generation tool that makes that easy, both for UI, but also like really being
able to precisely manage characters and other features within an image and keeping consistent
across an image set is going to open up much more additional power from a commercial perspective,
whether that's writing books and graphic novels through to business context.
So that's applying a commercial pressure to the developers of these tools to get those
things built, whereas they may not have previously realized how important that's going to be
to people.
But now they know.
Cool.
Well, thanks for sharing that tool with us.
Lots of fun to be had with that, Martin.
I think I might go and have a little play.
Hopefully everybody has enjoyed today's podcast.
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Other than that, thank you so much for your time, Martin.
Great hanging out with you as always.
Speak to you next week.
Cheers bud.
Bye.
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