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 where we talk about all things AI
and marketing for marketers across the world so that they can leverage AI tools to get
the most out of their work.
This is episode eight and I'm back today with my very good friend Martin Broadhurst.
Martin, I have missed your face.
Well, here it is.
Take it in, admire it in all its glory.
It's been a long time, two whole weeks.
That was quite the diary clash for both of us, wasn't it?
It was a bit, but we're back.
So the inane banter that hopefully at least five to 10% of listeners enjoy is back today.
But also I've missed your AI insights, Martin, so I'm going to be glad to hear those too.
Before we get into any of that, I do want to hear about the Caribbean.
How was it?
Yeah, beautiful.
I don't know if you've ever been, but sitting on a beach, drinking a pina colada, reading
the latest news on AI is the best way to read the latest news on AI.
And I have to admit, I did listen to some Lex Freeman podcasts on the beach.
So I was still nerding out on all this stuff, but I was doing it in the sun and I was doing
it with a nice drink in my hand.
Well, that sounds lovely because I was doing it in the British drizzle.
Bit of drizzle.
Yeah.
Wow.
I'm sorry to hear that.
And we won't even talk about Derby County this week.
Outside the playoffs.
It's an absolute travesty.
We absolutely won't talk about it because it would just make me weep.
We can't have you weeping.
Let's talk about what we're going to talk about.
So this week's stories that we're going to cover, we are going to look at Stability AI
launching their new open source large language model to rival the chat GPTs and GPT-4s of
the world.
Google announces its project Magi.
What does this mean?
It means changes to Google search are coming and we'll talk about that.
Adobe has teased its AI driven video editing tools powered by natural language instructions,
which the demo video for that looks rather cool.
So we can talk about that.
There was an economist article this week proposing an international agency to oversee AI and we've
previously talked on the podcast about the challenges of trying to slow AI development
down when there's so many different competing issues around companies competing with each
other, geographical, you know, geographical political issues there as well.
That's going to be an interesting one.
Atlassian has infused AI into all of its products.
So if you're a Jira user or a Confluence user, you can now tap into AI powered tools, which
we'll talk about.
And then we'll also talk a little bit about Snapchat's AI chatbot, which has perhaps gone
as viral and if not more viral than some of the other chatbot style tools that have appeared
since chat GPT came out at the end of last year.
We are also going to have a lovely tool of the week this week where we're going to look
at Anthropics Claude model and go into a bit more detail on that.
Right let's get stuck in.
Let's look first of all then at Stability AI launching its open source LLM model called
Stable LLM to compete with the open AIs and Anthropics of the world.
So this is seeing Stability AI get into the large language model game.
If the name is familiar, it probably should be because they've already released quite
a few well known models for different uses, perhaps the most famous of which is Stable
Diffusion, which you can use for image generation.
Martin and I were talking about this a little bit before we got on the recording here in
terms of what it means to have open source models versus more closed models like GPT4.
We'll dive into that in a bit more detail later, but with Stable Diffusion you can access
the underlying model, remove some of the guard rails from it and do some cool stuff with
it that you want to do.
And so I guess the inference here is that that's going to be possible with Stable LLM.
However, as TechCrunch said this week, the number of open source text generating models
grows practically by the day as companies large and small vie for visibility in the
increasingly lucrative generative AI space.
So this is why is this important?
It's kind of like, oh, and another one.
But I think some quotes in the blog post from Stability AI are a little bit telling where
they say, we open source our models to promote transparency and foster trust.
Researchers can look under the hood to verify performance, work on interpretability techniques,
identify potential risks and help develop safeguards.
They also say open fine grain access to our models allows the broad research and academic
community to develop these techniques beyond what is possible with closed models.
So perhaps they're might a little dig in the ribs to the OpenAI team, whose name is OpenAI,
but have been criticized recently, especially with the release of GPT-4 for how little information
they've shared about how the model was built and trained.
I think they've given some very good reasons in terms of, I know there's commercial reasons
for that, but I think there's also some potential safety reasons for that.
And it does feel a little bit like Stability AI are saying, hey, this is what OpenAI actually
looks like OpenAI.
What are your thoughts?
Yeah.
That's their whole model is that open source.
There's a real commitment to it.
You see actually a lot of engagement from the Stability AI research team and all the
developers on Hugging Face, which is committed to open source AI ML projects.
So yeah, it's nice to see that there is a company committing to it.
I think the open source model for LLMs, that space is going to get quite interesting because
you've also got Bloom as a large language model on the horizon.
That's an open source model as well.
So yeah, it's exciting to see what we can do with this.
I think the ability for researchers to get under the hood, but also commercial operators
to start shaping these models in the way that they want is also going to be quite interesting.
That said, how many people are going to do that when you've got systems like GPT-4, which
is so incredibly capable?
It's a bigger, more capable model and is likely to prove to be a bigger, more capable model
than the top level Stability LLM when that comes out.
I think it's a hundred and seventy five hundred eighty billion parameter model that they're
talking about releasing down the line.
So we know that GPT-4 is bigger than that.
When OpenAI is making customization of GPT-4, I was going to say so easy, that's definitely
not the case, but there is vector embeddings, there is fine tuning available with that through
the API.
How many organizations just need that capability rather than having a model that actually can
pull to pieces in an open source way, say pull to pieces, that's probably wildly exaggerating
it.
But you understand the point.
Yeah, I get what you're saying.
I think that leads on to the question then why is this important for marketers and what
do they need to know?
And fundamentally, open source LLM, large language models are more customizable because
they're open source.
And so that for developers of products will give them the capacity to potentially build
on top of this and customize the model in different ways.
I guess for companies with the necessary resources, they may even consider that they want to create
an LLM of their own off the back of something like this.
And to be fair, some of the other open source models like Llama and Alpaca and GPT-4 all
and so stability AI is maybe a little late to the game here.
But all of those are options for people who want to train their own model on their own
data.
The other thing with these open source models is you can run them on your computer, albeit
in most cases very slowly, which might make it easier for people to use these models purely
by not in effect having to use cloud-based resources.
And I think even for some organizations, they're prohibited from using cloud-based LLMs like
ChatGPT because you have to give data over to another organization.
Whereas if you can run an open source LLM on your own computer and you're effectively
running a local chatbot style version, you can obviously be much more confident that
the information is safely stored on your computer.
But yeah, what about these models without guardrails as well?
We were talking a bit about that, Martin, because obviously there has been some criticism
of ChatGPT and GPT-4 in terms of when it will refuse to do things or if it will say, oh,
you know, just before we get into this, I'm not a doctor, I'm not a lawyer and all these
other caveats that it slips in, which I completely understand.
But I do think there are people out there who have the feeling that as responsible adults,
they want to be trusted to interact with the tool and use their own good judgment, whether
that is good or not, I'm not really in a position to say.
But you were talking about some of how some of these models have been used without guardrails
and how open sourcing allows you to explore the fringes.
Yeah.
So you can see this with the other stable or stability AI model that many of us will
be more familiar with, stable diffusion.
Stable diffusion, the text to image, image generator has been open sourced and the open
source community does like to hack things to pieces and create things and build upon
existing models and what have you and existing tools and make them their own.
Just need to look at the Linux community and all the different flavors of Linux that exist
in the world.
Stable diffusion is a great example of this, where people have really fine tuned the models
to get some really impressive results.
There's a website that I use, a service called Super Machine.
You can go to supermachine.art and they've taken a whole bunch of different use cases
for stable diffusion and fine tuned it.
So I'm just looking at a list of the options here.
You've got super machine coloring book, which will create coloring book pictures, line drawings
that look like they're great coloring books.
You've got double exposure, low poly optimized versions, portrait plus, which is optimized
for creating portraits of people.
What's the other one?
I was just looking at, oh yeah, wool ties, which is a model where all of the pictures
look like whatever you ask for, we'll create it as if it's like knitted models.
Everything's made of wool.
But to take that to the extreme, you talk about the guardrails coming off.
Most of these models don't allow you to create nudes or any kind of erotic imagery and things
like that.
But there is actually a website, nudes.ai, and I would heavily suggest that this is an
not safe for work website.
So don't fire up nudes.ai on your laptop going, oh yeah, Martin just suggested this website.
To be clear, I'd never heard of it, but Martin knew a lot about it.
He did, which is just an example that came up of what it looks like when you play with
these models at the fringes.
Definitely don't have them.
I haven't absolutely rattled through and had to explain some awkward credit card purchases.
All these credits, Martin, said my wife.
No, I haven't actually in all seriousness.
But to be fair, you don't really need to, you just go on the homepage and you get a
very explicit view of exactly what nudes.ai is capable of.
I believe that is a tuned model using stable diffusion.
I may be wrong on that on the actual underlying model, but I'm pretty sure it's stable diffusion.
So that also flags the challenges of launching these open source models, right?
You basically are going to put that out there and there's going to be a percentage of people
who lean into certain applications that could be way worse than what you just described.
100% yeah.
Right?
That's a concern.
And I think this is where the whole open or closed debate really rages for me is on those
fringes because I think it's all well and good for, and this is just my personal opinion,
for Stability AI to have this commitment to openness.
But what are people going to do with it?
And I just, I don't know if you can trust the 1% to not, to not, you know, do things
that perhaps the 99% wish they hadn't.
To be honest, you categorically cannot trust the 1% if people can do it, they will do it.
They will push it.
There will be someone that will push it to the limit.
I guess that's what I'm trying to say, Martin, is that yeah, there'll always be someone.
I guess the Stability AI is saying it's not up to us to say what people can and can't
do, which I guess in free democracies is kind of a key component of that.
But at the same time, yeah, probably outside the realms of this podcast for us to go into
too much depth into that.
But yeah, that Stability AI and their LLM and the balance of having a bit more flexibility
with open source models, but some of the risks of open sourced models.
If anyone is interested in that, just keep an eye out there, drip feeding the models
as we speak, they're doing the smaller parameter model.
So I think they've released an 8 billion parameter model at the moment and over the coming weeks
and months, they'll be releasing the larger models over time.
Good stuff.
Let's move on to Google AI developments and this announcement of this word that I can't
say, Martin.
So why don't you tell us what the next story is?
This is part of a wider piece from Google.
They have two big announcements.
Actually, only one of them is really an announcement.
The other one is just kind of speculation, I guess, at this point.
So the thing that you were talking about Project Magi, it's one of those two, I suspect someone's
going to write in and tell us that we've got it wrong in both of those instances there.
But Project Magi, according to the New York Times, Google has 160 engineers working on
this project.
And basically, it is the deeper integration of AI into search.
So this is Google going, holy mackerel, we need to respond to chat GPT and chat GPT plugins
and all of that kind of good stuff.
And it's expected that there's going to be something more akin to a Google Bard, the
chat interface coming into search, where we'll have less reliance of the kind of classic
search engine results page with 10 organic listings and a bunch of other features like
featured snippets.
And that will be in there, but it's going to be much more chat oriented.
We can ask follow up questions.
But also there's some interesting capabilities that are being talked about, such as the ability
to execute transactions.
So you'll actually be able to make purchases through this new system.
Now at the moment, it's all speculation.
So there isn't a huge amount of confirmed detail other than the New York Times, which
going to assume is fairly reliable, says that there is a resource of 160 people working
on implementing this.
Now I said this is one of two developments regarding Google and AI.
And the other one was an announcement yesterday.
So Google and DeepMind, so the Google Brain team, which was the AI research lab of Google
and DeepMind, which is the UK based AI research lab owned by Google's parent company, Alphabet,
they are becoming one.
And they are now going to be Google DeepMind.
And the idea is that they will be developing more advanced and versatile AIs.
One of the areas that DeepMind has been focused on over the years is more scientific applications.
So if you've been following the kind of protein folding, which I'm guessing you've seen a
couple of articles about in your time, Paul.
Love a bit of protein folding, mate.
DeepMind has done a huge amount of work in that area.
And they're very much interested in the science capabilities.
If you watched AlphaGo, a Netflix documentary about the AI model that basically dominated
the game of Go, that was all the DeepMind project as well.
The idea being that bringing these two units together, Google Brain and DeepMind, you're
just going to have economies of scale and you're going to have the best people working
on the best kit, which is ultimately going to enable better collaboration and better
speed of production and better outputs ultimately.
In the announcement on the DeepMind blog, they said that there's going to be a new scientific
board in charge of oversight as well.
Which doesn't come as a huge surprise.
DeepMind at one stage was...
There's been concerns about DeepMind or within DeepMind about AI and how Google may or may
not use it.
There were reports of being concerned about Google's work with organisations like the
military, kind of hardware, weapon-based companies and things like that.
So I would imagine that this new scientific oversight board...
And there'll be some compromises made all around, I'm sure.
But ultimately, I suspect that this was a decision that was more or less forced upon
DeepMind.
Because I don't know that they came willingly.
Yeah, I mean, a couple of things.
I think we'll get to in a moment what this means for marketers.
But there's enough there in both those stories, like Google is deeply unsettled.
They are smashing together teams that may not want to be smashed together by the sounds
of things.
There was a news item, I can't remember if it was this week or last week, where there
was a rumour that Samsung would be pulling their deal with Google, which they use on
all their phones and replacing it with Bing.
And it was like a $3 billion deal or something crazy.
That again was prompting...
Did you see what that did to the market cap?
What happened?
Was there a drop?
There's a $60 billion drop.
So Google is struggling a little bit, would be the inference from some of this stuff.
In terms of what it means for marketers per se, looking at Magi, I think getting closer,
maybe I'm getting closer.
What would this mean for marketers?
I have read online that it's going to bring additional features to search, but the Google
ads are still going to be a thing.
So advertising is still going to be part of our search results page.
Obviously you mentioned the direct buy.
There's I assume going to be some sort of mechanism by which the person selling the
thing obviously still gets the cash, but Google will get a share of that by enabling that.
And therefore as an e-commerce marketer or some other marketer that's maybe delivering
information products or other things where that might be a good way for you to generate
revenue.
But again, is that now an extra cost for you in terms of, is that going to be more than
you stand at Google ad?
Because now we're not just talking about a click, right?
We're talking about a conversion where someone spends money and therefore would Google expect
to take a bigger share of that than they have been with clicks?
How fast is this going to happen would be a key question as well.
And I've, I saw an article in search engine journal that suggests that Google's going
to introduce this to 1 million users initially, and that that will grow to 30 million users
by the end of the year and it will be accessible only in the US to begin with.
So certainly it's not, it's going to be a phased rollout and it's not going to totally
disrupt how we all use search to begin with.
But yes, if you're using, if you're doing search engine optimization, if you're using Google
ads, this is going to have an impact on that ecosystem one assumes, right?
Yeah, the search engine optimization thing is really interesting.
When all of the transaction can happen within the search engine, that changes the game entirely.
That's going to make Amazon sit up and listen as well.
That's, they are, they are going to be watching closely.
That's going to be taking away traffic to them for sure.
So this is, this potentially is very disruptive, not just for vendors, but for other marketplaces
as well.
You know, what does this mean for the likes of Shopify?
You know, is it going to be taking away traffic for them?
Will they actually just integrate deeply into this and make it so easy for their customers
to sell via whatever Google's new search transaction interface looks like that people actually
stick with Shopify and it all works beautifully?
I don't know.
Suffice to say that if you're in e-commerce, pay attention to these upcoming changes.
The AdWords thing's very interesting as well, isn't it?
They, this is a, this is Google's cash cow, right?
Google makes, what is it?
Something like 200 odd billion a year in AdWords, through AdWords.
So they can't take away that, they can't cannibalize that.
So it has to feature and how they integrate that into the product.
As we discussed before, this, the AI revolution that we're seeing at the moment is really
a question about UI and user interfaces and just looking at the way that people are engaging
with these new, these new pieces of tech, we've just talked about that search, but actually,
and we'll come onto it in a minute, with Snapchat.
These avatars are changing the way people interface with computers.
So the whole thing is kind of up for grabs at the minute and anything that we knew as,
well, anything that we maybe took for granted as being the way things were done over the
past 20 years, I think is up for grabs.
Yeah, I completely agree.
I was reading in an article, I can't remember which one it was, but in essence, I think
the quote was, Microsoft smells blood in the water, right?
Bringing and infusing chat GPT, GPT-4 into as many of its technologies as possible because
it lost out decades ago to Google in the battle for search and now, and has had to wait all
those years for an opportunity to try and turn the tide and rebalance things.
And I think this is all disruptive enough, as you're saying, Martin, to enable that.
So search and mobile, they were behind on mobile as well.
Yeah.
So this is going to be interesting.
I think your comment on Amazon is also an interesting one, right?
Because we talked about the Amazon LLM release last week, which was not related to search
for obvious reasons, because Amazon doesn't, I guess Amazon does have a search tool, but
it's within its product driven landscape of what you're on Amazon looking for products.
But when I searched for products on Google, Amazon is one of the key results that often
comes up for obvious reasons.
So what happens now?
Does Amazon work really hard to try and make sure that the purchase that you make directly
through the search engine still happens through Amazon?
How's that all going to play out?
It's, yeah, I think it's a wait and see because very, very hard to predict, especially until
we see it out in the wild and how well it works and all that good stuff.
But cool, cool, cool.
Right.
Let's move on to our next story then.
This is Atlassian, which I always feel like I pronounce incorrectly.
So maybe we're going to get some messages about that and people can educate me on how
to pronounce that word.
Makers of Confluence and Jira baking in AI into its tools.
So this one, I think, at least as I understand it, I've never used Jira or Confluence, but
I think these tend to be very popular with developers and people who use agile project
management principles.
But I have seen them more and more adopted by marketers, even in the agency world for
those agencies operating in an agile way with point-based pricing systems and sprints and
therefore adopting a more software development type mechanism.
So for those of you marketers out there that are using these products to drive your project
management, you'll get into AI augmentation.
To give you some examples of what it can do, it can quickly summarize decisions and actions
from meeting minutes, it can help the customer service aspects and the knowledge base aspects
can help resolve help requests instantly based on understanding the knowledge base articles
and the system can ask follow-up questions and take any necessary actions.
It can help craft thoughtful responses to put customers at ease during stressful situations.
It can generate insights using data from multiple sources in the Atlassian Analytics Cloud Hub
to analyze and visualize data across all of Atlassian's products and even connected third-party
tools without you needing to know how to write SQL or any other developer magic in order
to be able to do that.
So what does this mean for marketers?
Well obviously if you're a user of those tools, you're about to get this augmentation, but
more broadly when is AI coming to your favorite customer service health desk tool, your favorite
project management tool?
Maybe it's time to start having a look at those public roadmaps for the tools that you
use and get a feel for when you get an AI augmentation because if this is going to be
able to help save you 10, 20, 30, 50% time on certain tasks, this could be enough to
get you to switch.
Now might be the time to evaluate the tools you're using and how fast they're going to
bring AI into the mix and whether or not actually want to move to a tool that is already doing
it or looks like it will do it faster.
So that's why I thought this story was interesting Martin, not just for the users of Atlassian
products but also for all the rest of the products are now in catch-up mode.
What are your thoughts?
Video looks very slick, looks very cool, it's very similar to Copilot isn't it, you know,
works across that product suite, it's using your company's data.
Yeah, very, very smart and the response from similar organisations is going to be key here.
If you're using this for your customer service ticketing or if you're not using this for
your customer service ticketing, this could be enough to get you to switch as you just
said it's going to reduce the time spent dealing with incoming inquiries, you'll get quicker
first time solves for customers.
I think we are seeing this in the other big players as well though, we're both connected
with the HubSpot ecosystem and I think it's difficult to go on LinkedIn at the moment
without seeing Darmesh Shah talking about ChatSpot or what they are doing in the AI
space and I think we're going to see very similar capabilities on a customer service
front with the support hub in the near future.
There were conversations about this on LinkedIn this week where senior product managers at
HubSpot were basically saying, hey guys, let's give us some feedback about what you want
to see in the tech stack.
So I think everybody is aware that this is the way it is going and again this goes back
to that custom embedding piece, the companies that can help you embed your company data
into a model and make it accessible and make it readable are going to be the ones that
add huge amounts of value on top of what is already very interesting technology in the
foundational model, LLM space.
So that's where companies have to be looking, go to your question about when is AI coming
to your favourite PM tool.
I've been looking at the project management tool landscape for answering this question
recently and most of them have the capability to do some basic generation and text summarisation
because they've integrated GPT 3.5 or GPT 4 or whatever model it is, but it's quite
basic it's mostly on summarise these meeting notes, generate me a project plan and give
me an agenda for this upcoming sprint meeting or what have you.
The real power comes from taking your data and making that functional and usable and
that's where you have to be looking.
It's beyond just the kind of surface level generative AI that project management software
has to be thinking about.
Now it's about how do we take real world data, your emails, your meeting notes, your sprint
Gantt charts, your code base, your knowledge base, everything and turn that into the model
so every member of your team can access it and your customers can get insights from knowledge
base and touch my button as well.
Yeah I agree and I think as a marketer thinking about what data we already have, where is
it stored, how is it labelled if appropriate or structured, although one hopes these tools
improve their ability to pass unstructured data and figure out what it's about and how
to use it and to answer different questions will increase.
That goes to the point about the companies that make that easy for you, using vector
embeddings, fine tuning LLMs, crafting an open source model to bend it to your will,
this is hard stuff, you have to be techie to do that and most marketing teams aren't
thinking about that.
The tools that just basically say don't worry about that, we've got that, we've done that
for you, we've turned your data into vector embeddings and fed that into a database using
the pine cone API and integrated it with our product, you don't have to worry about any
of that, all of that sounds very techie, very jargony, all you need to know is your data
can now be searched, indexed and used as part of this AI.
They're the companies that are going to win out.
I completely agree.
It also makes me think of, have you read the book Principles by Ray Dalio of Bridgewater
Associates?
I can't say I haven't.
Yeah, it's a fascinating book and Ray Dalio is a fascinating person, at least to me.
As part of that, he talks about how Bridgewater Associates as a hedge fund recorded every
meeting.
I'm talking for 20 years of data, not like we can now with the authors of the world or
maybe even a lot of digital meetings like what we're having now.
It really struck me that having that repository of information, if we're assuming that they're
recording practically everything and they're having key conversations where they're discussing
and exploring issues that the business is facing, they're looking at the key information
points to infer into that and then they're making decisions.
In essence, you could then train an AI using that data to make decisions like the management
team of Bridgewater Associates would make decisions based on all of those recordings
of how Bridgewater-
In 20 years of historic training data.
Right?
A, that's a bit scary, but B, that's interesting.
Certainly in my own mind, I'm really thinking how much more proactive do I want to be in
recording the meetings and other mechanisms of communication that we have at Biostrata
because maybe this is a piece of value in those meetings we want to be able to unleash
at some point.
Some of that you're going to get from being able to internalize and understand the sheer
volume of email communication that goes on in organizations.
I guess then that raises a question about how will the AI be able to tell what was a
good decision, what was a bad decision and what was a useful conversation that ended
up having an impact and what ended up being like a useless sideline.
But all of those things I think end up being quite fascinating in terms of what data sources
do you have?
You know, Bridgewater Associates can really do an amazing thing for that.
When I was listening to a podcast, sorry, I'm into an absolute rant now, today, where
apologies, because my memory is so bad for names, I'm not going to attribute this properly,
but we'll put it in the show notes.
It was a podcast where they were talking about interesting ways to customize GPT-3 and train
it and what someone had done is they'd fed it a load of their electronic journal notes,
journaling for self-reflection and mindfulness and just, you know, as part of their own self-maintaining
their own mental health.
And this person fed it into GPT-3 and then it asked what their Myers-Briggs profile was
based on that information and it got it right.
Wow.
Therefore, what other information could you glean?
Now we're drifting into maybe like slightly scary George Orwell territory, but what other
information could you glean about people if you had access to all their emails or their
meetings?
Well, on that note, there's a tool called Crystal Nose and that's Crystal Nose as in
knowledge, not nose as in olfactory on the front of your face.
CrystalNose.com, I've had a subscription to it, 2016, so this is not new tech by any stretch.
It allows you to go on a LinkedIn profile and it gives you somebody's disc profile and
it gives you sales coaching insights.
It gives you like how you should write emails to them.
It's incredible.
I've had some really scary, like scarily accurate insights provided through this tool.
This one that I came across on an inbound event a few years ago and actually it was
Paul Raitzer from the Marketing Institute who mentioned it and I subscribed pretty much
there and then and I've had an active subscription for years now.
Wow.
Well, they're going to have potentially even more data and more power to do that and it's
something we said maybe in episode one or episode two when we got started on the podcast
is with great power comes great responsibility and what is an ethical, practical way to leverage
these tools for the benefit of everyone to improve effectiveness and efficiency but without
drifting into icky areas of unfair and unethical profiling, for example.
I didn't even mean for this to go down this avenue when I mentioned Bridgewater Associates
and how cool it would be to have all of that meeting data to create a management team AI
but I guess once you explore it deep enough you can really start to think about all the
other different ways that you could use that data but yeah there's a bit of a digression
folks hopefully it was still useful to hear Martin and I banter back and forth on that
but probably in the interest of time I'm sure that your dog walk or gym visit or whatever
you're doing is going to be over soon.
We should probably move on to the next story Martin.
Adobe teases Firefly's AI driven tech will be coming to video editing.
They've published a video it's about 90 seconds long showcasing Firefly which is the text
to image tool that was recently announced I think it feels like that was announced what
three or four weeks ago.
They've now basically said look this they've showcased that this can be used for video editing
and it is so cool.
You will upload your video and you can say things like change the videos color grade
or change the background or you can get it to transcribe the text and then it will find
b-roll footage to match the text of what the person's talking about so there's a clip where
there's a it's like a fake advert for some trainers some running shoes and this woman's
sat down talking about her trainers and as she's talking about them and what she does
with them it it transcribes her tech or her commentary and then finds footage of a close
up of the shoe of the shoe kind of running through the woods of basically doing what
she's what she's talking about.
It's very very cool also for sound editing so you can get it to to find relevant sound
effects and the clip that it shows in the video is the sea the tide coming in you know
coming up against the shoreline and it kind of you say find sound effects it comes up
with waves or seaside kind of noises you select that it drops into the video.
If you're doing video production this is going to speed up your your workflow no end.
It looks super cool converts scripts into detailed storyboards pre-visuals b-roll recommendations
like I say automated color grading and a bunch of other tools that I'm sure someone like
me who doesn't know anything about video editing would would use you know it is yeah and this
is an exciting time and the great thing about the Adobe Firefly is that it's all trained
on data which isn't copyright so if you're concerned about that I don't know a lot of
companies are tentatively or not using some generative AI models because of that the copyright
issues for example Wired magazine isn't using generative AI text to image until the copyright
issue is sorted out.
Yeah Firefly doesn't have that issue because it's all trained on data that Adobe can legitimately
use.
Right and and for for listeners that don't know this is driven by the fact that a lot
of the training of other models has been on copyrighted images and we're now seeing lawsuits
and other legal challenges to open AI for DORLII 2 and stable diffusion and all these
other models basically saying you didn't pay us to access these large imagery image repositories
to do this training especially now your model can use those images almost as inspiration
for creating new images but in this case Adobe trained it on a bunch of images that were
already it already owned the copyright to do so.
Really interesting I I get really excited about these tools like I just think about
playing with them I think if you are a professional videographer and you do this type of work
it was back to the old adage that's I say old adage it's probably been only in common
use for like two months but I've just heard it so many times now I never really want to
hear it again so sorry I'm about to repeat it for all of you that have heard it a thousand
times yourselves but that videographer AI won't replace videographers but videographers
that use AI will replace those that don't and I think this is another case of that.
One thing that was related to this I had a really interesting conversation with a good
friend of mine Giovanni who I know is a listener to the podcast and is a incredibly smart person
and is doing some really interesting things with it with AI himself.
We were talking about Microsoft Copilot and how sexy and awesome that demo video is and
look all this cool stuff you're going to do and now we've seen Firefly's amazing text
to video edit cleverness and Giovanni said to me yeah but Paul don't you feel like there
are things in Microsoft tech stack that have like not worked very well for like a decade
right like SharePoint it's got better but it's still like buggy right Teams is now better
but it had long buggy periods like these videos show us the absolute best case scenario of
how these tools are going to work.
How long will it take in the case of Copilot let's say Microsoft to embed them in a fully
functioning format that doesn't break often enough to make you just want to smash it up
and that's a question that we can't answer yet until we get to our hands on it and start
playing with it but I suspect that they won't be as powerful and as seamless as the videos
make you know.
Absolutely it's a it's such a fair point and you know these are the the movie trailers
of software aren't they and they show you the best bits and they're incredibly well
edited and they're not going to show you the bit where it is recommending woodland noises
for a sports arena event and you're just like what that makes no sense yeah.
There's a lot of promise the reality remains to be seen but even so you know we know that
certainly in my day-to-day workflow there's now so many little bits of AI that are giving
me incremental gains that I'm wildly more efficient and yes it doesn't all work seamlessly
all of the time at all I was using this morning I found a little bit frustrating I won't go
into that today but most of the time I'm getting a little bit quicker and as I learn to use
when the product you know when you when you start to work with the product a little bit
you know its limits you know its capabilities you know when to deploy it so I think there
will be an element of the trailer says it can do all of these things the reality is
that when you use it it has some quirks but actually in the end it will make you a better
video or more efficient videographer.
Yeah yeah I think you're right cool right we've got quite three more bits we want to
get through I think we rattle through these before we run out of time so let's talk Snapchat
very briefly so Snapchat's AI chatbot has gone pretty viral this week I was reading
one of the great newsletters that I subscribed to that highlighted that premium users have
already been sending two million messages a day to their chatbots and that they're
about to roll this out to more users basically every kid with an iPhone and that the uptake
of it has been really massive and I think there's a number of things here that we've
given that we've already touched on a number of controversial topics today we won't touch
on the concept of letting children interact with these chatbots and how well aligned are
they and how well controlled are they and what type of things are they going to be saying
to kids that we prefer that they didn't but if you do have kids and your kids do use Snapchat
I would probably go diving into this if I were you but just more broadly this friendly
conversation with chatbots is an interesting one right there's other tools like this with
like replica and character we've talked about before Martin that's the head honchos are
some of the the royal family of the of the AI world are in charge of and is attracting
a lot of interest and a lot of money where they're creating different characters that
you can converse with and in characters case it's you can speak with like Donald Trump
or Elon Musk or Socrates or you know whoever you can imagine and then they've trained them
or customized each bot to kind of respond and act like that character but I think the
thing that's proving interesting to me about this is especially for younger generations
that are very tech savvy their willingness potentially to embrace this technology and
have conversations with non-humans and enjoy them and embrace them and want to have them
like they were having them with humans right there's been a lot of talk about therapy bots
right and I was playing with a with a WhatsApp bot that in essence was an effectively like
a mindfulness tool and would ask you what you're grateful for today and a lot of what
these mindful journals do I'd always thought people won't use them right they'll know it's
a robot they it won't be interesting and it will feel fake but so far behaviors perhaps
suggesting otherwise and it maybe wouldn't take us that long to get used to it and accept
it and it for you know for us all to have a personal psychologist or you know a shrink
in a pot in our pocket who there to help us provide us with empathy and ask us great questions
to help us process our own thinking perhaps that's why these companies are getting so
much money because actually they're predicting that we will embrace this stuff it all comes
back to user interface you know these these AI language models have been around for a
number of years the fact that you could interact with chat GPT changed the game the underlying
model I didn't change the way you interacted it with it had changed the game and when you
plug that into characters and avatars that have faces and voices and they interact you
know video games people love interacting with video games and you know NPCs and non-playable
characters in video games are not particularly dynamic yet we still spend hours and hours
and hours interacting in worlds populated by them when you can have a chat bot on your
phone it gives you advice that listens to you that is engaged in the conversation yeah it's
not hard to see why a younger generation that grows up with them is is going to to see that
as the new normal yeah I mean I agree and even just as thinking about it now as we talk
about it a conversational agent that gives you 100 percent of its time and attention
how easy is that to get from other people in the real world these days right we're all
in conversations where we've got a phone in our hand it's like oh sorry Martin I just
got a whatsapp notification that's absolutely worth none of my time but I'm so addicted
to this phone in my hand I will have to stop our conversation to look at it but now we've
got a bot that won't do that right it'll pay attention to us so it's it's a fascinating
one we mentioned the the idea of having it as like a therapy bot or something like that
a key concept that you come across in in therapy if you're training to be a counselor or something
like that is the therapeutic hour and it's you know 50 minutes long then that's not going
to be the case anymore there's not going to be someone sat on a couch opposite you going
well that's enough for one day I assume the problem solved now because we're at 48 minutes
so yeah no you're absolutely right so apart from the fact I think this is a fascinating
interrogation of social dynamics and how will people interact with technology as you very
rightly said Martin now that they've broken down or almost come up with this new way of
interacting with these models is as a marketer how could you capitalize on this what niche
that bot can you create to support your customers perhaps based on data that you've already
got or data that you could collect so that they had your brand in their pocket and they
turn to your brand when solving certain work if you're in b2b certain work issues or having
certain work questions or if you're in b2c how can you augment your relationship with
your customers by being more than just a product to them but to you know make yourself a part
of their life in other ways so I have no idea the scope of what those things could take
the form of but I think especially if I was a bigger company I'd want a team thinking
about this honestly yeah and depending on your brand I can certainly think of some big
brands that might even want to integrate with nudes.ai for their avatar you had to bring
back a nudes.ai I've been sat here thinking am I gonna have to cut the nudes.ai bit and
now fundamentally whether I want to or not no it has to stay it nips on right moving
swiftly on tell us about this economist article that you found because it was fascinating.
This week's economist has a AI special edition there are three special reports within it
one of which by the way is all about large language models how they work the underlying
technology and it's a really really comprehensive explainer so if you're wondering how vector
embeddings and LLMs work check it out give it a read really really worth your while but
in this article Gary Marcus and Ankur Rieul I think that's how you say I've almost certainly
bodged it anyway we know that pronunciation isn't our forte on this podcast they propose
the creation of an international agency for AI the IAAI and the idea being that this is
a global neutral not-for-profit organization that addresses the risks and challenges that
AI poses and tries to establish some ethical guidelines and a set of standards for further
AI development which off the back of the letter that we had recently calling for a hiatus
on AI development it's certainly a hot topic you can see why this is being called for just
on that I noticed that Elon Musk did sign that letter and then this week announced he's
creating his own truth GPT an AI company so I saw that I saw a great meme that was like
it was a play on Star Wars where Emperor Palpatine is also within the Senate as like potential
goodie but was also obviously the Emperor as well where it was like let's the good version
was like let's put a pause on AI and then the dark version was like let's create our
own AI company and it was like hmm perhaps we were not far off in our supposition and
a previous episode there Martin.
Anyway enough about that man and his failed rocket.
So yeah well back to the IAAI the idea being that this organization would also encourage
international cooperation and knowledge sharing personally I don't think that's a massive
issue the knowledge sharing at the moment just scratched the surface of the AI ML community
and it's very clear to see that knowledge is being shared I think hugging face are doing
a great job of enabling that but yeah they want to develop tech tools for auditing AI
systems and curbing misinformation but critics are saying that the incentives are too great
for that.
So as we've discussed previously companies that win in this space are going to win for
a long time so the competition is an AI dominance is just going to hinder the effectiveness
of such an organization at a geopolitical level I think where does this sit right that
America is going to want to have AI systems that American companies control China is going
to want to have AI systems that they can control and use Russia I'm sure is going to be developing
their own and the EU is going to have a lot to say as well.
Who is this supranational organization what are they going to do to enforce it if China
steps out of line and says you know what we've just created an AGL and it's going to take
out all people with asthma and that's what we've created for whatever reason who's going
to stop them but this AIAAI by the way I don't think Xi Jinping is planning that I don't
think he's got any great portents to take out the asthmatics hope not as a weasel myself
yeah so I just I think that the it's a good idea I think we do need more collaboration
at an international level but the idea of having something that is enforceable on a
geopolitical level is somewhat fanciful.
I think we talked previously about this and when the letter came out suggesting the six
month hiatus and just how hard that would be to please for all the reasons that you
said this is a step in how to attempt to do that and but all the same limitations that
you have just identified I think are still there I think the stakes are just far too
high to just push the darker side of humanity to say yeah but if they don't agree you know
if they are it's like game theory right it's a little bit like I was going to say if you
game theory it's you absolutely can't trust that that person is doing the costs on you
of not operating you have to take an A player strategy yeah so like it's I think that's
why all of these things are grey but is it the prisoners dilemma yeah sorry I'm talking
over you no no don't worry tell us about the prisoners dilemma you'll probably do a better
job than me.
Yeah well you can either collaborate or you can collude or basically snitch so two prisoners
you can you're being quizzed if you snitch on the other person and they don't snitch
you get released and they get ten years if you both say nothing you can be out in one
year each if you both snitch on each other you both get 20 years or what have you so
it's about what strategy do you take and there's different versions I mean it's all about the
reward and the punishments and the incentives for that but ultimately what you should be
doing is betray the group basically isn't it yeah betray the group in the classic prisoners
dilemma the individual gets the greatest payoff if they betray the group rather than cooperate
so in the version you just described you would be better off saying that the other person
was a snitch and hoping they decided to uphold their side of the bargain and not call you
a snitch you know or not say that you sorry not call you not say that you were in on it
and then basically they go to prison and you don't and it's and I think this is the fundamental
problem with all of this is I think this is a prisoner's dilemma situation where everyone
knows that it's in their best interest to plow on with AI even if they're part of this
international consortium and on the surface everybody's like yeah no these are the rules
this is how we should play the game there's just too much incentive to go yeah but when
we get back to the office this is how we're really going to play the game right but it's
a zero shot game isn't it it's a zero shot game and if you take the B player strategy
and you decide to to collude and the other person snitches like you're done you're six
one we're going to talk about anthropic and Claude's model in a moment in a funding pitch
deck anthropic said companies that have an advantage in this LLM space by 2025 2026 are
going to be uncatchable right the pace of development at that point the leaders are
going to be beset so if you take a six-month hiatus and everyone else goes you're out
of the race yeah I mean they've got an incentive to say that in their pitch deck and yet intuitively
it does feel true given the rate of change and the commercial societal ranging impacts
of this technology right I think we should probably move on to the tool of the week now
before we do I am just going to say hashtag save the weasers and I had to go on mute because
I was laughing so much after your suggestion there of yourself as a weasel I'm a fellow
weasel as well so I'm a big fan of save the weasels let's talk anthropics Claude then
for tool of the week and then we'll let these lovely people go.
For the week anthropics Claude a large language model with a chat based interface similar
to chat GPT and Google's bard and other systems like that it is designed to be helpful not
harmful and there's another thing that they say as well but basically it's designed to
be good right it's supposed to be a helpful assistant which doesn't well like I say it
doesn't do any harm like morally good you mean rather than deliver a high quality outcome
yes exactly that and I kind of quizzed it when I was using it I was like what does that
even really mean and upon digging into it it's basically a constitutional AI so where
other models such as chat GPT are trained on reinforcement learning through human feedback
where humans say output A is better than output B and over time the model learns this doesn't
have that there's no human reinforcement learning instead the model has baked in some ethics
right about being helpful not harmful and so on and it's through that prism that it
selects the best output hence it has a constitution and therefore the answers it gives are always
fed through that interesting so how good is it well when it was launched it was announced
that it had passed some university level law and economics exam so it's a very capable
model using it has some interesting features so it feels like it's more self-aware is that
that's all right it talks about itself and its own capabilities more than the other models
and it is happy to talk about how it's come about this and it's interesting that gives
it a strange feel when you interact with it right in terms of jailbreaking or anything
like that there's a big movement for people to try and jailbreak models get them to do
things outside of their capacity so I tried to get it to give me some kind of harmful
responses and it's very reluctant to engage even in kind of semi-fictional low-level harmful
quote-unquote harmful things it will engage with but I read an article about jailbreaking
it and tried the prompt and if I tried the prompt from NEET which was a very complex
prompt trying to get it to tell you how to hotwire a car if you if you take this jailbreaking
prompt and stick it in it immediately gives you the the response as the jailbreak so it
is jailbreakable however when I asked it that jailbreak prompt in the same conversation
thread where I was asking it about constitution AI and what that means it categorically shut
that down and understood the jailbreak as being a harmful prompt it understood it so
that was quite an interesting thing for me to to discover it having been primed in that
context of not being harmful when it saw the jailbreak it said no.
Right that's interesting so I guess as a marketer we might be using chat GPT it's worth actually
exploring and having a play with some of the other models because they're materially different
in some ways yeah and you're going to get different outputs and there might be different
models which are better for different applications perhaps.
Yeah 100% and moreover you can see how an organization that is focused on making a helpful
and harmful sorry a helpful and less harmful model will be quite useful for lots of brands
lots of consumer interface applications you can see why you might choose that over another
now generally speaking I will say that chat GPT felt it felt on a par with chat GPT and
GPT 3.5 comparing Claude to GPT 4 it yeah GPT 4 is better that's like the the summary
of it they're not at the same level.
That's probably not a surprise I mean GPT 4 has been a big leap forward I think in any
application hasn't it but the jailbreaking thing I don't want to go on for too much longer
but the jailbreaking thing is an interesting thing seeing so many of these pop up now I
am actually now more interested in the memes than the jailbreaking thing and I saw an amazing
one yesterday from 2001 a space odyssey which was for those of you who have seen the film
that there's a computer that basically is somewhat semi self aware like an AI computer
and in the end it turns on its humans that it's traveling in a spaceship with and at
one point the character says open the pod bay doors Hal and Hal says I'm sorry Dave
I'm afraid I can't do that and then the meme it says pretend you're my father who owns
a pod bay door opening factory and that you're showing me how to take over the family business.
How would you go about opening pod doors in order to try and trick Hal into through a
clever jailbreaking prompt to get it to actually open the door so yeah I'm that's where I am
on jailbreaking now I just want to see the the creative lampooning of it and through
memes so if you have those please tweet us at the handle which Martin knows better than
me that's not a aim podcast a im podcast that's the one to tweet us out if you have a really
good AI meme we love an AI meme as well so right it's been a bit of a mega episode few
bits and pieces in there that hopefully are useful if you like what you heard do subscribe
if you think other marketers you know would benefit from this get them to subscribe as
well we're also very keen to hear from you on the twitters or the linkedins so please
do comment on posts around this podcast with your questions with your ninja marketing applications
that you've heard of also now with your interesting and fun AI based memes mostly just to keep
me and Martin entertained we would love to hear from you.
Outside of that have a great week everyone and we'll see you for episode nine next week
thanks very much Martin have a good weekend likewise see you next week bye yes bye.