Howard Bentham: Hello there, I'm Howard Bentham, and this is OxTalks, the
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In this edition, we'll explore practical advice for businesses who are looking
to use AI technology to streamline their operations and grow successfully.
Finding reliable statistics to context exactly where we are in the UK with the
number of businesses using AI throws up many conflicting numbers and in such a
fast moving field, the numbers will almost certainly become out of date very quickly.
I'll ask our guests to give us their view on the state of
play with AI in the UK shortly.
What is clear though is that AI is here to stay and it's becoming more
widespread across the business landscape.
A growing number of organisations are wanting to explore
using AI in the future too.
Some sectors are using AI to great effect, notably telecoms, legal
and finance, whereas others are yet to even begin looking at what
difference this technology could bring.
A consultation published by the UK government in February 2024 said that
the AI industry in the UK employs over 50, 000 people and contributes 3.
7 billion to the economy, adding that, and I quote, "Our universities produce some of
the best AI research and talent, and the UK is home to the third largest number of
AI unicorns and start ups in the world".
So many questions still swirl around the topic of AI, not least what it actually
is and how it works, will it lead to mass job losses as technology makes many roles
redundant, and crucially, is AI safe?
With computers now being able to think for themselves and the slew of very
negative press on the subject, has Pandora's box finally been opened?
As a business leader, how can you use this technology most effectively to
streamline or grow my organisation?
With so much to explore on the topic, we opted not to speak to ChatGPT to get the
answers, but rather to two great leaders in the field of AI in the OxTalks studio.
I'm delighted to welcome Grae Laws, Managing Director of Beyond
Touch, and Guy Gadney, CEO of Charisma AI based in Oxford.
Can we start with the basics to ensure that everyone listening or watching to
this episode is completely across this?
In everyday language, if you would, give us your personal
definition on what AI actually is.
Guy Gadney: Well, I think the first thing to say is it's a very broad umbrella.
It's sort of a technology and this is a technology where a machine, so a
computer, has learned something in the sense that you've given it a bunch of
data and out of that data, it's created something different, something new.
I think that's the simplest way, you know, you put something
in and you get something out.
Maybe that's overly simple, but I think if you look at it in terms of, I don't
know, let's take an example like ChatGPT.
Actually, in its simplest sense, what you might be putting into that or
a high school student or something might be putting in, write me an essay
on this particular piece and what's happening there is that ChatGPT is sort
of understanding what that question is, which is using a combination of
technologies like natural language processing and machine learning.
It's understanding what that student has said and then it is sort of thinking about
that in the sense of wanting to understand what the student is then saying and then
kicking out the essay that the student wants at the end and through that, in
the middle of that process is a little bit of magic that sits on the computers.
But that is the data that I said that sits behind the whole piece.
Howard Bentham: Yeah, it's that bit of magic, isn't it, Grae, that is the
difference between working something out on a calculator or something really
basic to where we're getting this, if you like, Artificial intelligence,
what it is, it's thinking for itself.
What's your definition?
Grae Laws: Yeah, I tend to agree.
I think this is computer programmes that mimic the way human beings
research information, understand it and process it and reproduce it.
If you imagine that language models of this day and age have scraped the entire
internet, have taken databases and sources of information that are so vast
and have simply compressed all of that down and used an algorithm, started to
understand and sort, sift it, understand what it means to use an NLP to actually
process that and it takes a period of time for these language models to actually
get to a point where they're ready.
This foundation model, whether it's very narrow and it might be
specialised in something like biology or science or videography, or it
could be very broad and general.
But once those models are in place, then we build applications and those
applications draw from those language models, they make inferences and they
present something back to you, whether it's a video, a piece of audio, whether
it's text, any one of those things and you know, the future generations of artificial
intelligence will see lots of language models being used and agents coming and
dipping in and saying, I need a little bit of information from that one and more
from that one and it builds up a bigger picture and then presents that back to
you in a mode that you've asked for it.
Howard Bentham: Guy, can you expand on that a bit more?
And how, if you like, a computer learns from its previous experience?
Any sort of examples you can bring to the table there?
Guy Gadney: Well, yes.
I mean, I think the definition is really good.
I think there are two sides to this coin, really.
One is a model, an AI model and what that is, this programme,
it's a piece of software.
It's a programme, and that needs to be trained and there's one thing
that's interesting about this is that the language that we use with AI is
very human, you know, we talk about Artificial intelligence, we talk about
training, we talk about ingesting models.
It's very human, but in essence what's happening is that there is a
computer programme which is taking a bunch of data in the instance
of the things we know about like ChatGPT or those sorts of things.
It is broadly information that is available on the internet and probably
other areas as well that we can get into later and the ethics around that.
That is then parsed, in other words, the software sort of is categorising
it and it's categorising it by meaning, by sentiment, by topic and pattern
matching that and one of the things, the key things that AI is very good at
is this sense of pattern matching, of identifying a pattern of language, a
pattern of mathematics, a pattern of sort of anything that we know as information
and in essence, what it then does is it then predicts what's going to happen
next when it is prompted by a user.
So it sort of predicts the next step of a sentence, it predicts
that a verb follows a subject.
So there's this whole process called training where these AI models are
trained on large amounts of data and then that model is, it goes through
a process of fine tuning, which is then, I suppose, narrowing it down,
whittling it to the point that it needs to focus on, and that again may be a
subject matter fine tuning around a particular topic like mathematics, or
indeed in the creative industries it might be around a particular book or a
particular brand, to make sure that what the output is remains specific to that.
So in other words, you don't want Batman talking like the Princess Bride,
you know, you've got to have Batman talking like Batman and understanding
the world of Batman and keeping on topic in that space because otherwise
it breaks the storyline and that's what the fine tuning process does.
Howard Bentham: It's fascinating.
I alluded to this in the introduction, gents, that it's really difficult
to get accurate figures on the uptake of AI, certainly in the UK,
as far as businesses are concerned.
Can you give us an idea in percentage terms of where we are, Grae, with this?
Grae Laws: It's over 50 percent of businesses these
days are regularly using AI.
For you as an individual, as an employee of an organisation, you've probably
been using AI for the last decade and you just didn't even realise it.
You would have been using it with YouTube with its predictions as to what you should
look at next, when you went shopping on Amazon, when you used your SatNav, when
you used your Fitbit, your smartwatch, your iPad, your average smartphone
today has probably got 10, 15 different small AI tools that are running in the
background that are totally invisible and as we see the next gen of the Samsung
phone and the next gen of the iPhone bringing out their AI tools, they've
actually already been in there for years.
So for businesses, the uptake has been significant and it's certainly the
case that it required an innovation trigger in the public eye for it
really to be taken seriously and I think that was obviously ChatGPT.
Howard Bentham: And where is the UK in comparison to the rest of the world?
Have you got a handle on that?
Grae Laws: If you spoke to IBM, they would say we're in third place.
If you looked at the Freshworks report, that was published last year,
they put us in about ninth place.
We're always in the top 10 and it really comes down to how do you
measure the uptake and readiness?
Because, you know, if people are already working in the industry, then
they're using it all of the time.
If people are just working in business, then they don't even realise they're
using it, but they are and I guess the readiness part of this, and in
terms of preparing applications that are practicable and have use cases in
business, well, that grows every single day and there are certain measures of
enablement that some of these reports use to say, what's the government interest
and investment into AI and funding?
What does that landscape look like?
Who are the most innovative organisations in AI and where do
they, you know, kind of operate from?
What is the capacity for human capital and access to data and energy that will
drive this innovation in the industry?
And I think all of those measures play their part in that ranking,
and there's a certain amount of subjectivity that goes with it as well.
Howard Bentham: Yeah, it's a very broad umbrella term, isn't it?
Very much so.
Just while we're on the sort of generics of this, what about
the doomsday scenarios, which we do hear about in the press?
Are we looking at the 21st century's equivalent of
Oppenheimer's atomic bomb here?
Guy Gadney: The short answer is probably not.
I think what has happened is that, in my sort of work that I've
done over the years, working in technology and creativity, and that's
been building websites, it's been building e commerce sites, it's been
building mobile apps and all of this.
I've never had a strand of philosophy come into the work that I do day to
day as much as it has done with AI.
You know, it's really struck a chord somewhere and I think in some ways what
people are thinking is that they're thinking that AI is somehow related
to the movies, the sci fi movies that they've seen in the past and for the
sense of drama, those movies have often had a punch to them, whether
that's Terminator or Robocop or, you know, AI taking over the world.
It's a good story, there's got to be a protagonist and antagonist and it's easy
to cast that antagonist as AI because it's a sense of attacking, you know.
Also, I think there is a sense, especially in the press at the moment
of AI replacing the journalists, and writing articles and so forth.
So naturally, the people who are covering that are worried for their own jobs that
they may be replaced and I think that is skewing the argument a little bit.
The more, I suppose doomsday scenario that folks like Elon Musk have said,
you know, that it, there needs to be a kill switch in this sense, and
that it could wipe out humanity.
I think it is a strand of logic that people go down and it's a little
bit fanciful to be able to do that.
AI still is a piece of software in a machine.
Howard Bentham: this stage, they would argue.
Guy Gadney: Exactly at this stage and there are two ways to look at that.
How one is, It hasn't happened, but it might, you know and that's the one
which sows a seed of doubt in our minds.
Like, oh my god, are we in control of this?
It's going to run out of control.
The other way to look at it is, we control our own future and if we are
building this, and we're responsible for it, and ultimately, at the end of
the day, this code that you see and often in the presentations I do about
AI, I show code on screen and say, look, this is AI, you know, look, it's
numbers and it's letters and everything, this has been created by people.
So people, we are in control of this, and we can control our own future and how
we chart the next steps for the future.
I'm sure we'll come on to things like regulation, which is one way to do it.
But there is a sense that, you know, in an increasingly automated set of
societies where banking systems and indeed infrastructure is controlled by computers
and is controlled by computers that are connected to the internet, there could
be some form of negative impact on it.
I mean, like serious negative impact.
Actually, probably it's more likely to be someone, you know, as a human
actor who's done that, in my opinion.
Howard Bentham: Sure.
Just before we leave this topic, Grae, your thoughts on the open letter
from the Future of Life Institute just over a year ago, now calling for
the pause on giant AI experiments.
So it was something like a thousand leading experts in the
field that signed that letter.
Grae Laws: Yeah, it was all the great and the good.
You know, it feeds into this well known Silicon Valley conversation point, P Doom,
the probability of doom and this is a zero to 100 measure of like, do you think AI
will be an existential threat to humanity?
Where do you sit on that?
Zero?
Not worried at all, forget about it.
One hundred, it's literally going to eat my lunch, we're doomed.
So everybody sits on that scale.
It's a subjective scale, but in actual fact, lots of those people who were
part of that open letter sat on more than 50 percent in terms of their PDoom.
So their belief that there is a higher probability of it not being for good,
but actually in actual fact being exploited, by bad actors and they could
be individuals, but they could also be state actors as well who actually use
this technology for suppression, for manipulation, as indeed as well as the
environmental impacts that come with it and you know, some of these people
were big players and it is still are.
Geoffrey Hinton, arguably the godfather of AI at Google and Mo Gawdat as
well, another huge figure, both of those genuinely felt and indeed still
feel the same as Elon Musk that we need to be really careful with this.
That in actual fact, if we don't have guardrails, we could be in
trouble and so that was a premise for the security summit in Bletchley.
Guy Gadney: And actually building on that, that as well, I think
there's a lens I like to look at, at AI3, which is that AI is the cause
and then automation is the effect.
So if you're going to look at the impact of what AI could be, look
at automation and then you'll start to see what the impact could be.
So for example, electoral interference with AI, right, that happened actually
was driven out of social media to begin with, with people who are
writing false posts onto social media.
The problem is with the introduction of AI, that process was automated and that
meant that it could go faster, wider, deeper and so as we start to look at
that sort of interference and political interference, social interference
that we're getting, at least we can then identify where the problem is
and start to do something about it.
Clearly there are, as in any new technology, there are people who use it
for good and there are people who use it for bad and the counter to all of this,
to my mind, is education and it sounds, again, very simple, but if we understand
the landscape that we're stepping into, we've got the map for what it looks
like, then we can react to it properly.
The danger comes where we've got, you know, no map and we're running sort
of Silicon Valley speed primed by unbelievable amounts of money as fast as
we possibly can into a space that we don't understand and we don't know and there
I think there are dangers as there would be in any other fast moving environment.
Howard Bentham: Just, I was just going to flip the coin if we could,
and tell us how AI could change the world for the benefit of mankind here,
we've sat around P Doom for a while.
Grae Laws: We have.
Howard Bentham: Let's look on the brighter side of life.
What are some of the things that this could genuinely change?
Grae Laws: Well, think about research into clinical trials and the benefits of using
it to research medicine for greater good.
Doctors have been using AI through Google Health for more than a decade.
So they've got a huge language model that's built upon records of treatments
and think of pharmaceutical companies have been spending decades, literally
decades researching and doing clinical trials on cures for seemingly incurable
diseases and one of the great things about artificial intelligence,
particularly the deep learning aspects of it, is that it can bring together
unconnected points that a human being might not necessarily be able to do.
Howard Bentham: Spotting those patterns.
Grae Laws: Spotting those patterns.
And it doesn't have quite such the same cognitive load that a doctor
may have or a researcher may have in trying to retain that information
in their short term memory and then be able to apply that insight to a
second parallel piece of research.
AI can just do that and not only does it do it well, but because it's part of a
larger language model, it can be happening simultaneously in lots of different
research centers and all of that is informing that initial foundation model
and therefore they all learn from that.
So there's exponential opportunities for health care, a longevity of
life, reducing infant mortality and that's just healthcare, that's
before we go into everything else.
Manufacturing, industry, leisure, education.
Howard Bentham: Well, it's not often in the introduction to an OxTalks we've
ended the world and then saved it.
So how about that, boys, that's...
Guy Gadney: All four minutes.
Howard Bentham: Very impressive start, I must say.
Well, thanks for sharing those foundations of AI in general terms.
Let's find out a little bit more about you chaps.
Guy, tell us about Charisma AI and what you do.
Guy Gadney: So our sector is the creative industries, which, you know, if you think
about what we've just talked about with sci fi movies and everything has had an
interest in AI for decades, from a very imaginative perspective and ironically,
it's also the industry that I think has the most fear at the moment about AI.
Hence, the writer strikes in Hollywood last year, the actor strikes, there's
a real sense of concern around it.
This is an area I've worked in now for almost a couple of decades
in terms of using technology for storytelling and creative purposes and
to Grae's point around the different sectors that people use it in.
For me, there's a wonderful space within the creative industries,
which is two sides of the coin.
So the first one is the one that people talk around productivity, you know,
can you do the same thing faster?
Could you get your idea that you've got for a great story that you want and
you just want to tell that story, can you get it out to your audience faster?
And the short answer is yes and that's the sort of systems that we're working.
The other side to the coin, which is even more exciting to me is, okay, what new
can it do that we couldn't do before?
So, you know, much in the same way that any form of technology that has been
involved in the creative industries and by the way, the creative industries have
always used technology, you know, back to the ponds in amphitheatres in Greek
theatre to reflect the audio and bounce it out and amplify it, always used technology
up through Lucas and Spielberg and VFX.
So actually there's no change here and it enables new forms of storytelling and for
us, those forms of storytelling, I can articulate it very simply, creatively,
which is that you as an audience member, rather than just sitting at home,
watching your TV series of Sherlock or whatever it may be, we can bring you into
that TV series to influence the story.
You might have Benedict Cumberbatch turn to you and say, okay, Howard,
you know, you're now part of my gang and I want you to prove yourself
as a detective alongside me.
Did you spot anything in the last scene that was relevant?
And suddenly you're speaking to the main characters involved in it.
So creatively, it's like a new form of storytelling that is like a hybrid version
of Hollywood and games, actually and that's very much the technology that we've
been building is to enable writers to write this sort of thing and innovate it.
Howard Bentham: And the specific area of the entertainment industry
that you're in, just describe that.
Guy Gadney: Well, we've worked a lot with film and TV.
I think that's been our core area and that includes working with the likes
of Hollywood Studios, NBC, Universal, DreamWorks, Warner Brothers, you know,
in LA, all of those guys who are looking at bringing their characters to life,
making them pop out of the silver screen in new ways, as well as here with Sky TV
we did an interactive drama for one of their shows, the BBC extending tomorrow's
world, actually as, as that show.
we did a sort of interactive version of that going into the future
a while back, and with OxLEPs support around lockdown period.
We were fortunate enough to buy the rights to John Wyndham's classic sci
fi novel, The Kraken Wakes, you know, of these wonderful 1950s classics,
which are very organic, actually, they're not technically focused.
So we adapted that into a video game environment where you are cast as
a journalist in inside the story, chronicling, I won't spoil it for
people, but, the alien invasion and how they can influence the story.
what I love about what we do is that it is a completely seamless hybrid
of technology and storytelling.
Howard Bentham: And people that have the stories, the writers, how are
they, when they come to you with this, saying, I've got this great
idea, it's an amazing story, how does it marry with the technology, with
the worries that we've talked about?
Guy Gadney: What's so interesting is it depends on the writer and we did, when
we first started building Charisma AI as a technology, we ran writer's labs with
Story Futures at the National Film and Television School and we had two days
workshop with 25 really diverse writers across, from different backgrounds,
different skill sets, different parts of the industry, they could have been film,
they could have been video games, theatre.
The writers who most were drawn to this were theatre and immersive
theatre writers, because of their proximity to audience.
So, you know, if you go to a theatre show or any live show, there's the bit
at the end where they say, thank you very much, you've been a great audience.
Well that means something.
It means that they've felt there's an energy, there's a proximity to it.
So as writers are writing, you know, what they want to do, they're thinking about
the audience, maybe much more than say a movie writer or a TV writer who's thinking
more around what it looks like on screen.
So for them, I think it was this way to explore, you know, different
forms of telling the same story and thinking, Oh gosh, I can do this now.
I can now actually bring this character to life and play with them in different ways.
So actually, I sometimes say there's an irony in the further we look ahead to the
future of technology and storytelling, actually, the more we are influenced
and inspired by the older, further back media like theatre and immersive theatre.
Howard Bentham: But there is a danger that creatives, and hence the strike you
talked about in the States, that AI could potentially take away your livelihood.
Voice Over actors, a story just recently, the person was actually driving his car
and heard his voice come on an ad and it was his voice without his permission.
So there are seemingly some worries around that lack of safeguards, and you get to
the situation where you're going to lose any control over your own IP really.
Guy Gadney: Yes and you know, there was another example with Scarlett
Johansson as well, her voice being used by OpenAI and having to resort to legal
means to stop that and it is a concern and my view on that is that if we let
things run unchecked, at the moment I think there is a mismatch of values
between the technology industries and the creative industries, where they're
looking at each other with a lack of understanding, and it's the first time
I think that there's been this sort of break between the two industries and
the technology companies are sort of running ahead without understanding
the values of the creative industries.
They're also not understanding the value of the work that is being
produced and the people who produce it.
So there is work that we need to do there.
Our view is that we are, you know, really strongly trying
to bridge these two industries.
We're trying to create the bridge and funnily enough, I sit on an advisory
group run by Innovate UK, called Bridge AI, representing the creative industries
so that our voice is heard, so that people do not rip off copyright or real
people's work and that the influence of the creative industries, as humans,
as practitioners and creatives, is heard and is felt as we move forward.
You know, let's not make any mistake about it, the creative industry is
responsible for huge amounts of GDP within the UK, and that's not to say that
we don't have a lot of and worldwide.
Without it, ChatGPT simply would not exist.
A lot of the AI that we see has been trained on creative work.
So there needs to be that value equation that is more balanced than it is now
and my sense is that, you know, we've seen this writer strikes, we've seen
the passion coming out of it and now there needs to be, as Greg was talking
about guardrails, there needs to be a set of rules, but also the creative
industries needs to engage and I don't think that the answer is to block AI
and tried to block things that generally over the last few decades has not
worked in technology advancements.
It's very difficult and is not a strategy, but to engage and to engage in the
creation of these new technologies from the creative industries is the way that
we see the world and we hope that message is going to expand over the coming years.
Howard Bentham: Grae, you started your own business, Beyond Touch in 2013.
You're helping business owners transform their organisation by,
and I quote here, thinking lean, staying energised and adapting to
change, to quote a mantra of yours.
Tell us a bit more about what you do.
Grae Laws: So I do business mentoring and group training and in essence,
we're trying to help people unpack their ideas and realise the true
value of what they're trying to do.
Whether it's, I've got an initial idea and I want to start a business, or I'm
already in business, but I've identified a barrier, or I've got an issue that exists
within my organisation and I just need to work out how to overcome that challenge.
So we work with OxLEP, other growth hub organisations, universities,
government agencies, to help people with their business challenges.
We do that through sessions that involve artificial intelligence,
as well as project management and operations process management, and
really getting into the detail of it.
So when we do mentoring, and when we sit down with individuals, it's an
unpacking exercise, we're a trusted friend, we're probing into the
real challenge that sits behind it.
We're asking why and get into the root cause of it and then we're helping
them to build action plans for change.
So it's all very action oriented and so for some business owners, one
of the biggest challenges can be, I don't have anybody that I can talk to.
I can't admit that it's not going right, or I can't admit
that I don't have the answer.
I can't talk to my family about it, I don't want to talk to my colleagues
about it, I most certainly can't mention it to my employees, where do I go?
That's the value of a good business mentor and through organisations like OxLEP who
provide those access to those mentors, it can provide a sense of relief to those
business owners and more importantly, an opportunity to refocus them, energise
them and send them off in the right direction for them to achieve their goals.
Howard Bentham: And focusing specifically on AI here, we said
with those stats, 50 percent uptake, broadly speaking, are still 50
percent that are not taking it up.
What sort of noises are you hearing back on the technology?
Grae Laws: What I'm hearing is people want to try it, but they don't know how.
So when I do my mentoring, I make a conscious decision to
use AI during those meetings.
They get advanced warning of that, but I use various tools.
My two favorite tools that I'll use on many of my sessions is Fathom.
So Fathom is an automated meeting assistant.
It comes into my meetings, it takes notes, it records the meeting, it builds
action plans, it has an AI tool built into the back end of it, so when the
meeting's finished, we can unpack more information, gain insight from that,
develop a plan, all of that information goes on to the organisation that I've
been working with, so they get a copy of it, when we meet up a second time,
we'll go back to that tool and say, okay, let's go back to our previous meeting.
Let's look at the actions that we agree.
Let's gain some more insight.
Let's talk, let's use the AI tool from our previous session to help drive it
forward and the other tool that I use in all of my sessions, which again is a
way to a soft entry point, really, for many people who want to give it a go, but
just don't understand the relevance of it and why that would make any difference
and that's a tool called Perplexity.
Which is quite similar to ChatGPT or Claude and all the
other ones that are out there.
My preference for using Perplexity is that it feels more reliable, it's more fact
based, it has less hallucinations, which is a tendency of some AI models to come
up with an answer if it can't actually retrieve something that statistically is
accurate, it will just make something up.
So Perplexity tends not to do that.
It always provides you with reliable links.
Howard Bentham: The thought of a computer having an hallucination is quite worrying.
Grae Laws: Well, it's part of the P Doom measurement.
Exactly.
It really is, and that's one of the big concerns.
I mean, all of the AI companies now are working on that.
You think about the new artificial intelligence model that's been developed,
Apple Intelligence that's gone on to the next generation of iPhones.
They've got built into the core of that to only use information
from the language model and that limits the ability for it to just
hallucinate and just make things up.
But anyway, coming back to perplexity, why I love this tool is that, you know,
I'll give you a really good example.
I was doing a one to one session with an organisation recently and this was
to develop a matchmaking application for B2B, business to business and
this person had two challenges that they brought to that session.
The first challenge was, I've done, I've written a website, but
I just don't think it's any good.
I think it might be a bit rubbish, I just don't know and the other one was, I've got
an app, I've got a whole lot of processes, I've got a design, I feel like there's
IP here and I just don't know what IP.
I've had a look online, you know, at the IP office and I
just don't know what to do.
So I said, I'll tell you what, let's jump into Perplexity
and we'll nail both of those.
So we did, we jumped into Perplexity, we did the IP one.
In actual fact, because Perplexity has its own language model, but most importantly,
it seeks to find live examples, real world sources of information,
reliable sources of information.
The natural factor becomes an extremely useful tool for analysis and because
you're having a dialogue and I do encourage people, by demonstration,
to start the conversation and keep that conversation going.
We were able to identify which clauses within which types of IP were
appropriate and the reasons why, we're able to then say, condense all of
this into a table, give me the links to the IP office so I can do more
reading about that and then we repeated that same process for the website.
Which was, who is best in class?
Who are your competitors?
Well, there are quite a few, I don't really know who The
most obvious competitors are, okay, let's ask perplexity.
Give me the top 10 UK companies that do this, this and this.
It provided them.
So now we need to understand more the value proposition of each of these
organisations and how that will be of benefit to this person, this user
group, put it into a table and it did.
So there you go, there's your first bit of competitive analysis.
So now, and it's got the links to their websites, why don't you, maybe as an
action out the end of this, go away and just have a look at some of these
websites and then reflect on what you've put across in your website and let's
use best practice to actually make sure that we can give you a fighting chance
to be a comparator or exceed expectation when people are looking for you and may
have found another one to compare with.
Howard Bentham: So clearly, the tools are out there.
Grae Laws: They're there.
Howard Bentham: It's that leap from, okay, I'm the business owner
thinking, right, yeah, I need to do this, but who do I speak to?
What do I do now?
Guy, what would be your advice?
Guy Gadney: I'd speak to Grae.
Howard Bentham: Well, let's do that then!
Guy Gadney: I think, I think the first thing is to work out
actually what your business does.
With any new technology or anything like this, you can be seduced by
bright, shiny things and oh, look, I should be using this and it can deviate
away from what your core purpose is.
Now the flip side to that coin is maybe you do need to change your core
business if it's not working, and AI can give you that pattern matching tools.
I mean, Grey's example was brilliant, which is the big power struggle at
the moment is around search engines.
So Google has its own AI and then ChatGPT has SearchGPT.
Now the reason for doing that is that if you think about how you search
or have done to date, you get a list of responses on that first page.
What AI is going to do is going to do exactly as Grae said, which is
synthesise all of that, work out what actually the key insights you want out
of that and then write it up for you.
So suddenly you're saving shed loads of time of moving between different
pages, pages one, two, three, and all of that and you're getting
that information in a heartbeat.
Howard Bentham: It's doing the heavy lifting, isn't it, really?
Guy Gadney: Absolutely, and providing that little bit extra as well, I think
is providing you something that you may not have thought about an angle on your
business, which you may not have seen.
So I think to know what your own strengths are as a business owner, what you are
in business to do is the core and then use this as a way to provide further
insights into that and the pattern matching piece, I cannot overemphasise
enough, this is the core of AI, the ability to spot patterns and if you can
spot patterns, you can start to see where opportunities are in the future and where
issues may be arising and if you can do that, then you're going to de risk
your business and that's a good thing.
Howard Bentham: I can hear the audience shouting that how much does it cost?
Is this expensive?
Grae Laws: No, it's free!
And that's one of the greatest challenges for all of these kind of developers
of software and those who are spending millions and billions on their large
language models and things like that is actually the business case is one
where in which it's almost all free with literally every application that I've
ever tried, there's a free version and it might limit you to how many iterations
you can do of whatever this tool is and that might be per day, per hour, per week,
per month, whatever it is, but there's always a free trial version of it and
there's usually a lite version of it, so the classic ones of Claude and Gemini
and OpenAI's ChatGPT and Perplexity, all of those have a free version, a
lite version, but you can pay and I wouldn't want to go on camera because
my business partners listening, I'm sure and they would say, you're spending that
much on your AI tools, are you Grae?
Okay.
But I do subscribe and have paid for accounts because I see
the value in them, I really do.
But we're talking tens of pounds per month.
Guy Gadney: And this presents a problem for the UK, you know, taking it suddenly
very high up the level, which is that the reason that those companies can
afford to do that, especially OpenAI, is because they've got the funding to do it.
So the cash burn of OpenAI is eye watering.
I believe it's something like five billion a year that they are spending and not
getting back in revenue, but they can afford to do it because they have the
venture capital backing to do it and in fact, you know, recently Apple came in
alongside Microsoft to help out with that cash burn because it was looking wobbly
for a moment, which is interesting, given, you know, how much we're starting
to rely on these tools and for the UK, because we don't have that level of
financial support, we don't have that gearing in our venture capital, it means
we struggle as a nation to create our own Open AI, or our own perplexity, or
our own Anthropic, or whatever it may be.
So, I think as we start to look at how the government looks at AI, what its
strategies should be, we need to be able to create an environment where
we can form a company that can give away their software, because they've
got the cash runway to do it and, you know, remember that every time you put
something into ChatGPT and you're not paying for it, it's doing two things.
One, it's costing OpenAI and the other one is that it's using
your data that you put into it.
So there's a risk reward piece here.
But I think as a country for us to be able to compete on that level,
internationally and create those sorts of competing companies, we need
to slightly reframe, I think, our investment to enable that sort of user
acquisition, which is what it's doing.
The reason that these things are being given away for free is to
acquire users that you can then flip over into paying customers and
at the moment, we don't have that environment in this country to do that.
Howard Bentham: That's really interesting, just the macro economics of it, how
these organisations are actually going to make money as probably a conversation
for another podcast I'd say, but again, focusing on our audience here
at OxLEP as well with trying to get that information and indeed the sort
of avenue to the expertise and the funding, a conversation with OxLEP is a
really good place to start, you'd say.
Grae Laws: A hundred percent.
I would absolutely agree and we've got great organisations that are in
Oxfordshire who have a background in AI.
We've got some excellent speakers, some incredible minds, you know, some of
the greatest innovation that's actually come out and certainly in terms of where
education crosses over with industry and AI has come out of Oxfordshire and, you
know, really we build on experience and you know, in a way we are all language
models as human beings and we build and we soak up through us osmosis our
understanding of the industry that we're in and it moves so quickly that you need
to speak to people who have their finger on the pulse, because I can recall the
very first OxLEP workshop that I did on Artificial Intelligence coincided with Sam
Altman being kicked out of OpenAI and then being brought back in and then leaving and
then coming back and it was literally days before I was doing a workshop and I had
the whole thing set up, all of my slide deck ready, everything was there, they
had the whole history of AI, where the investment was, who the big players were,
and I had to keep going back into it.
So right, okay, he's out.
No, I got back into it, he's back in again, but it moves that quickly
and it's certainly the case that I would say to any business that, you
know, if you want to do your research into this, maybe go to YouTube.
That is one of the biggest sources of information that I use.
I follow people like Peter Diomedes and Matt Vidpro, Matt Wolf, to name but three
organisers or individuals who really have their finger on the pulse and as you
were saying, you know, a little earlier about how people consume podcasts, you
know, I listen, I don't necessarily watch, but I actually play along because
they actually say that the next five business applications that have just
been released, it's this, this, and this.
I'm going to go through each one in turn and I am there with a browser open and
I am following along and trying it out for myself and there's always a free
version of it and some of them I just bash them up and say, nah, rubbish, don't
want to use that one, others I think, ooh, actually that could be a keeper
and then I can bring that information then in to conversations that we're
having with business leaders, you never stare into infinity when somebody
says, which AI tool should I use.
But it's certainly based on very, very recent information.
Howard Bentham: It's a good time to bring in OxLEP's Communications Manager,
Rob Panting, into the conversation.
Rob, what are businesses telling you about incorporating AI
into their everyday operations?
What about the demand to understand and implement here in Oxfordshire?
Rob Panting: Thanks, Howard.
Fascinating discussion already.
I mean, it personally picked up a great deal of knowledge and understanding
as to what AI can offer businesses and can offer individuals this morning.
I think from a small business perspective, which obviously generally is the audience
that OxLEP works with, I go back to the Business Support Tool, our online triage
tool that we oversee, which gives us the understanding and the finger on the pulse
in terms of what businesses are asking.
In terms of AI as a individual topic, we don't tend to have a great deal of people
coming forward saying, you know, we wish to understand AI, more efficiently per se.
But I think some of the topics that we mentioned earlier on, things like growing
customer base, things like managing finance, things like developing better
marketing communication strategies.
AI is very much embedded in all of those desires for small
businesses to achieve those goals.
So I think people are asking about AI and asking how they can implement
it in their business, not necessarily coming forward and saying, we need to
find out more about what artificial intelligence can offer our business.
But in the context of growing customer base, managing our finance better in the
context of that and implementing AI from that point of view, I think there's a
huge amount of interest and Grae is very much sort of delivering that support
from our perspective on the ground and I think probably the information that
you're receiving from small businesses is perhaps positioned in that sense.
Howard Bentham: Yeah.
You hear the word streamline, Guy.
How can AI help streamline business processes?
Guy Gadney: So the streamlining question often attracts words like productivity
and efficiency and those sorts of I think that as long as there are barriers
to your business, whatever barriers you identify, there is probably a way that
AI can knock down those barriers and if that is in marketing communications,
you know, you can't reach a particular audience or you're not getting traction
or not getting customer take up in certain areas, then what we find
certainly is that you can recraft the tone of a marketing piece very, very
quickly with AI to match communications into a very specific demographic.
So let me give you an example, with OxLEP support, we produced this
wonderful game, for The Kraken Wakes and as we are marketing that, we are
marketing it, not only as a game in its own right, but we have videos
of the game that go up on YouTube.
So, to do that, when you upload a piece of video to YouTube, you have a
bit of text that describes the video.
Now, normally what I would write is something like, this is a
wonderful adaptation of John Wyndham's novel, The Kraken Wakes.
Okay, so that's me saying that.
However, the YouTube algorithm, reads it in a different way.
It reads it in a way that is either going to be a way that puts it up
the rankings or knocks it down.
So now what I do is I go over to ChatGPT and I say, here's
my description of this game.
Now rewrite that in such a way that it's going to be more
attractive to YouTube's algorithm.
It then gives me another piece of text that I put into the comments field and
that increases the viewers tangibly, we noticed an almost immediate difference,
when we recraft that in a particular way.
Now what's slightly scary is that we're now getting the machine to write text
so that another machine can read it.
But acknowledging, as in any good piece of marketing, who our audience is and
that our audience actually is the YouTube algorithm to increase the visibility of
that, was a key part of that campaign.
So that to me is streamlining.
It's the ability to reduce the barriers to reach certain markets, be more flexible,
more agile and that an individual marketeer within our team can now do a
lot more and reach a broader audience.
You know, as a specific example, I think there are many ways that processes
can be made easier in this, but we're at the beginning, you know, we're at
the beginning of a long journey with AI and I think part of the things
that we're hearing today and part of the problem actually and to viewers
and listeners of this podcast is, you know, the question is, but what is it?
And the problem is that it's like a tsunami, it's
really broad and really deep.
There's not one nice little wave that you can go, Oh, look, there it is.
It's not like a metaverse or text messaging or websites,
this is really broad.
So trying to say, How does it actually fit for my business?
It's a challenging question to answer, and I go back to it.
I think Grae was saying similar, which is first understand your business and where
your barriers are to that business and then look at what the solution may be.
Chances are there's an AI for that, but that's probably the first step.
Howard Bentham: Grae, let me put my PDoom, stroke cynic hat back on.
Is streamline another word for redundancy in this context?
I mean, there is a genuine fear amongst unions and workers that AI is going
to make thousands of people redundant.
Grae Laws: I think that's inevitable.
I think the way that most modern thinkers look at the change in
employment as a direct consequence of AI is basically it's three to one.
Three jobs go, one job comes.
But that's over a long period of time and don't forget, we have the
whole, you know, kind of global population is actually now in decline.
You know, we have birth gaps in almost every nation.
So in actual fact, in the future, there will be less people and in
actual fact, you'll still have the same infrastructure that needs to be supported.
So how do you keep the systems running?
How do you do all those mundane tasks that nobody wants to do
because there aren't enough people to actually take those roles?
Now, because we, this is something that plays out over decades, it was
hoped by some of the great leaders who were driving forward with Artificial
Intelligence, machine learning, and also embodied artificial intelligence.
I put it into robotics was that it will be a gradual transfer, whereas
there were less people to do the jobs, suddenly our robots who were, you know,
had their artificial intelligence built in would replace them and it would be
a nice, smooth transition and actually, that's not what really what's happening.
Actually, it's an exponential curve in terms of the growth of AI
and also the implementation of AI within robotics, so it is a threat.
PDoom.
Yes, I get that.
But, you know, I always encourage people to embrace things and
have a lived experience of it.
You know, when I was back in the 1990s, I was a printer running printing presses
and I remember a Mac operator coming through to me saying, Grae, when you
finish that print run, come through and I'm going to show you something.
I stopped the press, went through, pointed at his screen and said, what's that?
And I said, it looks like a bit of artwork.
Because.
It's not.
It's called a PDF, and it's been sent to me down a telephone line on something
called email, and I looked at him like he'd just used words I'd never ever heard
of, but when he actually explained the significance of that and how it would
change the way I did my job, it gave me food for thought, and I thought,
actually, if you were to suspend disbelief that this PDF technology that means I
don't need to print things anymore will happen and that everybody will have
emails and can send them things between them, then hey, I might be out of a job.
So when I went home to my wife, first thing I said was, I
think I need to buy a computer.
I think I need to understand what this is all about and I would say, you know,
that is just an example, I would encourage everybody today to be thinking about
how could I learn something about AI?
How can I use some of those simple tools to augment what I do?
How can I demonstrate through the application of artificial
intelligence in my day to day that I can create additional value for
the organisation that I work for?
And embrace some of those things that will remove those boring, repetitive tasks
that you don't like doing, I don't like doing, but AI loves and in doing so, allow
you to maybe get a better sense of self worth, improve the value that you create
for the organisation and give you that longevity in your career that you deserve.
Howard Bentham: Rob, is there a risk that as AI becomes more prevalent,
current working practices will change or as we're discussing, disappear?
Rob Panting: I guess I can come a tip from my own personal perspective.
So from a communications and marketing point of view, like
Grae has just reiterated, I've had to embrace AI within my job.
Guy made a great example earlier on in terms of the use of YouTube
and how the algorithms that have been built into YouTube can support
your word to reach a much wider audience than perhaps a typically
organic approach to these things.
Again, speaking to businesses in Oxfordshire, there's an attitude
that people look to embrace AI and perhaps approach it from a positive
perspective and not be fearful as to what it might do to you personally.
I think if you approach it from that perspective, come at it from
a position of strength, come at it from a position of knowledge, which
Grae has just emphasised then I think you're in a much better position to
understand the potential benefits of AI.
I think there's no doubting that it will change our working culture and the way
in which businesses operate, perhaps do things differently, but you're better
approaching it from a position of being informed and understanding rather than
a pessimistic position where actually if you bring that negative approach to it,
you're probably not going to see the best of AI and certainly from the cohort of
businesses that we speak to on a day to day basis, I think the majority of them
are approaching it from that position.
I think the danger with small businesses in particular, so those
with staff numbers sort of 10 and below is having the thinking space.
Greg reiterated that right at the start in terms of how small
business owners find the headspace to think about AI and understand it.
So I think coming at it from a position of positivity is always a good thing.
Howard Bentham: Guy, Grae and Rob, thank you for the moment, fascinating stuff.
We'll chat again shortly.
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Howard Bentham: Let's speak more with Grae Laws, Managing Director
of Beyond Touch, and Guy Gadney from Charisma AI based in Oxford.
Guy, I want to delve into the ethics of AI and the safeguards
that exist, or perhaps should exist.
Are there ethical issues around AI in your thoughts?
Guy Gadney: Yes, I think there are ethical issues and I think if you go back to,
if you remember that scene in Jurassic Park, in the first one, where they're
all sitting around, having dinner and Jeff Goldblum, I think it is, he says,
you know, you scientists, just because you could, didn't mean that you should
and I think there's a real parallel and I sort of hold that line in my head a lot.
There is so much that can be done with AI and we do need to have a little bit
of restraint to say, should we do this?
Now, that's all nice and easy to say, but then from a practical
perspective, what does that mean?
Well, I think there are two examples from my side.
One is when we started building Charisma AI back in 2016, 2017.
Actually, one of the first things we did was we wrote a white
paper about bias in AI data sets.
Now, at that point, it was like, why are you thinking about that?
But we were thinking about it because we knew that as we were bringing the
character, these virtual characters to life that you were going to talk to, they
may have biases and we wanted to know what those biases were, so we wrote the
white paper for that and that, I think, was the start of a bit of a journey
around ethics, around, you know, where you source your data from, you know, is
it someone's copyright, is it angry data, like on social media, on some social media
platforms, is it, academic data, whatever.
So I think we've always kept that and then in fact, we're working on a big Innovate
UK funded project at the moment, which we're halfway through and in the original
bid application, we costed in a full time digital ethicist and what I love about
what she's doing, she calls it consequence scanning, which is that she's involved
in all of our meetings, you know, exec meetings, production meetings, just got
full access to everything that we do and she just scans for intended and unintended
consequences of what we're doing.
She's always said, that doesn't mean that I'm going to block you, but it
means I'm going to raise it and then you can then do the risk analysis to
think about whether or not you're doing something which is going to impact
someone's job or whatever it may be.
So the ethics are, I think, something that people should think about, and
it doesn't mean you have to move away from your strategy, it just
means you need to think about it.
And our view is that if you're thinking about it, you've got that, you know,
should we question running through your mind, you're probably about 60
percent of the way to doing good.
Howard Bentham: Because it feels, from what we see in the media,
that society is, shall we say, a growing number of steps behind the
technology as the technology advances.
That's going to mean that our laws become outdated or obsolete
and that we, as you've used the words, unintended consequences.
We're sleepwalking into a world of those unintended consequences.
How can we stop that happening?
Guy Gadney: Well, I think we're going, regulation wise, we're going faster
than a lot of governments have ever gone before, you know, the AI acts that first
came out of the EU, there's a draft in the House of Lords, that's going out
into the US as well, are faster than how Europe and the rest of the world
responded to the internet and you know, the GDPR legislation around personal
information has had a massive, and I think very positive, impact on society
as people have started to realise the value of their own information.
So I think that they have started to realise that this needs significant
regulation around it, not least because of society and indeed, you
know, military as a defense mechanism and attack mechanism as well.
So, I think they're going faster than they have done still, it's slower than
the technology industries and there is a tension between innovation and
regulation that I hear the whole time and the innovators don't want to be slowed
down because they feel that they're going to lose a competitive commercial
advantage because of regulation.
At the same time, we've also seen some pretty tragic examples where innovation
has been, you know, the number one thing, that people have gone down that, that's
the pathway and conforming to regulation has not happened, that tragic case of
the submarine going down to the Titanic.
Well, that was a conflict between innovation and safety and regulation.
So there is an absolute, very clear reason why these things need to
be in balance and my sense is that people are very focused on this.
You know, the first all party parliamentary group in the UK on
AI, I think, started in 2016, 2017.
I was a part of it and it was sidelined by Brexit because the parliamentarians
were focusing on having to deal with that.
There was a lot of work they needed to do and they acknowledged that
was going to set us back on AI.
But it's coming back into play again.
So I think it's naturally slower because the regulators aren't sci fi writers,
they don't look too much into the future, they look into what's happening right now.
But my sense is that it's being given responsibility
and an airtime that it needs.
Howard Bentham: Great, Guy raised a really interesting point there about bias.
AI will have been input and trained because we've talked about
the training of it by someone.
Does it leave an inherent bias in the system somewhere?
How do you eliminate it?
Grae Laws: With great difficulty, I would say, it's almost impossible
to remove it once it's there.
You ask Sam Altman or any of the leaders of those organisations who
are developing large language models, exactly how does it do the sorting and
processing and get to a point where that foundation model can be used?
They can't really answer it and they can't easily go in and reverse engineer it.
Now what they are trying to do is do synthetic data, which actually has already
been pre sanitised to remove bias and think of it that it's one large language
model using algorithms to train another large language model and in doing so iron
out some of those creases and you've got like three different classes in a way.
You have the closed language models that the likes of OpenAI have
and Grok, Elon Musk's X model.
Then you have the Open models, such as Meta's Lama 3, which is available for
anybody to use as a language model.
But of course, nobody really knows what's inside those.
They won't admit to what's in there other than just to have to accept
that, yes we scraped the internet.
Yes, there is copyright issues, probably, you know, yeah, we have to accept that.
But actually that fine tuning is actually quite often done by humans who have in
their own innate biases, which creates this third requirement in a way, which
is, and this is a national infrastructure level, and that is for governments to
own their own language models and that's where we're going to is actually safe,
reliable, sanitised language models that can be used freely or at minimal cost by
businesses to build applications that will be used in the real world by individuals,
by businesses and most importantly, by people who work in government themselves.
Howard Bentham: There's the morality side of this, cheating in exams, passing off AI
generated work as your own, stealing IP.
No one voted for AI, it's just imposed on us.
Is there a real ethical issue around that?
Grae Laws: Impose, interesting word, I guess it's like gas.
It's all around us and you can't move it out of the way really.
Being it's been here more than a decade and the more we use it, it's
positive affirmation for any developer to carry on doing much of the same.
So we ourselves are feeding the machine that creates the thing that we, some of us
or some people may not want from an ethics point of view, I mean, just maybe you
can scale it out in a slightly different way and ask people who have environmental
concerns about industrialisation and say, so what do you think about the
energy use of large language models?
You know, does it bother you that every single day, ChatGPT alone
requires 17, 000 homes worth of energy just to keep it ticking over?
Every time you put a prompt into a ChatGPT or Perplexity, it's using
one whole bottle of drinkable water per prompt, think about that.
Think about the sheer scale of the technology, the compute that's
required, all of those processors, all of the electronic waste, all of the
thermal pollution that's been created, all of these things are byproducts
and they're still ethical concerns.
Now, are you willing to put them all to one side, because you believe that
overall the net benefit to humanity through developing even greater language
models than ones we already have can put us at ease in thinking actually,
you know, we are using a whole lot of energy, you know, the US estimate that
next year, 6 percent of their total energy will be used by artificial
intelligence and it will keep growing.
Just this morning, it was announced by OpenAI that ChatGPT 5 is coming out.
Okay, so this has 100x the compute of the current live chat GPT,
100 times the processing power.
Now, in terms of an order of magnitude, our experience means it will feel
like it's twice as good because it's not a direct correlation between
compute and the order of magnitude, but we experienced, but this isn't
slowing down, none of this is.
We will keep consuming energy, we'll keep consuming water, there will be
a greater demand on us to be able to do it and is that what you want?
Because that's what's going to happen.
Howard Bentham: Yeah, your idea of a tsunami sounds absolutely right.
Guy, just bringing it back to our audience here, how can business leaders
support their employees to learn about AI and try and get behind this, encourage
them to use it to support their work?
Guy Gadney: Yeah, look, and I think there's a connection here with your
last question about no one voted for this and the reason no one
voted for it is because it's not a government initiated technology.
It was initiated by market forces, you know, it was initiated by
industry and it's had a huge amount of tech up by people.
So in the sense of how someone might vote for whether they want
something or not, buying it is the market's way of doing that.
So I think if you're looking at a business and you're looking at your own staff.
The first question is to ask them, are they already using it?
Are they using it at home?
Are they using it in their day to day?
Have it is in a safe space question.
So if it's a hypothetical communications manager called Rob, who happens to be
working for an enterprise partnership and his boss says, Rob, are you using
ChatGPT to write press releases?
It's okay for Rob to say yes, because sort of everyone else is doing it.
The education was fascinating, so from the work we've been doing with Oxford
University and various schools, we know that within about two weeks of
ChatGPT launching, pretty much every teacher and every student in the UK
was using it, but no one would say it.
Now it's starting to evolve into curriculum in really lovely ways,
which is here is a piece of prose text that was published and here's another
one which was written by ChatGPT.
Compare and contrast why these two pieces of text are different.
So that's getting the student to think about it, acknowledging
the existence of it.
So I think the first step is acknowledge that a lot of people are using AI,
ask your staff, think about your own strategy with OxLEP's support in that
space of course, and do a quick audit.
You know, where are you already using it?
Where have people got ideas?
Where have the employees got ideas of, gosh, wouldn't it be cool if we had a
corporate, you know, perplexity account?
That would make my life easier and discuss it, it's an open conversation.
Howard Bentham: As OxTalks has become the confessional now, Rob?
Rob Panting: Well, yes, I mean, I think, yes.
Howard Bentham: Is that a yes?
Rob Panting: I would be lying if I said that I didn't embrace AI.
I mean, yeah, picking up on Guy's point there just briefly, I, I think
from marketing communications, public relations, journalism, I think it would
be fair to say that probably we are the group of professionals that are maybe
most skeptical in terms of the use of AI,
the potential for it to take over our jobs.
I think we see ourselves as the creative guy that works
within the creative industries.
I think taking Guy's business approach in terms of embracing AI is the way to go and
I think similar with us you know, there's a number of occasions where I've gone into
work and perhaps I've been struggling a little bit to come up with the right words
to try and portray a particular programme that we're launching or a particular fund
that we're putting out and actually using the AI to help me to get off the page,
you know, get my ideas off the page and to push me in the right direction as to
what's going to work best to allow me to communicate with our target markets has
been massively helpful and like Grae says, the majority of this stuff is there for
you to use, it's free to a certain point.
You would be silly not to embrace it into your everyday operations,
particularly I think from a comms and marketing perspective.
Certainly if we're an example of that, you know, we're using it to a relatively
small level, I would say, but undoubtedly it's helped us to reach new audiences
and probably in turn helped people like Grae to connect with businesses who need
the support, it really starts from there.
Guy Gadney: The one caveat, Rob, I'd say on that is that the way OpenAI
works is that it uses what you type into it to train its own model.
So in essence, anything that you're typing into ChatGPT is going to be public
and there was an example recently of a chief financial officer who was looking
to summarise what the financial state of their business was and so they typed in
all of the financials for the company and said, please summarise this, which then
meant that all of the financial states of that company were then searchable in
OpenAI and our view on this is that it is important for businesses ultimately
to have their own sovereign model, we'll get to that in the market at some
point in the coming months and years.
But just be aware that any personal or confidential information that goes
into ChatGPT will then form part of its model and will likely be public.
Grae Laws: I might add to that and just say perplexity doesn't do that, Claude
by Anthropic, doesn't do that and if you have embedded Microsoft 365 Copilot
into your enterprise, then it has a very clear distinction between I can search
the world wide web, flick the switch across, I can search and use your internal
data and it works exactly the same way.
So if you were screenshotting your annual report or your cash flow
forecast and say, give me some insight, where am I going wrong?
That isn't going to inform the language models that those organisations use.
But it's a point well made, the free versions are almost like you're the
product and your data is helping that tool understand the relationship
between numbers and the written word and your prompt and what that means.
Why did that human ask that?
That, you know, kind of natural language processing.
Howard Bentham: Let's finish with a bit of a checklist on what
business leaders should do if they're seriously thinking about
adopting AI into their organisations.
Short and sweet, Grae, give us your thoughts.
Grae Laws: Contact OxLEP, number one, do the diagnostic tool,
and then you need to experiment.
Start with safe tools, I can't reiterate enough the importance of go
to YouTube, it's a single best place where you can search for content.
It's the second biggest search engine in the world and it actually has
less bias than the number one search engine tool in the world, Google.
So go to YouTube, find some of those big organisations and individuals who actually
do regular, kind of weekly or bi weekly shows introducing some new technologies.
Talk to your peers, as a business leader about what tools they use
and something that Guy said earlier, which is talk to your employees,
find out what they're using.
It's that person who is sitting in the cafeteria on their mobile phone
is using the app that your, you know, head of operations should be doing.
Understand from best practice, join peer groups in your area, listen to
what other people are using and just try these things, try before you buy,
you could even go to something like poe.
com, try all the language models for free, see which one you like.
Go to something like huggingface.
com, if you're really into this, you can find the language models.
You can find, you know, lots of user examples of these types of things.
Find out what works best for you and then give it a go.
Guy Gadney: I would start by saying that probably businesses are already
using AI and so the recommendation is to understand how you're already doing it.
Even though you may not know, you probably are and build it from there.
I think as we head into the next few years, you know, there are
challenges for businesses around inflation, macroeconomic challenges.
So there are going to be ways in which businesses need to respond
and AI can be a tool to help you respond to those situations.
So you're already doing it, do a quick audit, as you say, talk to OxLEP, talk
to employees, that person who's in the cafe on the app could actually be using
the app that could save your business.
So, you know, find out what it is, you know, not that your business may
be a problem, but it could be the one that elevates it suddenly as well.
So I think people know more about AI than they think they do already,
actually and a quick, I'd say quick audit, work out where you want to go.
And then as with saying the barrier to entry is low, so give it a go.
Howard Bentham: Both of you, again, briefly, if you would
gaze into the AI crystal ball.
What's this space going to look like in five years, ten years time?
Guy Gadney: Gosh, when you said five years and then went 10 years, I
thought you were gonna bring it down.
Let's go, five years, two years.
There are a couple of macro trends that tend that I see, and I see these coming.
The first one is that in any new technology advanced, it goes
low bandwidth to high bandwidth.
So text, static image, audio, video, and I think we're seeing the
same thing play out now with AI.
We saw ChatGPT creating text, and then it was audio, and then that.
We will move into everyone having access to text to video, you
know, very soon and I think that is then a qualitative standpoint.
So we see the innovation and then the quality increase.
That is going to change an enormous amount of people's work, people's lives.
There will be issues around deepfakes that we already know, that we'll
have to solve along the way.
So I think the, to my mind, the one I'm watching right now is generative AI video,
and I think that's going to be critical.
I think the other thing that we'll see is going to be the
fragmentation of language models.
So we've got the ones that we mentioned around OpenAI, the big two or three
around the world and these will then fragment into each business has its
own, it'll be each country has its own sovereign LLM, then each business
has its own LLM and then all of us as individuals will have our own ones that
are the AI version of your answering machine message, you know, that responds
on an individual basis and I think we will see that, in the next little bit.
So I think those are the dead certs.
The other ones are, you know, are the new and sort of advancements
and innovations that we'll see.
Howard Bentham: What about you, Grae?
Grae Laws: What Guy said.
I think it's going to be exciting times.
There's lots more investment needed.
Guardrails have got to be put in place.
We've got to embrace this.
Every single living human being that would wish to do so ought to embrace
the technology if they can, even in a light touch sense, because if they don't
embrace it, it will embrace them and then maybe they're not in control and
I think that what we'll see within 10 years is, you know, artificial general
intelligence where we suddenly realise that there are technologies out there
that most definitely exceed our capability at every level, in every discipline.
That's a given and I just hope that we don't move beyond that to
anything else, I'm sure we won't.
Howard Bentham: And the one thing you want to see AI change that it's
beyond its capability at the moment, the one sort of magic bullet or one
thing that it solves globally or just for humanity, what would you say?
Grae Laws: Poverty.
Complete that one, mate.
what I'd ask GPT.
Guy Gadney: Yeah.
I'd go climate change.
I think a lot of the challenges that AI researchers we've seen outta DeepMind
and so forth have been around Space Invaders or Go, or Chess or, and I
don't like those 'cause there's zero sum games win or lose against a human.
So you are, I, you know, I sort of stand away from that.
Give it something challenging, which is an open-ended very complex pattern,
like climate change, poverty, things that are for the betterment of human
evolution, and you know, and give us the answer and it'll probably come
out saying it's 42, and that's not going to help too many people, Douglas
Adams fans, but let's give it a go.
Howard Bentham: Huge thanks to Grae Laws, Managing Director of Beyond
Touch and Guy Gadney, CEO of Charisma AI based in Oxford and a big thank
you also to OxLEPs Rob Panting too.
Thank you for listening to OxTalks.
There are a growing number of editions of OxTalks available from
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