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'Companies are not going to take the lead in making AI a nice transition for their workforce'
FRANCE 24 English
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2/7/2025
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00:00
This is Apropos.
00:04
Global experts are here in Paris this week to debate the threats and promise of artificial
00:09
intelligence.
00:10
The summit is aimed at finding common ground on the rapidly evolving and disruptive technology,
00:16
as well as examining how to keep France and Europe on the map as credible contenders in
00:21
the AI race.
00:23
Paris is expected to announce major investments in the fast-moving technology running into
00:27
the billions.
00:29
Peter O'Brien is there.
00:31
He spoke earlier with Camille Knight.
00:34
This is the first of two science days and boffins that have gathered here from around
00:38
the world were very, very excited, particularly because of this recent breakthrough by Deep
00:44
Seek.
00:45
The prospect that we're going to be able to deploy advanced, powerful AI models at a fraction
00:51
of the cost has got smaller players in France very excited.
00:57
Now a lot of big names expected at the summit.
01:00
Peter, you were able to speak to Yann LeCun, Meta's chief AI scientist.
01:04
What did you learn from that conversation?
01:09
Well I wanted to ask him whether he felt vindicated because he's French, of course, and he's been
01:15
absolutely championing a open source approach to AI for years now.
01:20
That's what Meta does.
01:21
They have these Lama models that are very powerful.
01:24
They get copied around the world because they are open source.
01:28
And he's been banging the drum and criticizing open AI, for instance, for closing off access
01:34
to its models.
01:35
So when Deep Seek came along and blew a lot of the competition away in terms of efficiency,
01:40
he sounded pretty happy.
01:42
I also talked to him about his boss, Mark Zuckerberg.
01:46
He said that more masculine energy was needed in corporations.
01:52
So when it comes to AI and developing AI, I asked Yann LeCun whether more masculine
01:58
energy was needed there as well.
02:00
I had a big project called Zeta, whose goal was to basically build a large-scale LLM.
02:08
And then for various reasons, a smaller group in France decided that they needed LLM for
02:15
their project.
02:16
And it turned out to work better than the big ones.
02:19
It's not because of the quality of the people.
02:20
They were both very talented, but the problem was that one of organization and management,
02:31
the small group had a lot of autonomy, a long leash, was relatively small, and had a lot
02:37
of freedom, essentially.
02:39
The big group was kind of top-down managed, more directed, and in the end, a less efficient
02:46
way of organizing research.
02:47
And so we see the same thing with diptych.
02:49
Nothing to do with masculine energy or lack thereof?
02:52
No, no.
02:53
Not at all.
02:54
That doesn't come into it?
02:56
Absolutely not.
02:58
Peter O'Brien there reporting.
02:59
Well, for more, we're joined now by Simon Coulton, Professor of Artificial Intelligence
03:04
at Queen Mary University of London.
03:08
Thank you so much, Simon, for being with us on the program.
03:11
Let's start with the timing of this summit, coming as it does in the aftermath of the
03:16
emergence of DeepSeek.
03:18
How much of a game-changer do you think this Chinese technology is?
03:24
I think it is a big game-changer.
03:27
Of all the various predictions of how this is going to change AI and AI funding, I think
03:32
the one which I think is most sensible is that we'll see this as a World Wide Web moment,
03:38
where it became a lot easier to make, post, and find web pages through the World Wide
03:43
Web.
03:44
The Internet was not so usable before that.
03:47
And now AI has become 50 times cheaper, if you believe the figures, to operate.
03:53
And that can be just the beginning of it.
03:56
If there's as much money poured into scaling down AI models as there was into scaling them
04:00
up, then we can imagine hundreds of times cheaper.
04:03
So that will make it available to organizations to use at scale a lot more often, a lot more
04:12
down the tech chain, so that we will find that it's an explosion of usages of AI.
04:19
And we might find that that will mean that money flows from the kind of data center area,
04:26
where we're building up these huge banks of graphics processors, into more startups, into
04:33
more thin-layer companies, which are able to run these models on their own machines.
04:39
And then if the models get even smaller, which I think is quite unlikely, to be perfectly
04:43
honest, but if they do get smaller and they can be crammed onto a laptop, the really good
04:48
models, not the smaller distilled versions of them, if the really good ones can be crammed
04:52
onto a laptop or a mobile phone, then that is a huge game changer, because we don't need
04:56
quite so much of the GPUs available.
04:59
So it could be a pivotal moment.
05:02
And then, of course, there's a whole geopolitical element to it as well, as well as a financial
05:06
element.
05:07
So I think it will be seen, ultimately, as a big moment in the tech arena.
05:13
A big moment as well.
05:14
It also wiped a lot of money off the value of some of the biggest players in the sector
05:18
initially.
05:19
Does this suggest that American tech companies who pledged billions of dollars in AI investment,
05:25
that perhaps that was a little short-sighted?
05:26
Possibly.
05:27
Certainly, the market thought that.
05:31
The timing was just fabulous of the release of this.
05:35
Not only was it just a day or so after the announcement by the American president of
05:40
the Stargate project, $500 billion is being pumped into infrastructure like data centers,
05:46
but it was also just before the weekend.
05:48
So that meant that the market had time to enact a kind of epic overreaction to it.
05:55
It wiped $600 billion off the market capital of NVIDIA and a trillion off the NASDAQ in
06:01
total.
06:02
However, I kind of believe the line that if you make something cheaper, people will buy
06:08
it more.
06:09
There's an economics theory about that.
06:12
So all of this is still going to be run on GPUs, and I don't think it will mean at all
06:17
that NVIDIA will suffer in the long term.
06:19
I think there'll be equally as much compute required for all of the extra usages of GPUs
06:28
that will be enabled by this leaner, slimmer technology.
06:32
And Simon, there's a global AI summit taking place in Paris this week.
06:38
We've been referring to it earlier.
06:40
The UAE has just announced that it'll be investing up to 50 billion euros in a data center here
06:46
in France.
06:47
What does Europe need to do at this point?
06:50
Is it those kind of investments that we need to be securing in order to become really a
06:55
global player when it comes to artificial intelligence?
06:59
Yes, I still think there's very much a requirement for compute.
07:04
Ask any of us in academia where we don't have access to these huge tens of thousands of
07:09
GPU units and we'll tell you that, yeah, compute is key.
07:13
All of my PhD students are always desperate to find GPUs in order to train their models.
07:19
But there are other factors at stake here that will need to change as well.
07:24
I try and take a balanced view.
07:25
I understand the value of AI safety and ethics, but there are reasons to think that the
07:34
European Union is being overly careful and that might stifle innovation and that
07:42
ultimately it means that companies can't take risks.
07:46
There's going to be battles over copyright, so over copyrighted data enacted in various
07:53
industries. So there are governmental requirements as well as just building compute
07:59
data centers, which will have to make it more amenable for startups to take advantage of
08:05
them and really flourish in a less risky environment.
08:11
And when it comes to investing into this technology, what then should be the priority?
08:16
Is it funding that's needed for the actual tech?
08:19
Is it funding that's needed for ethics?
08:21
Is it funding that's needed to ensure the safety of these AI models?
08:25
What should be the priority here?
08:29
Well, all of the above, really, and I might add to your list fundamental research like the
08:35
kind of thing that we carry out in universities.
08:38
I'm hoping that like Demis Hassabis, the DeepMind co-founder and recent Nobel Prize
08:45
winner, he's come out on record recently in the Financial Times saying that there needs to
08:49
be way more artificial intelligence PhDs funded in the UK.
08:54
And that is surely true of France and other countries, if not all countries.
08:58
PhDs can undertake really groundbreaking, risky research, but there just isn't enough
09:05
funding for them.
09:06
And often they go straight into industry to these big companies without giving back to the
09:14
society that funded them.
09:17
PhD ceases and results.
09:19
So I think compute data centers absolutely required technology in order to get these off
09:23
the ground. The fact that deep learning requires a huge amount of compute, a huge
09:27
amount of data and a huge amount of time is not going to go away, even with deep seeks
09:32
revelations. But also there needs to be more money into AI ethics regulations, but how we
09:40
can all come to a good agreement about that so that technology can move on for the good of
09:44
society without being hamstrung too much by regulations.
09:48
If you ask various people in various startups, they will point out that it is quite
09:53
stifling to be within EU regulations right now in the AI sector.
09:57
And Simon, you say that we're actually looking at a battle royale between capitalism and
10:03
AI and then government forces, on the other hand.
10:06
So where is all of this evolving to, do you think?
10:10
My guess is that capitalism will win.
10:12
It's depressing.
10:13
But ultimately on things like jobs, white collar jobs are now under threat in a way that
10:20
they weren't previously.
10:22
And in many respects, you could imagine companies saying, you know, this is great.
10:27
We can deploy our human resources in new, more interesting ways rather than doing
10:32
drudgery. But the reality is that if an AI system can take their job or can do their job in
10:39
a much cheaper way, then company executives are going to take that option.
10:43
And we'll have to start seeing real discussion about four day weeks, about universal basic
10:49
income, about ways in which society can cope if the changes in the job market, as are
10:57
predicted by a lot of people, really happen.
11:00
Now, I'm glad that we'll take away a lot of the drudgery, even from creative work and
11:05
freeing people up to be expressive in the arts and music.
11:09
But I don't think companies are really going to take the lead in making this a nice
11:16
transition for their workers.
11:17
And I think that's where government will have to pick up the slack and really legislate
11:21
so that not just that people keep their jobs, but also that they are replaced in a
11:27
human friendly way if AI systems can indeed take their jobs.
11:32
And just finally, Simon, everyone had assumed, I think, up until the last few weeks,
11:35
that the US sector was leagues ahead, really, when it came to artificial intelligence and
11:40
all the technology surrounding it.
11:41
But does the emergence of these Chinese competitors suggest that there really is room
11:46
at the top in terms of global leadership here?
11:49
Yes, I mean, that's clearly the message that has come out from China.
11:54
Those of us in the business kind of knew about DeepSeek for a while beforehand, but it
12:01
did come as a shock to most of us at how good this technology was, how competitive, how
12:06
fast. And of course, that it was done entirely by Chinese nationals in a Chinese
12:11
company operating openly under state intervention rules.
12:16
So they're quite clear that they are subject to Chinese regulation and therefore their
12:20
data is available to Chinese government and they are censored in various ways.
12:26
So it does, people are calling this a Sputnik moment for good reason.
12:31
During the space race, there was that moment when Sputnik was launched and the Americans
12:37
realized that they were in a competition and therefore that sparked the race to the moon.
12:43
I think history will record this time as being the AI race.
12:46
And if they didn't already, the Americans now know that they are in a proper race for AI
12:52
dominance. My hope is that it's a collaborative race.
12:55
I'm a utopian in that respect.
12:57
And like people like Yan Likun, I'm hoping this will be for the benefit of mankind
13:02
across the planet.
13:04
But it may all get nasty.
13:07
Let's see. If you control AI, you control a lot of other aspects of human culture.
13:13
Simon, we'll have to leave it there for now.
13:14
Thank you so much for being with us on the programme this evening.
13:17
That is Simon Colton, Professor of Artificial Intelligence at the Queen Mary University of
13:23
London. Well, that's it from us.
13:25
For now, just stay with us, though. We'll be back shortly with more world news.
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