'Companies are not going to take the lead in making AI a nice transition for their workforce'

FRANCE 24 English

Visit our website: http://www.france24.com  Like us on Facebook: https://www.facebook.com/FRANCE24.English  Follow us on Twitter: https://twitter.com/France24_en

Transcript

00:00This is Apropos.

00:04Global experts are here in Paris this week to debate the threats and promise of artificial

00:09intelligence.

00:10The summit is aimed at finding common ground on the rapidly evolving and disruptive technology,

00:16as well as examining how to keep France and Europe on the map as credible contenders in

00:21the AI race.

00:23Paris is expected to announce major investments in the fast-moving technology running into

00:27the billions.

00:29Peter O'Brien is there.

00:31He spoke earlier with Camille Knight.

00:34This is the first of two science days and boffins that have gathered here from around

00:38the world were very, very excited, particularly because of this recent breakthrough by Deep

00:44Seek.

00:45The prospect that we're going to be able to deploy advanced, powerful AI models at a fraction

00:51of the cost has got smaller players in France very excited.

00:57Now a lot of big names expected at the summit.

01:00Peter, you were able to speak to Yann LeCun, Meta's chief AI scientist.

01:04What did you learn from that conversation?

01:09Well I wanted to ask him whether he felt vindicated because he's French, of course, and he's been

01:15absolutely championing a open source approach to AI for years now.

01:20That's what Meta does.

01:21They have these Lama models that are very powerful.

01:24They get copied around the world because they are open source.

01:28And he's been banging the drum and criticizing open AI, for instance, for closing off access

01:34to its models.

01:35So when Deep Seek came along and blew a lot of the competition away in terms of efficiency,

01:40he sounded pretty happy.

01:42I also talked to him about his boss, Mark Zuckerberg.

01:46He said that more masculine energy was needed in corporations.

01:52So when it comes to AI and developing AI, I asked Yann LeCun whether more masculine

01:58energy was needed there as well.

02:00I had a big project called Zeta, whose goal was to basically build a large-scale LLM.

02:08And then for various reasons, a smaller group in France decided that they needed LLM for

02:15their project.

02:16And it turned out to work better than the big ones.

02:19It's not because of the quality of the people.

02:20They were both very talented, but the problem was that one of organization and management,

02:31the small group had a lot of autonomy, a long leash, was relatively small, and had a lot

02:37of freedom, essentially.

02:39The big group was kind of top-down managed, more directed, and in the end, a less efficient

02:46way of organizing research.

02:47And so we see the same thing with diptych.

02:49Nothing to do with masculine energy or lack thereof?

02:52No, no.

02:53Not at all.

02:54That doesn't come into it?

02:56Absolutely not.

02:58Peter O'Brien there reporting.

02:59Well, for more, we're joined now by Simon Coulton, Professor of Artificial Intelligence

03:04at Queen Mary University of London.

03:08Thank you so much, Simon, for being with us on the program.

03:11Let's start with the timing of this summit, coming as it does in the aftermath of the

03:16emergence of DeepSeek.

03:18How much of a game-changer do you think this Chinese technology is?

03:24I think it is a big game-changer.

03:27Of all the various predictions of how this is going to change AI and AI funding, I think

03:32the one which I think is most sensible is that we'll see this as a World Wide Web moment,

03:38where it became a lot easier to make, post, and find web pages through the World Wide

03:43Web.

03:44The Internet was not so usable before that.

03:47And now AI has become 50 times cheaper, if you believe the figures, to operate.

03:53And that can be just the beginning of it.

03:56If there's as much money poured into scaling down AI models as there was into scaling them

04:00up, then we can imagine hundreds of times cheaper.

04:03So that will make it available to organizations to use at scale a lot more often, a lot more

04:12down the tech chain, so that we will find that it's an explosion of usages of AI.

04:19And we might find that that will mean that money flows from the kind of data center area,

04:26where we're building up these huge banks of graphics processors, into more startups, into

04:33more thin-layer companies, which are able to run these models on their own machines.

04:39And then if the models get even smaller, which I think is quite unlikely, to be perfectly

04:43honest, but if they do get smaller and they can be crammed onto a laptop, the really good

04:48models, not the smaller distilled versions of them, if the really good ones can be crammed

04:52onto a laptop or a mobile phone, then that is a huge game changer, because we don't need

04:56quite so much of the GPUs available.

04:59So it could be a pivotal moment.

05:02And then, of course, there's a whole geopolitical element to it as well, as well as a financial

05:06element.

05:07So I think it will be seen, ultimately, as a big moment in the tech arena.

05:13A big moment as well.

05:14It also wiped a lot of money off the value of some of the biggest players in the sector

05:18initially.

05:19Does this suggest that American tech companies who pledged billions of dollars in AI investment,

05:25that perhaps that was a little short-sighted?

05:26Possibly.

05:27Certainly, the market thought that.

05:31The timing was just fabulous of the release of this.

05:35Not only was it just a day or so after the announcement by the American president of

05:40the Stargate project, $500 billion is being pumped into infrastructure like data centers,

05:46but it was also just before the weekend.

05:48So that meant that the market had time to enact a kind of epic overreaction to it.

05:55It wiped $600 billion off the market capital of NVIDIA and a trillion off the NASDAQ in

06:01total.

06:02However, I kind of believe the line that if you make something cheaper, people will buy

06:08it more.

06:09There's an economics theory about that.

06:12So all of this is still going to be run on GPUs, and I don't think it will mean at all

06:17that NVIDIA will suffer in the long term.

06:19I think there'll be equally as much compute required for all of the extra usages of GPUs

06:28that will be enabled by this leaner, slimmer technology.

06:32And Simon, there's a global AI summit taking place in Paris this week.

06:38We've been referring to it earlier.

06:40The UAE has just announced that it'll be investing up to 50 billion euros in a data center here

06:46in France.

06:47What does Europe need to do at this point?

06:50Is it those kind of investments that we need to be securing in order to become really a

06:55global player when it comes to artificial intelligence?

06:59Yes, I still think there's very much a requirement for compute.

07:04Ask any of us in academia where we don't have access to these huge tens of thousands of

07:09GPU units and we'll tell you that, yeah, compute is key.

07:13All of my PhD students are always desperate to find GPUs in order to train their models.

07:19But there are other factors at stake here that will need to change as well.

07:24I try and take a balanced view.

07:25I understand the value of AI safety and ethics, but there are reasons to think that the

07:34European Union is being overly careful and that might stifle innovation and that

07:42ultimately it means that companies can't take risks.

07:46There's going to be battles over copyright, so over copyrighted data enacted in various

07:53industries. So there are governmental requirements as well as just building compute

07:59data centers, which will have to make it more amenable for startups to take advantage of

08:05them and really flourish in a less risky environment.

08:11And when it comes to investing into this technology, what then should be the priority?

08:16Is it funding that's needed for the actual tech?

08:19Is it funding that's needed for ethics?

08:21Is it funding that's needed to ensure the safety of these AI models?

08:25What should be the priority here?

08:29Well, all of the above, really, and I might add to your list fundamental research like the

08:35kind of thing that we carry out in universities.

08:38I'm hoping that like Demis Hassabis, the DeepMind co-founder and recent Nobel Prize

08:45winner, he's come out on record recently in the Financial Times saying that there needs to

08:49be way more artificial intelligence PhDs funded in the UK.

08:54And that is surely true of France and other countries, if not all countries.

08:58PhDs can undertake really groundbreaking, risky research, but there just isn't enough

09:05funding for them.

09:06And often they go straight into industry to these big companies without giving back to the

09:14society that funded them.

09:17PhD ceases and results.

09:19So I think compute data centers absolutely required technology in order to get these off

09:23the ground. The fact that deep learning requires a huge amount of compute, a huge

09:27amount of data and a huge amount of time is not going to go away, even with deep seeks

09:32revelations. But also there needs to be more money into AI ethics regulations, but how we

09:40can all come to a good agreement about that so that technology can move on for the good of

09:44society without being hamstrung too much by regulations.

09:48If you ask various people in various startups, they will point out that it is quite

09:53stifling to be within EU regulations right now in the AI sector.

09:57And Simon, you say that we're actually looking at a battle royale between capitalism and

10:03AI and then government forces, on the other hand.

10:06So where is all of this evolving to, do you think?

10:10My guess is that capitalism will win.

10:12It's depressing.

10:13But ultimately on things like jobs, white collar jobs are now under threat in a way that

10:20they weren't previously.

10:22And in many respects, you could imagine companies saying, you know, this is great.

10:27We can deploy our human resources in new, more interesting ways rather than doing

10:32drudgery. But the reality is that if an AI system can take their job or can do their job in

10:39a much cheaper way, then company executives are going to take that option.

10:43And we'll have to start seeing real discussion about four day weeks, about universal basic

10:49income, about ways in which society can cope if the changes in the job market, as are

10:57predicted by a lot of people, really happen.

11:00Now, I'm glad that we'll take away a lot of the drudgery, even from creative work and

11:05freeing people up to be expressive in the arts and music.

11:09But I don't think companies are really going to take the lead in making this a nice

11:16transition for their workers.

11:17And I think that's where government will have to pick up the slack and really legislate

11:21so that not just that people keep their jobs, but also that they are replaced in a

11:27human friendly way if AI systems can indeed take their jobs.

11:32And just finally, Simon, everyone had assumed, I think, up until the last few weeks,

11:35that the US sector was leagues ahead, really, when it came to artificial intelligence and

11:40all the technology surrounding it.

11:41But does the emergence of these Chinese competitors suggest that there really is room

11:46at the top in terms of global leadership here?

11:49Yes, I mean, that's clearly the message that has come out from China.

11:54Those of us in the business kind of knew about DeepSeek for a while beforehand, but it

12:01did come as a shock to most of us at how good this technology was, how competitive, how

12:06fast. And of course, that it was done entirely by Chinese nationals in a Chinese

12:11company operating openly under state intervention rules.

12:16So they're quite clear that they are subject to Chinese regulation and therefore their

12:20data is available to Chinese government and they are censored in various ways.

12:26So it does, people are calling this a Sputnik moment for good reason.

12:31During the space race, there was that moment when Sputnik was launched and the Americans

12:37realized that they were in a competition and therefore that sparked the race to the moon.

12:43I think history will record this time as being the AI race.

12:46And if they didn't already, the Americans now know that they are in a proper race for AI

12:52dominance. My hope is that it's a collaborative race.

12:55I'm a utopian in that respect.

12:57And like people like Yan Likun, I'm hoping this will be for the benefit of mankind

13:02across the planet.

13:04But it may all get nasty.

13:07Let's see. If you control AI, you control a lot of other aspects of human culture.

13:13Simon, we'll have to leave it there for now.

13:14Thank you so much for being with us on the programme this evening.

13:17That is Simon Colton, Professor of Artificial Intelligence at the Queen Mary University of

13:23London. Well, that's it from us.

13:25For now, just stay with us, though. We'll be back shortly with more world news.

Category

Transcript

Recommended