Yoshua Bengio
speaker
2,216 appearances
5 recordings
5 series
first heard Oct 2018
last heard 7 May
Yoshua Bengio’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 3 in all, peaking in May 2026 with 1.
Appearances
And we've seen the behavior of those companies going exactly along that direction.
locally rational.
So from the point of view of a company, they know that if they put safety as a priority, like that they wouldn't deploy a dangerous model, that would put them out of the competition, out of the race, and then they would be irrelevant, right?
Yes, that's exactly what I'm saying.
So how do we change the game so that this will be less likely?
One issue right now is that they don't have a choice.
They don't know how to both remain competitive and have systems that will be strongly guaranteed to be safe.
If they had such a technique, it would be in their commercial advantage to use it, right?
If you can have safety and capability, then definitely most companies at least would go for that.
I guess depending on the cost.
That's right.
We can talk about that.
And then governments, right now they're under huge pressure because of the geopolitical competition and the belief that AI is going to be a huge economic growth factor.
are unwilling to regulate again for the same reason, that they think that if they put safety barriers that would stop some of their companies from continuing, then that will give an advantage to the other guys, right?
But same thing, if there was a demonstrably safe way of building competent AIs, then it would be much easier to regulate.
You would still want to regulate because there's going to be some bad actors, some companies that are willing to do the bad thing, even though there's a way to do the right thing.
So now about costs.
The scientist AI is gonna be trained using essentially the same machine learning techniques, stochastic gradient descent on large neural nets, transformers, whatever works best.
It doesn't care about what is the architecture of the neural net.
So all of the effort that is currently being done to improve, for example, memory and other properties and continue learning,
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