With GenAI, we understand that those models
will have a strong command of language,
but is that all they can do? Language?
So far, the greatest success we've had is with language models.
But if we ever want to get to general
artificial intelligence, that might not be enough.
In fact, we humans learn a lot from the environment,
we learn a lot from what we see,
we learn a lot from interacting with the environment.
And there is a big research, open question:
Is language enough to build our internal model of the world?
The model that allows us to predict how the world will respond to our actions,
because that is the essence for the intelligent system,
being able to predict what's going to happen when you act on the world.
So there is a lot of research happening in this field, and we're seeing a lot
of multi-modal models appearing, those that connect text and images,
text and audio, text and video and allowing it to go from text
to generating images or taking images and describing them with language.
What will be the impact for business or consumers of those multi-model models?
I think that impact will be huge.
We already have seen how quickly applications like Midjourney spread
around and how people enjoying creating images.
It really gives capability for those who cannot draw to create images,
for those who cannot design, and so on and so forth.
But if you think about businesses, about creative industries,
those technologies are clearly transformative for those industries.
And it will be very soon when we get algorithms that allow us to generate
videos, to generate audio, and that will change how creative industry works.
Leonid, we understand now, multi-modal models.
Now, I've heard you say sometimes that
this is a first step towards embodiment of agents.
Can you tell us more?
So embodiment is actually a very, very interesting concept.
It's really about a model having a 'body' or acting in the physical world.
And the way it is connected
to multi-modality is quite simple because in order for agent or model
to operate, it needs to sense the outside world.
Sensing usually happens through images,
through video, or maybe through audio.
And then multi-modality allows us to build
a single model that processes all that information, and then allows
the embodied agent, to act on outside physical world.
Will those embodied models change the way we or machines learn things?
We, as humans, we have our very individual
experience and individual learning pattern.
In fact, if you, for example, tell me how to ski,
I will not be able to ski because I don't have any experience in skiing.
And just by listening to you, I will not gain that experience.
So we literally need to live through our lives to gain experience.
Now, if you think about agents, they also need to have experience,
experiencing the physical world, getting feedback.
But the difference is that all the agents,
multiple agents can be connected in between themselves,
and so they can instantly share this experience and their learning becomes
much, much quicker and much, much more powerful.
So imagine if humans could be able,
instead of spending years in college, just instantly share their knowledge,
and that's what brings the power to this
collective intelligence or collective learning.