For 80 years, we have tried to make our computers more brain-like.

I would like to show you that there is value in making brain organoids, so human cell cultures, more computer-like.

We call this brain organoid plus AI, organoid intelligence, or OI.

It is essentially combining, connecting AI with a brain organoid system and have them talk to each other.

This all is possible because of the dramatic increases in the capabilities of AI.

Artificial intelligence is the synergy of three exponential growth curves.

The first one is data.

The data in the world are doubling every 18 months, or roughly 90% of all data in the world have been produced in the last three years.

Computers are doubling every second year in capacity at half the price.

That's what we know as Moore's law for 60 years.

But AI algorithms, since the introduction of deep learning in 2010, double in capacity every three months, which means this year's large language model, for example, is about eight times as powerful as the one from last year.

This altogether is giving rise to a tremendous use of AI in all parts of life.

However, we also know that these large language models are not reasoning.

They are learning tons of things, and they can use these informations, but they are not actually reasoning.

They are faking it.

However, our computer, the brain, just 1.4 kilogram on our shoulders, is actually quite a supercomputer.

It was only two years ago when the first time a supercomputer exceeded the computational capacity of a single human brain of estimated one exaflop.

This supercomputer was a $600 million installation on 6,800 square feet.

At the same time, the human brain consumes only about one millionth of energy as this supercomputer to the same computational work.

This shows you that there's a lot of things we can learn, and it is actual intelligence.

It is not faked intelligence.

And still, our little computer is doing many things better than even the best supercomputer.

For example, a child is able to distinguish between, let's say, a horse and a zebra with about 10 pictures each.

A computer needs hundreds, if not thousands, of these pictures.

Then you show the child one single unicorn, and it will distinguish new unicorns from now on, while the computer needs again hundreds of these pictures.

Our large language models are updated perhaps once per year.

We learn progressively.

Whatever you take from my presentation today, you have integrated into your knowledge from now on.

We call this progressive learning.

We also have the ability to decide very quickly, fast thinking, intuition.

If we hear going through the jungle a noise, we are jumping, because we assume there could be a tiger.

The answer from our chat models will be there after the meal.

We also have to see that real creativity is probably not yet there.

It is a rearrangement of human creativity, which we are observing.

So let's talk about making brain organics more computer-like.

Our cell cultures are actually keeping our brain very much in solitary confinement.

We are boring our cells to death.

They have nothing to do.

There is no input and no output to these systems.

Brain organoids, these balls of cells, which are derived from stem cells and are available now for about 10 years, are actually having an infrastructure of all the different cell types.

They're having the neurons, all the different types of them.

They're having oligodendrocytes, which are wrapping themselves around these axons of the neurons to allow faster connection.

And we also have the astrocytes, a very important cell type for learning and memory, because they are responsible to take away all of the many connections of the brain, which we do not need.

And this is how memory establishes.

They are pruning synapses.

So all together, they're forming a functional unit.

And this is what we want to use in a standardized way for reproducible reactions, mass-produced, and also, as I will show you in a minute, from different genetic backgrounds of patients in order to develop disease models for these.

In 2016, we were the first to mass-produce these type of organoids.

And since then, we have used them for many different disease models.

This is an article from the front page of the Financial Times at the time.

So the first thing is we need to talk to these brain organoids.

So we need the type of EEG, an electroencephalogram.

This is how it looks for a designer, for AI in this case.

Down here, you see the actual EEG, which at the time, nine electrodes, which we published two years ago.

But we are increasing the number of electrodes around this mesh electrode.

So at the moment, we are at 16.

But you have to imagine that this brain organoid is only half a millimeter in size.

It is just having 50,000 neurons and 50,000 helper cells.

However, it is already at the moment undergoing training.

And it is controlling through Bluetooth, for example, this little robot, where we're trying to explore its environment and find roadblocks in the map it is establishing.

But we have an entire suite of little computer games you can see here, which we call our mind gym.

And in this mind gym, we are using these type of video games to find out how well it performs.

And does it perform better and better over training periods and over the next day?

This is ongoing work.

But we have the first indications that there's really long-term memory establishing.

Very, very simple functionalities, to be clear here.

At the same time, we're making these brains bigger.

We are trying to achieve a brain organoid of one centimeter, which requires us to perfuse it not with blood, but with cell culture media to get oxygen and nutrients to the center that we can work with a larger one.

One centimeter is already twice a mouse brain, just to give you some type of proportion here.

And this is part of a surpass program, which Johns Hopkins University, my university, is financing.

This is opening up for a lot of ethical questions.

Nature titled once, can lab-grown brains become conscious?

We don't know.

But we have to prepare for the possibility of something like this.

So we are working very closely with ethicists.

They are meeting with us every week when we plan our experiments.

They come to the labs.

They see what we are doing.

We call this embedded ethics.

But they're also asking people on the street, what do you think about this type of research?

When does it start to feel perhaps better not?

And does this change if we tell you that this is to develop, for example, drugs for Alzheimer's?

Because this is one of the short-term perspectives of such a system.

It will not beat AI as it is.

It will probably not even beat a handheld calculator for the foreseeable future.

But it is something where we can build disease models, where we can try, if you take cells from a child with autism, are they communicating differently?

Are those with their new developmental disorders incapable of learning?

Is this changed if their cells were taken from an Alzheimer patient?

So we are already preparing with various expert groups in Hopkins to produce brain organics of this type, and we are characterizing them, and we are hoping to employ organic intelligence.

At the same time, we are trying to form a community.

We launched this just one and a half years ago with an article as the first article ever in the flagship journal Frontiers in Science.

And we are trying to form a community.

We are trying to bring people together because it needs a multidisciplinary team.

We have carried out a workshop, and instantly the White House has made this one of the bold biotechnologies goals of the U.S. to create these type of systems.

We have created a journal, a sub-journal of my journal, Frontiers in Artificial Intelligence, which is called Frontiers in Organic Intelligence now, and we have convinced the National Science Foundation to open a program, which is now open for Engineering Organic Intelligence, And we also created a newsletter, we created a website, and the community is at the moment 450 people.

It is free to join, and I would hope to see some of you do this.

It is a remarkable scientific exercise.

I consider it to lift science fiction, and to show that indeed this is the fact, a friend of mine after one of my first presentations on Organic Intelligence said to me, Thomas, do you recall Star Trek in 1966?

I didn't, I was three years old.

But in this episode, Captain Kirk finds this computer which is running on brains.

This is one of the incredible visions of this project, to really understand better how a brain could drive a computer, how we possibly could create neuromorphic algorithms and architectures which are embracing biology as a driving principle for Organic Intelligence.

Thank you very much.