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Many of those pigs were completely isolated for over a hundred years and entirely missed out on the globalization of tons of infectious diseases.

A while ago a group of them were picked up and brought to a special protected refuge in New Zealand, where they are being used for artificial organ research (https://nzeno.nz/) basically for the reasons you highlight.

It’s still very early days for software composing AI models and we almost certainly don’t have all the right metaphors yet. And I think there is a lot to be said for strong typing and simple, robust code!

- in this field, monkeys are high value animals and experimenters will often work with the same ones for many years; they are not, generally speaking, a high throughput model.

- to the extent a company does need to go through a large number of animals for a study, the way this works is you start by figuring out all of the problems you might be worried about, and choosing some rarity threshold to verify absence of (safety against), and then animal numbers are derived from the power calculation. For example, to rule out a potential complication to no more than 1% of patients with 95% confidence… you need a lot of animals, especially considering multiple study arms. This is the values tradeoff we as a society have chosen to make and empower our regulators to enforce. There is often a negotiation for the least controversial species to use that will satisfy the scientific goals.

I hope I don’t come across as uncivil, but you guys alienated a lot of people both in how you talked about “sentience” and also seemed to heavily hype this as totally novel.

I would never root against cool progress in neural engineering, but I would be curious as to what you think your first big product will be based on this. Past attempts have usually ended up pivoting to stuff like artificial noses.

Edit: I tried to ignore it but the bad faith attack on neuralink, which, look, I have complicated feelings about too — you should know the animal use data in the press is extremely out of context (to the point of simply being wrong) and also neuralink has had zero chimpanzees in its entire history.

There was a lot of coverage back in 2004 when DeMarse hooked it up to a flight simulator and claimed it was flying an F-22 [3] (lol, but I don't blame him too much...)

The basic idea is that if you culture neurons on an electrode array (not that hard) you can pick some electrodes to be "inputs" and some to be "outputs" and then when you stimulate both ends the cells wire together more or less according to Hebb's rule[4] and can learn fairly complex nonlinear mappings.

On the other hand, these cultures have essentially no advantage over digital computers and modern machine learning models. Once you get through the initial cool factor, you realize it's a pain to keep the culture perfectly sterile, fed, supplied with the right gases, among many other practical problems, for a model which is just much less powerful, introspectable, and debuggable than is possible on digital computers.

[1] https://bpb-us-w2.wpmucdn.com/sites.gatech.edu/dist/f/516/fi...

[2] https://potterlab.gatech.edu/labs/potter/animat/

[3] https://www.cnn.com/2004/TECH/11/02/brain.dish/

[4] https://en.wikipedia.org/wiki/Hebbian_theory