I would argue that "context" is intentional misdirection. Most people don't know that synchron is marketing an electrified stent that gives maybe one channel of data I/O whereas Neuralink has a robot that implants thousands of electrodes in multiple regions of the brain and spinal cord. They are different by orders of magnitude in complexity and potential utility.
> I would argue that "context" is intentional misdirection. Most people don't know that synchron is marketing an electrified stent that gives maybe one channel of data I/O whereas Neuralink has a robot that implants thousands of electrodes in multiple regions of the brain and spinal cord. They are different by orders of magnitude in complexity and potential utility.
The literal quote you're responding to says that Synchron's implant is "less ambitious." It's worth noting that being overambitious is often the root cause of fuck ups.
> But overambitious is only obvious in retrospect.
I disagree. If you're trying to do, say, implement five revolutionary things no one's ever done all at once, so you can tell people you're going to go from zero to sci-fi in a couple years, there's an extremely high likelihood you're being overambitious. That's something that's obvious from the start.
> Go tell that to Thomas Edison, I guess. Or Nikola Tesla.
The vast majority of people, including engineers and business leaders, are not Edisons or Telsas. Sometimes people get lucky or they have unusually well-resourced and competent teams to tackle an unusual amount of stuff at once. That's why I qualified my statement with "there's an extremely high likelihood..." Given Neuralink is facing "a federal probe and employee backlash" over shoddy practices, I highly doubt they have the unusually well-resourced and competent teams to not be overambitious.
What's an example of Edison or Tesla doing multiple "revolutionary things no one's ever done all at once"? I'm genuinely interested, but details matter a lot. For example, the Edison company's contribution to electric light was mainly extending the life and reducing the amperage of light bulbs. Other people had already demonstrated the potential of electric light.
There is nothing about what you said that suggests that this requires more animal testing in a shorter timeframe. If anything a single animal test should provide so much more data that it should take much longer to process and analyze the results, slowing down the speed at which animal tests occur.
On the one hand you seem to be arguing that neuralink is more complicated and has more unknowns, and that this explains why it needs to do more animal tests, but that depends on how much data one can capture in a single test. So it is not a given that the complexity-to-tests-needed graph is linear.
And assuming that we do actually capture a lot more data in a single test (I would hope so at least), then that also means more work needs to be done to interpret this data in a meaningful way and make improvements. Which would suggest that it should take more time to move on from one test to the next.
There is a difference between total animal tests and how quickly the tests are done.
One of the example applications proposes to stimulate patterns of neurons in visual cortex to produce vision. To even get to the point where you can train a monkey to detect phosphenes, Neuralink had to (a) develop a way of producing flexible electrodes that would measure activity from a single neuron, were robust enough to be implanted, would survive the punishing in-vivo environment, and retain their ability to measure and stimulate for long periods of time (none of those steps can be adequately done in in vitro models). (b) They then had to make sure that their robot could implant them to the proper depth (despite brain movement), and that during implantation they could maintain connection to the interface system. (c) They had to build a ASIC that would capture a 1000 of channels of neural data and wirelessly transmit them, while ensuring that the SNR was sufficient for use (again, no in vitro model). (d) They had to test the encapsulation of the ASIC to make sure that it, too, could survive in vivo.
They could certainly have done all these things serially, but it would have taken a lot longer. In the end, where they are is still far from a useful product - they have monkeys that can see phosphenes, they have electrodes that last 1 year, and they have a reasonable ASIC - but compared to the academic timescale, where we've been working on these individual pieces 1 PhD (6 years) at a time, they've made really remarkable progress.
