In grad school I worked with MRI data (hence the username). I had to upload ~500GB to our supercomputing cluster. Somewhere around 100,000 MRI images, and wrote 20 or so different machine learning algorithms to process them. All said and done, I ended up with about 2.5TB on the supercomputer. About 500MB ended up being useful and made it into my thesis.
Don’t stay in school, kids.
Thanks for the recommendation, I was worried they would be missing some of my artists but they had 99% of my music. Can’t wait to ditch Spotify.
ETA: dear lord the sound quality is so much better. I had no idea what I was missing.
We’ve got some really good theories, though. Neurons make new connections and prune them over time. We know about two types of ion channels within the synapse - AMPA and NMDA. AMPA channels open within the post-synapse neuron when glutamate is released by the pre-synapse neuron. And the AMPA receptor allows sodium ions into the dell, causing it to activate.
If the post-synapse cell fires for a long enough time, i.e. recieves strong enough input from another cells/enough AMPA receptors open, the NMDA receptor opens and calcium enters the cell. Typically an ion of magnesium keeps it closed. Once opened, it triggers a series of cellular mechanisms that cause the connection between the neurons to get stronger.
This is how Donald Hebb’s theory of learning works. https://en.wikipedia.org/wiki/Hebbian_theory?wprov=sfla1
Cells that fire together, wire together.
Actually, neuron-based machine learning models can handle this. The connections between the fake neurons can be modeled as a “strength”, or the probability that activating neuron A leads to activation of neuron B. Advanced learning models just change the strength of these connections. If the probability is zero, that’s a “lost” connection.
Those models don’t have physical connections between neurons, but mathematical/programmed connections. Those are easy to change.
I’ve been quoting Jordan Peterson for years?! Ahhh fuck.
Actually, we’ve got some pretty sophisticated models of neurons. https://en.wikipedia.org/wiki/Blue_Brain_Project?wprov=sfla1
See my other comment for an example of how little we truly understand about neurons.
Even assuming we can model the same number of (simple machine learning model) neurons, it’s the connections that matter. The number of possible connections in the human brain is literally greater than the number of atoms in the universe.
It’s not a terrible idea by any means. It’s pretty hard to do, though. Check out the Blue Brain Project. https://en.wikipedia.org/wiki/Blue_Brain_Project?wprov=sfla1
ETA: not to mention the brain is a heck of a lot more than a collection of neurons. Other commenters pointed out how we just discovered a new kind of brain cell - the brain is filled with so many different types of neurons (e.g. pyramidal, Purkinje, dopamine-based, myelinated, unmyelinated, internet Ron’s, etc.). Then there’s an entire class of “neuron support” cells called neuralgia. This includes oligodendrocytes (and Schwann cells), microglia, satellite cells, and most importantly, astrocytes. These star-shaped cells can have a huge impact on how neurons communicate by uptaking neurotransmitters and other mechanisms.
Here’s more info: https://en.wikipedia.org/wiki/Tripartite_synapse?wprov=sfla1
Heck, we barely know how neurons work. Sure, we’ve got the important stuff down like action potentials and ion channels, but there’s all sorts of stuff we don’t fully understand yet. For example, we know the huntingtin protein is critical to neuron growth (maybe for axons?), and we know if the gene has too many mutations it causes Huntington’s disease. But we don’t know why huntingtin is essential, or how it actually effects neuron growth. We just know that cells die without it, or when it is misformed.
Now, take that uncertainty and multiply it by the sheer number of genes and proteins we haven’t fully figured out and baby, you’ve got a stew going.
siRNA and miRNA: Are we a joke to you?
I continue to feed my X4 addiction. Picked up the DLC during the Thanksgiving sale. I’m on my second play, about 35 hours in. Realized I’ve made a lot of mistakes, but that’s half the fun.
Fair point. But, I think the headline was a but sensationalized. Or, I’m just bad at reading, which is possible.
So a republican in NORTH DAKOTA tweeted that OHIO should ignore the election? Correct me if I’m wrong, but that doesn’t seem like the concerted push to overturn the election that I expected when reading that headline.
Very nice, thanks!
I’ve never seen an exact number ascribed to it, any chance you have a source?
For those interested in more, I found this People Make Games video to be super interesting. https://youtu.be/lYaDXZ2MI-k?si=pxrioKZq_S7ka9il