Here’s a bit of hope for you, scientists have figured out how to trick the body into producing any protein or antibody they want, through technology like gene therapy and mRNA vaccines. We’re about to cure a lot of diseases that used to be 100% fatal. Diseases that kill kids and adults alike.
Most things seem to be getting worse these days, but at least we’re making progress in other areas.
Unironically, I had to delete this game from my phone because I wasn’t getting work done. This game slaps.
Outer Wilds was the best game I played on PS4. I strongly recommend experiencing it for yourself.
I would say the space ship/0g flight is maybe 30% of the gameplay, and you don’t need to be really excellent at it, thankfully.
It’s been in development for a while: https://ieeexplore.ieee.org/abstract/document/1396377?casa_token=-gOCNaYaKZIAAAAA:Z0pSQkyDBjv6ITghDSt5YnbvrkA88fAfQV_ISknUF_5XURVI5N995YNaTVLUtacS7cTsOs7o
Even before the above paper, I recall efforts to connect (rat) brains to computers in the late 90s/early 2000s. https://link.springer.com/article/10.1023/A:1012407611130
It’s a bunch of neurons that speak to a computer with a microelectrode array. So they “speak to” the neurons with electric impulses, and then “listen to” what they have to say. The computer it’s connected to uses binary, but the neurons are somewhere in between. Yes, the change in electrical potential is analog, but neurons are typically in their “on” state, recovering from their “on” state, or just chilling out.
The brain is incredible because of the network of connections between neurons that store information. It’ll be interesting to see if a small scale system like this can be used for anything larger scale.
Believe it or not, I studied this in school. There’s some niche applications for alternative computers like this. My favorite is the way you can use DNA to solve the traveling salesman problem (https://en.wikipedia.org/wiki/DNA_computing?wprov=sfla1)
There have been other “bioprocessors” before this one, some of which have used neurons for simple image detection, e.g https://ieeexplore.ieee.org/abstract/document/1396377?casa_token=-gOCNaYaKZIAAAAA:Z0pSQkyDBjv6ITghDSt5YnbvrkA88fAfQV_ISknUF_5XURVI5N995YNaTVLUtacS7cTsOs7o. But this seems to be the first commercial application. Yes, it’ll use less energy, but the applications will probably be equally as niche. Artificial neural networks can do most of the important parts (like “learn” and “rememeber”) and are less finicky to work with.
My job is 8:30 - 5 with a 30 minute lunch break. So almost.
But, we also get 2 days/week at home, and can flex time as required. Tons of international work, so the flexible hours are a godsend when time zones are against us.
It’s a salaried position and depending on your supervisor and stage of your career, you’re expected to work 40-45 hours a week. Deadlines and ugly projects tend to increase hours work. I’m very lucky, as my industry can be pretty brutal with sudden ends to projects and unexpected layoffs.
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.
Time to reboot and replay!!!
My understanding was you needed to have a second copy to 100% - I was always missing a specific mission item. So I never completed the game.
I loved FFTA so much, and did not care as much for FFTA2 on DS. Easily sunk 1000 hours into my GBA copy.
Very nice, thanks!
I’ve never seen an exact number ascribed to it, any chance you have a source?
Unfortunately there’s a lot of truth in that statement, especially in the case of rare disease. It’s really difficult to convince a company to spend billions to develop a treatment that will only cure 1 in 100,000 people without letting them charge an arm and a leg, and giving them a very long exclusivity deal so they can continue to charge high prices. So much of that cost to develop is due to the dozens of other failed drugs and formulations they tried on their way to success.
I don’t have a solution for the problem, and I’m always a little suspicious of anyone who claims it’s easy to solve. I think the UK has a decent idea, the NHS basically decides if the cost of a drug will be covered by insurance by comparing the expected benefit and the current cost. If the ratio is too skewed, they refuse to cover the medication. In theory, this should be an incentive for a company to charge less. In practice, it leads to some companies choosing not to market in the UK.