Windchaser
Probably not effective, our gut is very good at splicing up proteins into constituent amino acids.
If you want specific proteins/peptides in your bloodstream*, for now the most reliable way is generally to inject them.
But yeah, it is very much not necessarily the case that our own bodies will produce the same proteins under similar exercise, or that the mouse proteins released would have the same effects in us as in them, or that proteins released under similar exercise would actually de-age us.
It's interesting to track down the mechanisms in mice (exercise induces protein release - how? - which then de-ages the mice - also, how?) but you have to reproduce the work entirely separately in humans. Not just because it might not work, but because it is very important (and neat!) to understand the biochemical mechanisms of human ageing and de-ageing, and that understanding of How Things Work is a big part of the long-term reward.
[*] I'm not advocating for injecting untested/unregulated proteins or peptides, only speaking of ROA, route of administration
Well, there's personal racism, meaning personal prejudice against a race. But then there's also institutional racism, like policies that turn out to be racist. Racist policies can be blatantly racist, like redlining, or they may indirectly turn out to be racist.
But yes, I think institutional racism is fairly common and very well-documented in the US.
> You're literally just describing a chicken-and-egg problem.
If you want to understand this more deeply, I highly recommend Ta-Nehisi Coates' book "Between the World and Me".
Yes, it's a chicken and egg problem, but our police and judicial institutions are actively sustaining/aggravating the problem.
But it doesn't look great that we're up there with El Salvador (a failed state), Cuba, Rwanda (another failed state), and Turkmenistan
Is that true, though? I don't expect that the individual biases of officers or judges, or the institutional biases of the police or immigration departments, can switch at a moment's notice.
And: which country has the highest incarceration rate in the world?
This is not a personal story, not an anecdote. I'm reporting on a study that looked at incarceration rates for drug use vs the drug use itself.
Why is that important? Because the study itself is solid, and it shows that there is some sort of bias between police/policing and african-american communities.
Sure, maybe that bias doesn't show up in other areas like firearm-related crimes. Or: maybe it does, and we haven't yet figured out how. Or, maybe it plays an indirect role, further eroding the relationship between the AA communities and the police, gradually building up a mutual dynamic that subjects black people to an unhealthy chronic level of stress and despair and harassment while also "justifying" the prejudicial activities of the cops.
There are whole books written about this. But at a minimum, I can't imagine just brushing over a 4x higher arrest rate for the same level of crime. That's pretty damn big.
And then this just reinforces the idea: "well, look at the crime statistics, black kids are more crime-prone, right"
Both have valid use cases. It's weird to be sarcastic about it.
Can AI handle driving yet?
Compare 1926 to 1999, and how technology advanced in that time. Radio wasn't widespread in 1926, nuclear fission hadn't been demonstrated, the idea of the semiconductor energy band gap, underlying the entirety of the modern computing industry, wasn't put forth until 1928. And yet, 20 years later we were purifying silicon, and 10 years after that (1954) the first silicon transistor was created and kicked off the semiconductor boom. 50 years later, we were in the Internet bubble.
We've got decades upon decades upon decades to come up with new ideas and implement them, even before the end of the century.
huh. I can only think of one friend I've ever known who named their car.
Anyways, not saying I necessarily disagree with the rest of what you say, but it's out there, for sure. We're a good distance away from an AI that can meaningfully act like a friend.
(Though who knows what AI will look like in even 10 years? I'm not ruling this out)
This is very different from what I see.
At coffee shops and on trains, sure, people are working or on their phones. But at dinner and parties, at bars and climbing gym and dances, we're there to be there with each other.
Maybe a cultural difference between where you are and where I am?
Looks like AI will be another revolution, and eventually, probably the largest.
??
I have friends raised in the US who experienced serious food scarcity as children (~20-25 years ago), and they have plainly disordered eating as a result. The stories I hear, many variants on things like "oh, yeah, as a kid I learned you can get rid of hunger by just drinking more water".
Of the ~3500 mosquito species, only about 3% drink human blood. And many of those are invasive in the areas we care about.
Sampling bias. How many did you ask?
I dunno, this seems to be interpreting the comment in the worst way possible. Like, assuming bad faith.
The comment above suggested that guys approach less-attractive women until they "build some confidence". This is not about the woman's receptivity to attention, this is about the guy's confidence or lack thereof. It makes sense: when confidence is worse, the conversation is more awkward and stilted, and that awkwardness is more likely to reinforce the idea that talking to strangers is a waste of time.
The charitable interpretation would be this: that you practice talking to strangers in scenarios that feel safe. Gradually, work up towards your goal - making new friends, talking to people you want to date, etc.
And they basically did. Not a singular city of gold, perhaps, but the Spanish looted tens of billions of $$ worth silver and gold from Central/South America between 1492 and 1550. Which is all the more impressive given how little European manpower it took and how low their relative incomes would've been at the time.
Unpopular, maybe, but what about the normal reasons? The researchers are looking to make a name for themselves, and/or they genuinely care about AI advancement.
Well, I'm sold. Let's nuke the moon
For reference, the Bortle Scale[*] goes from 1 to 9, with 1 being pristine darkness and 9 being Manhattan.
Also worth noting that the Milky Way is brighter in early summer, late May to mid-July, as that's when the Earth's night sky is facing the most towards the Galactic Core. Go find yourself some deep dark sky on a new moon, and sit back and enjoy the enormity of the cosmos.
[*] https://en.wikipedia.org/wiki/Bortle_scale#/media/File:How_l...
I've got no problem with an AI doing something similar
(And yes, I know that they solved the 'easy' form of the NS problem. It's still pretty damn impressive)
Eh, it's not obvious to me. A lot of DL NNs generalize well, meaning that they learn whatever the underlying pattern to the data is, and then can accurately reproduce answers that are outside of the training set. (And we can verify this with mechanistic interpretability). They learn and "understand" the pattern, not just the training data.
So it is not clear to me that LLMs are fundamentally incapable of also generalizing broadly and learning to reason. "Reasoning", here, would be deriving the underlying pattern of how concepts logically relate to each other in the abstract, and applying that pattern as needed to reach new conclusions.
Can you explain your thinking here? I.e., why LLMs cannot generalize with regards to abstract deduction.