Millennials are pretty much f**ked. 911 created a jobs program for the military industrial complex, sending investments outside of the US. The real-estate crash led to government austerity and hence less opportunities. The pandemic was the nail in the coffin.
Now it's their responsibility to clean up the environmental mess that previous generations left them. They have to do this while no money is spent on there because previous generations want to retire comfortably.
But what are Millenials doing? They are focusing on cultivating their brand on social media. What is often the case is they avoid conflict and keep silent about the injustices that they are subjected to.
BTW, did you notice that the Jan6 insurrectionists were mostly middle-aged men and retirees? The only millennials were people pushing their brand (see: guy with Bison headgear).
We are heading rapidly to a world depicted by the movie Elysium. Where only the affluent live in a world of paradise, while everyone else lives in a dog-eat-dog world with all their attention paid towards surviving.
For Elysium to become reality, the status quo must be preserved. Those without financial mobility must remain without options. Those without options must realize that resistance is futile. One should burn their youth as a cog in the machinery that leads to Elysium.
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It's an inescapable reality that many of us humans are embedded in a world where we aren't one of the physically beautiful people. I suspect it's more difficult for people who are borderline beautiful. Fortunately, I have less of an issue! I accepted my standing early in life.
In social media, we are constantly bombarded with images of physically beautiful people. The kind of people that we don't often see in real life (unless you live in a big city). So what's one to do if she's constantly reminded of her lack of perfection?
We are evolutionarily wired to notice beauty (btw, what's considered beauty is in the eye of the beholder). It's an unconscious thing that constantly creeps up into one's consciousness. This attention device is omnipresent.
There's a mad rush in Machine Learning circles to say 'X is enough' or 'X is all you need'. We have 'Rewards is enough', 'Attention is all you need', 'Diverse training is all you need', 'Size is all you need' (Bitter truth/Scaling hypothesis).
These logical jumps are ignoring all the messy details. I'm guilty myself of some ideas like 'Intuition machines is all you need' or 'Empathy is the path to general intelligence'. These singular ideas are pleasurable because they make what's complex appear simple.
Brains and Deep Learning are both live-wired systems and they are anything but simple. They are complex adaptive systems and require the entire kitchen sink of technology and mathematical models to get a handle on.
The way modern civilization is rigged, it is no surprise that the greatest minds of our generation are wasting their lives hacking the system for profitable vulnerabilities.
There is a difference though with hacking nature and hacking human nature. It is just sad to see that most of society spends most of their lives hacking the latter.
This is because modern civilization involves humans in games of one-upmanship. Humans are rewarded in proportion to the number of people they can influence. We are rewarded by the quantity of influence and not the quality of influence.
In Apple's rendition of Asimov's Foundation, the empire is ruled by 3 clones of the same original ruler. These clones are at different ages where the middle-aged clone is the ruler, the elder is an advisor and the younger is his successor.
In addition, there is a character Demerzel that serves the trio of clones. She is ever-present with the clones and all their ancestors. From singing lullabies to them before their birth to sending them off to incineration in their death.
Demerzel is immortal because she's an android. In Asimov's Foundation universe there are no AIs with this exception. Apparently, an AI is always present that is serving (or perhaps manipulating) the rulers of the civilization.
One of the most dangerous afflictions of data science teams is to go really big for the sake of going really big. That is why everyone jumped on the Big Data bandwagon and got little ROI to show for it.
Yes, Microsoft and Nvidia have the compute resources to go very big (i.e. 530b parameters), but that doesn't justify that everyone else does the same thing! microsoft.com/en-us/research…
What do you call that cognitive bias where you believe that you cannot make good progress without the fastest most advanced piece of hardware? This affliction affects so many technical endeavors. We all want to play with the F1 cars that everyone raves about.
The academic community would like one to believe that a single AI training method can lead to a useful system. This belief is not even remotely true. Indeed it gets you to publish a paper, but a useful product is very different from an academic paper.
A useful product is one that can be operated economically and addresses a user's needs at the correct price point. There are a multitude of knobs to tune here and a multitude of methods with varying resource demands, latency and accuracy.
A one-size-fits-all solution is a fantasy when it comes to products driven by AI methods. To deploy the right product requires a balance of many existing methods. This kind of balancing act is extremely difficult to do if we have tunnel vision of what methods are available.