What's missing from this explanation is that the corporate tax rate was also much higher, but R&D dramatically cut down profit that would be taxed and was taxed lower. So large corporations like Bell Labs and co would basically say "do we give the government X in taxes, or do we spend X on research?". They chose research, so we got the technology that powers our world.
That, combined with stock buybacks and the general take over of Friedman-economics resulted in a far more focused short term thinking and outsourcing research as much as possible due to uncertain horizon risks.
These days you're better off giving it to a university with strings attached. Sure, they might piss a bunch of it away, but when you account for the dollars on the subject you care about after taxes are leeched out it's still more efficient than building out research within the confines of a for-profit entity that gets taxed at such.
This is why we no longer have corporate research labs and damn near every university is bristling with BigCo funded stuff.
The generally accepted term for the research around this in robotics is Constitutional AI (https://arxiv.org/abs/2212.08073) and has been cited/experimented with in several robotics VLAs.
There's shilling a product because someone handed you a bag, and then there's building a product you believe in. You feel okay with it because it's clearly the latter versus another NordVPN commercial. Even if the product ends up failing (and I am under no predilection to believe this will) he has presented nothing but honest enthusiasm towards his goal that you can't help but root for it.
He's gone all in on the Crunch Labs brand, which is kind of built around the younger audience. This isn't a bad thing, but it does mean that older edutainment enjoyers kind of age out of his stuff. Not to say there's no value in them, but there will be more of an entertainment focus than prior edutainment focused videos.
I recommend checking out Stuff Made Here; great build videos of engineering principles in an entertaining fashion to show building cool complicated stuff.
Xyla Foxlin, a wonderful maker, also posts educational videos between her projects, like an in-depth look at how plane wings work.
Whenever I am feeling smart or particularly talented, I like watching Shane's videos. I'm swiftly reminded that I have no idea what the hell I'm doing and carry on.
I like that he still shows the struggle, so it’s not like he’s pretending to know it all. I find this helps give me perspective when I’m in a similar situation, where everything seems to be going wrong.
Great recommendations. Steve Mould is another in that vein, and Kurzgesagt (though quite different stylistically) is one of my favorites and could be something you’re looking for.
Do the skills build on each other where they need to be done in order?
I got a subscription, but wasn’t super interested in the first one, so it’s still sitting in the box. Then the other boxes started showing up. I now have a full year’s worth and haven’t done a single one, because I feel like I should start with the one I’m least interested in.
They don’t… just do whichever one you are most interested in doing. Each box more or less stands alone (at least that is what I am observing from my kids assembly of them)
They use some similar ideas (a servo is still a servo in a different context), but they are totally independent of one another. Do the one you find most fun!
Taking a break from my agentic AI framework for prototypes and makers arkaine(1) and made two fun useful apps for myself
1. Eli5 equations(2) uses an LLM to convert a given picture of an equation to latex and, if given additional context, breaks down the equation parts to explain it. Gemini for the model.
2. reflecta - a journal prompting app with deepseek to help reword and target the prompts towards you better.
It's only a problem if we live in a society where people's perceived value, and thus capability of living a healthy, full life, is tied to their productivity to produce profit for an increasingly shrinking pool of people and organizations.
Which is what we have, hence the problem.
Yes, AI has the potential to screw things up royally. But do not mistake its' exacerbation of symptoms as the true illness.
The issue is that as music progresses and changes so too does distribution networks. Traditional, or even nontraditional to those from the pre spotify internet days, pipelines of music discovery have been largely co-opted by industry. Outlets of organic discovery are different now - and people typically don't continually keep changing their habits enough to keep up with it.
Pair this with the fact that most people settle their musical tastes to be in line with when they are experiencing the most emotionally significant time in their early lives (high school for some, college for others, etc) and the result is an assumption that
A) What they encounter forms an overall opinion of "all" new music despite being the tip of the iceberg and
That, combined with stock buybacks and the general take over of Friedman-economics resulted in a far more focused short term thinking and outsourcing research as much as possible due to uncertain horizon risks.
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