1. Your idea is probably not identical. You execution almost certainly won't be.
2. There is usually room to compete.
3. Innovations often take root slowly and need a network of collaborators and competitors to nurture them.
Continuous Liquid Interface Production (CLIP) also uses photopolymerization, but pulls the object from a liquid bath and uses a buffer zone. Still horizontal slices. The upshot is it's much faster. (Carbon 3D is the company behind this.)
The method in the article uses photopolymerization to solidify the object as a set of slices, but the slices are not horizontal.
The big drawback to photopolymerization is it only works on certain resins which can often have undesirable mechanical properties (high elasticity or brittlness, for e.g.) Potentially this method could be a way forward in that respect, because you might be able to put structural materials in the resin solution and end up with a composite. It seems easier to do this way than with CLIP or SLA/DLP, but I'm purely speculating.
Note that many people still use HMC without a closed form for the gradient, via approximation. In fact, Stan (http://mc-stan.org/) automatically approximates the gradient by default if none is given.
Specifically this is about what business customers of AI startups report about the impacts of AI adoption. Main result is for professional positions it creates more than it destroys, reverse for manual labor and clerical
>Auto executives say they need to avoid a nightmare tech scenario that’s become a common refrain at industry gatherings. They don’t want to become the next “handset makers”—commodity suppliers of hardware, helplessly watching all the profits flow to software makers like Apple
Weird comparison since Apple has always made the lion’s share of profits from hardware. Also interesting contrast between big automakers and Tesla. I see Tesla as being in the hardware biz primarily
This is a fascinating point. Perhaps the cleanest way to fairly treat your option value is to not compensate you in expectation, but to allow you to "sell" your idea internally when you have them. Employees could get a royalty, say, for a successful idea. Pricing the royalty is difficult, but it's still an interesting idea.
As I write, I realize this must have been tried somewhere. I know at one point Sandia Labs allowed employees to start spin-offs using tech developed there, but that's not quite the same.
These are price adjusted figures. So your truck driver could buy double the goods in the US on $4 compared to back home. If he could survive on $2, he can certainly survive on $4.
> Nielsen is eager to see what other disciplines will be refined or mastered by this type of learning
> of course it goes so much further
> The ramifications for such an inventive way of learning are of course not limited to games.
>But obviously the implications are wonderful far beyond chess and other games. The ability of a machine to replicate and surpass centuries of human knowledge in complex closed systems is a world-changing tool
I think R is in the early days of its demand lifecycle. Wait a decade or two (maybe less) and R will get more hate. I'm surprised how fast Julia has advanced toward being a suitable replacement for R. It's just a matter of time. Then Julia will be most hated when Language X comes to replace it.
This begged the question for me: "Is there a fire for AGI?"
He gives one definition that people have used before, about unaided machines performing every task at least as well as humans. But if you dwell on it a while, I'm sure you can find lots of disagreement about a) what that looks like and b) whether it is true or not (conditional on it being true to at least someone.)
This got me into a rabbit hole on Wikipedia about where all the peoples of Japan came from, and what makes the Ainu indigenous. If an indigenous people is the first to settle, not sure the Ainu are clear winners. Lots of dispute about early population dynamics of Japan.
It seems the Ainu are considered indigenous because some have maintained their culture instead of assimilating into the larger group, which is unlike the Jomon and Yayoi people who many believe are the ancestors of modern Japanese people.
In my view, there are many insights like this to be had by physically studying product users a bit more. The startup community has built a strong habit of studying users before a new solution is adopted, but not as much after.
'Desire lines' in parks are one example. Desire lines are the paths in the grass that get worn down because people use them even though the designer didn't plan for it.