There were no companies, as that would require private ownership of factories and other means of production. As the article says these were built in state owned factories. There were no other kinds.
There were no other factories and even small business was mostly nonexistent until the late 80s and in some cases punishable under the law as “speculation”.
The government very clearly provides for support for the equities in many ways (which I’m sure you’re aware of) How do the following not count as benefits to the equities in your vault?:
1. Maintaining a navy that reduces piracy enough to have global JIT delivery networks that reduce costs for corps
2. Protects corp interests abroad allowing a larger market and higher profits
3. Enforces regulations that attract a larger than otherwise likely share of people to put their money in the stock market, increasing the value of your equities.
I love the fact that a large portion of medicine is basically debugging and reverse engineering as a profession.
It seems to be a good time in the debugging of these complex pathways as there's another, related avenue of signal manipulation research that may lead to scar-less tissue healing (https://science.sciencemag.org/content/372/6540/eaba2374)
At first I thought it was yet another experiment that generates nonsense papers to show which journals will accept just about anything, but after running a quick search on some of the authors (https://pubpeer.com/search?q=Massimo+Fioranelli) seems like some sort of academic SEO/backlink/reference/paper mill operation going on?
Would be fascinating to map the cross referencing and co-author graph here.
That part is not as weird as it seems. It's not unheard of for VCs who are looking to maintain a relationship with a startup to provide an introduction even before investing as a gesture of good faith. Also, to clarify, the call was just a regular VC chat, the customer intro came later.
Granted that's usually the case when there's a competitive fundraising round that's coming up but it still not completely crazy.
I usually bring up this research when talking about employee onboarding but there was a study done in 2015 (with Mozilla) that showed a “good first issue” approach didn’t actually lead to the intended outcome - having more folks successfully integrate into and continue to contribute to a project over a long term. To my knowledge there hasn’t been a ton of follow up or replication but still something to consider.
Ahh this brings back memories. One of my first projects at a large investment bank was working on a tax engine where the first step was transaction classification using a decision table with dozens of columns and hundreds of rows.
The best part? It was loaded into a running service by parsing a complex Excel spreadsheet which lead to so much fun with debugging.
Results like these are not always malice, as other commenters pointed out search by price is not well figured out yet.
There are some issues with relevance ranking for price where junk rises to the top when you sort by price (https://medium.com/@dtunkelang/why-is-it-so-hard-to-sort-by-...) and Amazon may just be cutting off lower relevancy items when you sort by price as a heuristic.
What happened is that the technology spawned by the Semantic Web "fad" is now absolutely everywhere but it looks and works nothing like how people thought it would.
Freebase, after being bought by Google became the foundation of the Google Knowledge Graph (aka "things not links"). This kicked off an arms race between all the major search providers to build the largest and most complete knowledge graphs (or at least keep pace with Google [1]). Instead of waiting for folks to tag every single page, it turned out that simple patterns cross referenced across billions of pages were good enough to extract useful knowledge from unstructured text.
Some companies who had easier access to structured but dirty data (like LinkedIn and Facebook) were also able to utilize (and contribute to) all of that research by building their own knowledge graphs with names like the Social Graph and Economic Graph. Those in turn are helping to power a decent amount of their search and ad targeting capabilities as well as spawning some interesting work[2]
All those knowledge graphs became a major part of Siri, Alexa and Google Home's ability to answer a wide range of natural language queries. As well as being pretty fundamental to a lot of tech like semantic search, improved ecommerce search and a bunch of intent detection approaches for chatbots.
So yeah while the technology and associated research did turn out to be incredibly useful, adding fancier meta-tags to pages was not the direction that proved the most useful.
Retrofit(https://square.github.io/retrofit/) is probably one of the best Java libraries I've ever used, missed it a lot when working in Python. Cross-pollination is awesome.
I read it as the author of that quote explicitly _choosing_ to say that to make the message simpler to his target audience. I think the author fully understands that in reality it's a mix of both nurture and nature but there's plenty of unfulfilled potential in those kids so telling a little fib will help to push them to maximize their potential...and right now no one can definitively predict what that max is just by looking at their genetics
Something about your comment really struck me. In most sci-fi utopias, increasing automation was assumed to lead to cheaper marginal prices that gave everyone more leisure time. In reality the benefits from increasing automation (and globalization) have instead been naturally captured by those with the means (capital) to achieve them. Sounds a lot like we're either back on the road that Marx described where the few have all the capital or we're able to escape that fate by lowering the capital needed to gain those efficiencies (cloud computing, 3d printing)...
You are correct. The something new, at this point, is going on disability and waiting it out until they get Social Security payments. Most 50-year-olds with a high school education will not be becoming coders. If we are lucky, their kids are already working office jobs or have enough education/knowledge to do so.
As a country and society we will of course find new things to do, hopefully even replacing our manufacturing loss with even better technologies and methods. However, we will always have a huge discontinuity produced by globalization and automation that abandoned a significant portion of the population without the skills or the hope to catch on to the new fields.
I used GNOME for 10+ years and switched to the Mac a few years ago. The nail in the coffin was the Unity/Gnome Shell craziness that was so poorly executed.
Is it just me or this article outlining the most natural path for any Linux desktop? Rather then chase the general consumer, focus on your core audience who is already using your OS for the server.
Not only is it a more natural customer base, but you also have an advantage by eating your dogfood. GNOME devs would have 1st hand knowledge of what works and what doesn't for engineers and developers. And this sort of domain knowledge is gold when it comes to designing good interfaces.
I would love to see this effort happen, and might even go back to Linux if it really created something great.
I wish I could up vote the part about physical reality a few times more :) What's even worse is with something like usability, it's even more insidious since may never really find out something is "broken", or even think of it as being broken.
I've always thought of the various kinds of testing as adding some physics to constrain a purely abstract idea within some bounds.
There were no other factories and even small business was mostly nonexistent until the late 80s and in some cases punishable under the law as “speculation”.