41–50 of 119 posts
In a similar vein, Apple, Google and Microsoft control the medium and have grown so powerful, I can't imagine there ever being a new "Google" that comes about the old grass roots method.
Someday Apple will be bought though, probably by Facebook.
Thats a very bold claim, that goes against Ray Kurzweil's hypothesis tech is accelerating. Maybe (unlikely) that cloud/mobiles is the end game for silicon. But what about quantum? What about biological? What about Nano? What about AI? Literally there are a ton of potential generational changes in the making that could turn everything on its head again
I think it will, at best, be a semantic argument in retrospect. The companies highlighted are all clearly defined as being bolstered by computing technology. But what about next generation, huge companies that are bolstered by computing and other technologies fused together? For example, if a company manages to create a brain-computer interface that gains global adoption and equivalent valuations to the existing tech…
It seems like the whole analysis is predicated on the idea that technology = software made in Silicon Valley, with unimportant secondary factors. That 3M and ExxonMobil are not "tech" companies because they don't make iPhone apps.
Every company is a tech company, not because we've had computers for a while, but because technology is what we build to get what we want.
These kinds of narrow, myopic, siloed takes miss the forest for the trees.
If you think the epitome of human evolution is going to be people looking at bright rectangles for eternity, you haven't been paying attention to what technologists are doing.
Earlier quoted context omitted.
Because it's evidence is pretty straightforward: you can take wikipedia's list of important inventions and plot their frequency on a chart. Of course, there are debates around which inventions count as significant. And there is recency bias. Never underestimate the power in something easy to communicate.
I think population growth also factors in. Population is leveling off. In the past century, the global population has quadrupled, so there are four times as many people to invent things in raw numbers alone. But global population will increase no more than 50% in the next century, which means we aren't creating a lot more inventors than we are now.
This is wrong on merit, and I am not sure why it is presented this way. The difference between a car company and a software company is economy of scale. I.e. economy of scale dominate the physical world but does not exist in the software world since I can replicate software at zero cost. In addition, new tools and new processes for software has increased the productivity times fold, which means that you need fewer de…
> 1) Move to the edge. Specially for AI, there is really no need for a central public cloud due to latency, privacy, and dedicated hardware chips. I.e. most of AI traffic is inference traffic which should be done on the edge. Inferencing is done at the edge, but training must be done centrally.
Anyone else is busy building little dumb cubes with microphones and speakers that send sound bites into clouds and receive sound bites to play back (heck, even Apple does it this way with Siri). Or other dumb cubes that get plugged into a wall socket and that can switch lights that you plug into them by receiving commands from a cloud (even if the origin of the command is in the same room). Or dumb bulbs that get RGB values from a cloud server which inferred somehow that the owner must have come home recently and which then set the brightness of their RGB LEDs accordingly. Or software that lets you record sounds bites, send them into the cloud and receive transcripts back. Or software that sends all your photos to a cloud library where it is scanned and tagged so you can search for "bikes" or whatever in your photos.
No matter what you look at in all that stuff that makes up what consumers currently consider to be "AI", it does inference (if it even does anything like that at all) on some cloud server. I don't like that development myself, but unfortunately that's how it is.
Earlier quoted context omitted.
However, the network effect in tech can be leapfrogged due to the zero marginal cost (as shown in this post). I.e. what network effect do you get from doing ML inference in the cloud? The case for big tech today is still the economy of scale and not network effects (maybe facebook have those, but it exists only if the interface to facebook does not change). The big tech players have economy of scale, due to their abi…
Did you actually read the post? > The case for big tech today is still the economy of scale and not network effects (maybe facebook have those, but it exists only if the interface to facebook does not change). This is only true if you believe that the greatest cost of developing software is running hardware. The greatest cost of developing software is developing software. Not only are economies of scale in compute ma…
this is based on a very dubious assumption that bringing compute closer is the only path for innovation.
and even that is not true, you could imagine compute being even closer with a direct brain interface (actually you could consider google glasses to be an attempt at bringing compute closer)
Earlier quoted context omitted.
However, the network effect in tech can be leapfrogged due to the zero marginal cost (as shown in this post). I.e. what network effect do you get from doing ML inference in the cloud? The case for big tech today is still the economy of scale and not network effects (maybe facebook have those, but it exists only if the interface to facebook does not change). The big tech players have economy of scale, due to their abi…
Did you actually read the post? > The case for big tech today is still the economy of scale and not network effects (maybe facebook have those, but it exists only if the interface to facebook does not change). This is only true if you believe that the greatest cost of developing software is running hardware. The greatest cost of developing software is developing software. Not only are economies of scale in compute ma…
See: Walmart -> Amazon, Nokia->Apple, MSFT -> Andriod.
I mean, what more of network effect did MSFT had in the 90's. It was dominating both the OS layer AND the app layer (office). And yet, it does not have ANY share in mobile.
Kubernetes is not minor optimization if you think about what it is. Yes, if you see it as mere container orchestration. But it is the first time that a widely deployed, permissionless, open API platform exists.
This is wrong on merit, and I am not sure why it is presented this way. The difference between a car company and a software company is economy of scale. I.e. economy of scale dominate the physical world but does not exist in the software world since I can replicate software at zero cost. In addition, new tools and new processes for software has increased the productivity times fold, which means that you need fewer de…
It really doesn't make a lot of sense to do AI at the edge (in terms of the various edge providers). But then a lot of edge cases don't make a lot of sense. The best edge use cases are fan-in (aggregation and data reduction), fan-out (replication and amplification - broadcasting, conferencing, video streaming, etc.) and caching (which is just a variant of fan-out). The rest of the cases are IMHO largely fictional - m…
For inference, I See 90% on the edge (I.e. outside of the clouds).
I've been thinking along the same line, albeit on a more personal take as a software engineer. Basically, starting around 15 years ago, there's the proliferation of bootcamps teaching fullstack development, because software startups were the new hot thing, and they desperately need generalist engineers that were capable of spinning up web app quickly. Rails was the hot thing those days because of this as well. Hence…
The rest doesn't really seem to have enough evidence for such a bold claim.