julianpye

Very interesting figures. Can you share the sources?

Google is all about searching for results and Facebook is all about demography and thus brands.

So Facebook is taking a lot of advertising budget to establish brands that used to be for print and television.

Simple example: Diapers. By the time you have a baby, Facebook knows that you as a couple are expecting and you will see ads establishing relevant brands. You would never see those ads on Google, because at that time you're not searching for them. This used to be the business of television advertising. So you know the brand Pampers long before you ever think of buying a pack of them.

Isaac Asimov: "The only people I ever met whose intellects surpassed my own were Carl Sagan and Marvin Minsky."

As a teen on weekends I worked a lot on filmsets as assistant to a lighting cameraman. Switching HMI lamps on was really amazing, the mood of the set changed in an instant. It was quite energetic, so I completely get what the author is saying. They usually were positioned outside of windows, allowing for a stable consistent sunlight simulation across scenes.

Facebook is the most agile of the companies. Two years ago it was a desktop web company, now it is all mobile. With Instagram it arguably made the best tech acquisition of this tech generation - compare that to what Yahoo spent money on. So don't see Facebook as a social app, see them as a powerhouse capable of making big moves and being able to respond to trends better than any other player. Since it has a hard time accommodating new functionality under its Facebook brand, it's perfected the art of managing multiple consumer brands.

How many of the plugins do you use and how many are overengineered for a simple purpose?

My first thought for Perl 6 killerapp: a html5/js build replacement for grunt, gulp and other such monstrosities.

Also related is their Accelerator program for India, Indonesia and Brazil. https://news.ycombinator.com/item?id=10750930

It's a sound strategy: to compete against Apple from the other side of the market scaling that side of the market up.

For me the advantage for Echo is not so much in speech recognition, but in hearing all sorts of other cheap household sensors. An Amazon dash button that outputs a high-pitch sound can be manufactured ~10-30 times cheaper than one that needs Bluetooth and WiFi. A cheap Smokealarm can become fully networked, a doorbell heard can activate added features, etc.....

That may become the fastest journey across the Gartner trough of disillusionment that I have seen. So it answers Fred Wilsons's question at http://avc.com/2014/09/the-bitcoin-hype-cycle/

As a parent with a small baby, I support your claim and feel your pain... I also found out that the status/quality of the parents' relationship is totally dependent on the baby's sleep.

Also really cool are the first pictures from Venus from the USSR Venera missions: http://www.space.com/18551-venera-13.html

The environmental challenge here was of course far greater than for Mars.

Does this effectively render any Parse or Firebase application (they only have US servers) that stores user information (e.g. email account) illegal in the EU?

It just finished 10 minutes ago on the livestream - http://www.twitch.tv/oculus - so it should be posted somewhere soon on YT.

Watch this channel at 1pm for John Carmack's lecture.

From OC2, but semi-offtopic - What did people think about the Michael Abrash lecture "These are the good old days"? For me it was one of the most inspiring lectures on engineering solutions for HCI solutions. The cool part was that it positions Oculus as a technology company supporting senses far beyond vision.

Reminds me of the Lavarand, the random number generator by SGI, built out of lava lamps:

https://en.wikipedia.org/wiki/Lavarand

And its site in all its Web1.0 glory: http://web.archive.org/web/20010926221159/http://lavarand.sg...

Sure we are using them, but for example the design support library is not very satisfactory.

The whole approach of backwards compatibility has not worked out well. Google's alternative approach for the last two years have been the Play Services, which are now a behemoth requiring multidex in your app, when the majority just use the API client libraries from them.

There are many useful libraries to get a close-enough Material experience working on the older devices. And I am not talking about the official support library, which should be at least on a par of many MIT licensed Android extensions out in the marketplace.

Right now according to my user demographics, I just decided to move to 4.2 (API 17).

Which means that what I learned at I/O 2013 can finally be put to good use!

The sad part is that I decided to skip looking enthusiastically under the hood of M, because I won't be able to use it anyway for quite some time.

One thing we experienced is that the major devices often use different chipsets on the same model. So Samsung may source a Broadcom and an NXP chipset for NFC for the same Galaxy S model to prevent a vendor-lock-in. However this may result in different behaviour across users of 'the same device'.

Please note that this is article is part of a special section of the Economist this week called 'What If'. It is highly speculative and more about the potential of scenarios and alternatives rather than a real article. As an example another article is a retrospective on the first 100 days of Hillary Clinton as president, having won against Marco Rubio.

I love the Economist and find the section thought provoking, but hope it is not a trend to soften up the paper.

While this is a nice overview over current systems, I am not sure if I would care much that my kid one day should learn them (he is 4 months now, so still a long time away).

But a lot of friends with children ask me how to introduce their kids to computing at an early age. They often believe that learning a computer language would be like learning other languages, allowing for some 'bilingualism' early on. We all know that's not true.

I am not sure if introducing a child to computing languages is as important as introducing it to other things first. I would rather introduce it to music or another spoken language. That I assume would benefit it's brain more rather than using technology (probably already outdated) that will be certainly outdated by the time the child is at highschool level.

I once worked in a German field engineering department of a large US semiconductor company as a student. In the department there was a noticeable barrier between one manager and the engineers. The following had happened there a few years ago: a client required a DSP to calculate the weight on a landmine switch. The departments engineers refused to work for the client bar one manager. They were threatened to be fired and they stayed on course and ended up keeping their jobs.

The way it worked was by one guy rallying, taking apart the specifications and explaining the actual moral implications to the engineers.

Thank you for the tips. You're right, we can't stop anyone from copying it and tell them they are free to try to do so. We are thinking of positioning the product for the initial cooperation as a market research tool rather than a product license. So they get data and insight rather than technology.

In the end despite the expensive recall, this was a big win for the Intel brand. The early processor years were tumultuous as on the battleground the 486 clones of Cyrix and TI lost. Intel went the Trademark way with the Pentium and the media embraced the incident as something that would sink them.

Although very few people would ever come across the bug, Intel allowed every processor to be exchanged. No matter if you were a gaming consumer or a giant corporation using coprocessor-heavy software.

So I remember a UPS driver coming by my student flat with an exchange processor and picking my faulty unit up a week later or so. It was incredible service that made Intel as a brand very reliable.

The playback devices were basically your PC with anaglyph glasses (terrible experience) or a PC with Nvidia 3D setup. This is the main difference.

Editing software were expensive Sony setups ($5K), plugins for Adobe AE or very feature-poor setups such as from Magix (around $200). Editing was very tricky, since there were few standards here, just many custom ways to do it. This is a somewhat difference, since it can be assumed that the path from capture to quickly experienced content may be very short and allow for a camera to youtube experience.

Creation devices were custom 3D rigs as expensive as the GoPro setup or consumer cameras like the Fuji W3 camera series. In this space, you are right, there is not so much difference there.

The interesting aspect here is the iPhone availability for Cardboard and the use of Youtube as the platform for 3D VR.

Youtube already had stereoscopic support, but there were not many clients available, content was limited and difficult to create with 3rd party solutions that all cost money. It never took off and couldn't ride the wave of the studio and CE company driven 3D momentum, which quieted down after a while anyway.

This time Google ticks all the right boxes. Client devices on iOs and Android. The videoplayer everyone uses. A $5 cardboard enabler. A capture platform with GoPro and free assembly software.

Most people think that creating innovative products relies on 'trend-spotting' and on reacting quickly to demands. But that is reactive. You can have a much bigger impact if you're willing to shape the future. This is why Doug Leone quoted is wrong when he refers to the PC and the iPhone as black swans, because they were not. They were products attempting to shape the future. Marc has an uncanny talent at detecting what startup may shape the future and creating a set of financial tools to ensure that market acceptance can happen.

This talent is what makes A16Z so amazing - they are so different from the average bean-counting VCs, whose sets of tools are focused on financial exits and powerplays inside boards.

This trend is in most companies business-driven, in others it is technical-driven. Few companies have technical leadership that can manage true AI resources. If you remember the ML courses from Uni and experts in that field, you can imagine why. In many universities AI departments are assigned to schools of psychology and philosophy. Only companies with a deep engineering culture as those mentioned here can build up true AI departments.

The other driver is business-driven. And this is where management demands 'AI experts', when what they really want is data-miners. And in many cases management prides themselves on 'AI algorithms', but we know that this is a term for anything that gets the results that management wants and may be far from intelligent and in most corporate cases a bunch of SQL scripts.

I was raised bilingual in German and English, growing up in Germany. For me both languages are very different and to this day I prefer English when I want to talk about ideas and areas where I explore while talking and I use German when I need to be precise. I could never pitch in German and really don't like talking about my projects in German, since everything needs to be exact and committed to.