[deagler]

This is going to be great, The worlds top firms are now in direct competition with each other.

Microsoft(Cortana), Amazon(Echo), Apple(Siri), Google(Assistant/Now) and now Samsung with Viv. The possibilites are just endless, the space race netted us a lot of innovation and this should do the same. Competition leads to Innovation

[aswanson]

Competition is for losers. 10 years ago the battle was microsoft vs yahoo and whoever...and it turned out the ones to pay attention to were fb and twtr...etc. The big innovation, the one to dominate headlines in 10 years, is likely unknown, run by a few guys on a shoestring and barely on the radar right now.

[TheOtherHobbes]

MS, Apple, and Google are very much still around.

Twitter and Yahoo are up for sale.

FB is the only innovator on your list that could be classed as a newcomer. And it's been around for more than a decade.

I doubt we'll see the big innovation from a garage now, because the cost of entry has become too high for shoestring operators to succeed.

ML training needs fast, expensive hardware. You can experiment with it on a 1080 graphics card, but for industrial applications you need a lot more speed and power.

[aswanson]

The cost of starting a transistor startup in the 1950s was too high so the traitorous 8 started Fairchild.

The cost of starting a SSI company was too high in 1968 so 3 dudes started intel.

The cost of starting a new mainframe company in 1976 was too high for most garage ops but turns out two hippies were ready with a better, cheaper, replacement product anyway.

The cost of starting a pc company for Gates and Allen was too high in 1981 so they left it to IBM and wrote the OS. Turned out ok.

The cost of starting and OS company in 95 was too high for Brin and Page so they left it to msft and looked at how to reliably search the web.

The cost of starting a search engine was too high in 2004 so Zuck looked at how to connect people rather than documents. Good call.

See a pattern?

[madamelic]

>I doubt we'll see the big innovation from a garage now, because the cost of entry has become too high for shoestring operators to succeed. > ML training needs fast, expensive hardware. You can experiment with it on a 1080 graphics card, but for industrial applications you need a lot more speed and power.

This isn't the 1990's. AWS exists. Not to mention how hot VC is for AI startups.

Sure, we won't have 15-year olds making the next AI breakthrough but to say that AI is solely in the realm of "big business" is naive.

[JustSomeNobody]

Endless? No. We will have as many incompatible proprietary offerings. That's all.