@16z Outside of the USA, are we also seeing the same 16 themes in the way software eats the world? Here are my Oz impressions

I was perusing Marc Andresson's website. Marc is one of the better known venture capitalists and famously wrote that software is eating the world.

On his website there are 16 themes that he is seeing. Obviously, he invests big money in big startups, where I tend to be advising smaller and less splashy groups with little or no up-front cash. And north-western Sydney isn't Palo Alto. But there is quite a lot in common:

• Sensorification of the enterprise. Yes, the insurer-broking-customer system I've been developing with the best and brightest in the industry is doing that, and that's one of the big takeaways. We haven't even begun to tap what can be done with mobile sensors. This one is universal.
• Machine learning and big data. Obviously, I spend a lot of time helping customers with big data storage (as that's the other three-quarters of my work). Backup and recovery of big data is an issue that no-one knows how to do properly (myself included). But on the machine learning side, yes, I'm seeing this everywhere. There was the project where I was extracting keywords out from emails ( http://blog.ifost.org.au/2014/05/keywords-from-emails-on-google-app.html ) and displaying a colour summary of what the author of the email thinks about those topics. The data we got from the big data analysis I did of COI group's staff attitudinal surveys was extraordinary -- did you know that there are 5 distinct different ways to be a successful organisation, and another 14 to be unsuccessful? In another we found that a flower shop should stay open an hour later.
• Containerisation is not a trend I'm seeing yet in customers with existing infrastructure. What I am seeing is customers simply not having their own data centre presence -- not even maintaining a server rack or a local server. So the containerisation I'm seeing is more around self-contained applications managed by different companies.
• Digital health. From the dental camera system that I've been developing, to the start-up I was talking to last week, software is eating up the entire medical device industry. The medtech industry (which is big in Sydney -- bigger than most people realise) is turning into a developer of sophisticated software for small cheap sensors.
• I'm not seeing the efficient online marketplaces trend as clearly. Perhaps because I'm based in Australia with a smaller less efficient market (in general) but specialty and uniqueness is still common, and I don't see any Australian companies racing to the bottom on price and staying in business.
• Bitcoin and blockchain. The retailers I'm speaking to don't see bitcoin as a priority, but they don't really have a problem with it. So it will come, and the volatility will reduce. On the other hand, if I put insurance contract binding information into the blockchain, I'm pretty sure my insurance customers would freak out and run hiding. So this trend will come from the retail side.
• Funnily enough, whether to do cloud-client computing is a pressing question that I'm researching at the moment. That is, for two projects I'm doing at the moment I know I have a lot of in-mobile image and sound analysis computation to do. Bandwidth from the mobile is a problem, but so is CPU time on the mobile. Where to do it? It's not obvious which is better.
• I'm not doing any work for Controlability any more (that stopped when I went to google), but we were well ahead of the curve on that. What we were building in Darwin and Brisbane (hardly centres of technology) are what a whole bunch of "Internet of things" startups are trying to do now. It was secure, it was sensible, it was cost-effective and it made the residential development companies money. So I'm a bit biased on this: I think the rest of the world is playing catch-up.
• I can't say much about online video, but it seems to me that the money previously being spent on face-to-face training and e-learning is there for the taking as these move to video. I still don't have any video content to sell for anything I'm doing (I'm still writing books) but I can see the market is ready for it. Australia was well ahead of this curve, as the business of doing face-to-face training went undead several years ago; from what I've seen India and China are well behind on this curve.
• The changes sweeping the insurance industry: yes: real-time data extraction from company systems to give a day-by-day risk premium. We're working on it.
• DevOps: the week before last I was talking to a very famous software company about their SaaS offering. They have a long, long way to go to get from "sysadmins of a box that runs an application" to "site reliability engineering". Maybe, just maybe, some of the other Australian SaaS players are doing it better, but I doubt it. So few companies here have enough scale that they can do any statistically meaningful analysis of their outages or incidents. So while lots of people will talk about it, it's going to be a long time before DevOps is going to make a measurable difference here, sadly.
• Failure and the culture of fail fast. I see no evidence of this anywhere here. The vast majority of start-ups are self-funded, boot-strapping and grabbed an opportunity that arose. The QUT CAUSEE study showed no correlation between the success of a start-up and the number of failed startups the principals had been involved in. The closest QUT found was a kind of bonus for pivoting: if you changed direction as a result of customer feedback directing the company to a new product or solution in that industry then that was a very good predictor of success.
• I don't have enough experience to comment on full-stack startup, virtual reality and crowdfunding
• While I used to be able to say with confidence that I was a security guru, I don't think I can comment on Andresson's theme; I'm probably losing it.

What I found interesting is what didn't appear, but are really clear themes that I'm seeing:

• Image analysis is everywhere. Every company has dozens of problems which can be solved by moderately simple image analysis techniques. There simply aren't enough knowledgeable gurus out there to do the work.
• Interfacing with the low-tech. I think there's a Silicon Valley bubble which assumes that everyone wants to be on-line with a smart-phone all the time. But there are many workers and customers that simply can't or won't do this. In the last few weeks: a startup the severely disabled on-line with assistive technology; the retail conversations were around simplifying warehousing procedures so that the tech un-savvy can cope; the edutech project getting tech-averse sport coaches to be able to put wet weather into their school's twitter, facebook and skoolbag systems.