Ideas to kick start innovative thinking

A school friend asked me last night about how to build a unicorn-scale business from a relatively small amount of capital. Essentially it's a question of innovation -- given the worst problem in your industry, or the area that most begs for disruption, how do you kick start your brain to think of better solutions? 

So far, I've come up with six thought triggers.

• The etherealisation of devices. For example, 20 years ago, medical devices consisted of very expensive sensors with a bit of dumb logic to give a result. Today, it's a race to the bottom on dumb sensors with more and more sophisticated logic. What's the cheapest thing you could use to take a measurement?


• The availability of motion and position sensors. How would it help if you knew exactly where data was entered? Or if you knew how your physical product moved in real-time?


• Explore some of the demonstrations on http://www.alchemyapi.com/products/demo (now part of IBM Watson). In particular, look at their ability to do sentiment analysis -- to give you a summary of how people are feeling about topics. What could you do with a summary of everything your customers say about you?

• Most people don't realise how good speech recognition has become as their only experience is Siri (which is very, very good) and they don't realise how general it can be. Try out a demo of Dragon Dictate, or use "Ok, Google" on an Android phone. What would you do differently if you could run your business on spoken information?

• Get a feel for how conversational bots are working. Look at this demo of an agent that schedules meetings: https://meekan.com/hipchat/  . There have some competitors, such as Amy from http://x.ai/ . Do the interactions you have with your customers follow some formulaic approach? How would you do things differently if the initial engagement with your customers was handled by a bot?

• There are generational differences in the way we run businesses (here's a blog post about a very interesting company that I did some work for: http://blog.ifost.org.au/2015/04/gen-y-businesses.html). What are the assumptions you make because you expect to interact via email?

Greg Baker (gregb@ifost.org.au) has worked with numerous startups -- http://www.ifost.org.au/startups/ for a short list -- as a developer, manager and consultant. He also runs mentoring sessions helping entrepreneurs wanting to bootstrap their businesses without venture capital or angel investments.

#AlchemyAPI bought by IBM for #Watson -- it's obvious whom IBM will buy next

Every time I start getting enthusiastic about an artificial intelligence company's products, IBM buys them for Watson.

Last year I blogged about the code I had written to make a Google App Engine mail handler which displayed summaries of emails by keywords and sentiment. Today I've discovered that AlchemyAPI (who provided a lot of the smarts) have just been bought by IBM.

Earlier last year I was working with Cognea (and a few other chatbot companies) trying to get a service desk agent that could outperform human beings at a mega-sized organisation -- where even handling helpdesk text chats and email was a job handled by a large team. The part I was looking after (routing of incident tickets and predicting failed changes) turned into Queckt (AEED).

Yes, well, anyway, Cognea got bought last year too.

So here's my next prediction: IBM buys x.ai. 

Two reasons:

1. I'm a big fan of x.ai's work, so based on past experience they will be bought out by someone sooner or later. If IBM doesn't, someone else will.
2. Lotus has an integrated calendar and mail system. It's in large organisations with busy executives who could be served very well by an (AI) agent who could organise meetings on their behalf. x.ai only need to plug-in a new back-end calendar service and a new fetch-from-a-Domino-server mail client. Then Notes actually has a useful feature that might stop customers slipping away to Google Apps and Office365.

On the other hand, not every company with artificial intelligence products gets bought by IBM. For example, IFOST hasn't. ;-)

Here are some of the things we've done:

• Smart systems monitoring: automatic anomaly detection for events on CPU, memory and I/O; detection of log files without human intervention and then determining which messages are important or trivial; prediction of future capacity exhaustion.
• Intra-oral dental image analysis
• Improving ITIL ticket handling by 30% using vocabulary detection
• Identifying student learning disabilities by timing analysis

Let me know if you are interested in any of these. I'll make sure we're not bought out by IBM!

@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.

HP and Gartner doing a joint webinar on Data Protector

It's happening on Jan 30th, very early in the morning Sydney time, or Jan 29th for everyone else. Just for fun I ran the announcement through AlchemyAPI's language analysis tools to see what HP's key messages are...

Keyword and Relevance

data center environment

0.900901

positive

analyst firm Gartner

0.684689

positive

continuously evolving landscape

0.675654

positive

analyst Dave Russell

0.663644

positive

elastic core data

0.640681

positive

modern data center

0.59824

positive

data protection

0.596675

positive

Adaptive Backup

0.551905

neutral

traditional architectures

0.496183

positive

recovery challenges

0.490281

positive

Key trends

0.469901

positive

recovery requirements

0.462933

positive

HP

0.386948

positive

webinar

0.359441

positive

datacenter

0.358502

positive

solutions

0.353497

positive

demands

0.3495

positive

functions

0.333073

neutral

legacy

0.332964

positive

foundation

0.332838

neutral

ability

0.331847

positive

components

0.330498

positive

Topics

0.329724

neutral

environments

0.329655

positive

organization

0.329415

positive

business

0.329328

positive

Constantly evolving data centre: yes, that sounds about right.

Greg Baker is an independent consultant who happens to do a lot of work on HP DataProtector. He is the author of the only published books on HP Data Protector (http://www.ifost.org.au/press/#dp). He works with HP and HP partner companies to solve the hardest big-data problems (especially around backup). See more at IFOST's DataProtector pages at http://www.ifost.org.au/dataprotector

Keywords from emails on Google App Engine

Today I was working on a project which needed to have a summary of comments (especially emails) sent by the staff working on it.

The software runs on Google App Engine (because I wrote it), so it was surprisingly easy to add this courtesy of AlchemyAPI.

App Engine can receive emails, that's just a matter of adding to the app.yaml configuration.

inbound_services:

- mail

- url: /_ah/mail/.+

  script: emailmgmt.app

  login: admin

Skipping most of the actual program, it was essentially this.

class EmailHandler(InboundMailHandler):

  def receive(self,message):

   (content_type,body) = message.bodies().next()

   a = alchemyapi.AlchemyAPI()

   data = a.keywords('html',body.decode(),{'sentiment':1})

   for k in data['keywords']:

      # store keywords and sentiment analysis 

   

That extracts the body out of the email, calls out to the Alchemy API, and returns the keywords from the email including the sentiment of the words around it (whether the word is positive or negative).

A bit of JavaScript had it displaying the keywords in colour. I sent the following email:

From: gregb@ifost.org.auTo: fun@app.appenginemail.comSubject: Site report 

They had some lovely stone gargoyles and some horrible fountains.

And out came some coloured summary keywords: stone gargoyles, fountains.

Greg Baker (gregb@ifost.org.au) is an independent consultant. If you are an industry leader and you need someone to catch your vision and help you make it reality, Greg might well be the right person to call.