Your body language hints at your emotional state. Communication Department scholars find that observing subtle changes in your torso and head movements can predict creative output or learning ability.
Mike Torres, Amazon Fire Phone, launch event!
- More innovation on Fire phone data plan wanted
- App developers should focus on Dynamic Perception API
- Out of box apps games / health / medical
In addition to Mike Torres, we had an opportunity to mix and mingle with the developers and other people who build software for all Amazons devices. Mike did live demo with Q&A shared insights I haven’t seen covered by the tech press.
To wit: I recorded on raw video all except three developer community questions that I asked. Roughly Mike’s answers:
Q. What Apps would Amazon like to see developers develop for Fire?
A. Firstly don’t be put of by compatibility with mainstream Android, we’ve done loads of work to make Fire compatible, its gonna take a day or two to make adjustments to typical Android apps. Get stuck on a technical issue and we’ve every incentive to help you remedy.
Q. What Apps are biggest opportunities for developers to write for Fire?
A. Apps using the Perception API (the four face tracking cameras) interactive games. [I’m thinking 3DS and PSP console apps where developers can develop for Fire w/o game studio budget]
Q. What out of the box Apps would Mike write if he was a Stanford PhD.
A. Medical Apps, again with the Perception API. [Amazon send Leslie a Fire Phone she is absolutely the smartest developer in HCI Medical field]
Mostly, my other focus was noshing on a variety of slider type foods and enjoying a couple of Pike Kilt Lifter ales. I did play hands on with the Fire Phone scanning UPC labels, which it handled with flawless product look ups into the Fire Phone notification bus (emails, texts, searches, all show up here).
What the phone didn’t do was recognize logo’s for example, a young lady had a Coach Handbag, the logo is uniquely recognizable to the eye. However its clear from Mike’s demo and playing with the Firefly camera scanner that Amazon is using a machine learning model to power recommender based search, thus the phone should learn. Perhaps this is an opportunity for a Startup Weekend ML apprentice learning app?
After the Q&A, Mike shared with interested folks how he went about preparing for interviews to get his job at Amazon, certainly these tips would have come in handy, I royally screwed my opportunity up. Google is your fire here! Also thanks Google for the Auto Awesome video above.
Coda: I really liked the Mayday guy demo. You can see him; but he can’t see you camera privacy. Worthy review from Todd Bishop at Geekwire more innovation on data plan.
For some startups, going mobile first will kill you, while going mobile second will let you live long and prosper. Here are four things VCs will tell you about going mobile first — and how to answ…
As top patent litigator Matthew Powers told VICE News, “The standard line in the business is, ‘The definition of a troll is anyone who’s suing me.’”
Bereft Respect, Hadoop’s the new MRP?
Why aren’t they famous yet?
Only time will tell.
Many of us expert in industrial recommender systems matching Supply and Demand missed the change over from shortage of supply to shortage of demand.
Venture Capital didn’t miss this backing anything mining demand inferences. In doing so helping create the open source Web 2.0 Hadoop business architecture to mine closed data sources for your personal demand, or rather inferences of your personal intentions, then often sold to advertisers for targeting.
Private Equity didn’t miss this shift, taking nearly every public ERP/CRM company operating at scale private. At the core of ERP is MRP (material requirements planning) which business use to match supply/demand. With shortage of supply, MRP behaves as a recommender system for chasing exceptions. With abundant supply, that came with globalization, quality demand becomes the imperative to chase.
In hindsight a new classes of companies have come to the for to creating certainty of demand. Greg Gottlesman at Madrona Venture Capital believes that Amazon is in the process of becoming the world’s most valuable company. Amazon creates the best quality demand, a credit card cleared order.
Meanwhile Facebook uses social computing to gather and mine personal data for demand, and sprinkles in adverts to help persuade demand. Others sell your data to ad-tech for targeting. Some even sell your identity details. Just about all make extensive use of Web 2.0 Hadoop for “big data” demand mining.
What can upset this Golden Pony, shortage of supply?
Shortage of water, oil and other precious raw materials can and will disrupt supply and demand. For example McDonalds and Nike are already investing in smaller suppliers and alternative sources to add diversity and reduce risks in regions of the world with sustainability issues like Indonesia and drought regions.
Nike even went as far as hiring Ward Cunningham to help with prototypes for working in the emerging era of sustainability. Alas, currently over investment in demand systems feels inversely proportional to under investment in supply systems technologies.
For example the core algorithm for MRP, around since 1970s has been revised for the demand driven era by Carol Patk & Chad Smith in Orlicky’s third ‘DDMRP’ edition — but not web 2.0 social technology updated. Internally we can surmise Amazon has built Hadoop MRP.
The DDMRP authors are superb APICs, Goldratt, TOC, Lean, operations experts not computer scientists — Carlos Guestrin, Ed Chi — versed in machine learning, or social computing technologies.
What can upset this Golden Pony, shortage of demand?
Another possibility, the search for quality demand runs into stricter privacy laws in Europe, UK, Australia. Requiring a shift from away from mining personal data. Emerging pointers supporting this direction are:
- Ward Cunningham’s (Smallest Federated Datastore) Wiki
- Brad Fitzpatrick’s (Personal Git) Camlistore
- Eve Maler’s (User managed identity) UMAWG
- Adrian Hall’s (user data-flows across devices) deconstructed.io
- Doc Searl’s (reverse CRM) VRM
- Drummond Reed’s (VRM cloud services) Respect Network
All these are private by default, put the person or enterprise back to control of their own data for generating quality demand in a granular fashion. Doc’s keynote for the Respect Network brings this shift to trust and respect into commercial perspective.
Net-net: I need to find a startup crazy enough to explore updating MRP, to match demand and supply with VRM and Respect. Perhaps Jordan Ritter of Napster fame, who has set up Ivy Softworks in Seattle for Data Psychics will incubate joining up the dots?