While we do a lot of podcasts and videos at RedMonk, we get that not everyone wants to consume information in that format, as Dan Farber once described video to, it can be “incomprehensible media” to many. Thankfully, with a recommendation from Dana Gardner for the service, we’ve found an outfit that’s turning out to do high quality transcripts with a quick turn-around time.
Tom has been transcribing things over at Greenmonk, I’m starting to do some here. I’ll try this our on our regular podcasts as well. So far, I have tow recent videos done: FedEx Critical using RIA and an overview of IBM SAFE with Jeff Smith.
The interview and demo for FedEx Critical’s tracking application have gotten a lot of attention. As always, the demo gets much more than the face-to-face interview: people want to eat the meat, not only hear about the sizzle. But, there’s actually a good amount of RIA evaluation content in the interview, which you can now get to through plain text if you’d prefer. For example, Adam Mollenkopf walks through how they decided to go RIA:
It was actually quite a long process to get to the Adobe solution and we finally found a good solution with Adobe. So we experimented with a number of other technologies for the last few years honestly. We tried this with [Java] Swing, we tried this with Ajax component vendors and had miserable performance and scalability issues with it in the past.
And just due to the sheer volume of the thousands of trucks that we are trying to ship and the thousands of trucks that we are trying to track and the shipments that are trying to track as well just the amount of volume was too much for those frameworks to handle.
The other new transcript is for the discussion I had with IBM’s Jeff Smith about SAFE, the IBM Solutions Architecture for Energy and Utilities Framework. There’s also a great, short demo with Paul Williamson. As the interview and then demo show, it’s IBM’s approach for servicing the energy sector.
SAFE does a lot of work to, essentially, instrument and then data collect from energy grids, something that’s revolutionary from the sounds of it in the industry. What’s the point of doing all that? This transcript excerpt starts to paint the picture:
Really what this is, is a meter that can gather a lot of information about what’s going on in the realm that it can see and communicate in a two-way fashion with not only the items in the realm that it can see that are consuming the power, but also the utility that’s controlling the power in way that either causes intelligent things to happen in the facility or that gathers a lot of information, brings it back to the central location and then they can do something smart with it.
In the beginning the whole notion of an intelligent meter was to allow you to turn service on and off without having to do a truck roll and send a guy out there or a person out there to turn it on or not have to send somebody out there to read it, so you can tell how much power that the company was using.
Increasingly the intelligent meter will play a central role in and the actual optimization of the entire flow and so most people are starting with this notion of an intelligent meter. If you look at how this section of our framework we point out the technologies in the IBM product portfolio that would be involved in that example.
IBM is not in the meter business. We are for sure the business of the software, which would instrument the meter like actually — perhaps a piece of software that might sit inside a meter or in some kind of a collection point in a neighborhood were lots of meters are talking to it and doing an intelligent job of correlating all the information that comes from that meter – categorizing it, sending it back to central facilities, housing it, storing it and then allowing you to do trend analysis or predictive analysis on that and then ultimately feeding the notion of using that information for optimization.
Disclosure: Adobe and IBM sponsored the videos, and both are clients.