No, I’m not Dead. I’m just “very Busy” guys
A lot of things are happening at the same time: as soon as I have more time I’ll speak about it.

I’ll just make a list of things I would like to speak about… if I would have time to do so:

• My new Job in France Telecom R&D UK - Orange Labs and my work inside the Source of Webkit (and a bit of Opera)
• The fact that Joe Nocera was finally kicked in his balls by a proud Steve Jobs about his health
• Symbian going Open Source AND some (stupid?) rumors about Symbian “merging” with Android
• My aiming to buy a Samsung SM2032MW 20″ Widescreen TV Monitor- Black (that supports HDMI, DVI, RGB, SCART, 1080p/i and so on… (yes, for a PS3 ) )

But… I’ll just keep doing what I’m doing.
See you soon

After a year and a couple of months I’m going to leave Symbian Software Ltd. (London). It has been a very good experience as my first job in UK: a way to grow mainly, first as a Man, then as a Software Engineer… and then professionally in general.

A lot of interesting, inspiring, intelligent people (and a lot of NOT), that showed me “their way”: I took where it was worth it, not where it wasn’t… and left where I was able to.

Continue…

I was on my way to the office (yes, on Sunday: I have stuff to do ), when I see something that doesn’t look correct or “in the right place”. A Fox in the middle of Boundary Row!!!

A Fox in Boundary Row O_o

I don’t know, probably was bringing to my desk Firefox 3 RC1
Yes yes, I know: Firefox is not a Fox, but a Red Panda!!!.

I was looking for info about MapReduce and I thought that would have been a good idea to take a look at the Tech Talks published by Google. Here we go.

Title: 2007 Seattle Conference on Scalability: MapReduce Used on Large Geographic Data Sets
Location: Google Tech Talks June 23, 2007
Speaker: Barry Brumitt, Google Inc.
Abstract: MapReduce is a programming model and library designed to simplify distributed processing of huge datasets on large clusters of computers. This is achieved by providing a general mechanism which largely relieves the programmer from having to handle challenging distributed computing problems such as data distribution, process coordination, fault tolerance, and scaling. While working on Google maps, I’ve used MapReduce extensively to process and transform datasets which describe the earth’s geography. In this talk, I’ll introduce MapReduce, demonstrating its broad applicability through example problems ranging from basic data transformation to complex graph processing, all the in the context of geographic data.

Other than just the topic of MapReduce technique itself, this guy, Barry Brumitt, gives an hint of “how things work” in Google (developer wise). And it’s not boring at all: is actually quite funny.