Negative economic times generally have an interesting impact on technology tools because the resources dry up and organizations have less ability to take risks and buy new toys. So they replace this with learning how to use their current tools better, and figuring out how to leverage free technology tools. A simple example of this would be that small companies decide that there is no use spending $300 on Microsoft Office when they can use Google Docs for free. Another example is that instead of buying a whole new accounting system, people try to figure out how to extend the current system they have. In many cases this is a good thing because they learn that they can get a lot done with the horse they are riding instead of trading her in on the new model. Ergo, from a vendor viewpoint, there will clearly be winners and losers.

I like Google in a down market because their model is primarily free for tools, and funding that through advertising. Sure, their advertising revenues will drop, but their usage base will go up and as soon as the economy comes back, there they will sit with millions of additional users. I do not like Oracle, SAP, HP and Dell. These are easy suppliers to cut back on because they either make expensive software, or hardware that can be delayed. What about the small or medium sized business out there. How can they leverage technology in a down market…

Well, first off, be open to using free tools where you might not have earlier. There are open source applications that can be used if you will just invest some time to learn them. There are many clever marketing and advertising options that only cost your time to learn them and experiment. Every day of every week of every year at this point I see some new, free Website or online scheme that can help you find new customers or improve the relationships with current ones. Necessity is the mother of invention I suppose, but I would rather think if it as a recession is the mother of invention The next thing to do is take some of the free time you have on your hands since many of your customers are now wringing theirs, and learn how to fully utilize the software you have already purchased.

This is a great time to take a deep breath and really take the investments you have already made and leverage them. The fact is that when things are going really well, we are too distracted to fully implement software and hardware systems, so a slow down can give us extra time to go back and really figure out how to use everything we have paid for. My observation is that software like CRM systems rarely get even 50% utilized. Even network equipment can be sitting there partially implemented. We have custom reporting software, but do not spend the time to really build all the custom reports or dashboards that we need. We have website content management systems that let us have complete control over our sites, but we don’t update them nearly as often as we should. My metaphor is that a soldier uses peacetime to clean the guns and do some target practice so that when the battle starts, they are fully prepared. The same is true for this downturn. Now is the time to evaluate all the technology you use, and invest time in learning how to fully leverage it. Then take the next step and figure out what free technology exists that you could be using. Then when the smoke clears and the economy rises like a phoenix, you will be prepared to leapfrog your competitors.

Hidden in this is a message that it is not wise to fire all your IT people in a downturn. Although they may not appear to be revenue generators directly, they are often the people that can assure you can generate that revenue in the future.

Scott Klososky
Scott@klososky.com

This morning Picasa shot me an email, letting me know that my little sister had just posted her vacation pictures for all of her family and friends.  She went to New Mexico, and now she wanted to rub it in a little.  I was halfway through her photos when something caught my eyes.  Off o the right of the view area there was a new message… Picasa wanted me to add name tags.  You know, at first this didn’t shock me.  Flickr does it, MySpace does it, Facebook does it… but this is different.  Picasa first indexed my photos, all 5000+ of them.  That took a few minutes.

Then Picasa offered me a screen that showed me a view of faces it thought to be of the same person, but in different images.  And it was very, very accurate.  The image I scraped of my screen shows you some random faces.  (By this time I had spent too much time playing and already had the bulk finished.)  The face selected is that of Dana White, the guy that runs the UFC.  I selected him because he is already a celebrity, and because he’s a nice guy too.

Once I had selected his image Picasa prompted me to associate his face with a contact out of my Gmail account, smart.  (I will tell you why that is so smart in a moment.)  I typed in his name, as he was not a contact already in my Gmail system, and saved the tag to his image.   So now when Picasa finds his face in my other images, it has to decide if it is him or not.  Picasa is a machine, so it doesn’t exactly make arbitrary guesses, rather it uses mathematical equations to decide probabilities: is this image close enough to the tagged image to be considered a possible match or not.

Once the image is tagged, you see a cool little box around the person’s face when you are viewing a picture that contains them, like the one to the right here. (Click on it for a better view.)  If I had linked you directly to my Picasa album you could have clicked on his name to the right of the photo to see more images tagged for him.  On each of the photos there can be faces that are present in many more images on my Picasa site.  By tagging their faces you can allow the viewer to quickly move around the diverse albums but stay with an individual.  My wife thought this was so cool, she looked at pictures of the kids all night.  This is where the viewer gets the value, and where Google learns.

Google is using that mathematical equation that I mentioned a bit earlier, but it isn’t perfect, yet.  As I move through my Picasa pictures and tag all of these faces, the machine is learning, from me.  I find a picture with my 5 year old in it, tag it to her name, find her in another picture from three years ago, and tag that one; Google’s Picasa engine sees that, registers it and ‘learns’ that both images are of the same face.  This happens over and over, and soon enough, the Picasa engine will become very accurate at more than just facial recognition.  Not just accurate with pictures of my daughter, but with pictures of any face, or any two like objects.  You see, Picasa doesn’t really care that they are faces, in fact, they are just similar objects according to the math.  A set of measurements that do, or do not, coincide to produce a similar image.

But earlier I mentioned that Picasa was allowing me to associate these facial images with my Gmail contacts.  This is brilliant.  I get to associate more information with the person in my contacts section, and Google is again learning.  So what are they learning from this?  Well, they are getting a ton of useful data again.  Stuff like this:

• Am I in pictures with some of my contacts?
• What is the geographical location where the image was taken?
• In what other pictures is this person showing up in, and are those picture outside of my albums?

For instance, if I have you in my contacts, and you show up in some of my images, then there is a greater chance that we are actually more closely associated than just the many emails we exchange.  (Don’t forget that Google reads those emails too, only to provide ads, but still…) So now Google knows that you and I hang out and watch movies together, but hey, you show up in other Picasa albums across the ‘net too.  You know people I don’t know yet.  Perhaps Google should recommend that I meet your other associates?  Maybe Google will market similar products to you, me and the other person that has your images too?  If we attend social gatherings together, we might have similar taste in commercial products, right?

The first time I saw some technology like this from Google was the Google Image Labeler.  Image Labeler pairs you with an anonymous partner and then you are both shown an image, and a set of words that you cannot associate with that image.  Then you have a set amount of time to offer applicable suggestions as to what the image contains.  The more matches you get with your partner, the more points you both get.  This was, as far as I know, Google’s first real attempt to get the crowd to teach the machine.  Humans spend time looking at images, tagging them and the machine looks at the data to learn what the images mean to the humans.

Perhaps this technology will find its way into the enterprise in a way that will revolutionize our workforce.  Comparing your pictures of your products to every image Google can find, looking for the copyright infringement.  Or perhaps a service will spring up that can search images from public events,pictures taken by you and me, but tagged with the date and name of the event.  Once those images are known, the service could be searching for known people in the crowd so that you can market to them. Hey Bob, glad you enjoyed the event, here is a coupon for dinner in a deli close to the event.

All of this to show you that we are speeding head-first into a new era of computing.  One where the cloud is smarter than the individuals that make up the cloud, and Google is striving to be a massive current within this cloud.  The possibilities are endless…

Matt
matt (at) technologystory.com

Let’s start with the fact that we already know that we will have a much faster infrastructure shortly.  The Internet 2 system is already running in universities around the country and it is blazingly fast – some say over 100 times as fast – as what we use currently.  As we gain speed, we will also increase the availability of access because anyone that has a building will provide free access because they will have to; to not supply that connection will be to drive off 95% of the human race that will depend on immersive access.  This is not even hard to project it is so obvious.

Less obvious will be the impact of software and infrastructure standards on the Web.  Most users would not have an appreciation for the fact that we are still living in a world today where we have four different major browsers that are not compatible, and a complete jumble of back end technologies that provide the Web applications we run on.  Our current lack of standards makes it hard for developers to write software quickly and make it work for everyone.  The jumble of back-end technologies does a great job of crippling the ability to turn ideas into reality without month’s worth of testing and bug fixing across the competing designs.  A number of groups are working on a set of standards that would allow developers to write on piece of software and be assured that it will work on any computer flawlessly.  The will serve to speed up the pace of development and it is already moving pretty fast!

Another observation is that the browser and the desktop will become more and more the same.  In other words, you will be able to get on the Internet from any device and the desktop that you see will be completely Web-based but will appear more and more like your current Windows or Mac desktop.  This will cause users to become un-tethered from a specific machine and will become a critical front end for the cloud computing wave that is coming at us quickly.  Already I am starting to use my iGoogle screen as kind of desktop because it provides me all the widgets I need, and also gives me access to applications like email and Google Docs applications.  In other words, it has what I used to run from my Windows desktop in years past. I can sit down at any computer and log in to my Google desktop and BANG, I have access to my docs and email – and all the handy widgets I use.  Google provides the applications, the storage, and the front end – for free basically.

I will give you more thoughts on the Second Generation in a few days…

Scott