Incremental Blogger

Happy Birthday to my brother Layne!

The NYTimes has an interesting article on digital interuptions and productivity. The suggestion passed on in the article: Check your email less often. How often? Hmmm. Those details will be passed on in a forthcoming email :-).

NBC’s Tim Russert died today of a heart attack.

Listening to MSNBC online remembering Tim Russert.

We’ll miss you.

As the news settles down about Microsoft-Yahoo-Google dealings, I can’t help but reflect on a few things. Namely, the fate of these companies–at least in the stock market–is almost always tied together. They’re independent companies, yes, but when one is impacted by something they either all trend up or down together. Just look what happened over the last six months or so with Google, Apple, and Microsoft stock. There are very similar patterns in all three. Yep, their fates are tied together–not strongly, but tied enough.

Think back to when the DOJ made its anti-trust ruling against Microsoft back a few years. Is it a coincidence that it wasn’t just Microsoft that got hurt in the stock market after the decision, but almost about everyone? Put another way, almost all the tech companies rode a wave up and almost all rode the same wave down.

Now not all of the companies perform exactly the same. That’s where the real money making comes in for the traders. They predict when Apple will outsell the bunch or when Yahoo will fade back from the pack. But there’s no denying that one can affect the others.

The other point I’d make is that all of this focus on shareholder value isn’t the healthiest thing to do. The only focus of a business is not to maximize the return for its owners. Never has been. Never will be. Show me a company that’s doing this and I’ll show you a company that’ll be gone in no time flat. It’s important to keep making money, yes, but it’s not the only thing and there are many, many legitimate things that a company may need to do which at any given time do not maximize the returns for its owners at that time. It’s the time period that’s so crucial to everyone. And that’s the key. That’s where the money’s made. When a handful of people maximize their returns relative to the others because they did or did not maximize their returns earlier. Put another way, owners don’t cash out at every chance they get. It doesn’t work that way. I can appreciate why there’s talk of “maximizing shareholder value,” but it’s implementation is quite nefarious. There’s no recipe–except for sell now and if everyone did that right this minute, there’d be a terrible collapse in all businesses. They’re all that connected.

In a trip to tech-central, the Silicon Valley, Josh Bancroft finally figured out why he doesn’t feel like he belongs there: He hates the technology industry–not the tech part, but the business part.

Believe me, Josh, there are all kinds. It’s not just about Gizmodo gadgeteers or bluetoothed business people. It’s not a single dimensioned spectrum.

Take me, for instance. I’m a tech enthusiast that you’d probably group on the business side of things because I thoroughly enjoy thinking about how technology and businesses go together. However, to me it’s all about building and seeing someone benefit from something I’ve worked on. How does the business part fit in? First and foremost I’m a builder. I love making things. It doesn’t matter what it is–digging ditches, writing software, building Robots–I just like making things. But I can’t just stop at creating something in the basement. Doing so would give it no value, would be of no use to anyone else. I have to share it with others; I have to see people use it and learn from how they view it. This is where the business part comes in. This is where communication is so central to the technology itself. You have to not only make something, you have to communicate it, you have to transport whatever it is to them. I’m enthralled by the whole package. It’s a single thing to me.

I’m a bit quirky, I know. Besides making things I get a kick out of looking at office buildings and office furniture (I really do!) or reading about how people created this or that, the decisions they made, why they made them, what worked, what didn’t, what people at the time thought about what they were doing. All of this is so fascinating to me.

Over the years I’ve gotten a kick out of people trying to label me one way or another. I’m too much an engineer, not enough of an engineer, too much a thinker, not enough of a thinker, too much business minded, not enough business minded, don’t have enough commercial experience, too experienced with old technologies, too focused on new technologies. Don’t fall asleep yet. I could go on, but I won’t.

You know what’s funny though? They’re all correct. I’m all of those things. It may sound strange, but that’s why I love the tech industry so much. It’s so vast that I can be all of these things giving myself room to learn more and do better.

After the dot com bust the conventional wisdom was that tech was washed up. The big buyers were gone. No more $12 per click on web sites. No more IT infrastructure spends. No more big investment opportunities.

And then came Google’s 10x cheaper search ads. And then came Apple with its psuedo inexpensive consumer-focused iPod offerings. And then grew Google and MySpace and overnight efforts like YouTube. My, the world has changed.

What’s fascinating to me is how the success of these later efforts all grew during an economic lull.

So as we teeter on the brink of a recession here in the US, I’m wondering where things might be going next.

Will government efforts keep us through like we saw in the early 80s? Will the consumer and small businesses crank the economy along as they did after the dot com bust? Or will IT spending keep chugging away as enterprises try to cut their costs by moving to the Internet?

Not being very good at predicting the future, I’m going to pick the consumer in part because consumer spending can continue to benefit from the cost reduction and exposure of new products in the Asian markets. Given Apple’s propensity for focusing on consumer trends, this bodes well for Apple. If the costs are incremental enough, Apple probably will probably be able to keep a good thing going.

I also think Google–if they repeat their DNA of providing 10x cost reduction innovations–will fare quite well, because I think we’ll see more and more enterprises try to cut costs by moving to the Net, thereby effectively outsourcing and reducing tech management overhead. Likewise, as big expenditures will become capped, this means smaller departnamental purchases will become the norm and this again will play into the hands of individuals innovating by moving their department’s content and tools online thereby taking advantage of new communication and management efficiencies.

How will Adobe or Microsoft benefit? I’m guessing they will continue to solidify their strengths at the governmental levels, but that’s just a guess. They both will become standards.

Sun will strike to shine in all things Java, but against Adobe and Microsoft’s efforts I just don’t see it happening. I’ve been wrong about Sun’s demise for awhile though.

And then there’s the whole phone/communication thing going on. Might we see that the next big OS not be a desktop OS at all? I think so. Whether it’s Apple’s embedded OS X, or Google’s Android, or Microsoft’s Windows Mobile, or some other player, we’re going to see the crossover soon to these smaller OSes in part because the communication capabilities are so crucial to us, in part because Intel has hit a single-chip performane lull, and also because they will be at the one price point we can all afford during a recession. I’d put MIDs and low-cost PCs in this category too as beneficiaries of a tighter economy. There may be no better time than now for Google to introduce a very low-cost PC running Android, for instance.

Of course, I was wrong thinking that the economy was not going to faulter as much as it has. And I’ve been wrong about the success of various companies over the years. So don’t listen to me. However, I can’t help but ponder a bit about what this all might mean. What’s your take?

I’m trying out the new Windows Live Writer Technical Preview. All I can say is: Still no built in ink. Sorry folks. I want ink :-).

What will people think of next?: According to this site, artist Erik Nordenankar and DHL collaborated to track a package–containing a GPS–as it travelled a pre-defined route via DHL. The really clever part? The requested path created created the path shown here:

The making of the “drawing” is shown in the YouTube video below:

You don’t know how many times people have told me that this or that product/service/trend was a fad and therefore there was no reason to try it for themselves. The latest tech trend that people are calling a fad? Twitter.

After hearing this excuse for the umpteen time, I realized today that everything is a fad. Yep. Just look at all the things around you which are fads.

People often focus on the temporal nature of things as permission to call something a fad. Think about this though. How long does something have to exist before it’s not a fad? Five years? Ten years? Blogging has been around longer than that and people still tell me it’s a fad.

By this criteria, all restaurants are fads. How many eateries do you know that last five years? Ten? or more? Not many. Therefore, restaurants are fads. No reason to eat at them I guess.

And how many businesses really last that long. Not many. And of those that are fortunate to last over several decades, how many skip from one new thing to the next? By changing are they accepting the fact that the way they used to be was a fad, and that now they are on to the real thing? Guess so.

Take the airplane industry for instance. Was barnstorming a fad? Biplanes? Flying without electronic guidance? Beds on a plane? Eating a full meal on a plane? Checking in two bags of luggage? Must be.

Of course, this is all absurd. These aren’t fads. They’re more like things that were once viable and pragmatic given the realities at the time. And since things change, well, more things change. That doesn’t mean these things were fads. There might have been tremendous value in the way things were at the time.

Show me something who’s long term value is not proven or self-evident, and I’ll show you something that may or may not be a fad. You can’t tell. But be clear, that’s not what most people mean when they label something as a fad when you’re explaining something new to them. No. They’re just telegraphing to you that they’re not an explorer. So be it.

I’d like to see more technology used in schools, but requiring students to wear ankle bracelets wasn’t what I had in mind.

I guess there are several ways you could track someone’s location nowadays (such as monitoring someone’s cell phone location), but either way is tracking a student’s whereabouts for a school’s requirement to boost attendance really a good idea? This is especially unnerving because attendance is linked with financing to public schools. The greater the attendance, the more money the school receives.

I don’t think so.

From Geeks In Action:

“Carl Hayden High School’s Falcon Robotics team won the top prize in the international robotics championship over the weekend in Atlanta. The 42-member high school team includes students from some of the lowest income neighborhoods in Phoenix. The teens have competed this school year with a robot they built and named “Virginia’s Dream.” It was named for a girl that team members knew before she was deported after it was discovered her family was in Arizona illegally.”

Congrats to the Carl Hayden team. By the way, this isn’t the first time they’ve won a robotics competition. A couple years back they beat out several leading colleges to place first in an underwater robotics competition. Do you see a pattern here? I do.

I friend just IMed me a docx file that he wrote about his latest biking adventure. But I can’t read it. Why? I’m on my new dev machine and it doesn’t have Office. All I want to do is read this simple little file, but to do so I need to install Office. Call me lazy, but I don’t want to install Office for the umpteen time to just read a little file. (Yeah, I know eventually I’ll need to break down and install Office, but for now while I’m getting used to this new setup I like the simplicity of just the installed apps that I really.) What I would like is an online service that I can upload the docx file to and read it there.

I see I can convert it using Zamzar.com and I guess I could try emailing it to myself using Google GMail. I think it has a converter. However, both solutions involve emailing the document to myself. I just want to read it. I don’t need another copy of anything in my email.

I just checked out Writer at Zoho.com too. It’s an online Word processor that can import documents. Unfortunately, it doesn’t support docx files yet–at least that’s the error I’m getting–despite the fact that I read that Zoho supports this file type.

Hmmm.

And Microsoft has a free Word Viewer that I guess I could download. But if I go this route I might as well install Office.

All I want is a web service that lets me read a docx file. Does Microsoft’s Live group have something like this? I can’t find a reference to anything online. Seems like a natural.

There has been on and off again chatter about the semantic web. I can appreciate the goal of making the information on the Internet more searchable, processable and valuable.

Exactly how we get there is anyone’s guess.

The classic approach is to focus on text content. That makes sense, because that’s where the most value is on the web up to this point. However, with the explosive growth of digital cameras and live video feeds pounding at the door and ever smarter cameras as I outlined in an earlier post this all may be changing.

Here’s the deal: Automatic semantic interpretation of text is a tough problem. And human-based tagging of text is a pain. It’ll only get us so far. What we need are algorithmic friendly tools that will ease the growth of the semantic web.

As I pointed out in the last post, one of the tricks we need to employee is leveraging sensed data. The thing is that for the most part, text is written by a human and only consists of text. Photos and video streams come from devices and as such potentially also have augmenting sensory information. There might be local and global positioning information, there might be depth maps that go beyond the images themselves, and so on. Combining this information with a priori knowledge as I described in the post linked to above, you could make some rather good inferences about what’s in the images or at least what their context might be.

I think that leveraging the collective world of a priori knowledge plus sensory information that can “index” into it, would give the semantic web the most scalable and powerful results for the near term.

In fact, it could change the whole search game. Assume for instance that you’re searching for information on some new gadget. Text searches work well. But all text being equal it can be a bit tricky to find the best match based on the text. Search engines use authority and other measures to guess at what to return as search results. But assume that a writer of an article took and posted a photo auto-tagged with the product name, taken by him or herself, taken from the conference where the product was announced, and from within a private press area in the conference? Now it might be a bad judgement, but this may be the closest thing to a primary reporting source based on the image in the article, not just the text. As such, it probably ought to rank higher than other articles–no matter how authoritative they might be in other respects.

Now text does give us useful information. Analyzing the words, sentences, quotes (essentially social links), text format (short declarative, essay, Q&A, bulleted, etc), temporal context, and the like can give us clues about the meaning or context. But I also see potential information beyond what can be analytically extracted from the static text itself. For instance, editors could pay more attention to what we’re writing. For instance, when you’re typing all text is equal. But if you’re going back time and again editing a particular paragraph or sentence, that’s pointing out something to the program. It may be useful. It may not. Or what about collaborative edits? From your coworker? From your boss? From an anonymous online editor within a Wiki? Looking at these deltas the editor may be able to infer what’s important. After all, you’re probably putting more time into the key points, than minor ones. This may be a bad guess, but it points out that how we type may contain quite useful information. Think about it: A movie about the US’s Declaration of Independence doesn’t focus primarily on the words of the document itself, but rather the struggles over key words and phrases in the document as it was written. The edits.

There’s one other area where semantic processing may be relatively easy and that’s with processing computer generated content–for the most part. (Think databases at this point.) Column names and table names in databases often mean something. An app searching the web, scanning computer generated data ought to be able to leverage these and the databases themselves. With developers coallescing around a common language, or subsets of languages, it’ll ease interpretation of the results later. In some cases, the database-hosted information will be most important to interpretation. In some cases, the human-focused web pages will. In some cases, it’ll be the intersection, union, or non-overlapping nature of the information.

No matter what techniques actually make up the semantic web, my guess is that they will be incremental and will probably gain popularity and value because of some additional changes in how we do things. Might this be with smarter, sensory-based cameras? Dunno, but that’s where my guess is now.

There’s another round of bloggers talking this morning about image recognition–this time because tagging startup tagcow.com has entered the mix. Tagcow wants to help you tag images using some as of yet undisclosed processes. However it is done, photographer Thomas Hawk is impressed with the service. Michael Arrington suspects that humans are behind the magical process. Could be. Image recognition is tough–no matter how much startup passion you apply to it.

My stomach churns every time I hear about another image reco startup. Why? Because I think they’re essentially starting at the wrong end of the problem. For most image recognition, you don’t want to start with the image, you want to start before you’ve taken the image. Using whatever hardware or software combination you can, you want to be able to sense directly or infer directly at the time that the image is captured and tag the photo based on this data. If you’re taking a photo of people, let the camera tag the general area where the people are in the image. The camera at least has the potential of detecting the people (via motion or IR sensing) This is actually quite doable. Not perfect, but doable for many standup shots.

How might this work? The cameras need more sensing built in and open access to this information.

Yes, cameras already include fairly sophisticated sensing. They can adjust image capture based on distance measurements or light measurements or guesses about horizons and objects moving in the image and so on. This is a good start. But it puts the pressure on the camera companies to do all the work. As people want to do more and more electronically with their images, however, as you can see with tagging, the camera companies can’t keep up. One result is that people start dreaming up businesses to try to address the problems that the cameras aren’t solving. Unfortunately they are trying to solve a problem late in the pipeline, which only makes their work quite challenging, and quite often is a waste of money.

The better solution? Build cameras that are open platforms–both in terms of software and hardware. You need to be able to add sensors focused on your tasks at hand. You need to be able to tweak the camera’s software not only to improve the photo quality, but to target the tagging you need for the way you take photos. Many of the best techniques–whatever they are–eventually will make their way into the cameras themselves–but for the early adopters and trend setters, there’s not usually going to be enough there.

So what kind of hardware and software am I suggesting? I’d like to see hardware and software solutions that directly sense or infer the tags about the photos I’m taking at the time–or at least based on the sensed information of the image at the time.

If there is any image processing to do, processing image sequences yields better data than that which you can get from analyzing a single frame. You can see motion. You can average out noise. You can build confidence measures over time. You can try to build context from frame to frame. Working with one frame is tough–at times even for a human.

OK, so you’re shaking your head insisting that there’s no way all this hardware and software can be supported in a camera. Even if it were available today, you’d weigh down the cameras or eat up all the power. Quite possibly. But there’s nothing forcing everything to be within the camera itself. The key is to build cameras with open communication and enable a market of companion devices and services.

What kind of communication am I suggesting? You want all the data being collected by the camera sent to the companion device–in real time. You want access to the all the control within the camera from the companion unit. In essense, you want to be able to process the images using whatever it takes and then turn around and tell the camera to adjust the image this way or that way before and after the image is taken and then tag this or that part of the image based on sensed information. So at its most basic level you want a real-time video stream out from the camera and a control path back (possibly including processed image(s) and possibly additional sensed EXIF data). Alernatively, you want to have open extensibility within the cameras themselves. If you want to add a gyro sensor, you should be able to do so.

So what kind of sensors and data am I envisioning that cameras collect? Some simple ones: GPS (for global positioning); some new ones: camera orientation for location orientation (including inclination, compass heading, elevation, etc), light conditions, distance measurements using time of flight or whatever technique, etc. The trick here is that if there’s anything you want to know about the image, try to sense it directly rather than try to guess about it later in software. Likewise, whatever you can sense directly, try to build up processes that leverage this information the most, because it’s probably the most reliable and consistent.

But sensors will get you only so far. And here comes the next big step. Cameras (or the processing of images) need to leverage as much a priori knowledge about its surroundings as possible. If you’re taking a picture that intersects the GPS point latitude 37.74611 and longitude -119.53194, then you’re probably taking a picture of Yosemite’s Half Dome. If you’re at this location and your elevation is 8,836 feet then you’re at the top of Half Dome. Now let’s place the elevation at 30,000 feet. Now you might assume the Half Dome photo is taken from a plane. Three different interpretive tags. All useful. Essentially you’re leveraging “pre-tagging” or “a priori tags” of information.

This pre-tagging notion can go even further. Think about it. There can be a priori-tag services for sporting events, for graduations, for conferences and even showroom floors, for the national parks, and on and on. Imagine a service that the camera or post-processing of the camera location/orientation data can leverage to automatically tag the photo. Some of the tags could be entered by a Mahalo-like service, some by community efforts, some by the organizers of events. The point is: Why are all 10,000 people attending a basketball game expected to tag their own photos of the game, when we all already know they were there and the main context of the location?

Why are we not leveraging a priori knowledge that such and such location is of Robert Scoble’s house (notice the implication of time)? Or the beach? Or going further–my kitchen–or my backyard–or a booth at a conference–or a particular display area of a booth at a conference–or with the right local positioning information a particuilar gadget within the display area of a booth at a conference? It all depends on the collected sensed data from the camera. Some of these tags are easier to come by than others, but there’s lots of low-hanging a priori fruit.

Maybe such a service is provided by flickr, maybe by Live Search, maybe by the camera companies themselves, maybe by a Photoshop plugin, maybe all of the above. No doubt this would be a massive service on par witih Google Earth or Virtual Earth, but can you imagine??? Now this is where the VCs should be putting their tagging money.

Can a tagging service help me find all pictures of my dog? Probably not. It may not even be able to recognize a dog from a cat or a person (although maybe someone will figure that out too), but with the right information you may be able to leverage a priori tags to help in the search. You might have to think different about searches–kind of like how we all have adjusted to searching the “Google” way, if you will. For instance, to find all pictures of my dog I might think in terms of where he was and when. Was he in the backyard when I took a picture of him? Was he inside my house? This would yield a much smaller set of images that someone could quickly scan through.

This doesn’t help with tagging the names of people in the photos either. True. Maybe the human is best for this. But there are some possibilities. Maybe tags could be shared and cross-referenced so if two people took the same photo with intersecting rays at nearly the same time and both include people and one is tagged, then maybe the photo from the other person could be auto-tagged–maybe not at the level of faces, but of the image itself. Again, this would depend on additional sensory informaion collected at the time a photo is taken.

Anyway, lots of possibilities here. Lots of market potential. My guess is that Google has the right mindset to do it, but I wouldn’t count out Microsoft or Yahoo. Who knows.

I’m at a local developer event today, which is showcasing Silverlight 2. The event is being put on by Microsoft and a local developer group. Most of the people here appear to be .Net developers in one way or another. My guesstimate is that there are 400 people here, plus or minus.

Will it be interesting enough to Twitter? Hmm. It depends on whether Scott Guthrie, who will be giving the “keynote,” will audition with his latest Vegas act.