I’ve spent most of the morning reading blogs and articles containing tech predictions for 2010. While I don’t have much faith in any one person’s prognostication skills, browsing through a bunch of these lets you triangulate your way toward a general sense of where things may be headed.

Anyway, here are 50 or so of the more interesting ones…

• 2010 Predictions For Virtual Events
• IDC IT Predictions 2010
• Top 5 trend predictions for analytics in 2010
• Predictions for 2010: Chris Selland’s List
• Five Enterprise Software Predictions for 2010
• 2010 Predictions from ReadWriteWeb
• Eight Predictions for 2010 from CCSinsight
• 10 Predictions for 2010 from PCworld
• Wired’s Predictions 2010: The future of Twitter, Google, everything else
• Top 10 Telecom Predictions for 2010
• 2010 Consumer Internet Predictions
• 2010 Mobile Predictions
• 2010 Cleantech Predictions
• 2010 Top 10 SMB Technology Market Predictions
• Five Social Media Predictions for 2010
• 2010 Prediction: Harry Ruda, Desktone
• Middle School Marketing: 10 Predictions for 2010
• inCode Reveals Top 10 Telecom Predictions for 2010
• The Year in Digital Music and Predictions for 2010
• The Future of Tech, 2010 Edition
• 2010 Predictions for the Outsourcing Industry
• Not the first, not the last, technology predictions for 2010
• Cast Your Top 5 Predictions for 2010!
• 2010 mobile advertising predictions from the road
• Predictions for 2010
• My Three iPhone Predictions For 2010
• Predictions 2010
• SNS Predictions for 2010 Released from New York
• CMS Watch announces Content Technology Predictions for 2010
• 2010 Predictions for Endpoint Virtualization
• Six Social Media Predictions for 2010
• Cloud Computing with a Chance of Convergence for 2010 Predictions
• 10 Storage Predictions For 2010
• Advanced Analytics Predictions For 2010
• 2010 IT Management Predictions For 2010
• 10 Predictions for 2010
• Predictions 2010: Media (Dinosaur Media DeathWatch)
• Ten predictions for 2010
• Microsoft Will Buy Twitter, Adobe to Buy Picnik, and Other Bold Predictions for 2010
• Five Music Predictions for 2010 (and Five Reasons Why 2009 was a Flop)
• CNBC Predictions 2010: Media
• 2010 Online Marketing Predictions And Insights
• Predictions for DNS 2010
• Top Ten ERP Software Predictions for 2010
• Technology Predictions 2010
• Ten Predictions For The E-Reader/E-Book Market In 2010
• 20 social media predictions for 2010 that might actually happen
• 8 Predictions for SEO in 2010
• Early Predictions for 2010
• Predictions Thread - 2010
• Top 11 Predictions for 2010
• What’s Coming for Open Source in 2010
• Predictions for the Groundswell in 2010 — Twitter gets serious or gets bought

Every year before Techcrunch50, I predict which startups I think will present at the conference. Here’s how I did:

Of the 50 main stage presenters, I predicted 7 of them. (Actually I picked 8 of them, but I removed “Yext” at the last minute because it’s not really a startup.)

Of the 100 Demo Pit companies, I personally predicted 34 of them, and the follow-up emails I received from other people contained another 10 I didn’t know about.

I disclosed my methods to some of the folks at Techcrunch, so I suspect that next year (if the conference survives another year) this will be considerably more difficult!

A few days before Techcrunch50 last year, I made some predictions about the presenting companies, and I think I did pretty well.

On my list of predicted presenters, I correctly guessed 65 of the Demo Pit companies and 3 of the Main Stage companies on it. Not too bad.

I’m not sure I can match that performance this time around. Everybody seems a little “stealthier” this year. But I decided to go ahead and compile a list of startups that I think might be launching at TC50 (aside from
the Penn & Teller project which has already been announced).

Fair warning - this is about as unscientific as it gets. The list is mostly based on stumbling across private betas that just look right, published launch dates (eg, “Launching September, 2009″), Twitter rumors, YouNoodle, Google and general web chatter, so your mileage may will vary.

So here are my top 100 predictions (in alphabetical order):

UPDATE Fri, 09/11 - I’ve received a couple emails today from my fellow researchers with still more possible presenters:

Email #1 from CA:
—————–
meebee.com
cloudfederation.com
tinychat.com
todayforward.com
ecomkick.me
yoomoot.com
rentoni.com
devstrom.com
myinfoq.com
diagramic.com

Email #2 from GW:
——————
Kijubi
Wello Horld
Motally
GoGrid

UPDATE Sat, 09/12 - Another email w/3 TC50 possibles:

Hytle.com
RentCycle.com
UltimateHire.com

Last year, I did surprisingly well in my attempt to guess the TC50 presenters.

Unfortunately, this year I’m too busy preparing to launch my own startup to focus too much on the goings-on of other people’s. Even so, habits die hard so here are 10 startups that I’m pretty sure have submitted applications to Techcrunch 50. I’ll post more as time allows.

1. otherpage.com - revenue sharing platform
2. shecket.com - residential property management software
3. worknlearn.com - student-related
4. klickfu.com - computer gaming
5. inviko.com - “monetize your contacts”
6. kotsego.com - “creating and optimizing user experiences”
7. touchring.com - “style your social voice”
8. d3sync.com - not sure
9. puffingnew.com - not sure
10. fabeetle.com - financial advisor rating platform

In the so-called “second-place search wars”, Bing appears to be solidly ahead of Yahoo Search in Scandinavia, and is now steadily achieving more search share than Yahoo Search in two major search markets: Australia and Canada.

The following is based on searches conducted on Statcounter clients, from June 1st until today (June 18th):

StatCounter’s global search engine referrer data indicated that on Thursday, June 4th, Bing.com brought in more search traffic than Yahoo Search… at least to the sites they provide analytics for.

After the initial buzz - and astonishment - quite a few bloggers, commenters and twitterers jumped in and basically said “But who the heck is StatCounter? Let’s see what Hitwise, Comscore, Compete etc. say about it.”

Although that may be a perfectly reasonable response, it bugged me a little because I’m not convinced that web panels (like Comscore, Hitwise, Alexa, Compete, etc.) are the best way of getting at THAT type of data. Different data requires different approaches and, in this case, I think I prefer StatCounters’ approach.

A panel of web surfers is at its best when gauging “broad-spectrum” results, like the “100,000 most popular websites” for example. But a web panel is NOT a superior method for obtaining narrow-spectrum results, like “most popular monitor resolution” and the like.

Here’s why:

If your user panel size is 2 million (like Comscore’s, the gold standard), you only have 2 million “sources” of data. For broad-spectrum work, where you obtain multiple datapoints per user, that’s great. In other words, if each user views an average of 100 web pages/day, that’s 200 million datapoints/day, and that’s a nice big number.

But for narrow-spectrum work, ie, things that yield fewer datapoints per user (usually just one) like operating system or geographic location, panels are not necessarily superior, and there’s no inherent advantage of using that method over Statcounter’s inbound analytics approach.

The question is: is search engine referrer data a broad-spectrum or narrow-spectrum dataset? Honestly, I’m not sure, but I would argue that it’s fairly narrow:

While a panel member may visit 100 different websites/day, many will use just ONE search engine. (Maybe two for the more adventurous types.) So even with an enormous panel of 2,000,000 users, you’ll still get just 2,000,000 datapoints on the matter of search engine preference, regardless of how many pages they actually view on the site.

And, if it is a narrow-spectrum datapoint, then given the same sample size, I personally would prefer to observe a group of sites instead of observing a group of users. In other words instead of using the panel model of tracking the surfing activity of a set of known users, I suspect you’d get superior results from using the analytics approach and observing the incoming activity of a dispersed, unknown group of RANDOM users. Again, this assumes the user sample size is the same and that we’re tracking something sufficiently narrow.

As for sample size, StatCounter says they track over 10 billion pageloads per month, representing over 2,000,000 unique visitors to the 3,000,000 websites they track. If so, that’s roughly the size of the well-known web panels, and, again, a bit “more random” than web panels since the visitors to StatCounter’s client sites haven’t self-selected to have their online behavior tracked.

Back in the good old days (2007), it used to be the courteous thing to do on Twitter: to follow those who followed you. Of course at a certain point, that philosophy rendered Twitter less and less useful to you. That is, if you follow 1,000 people, you don’t really follow anyone. But even so, that was sort of the custom.

But now the Twammers (twitter spammers) have arrived in full force, and I think we’re about to see “Twitter bankrupcy” - wholesale UNfollowing - on an unprecedented scale. People are waking up to the fact that not all Twitter followers are created equal.

There are now lists being published and sold of Twitterers who tend to follow their followers. If you’re on the list, you will be deluged with highly motivated internet marketers looking to build their Twitter following… by following you and thousands more like you in hopes of reciprocation.

That’s all they want. They have no interest in who you are or what you’re saying. They only pretend to listen to you, so you’ll listen to them. (The irony is, of course, most of THEIR followers are only pretending to listen to them for the same reason!)

There is a large (and growing) sub-industry that I’ll call “How to get more Twitter followers” (as if that were an end in itself). Dozens, maybe hundreds of ebooks have been written on the subject. There are at least 4 major software apps being marketed that automatically grow your Twitter followers. How? They automatically follow 2-3 hundred people/day and then wait to see which ones reciprocate by following you back. Those that don’t follow you back get unfollowed. Rinse. Repeat.

Oh yes, there are also apps that will automatically follow those who follow you so that YOU can get on those lists as well and “build your Twitter following.”

But people aren’t stupid. Not for long anyway. Eventually, the only people who will “followpricate” (I just made that up) will be fellow marketers, and the bots mentioned above. Ideally, this will come down to 20,000 internet marketers each with 19,999 followers, all broadcasting their spammy offers to each other, leaving the rest of us alone. Hopefully.

But the only way to make that happen is for regular people (those who aren’t self-serving internet marketers) to declare Twitter bankrupcy… at least the Chapter 11 version of it, and stop enabling and encouraging junk by unfollowing anyone who spews it.

In South Korea, naver.com is huge. In fact, it’s the #1 website in the country… even bigger than Google.

Did you know that QQ.com is the second most popular site in China? Or that fc2.com is the second most popular in Japan. Yeah, me neither. In fact, I’d never heard of any of these until just a few minutes ago.

It’s not just Asian websites I’m unfamiliar with. Certainly Americans tend to be, well, “Americentric” but I like to think that I keep up with these kinds of things. I mean, it is the WORLD wide web after all. But I was surprised at how many VERY popular foreign sites I had never heard of. Ever.

Below is a small list of important foreign sites that we probably ought to know. All of these are extremely popular in certain parts of the world, and I’m embarrassed to admit that I’d never heard of any of them.

IBM has the unfortunate - although accurate - reputation of being right there at the birth of new technology, and not capitalizing on it.

IBM famously blew it on the PC and the graphical OS interface (anybody remember OS/2?), and less famously on word processors, and… search engines.

Yes, IBM had their own “Google” way back in 1997 with the same basic concepts and technology. And since you’ve never heard of “Clever”, you already know how that turned out for them.

In May of 1997 (a year and a half before Google launched) the clever folks at IBM’s Almaden Research Center invented a search technology they called “Clever.”

Here’s how they described it back then…

In other words, Google.

On October 1998, a month after Google’s launch, the journal Management Consultancy wrote a review of Google and Clever. (This may have been the first published review of Google, BTW.) In it, author John Geralds interviews Larry Page on the technology basics and then says…

“Google currently has more than 25 million indexed pages and hopes to raise that to 100 million.”

As for Clever, Geralds writes:

Google is not the only start-up developing new ways to search the Web. Clever is being developed at IBM’s Almaden Research Center. Like Google it ranks pages by calculating links between them and measuring importance but it does not crawl the Web*.

The system, based on an algorithm developed by Jon Kleinberg, a Cornell University researcher, looks at the links between pages and ranks the important pages at the top of the list.

“The principle of Clever is to exploit the work of millions of participants on the Web, who are all over the world, creating pages without any centrally directed motivation,” said Prabhakar Raghavan, a researcher at the research centre. “The Clever system exploits these distributed judgments and aims to extract one consensus view on any given topic.”

For example, people with soccer fan pages point to the same kinds of sites. Not only are they pointing to other sites, they are annotating what they point to. Clever follows these links, processes the text around the links and uses the information to draw out the communities around the topic in which the searcher is interested. The result is a page of relevant links separated into ‘hubs’ and ‘authorities’.

Now, one could argue that since “Backrub”, Google’s predecessor, actually began in 1996, predating the May 1997 publication of IBM’s “Clever” technology by over a year, Google had the jump on IBM. I’m not so sure. First of all, the IBM paper may have been published in May 97, but the IBM research project would obviously have been going on well before that. And given the state of IBM bureaucracy back then, it may have even predated Page & Brin’s original 1996 work.

But whoever thought of it first is beside the point because by late 1998, IBM was at least even with, if not ahead, of Google. Furthermore, IBM had thousands of scientists and billions of dollars at their disposal. Google was 2 Stanford kids with Andy Bechtolsheim’s $100,000.

*One could also say that Clever’s fatal mistake was not crawling the entire web instead of just following authoritative links. But once it became obvious that was a superior solution, why didn’t IBM just flip that switch and begin crawling? Why did they let it die? How did that happen?

Postscript - I’ve asked a friend I know at IBM to explain the sad fate of Clever. He said he would request additional information from up the “chain of command” and get back to me in a few weeks. That’s okay, I think I just got the answer.