John Zeratsky writes:

Major corporations like Amazon, Google, and eBay see the value in doing this. Smaller but significant players like Six Apart and Ludicorp (Flickr) obviously see the value. By making their services transparent (whether that is an implicit or explicit goal), they are providing in-roads for other developers.

Which is how Andre Torrez can tie TypeKey’s authentication services to PayPal’s financial services and make something cool happen.

Similar things are happening at every level, from the bloggers (who include del.icio.us links or Flickr photos on their sites) to the developers (who integrate DropCash with MovableType or iPhoto with Flickr). I think this is just the beginning.

Forget the Google OS — we are well on our way to a viable Web OS. It may never have the grandeur of the semantic web, but it will have lots of small pieces, loosely joined.

Atanu Dey writes:

Stuff matters. What is stuff? Things that you find, things that grow, things that you produce, and so on. At the very bottom of the structure of any economic system is stuff. Economists call it “goods”.

Stuff is produced using land, labor, and capital – the factors of production. Advanced industrialized economies use relatively more land and capital (and use them more efficiently given that they have advanced technologies) and relatively less labor and produce a lot of stuff. The average amount of stuff available is therefore high because they have fewer people to divide the stuff among. So they are rich. They are rich not because they have more money, but because they have more stuff per capita. Since they can produce a lot of stuff using less labor, all of the labor is not employed in producing stuff and so the surplus labor can produce services. and the labor involved in services can be given a share of the aggregate production of goods. That share is called “income”. And this income is denominated in monetary terms. Money, in this case, is for facilitating accounting of the stuff produced and who gets how much. If you don't have stuff backing the money, it is useless. That is, handing out money to people does no good unless there is some stuff behind it all.

Production of stuff matters. That labor is required to produce the stuff is an unfortunate fact of life – so far at least. In a perfect world, robots would produce stuff and people would be unemployed, free to compose music or watch the grass grow or whatever. In the imperfect world we live in, we have to use labor to produce stuff. But the less labor we use to produce stuff, the better off we all are – with the obvious caution that we have to distribute the stuff equitably, of course. But the problem of distribution only arises after we have produced stuff. If little is produced, little can be distributed on average and therefore on average we will be poor. Distribution is a less taxing problem than production.

Now here is the point that I am building up to. If an economy produces a heck of a lot, and yet a significant percentage of the population is poor, then we know that there is a problem of distribution. In that case, we can improve the situation by a better distribution through transfer of stuff to those who are poor. But if the aggregate production of stuff divided by the total population is a small number, the economy will be a poor one irrespective of the distribution. Merely taking from Peter to give to Paul makes no difference to the aggregate amount of stuff available.

David Galbraith writes:

Having just searched for some software on Google I realized that the top results were 4 years old and useless.

It is not technically difficult to create date ordering, but it is computationally expensive and requires comparisons as documents are crawled. There is, however, one area where searching by date is already there: weblog searching.

The model where content sites ping a server when there are updates soves the date problem cheaply and increases overall relevancy. The ping model is as different from the way search engines currently work, as push is to pull.

This is another compelling reason why the search engines will be caught off guard if they do not pay attention to weblog style publishing and ping servers, not just as an additional feature, but a component that is core to what they do.

Jeff Jarvis has an idea:

It's time to tag people.

This comes out of David Galbraith's one-line bio and out of arguments I've made over time that the real future of classifieds is a generation beyond Craig and Monster: It's a distributed world where resumes and jobs (or men seeking women and women seeking men) live anywhere and they are found and matched by some specialized successor to Google that uses tags (e.g., work status, education, location, languages.... or smoker, nonsmoker, single, divorced, great personality). In that world, in essence, people, ads, and content are all tagged.

This also fits into the discussion below about the ethic of exhibitionism -- finding a way to exhibit key facts about our perspective so our public can judge what we say in that context.

So I started to wonder how I'd be tagged. Would I tag myself? Would the crowd tag me? Would a machine (based on my content and the links to it)? Would it be some Frankensteiny combination?

Would tags go to war with each other? Would the Democrats for whom I'm not conservative enough slap the Repubicans for whom I'm too liberal or would it all average out to centrist?

Would the tagee have the right to modify tags (like a credit report) or would that be self-promotion?

In the end, it needs to be a way for people to find people as well as content and comment and communities.

So how would I tag myself? Here's a try: media man... blog boy... tall... fast-talking... parent... Howard Stern... Entertainment Weekly... TV Guide... New York... New Jersey... Iraq... Iran... FCC... centrist... shaky Congregationalist... exploding TV...

Bundeep Singh Rangar of Ariadne Capital writes:

The telecom company of the 21st Century is a software company. It is hereby dubbed the “Softcom.” Gone are expensive installations and maintenance of PSTN networks. Softcom’s hallmark is its use of software, soft-switches and the Internet Protocol to route data across millions of Internet routers across the world. Voice is just one of many data applications across its myriad of IP connections. Broadband connections to the home and office have opened up what was the privilege of those who owned the last mile. Customer service is courtesy of your best friend.

What does this mean for the telecom company as we know it? What does it mean to own legacy infrastructure? Does it fight the Softcom, partner with it, or indeed, become it? Will its deep technology, customer base and telecom operations experience ultimately make it a winner?

What does this mean for the mobile network operators? Will the Softcom challenge its ubiquity? And drive prices down to nothing. Will the fixed line telecom and the Softcom become best friends and take on the MNOs?

Is the triple play of voice, data and video is just the beginning of things to come? If that’s the case, why won’t that get ultimately commoditised making the Softcoms and telecoms companies just like other utility companies. Telecoms could look more like cable companies with data pipes being their business.

The New York Time has an essay by Steven Johnson:

2005 may be the year when tools for thought become a reality for people who manipulate words for a living, thanks to the release of nearly a dozen new programs all aiming to do for your personal information what Google has done for the Internet. These programs all work in slightly different ways, but they share two remarkable properties: the ability to interpret the meaning of text documents; and the ability to filter through thousands of documents in the time it takes to have a sip of coffee. Put those two elements together and you have a tool that will have as significant an impact on the way writers work as the original word processors did.

For the past three years, I've been using tools comparable to the new ones hitting the market, so I have extensive firsthand experience with the way the software changes the creative process. (I have used a custom-designed application, created by the programmer Maciej Ceglowski at the National Institute for Technology and Liberal Education, and now use an off-the-shelf program called DEVONthink.) The raw material the software relies on is an archive of my writings and notes, plus a few thousand choice quotes from books I have read over the past decade: an archive, in other words, of all my old ideas, and the ideas that have influenced me.

Having all this information available at my fingerprints does more than help me find my notes faster. Yes, when I'm trying to track down an article I wrote many years ago, it's now much easier to retrieve. But the qualitative change lies elsewhere: in finding documents I've forgotten about altogether, documents that I didn't know I was looking for.

What does this mean in practice? Consider how I used the tool in writing my last book, which revolved around the latest developments in brain science. I would write a paragraph that addressed the human brain's remarkable facility for interpreting facial expressions. I'd then plug that paragraph into the software, and ask it to find other, similar passages in my archive. Instantly, a list of quotes would be returned: some on the neural architecture that triggers facial expressions, others on the evolutionary history of the smile, still others that dealt with the expressiveness of our near relatives, the chimpanzees. Invariably, one or two of these would trigger a new association in my head -- I'd forgotten about the chimpanzee connection -- and I'd select that quote, and ask the software to find a new batch of documents similar to it. Before long a larger idea had taken shape in my head, built out of the trail of associations the machine had assembled for me.

A second post has more.

How does one go about building multiple models in our minds? There are three things that we can do which can help us. Underlying these ideas is the assumption that we are open to learning.

1. Read-Think-Write: The importance of reading is only too evident. But that reading also needs to work as a stimulant for thinking as well an attractor for external feedback. All of this can be accomplished via a weblog. I think to sustain a blog requires that it may made part of a daily discipline. It is not necessary to always write something new. Some of the posts can also be an aggregation of what others have written, serving to amplify one’s own memory.

2. Meet People: Interacting with people form outside one’s immediate circle of family, friends and business associates is important because it exposes one to different, often contradictory viewpoints which can challenge our mental models. By opening ourselves to constructive criticism from others, we can enrich our own ideas. I find meetings useful both for clarifying one’s own thinking (how well are we able to explain ideas to semi-strangers) as well as generating new ideas (often, these ideas come from some associative memory link that I find myself navigating).

3. Eliminate Blindspots: Many times, we just close ourselves off to certain things – perhaps, based on a past experience. It is necessary to revisit what we perceive as our blindspots and work towards limiting their impact or even eliminating for them. For example, until recently, I complete ignored the developments in mobile phones. I thought that networks were too slow for any data services and that the input/output mechanisms were too primitive. It was only when I consciously decided to give it a try that I realized how wrong I was and how much the technology had progressed – the thrill I experienced getting my email auto-delivered to my Nokia 6600 was comparable to my first experience of the Web just over a decade ago. Now, I am clear that mobility has to be a key component of all our future thinking.

Going back to the earlier discussion on rural India: how can we apply a multi-model mind to come up with solutions? To me, two points stood out that day as I listened to the presentations. First, the notion of hubs. Rather than trying to solve the problem at 600,000 distributed places across rural India, perhaps we should first look at 10,000 places which have economies of scale. This would be similar to the Atanu Dey-Vinod Khosla paper on Rural Infrastructure and Services Commons. Second, the need was for increasing their incomes – either by reducing input costs or increasing output costs. It boils down to providing access to markets – an idea so fundamental to our lives that we often overlook it.

When I thought about the hubs and information marketplaces, I realised that these two ideas also underpinned my vision of centralised computing for the next billion users: building “computing hubs” to reduce cost and complexity, and building a compelling set of services accessible via the thin clients and mobile phones. Life, it seems, is a set of simple, recurring themes!

Tomorrow: Correcting Education