Archive for the ‘Uncategorized’ Category

P2P version of Twitter using Flash 10.1

In Uncategorized on May 22, 2008 at 3:54 am

A massively scalable, highly redundant version of Twitter can be built using the P2P feature of Flash 10.

For pennies, too.

The devil is always in the details but this is something that can be conquered now, thanks to Adobe.

Another way of saying it, building a massively scalable, highly redundant Twitter clone is not exactly trivial but it can NOW be done 800 times easier than having to write your own P2P layer not to mention having to ask people to download a PC client.

Adobe has just changed the game by making P2P technology accessible to all Flex/Flash developers.

Towards a World Wide Mesh (WWM)

In Uncategorized on March 8, 2008 at 6:34 am

Author: Marc Fawzi

Twitter: http://twitter.com/#!/marcfawzi

License: Attribution-NonCommercial-ShareAlike 3.0

The One Laptop Per Child (OLPC) project has brought some interest to mesh networking.

In theory, the XO laptop has the ability to form a wireless mesh together with other XO laptops in its vicinity. Each laptop extends the mesh further, like a link in a long chain.

Such mesh technology, when supplemented by signal repeaters, can theoretically cover entire villages. Since villages, towns, cities are connected to each other via the Internet these meshes come together in one world-wide mesh.

The Web and the Internet as a result is constrained (by many economic, political and technical factors) to working within the client-server model. The inability to establish direct communication between applications on different PCs, without having to go through difficult -and sometimes- unreliable paths (think: UDP hole punching, NAT traversal, uPnP etc), combined with ISPs’ tendency to throttle and even block P2P traffic has resulted in an unhealthy environment for P2P applications.

The XO laptop maybe the first sign of a global shift from the client-server model of the Web to the peer-to-peer model of wireless mesh technology.

The current Web architecture is bound to evolve over the next few decades as the architecture of global communication moves from the network-centric model to the peer-to-peer model, enabled by wireless mesh technology.


  1. World Wide Mesh

Google Warming Up to the Wikipedia 3.0 vision?

In Uncategorized on December 14, 2007 at 8:09 pm

[source: slashdot.org]

Google’s “Knol” Reinvents Wikipedia

Posted by CmdrTaco on Friday December 14, @08:31AM
from the only-a-matter-of-time dept.


teslatug writes “Google appears to be reinventing Wikipedia with their new product that they call knol (not yet publicly available). In an attempt to gather human knowledge, Google will accept articles from users who will be credited with the article by name. If they want, they can allow ads to appear alongside the content and they will be getting a share of the profits if that’s the case. Other users will be allowed to rate, edit or comment on the articles. The content does not have to be exclusive to Google but no mention is made on any license for it. Is this a better model for free information gathering?”

This article Wikipedia 3.0: The End of Google?  which gives you an idea why Google would want its own Wikipedia was on the Google Finance page for at least 3 months when anyone looked up the Google stock symbol, so Google employees, investors and executive must have seen it. 

Is it a coincidence that Google is building its own Wikipedia now?

The only problem is a flaw in Google’s thinking. People who author those articles on Wikipedia actually have brains. People with brains tend to have principles. Getting paid pennies to build the Google empire is rarely one of those principles.


The World Wide Mesh (WWM)

In Uncategorized on December 7, 2007 at 6:01 am

I’m not sure why Wifi hardware vendors don’t update their firmware so that each Wifi router/bridge sold can communicate with nearby ones.

Who needs Level 3 and Worldcom if we have the ability to connect to each other over the air!


This article below talks about P2P set-top boxes, i.e. the wired version of the World Wide Mesh.

Using set top boxes and Peer-to-Peer technology.

Thought Seeders and Thought Leechers – Updated

In Uncategorized on April 7, 2007 at 2:52 pm

Author: Marc Fawzi

Twitter: http://twitter.com/#!/marcfawzi

License: Attribution-NonCommercial-ShareAlike 3.0


My intention with Evolving Trends was not to see the ideas that are articulated here get adopted by others with no contribution to the debate whatsoever.

But I was reminded today about the true purpose of this blog:

“Don’t worry about people stealing your ideas. If your ideas are any good, you’ll have to ram them down people’s throats.”

— Howard Aiken quoted by Ken Iverson quoted by Jim Horning, 1979

So far, it looks like we did our part by ramming it down Google’s throat: link (and now Google “Knol” )

And we believe that we got Wikipedia’s founder Jimmy Wales to jump on the crowd-enhanced semantic search bandwagon with Wikia, his VC-backed startup: link (also see the Update section of this post re: Jimmy Wales’ conflict of interest)

Here’s the popular Evolving Trends article, Wikipedia 3.0: The End of Google, that preceded both Google Knol and Wikia.

Now, it seems that Hakia may have joined the club, too.

Description of a new service that Hakia just put on their site http://labs.hakia.com/hakia-lab-dial.html

Dialogue Algorithm

The long-term objective of the Dialogue algorithm is to establish a human-like dialogue with the user. The vision is to convert the search engine’s role into a computerized assistant with advanced communication skills while utilizing the largest amount of information resources in the world.The challenge is to analyze search results ranked by the SemanticRank algorithm one step further to determine whether the information can be used to communicate with the user at an elevated level of confidence about its accuracy and credibility. hakia’s conversational system is currently under development. A simplified version of this utility is at the BETA site that allows hakia developers (and the users) to monitor the incremental improvements at every step of the way.An interactive test system is available by invitations which is further advanced than that on the BETA site. You can request access to test this system, or Login using your access code.

Compare this to the Evolving Trends article that preceded their description:

Designing a Better Web 3.0 Search Engine

It’s intriguing to see how ideas spread… but a society where most people are thought leechers (as opposed to thought seeders) is a society that is headed for failure.

It would be great if the broken patent system was to be replaced with a simple P2P co-creative system that promotes balanced ‘contribution ratios’ so everyone contributes to the debate, not simply copy and co-opt other people’s contributions…

Google and Web 3.0

In Uncategorized on March 24, 2007 at 11:35 pm

In Web 3.0, he who owns the metadata owns the Web.

With Googel Co-Op, Google tried to leverage user-supplied metadata to enhance the accuracy and relevance of Google searches.

Now they’re trying it again with Image Labeler.

But this time they want users to actually use it so they’re making it into a Squirrel Wheel kind of game where you get to play the squirrel.

From their description:

“You’ll be randomly paired with a partner who’s online and using the feature. Over a 90-second period, you and your partner will be shown the same set of images and asked to provide as many labels as possible to describe each image you see. When your label matches your partner’s label, you’ll earn some points and move on to the next image until time runs out. After time expires, you can explore the images you’ve seen and the websites where those images were found. And we’ll show you the points you’ve earned throughout the session.”

You’re better off annotating Wikipedia (using Semantic MediaWiki) and applying your knowledge of a given subject (or domain) to build intelligence into Wikipedia, which is owned by the people (as a non-profit, people funded, people powered encyclopedia.) Why be a hamster in Google’s hamster wheel only to have Google exploit your good will?


Here is Google co-opting the “Wikiedpai 3.0” vision by developing their own version of Wikipedia:

  1. https://evolvingtrends.wordpress.com/2007/12/14/google-tries-again-to-co-opt-the-wikipedia-30-vision/

Again, the only problem is a flaw in Google’s thinking. People who author those articles on Wikipedia actually have brains. People with brains tend to have principles. Getting paid pennies to build the Google empire is rarely one of those principles.


  1. Wikipedia 3.0: The End of Google?
  2. Google Co-Op: The End of Wikipedia?
  3. Web 3.0 Update
  4. Is Google a monopoly?
  5. Designing a Better Semantic Search Engine*
  6. Web 3.0 (Definition)

The Missing Link

In Uncategorized on February 5, 2007 at 5:28 am

At the time the Wikipedia 3.0: The End of Google? article was written, I didn’t think it necessary to supply external references, since it was just another idea of mine (came out of the blue on evening) and I had not expected the massive interest it would generate. Lately, however, I’ve been looking at what others have done and I came across this old but relevant paper from 2003, which should provide a more detailed technical context to developers as far as the use of rule-based inference engines and ontologies in the context of Semantic Web + AI (or Web 3.0.)

  1. Description Logic Programs: Combining Logic Programs with Description Logic

“A key requirement for the Semantic Web’s architecture overall is to be able to layer rules on top of ontologies–in particular to create and reason with rule-bases that mention vocabulary specified by ontology-based knowledge bases–and to do so in a semantically coherent and powerful manner.”

Self-Aware Text

In Uncategorized on January 13, 2007 at 4:57 am

Author: Marc Fawzi

Twitter: http://twitter.com/#!/marcfawzi

License: Attribution-NonCommercial-ShareAlike 3.0

Enabling self-organizing text

Below is a summary of an interesting model that I believe can be used to realize self-organizing text (excerpted from this rather weird but technically sound source):

Spin glasses are materials with chaotically oriented atomic spins which can reach neither a ferromagnetic equilibrium (spins aligned) nor a paramagnetic one (spins canceling in pairs), because of long-range spin interactions between magnetic trace atoms (Fe) and the conduction electrons of the host material (Cu). Because these effects reverse repeatedly with distance, no simple state fully resolves the dynamics, and spin glasses thus adopt a large variety of [globally] disordered states [with short range order.] Modeling the transition to a spin glass [i.e. simulated annealing] has close parallels in neural nets, particularly the Hopfield nets consisting of symmetrically unstable circuits. Optimization of a task is then modeled in terms of constrained minimization of a potential energy function. However the problem of determining the global minimum among all the local minima in a system with a large number of degrees of freedom is intrinsically difficult. Spin glasses are also chaotic and display sensitive dependence. Similar dynamics occurs in simulations of continuous fields of neurons.

Annealing is a thermodynamic simulation of a spin glass in which the temperature of random fluctuations is slowly lowered, allowing individual dynamic trajectories to have a good probability of finding quasi-optimal states. Suppose we start out at an arbitrary initial state of a system and follow the topography into the nearest valley, reaching a local minimum. If a random fluctuation now provides sufficient energy to carry the state past an adjacent saddle, the trajectory can explore further potential minima. Modeling such processes requires the inclusion of a controlled level of randomness in local dynamical states, something which in classical computing would be regarded as a leaky, entropic process. The open environment is notorious as a source of such [controlled level of randomness], which may have encouraged the use of chaotic systems in the evolutionary development of the vertebrate brain.

—End of Excerpted Model Summary—

Imagine the interaction between random words in the English language having two properties: aligned and non-aligned. If you throw the whole set of words into a heated spin-glass alloy, where the words replace the atoms and where word-word interactions replace spin-spin interactions, and then let it cool slowly (i.e. anneal it) then the system (of word-word interactions) should theoretically self-organize into the lowest potential energy state it could find.

The spin glass model (from the above quoted summary) implements an optimization process that is also a self organizational process that finds the local energy minima associated with a quasi-optimal state for the system which in turn organizes the local interactions between atomic spins (or words) to minimize discordant interactions (or disorder) in the short range, thus (in the case of word-word interactions) generating text that goes from garbage in the long range (as a result of globally disordered interactions in the long range) to well-formed in the short range (as a result of mostly aligned/ordered interactions in the short range.)

This idea is pretty raw, incomplete, and may not be the most proper use (or abuse) of the spin glass model (see References.)

However, in line with evolution’s preference for such a model for the brain, I find it useful to inject a controlled level of noise (randomness) into the thinking process.

Well, after having some apple crumble, I realize now (randomness works) that the reason this model will work well is because it will generate many well-formed sentences in each region in the state space (see image below) so there is bound to be a percentage of sentences that will actually make sense!

Having said that, this interpretation of the [SK] spin-glass model is pretty rough and needs more thinking to nail down, but the basic idea is good!

From Self-Organizing to Self Aware

What if instead of simply setting the rules and letting order emerge out of chaos (at least in the short range), as implied above, what if each word was an intelligent entity? What if each word knew how to fit itself with other words and within a sentence such that the words work collaboratively and competitively with each other to generate well-formed sentences and even whole articles?

The words would have to learn to read. :)

[insert your Web X.0 fantasy]


  1. Spin Glass Theory and Beyond


Short range ordered regions in 2D state space of a spin glass.


web 3.0, web 3.0, web 3.0, semantic web, semantic web, artificial intelligence, AI, statistical mechanics, stochastic, optimization, simulated-annealing, self-organization, spin glass

Designing a better Web 3.0 search engine

In Uncategorized on January 7, 2007 at 7:09 pm

Author: Marc Fawzi

Twitter: http://twitter.com/#!/marcfawzi

License: Attribution-NonCommercial-ShareAlike 3.0

This post discusses the significant drawbacks of current quasi-semantic search engines (e.g. hakia.com, ask.com et al) and examines the potential future intersection of Wikipedia, Wikia Search (the recently announced search-engine-in-development, by Wikipedia’s founder), future semantic version of Wikipedia (aka Wikipedia 3.0), and Google’s Pagerank algorithm to shed some light on how to design a better semantic search engine (aka Web 3.0 search engine)

Query Side Improvements

Semantic “understanding” of search queries (or questions) determines the quality of relevant search results (or answers.)

However, current quasi-semantic search engines like hakia and ask.com can barely understand the user’s queries and that is because they’ve chosen free-form natural language as the query format. Reasoning about natural language search queries can be accomplished by: a) Artificial General Intelligence or b) statistical semantic models (which introduce an amount of inaccuracy in constructing internal semantic queries). But a better approach at this early stage may be to guide the user through selecting a domain of knowledge and staying consistent within the semantics of that domain.

The proposed approach implies an interactive search process rather than a one-shot search query. Once the search engine confirms the user’s “search direction,” it can formulate an ontology (on the fly) that specifies a range of concepts that the user could supply in formulating the semantic search query. There would be a minimal amount of input needed to arrive at the desired result (or answer), determined by the user when they declare “I’ve found it!.”

Information Side Improvements

We are beginning to see search engines that claim they can semantic-ize arbitrary unstructured “Wild Wild Web” information. Wikipedia pages, constrained to the Wikipedia knowledge management format, may be easier to semantic-ize on the fly. However, at this early stage, a better approach may be to use human-directed crawling that associates the information sources with clearly defined domains/ontologies. An explicit publicized preference for those information sources (including a future semantic version of Wikipedia, a la Wikipedia 3.0) that have embedded semantic annotations (using, e.g., RDFa http://www.w3.org/TR/xhtml-rdfa-primer/ or microformats http://microformats.org) will lead to improved semantic search.

How can we adapt the currently successful Google PageRank algorithm (for ranking information sources) to semantic search?

One answer is that we would need to design a ‘ResourceRank’ algorithm (referring to RDF resources) to manage the semantic search engines’ “attention bandwidth.” Less radical, may be to design a ‘FragmentRank’ algorithm which would rank at the page-component level (ex: paragraph, image, wikipedia page section, etc).


  1. Wikipedia 3.0: The End of Google?
  2. Search By meaning


  1. See relevant links under comments


web 3.0, web 3.0, web 3.0, semantic web, semantic web, ontology, reasoning, artificial intelligence, AI, hakia, ask.com, pagerank, google, semantic search, RDFa, ResourceRank, RDF, Semantic Mediawiki, Microformats

Who 2.0: Update

In Uncategorized on December 20, 2006 at 7:40 am

First see:

Then read this (coming to a cell phone/search engine near you):

P2P to Disrupt eBay, Google, Yahoo

In Uncategorized on December 14, 2006 at 1:35 am

Forget Web 3.0 and P2P 3.0 for a second…

Non-Semantic, P2P-enabled versions of Google, eBay, Yahoo et al. can shift power to the user, especially since P2P eliminates the need for massive corporations to spend massive amounts of money on server farms to process the users’ transactions. Each user provides a piece of the server farm. The Web’s reported 2 billion users mean that a P2P version of Google can run on a server farm of at least 200 million servers. That is significantly more servers than Google can ever have.

So you wanna take on Google, eBay, Yahoo et al…? Then build a P2P version of any of their core services.

Web 3.0: Update

In Uncategorized on November 19, 2006 at 2:21 pm

As a key step in enabling the Web 3.0 vision (which is not to be exclusively associated with Wikipedia), startups and researchers are developing tools and processes to let domain experts with no knowledge of ontology construction build formal ontologies in a manner that is transparent to them, i.e. without them realizing that they’re building one.Such tools and processes are emerging from research organizations and Web 3.0 ventures.

This cripples the argument that domain specific ontologies can only be created by Semantic Web experts. Expert knowledge of your particular domain (or profession) is the only thing you’ll need to be part of the revolution.


  1. Wikipedia 3.0: The End of Google?


Web 3.0, Web 3.0, Semantic Web, AI

P2P 3.0: Shaking the Web to its Roots

In Uncategorized on October 8, 2006 at 5:02 pm

The application of P2P Search (semantic and non-semantic) to the Web will involve transforming the Web from the existing browser-server model to a browser-as-both-client-and-server model. This is different than P2P file sharing in the sense that it is about producing and consuming information (or meaning – in case of the P2P semantic Web model) rather than sharing digital data. Thus, P2P Search and P2P Semantic Search in particular may be viewed as being part of the Web 3.0 set of technologies.

[The abstract above hints at a “decentralized knowledge base” version of the previous model implied in the People’s Google post]


  1. Get Your DBin


p2p search, p2p Web, Web 3.0, Web 3.0

Google Co-Op: The End of Wikipedia?

In Uncategorized on September 24, 2006 at 11:11 am

Did Google get the idea of using [subject matter] experts to structure [and give meaning to] information for improved findability from the Wikipedia 3.0 article? or as a pure and natural evolution of their thinking? or both?

In case you’re taking it literally, both the question and the title of the post are purely rhetorical at this point, now that Google seems to be on its way to adopting (or co-opting) the Web 3.0 vision.

Here is an excerpt from the newly announced Google Co-Op experiment:

Google Co-op gives you a way to improve search in the topics you know best. If you’re a doctor, for instance, with specific expertise in a particular disease, you can contribute by using the labels in the health topic to annotate all the webpages that you know provide useful, reliable information about that disease. Your patients and other Google users could then subscribe to you and benefit from your expertise.

You can participate in a number of topics that are already being worked on, such as health, destination guides, autos, computer & video games, photo & video equipment, and stereo & home theater. Or, if you’re passionate about something entirely different, go ahead and start a topic of your own. In this guide, we will walk you through an example of how to label webpages for an existing topic as well as how to create a topic of your own.

Google Co-Op has the potential in the future to follow the vision articulated in the Wikipedia 3.0 article as Google adds Web 3.0 capabilities to its search engine.


  1. Google Tries Again to Co-opt the Wikipedia 3.0 Vision


  1. Wikipedia 3.0: The End of Google?


  1. Web 2.0 or Web 3.0?


Semantic Web, Web strandards, Trends, OWL, innovation, Startup, Evolution, Google, GData, inference, inference engine, AI, ontology, Semanticweb, Web 2.0, Web 2.0, Web 3.0, Web 3.0, Google Base, artificial intelligence, AI, Wikipedia, Wikipedia 3.0, collective consciousness, Ontoworld, Wikipedia AI, Info Agent, Semantic MediaWiki, DBin, P2P 3.0, P2P AI, P2P Semantic Web inference Engine, Global Brain, semantic blog, intelligent findability, Google Co-Op

Wisdom Addition Machine – Updated

In Uncategorized on September 3, 2006 at 11:18 am

Updated on November 12, 2008

This is a reblogging of my email response on September 3, 2006 to Michel Bauwens, founder of The Foundation for P2P Alternatives, and other participants in the dialog.


The statement from Michel’s interview that captures the difference in our thinking is:

Michel stated:

“The difference today, of course, is that we are no longer waiting for great leaders, since it is the collective intelligence of humankind that needs to rise to the level of its global challenges.”

While I agree with the ideal, I don’t see how we can ignore the fact that the crowd will always be less intelligent and less capable than its most intelligent and capable member.

I don’t yet see the conceptual scheme that would allow the individual wisdom of individuals in a crowd to be added up or multiplied rather than replaced with averaged judgment (not wisdom) or the lowest common denominator opinion.

Unless we can come up with a wisdom addition machine we still need to rely on individuals whose intellect, wisdom, taste, and ability exceed that of the crowd (i.e. exceed the average.) to lead the crowd.

The question is can wisdom be calculated? My answer is no, and the same goes for beauty, trust, friendship, love, goodness and all such concepts.


  1. The Unwisdom of Crowds


Trends, wisdom of crowds, mass psychology, cult psychology, Web 2.0, Web 2.0, digg, censorship, democracy, P2P, P2P 2.0, social bookmarking