Category Archives: Science

Distributed Processing and Biological Approximation

Posted on April 21, 2001 | Leave a comment

The complexity of biological thinking is impossible is impossible to replicate today when constrained by the limitations of a single machine. With the ability to define and exchange standard objects and a standard interface, this barrier could be broken. The hurdle of coding models that approximate the function of the brain has also been insurmountable as long as development was dictated, managed, and organized within a company. The upper limit on programs of this origin seems to be in the range of 10 million lines. The growth of open source development opens the door to the integration of many codes to form the billions of lines necessary to approach human capacity for thought.

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Posted in Brain in a jar, Just for fun, Science, Tech, The Future

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Building Intelligent systems: biological and software

Posted on April 17, 2001 | Leave a comment

There are amazing analogies between computer processors and the brain, and it is just a matter of time before the algorithms that define electronic processors mirror the functionality of the chemical processors of our brains. The biological neural systems rely on inputs and pattern recognition to learn. Computers are excellent at storing (remembering) facts, and are becoming proficient at recognizing relationships as defined by statistical patterns and neural networks. However, computers cannot yet create metaphors or learn how to independently process new information.

Metaphors are an important part of how humans think. We understand new information as we draw parallels and connections between it and prior information. Over-simply put, we learn by recognizing relationships between new information and old. Computers could do the same when their sets of data include enough relevant fields to be able to computationally identify systems that are described by similar dynamics. In other words, when a computer has data about how things works, it can find systems that work similarly to each other. The leap from there to drawing metaphors is a data-mining process: it can be solved by computational rote, where statistical relationships are identified, prioritized, and used for prediction.

This process also leads to “learning” about how to process new information. By recognizing the metaphors, new data can be classified and described according to how it is understood. And just like in our brains, there will be errors. Misunderstanding will occur as metaphors are calculated based on incomplete data sets. As more data is input, systems will have to be able to make corrections and re-calculate all of the other metaphors that included the corrected data. New corrections will be made and a cascade of corrections will result in a modified historical data record. A large number of calculations and recalculations will occur with each new input, and the storage of historical data (and calculated results) will require substantial processing and storage.

Recognizing metaphors will allow machines to output statements like: “It appears that ABC is driven in many similar ways to XYZ. The result we are seeking might be accomplished by A because a similar result was achieved in XYZ when X was applied.” Put more simply, computers will be able to express creative suggestions.

Interestingly, storage could be massively reduced by deleting large volumes of data that support the relationships that are strong enough to overcome some threshold level of certainty. For example, if everything falls, then we don’t have to keep all that data, just the relationship that everything falls. This may be analogous to forming intuitions.

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Posted in Brain in a jar, Just for fun, Psychology, Science, Tech, The Future

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Centralized network computing will win

Posted on March 24, 2001 | Leave a comment

I know it’s a big debate right now, but centralized network computing will win in the end.

Centralized network computing is the term used to describe a system of networked web servers (or a single web server) that provides integrated applications and storage for multiple users who can access the system through distributed terminals. The system can be geographically distributed or not, but will share a common (integrated) network of applications, probably using a software interface standard to encourage and enable multiple independent application development teams.

Centralized networks are inevitable because of self-reinforcing competitive advantages. Economies of scale and market forces will lead to substantial change in the way we compute, and the systems we use now are simply the seeds that will grow into (and merge together to form) global centralized information service providers. There are already some very strong indicators that this trend is happening, and the potential points to this trend being a very long one.

  1. There are economies of scale in processing Load balancing can optimize processor utilization and provide both faster interactivity and reduced hardware investment.
  2. There are competitive advantages in information and application aggregation Integrations can break down the walls between programs, improving functionality through better integration and data sharing. You can analyze data in more dimensions and with more flexibility. Development rates can improve as it becomes possible to support separation of more software components and the people that work on them.
  3. Load balancing improves transmissions Transfer rates improve because fewer nodes are required and data traffic can be optimized. Information served to you from a server on your edge is more reliable and fast than information sent to you from another server through your edge.
  4. End-user transparency The front-end possibilities under centralized computing are not limited beyond that of other systems. This implies that there will not be a selection bias away from centralized systems because end-users will not prefer or recognize the difference between systems. That is not to say that they will all be the same – only that they all could be. The opportunity set in one system is available in the other.
  5. The outsourced storage industry exists This implies that there is a willingness to adopt on the part of the owners of data.

You can see the markets already rewarding companies that are moving to take advantage of this trend. Many of these companies are providing application services along with ISP connectivity, and they are capturing traffic. This traffic is investing time and thought into signaling their own preferences. Some examples include personalizing page layout and content — often even using system-wide wallets and e-mail. Giving users what they prefer is a huge competitive advantage. The time it takes to personalize a competing system is a high transaction cost – especially relative to the low cost of inertia.

Eventually, you will be using only a browser. All your computing will occur on a centralized system and be sent to your browser for translation into your interface. All of your applications will be centrally hosted, so your profile and applications – essentially everything you do on your computer – will be available to you from any machine, at any time.

Multiple systems will compete for scale, reducing marginal costs and creating meaningful and irreproducible competitive advantages. This race will likely be won permanently by 2050. Before that time, ASP services will consolidate rapidly along with economic cycles. the early players will rely on loss leader models to attract user bases, and will transition to profitability as the scale reaches the tipping point. The companies that make it to profitability first and reinvest in their technology platform will improve their integration, breadth, and quality to further support their competitive advantages.

In the first decade or two of this trend, there will probably be dozens of smaller companies that are able to enter and gain market share against their larger competitors. These companies will have competitive advantages most likely based on data storage, traditional media integration, wireless adoption, software platform architecture, applications suite integrations, and possibly international comparative advantage. After 20 years, the marginal advantages possible from these characteristics will not pose a meaningful threat to the aggregation and scale advantages of the top few market participants.

Consolidate or die will be the mantra of information companies.

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Posted in Brain in a jar, Early Stage, Investment, Just for fun, Media, Science, Tech, The Future

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Forecast Changes in Asset Values based on Measurable Cultural influences

Posted on March 23, 2001 | Leave a comment

The sum total of the media contributed to the internet approximates the attention of society during that period. Then analysis of this media indicates trends in attention and preferences. These trends create signals about the directions of values for securities and other assets. Frequency and trend directions of keyword usage, volume of content in certain classifications, and level and type of contribution of media files vs. sector and industry pricing trends are recommended starting points for analytical comparison.

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Posted in Bonds, Brain in a jar, Commodities, Early Stage, Economics, Freakonomics, Investment, Psychology, Science, Stocks, Tech

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Competition in the information age

Posted on February 22, 2001 | Leave a comment

Consolidation is the result of economies of scale – essentially horizontal integration, vertical integration, and resource sharing. These methods create competitive advantages in powerful ways that make it difficult for smaller players to compete in the same markets. There is nothing necessarily wrong with this trend, but it creates large barriers to entry and often leads to larger profit margins than would be otherwise possible.

In the information age – yes, now – this effect is greatly increased, and the limitations of transportation and capacity have been eliminated. The ability to integrate and share resources is much easier, and new extra-strength synergies are created. For example, if a website allows you to shop for both books and music, then it is possible to tailor your music shopping experience based on your book purchasing preferences. This is a very simple example of a much more powerful trend. It may be impossible to enter into any sort of competition with large information companies after the next 20 years.

You can already see it beginning to happen: Yahoo builds from scratch any web business that seems to make sense. Then because of its existing market coverage, and the ability to integrate new businesses with existing businesses and data, Yahoo is able to capture so much synergistic value that they gain an insurmountable competitive advantage. In this way, I think that Yahoo and the other major aggregators and integrators are great companies.

There are risks. Big ones. And the FTC may not be able to do anything about it.

It may be inevitable that the consolidation will lead to a stable equilibrium under monopoly – where there would be no reason to be a competitor because the types of services being provided rely on historical information and broad business integration that is impossible to recreate or beat. Then this monopolist would have virtually limitless pricing discretion, and the ability to manipulate markets and cultures in unprecedented ways. Humanity, in many ways, would be at the mercy of the monopolist. (I hope that its leaders are benevolent democrats with philosophically sound motivations and long time horizons – but what if they are not?)

The only way to eliminate this market dynamic is to eliminate the factors that make it possible, namely, the opportunity to use your market dominance in one field to create dominance in another field. More specifically, eliminate the competitive advantage created by archival data. This can be accomplished by sharing archival data freely. But what about my privacy? Good question. We have a big problem here. The private information about you and your preferences plays a large role in creating the value that leads to this consolidation. If you want to eliminate this competitive advantage, then you either eliminate the value or you share private information.

There is another way.

What if users owned their own archival data? Amazon could still track my click streams, and do whatever they wanted with them. But I would also be tracking my own use, and have control over my own preferences and historically available data. Amazon would quickly learn that the personalization algorithms produce much more valuable customization using the users’ data than the Amazon archives. Market entry for this standard benefits from this implication. Now what happens if you go to a small competitor – one with little history, but better value than the others? They would be able to provide you with services that took advantage of your archival data, just as the monopolist would have. Competition is restored, and the advantages for humanity are regained as well.

Somebody should create a standard – probably using an XML document editable from within your browser. I’d love to help. Somebody has to do it eventually, and the sooner the better for all of us (except the monopolist, of course!)

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Posted in Early Stage, Economics, Freakonomics, Investment, Media, Public Policy, Science, Stocks, Tech, The Future

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