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<title>The Cash and the Calling LG #46</title>
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<H4>
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"Linux Gazette...<I>making Linux just a little more fun!</I>"
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<H1><font color="maroon">The Cash and the Calling</font></H1>
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<H4>By <a href="mailto:bmarshal@agt.net">Brian Marshall</a></H4>
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September 1999<br>
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</b>
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<p>
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<blockquote><i>
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This paper analyzes a model of software development in which
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closed-source applications make use of open-source artificial
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intelligence parts. We begin by observing that AI has a huge
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potential but that problems limit the development of
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applications. We consider why there will continue
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to be closed-source AI applications and note that pure
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open-source development is limited by the number of
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people interested in starting open-source projects.
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We consider the possibility of closed-source applications
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based on open-source parts, both in a two-tier and a
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three-tier architecture. We look at the pool of talent
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available for open-source projects. We conclude that
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the use of open-source AI parts may significantly
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increase the development of AI applications and that this
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may be good for the state of the art of AI.
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</i></blockquote>
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<p>
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<hr>
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<p>
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<b>Table of Contents</b>
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<ol>
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<li>Introduction - Potential Applications of AI</li>
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<li>Closed-Source and Open-Source</li>
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<li>Two-Tier AI: Closed Application, Open AI</li>
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<li>Three-Tier AI: Application, Problem-Domain, AI</li>
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<li>The Pool of Talent</li>
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<li>Conclusion - The Potential of Open-Source AI Parts</li>
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<li>Bibliography and Acknowledgements</li>
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</ol>
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<p>
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<hr>
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<p>
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<h4>1. Introduction - Potential Applications of AI</h4>
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There seems to be more potential applications for artificial intelligence
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than actual. The untapped market for staff-scheduling alone is immense.
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The opportunities in the areas of materials scheduling, process
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optimization, expert decision-making and image interpretation seem
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endless. The development of AI applications would appear to be a field
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with a lot of potential for growth.
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<p>
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Presumably there is money to be made satisfying some of this potential
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demand. Why is this happening so slowly? Why are there so many
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potential products that people would pay for but that have not been
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developed?
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<p>
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There are a number of reasons why there are so many potential, as
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opposed to actual, applications of artificial intelligence:
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<ul>
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<li>AI software is expensive and risky to develop. It tends to be
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complex and subtle. It generally requires a large investment in
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problem analysis. More AI software would be developed if it
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were cheaper to do so.</li>
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<p>
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<li>AI applications tend to require a lot of support and they tend to
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have a lot of future-risk. It is particularly difficult for a
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tiny software venture to develop and market new AI software.
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More AI applications would be developed if getting involved
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with them was safer.</li>
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<p>
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<li>Some problems are sufficiently hard that no known AI technique is
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completely satisfactory. More AI would be used if trying to do so
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was more likely to be successful.</li>
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</ul>
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<p>
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Artificial intelligence is limited by the expense and risk associated
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with trying to take advantage of particular opportunities.
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<p>
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<h4>2. Closed-Source and Open-Source</h4>
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<p>
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There will probably always be opportunities to develop closed-source
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AI software for rent. Companies identify potential applications, and
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where there is sufficient expected demand, they develop new products.
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This is expensive because of the amount of analysis and design required.
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The development only occurs because rents are expected. The source
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is closed to enable capture of those rents.
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<p>
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As we have noted, however, this sort of scenario is limited by the
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expense and risk involved.
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<p>
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What about open-source? Free should mean less expense. Open-source
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reduces future-risk. AI would definitely seem to be a good candidate
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for peer-review. Eric Raymond describes these benefits and how they
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come about in
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<a href="http://www.tuxedo.org/~esr/writings/cathedral-bazaar/">
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"The Cathedral and the Bazaar"</a>.
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<p>
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But each open-source project must be started by someone
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who does the initial analysis, design and development. There are
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a lot more potential AI projects than people interested in
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starting them. Open-source application development isn't likely
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to make a big dent in the pile of unexploited AI opportunities.
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<p>
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<h4>3. Two-Tier AI: Closed Application, Open AI</h4>
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<p>
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The expensive part of an AI application is not necessarily the AI.
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There are a variety of artificial intelligence techniques, tools,
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frameworks and engines available. The most expensive part of
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developing an AI application can be the problem-analysis and the
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design of how the AI is to be used.
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<p>
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It may well be reasonable for an application, based on expensive
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analysis and design, to be closed-source. But what if the
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application got its AI functionality from open-source AI parts?
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A staff-scheduling system could be based on open-source AI
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problem-solving parts. An image-recognition system could be based
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on an open-source neural-network.
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<p>
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In <a href="http://www.tuxedo.org/~esr/writings/magic-cauldron/">
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"The Magic Cauldron"</a>, Eric Raymond describes five discriminators
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that "push towards open source". The first four discriminators
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indicate that AI parts would be a good candidate for open-source:
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<ul>
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<li>Reliability is a major concern</li>
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<li>Verification of design is difficult</li>
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<li>AI applications can be critical to business processes</li>
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<li>AI parts establish/enable a common computing infrastructure</li>
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</ul>
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<p>
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The fifth discriminator, however, indicates the opposite. Artificial
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intelligence is not part of "common engineering knowledge". It is
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an area in which one would expect good proprietary techniques be able
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to generate good rents.
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<p>
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In practice, this can be difficult. The customers for software parts
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are developers of other software. Convincing a potential customer
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of the worth of a secret technique can be a tough sell.
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But more importantly, a company will not be interested in having its
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product dependent on a secret technique that may not satisfy future
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requirements.
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<p>
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Open-source software parts offer much less risk. They are easier to
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judge, they tend to be more reliable and customers always have the
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option of making their own changes.
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<p>
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<p>
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<h4>4. Three-Tier AI: Application, Problem-Domain, AI</h4>
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<p>
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If open-source general-purpose AI parts are available, an interesting
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new product is possible. People can use the general-purpose AI to
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develop parts that are specific to a problem domain like
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staff-scheduling or courier-dispatching.
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This can make for a three-tier architecture -
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<ul>
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<li>The open-source, general-purpose AI parts</li>
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<li>The problem-domain-specific AI parts</li>
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<li>The application/interface</li>
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</ul>
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<p>
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Much of the analysis and design goes into the middle tier - the
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problem-domain-specific AI. It can be expensive to develop and the
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market is much narrower than the market for general-purpose AI.
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<p>
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A middle-tier AI product might be developed by a company who will use
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it to develop an application for sale. In this case, the middle-tier
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would likely be closed-source.
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<p>
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A middle-tier AI product might be developed by a company or individual
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with the intention of offering application development services to
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narrow markets. The middle-tier might be closed to help capture the
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market or open to help sell the service.
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<p>
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The three-tier architecture provides more ways to take advantage of
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AI opportunities. The development of middle-tier AI products is
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encouraged by the existence of open-source general-purpose AI parts.
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<p>
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<h4>5. The Pool of Talent</h4>
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<p>
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Many programmers are interested in AI. It's an intriguing field -
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problem-solving, decision-making, remembering and recognizing...
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it's the ultimate challenge - software that thinks.
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<p>
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The vast majority of these programmers never apply their talents to AI -
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they have no opportunity in their jobs and they are not part of the
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academic AI community. The Open-source phenomenon provides a number
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of ways of tapping this pool of talent.
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<p>
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Programmers with a calling and/or a desire to make a name for themselves
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will do original research, write new open-source software
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and start open-source projects. Much unconventional thought will be
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brought to bear on various problems in artificial intelligence. Many
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thinkers will have a higher opinion of their thoughts than will
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later prove to be justified (your present author probably included).
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But the effect of the open-source movement on the state of the art of
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AI may be the next great thing that happens in the world of computers.
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<p>
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Open-source projects need participants - people who contribute time
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designing, developing, debugging and testing. The open-source culture
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that supports this participation is described in Eric Raymond's paper,
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<a href="http://www.tuxedo.org/~esr/writings/homesteading/">
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"Homesteading the Noosphere"</a>. AI open-source projects should
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be particularly good at attracting participants.
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<p>
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Open-source AI that is used in commercial products should
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be particularly attractive to talent. There are a few reasons for this.
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One is that the the AI has proven to be useful - it is something worth
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working on. Another reason is that the work of the project is
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obviously important and the project is therefore an excellent place to
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make a name for oneself. A third reason is that money is involved,
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there is the possibility of paying work and the possibility of getting
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involved in new business ventures. Even people who aren't looking for
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work like the idea of acquiring knowledge that can be worth money.
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<p>
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If a commercial product uses open-source AI, there is the potential
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for paying work related to the AI. The product developer pays people to
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initially make use of the AI and this use may have to be maintained.
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Customers may require consulting, customization and integration
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services. The product developer and large customers may fund
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projects aimed at improving the open-source AI.
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<p>
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If money is being made on a commercial product that uses open-source
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software, there will be people trying to dream up ways of getting in
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on the action. People may start third-party consulting and integration
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services. People may launch a venture to develop a competing product.
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The possibility of acquiring an equity interest in some new venture
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has its attractions.
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<p>
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<h4>6. Conclusion - The Potential of Open-Source AI Parts</h4>
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<p>
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Open-source AI parts may significantly increase the development of
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commercial AI applications. Such development will become cheaper
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and less risky. Small companies that would lack credibility as
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developers or purveyors of closed-source AI could have adequate
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credibility as users of open-source AI.
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<p>
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Open-source AI parts may also significantly increase the development
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of home-grown AI applications. Many applications of AI in business
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are so specific that they will not be developed at all unless they
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are developed by, or at least for, an individual company for its own
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use. Development that would be too expensive and risky with
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closed-source AI products could be feasible with open-source AI.
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<p>
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As the open-source movement increases the application of AI, more time
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and money will be directed at improving the AI. As the state of the
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art of AI advances, more time and money will be directed at trying
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to apply it.
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<p>
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The open-source movement could have important effects on the
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application of AI.
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<p>
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<h4>7. Bibliography and Acknowledgements</h4>
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<p>
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<a href="http://www.tuxedo.org/~esr/writings/cathedral-bazaar/">
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"The Cathedral and the Bazaar"</a> - Eric Raymond<br>
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http://www.tuxedo.org/~esr/writings/cathedral-bazaar/
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<p>
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<a href="http://www.tuxedo.org/~esr/writings/homesteading/">
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"Homesteading the Noosphere"</a> - Eric Raymond<br>
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http://www.tuxedo.org/~esr/writings/homesteading/
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<p>
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<a href="http://www.tuxedo.org/~esr/writings/magic-cauldron/">
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"The Magic Cauldron"</a> - Eric Raymond<br>
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http://www.tuxedo.org/~esr/writings/magic-cauldron/
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<p>
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I owe much of my appreciation for the open-source movement to
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the writings of Eric Raymond. There are many good things to read
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at his <a href="http://www.tuxedo.org/~esr/">web-site</a>.
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<p>
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<a href="http://www.agt.net/public/bmarshal/homepage.htm">
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Brian Marshall's Home Page</a>
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<!-- BEGIN copyright ==================================================-->
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<P> <hr> <P>
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<H5 ALIGN=center>
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Copyright © 1999, Brian Marshall<BR>
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Published in Issue 46 of <i>Linux Gazette</i>, October 1999</H5>
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