About This Blog
Automating Invention is Robert Plotkin's blog on the impact of computer-automated inventing on the future of invention and patent law.
- Artificial Invention
- Design & Engineering
- Evolutionary Computation
- Genie in the Machine
- History of Computing
- Human Creativity
- Intellectual Property Law
- Philosophy of Computing
- Software Patents
- Technology Industry
- AI-Controlled Super Mario Brothers
- Using a Game to Harness Human Intuition
- The Blue Brain Project and Creation of an Artificial Brain
- Contract by Computer
- The Future of Invention at WorldFuture 2009
- AI: Science Fiction or Science Fact?
- GA Gaming Coming to the App Store
- Your Desktop Supercomputer
- Alogrithmic Systems Biology
- The EDLUT Nervous System Simulator
- Interview About Invention Automation on Nolo Press Blog
- BusinessWeek Touts Cust-Cutting Ability of Automated Inventing
- December 2009
- November 2009
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- September 2009
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- July 2009
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November 4, 2009
AI-Controlled Super Mario Brothers
A competition that tested the programming skills of researchers in artificial intelligence (AI) was organized this September by Julian Togelius of the University of Copenhagen. The Mario AI Competition challenged researchers to develop the best AI "agent" for a special version of the popular Super Mario Brothers video game that's implemented in Java and capable of infinite random level generation. According to Togelius, the purpose of the competition was to compare different agent development methodologies, including those that use learning techniques and genetic algorithms compared to these which are more on the "hand-coded" side.
The winner of the competition was Robin Baumgarten, a PhD student at Imperial College in London. Baumgarten used A*, a standard graph search algorithm in computer science that dates back to the 1960s. His Mario program had also won an earlier competition at Imperial College in July. The A*-based approach was more in keeping with classical AI game programming than with genetic algorithms.
October 27, 2009
Using a Game to Harness Human Intuition
Computer science researchers at the University of Michigan have prototyped a computer game that addresses a fundamental problem faced by computer hardware designers. The game is an online logic puzzle called FunSAT. It simulates the challenges faced by integrated circuit designers when they arrange transistors and connections on silicon microchips. Chip architecture is usually aided by computer design, but human pattern recognition and intuition are important components that are often missing from automated design. FunSAT was developed as an answer to that problem, harnessing the human ability to strategize and visualize complex systems.
August 29, 2009
The Blue Brain Project and Creation of an Artificial Brain
Henry Markram, a professor at Switzerland's Eucole Polytechnique Federale de Luasanne and director of the Blue Brain Project, recently stated that scientists are within 10 years of creating a fully-functioning artificial brain. Speaking at the TED Global Conference in Oxford, Dr. Markram said the Blue Brain Project has already simulated elements of a rat brain. Why is the team attempting to create an artificial brain? Dr. Markram pointed out the value of the research for treating mental illness and other types of brain impairment. The Blue Brain Project team was formed in 2005 with the aim of reverse engineering the mammalian brain from lab data.
July 22, 2009
Contract by Computer
A team of European researchers have created a set of computer algorithms which will effectively validate e-business contractual agreements. The Contract Project is part of a European Union-funded project to develop computer systems which will verify and monitor contracts. The verification process will test for conflicts between the existing contracts for an individual or organization and the terms of new contracts that are about to be entered. The process can also check for conditions that will impact contract fulfillment.
The tools and libraries for checking contracts have been made available to the public. Real-life case studies were used to test the systems. One of the case studies monitored the commitments of students and lecturers in a Czech educational institute. Research partner Fujitsu will participate in a future case study which will track and manage contracts for custom software.
July 3, 2009
The Future of Invention at WorldFuture 2009
I will be giving a talk on "The Future of Inventing" at the WorldFuture 2009 conference on July 19, 2009 from 11am-12pm (see pp. 50-51 of the program for more details). In the talk I will focus on how computers are enabling inventors to invent more efficiently and effectively, and how in the future even people without technical skill may be able to use computers to become inventors.
I will also be available for a meet-the-author session in connection with my book, The Genie in the Machine, on July 19 from 3:30-4:00pm. Copies of The Genie in the Machine will be available for sale at the Futurist Bookstore throughout the conference.
For a preview of the kinds of topics I will be discussing in my talk, see my article in the July-August issue of The Futurist magazine.
July 1, 2009
AI: Science Fiction or Science Fact?
In a comprehensive New York Times article titled "The Coming Superbrain," columnist John Markoff surveys the current state of Artificial Intelligence. Markoff begins with a look at how AI is depicted in popular culture, as seen in this summer's latest Terminator offer, "Terminator Salvation," touches on the history of AI, and progresses through to Raymond Kurzweil's theories on the concept of the Singularity. Dr. Kurzweil predicts a point in the future when powerful computers and cyborg humans will be developed to a point where machine intelligence surpasses human intelligence and takes over the process of technological invention. Markoff's article presents some of the expert opinions in favor of and opposed to Kurzweil's theory.
June 29, 2009
GA Gaming Coming to the App Store
Genetic algorithms (GA) have entered into the video game arena with Firemint's new highly anticipated Real Racing simulator, soon to be launched for the iPhone. Rather than using the traditional hardcoded method where drivers in the game are programmed to get better and better, Real Racing uses GAs to simulate more life-like opponents.
"What is great about genetic algorithms (GA) is that they produce AI that is much smarter, but also more human like," explains Firemint CEO Rob Murray. "What isn't so good (as we have discovered) is that just like good human players, they misbehave and find exploits."
Examples of these exploits include driving on the grass at high speeds and entering curves without braking and then bouncing off the racetrack walls. Firemint has had to address these issues, just as real race officials often have to reign in real race drivers. The fine tuning required for Real Racer's GA has led to a delay in its release, but there is the promise of a heightened gaming experience.
June 27, 2009
Your Desktop Supercomputer
In a recent blog post, Nick Jones forecasts a time in the not-too-distant future when home computers will have acquired the processing power and memory capacity of today's supercomputers. Jones ponders the question of what people will do with all that computing power. While some have suggested that the future of home computing lies in massive computer centers which home users will connect to, Jones doesn't think network technology will be advanced enough to support the resulting huge increase in data transmissions. Instead, he thinks today's PC will be beefed up to supercomputer levels.
Jones suggests that home supercomputers could make use of genetic algorithms (GA). He suggests that a variant of GA known as genetic programming (GP) could be used to evolve programs which solve problems. To put it simply, a home supercomputer would take a fitness function which determines what defines the best program to solve a problem and then use GP to 'breed' various solution programs until the best match was found.
Jones suggests that companies that have an interest in personal computers, including Intel and Microsoft, should start investing in the development of GA and GP tools for the mass market.
June 25, 2009
Alogrithmic Systems Biology
An article entitled "Algorithmic Systems Biology" in Communications of the ACM (access to full article requires a paid subscription) describes a relatively new inter-disciplinary field of study. Systems biology focuses on the study of interactions in biological systems from a holistic perspective. One of the goals in using the systemic view approach is discovering new emergent properties that provide a better understanding of processes in a biological system. Mathematical modeling via computer algorithms is one of the foundations of systems biology. The article describes how this approach differs from other approaches which use equations.
June 21, 2009
The EDLUT Nervous System Simulator
Researchers at the University of Granada have developed a simulator which is able to reproduce any part of the human nervous system. The EDLUT system (for "Event Driven LookUp Table") will aid in study of the nervous system in relation to new pathologies and diseases and to test new medicines. The simulator will also be used to improve the design of robots and machines which attempt to replicate the nervous system. The simulator is an advance over previous systems such as NEURON and GENESIS in its ability to simulate several hundred thousand neurons at once. The EDLUT software is open source and can be downloaded from the Internet.
June 17, 2009
Interview About Invention Automation on Nolo Press Blog
Rich Stim of the Nolo Press Patent, Copyright & Trademark Blog interviewed me about The Genie in the Machine and has posted the audio of the interview on the blog. Rich asked some great questions about how invention automation technology works and its implications for the future of patent law.
June 14, 2009
BusinessWeek Touts Cust-Cutting Ability of Automated Inventing
A new article in BusinessWeek points out that as "recession-racked companies search for ways to cut costs, some are rediscovering automated innovation." Although some early attempts at automated inventing years ago did not live up to original expectations, increases in computing power and improvements in invention automation techniques themselves are now enabling businesses to use the latest technology to create new products and improve business processes more efficiently than ever before.
The article confirms one of the theses of The Genie in the Machine, namely that the most recent advances in artificial invention technology are no longer merely academic curiosities. Instead, they are ready for use by businesses to solve cutting-edge problems while reducing the cost of innovation at the same time.
June 13, 2009
Algorithms which Automate Creativity
In the Journal of Genetic Progamming and Evolvable Machines, a paper entitled Incorporating characteristics of human creativity into an evolutionary art algorithm examines computer-generated art and design software which uses an evolutionary approach. This software usually relies on human intervention to select the 'best' of two variants and determine the makeup of the next generation. The paper's authors, Steve DiPaola and Liane Gabora, discuss ways in which the software can incorporate this human intervention into its algorithms, automating one more step of human creativity.
June 11, 2009
AI and Future Enterprise
In Future Enterprise - the Intelligent Enterprise Revolution, futurist David Tow discusses the state of artificial intelligence in relation to e-commerce and global competitiveness. Tow lists the most promising AI trends as evolutionary or genetic algorithms, bayesian networks, fuzzy logic, swarm intelligence, neural networks, and intelligent agents.
Tow cites four major trends which are now emerging in relation to AI and the intelligent enterprise revolution:
1. AI is being used more frequently in e-commerce to achieve higher quality decision outcomes.
2. AI is moving up the decision chain to strategic and senior management levels.
3. AI techniques are being linked and used in more powerful combinations.
4. AI is beginning to leverage web intelligence from social networks, search services, and semantic applications.
See his article for more details and for his predictions on future trends. There is also an interesting analysis of Tow's ideas on the Genetic Argonaut.
May 23, 2009
The Pursuit of Thinking Machines
In March of 2009, the Second Conference on Artificial General Intelligence, AGI-09, was held in Arlington, Virginia. The conference's main topic is the Holy Grail of the AI field -- the creation of thinking machines with human-level (or higher) intelligence. The 100 attendees included independent researchers, members of academia as well as representatives from major tech companies like Google, GE, AT&T, and Autodesk.
Conference Chair Ben Goertzel sees most AI research today as having a focus which is too narrow and specialized. The dream on which he says AI was founded, of "software displaying intelligence with the same sort of generality that human intelligence seems to have," is not being addressed by research. The AGI conference is part of concerted effort to form a cohesive community ready to focus on radical innovation and an acceptance of diverse approaches.
May 19, 2009
Automating the Work of Scientists
We wrote here in an earlier post about a robot in the U.K. that can perform laboratory experiments independently ("Meet Adam, the Robotic Junior Lab Assistant"). Now the journal Science reports that two Cornell scientists have developed a computer program that sifts raw data to uncover fundamental laws of nature.
The program, developed by professor Hod Lipson and graduate student Michael Schmidt, uses genetic programming techniques by starting with random guesses at a solution and then using an evolutionary algorithm to mutate equations until it finds a solution that works. The research worked on data to find invariant equations. Such equations often point to fundamental natural laws.
"It's a nice piece of work," said John R. Koza, a computer scientist at Stanford who pioneered genetic programming. "It's another good example of how genetic programming can do things that are comparable to what human scientists can do."
See video of Hod Lipson and his self-replicating robots on TED.com.
May 5, 2009
Meet Adam, the Robotic Junior Lab Assistant
The BBC News reports that scientists in the U.K. have created a robot that can perform experiments on its own. The robot is named Adam and is described as the first automated machine to have independently "discovered new scientific knowledge." This was accomplished when Adam identified the role of several genes in yeast cells and then planned future experiments to test the hypotheses. The team of computer scientists at Aberystwyth University who developed the robot say it's a prototype for machines that could be commonly used in labs to complete mundane experiments, freeing up scientists to carry out more advanced work.
April 19, 2009
NewScientist reports on video modular robots which "reassemble when kicked apart." The technology is actually called self-configurable robotics, and it's been enabled recently by advances in robot hardware, communications, and control algorithms. A year ago, a team of U.S. researchers from several universities created a blueprint for cell-like robotic modules that can rearrange themselves to create different shapes. The Defense Advanced Research Projects Agency (DARPA) then set aside $4 million for studies to see if these modules can be mass produced for demonstrations. See the fascinating video and read more about self-reconfigurable robots here.
April 4, 2009
Duke University's K* Program and the War on Germs
A team of computer scientists and biochemists at Duke University have developed a computer program that will help researchers discover how bacteria become resistant to antibiotics. Results of the program, a set of computer rules known as the K* ("K Star") algorithm, have been verified in laboratory experiments. The techniques used by the K* program could lead to more automated redesign of drugs to battle drug resistance in germs. The K* software is open source code and available to other researchers to evaluate, use and possibly extend.
March 29, 2009
AI Test Patterns
A team of vision research scientists at Queen Mary University of London have developed computer software which creates pictures and stimuli to test visual search abilities in the human brain. The team used a genetic algorithm to 'breed' a range of images and visual stimuli. By using artificial intelligence for test pattern design, the team was able to produce unique tests which were free of predetermined results.
March 23, 2009
Charles Darwin and Robots
Many tributes have been paid to Charles Darwin this year in honor of the double anniversaries of his 200th birthday and 150 years since the publication of On the Origin of Species. On the website Robots.net, Darwin's influence on the field of robotics is examined. The development of bipedal walking and flapping wing mechanisms used evolutionary techniques, as did neural networks which allow robots to learn simple behaviors. See the article for more details on these and other innovations in robotics which are attributable to Darwin's theories.
March 21, 2009
Charles Darwin and Online Dating
To commemorate the 200th anniversary of Darwin's birth and the 150th anniversary of the publication of On the Origin of Species, Discovery Magazine published a special series of articles examining Darwin's impact on modern perceptions of the world. In an article titled We all Live in Darwin's World, the work of Rutgers University biological anthropologist Helen Fisher is discussed. Fisher is a best-selling author of books on love and an advisor to online dating service Chemistry.com. For the dating service, she created a questionnaire based on years of research on the science of romantic attraction. Fisher used the principles of evolutionary psychology, a field with its roots in Charles Darwin's theories.
See the entire article here.
March 9, 2009
Networked Human Computation and the Phrase Detective Game
Researchers at the University of Essex are using an online "game with a purpose" (GWAP) called Phrase Detective to enlist the help of the general public in creating annotated linguistic references. These references are needed in the design of computer programs which recognize human text. Language recognition programs, which include search, translation and summarization applications, work from a large database of language examples where the meaning of individual phrases has been explained. Creating this type of knowledge database is time-consuming and labor-intensive. Making use of networked human computation through the Phrase Detective game allows the University to tap into a free labor force.
In the first four weeks online, Phrase Detective players created more than 40,000 linguistic annotations. This is a promising beginning and will help answer the question of whether networked human computation help provide data to solve complex language comprehension tasks.
February 23, 2009
Garage Genome Hackers
NewScientist describes a do-it-yourself movement in biotechnology, specifically in the area of synthetic biology, which uses genes and cells as the building blocks for the creation of new organisms. The movement includes a diverse mix of people who enjoy tinkering with DNA in their spare time.
The science fiction website io9.com recently sponsored a Mad Scientist contest aimed at "mad scientists with homebrew closet labs, grassroots geneticists, and garage genome hackers." Contestants were asked to build a real life form using MIT's registry of standard biological parts known as "biobricks," or by using other scientifically plausible materials. The idea behind encouragement of this grass-roots movement is to bring a wider group of people into the field of discovery, similar to what happened when tinkerers like the Homebrew Computer Club of the 1970s spawned the first personal computers.
February 21, 2009
New Solar Energy Material Captures the Rainbow
Researchers at Ohio State University have developed a new solar cell material that can absorb all of the energy contained in sunlight. Current solar cell materials capture only a small range of frequencies of light, meaning they capture only part of the energy contained in sunlight. Since the new material is able to absorb all of the light frequencies from sunlight at once, it can be said to capture all of the colors of the rainbow.
Computer-aided molecular design was used to explore different molecular configurations. According to Malcolm Chisholm, Chair of the Department of Chemistry at Ohio State, a commercial version of the new material is several years away. However, the research that has been completed is proof of concept that the new material is viable.
February 3, 2009
Simulating the Evolution of Photosynthesis
A study published in the journal Plant Physiology describes how a team of researchers from the University of Illinois at Urbana-Champaign have used a supercomputer to design a photosynthetic pathway which is 76 percent more efficient than natural pathways. Photosynthesis is a critical biological process in plants which uses sunlight to convert water and carbon dioxide into oxygen and energy stored as carbohydrates. Attempts to improve crop yields without increasing the use of nitrogen-based fertilizers have led to an interest in improving the energy-amassing processes of photosynthesis.
Stephen Long, professor of Crop Sciences at the University of Illinois and a member of the research team, is optimistic about using findings from the simulation to support evolution of more powerful pathways in living plants.
January 27, 2009
GIVE: Human Gamers vs. AI Systems
Northwestern University and an international team of researchers have created an online game which uses artificial intelligence (AI) to challenge players to solve a virtual treasure hunt. Players who visit the GIVE (Generating Instructions in Virtual Environments) game website until the end of January have the opportunity to play the game and provide feedback on how well the system provided instructions. According to Justine Cassell, director of Northwestern University's Center for Technology and Social Behavior, the feedback will be used to help improve NLG (natural language generation) system design.
The GIVE game is part of a growing trend in AI research to allow Internet users to participate in AI system assessment.
January 19, 2009
Simulator Predicts Evolution
Rockefeller University biophysicists Eric D. Siggia and Paul Francois have developed a simulator which can model evolutionary steps to build an adaptive biochemical network. In test runs, Siggia and Francois found that the same series of specific mutations were repeated each time the simulation was restarted. Evolution's next best move was predictable at each step. This simulator takes Darwin's theories to a new level, allowing scientists to study each step in the natural selection process as it occurs.
January 15, 2009
My Presentation Today at the MIT Technology and Culture Forum
I gave a talk today at the MIT Technology and Culture Forum on "The Future of Inventing: Automated, Collaborative, and Distributed Inventing." The talk was attended by a nice cross-section of the MIT community and engendered good discussion about the changing nature of invention.
You can download the slides for the presentation here. You will get the most of the slides if you view them in slideshow mode, since some of the slides contain animations which will not appear correctly otherwise.
I hope to post video clips from the talk soon.
January 11, 2009
New Self-Training Program Predicts Fungi Genes
Science Daily reports that scientists at the Georgia Institute of Technology have developed a self-training software program that will predict genes in the DNA sequences of fungi. Gene prediction for fungal genomes can help in the development and production of important pharmaceuticals and can also aid in the eradication of pathogenic fungi.
According to Mark Borodovsky, director of Georgia Tech's Center for Bioinformatics and Computational Genomics, hundreds of fungal genome sequencing projects currently underway will benefit from the new program.
November 16, 2008
Gamers Solve Problems in Science and Computing
New Scientist reports on an expanding breed of online games that use human problem-solving skills to make progress on cutting-edge problems in science and computing. For example, the puzzles at www.fold.it require players to manipulate 3D structures to fit into the smallest possible space. The web site uses the solutions provided by users to help scientists learn about how proteins fold in the real world.
This and other examples provided in the article are examples of ways in which clever uses of distributed computing are increasingly combining software with human problem-solvers to leverage and combine the strengths of each, and to achieve results that could not have been obtain by either computers or humans individually.
October 13, 2008
Software Improvises Musical Accompaniments
Two University of Southern California researchers have created software that can create an accompaniment to any song "in the style of any chosen artist, or even the particular style used in select pieces by the artist."
October 5, 2008
Complexity: Computers Come to the Rescue
New Scientist reports on how computers are increasingly being used to solve problems that are too complex for human minds to handle, such as making sense out of traffic patterns and assigning robots to paint trucks coming off the assembly line.
September 11, 2008
Evolutionary Computation Solves Century-Old Algebra Problem
Professor Lee Spector and others at Hampshire College used evolutionary computation "to solve a century-old algebra problem far faster and more efficiently than any past efforts of humans or machines." The problem involved finding formulas useful for designing electronic switching circuits. Although previous solutions had been found, such methods resulted in formulas that were so large that they were useless in practice. In contrast, Professor Spector's evolutionary computation-based technique found useful formulas containing fewer than 300 characters in a few hours of computing time.
September 2, 2008
Evolutionary Computation Community Experiences Explosive Growth
Gregory Hornby and Tina Yu have published the "Results of the First Survey of Practitioners of Evolutionary Computation," which reveals that "in recent years there has been an explosion not only in the different types of biologically inspired algorithms, but also in the number of practitioners in the field." The survey also found that the biggest obstacle for the acceptance of evolutionary computation in industry is that it is poorly understood. The survey was conducted in 2005-2006 by posting 14 survey questions on the web site of the Special Interest Group on Genetic and Evolutionary Computation of the Association for Computing Machinery.
August 15, 2008
Two Heads (One Silicon, One Carbon) Are Better Than One
Using computers to automate inventing does not mean that humans become irrelevant. To the contrary, the most effective kinds of invention automation often involve cooperation between human and computer, a partnership in which each member does what it does best. Interactive evolutionary computation strives to take advantage of such synergies.
Louis von Ahn has developed a specialty in creating computer games which double as human-computer teams for solving problems that neither could solve by itself, such as:
- The ESP Game, which shows the same image to two people and requires them to type in a word describing it, ostensibly to read each others' minds, but also to create a text-searchable database of images (a problem which computer algorithm designers have yet to crack);
- Tag a Tune, a similar game using songs instead of images; and
- Verbosity, in which one player is shown a secret word and must provide clues from which a second player attempts to guess the secret word, all with the effect of creating a database of word meanings.
August 12, 2008
Software (Re)Invents the Wheel
Evolutionary software has invented the wheel.
Not impressed? Then consider that a circle is not the only shape which maintains a constant height when rolled across flat ground. Can you figure out what the other shapes are? If not, then don't feel bad. They were not discovered until the late 19th century. Yet an evolutionary algorithm rediscovered them in under an hour.
August 9, 2008
See Evolved LEGO Structures in Action
Check out the Brandeis DEMO (Dynamical and Evolutionary Machine Organization) web site for videos of LEGO bridges, cranes, tables, and other structures designed using evolutionary algorithms.
August 6, 2008
Combining Real and Simulated Evolution for Aircraft Design
Most of the examples of automated inventing described on this web site to date were generated using computer simulations. In contrast, Will Regan, Floris van Breugel, and Hod Lipson of Cornell University have used a combination of simulation and a real-world hardware implementation of a "hovering flapping ornithopter" -- essentially an aircraft with flapping wings -- demonstrate the feasibility of this kind of flight (which, as we all know, is not how the airplanes we know and love work). Their paper includes images of both the simulated and physical models they used.
August 3, 2008
Computer Game Opponents Evolve
Steffen Priesterjahn and others at the University of Paderborn in Germany have used evolutionary algorithms to generate smarter computer players for the game Quake 3. They generated a set of players which played with an initial set of strategies, then played them against the standard computer opponent. The strategies of the best-performing players were combined (mated) with each other to produce offspring, some of which were also mutated. After multiple generations this evolutionary process created computer players that were significantly more difficult for human players to beat.
July 31, 2008
Automated Invention of a Thrombin Inhibitor
Matrix Advanced Solutions has used its "artificial creativity" software to create an orally-available thrombin inhibitor to act as an anticoagulant. The thrombin inhibitor, which was developed without the use of any expert knowledge, is now in pre-clinical trials.
July 28, 2008
Affinnova, Inc. has used its "evolutionary optimization" technology to help its clients optimize ad strategies, product package designs, and product promotions. For example, the company used its software to develop a new logo for Cadbury-Scweppe's 7-Up soft drink by displaying millions of possible combinations of design elements (such as backgrounds, color schemes, and logo placements) to consumers in an online selection process which "evolved" the logo in response to consumer preferences.
February 20, 2006
February 4, 2006
Software That Learns on the Job
TRN Research News reports that researchers at Princeton University have developed two "self-improving" algorithms, a sorting algorithm (which sorts data into a logical order) and a clustering algorithm (which groups similar items together).
January 22, 2006
Computer Science Cuts Across Disciplines
An article entitled "Computer Science Growing Into a Basic Science" describes how increases in computing power are fueling the use of computers "to solve fundamental problems across physical, chemical, biological, engineering, medical and social sciences," and includes several concrete examples.
January 16, 2006
Thoughts on Software Design Automation from 32 Years Ago
Because of the expense it is not practical to develop design-specific D[esign] A[utomation] systems. Designers of DA systems are thus confronted with the task of building 'large, generalized, flexible' (software) systems with very little design assistance from the computer. If only we had systems which apply the computer and computer techniques to automate (or at least facilitate) the design of software: software design automation! Unfortunately, while the theory underlying the application of comptuers in the design of computing hardware has developed thoroughly, keeping pace (or nearly so) with the developing technology, the implementation of this theory remains a difficult, mostly manual exercise in the design of programs and programming systems.
January 4, 2006
Quantum Computing Comes One Step Closer
ACD points out that the IQOQI (Institute of Quantum Optics and Quantum Information) in Austria has produced the first "quantum byte," consisting of 8 Calcium ions. This development brings the "quantum computer" closer to becoming a reality.
According to the current Wikipedia entry for "quantum computer," "It is widely believed that if large-scale quantum computers can be built, they will be able to solve certain problems faster than any classical computer." The implications for artificial invention are clear. Most of the software that is being used for artificial inventing relies on powerful computers and, perhaps more importantly, provides better results when run on even more powerful computers. As a result, people in the field are always seeking more powerful computers at lower cost. Why design better software when you can improve your results just by running the same software on a more powerful computer?
John Koza began using a 1,000-Pentium computer back in 1999 to run genetic algorithms for (among other things) inventing new hardware and software (see photo). Although today's computers can provide the same performance for about 1/10th of the price of Koza's 1999 system, he was able to achieve impressive results using the technology that was available at the time. Fully quantum computers, if they were to become possible, could take this forward by (pun fully intended) a quantum leap.
December 31, 2005
I changed the name of the "Artificial Creativity" category on this blog to "Artificial Invention." Invention doesn't always involve "creativity," and I wanted the name of the category to reflect this. Sometimes invention results from serendipity, brute force trial-and-error, or following design rules. The path leading to an invention may involve some combination of these and other features. So "artificial invention" it is.
December 30, 2005
The Latest in Automatic Programming
- A program, developed by Doug Smith and others at the Kestrel Institute, that "translates a description of a problem into guidelines a computer can understand," and which has been used "to develop software for scheduling cargo deployment for the U.S. military."
- Software from SciComp that "helps investment banks design programs to price financial derivatives."
- An automatic programming program from Tenfold which "can generate corporate software in three weeks, compared with more than a year when done by hand."
The article ends on a note that is consistent with my posting yesterday: "Still, automated code doesn't yet compare in quality to what's generated by hand . . . . Programmers can rest easy knowing that their jobs are safe--at least for now."
August 11, 2005
Never send a computer to do a human's job, especially if the human works for free
Although this blog is about computer automation, humans still outshine computers in the ability to make aesthetic judgments. Despite advances in automated image processing, for example, computers still have a long way to go in recognizing the contents of a photograph or judging whether a new clothing design would be visually appealing to customers.
Interactive evolutionary computation attempts to provide the best of both worlds by combining the ability of computers to generate new designs with the ability of humans to evaluate their aesthetics. Techdirt writes about a researcher at Carnegie Mellon University who has created two online games (here and here) that are fun to play in their own right, and which use the input of the games' users to improve the ability of computers to search for and recognize digital images.
The human players of these games provide descriptive labels of images they are shown and point out key portions of such images, two tasks that computers perform poorly. The human input, however, can then be used by computers to better search for and recognize subsequent images. For example, if many human players of the first game have labeled images of elephants with the word "elephant," when someone then performs a search for "elephant" images, computer software can easily pull up the right pictures just by searching through the human-provided labels, rather than by attempting to recognize the images themselves.
Although I don't believe that either of these games uses interactive evolutionary computation, the philosophy behind both is the same: to form a partnership between computers and humans, using each for what it does best. And when the humans provide input for free, deciding whether to incorporate their superior aesthetic judgments into computer software is a no-brainer.
August 10, 2005
IPcentral ponders the difficult question of who should own the technical know-how that is inside the heads of workers at high-tech companies. The posting was motivated by a recent court ruling that temporarily bars a former Microsoft employee from performing search-related work for his new employer, Google, because doing so would violate his non-compete agreement with Microsoft.
Trade secret law and non-compete agreements have long been used to control the movement of know-how and other information stored in the heads of human scientists, engineers, and programmers. But what happens when we "bottle" such know-how, or its equivalent, in the form of software that can design machines and write software? You might think that a company that develops an improved genetic algorithm that assists it in designing new machines should maintain that algorithm as a closely-guarded trade secret. After all, isn't the algorithm the functional equivalent of an engineer's know-how within the framework of the company's business model?
But I don't think the answer is entirely obvious. Perhaps the company should seek a patent on the algorithm, thereby obtaining a period of time in which it can block competitors from using the same algorithm even if they develop it themselves independently. Or maybe they should use some combination of intellectual property protection and licensing mechanisms to secure the maximum value to the company.
The point is that transferring know-how from a human mind to software raises some tricky legal and business considerations that will need to be addressed as the automation of invention continues.
July 22, 2005
Artificial inventions in simulated worlds
And what if the simulated humans discover fire, invent the wheel, or invent something completely new? Who would own the patent rights?
I suppose the next step would be for the simulated humans to write a (simulated) simulation of (simulated) humans, and so on, and so on . . .
July 18, 2005
Imagination Engines Launches New Web Site
Imagination Engines is a small company working with what many have recognized as potentially the biggest idea in history, a technology that can invent everything else. Accordingly, largely due to issues of credibility, the company's road to success has been rocky. There have been many skeptics and critics, but there have been more believers and supporters. Now the company thrives upon a significant contract stream and tangible products that speak louder for the technology than words possibly could.
I believe I first heard about the company when I read an article (such as this one) describing how the company had used its patented Creativity Machine to invent the Oral-B CrossAction toothbrush. Although genetic algorithms seem to be getting most of the attention these days, Imagination Engines' Creativity Machine relies on neural networks.
June 21, 2005
European Parliament Renames the "Software Patent Directive"
ZDNet UK has an article reporting that the European Parliament has proposed changing the name of the so-called "software patent directive" to use the term "computer-aided invention" in place of the old term, "computer-implemented invention." For those of you who can't see what difference this could possibly make, the stated reason for the proposed change is to make it clear that software is not patentable per se, but rather only as part of an innovation that uses software "to aid the performance of the invention."
These and other attempts over the years to find just the right term to define patents on software are, in my view, doomed to fail. One motivation for my "software patent puzzle" (see parts 1 and 2) is to demonstrate that there is no principled way to use the hardware/software distinction as a basis for distinguishing patentable inventions from unpatentable ones.
Instead, I propose that we focus our attention on the patentability of "computer-generated inventions." Examples of computer-generated inventions include software (a computer generates software when you program the computer) and any device whose design is generated by a genetic algorithm or other artificial creativity software.
It is the "computer-generated" feature of software that keeps causing problems for patent law, and that will continue to cause problems for patent law as computers automate the invention of things other than software. I can't justify that claim in a single blog posting, but I tried to make the basic argument here, and will continue to extend the argument in future postings.
June 16, 2005
Blogging from GECCO and NASA/DOD EH Conferences
I will be attending and blogging from the Genetic and Evolutionary Computation Conference (GECCO 2005) and the NASA/DOD Conference on Evolvable Hardware from June 27-July 1. (Unfortunately I will miss the first two days of GECCO.) These conferences will provide tutorials and updates on the latest developments not only in computer-automated design, but more generally in evolution-inspired computing.
Instead of attempting to duplicate or compete with Illigal Blogging's live coverage of the GECCO conference, I plan to post my thoughts on the legal and broader social implications of the topics covered in the conference sessions. I will also interview presenters and attendees for a book I am writing on computer-automated invention and the law. (I may post excerpts/summaries of those interviews here, with the interviewees' permission.) If you would like to speak with me, just track me down at the conference (you can see what I look like here).