computer science

Steve Omohundro

Steve Omohundro is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Steve Omohundro rather than just read about it. In short: Stephen Malvern Omohundro (born 1959) is an American computer scientist whose areas of research include Hamiltonian physics, dynamical systems, programming languages, machine learning, machine vision, and the social implications of artificial intelligence. His current work uses rational economics to develop safe and beneficial intelligent technologies for better collaborative modeling, understanding, innovation, and…

Key takeaways

Steve Omohundro belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Steve Omohundro to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Steve Omohundro from memory before moving on to harder problems.

Reference excerpt

Stephen Malvern Omohundro (born 1959) is an American computer scientist whose areas of research include Hamiltonian physics, dynamical systems, programming languages, machine learning, machine vision, and the social implications of artificial intelligence. His current work uses rational economics to develop safe and beneficial intelligent technologies for better collaborative modeling, understanding, innovation, and decision making.

Education Omohundro has degrees in physics and mathematics from Stanford University (Phi Beta Kappa) and a Ph.D. in physics from the University of California, Berkeley.

Learning algorithms Omohundro started the "Vision and Learning Group" at the University of Illinois, which produced 4 Masters and 2 Ph.D. theses. His work in learning algorithms included a number of efficient geometric algorithms, the manifold learning task and various algorithms for accomplishing this task, other related visual learning and modelling tasks, the best-first model merging approach to machine learning (including the learning of Hidden Markov Models and Stochastic Context-free Grammars), and the Family Discovery Learning Algorithm, which discovers the dimension and structure of a parameterized family of stochastic models.

Self-improving artificial intelligence and AI safety Omohundro started Self-Aware Systems in Palo Alto, California to research the technology and social implications of self-improving artificial intelligence. He is an advisor to the Machine Intelligence Research Institute on artificial intelligence. He argues that rational systems exhibit problematic natural "drives" that will need to be countered in order to build intelligent systems safely. His papers, talks, and videos on AI safety have generated extensive interest. He has given many talks on self-improving artificial intelligence, cooperative technology, AI safety, and connections with biological intelligence.

Programming languages At Thinking Machines Corporation, Cliff Lasser and Steve Omohundro developed Star Lisp, the first programming language for the Connection Machine. Omohundro joined the International Computer Science Institute (ICSI) in Berkeley, California, where he led the development of the open source programming language Sather. Sather is featured in O'Reilly's History of Programming Languages poster.

Physics and dynamical systems theory Omohundro's book Geometric Perturbation Theory in Physics describes natural Hamiltonian symplectic structures for a wide range of physical models that arise from perturbation theory analyses. He showed that there exist smooth partial differential equations which stably perform universal computation by simulating arbitrary cellular automata. The asymptotic behavior of these PDEs is therefore logically undecidable. With John David Crawford he showed that the orbits of three-dimensional period doubling systems can form an infinite number of topologically distinct torus knots and described the structure of their stable and unstable manifolds.

Mathematica and Apple tablet contest From 1986 to 1988, he was an Assistant Professor of Computer science at the University of Illinois at Urbana-Champaign and cofounded the Center for Complex Systems Research with Stephen Wolfram and Norman Packard. While at the University of Illinois, he worked with Stephen Wolfram and five others to create the symbolic mathematics program Mathematica. He and Wolfram led a team of students that won an Apple Computer contest to design "The Computer of the Year 2000." Their design entry "Tablet" was a touchscreen tablet with GPS and other features that finally appeared when the Apple iPad was introduced 22 years later.

Other contributions Subutai Ahmad and Steve Omohundro developed biologically realistic neural models of selective attention. As a research scientist at the NEC Research Institute, Omohundro worked on machine learning and computer vision, and was a co-inventor of U.S. Patent 5,696,964, "Multimedia Database Retrieval System Which Maintains a Posterior Probability Distribution that Each Item in the Database is a Target of a Search."

Pirate puzzle Omohundro developed an extension to the game theoretic pirate puzzle featured in Scientific American.

Outreach Omohundro has sat on the Machine Intelligence Research Institute board of advisors. He has written extensively on artificial intelligence, and has warned that "an autonomous weapons arms race is already taking place" because "military and economic pressures are driving the rapid development of autonomous systems".

References

External links Official website Self-Aware Systems Steve Omohundro Interviews Playlist

Illustrations

Worked examples

Example 1 — a first encounter with Steve Omohundro

Start with the simplest possible case. Write down what Steve Omohundro claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Steve Omohundro before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Steve Omohundro ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Steve Omohundro

In research: Steve Omohundro appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Steve Omohundro in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Steve Omohundro is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1959 births, AI safety scientists, American artificial intelligence researchers, so understanding it makes those chapters shorter.
In everyday life: Look for Steve Omohundro outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Steve Omohundro” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Steve Omohundro in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Steve Omohundro means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Steve Omohundro out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Steve Omohundro in simple terms?

Why does Steve Omohundro matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Steve Omohundro?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Steve Omohundro.