science

Machine Intelligence Research Institute

Machine Intelligence Research Institute is a 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 Machine Intelligence Research Institute rather than just read about it. In short: The Machine Intelligence Research Institute (MIRI), formerly the Singularity Institute for Artificial Intelligence (SIAI), is a non-profit research institute focused since 2005 on identifying and managing potential existential risks from artificial intelligence. MIRI's work has focused on a friendly AI approach to system design and on predicting the rate of technology development.

Key takeaways

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

Reference excerpt

The Machine Intelligence Research Institute (MIRI), formerly the Singularity Institute for Artificial Intelligence (SIAI), is a non-profit research institute focused since 2005 on identifying and managing potential existential risks from artificial intelligence. MIRI's work has focused on a friendly AI approach to system design and on predicting the rate of technology development.

History

In 2000, Eliezer Yudkowsky founded the Singularity Institute for Artificial Intelligence with funding from Brian and Sabine Atkins, with the purpose of accelerating the development of artificial intelligence (AI). However, Yudkowsky began to be concerned that AI systems developed in the future could become superintelligent and pose risks to humanity. In 2005 the institute moved from Atlanta to Silicon Valley and began to focus on ways to identify and manage those risks, which were at the time largely ignored by scientists in the field. Starting in 2006, the Institute organized the Singularity Summit to discuss the future of AI including its risks, initially in cooperation with Stanford University and with funding from Peter Thiel. The San Francisco Chronicle described the first conference as a "Bay Area coming-out party for the tech-inspired philosophy called transhumanism". In 2011, its offices were four apartments in downtown Berkeley. In December 2012, the institute sold its name, web domain, and the Singularity Summit to Singularity University, and in the following month took the name "Machine Intelligence Research Institute". In 2014 and 2015, public and scientific interest in the risks of AI grew, increasing donations to fund research at MIRI and similar organizations. In 2019, Open Philanthropy recommended a general-support grant of approximately $2.1 million over two years to MIRI. In April 2020, Open Philanthropy supplemented this with a $7.7M grant over two years. In 2021, Vitalik Buterin donated several million dollars' worth of Ethereum to MIRI.

Research and approach

MIRI's approach to identifying and managing the risks of AI, led by Yudkowsky, primarily addresses how to design friendly AI, covering both the initial design of AI systems and the creation of mechanisms to ensure that evolving AI systems remain friendly. MIRI researchers advocate early safety work as a precautionary measure. However, MIRI researchers have expressed skepticism about the views of singularity advocates like Ray Kurzweil that superintelligence is "just around the corner". MIRI has funded forecasting work through an initiative called AI Impacts, which studies historical instances of discontinuous technological change, and has developed new measures of the relative computational power of humans and computer hardware. MIRI aligns itself with the principles and objectives of the effective altruism movement.

Works by MIRI staff Graves, Matthew (8 November 2017). "Why We Should Be Concerned About Artificial Superintelligence". Skeptic. The Skeptics Society. Retrieved 28 July 2018. LaVictoire, Patrick; Fallenstein, Benja; Yudkowsky, Eliezer; Bárász, Mihály; Christiano, Paul; Herreshoff, Marcello (2014). "Program Equilibrium in the Prisoner's Dilemma via Löb's Theorem". Multiagent Interaction without Prior Coordination: Papers from the AAAI-14 Workshop. AAAI Publications. Soares, Nate; Levinstein, Benjamin A. (2017). "Cheating Death in Damascus" (PDF). Formal Epistemology Workshop. Retrieved 28 July 2018. Soares, Nate; Fallenstein, Benja; Yudkowsky, Eliezer; Armstrong, Stuart (2015). "Corrigibility". AAAI Workshops: Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, Austin, TX, January 25–26, 2015. AAAI Publications. Archived from the original on 2016-01-15. Retrieved 2015-10-16. Soares, Nate; Fallenstein, Benja (2015). "Aligning Superintelligence with Human Interests: A Technical Research Agenda" (PDF). In Miller, James; Yampolskiy, Roman; Armstrong, Stuart; et al. (eds.). The Technological Singularity: Managing the Journey. Springer. Yudkowsky, Eliezer (2008). "Artificial Intelligence as a Positive and Negative Factor in Global Risk" (PDF). In Bostrom, Nick; Ćirković, Milan (eds.). Global Catastrophic Risks. Oxford University Press. ISBN 978-0199606504. Taylor, Jessica (2016). "Quantilizers: A Safer Alternative to Maximizers for Limited Optimization". Workshops at the Thirtieth AAAI Conference on Artificial Intelligence. Yudkowsky, Eliezer (2011). "Complex Value Systems in Friendly AI" (PDF). Artificial General Intelligence: 4th International Conference, AGI 2011, Mountain View, CA, USA, August 3–6, 2011. Berlin: Springer. Yudkowsky, Eliezer; Soares, Nate (2025). If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All. p. 256. ISBN 9781668652657.

See also Allen Institute for Artificial Intelligence Future of Humanity Institute Institute for Ethics and Emerging Technologies

References

Further reading Russell, Stuart; Dewey, Daniel; Tegmark, Max (Winter 2015). "Research Priorities for Robust and Beneficial Artificial Intelligence". AI Magazine. 36 (4): 6. arXiv:1602.03506. Bibcode:2016arXiv160203506R. doi:10.1609/aimag.v36i4.2577.

External links Official website "Machine Intelligence Research Institute". Internal Revenue Service filings. ProPublica Nonprofit Explorer.

Illustrations

Worked examples

Example 1 — a first encounter with Machine Intelligence Research Institute

Start with the simplest possible case. Write down what Machine Intelligence Research Institute claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In 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 Machine Intelligence Research Institute 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 Machine Intelligence Research Institute 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 Machine Intelligence Research Institute

In research: Machine Intelligence Research Institute appears in 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 Machine Intelligence Research Institute 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: Machine Intelligence Research Institute is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2000 establishments in California, 501(c)(3) organizations, American organizations established in 2000, so understanding it makes those chapters shorter.
In everyday life: Look for Machine Intelligence Research Institute 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.

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How to study Machine Intelligence Research Institute in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Machine Intelligence Research Institute 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 Machine Intelligence Research Institute out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Machine Intelligence Research Institute in simple terms?

Why does Machine Intelligence Research Institute matter?

Because it connects several 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 Machine Intelligence Research Institute?

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 Machine Intelligence Research Institute.