Johns Hopkins Center for Health Security

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https://en.wikipedia.org/wiki/Johns_Hopkins_Center_for_Health_Security 

 

Johns Hopkins Center for Health Security

Abbreviation	CHS
Formation	1998
Type	Think tank
Location	Baltimore, Maryland, United States of America
CEO and Director	Tom Inglesby
COO and Deputy Director	Anita Cicero
Key people	D. A. Henderson Tara O'Toole
Affiliations	Johns Hopkins Bloomberg School of Public Health
Staff (2021)	29
Website	www.centerforhealthsecurity.org
Formerly called	Johns Hopkins Center for Civilian Biodefense Strategies (1998–2003) Center for Biosecurity of UPMC (2003–2013) UPMC Center for Health Security (2013–2017)

The Johns Hopkins Center for Health Security (abbreviated CHS) is an independent, nonprofit organization of the Johns Hopkins Bloomberg School of Public Health. The center works to protect people's health from epidemics and pandemics and ensures that communities are resilient to major challenges. The center is also concerned with biological weapons and the biosecurity implications of emerging biotechnology.

The Center for Health Security gives policy recommendations to the United States government, the World Health Organization and the UN Biological Weapons Convention.

History

The Center for Health Security began as the Johns Hopkins Center for Civilian Biodefense Strategies (CCBS) in 1998 at the Johns Hopkins Bloomberg School of Public Health. D. A. Henderson served as the founding director. At that time, the center was the first and only academic center focused on biosecurity policy and practice.

At one point around 2003, CHS had become part of a new umbrella organization called the Institute for Global Health and Security at the Johns Hopkins Bloomberg School of Public Health.

In November 2003, some of the leaders left Johns Hopkins to join the University of Pittsburgh Medical Center (UPMC), and launched their own Center for Biosecurity of UPMC. This move apparently split the organization in two, and it is unclear what happened to the old organization.

On April 30, 2013, the UPMC Center changed its name from "Center for Biosecurity of UPMC" to "UPMC Center for Health Security". This name change reflected a broadening of the scope of CHS's work.

In January 2017, the JHU Center became part of the Johns Hopkins Bloomberg School of Public Health. Its domain name changed from upmchealthsecurity.org to centerforhealthsecurity.org.

Funding

In 2002, the center received a $1 million grant from the US federal government.

Before 2017, CHS was heavily reliant on government funding.

In January 2017, the Open Philanthropy Project awarded a $16 million grant over three years to the Center for Health Security. Another grant of $19.5 million was awarded in September 2019.

Publications

The Center for Health Security publishes three online newsletters:

• Clinicians' Biosecurity News (formerly the Clinicians' Biosecurity Network Report), published twice each month
• Health Security Headlines, a news digest published 3 times a week (previously called Biosecurity Briefing, then Biosecurity News in Brief starting in 2009, then Biosecurity News Today starting in 2010 or 2011, and finally Health Security Headlines starting in 2013; the digest used to also be weekly until in February 2009, HSH was published daily from 2009 until late 2021 when it was changed to 3 times per week to accommodate the COVID-19 Update briefings published twice a week since January 2020)
• Preparedness Pulsepoints, published weekly

It maintains and edits a peer reviewed journal Health Security which is part of the Mary Ann Liebert publishing group.

It also provides editorial oversight for the journal Health Security, which was launched in 2003 and called Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science until 2015.

CHS published the blog The Bifurcated Needle until 2020.

The Open Philanthropy Project's grant writeup of CHS noted several publications:

• Boddie, Crystal; Watson, Matthew; Ackerman, Gary; Gronvall, Gigi Kwik (August 21, 2015). "Assessing the bioweapons threat: Is there a foundation of agreement among experts about risk?" (PDF). Science. 349 (6250): 792–793. doi:10.1126/science.aab0713. ISSN 0036-8075. PMID 26293941. S2CID 206637099.
• Inglesby, Thomas V.; Relman, David A. (February 1, 2016). "How likely is it that biological agents will be used deliberately to cause widespread harm?". EMBO Reports. 17 (2): 127–130. doi:10.15252/embr.201541674. ISSN 1469-3178. PMC 5290809. PMID 26682799.
• Gronvall, Gigi Kwik; Shearer, Matthew; Collins, Hannah; Inglesby, Thomas (July 14, 2016). "Improving Security through International Biosafety Norms" (PDF). UPMC Center for Health Security.

The center has published in journals including JAMA and The Lancet. A full list of publications is available on the CHS website. As of February 2017, the list shows more than 400 publications.

Major conferences and tabletop exercises

Operation Dark Winter

Main article: Operation Dark Winter

From June 22–23, 2001, CHS co-hosted Operation Dark Winter, a senior-level bioterrorism attack simulation involving a covert and widespread smallpox attack on the United States.

Atlantic Storm

On January 14, 2005, CHS helped to host Atlantic Storm, a table-top smallpox bioterrorism simulation.

Clade X

On May 15, 2018, the Center hosted Clade X, a day-long pandemic tabletop exercise that simulated a series of National Security Council–convened meetings of 10 US government leaders, played by individuals prominent in the fields of national security or epidemic response.

Drawing from actual events, Clade X identified important policy issues and preparedness challenges that could be solved with sufficient political will and attention. These issues were designed in a narrative to engage and educate the participants and the audience.

Clade X was livestreamed on Facebook and extensive materials from the exercise are available online.

Event 201

On October 18, 2019, the CHS partnered with the World Economic Forum and the Bill and Melinda Gates Foundation to host the tabletop exercise Event 201 in New York City. According to the CHS, "the exercise illustrated areas where public/private partnerships will be necessary during the response to a severe pandemic in order to diminish large-scale economic and societal consequences".

Event 201 simulated the effects of a fictional coronavirus passing to humans via infected pig farms in Brazil with "no possibility of a vaccine being available in the first year". The simulation ended after 18 months with 65 million deaths from the coronavirus.

Other

• Improving Epidemic Response: Building Bridges Between the US and China. May 2012.
• Considerations for the Reauthorization of the Pandemic and All-Hazards Preparedness Act (PAHPA). March 2012.
• U.S. Preparedness for a Nuclear Detonation. October 2011.
• Charting the Future of Biosecurity: Ten Years After the Anthrax Attacks. October 2011.
• Advancing US Resilience to a Nuclear Catastrophe. May 2011.
• Preserving National Security: The Growing Role of the Life Sciences. March 2011.
• Improving Global Health, Strengthening Global Security. November 2010.
• The State of BIOPreparedness: Lessons from Leaders, Proposals for Progress. September 2010.
• Preparing to Save Lives and Recover After a Nuclear Detonation: Implications for US Policy. April 2010.
• The 2009 H1N1 Experience: Policy Implications for Future Infectious Disease Emergencies. March 2010.
• Resilient American Communities: Progress In Practice and Policy. December 10, 2009.
• Prevention of Biothreats: A Look Ahead. October 6, 2009.
• Disease, Disaster, and Democracy: The Public's Stake in Health Emergency Planning. May 2006.
• Bulls, Bears, and Birds: Preparing the Financial Industry for a Pandemic. September 2005.
• Conference on Biosafety and Biorisks. May 2005.
• The Public as an Asset, Not a Problem: A Summit on Leadership During Bioterrorism. February 2003.
• 2nd National Symposium on Medical and Public Health Response to Bioterrorism. November 2000.
• National Symposium on Medical and Public Health Response to Bioterrorism. February 1999.

Bulletin of the Atomic Scientists

From Wikipedia, the free encyclopedia

 

 

Bulletin of the Atomic Scientists

The cover of the Bulletin of the Atomic Scientists has featured the famous Doomsday Clock since it debuted in 1947, when it was set at seven minutes to midnight.
Discipline	Science policy
Language	English
Edited by	John Mecklin
Publication details
Former name(s)	Bulletin of the Atomic Scientists of Chicago
History	1945–present
Publisher	Taylor and Francis for the Bulletin of the Atomic Scientists (United States)
Frequency	Bimonthly
Impact factor	2.092 (2020)
Standard abbreviations
ISO 4	Bull. At. Sci.
Indexing
CODEN	BASIAP
ISSN	0096-3402 (print) 1938-3282 (web)
LCCN	48034039
OCLC no.	470268256
Links
Journal homepage Free-access website Taylor & Francis Online

The Bulletin of the Atomic Scientists is a nonprofit organization concerning science and global security issues resulting from accelerating technological advances that have negative consequences for humanity. The Bulletin publishes content at both a free-access website and a bi-monthly, nontechnical academic journal. The organization has been publishing continuously since 1945, when it was founded by former Manhattan Project scientists as the Bulletin of the Atomic Scientists of Chicago immediately following the atomic bombings of Hiroshima and Nagasaki. The organization is also the keeper of the symbolic Doomsday Clock, the time of which is announced each January.

Background

One of the driving forces behind the creation of the Bulletin was the amount of public interest surrounding atomic energy and rapid technological change at the dawn of the Atomic Age. In 1945 the public interest in atomic warfare and weaponry inspired contributors to the Bulletin to attempt to inform those interested about the dangers of the nuclear arms race they knew was coming and about the destruction that atomic war could bring about. To convey the particular peril posed by nuclear weapons, the Bulletin devised the Doomsday Clock in 1947, with an original setting of seven minutes to midnight.

The minute hand of the Clock first moved closer to midnight in response to changing world events in 1949, following the first Soviet nuclear test. The Clock has been set forward and back over the years as circumstances have changed; as of 2023, it is set at 90 seconds to midnight. The Doomsday Clock is used to represent threats to humanity from a variety of sources: nuclear and other weapons of mass destruction, climate change, and disruptive technologies. In 2015, the Bulletin unveiled its Doomsday Dashboard, an interactive infographic that illustrates some of the data the Bulletin's Science and Security Board takes into account when deciding the time of the Clock each year. As of August 2018, the Bulletin's Board of Sponsors boasts 14 Nobel Laureates.

In the 1950s, the Bulletin was involved in the formation of the Pugwash Conferences on Science and World Affairs, annual conferences of scientists concerned about nuclear proliferation, and, more broadly, the role of science in modern society.

History

Founders and contributors

The founder and first editor of the Bulletin of the Atomic Scientists was biophysicist Eugene Rabinowitch (1901–1973). He founded the magazine with physicist Hyman Goldsmith. Rabinowitch was a professor of botany and biophysics at the University of Illinois and was also a founding member of the Continuing Committee for the Pugwash Conferences on Science and World Affairs. In addition to Rabinowitch and Goldsmith, contributors have included: Morton Grodzins, Hans Bethe, Anatoli Blagonravov, Max Born, Harrison Brown, Stuart Chase, Brock Chisholm, E.U. Condon, Albert Einstein, E.K. Fedorov, Bernard T. Feld, James Franck, Ralph E. Lapp, Richard S. Leghorn, J. Robert Oppenheimer, Lord Boyd Orr, Michael Polanyi, Louis Ridenour, Bertrand Russell, Nikolay Semyonov, Leó Szilárd, Edward Teller, A.V. Topchiev, Harold C. Urey, Paul Weiss, James L. Tuck, among many others.

In 1949, the Educational Foundation for Nuclear Science incorporated as a not-for-profit 501(c)(3) organization to serve as the parent organization and fundraising mechanism of the Bulletin. In 2003, the Board of Directors voted to change the foundation's name to Bulletin of the Atomic Scientists.

Purpose

The Bulletin of the Atomic Scientists began as an emergency action undertaken by scientists who saw urgent need for an immediate educational program about atomic weapons. The intention was to educate fellow scientists about the relationship between their world of science and the world of national and international politics. A second was to help the American people understand what nuclear energy and its possible applications to war meant. The Bulletin contributors believed the atom bomb would only be the first of many dangers. The aim of the Bulletin was to carry out the long, sustained effort of educating people about the realities of the scientific age.

The Bulletin of the Atomic Scientists seeks to educate citizens, policy makers, scientists, and journalists by providing non-technical, scientifically sound and policy-relevant information about nuclear weapons, climate change, and other global security issues. The Bulletin also serves as a reliable, high-quality global forum for diverse international opinions on the best means of reducing reliance on nuclear weapons. Since its inception in 1945, the Bulletin has sought to educate the American public of the continual danger posed by nuclear weapons and other global dangers, most recently adding climate change and disruptive technologies in the life sciences to the list of concerns.

The Bulletin's leadership consists of three boards, and it was announced on October 25, 2018 that California Governor Jerry Brown is joining the organization as executive chair.

Board of Sponsors

The Bulletin's Board of Sponsors is composed of accomplished science and security leaders from around the world. Members of the Board of Sponsors weigh in on critical issues, including the setting of the organization's Doomsday Clock. As of October 2018, the Bulletin's Board of Sponsors lists 14 Nobel Laureates.

Science and Security Board

The Bulletin's Science and Security Board is composed of globally-recognized leaders who have specific areas of expertise in nuclear risk, climate change, and disruptive technologies. Members of the Science and Security Board provide the Bulletin organization and editorial staff with perspectives on trends and issues in their respective fields. Among their duties is the annual setting of the Doomsday Clock, with input from the Board of Sponsors.

Doomsday Clock

Main article: Doomsday Clock

 

The Bulletin's logo of the Doomsday Clock as of January 2023.

Once the Soviet Union developed atomic weapons, the concern surrounding the world's destruction was a great fear of the scientists working on the Bulletin. The proximity of nuclear devastation was a popular interest and, as a result, Bulletin co-editor Hyman Goldsmith asked landscape artist Martyl Langsdorf to create a cover for the June 1947 magazine. Langsdorf, who was married to Manhattan Project physicist Alexander Langsdorf, first considered using the symbol for uranium but then realized that a clock would better convey "a sense of urgency." The resultant Doomsday Clock, which only has bullets labeling the numbers in the upper left hand corner, has been featured on the cover of the Bulletin many times since its creation.

The proximity of the minute hand to midnight has been the Bulletin leadership's way of warning the public about manmade threats to humanity; the Clock is a metaphor, not a prediction. When it began in 1947, the minute hand was 7 minutes to midnight; in 1953, when the Soviet Union continued to test more and more nuclear devices, it was 2 minutes to midnight. This proximity to midnight of the Doomsday Clock during the early 1950s shows the concern that the Bulletin contributors had about the Soviet Union and the nuclear arms race. The warnings of the Bulletin continued throughout the 1950s and 1960s, and the focus of the efforts shifted slightly from warning about the dangers of nuclear war to the necessity of disarmament. In 2007, the leadership began taking anthropogenic climate change into account in its Clock discussions. Throughout the history of the Doomsday Clock, it has moved closer to midnight, and farther away, depending upon the status of the world at that time. The Doomsday Clock has been getting closer to midnight since 1991, when it was set to 17 minutes to midnight after the superpowers reached agreement on a nuclear arms reductions.

As of 24 January 2023, the Doomsday Clock stands at 90 seconds to midnight. It is the closest approach to midnight, exceeding that of 1953, 2018 and 2020. The decision to move the hand of the Clock is made by the Bulletin's Science and Security Board, which meets in person twice a year, with subcommittees meeting more often; the announcement of the decision is made each January. Each November, just prior to the Science and Security Board's fall discussion, the Bulletin hosts an annual dinner and meeting in Chicago; both events are open to the public. Reflecting international events dangerous to humankind, the Clock's hand has been adjusted 25 times since its inception in 1947, when it was initially set to seven minutes to midnight (11:53pm).

Present

In more recent years, articles of the Bulletin have focused on many topics, ranging from the dangers of radiation following the Chernobyl disaster to the impact of the fall of the Soviet Union. In the wake of the Soviet Union's collapse, other articles have focused on issues such as military spending and the continued funding of missile defense systems designed to thwart nuclear attacks but that in reality may not work. With the ever-growing number of nuclear power plants and the demand for nuclear energy as a solution to climate change, the publication has focused a great deal on the costs and problems surrounding nuclear energy. In 2015, the Bulletin of the Atomic Scientists unveiled the Nuclear Fuel Cost Calculator.

Although the arms race and the Cold War, which were focuses of the Bulletin for many of the earlier years, are no longer occurring, the publication still focuses on the nuclear dangers that exist in the world today. As more countries such as Pakistan and India have tested nuclear weapons, the Bulletin has focused on the dangers posed by these countries. The Bulletin's bi-monthly "Nuclear Notebook" is written by Federation of American Scientists experts Hans Kristensen and Matt Korda and tracks the number of nuclear weapons in the world by country. Robert "Stan" Norris, who was a founding co-author of the Nuclear Notebook, retired from the Notebook in 2018, although he is still a senior fellow at FAS. In 2015, the Bulletin added the Nuclear Notebook Interactive, an infographic that illustrates which countries have nuclear weapons and when they got them, and how many nuclear warheads they have in any given year. All nine nuclear-armed states are featured: the United States, Russia, China, India, Pakistan, France, Britain, Israel, and North Korea.

In the 21st century, articles have covered threats to humanity from a variety of sources. The potential dangers of nuclear weapons and energy, military and political developments in the Post-Cold War world, political unrest in the Middle East (and its attendant potential for proliferation risks of nuclear and chemical weapons), myriad negative consequences of climate change, cyber warfare, and changes wrought by emerging technologies have all been examined in the Bulletin in the most recent years. Examples include North Korea, Middle East, Syria, Fukushima, Cybersecurity, and Climate Change.

In January 2015, longtime Executive Director and Publisher Kennette Benedict retired. Rachel Bronson took over as president and CEO of the organization. The editor of the Bulletin is John Mecklin.

Next Generation Initiative

As part of the Bulletin's work to engage new audiences in issues related to nuclear threats, climate change, artificial intelligence, and biological threats, the publication launched its Next Generation Initiative to encourage young and emerging scholars to engage on these issues. Programs under the initiative have included writing workshops for graduate and undergraduate students, as well as the Voices of Tomorrow feature, which publishes articles and multimedia projects from emerging scholars and experts working in the Bulletin's interest areas. Two Voices of Tomorrow authors, Emma Bastin and Yangyang Cheng, had their work republished in Teen Vogue.

The capstone of the initiative is the Leonard M. Rieser Award, selected each December by the Bulletin's editorial team from among the year's Voices of Tomorrow submissions. The recipient of the Rieser Award receives $1,000 and a subscription to the Bulletin's bi-monthly magazine. In 2018, Erin Connolly and Kate Hewitt shared the award for their article "American students aren't taught nuclear weapons policy in school. Here's how to fix that problem." Recent recipients include Yangyang Cheng, Nikita Perumal and Moritz Kütt.

Online editions

The Bulletin has had a public-access website available online for some years, with a subscription magazine that comes out 6 times per year and is currently published by Taylor & Francis Online. An e-newsletter is also available without charge by signing up via the Bulletin website.

Backfiles of the subscription magazine are available in the John A. Simpson Collection. The backfile from the first (1945) issue through the November 1998 issue of the Bulletin has also been made available free of charge via Google Books.

November/December 2008 was the last print edition of the Bulletin, which became all-digital only that year. SAGE Publications began publishing the Bulletin's subscription magazine in September 2010; Taylor & Francis took over from Sage in January 2016.

Indexing

The journal is indexed in the Journal Citation Reports, which states that the journal has a 2016 impact factor of 0.452, ranking it 71st out of 83 journals in the category "International Relations" and 32nd out of 41 journals in the category "Social Issues".

Awards

• Finalist for 2009 Lumity Technology Leadership Award
• 2007 National Magazine Award for General Excellence under 100,000 circulation sponsored by the American Society of Magazine Editors with the Columbia University Graduate School of Journalism
• 2006 Silver Excel Award for Magazine Excellence, 20,000 or Fewer for the July/August, September/October, and November/December 2005 issues sponsored by the Society of National Publications
• 2002 Nuclear-Free Future Award
• 1992 Olive Branch Award for articles by David Albright and Mark Hibbs from the N.Y.U. Center for War, Peace and the News Media
• 1990 Olive Branch Award from the N.Y.U. Center for War, Peace and the News Media
• 1989 Olive Branch Award from the N.Y.U. Center for War, Peace and the News Media
• 1988 Olive Branch Award from the N.Y.U. Center for War, Peace and the News Media
• 1987 Olive Branch Award from the N.Y.U. Center for War, Peace and the News Media
• 1987 National Magazine Award
• 1983 Forum Award for the Bulletin of the Atomic Scientists and Ruth Adams, editor sponsored by the Forum on Physics and Society American Physical Society

Allen Institute for Brain Science

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Allen_Institute_for_Brain_Science 

 

Allen Institute for Brain Science

Headquarters of the Allen Institute for Brain Science
Formation	2003
Founders	Paul Allen, Jody Allen
Type	501(c)(3)
Purpose	Neuroscience, brain research, biology, technology
Headquarters	Seattle, Washington, U.S.
Area served	Worldwide
Key people	Hongkui Zeng (director) Christof Koch (chief scientist of the Mindscope Program)
Website	alleninstitute.org/what-we-do/brain-science/

The Allen Institute for Brain Science is a division of the Allen Institute, based in Seattle, Washington, that focuses on bioscience research. Founded in 2003, it is dedicated to accelerating the understanding of how the human brain works. With the intent of catalyzing brain research in different areas, the Allen Institute provides free data and tools to scientists.

Started with $100 million in seed money from Microsoft co-founder and philanthropist Paul Allen in 2003, the institute tackles projects at the leading edge of science—far-reaching projects at the intersection of biology and technology. The resulting data create free, publicly available resources that fuel discovery for countless researchers. Hongkui Zeng is the director of the institute.

History and funding

The Allen Institute for Brain Science is a scientific division of the Allen Institute, a nonprofit research organization that also includes the Allen Institute for Cell Science, launched in 2014. The Paul G. Allen Frontiers Group was launched in 2016 while the Allen Institute for Immunology was launched in 2018. All four divisions of the Allen Institute are housed in the same building in Seattle's South Lake Union neighborhood. The institute employs a business model that combines the operational agility and accountability of a for-profit enterprise with the founding vision to take on ambitious projects in neuroscience.

In 2012, the institute received an additional pledge of $300 million from Paul Allen, bringing his total commitment to $500 million.

Online public resources

The Allen Institute for Brain Science provides researchers and educators with a variety of unique online public resources for exploring the nervous system. Integrating extensive gene expression data and neuroanatomy, along with data search and viewing tools, these resources are openly accessible via the Allen Brain Atlas data portal.

Allen Mouse Brain Atlas

The inaugural project of the Allen Institute was announced on September 26, 2006. Named the Allen Brain Atlas, it was a web-based, three-dimensional map of gene expression in the mouse brain detailing more than 21,000 genes at the cellular level. Since the project's launch, it has been renamed the Allen Mouse Brain Atlas to distinguish it from subsequent atlas projects.

Allen Spinal Cord Atlas

On July 17, 2008, the Allen Institute for Brain Science launched the online Allen Spinal Cord Atlas. The spinal cord atlas is an interactive, genome-wide map showing where each gene is expressed, or "turned on", throughout the mouse spinal cord. It is set up like the Allen Institute's earlier atlas of the adult mouse brain. The map could help reveal new treatments for human neurological disorders. The map points researchers toward places where genes are active.

The Allen Spinal Cord Atlas led to the discovery of a new class of cells in the spinal cord that behave like stem cells, according to researchers at the University of British Columbia. Jane Roskams, the neuroscientist who led the study, said that, "By using the Allen Spinal Cord Atlas, we were able to discover a brand new cell type that has previously been overlooked and that could be an important player in all manner of spinal cord injury and disease, including multiple sclerosis and ALS."

Allen Developing Mouse Brain Atlas

On November 14, 2008, the Allen Institute for Brain Science announced the launch of the Allen Developing Mouse Brain Atlas, providing a highly detailed map of gene activity in the mouse brain at several time points across development, including four embryonic ages, three postnatal, and aging time points. The in situ hybridization data is accompanied by a set of reference atlases drawn by neuroanatomist Luis Puelles.

Allen Human Brain Atlas

On May 24, 2010, the Allen Institute announced it was expanding its tools from the mouse into the human brain with the launch of the Allen Human Brain Atlas. This highly comprehensive atlas integrates several kinds of data, including data collected by magnetic resonance imaging (MRI), diffusion tensor technology (DTI), as well as histology and gene expression data derived from both microarray and in situ hybridization (ISH) approaches. The Allen Human Brain Atlas allows researchers to see where a gene is turned on. "The location of where these genes are active is at the very center of understanding how brain diseases work", neurologist Jeffrey L. Noebels told The Wall Street Journal in April 2011. The Allen Human Brain Atlas was profiled in the journal Nature on September 19, 2012.

Allen Mouse Brain Connectivity Atlas

The Allen Mouse Brain Connectivity Atlas was launched online on November 3, 2011, and moved the Allen Institute's mapping efforts beyond its historical focus on gene expression toward neural circuitry. The atlas is a three-dimensional, high-resolution map of neural connections throughout the mouse brain, designed to help scientists understand how the brain is wired, offering new insights into how the brain works and what goes awry in brain diseases and disorders.

Allen Cell Types Database

Launched in 2015, the Allen Cell Types Database is a new tool to help scientists understand the building blocks of the brain and a major step toward creating a comprehensive map of the brain. The database will help create a common language for researchers around the world to use in observing, measuring and ultimately sorting cells into types much like the periodic table sorts elements. The first release of data includes information on more than 240 cells in the mouse brain. In 2017, the Allen Institute added data from human brain cells to the database.

Allen Brain Observatory

The Allen Brain Observatory was launched in 2016 to capture cellular-level activity of neurons in the mouse visual cortex. Experiments through the observatory use visual or electrical readouts of neural activity as animals see visual stimuli, ranging from natural images to black and white grid lines to a clip from the Orson Welles film noir, Touch of Evil. In 2018, the institute opened the observatory for research projects proposed by scientists from the broader community through a program called OpenScope, which was modeled after large-scale shared physics observatories such as the Hubble Space Telescope.

Other online resources

In addition to the atlas resources, the Allen Institute has generated several other online research tools, including:

• The Ivy Glioblastoma Atlas Project (Ivy GAP), a platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels.
• The BrainSpan Atlas of the Developing Human Brain, a resource for studying human brain development developed by a consortium of scientific partners and funded by awards from the National Institutes of Health.

Awards

• Forbes – 30 Under 30 Rising Stars Transforming Science and Health to Allen Institute scientist Adrian Cheng (2012)
• Cajal Club – Krieg Lifetime Achievement Award to Paul Allen for extraordinary contributions in neuroscience through his work with the Allen Institute (2010)
• American Academy of Neurology – Public Leadership in Neurology Award to Paul Allen for his strong commitment to brain research and work with the Allen Institute (2009)
• Time – "Top 100 Most Influential People in the World" to Paul Allen for his successful achievements at the Allen Institute (2007, 2008)
• Time – "Top Ten Medical Breakthroughs" (2006)
• Wired – Rave Award to Paul Allen and the Allen Institute for the completion of the Allen Mouse Brain Atlas (2007)
• Society for Neuroscience – Special Recognition Award to Paul Allen for his generous contributions to neuroscience through his work with the Allen Institute (2007)
• USA Weekend – "Top 10 Medical Breakthroughs of the Year" for the Allen Mouse Brain Atlas (2006)

OpenAI

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/OpenAI 

OpenAI

Headquarters at the Pioneer Building in San Francisco
Industry	Artificial intelligence
Founded	December 11, 2015
Founders	Sam Altman Trevor Blackwell Greg Brockman Vicki Cheung Reid Hoffman Andrej Karpathy Durk Kingma Jessica Livingston Elon Musk John Schulman Ilya Sutskever Peter Thiel Pamela Vagata Wojciech Zaremba
Headquarters	Pioneer Building, San Francisco, California, US
Key people	Greg Brockman (chairman & president) Sam Altman (CEO) Ilya Sutskever (chief scientist)
Products	DALL-E GPT-3 OpenAI Five ChatGPT OpenAI Codex
Number of employees	375 (as of 2023)
Website	openai.com

OpenAI is an American artificial intelligence (AI) research laboratory consisting of the non-profit OpenAI Incorporated (OpenAI Inc.) and its for-profit subsidiary corporation OpenAI Limited Partnership (OpenAI LP). OpenAI conducts AI research to promote and develop friendly AI in a way that benefits all humanity. The organization was founded in San Francisco in 2015 by Elon Musk, Sam Altman, Peter Thiel, Reid Hoffman, Jessica Livingston and others, who collectively pledged US$1 billion. Musk resigned from the board in 2018 but remained a donor. Microsoft provided OpenAI LP a $1 billion investment in 2019 and a second multi-year investment in January 2023 reported to be $10 billion.

History

In December 2015, Sam Altman, Elon Musk, Greg Brockman, Reid Hoffman, Jessica Livingston, Peter Thiel, Amazon Web Services (AWS), Infosys, and YC Research announced the formation of OpenAI and pledged over US$1 billion to the venture. The organization stated it would "freely collaborate" with other institutions and researchers by making its patents and research open to the public. OpenAI is headquartered at the Pioneer Building in Mission District, San Francisco.

In April 2016, OpenAI released a public beta of "OpenAI Gym", its platform for reinforcement learning research. In December 2016, OpenAI released "Universe", a software platform for measuring and training an AI's general intelligence across the world's supply of games, websites, and other applications.

In 2018, Musk resigned his board seat, citing "a potential future conflict (of interest)" with Tesla AI development for self driving cars, but remained a donor.

In 2019, OpenAI transitioned from non-profit to "capped" for-profit, with profit cap set to 100X on any investment. The company distributed equity to its employees and partnered with Microsoft and Matthew Brown Companies, who announced an investment package of $1 billion into the company. OpenAI then announced its intention to commercially license its technologies.

In 2020, OpenAI announced GPT-3, a language model trained on large datasets from the Internet. It also announced that an associated API, named simply "the API", would form the heart of its first commercial product. GPT-3 is aimed at natural language answering of questions, but it can also translate between languages and coherently generate improvised text.

In 2021, OpenAI introduced DALL-E, a deep learning model that can generate digital images from natural language descriptions.

Around December 2022, OpenAI received widespread media coverage after launching a free preview of ChatGPT, its new AI chatbot based on GPT-3.5. According to OpenAI, the preview received over a million signups within the first five days. According to anonymous sources cited by Reuters in December 2022, OpenAI was projecting a $200 million revenue for 2023 and $1 billion revenue for 2024.

As of January 2023, OpenAI was in talks for funding that would value the company at $29 billion, double the value of the company in 2021. On January 23, 2023, Microsoft announced a new multi-year, multi-billion dollar (reported to be $10 billion) investment in OpenAI.

Participants

Key employees:

• CEO and co-founder: Sam Altman, former president of the startup accelerator Y Combinator
• President and co-founder: Greg Brockman, former CTO, 3rd employee of Stripe
• Chief Scientist and co-founder: Ilya Sutskever, a former Google expert on machine learning
• Chief Technology Officer: Mira Murati, previously at Leap Motion and Tesla, Inc.
• Chief Operating Officer: Brad Lightcap, previously at Y Combinator and JPMorgan Chase

Board of the OpenAI nonprofit:

• Greg Brockman
• Ilya Sutskever
• Sam Altman
• Adam D'Angelo
• Reid Hoffman
• Will Hurd
• Tasha McCauley
• Helen Toner
• Shivon Zilis

Other backers of the project include:

• Reid Hoffman, LinkedIn co-founder
• Peter Thiel, PayPal co-founder
• Jessica Livingston, a founding partner of Y Combinator

Companies:

• Microsoft
• Khosla Ventures
• Infosys

The group started in early January 2016 with nine researchers. According to Wired, Brockman met with Yoshua Bengio, one of the "founding fathers" of the deep learning movement, and drew up a list of the "best researchers in the field". Microsoft's Peter Lee stated that the cost of a top AI researcher exceeds the cost of a top NFL quarterback prospect. While OpenAI pays corporate-level (rather than nonprofit-level) salaries, it doesn't currently pay AI researchers salaries comparable to those of Facebook or Google. Nevertheless, Sutskever stated that he was willing to leave Google for OpenAI "partly because of the very strong group of people and, to a very large extent, because of its mission." Brockman stated that "the best thing that I could imagine doing was moving humanity closer to building real AI in a safe way." OpenAI researcher Wojciech Zaremba stated that he turned down "borderline crazy" offers of two to three times his market value to join OpenAI instead.

Motives

Some scientists, such as Stephen Hawking and Stuart Russell, have articulated concerns that if advanced AI someday gains the ability to re-design itself at an ever-increasing rate, an unstoppable "intelligence explosion" could lead to human extinction. Musk characterizes AI as humanity's "biggest existential threat." OpenAI's founders structured it as a non-profit so that they could focus its research on making positive long-term contributions to humanity.

Musk and Altman have stated they are partly motivated by concerns about AI safety and the existential risk from artificial general intelligence. OpenAI states that "it's hard to fathom how much human-level AI could benefit society," and that it is equally difficult to comprehend "how much it could damage society if built or used incorrectly". Research on safety cannot safely be postponed: "because of AI's surprising history, it's hard to predict when human-level AI might come within reach." OpenAI states that AI "should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as possible...". Co-chair Sam Altman expects the decades-long project to surpass human intelligence.

Vishal Sikka, former CEO of Infosys, stated that an "openness" where the endeavor would "produce results generally in the greater interest of humanity" was a fundamental requirement for his support, and that OpenAI "aligns very nicely with our long-held values" and their "endeavor to do purposeful work". Cade Metz of Wired suggests that corporations such as Amazon may be motivated by a desire to use open-source software and data to level the playing field against corporations such as Google and Facebook that own enormous supplies of proprietary data. Altman states that Y Combinator companies will share their data with OpenAI.

In 2019, OpenAI became a for-profit company called OpenAI LP to secure additional funding while staying controlled by a non-profit called OpenAI Inc in a structure that OpenAI calls "capped-profit", having previously been a 501(c)(3) nonprofit organization.

Strategy

Musk posed the question: "What is the best thing we can do to ensure the future is good? We could sit on the sidelines or we can encourage regulatory oversight, or we could participate with the right structure with people who care deeply about developing AI in a way that is safe and is beneficial to humanity." Musk acknowledged that "there is always some risk that in actually trying to advance (friendly) AI we may create the thing we are concerned about"; nonetheless, the best defense is "to empower as many people as possible to have AI. If everyone has AI powers, then there's not any one person or a small set of individuals who can have AI superpower."

Musk and Altman's counter-intuitive strategy of trying to reduce the risk that AI will cause overall harm, by giving AI to everyone, is controversial among those who are concerned with existential risk from artificial intelligence. Philosopher Nick Bostrom is skeptical of Musk's approach: "If you have a button that could do bad things to the world, you don't want to give it to everyone." During a 2016 conversation about the technological singularity, Altman said that "we don't plan to release all of our source code" and mentioned a plan to "allow wide swaths of the world to elect representatives to a new governance board". Greg Brockman stated that "Our goal right now... is to do the best thing there is to do. It's a little vague."

Conversely, OpenAI's initial decision to withhold GPT-2 due to a wish to "err on the side of caution" in the presence of potential misuse, has been criticized by advocates of openness. Delip Rao, an expert in text generation, stated "I don't think [OpenAI] spent enough time proving [GPT-2] was actually dangerous." Other critics argued that open publication is necessary to replicate the research and to be able to come up with countermeasures.

In the 2017 tax year, OpenAI spent $7.9 million, or a quarter of its functional expenses, on cloud computing alone. In comparison, DeepMind's total expenses in 2017 were much larger, measuring $442 million. In Summer 2018, simply training OpenAI's Dota 2 bots required renting 128,000 CPUs and 256 GPUs from Google for multiple weeks. According to OpenAI, the capped-profit model adopted in March 2019 allows OpenAI LP to legally attract investment from venture funds, and in addition, to grant employees stakes in the company, the goal being that they can say "I'm going to Open AI, but in the long term it's not going to be disadvantageous to us as a family." Many top researchers work for Google Brain, DeepMind, or Facebook, which offer stock options that a nonprofit would be unable to. In June 2019, OpenAI LP raised a billion dollars from Microsoft, a sum which OpenAI plans to have spent "within five years, and possibly much faster". Altman has stated that even a billion dollars may turn out to be insufficient, and that the lab may ultimately need "more capital than any non-profit has ever raised" to achieve artificial general intelligence.

The transition from a nonprofit to a capped-profit company was viewed with skepticism by Oren Etzioni of the nonprofit Allen Institute for AI, who agreed that wooing top researchers to a nonprofit is difficult, but stated "I disagree with the notion that a nonprofit can't compete" and pointed to successful low-budget projects by OpenAI and others. "If bigger and better funded was always better, then IBM would still be number one." Following the transition, public disclosure of the compensation of top employees at OpenAI LP is no longer legally required. The nonprofit, OpenAI Inc., is the sole controlling shareholder of OpenAI LP. OpenAI LP, despite being a for-profit company, retains a formal fiduciary responsibility to OpenAI's Inc.'s nonprofit charter. A majority of OpenAI Inc.'s board is barred from having financial stakes in OpenAI LP. In addition, minority members with a stake in OpenAI LP are barred from certain votes due to conflict of interest. Some researchers have argued that OpenAI LP's switch to for-profit status is inconsistent with OpenAI's claims to be "democratizing" AI. A journalist at Vice News wrote that "generally, we've never been able to rely on venture capitalists to better humanity".

Products and applications

OpenAI's research tend to focus on reinforcement learning (RL). OpenAI is viewed as an important competitor to DeepMind.

Gym

Gym aims to provide an easy to set up, general-intelligence benchmark with a wide variety of different environments—somewhat akin to, but broader than, the ImageNet Large Scale Visual Recognition Challenge used in supervised learning research—and that hopes to standardize the way in which environments are defined in AI research publications, so that published research becomes more easily reproducible. The project claims to provide the user with a simple interface. As of June 2017, Gym can only be used with Python. As of September 2017, the Gym documentation site was not maintained, and active work focused instead on its GitHub page.

In "RoboSumo", virtual humanoid "metalearning" robots initially lack knowledge of how to even walk, and are given the goals of learning to move around, and pushing the opposing agent out of the ring. Through this adversarial learning process, the agents learn how to adapt to changing conditions; when an agent is then removed from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had learned how to balance in a generalized way. OpenAI's Igor Mordatch argues that competition between agents can create an intelligence "arms race" that can increase an agent's ability to function, even outside the context of the competition.

Debate Game

In 2018, OpenAI launched the Debate Game, which teaches machines to debate toy problems in front of a human judge. The purpose is to research whether such an approach may assist in auditing AI decisions and in developing explainable AI.

Dactyl

Dactyl uses machine learning to train a Shadow Hand, a human-like robot hand, to manipulate physical objects. It learns entirely in simulation using the same RL algorithms and training code as OpenAI Five. OpenAI tackled the object orientation problem by using domain randomization, a simulation approach which exposes the learner to a variety of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having motion tracking cameras, also has RGB cameras to allow the robot to manipulate an arbitrary object by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism.

In 2019, OpenAI demonstrated that Dactyl could solve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to model. OpenAI solved this by improving the robustness of Dactyl to perturbations; they employed a technique called Automatic Domain Randomization (ADR), a simulation approach where progressively more difficult environments are endlessly generated. ADR differs from manual domain randomization by not needing there to be a human to specify randomization ranges.

Generative models

GPT

The GPT model

The original paper on generative pre-training (GPT) of a language model was written by Alec Radford and his colleagues, and published in preprint on OpenAI's website on June 11, 2018. It showed how a generative model of language is able to acquire world knowledge and process long-range dependencies by pre-training on a diverse corpus with long stretches of contiguous text.

GPT-2

Main article: GPT-2

 

An instance of GPT-2 writing a paragraph based on a prompt from its own Wikipedia article in February 2021

Generative Pre-trained Transformer 2, commonly known by its abbreviated form GPT-2, is an unsupervised transformer language model and the successor to GPT. GPT-2 was first announced in February 2019, with only limited demonstrative versions initially released to the public. The full version of GPT-2 was not immediately released out of concern over potential misuse, including applications for writing fake news. Some experts expressed skepticism that GPT-2 posed a significant threat. The Allen Institute for Artificial Intelligence responded to GPT-2 with a tool to detect "neural fake news". Other researchers, such as Jeremy Howard, warned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". In November 2019, OpenAI released the complete version of the GPT-2 language model. Several websites host interactive demonstrations of different instances of GPT-2 and other transformer models.

GPT-2's authors argue unsupervised language models to be general-purpose learners, illustrated by GPT-2 achieving state-of-the-art accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further trained on any task-specific input-output examples). The corpus it was trained on, called WebText, contains slightly over 8 million documents for a total of 40 GB of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain issues encoding vocabulary with word tokens by using byte pair encoding. This allows to represent any string of characters by encoding both individual realse

characters and multiple-character tokens.

GPT-3

Main article: GPT-3

Generative Pre-trained Transformer 3, commonly known by its abbreviated form GPT-3, is an unsupervised transformer language model and the successor to GPT-2. It was first described in May 2020. OpenAI stated that full version of GPT-3 contains 175 billion parameters, two orders of magnitude larger than the 1.5 billion parameters in the full version of GPT-2 (although GPT-3 models with as few as 125 million parameters were also trained).

OpenAI stated that GPT-3 succeeds at certain "meta-learning" tasks. It can generalize the purpose of a single input-output pair. The paper gives an example of translation and cross-linguistic transfer learning between English and Romanian, and between English and German.

GPT-3 dramatically improved benchmark results over GPT-2. OpenAI cautioned that such scaling up of language models could be approaching or encountering the fundamental capability limitations of predictive language models. Pre-training GPT-3 required several thousand petaflop/s-days of compute, compared to tens of petaflop/s-days for the full GPT-2 model. Like that of its predecessor, GPT-3's fully trained model was not immediately released to the public on the grounds of possible abuse, though OpenAI planned to allow access through a paid cloud API after a two-month free private beta that began in June 2020.

On September 23, 2020, GPT-3 was licensed exclusively to Microsoft.

ChatGPT

Main article: ChatGPT

ChatGPT is an artificial intelligence tool that provides a conversational interface that allows you to ask questions in natural language. The system then responds with an answer within seconds. ChatGPT was launched in November 2022 and reached 1 million users only 5 days after its initial launch.

Music

OpenAI's MuseNet (2019) is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can generate songs with ten different instruments in fifteen different styles. According to The Verge, a song generated by MuseNet tends to start reasonably but then fall into chaos the longer it plays.

OpenAI's Jukebox (2020) is an open-sourced algorithm to generate music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs song samples. OpenAI stated the songs "show local musical coherence, follow traditional chord patterns" but acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" and that "there is a significant gap" between Jukebox and human-generated music. The Verge stated "It's technologically impressive, even if the results sound like mushy versions of songs that might feel familiar", while Business Insider stated "surprisingly, some of the resulting songs are catchy and sound legitimate".

Whisper

Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.

API

In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new AI models developed by OpenAI" to let developers call on it for "any English language AI task."

DALL-E and CLIP

Main article: DALL-E

 

Images produced by DALL-E when given the text prompt "a professional high-quality illustration of a giraffe dragon chimera. a giraffe imitating a dragon. a giraffe made of dragon."

DALL-E is a Transformer model that creates images from textual descriptions, revealed by OpenAI in January 2021.

CLIP does the opposite: it creates a description for a given image. DALL-E uses a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images. It can create images of realistic objects ("a stained-glass window with an image of a blue strawberry") as well as objects that do not exist in reality ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.

In March 2021, OpenAI released a paper titled Multimodal Neurons in Artificial Neural Networks, where they showed a detailed analysis of CLIP (and GPT) models and their vulnerabilities. The new type of attacks on such models was described in this work.

We refer to these attacks as typographic attacks. We believe attacks such as those described above are far from simply an academic concern. By exploiting the model's ability to read text robustly, we find that even photographs of hand-written text can often fool the model.

— Multimodal Neurons in Artificial Neural Networks, OpenAI

In April 2022, OpenAI announced DALL-E 2, an updated version of the model with more realistic results. In December 2022, OpenAI published on GitHub software for Point-E, a new rudimentary system for converting a text description into a 3-dimensional model.

Microscope

OpenAI Microscope is a collection of visualizations of every significant layer and neuron of eight different neural network models which are often studied in interpretability. Microscope was created to analyze the features that form inside these neural networks easily. The models included are AlexNet, VGG 19, different versions of Inception, and different versions of CLIP Resnet.

Codex

Main article: OpenAI Codex

OpenAI Codex is a descendant of GPT-3 that has additionally been trained on code from 54 million GitHub repositories. It was announced in mid-2021 as the AI powering the code autocompletion tool GitHub Copilot. In August 2021, an API was released in private beta. According to OpenAI, the model is able to create working code in over a dozen programming languages, most effectively in Python.

Several issues with glitches, design flaws, and security vulnerabilities have been brought up.

Video game bots and benchmarks

OpenAI Five

Main article: OpenAI Five

OpenAI Five is the name of a team of five OpenAI-curated bots that are used in the competitive five-on-five video game Dota 2, who learn to play against human players at a high skill level entirely through trial-and-error algorithms. Before becoming a team of five, the first public demonstration occurred at The International 2017, the annual premiere championship tournament for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live 1v1 matchup. After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for two weeks of real time, and that the learning software was a step in the direction of creating software that can handle complex tasks like a surgeon. The system uses a form of reinforcement learning, as the bots learn over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives.

By June 2018, the ability of the bots expanded to play together as a full team of five, and they were able to defeat teams of amateur and semi-professional players. At The International 2018, OpenAI Five played in two exhibition matches against professional players, but ended up losing both games. In April 2019, OpenAI Five defeated OG, the reigning world champions of the game at the time, 2:0 in a live exhibition match in San Francisco. The bots' final public appearance came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games.

GYM Retro

Gym Retro is a platform for RL research on video games. Gym Retro is used to research RL algorithms and study generalization. Prior research in RL has focused chiefly on optimizing agents to solve single tasks. Gym Retro gives the ability to generalize between games with similar concepts but different appearances.