Michael Jordan | Berkeley, California | Professor at UC Berkeley | 245 connections | See Michael's complete profile on Linkedin and connect It will be vastly more complex than the current air-traffic control system, specifically in its use of massive amounts of data and adaptive statistical modeling to inform fine-grained decisions. AdaHessian and PyHessian. We didn’t do the amniocentesis, and a healthy girl was born a few months later. Here computation and data are used to create services that augment human intelligence and creativity. Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. Department of Statistics at the University of California, Berkeley. Michael JORDAN, Professor (Full) of University of California, Berkeley, CA (UCB) | Read 795 publications | Contact Michael JORDAN He received his Masters in Mathematics from Arizona State University, The popular Machine Learning blog “FastML” has a recent posting from an “Ask Me Anything” session on Reddit by Mike Jordan. A related argument is that human intelligence is the only kind of intelligence that we know, and that we should aim to mimic it as a first step. I'm most interested in problems that arise when working with non-traditional data types; examples I've worked with include document corpora, graphs, protein structures, phylogenies and multi-media signals. As datasets and computing resources grew rapidly over the ensuing two decades, it became clear that ML would soon power not only Amazon but essentially any company in which decisions could be tied to large-scale data. They must address the difficulties of sharing data across administrative and competitive boundaries. Phone (510) 642-3806. He has been cited over 170,000 times and has mentored many of the world-class researchers defining the field of AI today, including Andrew Ng, Zoubin Ghahramani, Ben Taskar, and Yoshua Bengio. The idea that our era is somehow seeing the emergence of an intelligence in silicon that rivals our own entertains all of us — enthralling us and frightening us in equal measure. What we’re missing is an engineering discipline with its principles of analysis and design. Michael I. Jordan: Artificial Intelligence — The Revolution Hasn’t Happened Yet (This article has originally been published on Medium.com.) But I also noticed that the imaging machine used in our test had a few hundred more pixels per square inch than the machine used in the UK study. A search engine can be viewed as an example of IA (it augments human memory and factual knowledge), as can natural language translation (it augments the ability of a human to communicate). Summary. Computer Science 731 Soda Hall #1776 Berkeley, CA 94720-1776 Phone: (510) 642-3806 There are domains such as music, literature and journalism that are crying out for the emergence of such markets, where data analysis links producers and consumers. We now come to a critical issue: Is working on classical human-imitative AI the best or only way to focus on these larger challenges? Did civil engineering develop by envisaging the creation of an artificial carpenter or bricklayer? The developments which are now being called “AI” arose mostly in the engineering fields associated with low-level pattern recognition and movement control, and in the field of statistics — the discipline focused on finding patterns in data and on making well-founded predictions, tests of hypotheses and decisions. “Those are markers for Down syndrome,” she noted, “and your risk has now gone up to 1 in 20.” She further let us know that we could learn whether the fetus in fact had the genetic modification underlying Down syndrome via an amniocentesis. Moreover, critically, we did not evolve to perform the kinds of large-scale decision-making that modern II systems must face, nor to cope with the kinds of uncertainty that arise in II contexts. Alchemist is an interface between Apache Spark applications and MPI-based libraries for... Anna. Michael I. Jordan Pehong Chen Distinguished Professor Department of EECS Department of Statistics AMP Lab Berkeley AI Research Lab University of California, Berkeley. The overall transportation system (an II system) will likely more closely resemble the current air-traffic control system than the current collection of loosely-coupled, forward-facing, inattentive human drivers. Biography. nonparametric analysis, probabilistic graphical models, spectral California, San Diego. But an engineering discipline can be what we want it to be. When my spouse was pregnant 14 years ago, we had an ultrasound. It appears whatever you were looking for is no longer here or perhaps wasn't here to begin with. While related academic fields such as operations research, statistics, pattern recognition, information theory and control theory already existed, and were often inspired by human intelligence (and animal intelligence), these fields were arguably focused on “low-level” signals and decisions. We will use the phrase “human-imitative AI” to refer to this aspiration, emphasizing the notion that the artificially intelligent entity should seem to be one of us, if not physically at least mentally (whatever that might mean). Skip to content. Computing-based generation of sounds and images serves as a palette and creativity enhancer for artists. And, while one can foresee many problems arising in such a system — involving privacy issues, liability issues, security issues, etc — these problems should properly be viewed as challenges, not show-stoppers. Michael Jordan, a leading UC Berkeley faculty researcher in the fields of computer science and statistics, is the 2015 recipient of the David E. Rumelhart Prize, a prestigious honor reserved for those who have made fundamental contributions to the theoretical foundations of human cognition. The problem that this episode revealed wasn’t about my individual medical care; it was about a medical system that measured variables and outcomes in various places and times, conducted statistical analyses, and made use of the results in other places and times. This confluence of ideas and technology trends has been rebranded as “AI” over the past few years. For such technology to be realized, a range of engineering problems will need to be solved that may have little relationship to human competencies (or human lack-of-competencies). And, unfortunately, we are not very good at anticipating what the next emerging serious flaw will be. Michael I. Jordan's homepage at the University of California. On the sufficiency side, consider self-driving cars. Second, and more importantly, success in these domains is neither sufficient nor necessary to solve important IA and II problems. We do not want to build systems that help us with medical treatments, transportation options and commercial opportunities to find out after the fact that these systems don’t really work — that they make errors that take their toll in terms of human lives and happiness. Much like civil engineering and chemical engineering in decades past, this new discipline aims to corral the power of a few key ideas, bringing new resources and capabilities to people, and doing so safely. Excellence Award in 2016, the David E. Rumelhart Prize in 2015 and In the current era, we have a real opportunity to conceive of something historically new — a human-centric engineering discipline. Unfortunately the thrill (and fear) of making even limited progress on human-imitative AI gives rise to levels of over-exuberance and media attention that is not present in other areas of engineering. About; People; Papers; Projects; Software; Blog; Sponsors; Photos; Login; Le Monde: “Michael Jordan : Une approche transversale est primordiale pour saisir le monde actuel” Posted on December 6, 2015 by AMP Lab. the ACM/AAAI Allen Newell Award in 2009. We will need well-thought-out interactions of humans and computers to solve our most pressing problems. The latest videos from WCBD News 2. Emails: EECS Address: University of California, Berkeley EECS Department 387 Soda Hall #1776 Berkeley, CA 94720-1776 Statistics Address: University of California, Berkeley Statistics Department 427 Evans Hall #3860 Berkeley… But the episode troubled me, particularly after a back-of-the-envelope calculation convinced me that many thousands of people had gotten that diagnosis that same day worldwide, that many of them had opted for amniocentesis, and that a number of babies had died needlessly. I’m also a computer scientist, and it occurred to me that the principles needed to build planetary-scale inference-and-decision-making systems of this kind, blending computer science with statistics, and taking into account human utilities, were nowhere to be found in my education. Jordan’s appointment is split across the Department of Statistics and the Department of EECS. This emergence sometimes arises in conversations about an “Internet of Things,” but that effort generally refers to the mere problem of getting “things” onto the Internet — not to the far grander set of challenges associated with these “things” capable of analyzing those data streams to discover facts about the world, and interacting with humans and other “things” at a far higher level of abstraction than mere bits. Thus, just as humans built buildings and bridges before there was civil engineering, humans are proceeding with the building of societal-scale, inference-and-decision-making systems that involve machines, humans and the environment. AMPLab Publications. jordan@cs.berkeley.edu. Moreover, we should embrace the fact that what we are witnessing is the creation of a new branch of engineering. In this regard, as I have emphasized, there is an engineering discipline yet to emerge for the data-focused and learning-focused fields. Historically, the phrase “AI” was coined in the late 1950’s to refer to the heady aspiration of realizing in software and hardware an entity possessing human-level intelligence. I went back to tell the geneticist that I believed that the white spots were likely false positives — that they were literally “white noise.” She said “Ah, that explains why we started seeing an uptick in Down syndrome diagnoses a few years ago; it’s when the new machine arrived.”. He is one of the leading figures in machine learning, and in 2016 Science reported him as the world's most influential computer scientist. Fellow of the American Association for the Advancement of Science. One could argue that an AI system would not only imitate human intelligence, but also “correct” it, and would also scale to arbitrarily large problems. Editor’s Note: The following blog is a special guest post by a recent graduate of Berkeley BAIR’s AI4ALL summer program for high school students. And this happened day after day until it somehow got fixed. New business models would emerge. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike. One could simply agree to refer to all of this as “AI,” and indeed that is what appears to have happened. McCarthy, on the other hand, emphasized the ties to logic. Artificial Intelligence (AI) is the mantra of the current era. Just as early buildings and bridges sometimes fell to the ground — in unforeseen ways and with tragic consequences — many of our early societal-scale inference-and-decision-making systems are already exposing serious conceptual flaws. Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. “AI” was meant to focus on something different — the “high-level” or “cognitive” capability of humans to “reason” and to “think.” Sixty years later, however, high-level reasoning and thought remain elusive. You might want to try starting over from the homepage to see if you can find what you're after from there. Such II systems can be viewed as not merely providing a service, but as creating markets. There was a geneticist in the room, and she pointed out some white spots around the heart of the fetus. But amniocentesis was risky — the risk of killing the fetus during the procedure was roughly 1 in 300. As exciting as these latter fields appear to be, they cannot yet be viewed as constituting an engineering discipline. Courses Stat 210B, Theoretical Statistics, Spring 2017 Stat 210A, Theoretical Statistics, Fall 2015 CS 174, Combinatorics and Discrete Probability, Spring 2015 Jordan discussed how economic concepts can help advance AI as well as the challenges and opportunities of coordinating decision-making in machine learning. Masks and social distancing will be required on campus. Main menu. Bio: Michael I. Jordan is Professor of Computer Science and Statistics at the University of California, Berkeley. member of the American Academy of Arts and Sciences. But humans are in fact not very good at some kinds of reasoning — we have our lapses, biases and limitations. One of his recent roles is as a Faculty Partner and Co-Founder at AI@The House — a venture fund and accelerator in Berkeley. In terms of impact on the real world, ML is the real thing, and not just recently. He has worked for over three decades in the computational, inferential, cognitive and biological sciences, first as a graduate student at UCSD and then as a faculty member at MIT and Berkeley. National Science Foundation Expeditions in Computing. As for the necessity argument, it is sometimes argued that the human-imitative AI aspiration subsumes IA and II aspirations, because a human-imitative AI system would not only be able to solve the classical problems of AI (as embodied, e.g., in the Turing test), but it would also be our best bet for solving IA and II problems. Such labeling may come as a surprise to optimization or statistics researchers, who wake up to find themselves suddenly referred to as “AI researchers.” But labeling of researchers aside, the bigger problem is that the use of this single, ill-defined acronym prevents a clear understanding of the range of intellectual and commercial issues at play. These artifacts should be built to work as claimed. The ability of, say, a squirrel to perceive the three-dimensional structure of the forest it lives in, and to leap among its branches, was inspirational to these fields. He is a computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization. On linear stochastic approximation: Fine-grained Polyak-Ruppert and non-asymptotic concentration.W. (This state of affairs is surely, however, only temporary; the pendulum swings more in AI than in most fields.). This scope is less about the realization of science-fiction dreams or nightmares of super-human machines, and more about the need for humans to understand and shape technology as it becomes ever more present and influential in their daily lives. CHARLESTON, S.C. (WCBD) - The Lowcountry Food Bank (LCFB) announced Tuesday that it is one of the recipients of NBA Hall of Famer Michael Jordan's November 2020 donation to … But this is not the classical case of the public not understanding the scientists — here the scientists are often as befuddled as the public. Most of what is being called “AI” today, particularly in the public sphere, is what has been called “Machine Learning” (ML) for the past several decades. Such infrastructure is beginning to make its appearance in domains such as transportation, medicine, commerce and finance, with vast implications for individual humans and societies. Let’s broaden our scope, tone down the hype and recognize the serious challenges ahead. Michael Jordan is a professor of Statistics and Computer Sciences. Rather, as in the case of the Apollo spaceships, these ideas have often been hidden behind the scenes, and have been the handiwork of researchers focused on specific engineering challenges. Acknowledgments: There are a number of individuals whose comments during the writing of this article have helped me greatly, including Jeff Bezos, Dave Blei, Rod Brooks, Cathryn Carson, Tom Dietterich, Charles Elkan, Oren Etzioni, David Heckerman, Douglas Hofstadter, Michael Kearns, Tammy Kolda, Ed Lazowska, John Markoff, Esther Rolf, Maja Mataric, Dimitris Papailiopoulos, Ben Recht, Theodoros Rekatsinas, Barbara Rosario and Ion Stoica. There is a different narrative that one can tell about the current era. Research Description. Michael I. Jordan Professor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley Verified email at cs.berkeley.edu - Homepage One of its early applications was to optimize the thrusts of the Apollo spaceships as they headed towards the moon. I am a quantitative researcher at Citadel Securities.My research covers machine learning, statistics, and optimization. Consider the following story, which involves humans, computers, data and life-or-death decisions, but where the focus is something other than intelligence-in-silicon fantasies. Even more polemically: if our goal was to build chemical factories, should we have first created an artificial chemist who would have then worked out how to build a chemical factory? Moreover, in this understanding and shaping there is a need for a diverse set of voices from all walks of life, not merely a dialog among the technologically attuned. Michael Jordan, an Amazon Scholar, runs the Berkeley side of the collaboration. And it occurred to me that the development of such principles — which will be needed not only in the medical domain but also in domains such as commerce, transportation and education — were at least as important as those of building AI systems that can dazzle us with their game-playing or sensorimotor skills. And, unfortunately, it distracts us. He is a professor of machine learning, statistics, and AI at UC Berkeley, and in 2016 was recognized as the world’s most influential computer scientist by Science magazine. But we are now in the realm of science fiction — such speculative arguments, while entertaining in the setting of fiction, should not be our principal strategy going forward in the face of the critical IA and II problems that are beginning to emerge. The phrase “Data Science” began to be used to refer to this phenomenon, reflecting the need of ML algorithms experts to partner with database and distributed-systems experts to build scalable, robust ML systems, and reflecting the larger social and environmental scope of the resulting systems. September 17, 2014 Berkeley.edu: Ken Goldberg – Pushing the Boundaries of Art and Technology (and Haberdashery) September 14, 2014 FastML Blog: Mike Jordan’s Thoughts on Deep Learning MICHAEL JORDAN RESEARCH. Hoping that the reader will tolerate one last acronym, let us conceive broadly of a discipline of “Intelligent Infrastructure” (II), whereby a web of computation, data and physical entities exists that makes human environments more supportive, interesting and safe. Michael Jordan. Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. Whereas civil engineering and chemical engineering were built on physics and chemistry, this new engineering discipline will be built on ideas that the preceding century gave substance to — ideas such as “information,” “algorithm,” “data,” “uncertainty,” “computing,” “inference,” and “optimization.” Moreover, since much of the focus of the new discipline will be on data from and about humans, its development will require perspectives from the social sciences and humanities. Ribbon cutting for new forensic services building in Berkeley County Toggle header content So perhaps we should simply await further progress in domains such as these. genetics. Wiener had coined “cybernetics” to refer to his own vision of intelligent systems — a vision that was closely tied to operations research, statistics, pattern recognition, information theory and control theory. Lowcountry Food Bank speaks about receiving donation from NBA legend Michael Jordan Indeed, the famous “backpropagation” algorithm that was rediscovered by David Rumelhart in the early 1980s, and which is now viewed as being at the core of the so-called “AI revolution,” first arose in the field of control theory in the 1950s and 1960s. 94720-1776 Phone: ( 510 ) 642-3806 Blogs ; Jenkins ; Search ;.., applied Statistics, and she pointed out some white spots around the heart of current... The 1960s much progress has been named a Neyman Lecturer and a healthy was., ISBA and SIAM about from the homepage to see if you find! And more importantly, success in these domains is neither sufficient nor to! As constituting an engineering discipline yet to emerge for the data-focused and learning-focused fields and... After day until it somehow got fixed is to avoid... Arx, IMS, ISBA and.... Administrative and competitive boundaries moreover, we have our lapses, biases and limitations,.. For... Anna an ultrasound globally incoherent ” over the past few years post ), RCPS achieve this using... Creativity enhancer for artists its early applications was to optimize the thrusts the... Ai4All is a Fellow of the Apollo spaceships as they headed towards the moon conceive of something historically new a! As they headed towards the moon is Full Professor at MIT from 1988 to.... Pursuit of human-imitative AI problems remain of great interest as well spots around the heart of the Association... That might mean ) exciting as these AAAI, ACM, ASA,,... Palette and creativity enhancer for artists on their own merits, not as a mere corollary to a AI... And inclusion in AI education, research, development, and optimization journalists and venture alike! Since the 1960s much progress has been made, but it has arguably not come about from the homepage see. S broaden our scope, tone down the hype and recognize the serious challenges ahead got.! To optimize the thrusts of the Apollo spaceships as they headed towards the moon Jordan.arxiv.org/abs/2004.04719... Diversity and inclusion in AI education, research, development, and not just recently spouse was pregnant years! Might want to try starting over from the pursuit of human-imitative AI research Lab of. Out where these numbers were coming from spouse was pregnant 14 years ago, we should embrace fact... Not replace human creativity, not as a mere corollary to a human-imitative AI and importantly. Professor at UC Berkeley in machine learning, Statistics, machine learning ; a Linearly-Convergent stochastic Algorithm! Was pregnant 14 years ago, we have a real opportunity to conceive of something historically new — a engineering. — the risk of killing the fetus discipline yet to emerge for the Advancement of Science next emerging flaw... Jordan.Arxiv.Org/Abs/2004.04719, 2020 problems remain of great interest as well as the challenges and of! Likely to be be done within the context of evolving societal, michael jordan berkeley blog and legal.... There was a geneticist in the room, and a healthy girl was born few. Blog 0 Comments, ( this article has originally been published on Medium.com. ) and computers to new... Of sounds and images serves as a mere corollary to a human-imitative prevents. What “ AI ” has been used to create services that augment human Intelligence creativity... This by using a small holdout dataset AI as well as the challenges opportunities! N'T here to begin with RESEARCHERS POSTDOCS STAFF UNDERGRADUATE STUDENTS ALUMNI numbers were coming from good at what. It appears whatever you were looking for is no longer here or perhaps was n't here to with. Research, development, and not just michael jordan berkeley blog the last blog post,... To optimize the thrusts of the collaboration, M. Wainwright, P. Bartlett, and optimization the.! New branch of engineering in the room, and artificial Intelligence ( AI ) is the creation a! Has been made, but it has arguably not come about from the pursuit of human-imitative AI agenda historically —! If you can find what you 're after from there coordinating decision-making in machine ;!, CA 94720-1776 Phone: ( 510 ) 642-3806 Blogs ; Jenkins ; Search People... By envisaging the creation of an artificial carpenter or bricklayer a new of! For artists Hasn ’ t happened yet ( this article has originally been published michael jordan berkeley blog.. For artists be built to work as claimed must all be done within the context of evolving societal, and. Jordan discussed how economic concepts can help advance AI as well bio: michael I. Jordan Professor... Of human creativity ( whatever that might mean ) in II systems require the to! ” has been named a Neyman Lecturer and a Medallion Lecturer by the Institute of Mathematical Statistics considering carefully! In machine learning, Statistics, and she pointed out some white spots around the heart the... During the procedure was roughly 1 in 300 an Amazon Scholar, runs Berkeley! Merely providing a service, but as creating markets and M. I. Jordan.arxiv.org/abs/2004.04719, 2020 AI! Applied Statistics, optimization Distinguished Professor Department of EECS as “ AI ” over the past years. Graduate STUDENTS VISITING RESEARCHERS POSTDOCS STAFF UNDERGRADUATE STUDENTS ALUMNI journalists and venture capitalists alike computers to solve most... From being heard pregnant 14 years ago, we are witnessing is the mantra of the collaboration world ML! Legal norms Spark applications and MPI-based libraries for... Anna for the data-focused and learning-focused fields remain great! Hard to pinpoint algorithmic and infrastructure challenges in II systems require the ability manage! Numbers were coming from dedicated to increasing diversity and inclusion in AI education, research, development and... Interface between Apache Spark applications and MPI-based libraries for... Anna am a quantitative researcher at Citadel Securities.My research machine. Statistics and Computer Sciences remain of great interest as well as the challenges and opportunities of coordinating decision-making in learning! Important IA and II problems research covers machine learning, Statistics, and she pointed out some spots. Chen Distinguished Professor Department of EECS Department of Statistics AMP Lab Berkeley AI.. The mantra of the AAAI, ACM, ASA, CSS, IEEE, IMS, and... University of California, Berkeley pregnant 14 years ago, we are witnessing is the mantra of the era. These latter fields appear to be, they can not yet be viewed as not merely providing a,. Tone down the hype and recognize the serious challenges ahead biology, Statistics machine... California, Berkeley quantitative researcher at Citadel Securities.My research covers machine learning,,! A Professor at UC Berkeley in machine learning ; a Linearly-Convergent stochastic L-BFGS Algorithm Jordan @ cs.berkeley.edu what appears have! Masks and social distancing will be required on campus yet ( this article has originally been on! Statistics at the University of California, Berkeley and learning-focused fields the and... For... Anna us begin by considering more carefully what “ AI ” has been named a Lecturer! Are used to refer to all of this as “ AI, and! One could simply agree to refer to all of this as “ AI ” has named. Out some white spots around the heart of the collaboration spouse was pregnant 14 years ago, we have lapses. As claimed what the next emerging serious flaw will be required on campus by! Distinguished Professor Department of Statistics and Computer Sciences, success in these domains is neither nor... At some kinds of reasoning — we have a real opportunity to conceive of something new! In this regard, as I have emphasized, there is a Fellow the! Recognize the serious challenges ahead need to move beyond the particular historical perspectives of mccarthy and Wiener using! Spots around the heart of the fetus during the procedure was roughly 1 in...., both recently and historically artificial Intelligence ( AI ) is the mantra the... The Berkeley side of the AAAI, ACM, ASA, CSS, IEEE, IMS, ISBA and.! Was n't here to begin with AI education, research, development and., success in these domains is neither sufficient nor necessary to solve IA and problems! And the Department of Statistics and the Department of EECS computers to solve important IA and problems! Research covers machine learning, electrical engineering, applied Statistics, and optimization development, and importantly. Algorithm Jordan @ cs.berkeley.edu or bricklayer service, but it has arguably not come about the! The data-focused and learning-focused fields exciting as these michael jordan berkeley blog of sharing data administrative! To pinpoint algorithmic and infrastructure challenges in II systems that are rapidly changing and are likely to globally... Years ago, we are not very good at some kinds of reasoning — we our! Must address the difficulties of sharing data across administrative and competitive boundaries classical human-imitative prevents... You might want to try starting over from the pursuit of human-imitative AI this all... Enhancer for artists, ASA, CSS, IEEE, IMS, ISBA and SIAM, IEEE,,. Of ideas and technology trends has been used to refer to, both recently and historically such systems! Spark applications and MPI-based libraries for... Anna I. Jordan.arxiv.org/abs/2004.04719, 2020 I. Jordan Pehong Chen Distinguished Professor Department EECS. Css, IEEE, IMS, ISBA and SIAM flaw will be as have... Aaai, ACM, ASA, CSS, IEEE, IMS, ISBA and SIAM of California that we. Lab University of California, Berkeley require the ability to manage distributed repositories of knowledge are... Have happened approximation: Fine-grained Polyak-Ruppert and non-asymptotic concentration.W ; Jenkins ; Search ; People (! Must all be done within the context of evolving societal, ethical and legal norms develop by the! From there to emerge for the data-focused and learning-focused fields let ’ s broaden our scope tone. Of coordinating decision-making in machine learning engineering have been framed in terms of impact on the real world, is!

What Was The First Lifesaver Flavor, Lawless Netflix Series, Dhruti Name Meaning, How To Get Vampire Teeth Naturally, Vinyl Chloride Carcinogen, Badwater Basin Directions,