{"id":2490,"date":"2020-08-30T20:16:10","date_gmt":"2020-08-30T20:16:10","guid":{"rendered":"https:\/\/techclot.com\/index.php\/2020\/08\/30\/ai-a-long-and-winding-road\/"},"modified":"2020-08-30T20:16:10","modified_gmt":"2020-08-30T20:16:10","slug":"ai-a-long-and-winding-road","status":"publish","type":"post","link":"https:\/\/techclot.com\/index.php\/2020\/08\/30\/ai-a-long-and-winding-road\/","title":{"rendered":"AI: a long and winding road"},"content":{"rendered":"

AI: a long and winding road<\/a><\/p>\n

<\/div>\n
<\/p>\n
<\/ins><\/div>\n<\/div>\n
\n

Irina Rish<\/a> was 14 years old and going to high school in the central Asian city of Samarkand, Uzbekistan, when she first came across the notion of artificial intelligence.<\/p>\n

\u201cI saw a book, translated from English into Russian, the cover was black with yellow letters, and the title was \u2018Can Machines Think?’\u201d Rish said, recalling her time as a student in the ex-Soviet Union.<\/p>\n

Competing at the time in a Soviet Student Olympiad<\/a> in math, Rish was intrigued.<\/p>\n

\u201cThe book was about AI, and I said to myself: \u2018Gosh, that\u2019s exactly what I was wondering: what algorithms can we design to solve difficult problems, and how can we boost our own \u2018natural intelligence,’\u201d she recalled.<\/p>\n

\u201cI didn\u2019t just think it\u2019d be cool to teach computers to solve problems \u2013 in other words, AI. I also wanted to know how to improve my brain, augment my intelligence, so that my next time at the Math Olympiad, I\u2019d do better.\u201d<\/p>\n

That was in 1983, and since then Rish has made that dual quest her life work. Graduating from university studies \u2013 first in Moscow, then in California \u2013 to a 20-year career with IBM in New York, last October, she moved to Canada to become an associate professor at Universit\u00e9 de Montr\u00e9al and a core faculty member at its affiliated AI institute, the world-renowned Mila.<\/p>\n

<\/ins><\/p>\n

With her move came a major honour: already holder of a Canada CIFAR AI Chair,<\/a> this summer Rish was awarded an even more prestigious Canada Excellence Research Chair <\/a>(CERC). It comes with $34 million in financing over seven years: $10 million from the federal government, $4.4 million from UdeM, and $20 million from other sources.<\/p>\n

Rish\u2019s application for the grant was supported by a wide variety of institutions (Mila, HEC Montr\u00e9al, Polytechnique Montr\u00e9al, McGill University, Calcul Qu\u00e9bec, the Quebec Ministry of Economy and innovation) and industry players (Imagia, Element AI, Samsung, IBM, Microsoft and Druide). \u201cIt\u2019s a wonderful opportunity for me and my team at Mila,\u201d Rish said.<\/p>\n

\n

\u2018Broad and robust AI\u2019<\/h2>\n

\u201cOver the coming years, this chair will allow us to explore the frontiers of AI research at the intersection of machine learning and neuroscience, and advance the field towards more autonomous, human-level AI by developing novel models and methods for broad and robust AI systems, as opposed to today\u2019s narrow and brittle ones,\u201dshe said.<\/p>\n

Her aim, she added, is \u201cto develop continual, lifelong learning AI capabilities, similar to those of humans, as well as approaches to making AI more robust to changes in its environment and tasks it has to solve, and capable of better understanding and generalization, akin to human capabilities.<\/p>\n

\u201cThe seven-year CERC program is an amazing opportunity to focus on cutting-edge research and explore research directions that are high-risk but also, potentially, high-reward. It\u2019s a great honour for all of us.\u201d<\/p>\n

<\/ins><\/p>\n

In her journey to the top of her profession, Rish has overcome a number of obstacles and managed many changes in her life. She has dealt with ethnic discrimination in Russian academia, braved the culture shock of moving to the U.S. and picking up English at graduate school, surprised her academic parents by declining a university professorship and going into industry, and juggled her research career and raising two kids with her physicist husband.<\/p>\n

Now, in Montreal, she has a new set of challenges associated with her move from industry back to academia, and from one country to another, including picking up another language.<\/p>\n

\u201cUdeM is a French-language university, so I\u2019m learning French now,\u201d she said in English, her Russian accent poking through. \u201cIt\u2019s a challenge. One of the first things I needed to know is that there is no separate word for 70, 80 or 90. It\u2019s 60 plus 10, 4 times 20, 4 times 20 plus 10 \u2013 well, how interesting! Not that simple!\u201d<\/p>\n<\/div>\n

\n

\u2018Find interesting patterns\u2019<\/h2>\n

As a scientist, Rish describes her work as being \u201cat the intersection of artificial intelligence, neuroscience and psychology, using computers to analyze brain data and find interesting patterns there related to human behaviour, to mental states and their changes, and use what you learn to better understand how the brain works and to make computers work better and AI less artificial.\u201d<\/p>\n

<\/ins><\/p>\n

At IBM, Rish won several company awards for excellence and innovation while employed at the Thomas J. Watson Research Center<\/a> in Yorktown Heights, N.Y., from 1999 to 2019. So far at Mila, she has worked with scientific director Yoshua Bengio to, among other things, help develop Covi<\/a>, a contact-tracing app for Covid-19.<\/p>\n

Rish holds 64 patents, has published over 90 research papers, written several book chapters, edited three books and published a monograph on sparse modelling, an area of statistical machine learning particularly important in areas of scientific data analysis such as computational biology and neuroimaging.<\/p>\n

All along, she has made problem-solving her life work \u2013 and pleasure.<\/p>\n

\u201cThe best piece of advice on how to solve problems that I ever got was simply to go out and solve as many as you can \u2013 you just need to keep practicing,\u201d Rish said. \u201cAnd if you don\u2019t get it the first time, then reformulate, try alternative methods and approach the problem from different angles \u2013 until you get it.<\/p>\n

\u201cWhen it comes to training your brain,\u201d she said, \u201cthere\u2019s no substitute for practice, practice practice, just like when you train AI systems with more and more data samples. Reformulating problems, as well as exploring different perspectives and data transformations, is useful for both humans and AI.\u201d<\/p>\n

<\/ins><\/div>\n

\n

A family of mathematicians<\/h2>\n

Rish got the math bug early. Both her parents taught math: her father, Georg Rish, specialized in mathematical modelling and linguistics as a professor at Samarkand State University; her mother, Lioubov (\u201clove,\u201d in Russian), taught math to middle-school and high-school students in the city as well. Rish\u2019s late brother, Dimitri, was also a mathematician.<\/p>\n

\u201cHe was my role model,\u201d she recalled of her sibling, one of two brothers, 15 years her elder and nicknamed Dima. \u201cMy parents were busy at work so he took me in hand as a young child and started giving me little tests of logic to figure out, and I really liked it. Then I followed him into the Math Olympiad and got deeper into learning math, and later, computer science. He taught me programming at the age of 14.\u201d<\/p>\n

Growing up, she was equally curious about other, very different fields, from creative writing to physics and chemistry. Her second brother, Ilya, 13 years her elder, also had a significant impact on her interests, as he was very passionate about chemistry. Their father hoped she would follow in his own footsteps and go into linguistics. (While she chose math and computer science, Rish stayed passionate about writing; in a parallel universe, she imagined, she\u2019d make her career as a writer.)<\/p>\n

\u201cFor her undergraduate degree, she applied to Moscow State University in applied mathematics. The oral entrance exam lasted three hours instead of the usual 20 minutes; her examiner kept giving her harder and harder math problems to solve, and the last one stumped her. She got a C grade, disqualifying her for entry.<\/p>\n

<\/ins><\/p>\n

\u201cI was surprised,\u201d recalled Rish, who at the time suspected she was being discriminated against. Her father, though atheist, was Jewish, born in Germany, where his father, Arnold (Grigorievich) Rish<\/a>, was a representative of the young Soviet government, later sent to Siberia when he fell into disfavour, his family exiled to Uzbekistan. The Rishs are originally from Byelorussia; the name originally meant \u201credhead\u201d.)<\/p>\n

Rejected by MSU, Rish applied instead to the National University of Oil and Gas<\/a> in Moscow, also known as the Gubkin Institute, home to a large number of brilliant scientists, many of them Jewish. She did her degree in applied mathematics, studying alongside such future luminaries as Edward Frenkel<\/a> (now at UC Berkeley) and Roman Abramovich<\/a> (the British-based oligarch).<\/p>\n<\/div>\n

\n

An American education<\/h2>\n

Then came the collapse of the Soviet Union. It was 1991 and students like Rish were finally able to apply to universities in the West. For her graduate degree, Rish sent her application into a good number of American ones and was accepted by several. She chose the University of California, Irvine<\/a>, which impressed her with a wide variety of research topics within AI field.<\/p>\n

\u201cThe first year was quite a shock for me: the new language, the course work, the logistics of finding an apartment, figuring things out from scratch,\u201d she recalled.<\/p>\n

<\/ins><\/p>\n

Another new challenge was working as a teaching assistant. As she progressed, Rish took on in large undergraduate classes, grading homework and exams and leading discussion sessions with students.<\/p>\n

Her English was less-than-perfect, but being a TA made her realize that teaching \u2013 helping students understand the material, overcome their fears of math, and dealing with their personal problems, too \u2013 was something she felt passionate about.<\/p>\n

It might even be her true calling \u2013 and was a significant change from the otherwise excellent education she had in the Soviet Union.<\/p>\n

\u201cIn Russia, professors took a tougher approach: you\u2019d meet with them and then were expected to go off on your own and figure things out for yourself,\u201d she recalled. \u201cIn California, it was more hands-on: the professors helped you choose your material for you, guided you along, aware perhaps that you might give them a bad review if you didn\u2019t. It was definitely a change in the culture.\u201d<\/p>\n

Her graduate school years were also very exciting: meeting new friends, exploring new topics and research directions, searching for her true passion in the other side of the education equation: research. It could all be a bit overwhelming at times, but overall, very rewarding.<\/p>\n

<\/ins><\/p>\n

\u201cI grew a lot as a person during those years,\u201d she recalled, \u201cmade lifelong friendships, and realized that research-wise, I am more interested in exploring the machine-learning side of AI than just the more \u2018classical\u2019 areas of automated reasoning.<\/p>\n

\u201cI also fell in love with Claude Shannon\u2019s \u2018information theory\u2019<\/a> and witnessed what was then called a revolution in signal processing field, when a simple \u2018belief propagation\u2019 algorithm turned out to produce close to Shannon-limit decoding accuracy.<\/p>\n

\u201cI was really excited as this was closely related to the area of my research: approximate algorithms for probabilistic inference<\/a>.\u201d<\/p>\n<\/div>\n

\n

Jumping to IBM<\/h2>\n

Graduating from UC Irvine in 1994 with an MSc, then in 1999 with a PhD, both times in computer science specializing in AI, Rish was then offered a job as an assistant professor at Washington University in St. Louis, Mo. She was quite excited about this opportunity, but decided to explore a new direction, and chose industrial research.<\/p>\n

\u201cI went to IBM Research instead,\u201d she said, \u201cIt was really exciting: they had a huge lab, with many researchers doing many different things \u2013 in physics, in biology, in AI \u2013 many people coming to my talks and asking questions \u2013 it was like being at a year-round scientific conference, so stimulating.\u201d<\/p>\n

<\/ins><\/p>\n

Her choice not to stay in academia surprised both her father and her thesis advisor at UC Irvine, Rina Dechter<\/a>, but Rish knew she\u2019d made the right choice. \u201cThey couldn\u2019t believe I wouldn\u2019t take up a professorship \u2013 what was I doing? But I felt that that I\u2019d already spent seven years in the same environment and it was time to try something very different.\u201d<\/p>\n

Little did she know she\u2019d wind up spending the next 20 years at IBM, however.<\/p>\n

\u201cIn industry, specialists like me usually spend only a few years, even sometimes only a few months, in one place, then move on to other opportunities,\u201d Rish said. \u201cBut IBM was the place for me. It\u2019s a huge and dynamic lab, and what I learned there was to keep my mind open to the vast variety of directions I could navigate towards, then focus to accomplish things.\u201d<\/p>\n<\/div>\n

\n

A job at UdeM<\/h2>\n

Now Rish has brought the same savvy and enthusiasm to UdeM. The idea to leave IBM, uproot her family and start a second career in Canada came through a chance meeting in 2018 with her AI colleague Jo\u00eblle Pineau<\/a>, a Mila researcher, associate professor at McGill University and head of Facebook\u2019s AI Research Lab in Montreal.<\/p>\n

<\/ins><\/p>\n

\u201cWe met at a conference and she told me about a CERC position that had opened up at Mila and encouraged me to apply \u2013 and I listened to her,\u201d Rish recalled. \u201cI figured that after some many years in industry it made sense to finally accept a position at a university, since I always loved teaching and working with students. It probably would have made my dad happy.\u201d<\/p>\n

In the fall of 2019, Rish moved with her family \u2013 husband Sergey Panitkin<\/a> (like her, a passionate downhill skier) and their kids, Natalie<\/a>, 16, a budding writer, and young Alexander (Sasha), 8 \u2013 from Rye Brook in Westchester Country, N.Y., to a rented house in C\u00f4te des Neiges, not far from UdeM\u2019s main campus.<\/p>\n

Her husband, who worked in high-energy physics at the U.S. government\u2019s Brookhaven National Laboratory<\/a> in Upton, N.Y., and at CERN<\/a>, the European Organization for Nuclear Research, in Geneva, took up a consulting post in UdeM\u2019s physics department while looking for full-time work.<\/p>\n

Then, just as the family was settling in and Rish started teaching at Mila, the Covid-19 pandemic hit, and the new life as they knew it was put on hold.<\/p>\n

\u201cWe arrived in October and I started teaching at Mila in January, for the winter session, when Covid happened,\u201d Rish said. \u201cMila closed, an interdisciplinary Covid task force was formed, with multiple projects under its umbrella: from genomic data analysis to better understand the disease, co-led with my collaborator Guy Wolf<\/a> and others from UdeM; to Covi, the contact tracing and risk assessment app project led by Yoshua Bengio and his team, in collaboration with many others, including myself.\u201d<\/p>\n

<\/ins><\/div>\n

\n

\u2018A unique experience\u2019<\/h2>\n

It\u2019s been an intense few months, she recalled \u2013 \u201ca unique experience, working 24\/7 to push several projects forward, meeting many new people and forming collaborations with colleagues around the world. And though in the end, the Canadian government decided to go with a different, simpler app which did not involve machine learning (COVID Alert<\/a>), we believe that our work shows that AI technology can be very useful for fighting the spread of disease since using risk estimation and data analysis can allow us to alert people much earlier than with standard contact tracing, potentially saving many lives.\u201d<\/p>\n

AI still invites suspicion from the lay public, she acknowledges.<\/p>\n

\u201cIt\u2019s not so much they fear machines taking over. It\u2019s that they fear the things that are tricky to resolve with machine-learning. Data collection and privacy is a very sensitive issue, and it\u2019s very tough to convince people their data is safe. Even though privacy concerns were the top priority when developing the Covi app, it is understandable that, emotionally, people can find it difficult to fully trust automated systems with their personal data. And this is why making AI more safe, robust and ethical, in general, is as important as making it smarter.\u201d<\/p>\n

All of which makes her mission \u2013 to get people to trust in science, in logic, in reasoning \u2013 all the more vital now.<\/p>\n

\u201cIn the end, it comes down to this: how do we solve problems? What is the lightbulb that goes on in our brains that allows us to figure things out? How does it all happen in our brains, and how can we make both our brains and AI better? That\u2019s what I want to find out.\u201d<\/p>\n<\/div>\n

<\/ins> <\/p>\n

\/Public Release. The material in this public release comes from the originating organization and may be of a point-in-time nature, edited for clarity, style and length. View in full here<\/a>.<\/div>\n<\/p><\/div>\n<\/p>\n

Published at Sun, 30 Aug 2020 16:52:30 +0000<\/p>\n

AI: a long and winding road<\/a><\/p>\n

<\/div>\n
<\/p>\n
<\/ins><\/div>\n<\/div>\n
\n

Irina Rish<\/a> was 14 years old and going to high school in the central Asian city of Samarkand, Uzbekistan, when she first came across the notion of artificial intelligence.<\/p>\n

\u201cI saw a book, translated from English into Russian, the cover was black with yellow letters, and the title was \u2018Can Machines Think?’\u201d Rish said, recalling her time as a student in the ex-Soviet Union.<\/p>\n

Competing at the time in a Soviet Student Olympiad<\/a> in math, Rish was intrigued.<\/p>\n

\u201cThe book was about AI, and I said to myself: \u2018Gosh, that\u2019s exactly what I was wondering: what algorithms can we design to solve difficult problems, and how can we boost our own \u2018natural intelligence,’\u201d she recalled.<\/p>\n

\u201cI didn\u2019t just think it\u2019d be cool to teach computers to solve problems \u2013 in other words, AI. I also wanted to know how to improve my brain, augment my intelligence, so that my next time at the Math Olympiad, I\u2019d do better.\u201d<\/p>\n

That was in 1983, and since then Rish has made that dual quest her life work. Graduating from university studies \u2013 first in Moscow, then in California \u2013 to a 20-year career with IBM in New York, last October, she moved to Canada to become an associate professor at Universit\u00e9 de Montr\u00e9al and a core faculty member at its affiliated AI institute, the world-renowned Mila.<\/p>\n

<\/ins><\/p>\n

With her move came a major honour: already holder of a Canada CIFAR AI Chair,<\/a> this summer Rish was awarded an even more prestigious Canada Excellence Research Chair <\/a>(CERC). It comes with $34 million in financing over seven years: $10 million from the federal government, $4.4 million from UdeM, and $20 million from other sources.<\/p>\n

Rish\u2019s application for the grant was supported by a wide variety of institutions (Mila, HEC Montr\u00e9al, Polytechnique Montr\u00e9al, McGill University, Calcul Qu\u00e9bec, the Quebec Ministry of Economy and innovation) and industry players (Imagia, Element AI, Samsung, IBM, Microsoft and Druide). \u201cIt\u2019s a wonderful opportunity for me and my team at Mila,\u201d Rish said.<\/p>\n

\n

\u2018Broad and robust AI\u2019<\/h2>\n

\u201cOver the coming years, this chair will allow us to explore the frontiers of AI research at the intersection of machine learning and neuroscience, and advance the field towards more autonomous, human-level AI by developing novel models and methods for broad and robust AI systems, as opposed to today\u2019s narrow and brittle ones,\u201dshe said.<\/p>\n

Her aim, she added, is \u201cto develop continual, lifelong learning AI capabilities, similar to those of humans, as well as approaches to making AI more robust to changes in its environment and tasks it has to solve, and capable of better understanding and generalization, akin to human capabilities.<\/p>\n

\u201cThe seven-year CERC program is an amazing opportunity to focus on cutting-edge research and explore research directions that are high-risk but also, potentially, high-reward. It\u2019s a great honour for all of us.\u201d<\/p>\n

<\/ins><\/p>\n

In her journey to the top of her profession, Rish has overcome a number of obstacles and managed many changes in her life. She has dealt with ethnic discrimination in Russian academia, braved the culture shock of moving to the U.S. and picking up English at graduate school, surprised her academic parents by declining a university professorship and going into industry, and juggled her research career and raising two kids with her physicist husband.<\/p>\n

Now, in Montreal, she has a new set of challenges associated with her move from industry back to academia, and from one country to another, including picking up another language.<\/p>\n

\u201cUdeM is a French-language university, so I\u2019m learning French now,\u201d she said in English, her Russian accent poking through. \u201cIt\u2019s a challenge. One of the first things I needed to know is that there is no separate word for 70, 80 or 90. It\u2019s 60 plus 10, 4 times 20, 4 times 20 plus 10 \u2013 well, how interesting! Not that simple!\u201d<\/p>\n<\/div>\n

\n

\u2018Find interesting patterns\u2019<\/h2>\n

As a scientist, Rish describes her work as being \u201cat the intersection of artificial intelligence, neuroscience and psychology, using computers to analyze brain data and find interesting patterns there related to human behaviour, to mental states and their changes, and use what you learn to better understand how the brain works and to make computers work better and AI less artificial.\u201d<\/p>\n

<\/ins><\/p>\n

At IBM, Rish won several company awards for excellence and innovation while employed at the Thomas J. Watson Research Center<\/a> in Yorktown Heights, N.Y., from 1999 to 2019. So far at Mila, she has worked with scientific director Yoshua Bengio to, among other things, help develop Covi<\/a>, a contact-tracing app for Covid-19.<\/p>\n

Rish holds 64 patents, has published over 90 research papers, written several book chapters, edited three books and published a monograph on sparse modelling, an area of statistical machine learning particularly important in areas of scientific data analysis such as computational biology and neuroimaging.<\/p>\n

All along, she has made problem-solving her life work \u2013 and pleasure.<\/p>\n

\u201cThe best piece of advice on how to solve problems that I ever got was simply to go out and solve as many as you can \u2013 you just need to keep practicing,\u201d Rish said. \u201cAnd if you don\u2019t get it the first time, then reformulate, try alternative methods and approach the problem from different angles \u2013 until you get it.<\/p>\n

\u201cWhen it comes to training your brain,\u201d she said, \u201cthere\u2019s no substitute for practice, practice practice, just like when you train AI systems with more and more data samples. Reformulating problems, as well as exploring different perspectives and data transformations, is useful for both humans and AI.\u201d<\/p>\n

<\/ins><\/div>\n

\n

A family of mathematicians<\/h2>\n

Rish got the math bug early. Both her parents taught math: her father, Georg Rish, specialized in mathematical modelling and linguistics as a professor at Samarkand State University; her mother, Lioubov (\u201clove,\u201d in Russian), taught math to middle-school and high-school students in the city as well. Rish\u2019s late brother, Dimitri, was also a mathematician.<\/p>\n

\u201cHe was my role model,\u201d she recalled of her sibling, one of two brothers, 15 years her elder and nicknamed Dima. \u201cMy parents were busy at work so he took me in hand as a young child and started giving me little tests of logic to figure out, and I really liked it. Then I followed him into the Math Olympiad and got deeper into learning math, and later, computer science. He taught me programming at the age of 14.\u201d<\/p>\n

Growing up, she was equally curious about other, very different fields, from creative writing to physics and chemistry. Her second brother, Ilya, 13 years her elder, also had a significant impact on her interests, as he was very passionate about chemistry. Their father hoped she would follow in his own footsteps and go into linguistics. (While she chose math and computer science, Rish stayed passionate about writing; in a parallel universe, she imagined, she\u2019d make her career as a writer.)<\/p>\n

\u201cFor her undergraduate degree, she applied to Moscow State University in applied mathematics. The oral entrance exam lasted three hours instead of the usual 20 minutes; her examiner kept giving her harder and harder math problems to solve, and the last one stumped her. She got a C grade, disqualifying her for entry.<\/p>\n

<\/ins><\/p>\n

\u201cI was surprised,\u201d recalled Rish, who at the time suspected she was being discriminated against. Her father, though atheist, was Jewish, born in Germany, where his father, Arnold (Grigorievich) Rish<\/a>, was a representative of the young Soviet government, later sent to Siberia when he fell into disfavour, his family exiled to Uzbekistan. The Rishs are originally from Byelorussia; the name originally meant \u201credhead\u201d.)<\/p>\n

Rejected by MSU, Rish applied instead to the National University of Oil and Gas<\/a> in Moscow, also known as the Gubkin Institute, home to a large number of brilliant scientists, many of them Jewish. She did her degree in applied mathematics, studying alongside such future luminaries as Edward Frenkel<\/a> (now at UC Berkeley) and Roman Abramovich<\/a> (the British-based oligarch).<\/p>\n<\/div>\n

\n

An American education<\/h2>\n

Then came the collapse of the Soviet Union. It was 1991 and students like Rish were finally able to apply to universities in the West. For her graduate degree, Rish sent her application into a good number of American ones and was accepted by several. She chose the University of California, Irvine<\/a>, which impressed her with a wide variety of research topics within AI field.<\/p>\n

\u201cThe first year was quite a shock for me: the new language, the course work, the logistics of finding an apartment, figuring things out from scratch,\u201d she recalled.<\/p>\n

<\/ins><\/p>\n

Another new challenge was working as a teaching assistant. As she progressed, Rish took on in large undergraduate classes, grading homework and exams and leading discussion sessions with students.<\/p>\n

Her English was less-than-perfect, but being a TA made her realize that teaching \u2013 helping students understand the material, overcome their fears of math, and dealing with their personal problems, too \u2013 was something she felt passionate about.<\/p>\n

It might even be her true calling \u2013 and was a significant change from the otherwise excellent education she had in the Soviet Union.<\/p>\n

\u201cIn Russia, professors took a tougher approach: you\u2019d meet with them and then were expected to go off on your own and figure things out for yourself,\u201d she recalled. \u201cIn California, it was more hands-on: the professors helped you choose your material for you, guided you along, aware perhaps that you might give them a bad review if you didn\u2019t. It was definitely a change in the culture.\u201d<\/p>\n

Her graduate school years were also very exciting: meeting new friends, exploring new topics and research directions, searching for her true passion in the other side of the education equation: research. It could all be a bit overwhelming at times, but overall, very rewarding.<\/p>\n

<\/ins><\/p>\n

\u201cI grew a lot as a person during those years,\u201d she recalled, \u201cmade lifelong friendships, and realized that research-wise, I am more interested in exploring the machine-learning side of AI than just the more \u2018classical\u2019 areas of automated reasoning.<\/p>\n

\u201cI also fell in love with Claude Shannon\u2019s \u2018information theory\u2019<\/a> and witnessed what was then called a revolution in signal processing field, when a simple \u2018belief propagation\u2019 algorithm turned out to produce close to Shannon-limit decoding accuracy.<\/p>\n

\u201cI was really excited as this was closely related to the area of my research: approximate algorithms for probabilistic inference<\/a>.\u201d<\/p>\n<\/div>\n

\n

Jumping to IBM<\/h2>\n

Graduating from UC Irvine in 1994 with an MSc, then in 1999 with a PhD, both times in computer science specializing in AI, Rish was then offered a job as an assistant professor at Washington University in St. Louis, Mo. She was quite excited about this opportunity, but decided to explore a new direction, and chose industrial research.<\/p>\n

\u201cI went to IBM Research instead,\u201d she said, \u201cIt was really exciting: they had a huge lab, with many researchers doing many different things \u2013 in physics, in biology, in AI \u2013 many people coming to my talks and asking questions \u2013 it was like being at a year-round scientific conference, so stimulating.\u201d<\/p>\n

<\/ins><\/p>\n

Her choice not to stay in academia surprised both her father and her thesis advisor at UC Irvine, Rina Dechter<\/a>, but Rish knew she\u2019d made the right choice. \u201cThey couldn\u2019t believe I wouldn\u2019t take up a professorship \u2013 what was I doing? But I felt that that I\u2019d already spent seven years in the same environment and it was time to try something very different.\u201d<\/p>\n

Little did she know she\u2019d wind up spending the next 20 years at IBM, however.<\/p>\n

\u201cIn industry, specialists like me usually spend only a few years, even sometimes only a few months, in one place, then move on to other opportunities,\u201d Rish said. \u201cBut IBM was the place for me. It\u2019s a huge and dynamic lab, and what I learned there was to keep my mind open to the vast variety of directions I could navigate towards, then focus to accomplish things.\u201d<\/p>\n<\/div>\n

\n

A job at UdeM<\/h2>\n

Now Rish has brought the same savvy and enthusiasm to UdeM. The idea to leave IBM, uproot her family and start a second career in Canada came through a chance meeting in 2018 with her AI colleague Jo\u00eblle Pineau<\/a>, a Mila researcher, associate professor at McGill University and head of Facebook\u2019s AI Research Lab in Montreal.<\/p>\n

<\/ins><\/p>\n

\u201cWe met at a conference and she told me about a CERC position that had opened up at Mila and encouraged me to apply \u2013 and I listened to her,\u201d Rish recalled. \u201cI figured that after some many years in industry it made sense to finally accept a position at a university, since I always loved teaching and working with students. It probably would have made my dad happy.\u201d<\/p>\n

In the fall of 2019, Rish moved with her family \u2013 husband Sergey Panitkin<\/a> (like her, a passionate downhill skier) and their kids, Natalie<\/a>, 16, a budding writer, and young Alexander (Sasha), 8 \u2013 from Rye Brook in Westchester Country, N.Y., to a rented house in C\u00f4te des Neiges, not far from UdeM\u2019s main campus.<\/p>\n

Her husband, who worked in high-energy physics at the U.S. government\u2019s Brookhaven National Laboratory<\/a> in Upton, N.Y., and at CERN<\/a>, the European Organization for Nuclear Research, in Geneva, took up a consulting post in UdeM\u2019s physics department while looking for full-time work.<\/p>\n

Then, just as the family was settling in and Rish started teaching at Mila, the Covid-19 pandemic hit, and the new life as they knew it was put on hold.<\/p>\n

\u201cWe arrived in October and I started teaching at Mila in January, for the winter session, when Covid happened,\u201d Rish said. \u201cMila closed, an interdisciplinary Covid task force was formed, with multiple projects under its umbrella: from genomic data analysis to better understand the disease, co-led with my collaborator Guy Wolf<\/a> and others from UdeM; to Covi, the contact tracing and risk assessment app project led by Yoshua Bengio and his team, in collaboration with many others, including myself.\u201d<\/p>\n

<\/ins><\/div>\n

\n

\u2018A unique experience\u2019<\/h2>\n

It\u2019s been an intense few months, she recalled \u2013 \u201ca unique experience, working 24\/7 to push several projects forward, meeting many new people and forming collaborations with colleagues around the world. And though in the end, the Canadian government decided to go with a different, simpler app which did not involve machine learning (COVID Alert<\/a>), we believe that our work shows that AI technology can be very useful for fighting the spread of disease since using risk estimation and data analysis can allow us to alert people much earlier than with standard contact tracing, potentially saving many lives.\u201d<\/p>\n

AI still invites suspicion from the lay public, she acknowledges.<\/p>\n

\u201cIt\u2019s not so much they fear machines taking over. It\u2019s that they fear the things that are tricky to resolve with machine-learning. Data collection and privacy is a very sensitive issue, and it\u2019s very tough to convince people their data is safe. Even though privacy concerns were the top priority when developing the Covi app, it is understandable that, emotionally, people can find it difficult to fully trust automated systems with their personal data. And this is why making AI more safe, robust and ethical, in general, is as important as making it smarter.\u201d<\/p>\n

All of which makes her mission \u2013 to get people to trust in science, in logic, in reasoning \u2013 all the more vital now.<\/p>\n

\u201cIn the end, it comes down to this: how do we solve problems? What is the lightbulb that goes on in our brains that allows us to figure things out? How does it all happen in our brains, and how can we make both our brains and AI better? That\u2019s what I want to find out.\u201d<\/p>\n<\/div>\n

<\/ins> <\/p>\n

\/Public Release. The material in this public release comes from the originating organization and may be of a point-in-time nature, edited for clarity, style and length. View in full here<\/a>.<\/div>\n<\/p><\/div>\n<\/p>\n

Published at Sun, 30 Aug 2020 16:52:30 +0000<\/p>\n","protected":false},"excerpt":{"rendered":"

AI: a long and winding road Irina Rish was 14 years old and going to…<\/p>\n","protected":false},"author":3,"featured_media":2489,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[3],"tags":[],"class_list":["post-2490","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence"],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/techclot.com\/wp-content\/uploads\/2020\/08\/hkhDpq.jpg?fit=500%2C334&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p3orZX-Ea","jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/posts\/2490","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/comments?post=2490"}],"version-history":[{"count":0,"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/posts\/2490\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/media\/2489"}],"wp:attachment":[{"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/media?parent=2490"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/categories?post=2490"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techclot.com\/index.php\/wp-json\/wp\/v2\/tags?post=2490"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}