Data Science newsletter – January 25, 2022

Mustafa Suleyman, a co-founder of artificial intelligence research company DeepMind, has left Google to join venture capital firm Greylock Partners. Suleyman has brought to an end an eight-year run at Google, where he was most recently the company’s vice president of AI product management and policy.

He joined Google when it bought DeepMind in 2014 and became the latter’s head of applied AI. Suleyman was reportedly placed on administrative leave in 2019 following allegations that he bullied employees. Suleyman, who moved to Google at the end of that year, said on a podcast with Greylock partner Reid Hoffman this week that he “really screwed up” and that “I remain very sorry about the impact that that caused people and the hurt that people felt there.”

The University of Rochester is the new home of a research center devoted to computer simulations used to advance the understanding of astrophysics, plasma science, high-energy-density physics, and fusion energy.

The Flash Center for Computational Science recently moved from the University of Chicago to the Department of Physics and Astronomy at Rochester. Located in the Bausch and Lomb building on the River Campus, the center encompasses numerous cross-disciplinary, computational physics research projects conducted using the FLASH code. The FLASH code is a publicly available multi-physics code that allows researchers to accurately simulate and model many scientific phenomena—including plasma physics, computational fluid dynamics, high-energy-density physics (HEDP), and fusion energy research—and inform the design and execution of experiments.

The program will provide up to $1.5 million per faculty hire to help UI colleges attract “outstanding faculty in key areas of innovation and interdisciplinary strength.” Most of the money will support the faculty member’s research and teaching.

“Separate resources will provide some salary support, with the home college expected to also provide support,” UI Executive Vice President and Provost Kevin Kregel told The Gazette.

The program will enable up to three recruits per year for three years, with expectations the first new hires will start in the 2024 budget year, which begins July 1, 2023. The process, though, will launch this spring — when “areas of excellence will be identified,” according to Kregel.

The Edelman Trust Barometer 2022 finds almost two-thirds of people are inclined to distrust organizations, which could impact attempts to tackle COVID-19 and climate change.

Scientists are the most trusted in society – and government leaders the least trusted.

The Barometer shows four forces at work, including a failure of leadership that could destabilize society, according to Richard Edelman.

But he says it’s possible to break the cycle of distrust and rebuild public trust through factual information and demonstrable progress.

We have designed a course on Responsible AI, Law, Ethics, and Society that helps develop effective multidisciplinary dialogue. The novel approach we use sought to build collaborative skills among joint teams of data sciencea and law students, by engaging them in joint problem-solving tasks on real-world AI challenges, such as liability and responsibility, discrimination and equality, transparency and privacy. See the first sidebar here for the learning objectives.

The idea of introducing legal or ethical studies in computer (and data) science syllabi is not new. Recent years have seen an increase in the number of tech ethics modules offerings. Of these, some are offered as embedded units in existing courses rather than standalone courses,4,6,7,11,16 and several are offered by instructors whose background is in philosophy or information science rather than computer or data science. In addition, to the best of our knowledge, the nature of many of the courses is based on insights from law, ethics and STS (Science, Technology, and Society), and lacks technical activities. Finally, there are other courses directed for students from additional disciplines, such as philosophy.

The community’s growth has been partially aided by Cobble’s format, which works like a social media feed where users can view posts of fellow creators looking to share their work or find collaborators. For example, head developer of Cobble, Carson Kim, said he found a new bandmate through the site. The fourth-year linguistics and computer science student said he initially focused only on developing Cobble but now has the freedom to use the site for its intended purpose as well and will now be auditioning for Spring Sing with the drummer he met on the site.

In terms of reshaping UCLA’s social landscape, Cobble’s head of product, fourth-year linguistics and computer science student Shreya Chatterjee, said she thinks the site is also important for shutting down the widespread stereotype that STEM majors lack creativity. Chatterjee said she knows plenty of STEM students like herself who have creative hobbies and passions, and she is excited to see them congregate. She said she hopes Cobble can reject this assumption by revealing how everyone’s disciplines and majors have creative roots in their own rights and ways.

“Even if you do your art for one minute a day or for five hours a day, it doesn’t matter,” Chatterjee said. “Everyone is welcome. There’s no shame in how you express yourself in the creations you make.”

There is good reason to expect that there are more billion-dollar equations out there: generations-old mathematical theorems with the potential for new applications. The question is where to look for the next one.

A few candidates can be found in mathematical work in the latter part of the 20th century. One comes in the form of fractals, patterns that are self-similar, repeating on many different levels, like the branches of a tree or the shape of a broccoli head. Mathematicians developed a comprehensive theory of fractals in the 80s, and there was some excitement about applications that could store data more efficiently. Interest died out until recently, when a small community of computer scientists started showing how mathematical fractals can produce the most amazing, weird and wonderful patterns.

Another field of mathematics still looking for a money-making application is chaos theory, the best-known example of which is the butterfly effect: if a butterfly flaps its wings in the Amazon, we need to know about it in order to predict a storm in the North Atlantic. More generally, the theory tells us that, in order to accurately predict storms (or political events), we need to know about every tiny air disturbance on the entire planet. An impossible task. But chaos theory also points towards repeatable patterns. The Lorenz attractor is a model of the weather that, despite being chaotic, does produce somewhat regular and recognisable patterns. Given the uncertainty of the times we live in, it may be time to revive these ideas.

Three UO geography students have formed a new group to develop networking opportunities and spur discussion with professionals in the field.

Claire Parton, Morgan Scafidi and Madison Fung are co-leaders of Oregon Women in Geographic Information Systems, which they formed in the current academic year.

Parton reached out last year to Scafidi, a fellow spatial data science and geography student, after some encouragement from an adviser. The two discussed their shared vision of forming the new organization to help women in their field find networking opportunities.

Mentor Collective, the leading provider of scalable, structured mentorship programs, announced today that it has raised strategic funding to meet the growing demand for large-scale peer mentorship on today’s college campuses. The Series A investment round was led by Resolve Growth Partners – a venture capital and growth equity firm committed to helping technology-enabled companies realize their full potential. Additionally, the round included reinvestments from Mentor Collective’s initial thought partner Lumina Foundation – an independent, private foundation in Indianapolis committed to making opportunities for learning beyond high school available to all. In 2021, Mentor Collective – a remote-first company founded in Boston – created over 83,000 mentorships, exceeding the cumulative total of the last six years. Since its founding, the company has trained over 50,000 mentors. This engagement along with the confidence of both for-profit and non-profit investors is a clear indication of the current success of Mentor Collective and the critical need for mentorship in higher education.

Researchers at the Yale School of Public Health were able to accurately predict outbreaks of COVID-19 in Connecticut municipalities using anonymous location information from mobile devices, according to a new study published in Science Advances.

The novel data analysis applied in the study could help health officials stem community outbreaks of COVID-19 in the future and allocate testing resources more efficiently, the researchers said.

The research was a collaborative effort involving data scientists and epidemiologists from YSPH, the Connecticut Department of Public Health, the U.S. Centers for Disease Control and Prevention and Whitespace Ltd., a spatial data analytics firm.

The key to the findings was the precision with which researchers were able to identify incidents of high-frequency close personal contact (defined as a radius of 6 feet) in Connecticut down to the municipal level. The CDC advises people to keep at least six feet of distance with others to avoid possible transmission of COVID-19.

High school graduation rates dipped in at least 20 states after the first full school year disrupted by the pandemic, suggesting the coronavirus may have ended nearly two decades of nationwide progress toward getting more students diplomas, an analysis shows.

The drops came despite at least some states and educators loosening standards to help struggling students.

The results, according to data obtained from 26 states and analyzed by Chalkbeat, are the latest concerning trend in American education, which has been rocked by a pandemic that left many students learning remotely last year and continues to complicate teaching and learning. Some fear that the next several graduating classes could be even more affected.

The news demonstrates the absolute centrality of AI research to companies like Meta. Rivals like Microsoft and Nvidia have already announced their own “AI supercomputers,” which are slightly different from what we think of as regular supercomputers. RSC will be used to train a range of systems across Meta’s businesses: from content moderation algorithms used to detect hate speech on Facebook and Instagram to augmented reality features that will one day be available in the company’s future AR hardware. And, yes, Meta says RSC will be used to design experiences for the metaverse — the company’s insistent branding for an interconnected series of virtual spaces, from offices to online arenas.

“RSC will help Meta’s AI researchers build new and better AI models that can learn from trillions of examples; work across hundreds of different languages; seamlessly analyze text, images, and video together; develop new augmented reality tools; and much more,” write Meta engineers Kevin Lee and Shubho Sengupta in a blog post outlining the news.

Western users are logging off, but across the continent the social media company is indispensable for everything from running a business to sourcing vaccines. How did it become inescapable?

The latest achievement is what’s called “data2vec,” developed by researchers at the AI division of Meta (parent of Facebook, Instagram, and WhatsApp).

The point, as Meta researcher Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, and Michael Auli reveal in a blog post, is to approach something more like the general learning ability that the human mind seems to encompass.

“While people appear to learn in a similar way regardless of how they get information — whether they use sight or sound, for example — there are currently big differences in the way self-supervised learning algorithms learn from images, speech, text, and other modalities,” the blog post states.

The first phase of the project calls for Intel to make a $20 billion investment to build two plants, called fabs, in Jersey Township in Licking County northeast of Columbus that will employ 3,000 workers with an average salary of $135,000 per year. There also will be 3,000 construction jobs and as many as 10,000 indirect jobs.

The project could have three more phases, employing thousands more workers and tens of billions of dollars in additional investment by the Silicon Valley-based semiconductor company.

DeWine and Husted spent hours with The Dispatch detailing how this project came together.

When it comes to killing and eating other creatures, chimpanzees—our closest relatives—have nothing on us. Animal flesh makes up much more of the average human’s diet than a chimp’s.

Many scientists have long suggested our blood lust ramped up about 2 million years ago, based on the number of butchery marks found at ancient archaeological sites. The spike in calories from meat, the story goes, allowed one of our early ancestors, Homo erectus, to grow bigger bodies and brains.

But a new study argues the evidence behind this hypothesis is statistically flawed because it fails to account for the fact that researchers have focused most of their time and attention on later sites. As a result of this unequal “sampling effort” over time at different sites, the authors say, it’s impossible to know how big a role meat eating played in human evolution.

The digital environment offers a world of opportunity – especially during the pandemic, when virtually everything kids do, from school, to socializing, to games has some sort of online component. And while it can all seem like child’s play, cyberspace is also home to threats ranging from data-hungry corporations to cyberbullies.

So, while we can’t protect kids from every online threat, you can help them better protect themselves. Here are a few tips:

1. Change the privacy settings