Artificial intelligence (AI) transforms various aspects of human society, such as the economy, health, education, security, and culture. As AI becomes more powerful and pervasive, many nations invest heavily in building their own AI capabilities and ecosystems, aiming to gain global competitive advantages and strategic influence….
Tutorial: How To Make and Share Custom GPTs
The realm of artificial intelligence is continually expanding, introducing groundbreaking tools that transform how we interact with technology. Among these innovations, custom Generative Pre-trained Transformers, commonly known as GPTs, have emerged as a fascinating development. These AI models, which go beyond standard ChatGPT capabilities, allow for…
Just-in-time provisioning: Defined, explained, explored – CyberTalk
EXECUTIVE SUMMARY:
Just-in-time (JIT) provisioning doesn’t quite get as much attention as other account authentication or access mechanisms, but that doesn’t mean that it isn’t worthwhile. If you’re curious about how just-in-time provisioning could benefit your organization, keep reading.
What is just-in-time (JIT) provisioning?
Just-in-time provisioning is a cyber security practice that provides users, processes, applications and systems with a certain level of access to resources for a limited length of time; as much as required to complete essential tasks.
In other words, it’s a way to provide secure privileged access while minimizing standing access.
Why does just-in-time provisioning matter for organizations?
Just-in-time provisioning reduces the risk of privileged access abuse and lateral network movement on the part of threat actors, allowing organizations to maintain a robust cyber security posture.
Just-in-time provisioning can also position organizations to better achieve compliance goals, as JIT not only minimizes the number of privileged users and sessions, but it also provides full audit trails of all privileged actions.
With just-in-time provisioning, new users can be added at-scale, meaning that new hires and acquired employees are no problem.
For many organizations, JIT is a component of a broader automation strategy. By automating the process of providing temporary access, organizations reduce manual intervention — eliminating admin review cycles and wait times — and allow for fast and accurate access provisioning.
What are the different types of just-in-time access?
- Temporary elevation. This form of access permits a temporary increase in privileges, allowing users to have access to privileged accounts or to execute privileged commands on a per-instance and time-limited basis. Access is revoked after a specified time.
- Ephemeral accounts. These are one-time-use accounts. They are created on a per-instance basis and immediately deprovisioned or deleted after use.
- Broker and remove access. These accounts are intended for routine use, but users are still responsible for providing a justification if connecting to a specific target. Users typically have a shared account. Credentials for the account are often centrally managed, secured and regularly rotated in a central vault.
Implementing just-in-time provisioning for your organization
In terms of implementing efficient just-in-time provisioning, administrators must set up Single Sign-On (SSO) between the target service provider and the identity provider. In addition, administrators must confirm the inclusion of user attributes necessary for the application.
In turn, when a new user logs onto the application, they will effectively auto-create an account, rather than requiring administrator assistance. SAML assertions present the web application with the details needed from the identity provider.
Administrators can leverage a centralized cloud identity provider or an SSO service developed on top of a traditional directory to achieve the JIT workflow.
During initial set-up, ensuring JIT provisioning compatibility is crucial. Popular applications, such as Slack and the Atlassian Suite, are notable examples of platforms that support just-in-time access.
More JIT information
Just-in-time provisioning represents a dynamic cyber security approach that enhances security, streamlines administrative processes, assists with access-at-scale, and helps organizations achieve compliance objectives while optimizing operational efficiency. For more information about just-in-time services, please click here.
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Nancy Hopkins awarded the National Academy of Sciences Public Welfare Medal
The National Academy of Sciences has awarded MIT biologist Nancy Hopkins, the Amgen Professor of Biology Emerita, with the 2024 Public Welfare Medal in recognition of “her courageous leadership over three decades to create and ensure equal opportunity for women in science.”
The award recognizes Hopkins’s role in catalyzing and leading MIT’s “A Study on the Status of Women Faculty in Science,” made public in 1999. The landmark report, the result of the efforts of numerous members of the MIT faculty and administration, revealed inequities in the treatment and resources available to women versus men on the faculty at the Institute, helped drive significant changes to MIT policies and practices, and sparked a national conversation about the unequal treatment of women in science, engineering, and beyond.
Since the medal was established in 1914 to honor extraordinary use of science for the public good, it has been awarded to several MIT-affiliated scientists, including Karl Compton, James R. Killian Jr., and Jerome B. Wiesner, as well as Vannevar Bush, Isidor I. Rabi, and Victor Weiskopf.
“The Public Welfare Medal has been awarded to MIT faculty who have helped define our Institute and scientists who have shaped modern science on the national stage,” says Susan Hockfield, MIT president emerita. “It is more than fitting for Nancy to join their ranks, and — importantly — celebrates her critical role in increasing the participation of women in science and engineering as a significant national achievement.”
When Hopkins joined the faculty of the MIT Center for Cancer Research (CCR) in 1973, she did not set out to become an advocate for equality for women in science. For the first 15 years, she distinguished herself in pioneering studies linking genes of RNA tumor viruses to their roles in causing some forms of cancer. But in 1989, Hopkins changed course: She began developing molecular technologies for the study of zebrafish that would help establish it as an important model for vertebrate development and cancer biology.
To make the pivot, Hopkins needed more space to accommodate fish tanks and new equipment. Although Hopkins strongly suspected that she had been assigned less lab space than her male peers in the building, her hypothesis carried little weight and her request was denied. Ever the scientist, Hopkins believed the path to more lab space was to collect data. One night in 1993, with a measuring tape in hand, she visited each lab to quantify the distribution of space in her building. Her hypothesis appeared correct.
Hopkins shared her initial findings — and her growing sense that there was bias against women scientists — with one female colleague, and then others, many of whom reported similar experiences. The senior women faculty in MIT’s School of Science began meeting to discuss their concerns, ultimately documenting them in a letter to Dean of Science Robert Birgeneau. The letter was signed by professors Susan Carey, Sylvia Ceyer, Sallie “Penny” Chisholm, Suzanne Corkin, Mildred Dresselhaus, Ann Graybiel, Ruth Lehmann, Marcia McNutt, Terry Orr-Weaver, Mary-Lou Pardue, Molly Potter, Paula Malanotte-Rizzoli, Leigh Royden, Lisa Steiner, and Joanne Stubbe. Also important were Hopkins’s discussions with Lorna Gibson, a professor in the Department of Materials Science and Engineering, since Gibson had made similar observations with her female colleagues in the School of Engineering. Despite the biases against these women, they were highly accomplished scientists. Four of them were eventually awarded the U.S. National Medal of Science, and 11 were, or became, members of the National Academy of Sciences.
In response to the women in the School of Science, Birgeneau established the Committee on the Status of Women Faculty in 1995, which included both female faculty and three male faculty who had been department chairs: Jerome Friedman, Dan Kleitman, and Robert Silbey. In addition to interviewing essentially all the female faculty members in the school, they collected data on salaries, space, and other resources. The committee found that of 209 tenured professors in the School of Science only 15 were women, and they often had smaller wages and labs, and were raising more of their salaries from grants than equivalent male faculty.
At the urging of Lotte Bailyn, a professor at the MIT Sloan School of Management and chair of the faculty, Hopkins and the committee summarized their findings to be presented to MIT’s faculty. Struck by the pervasive and well-documented pattern of bias against women across the School of Science, both Birgeneau and MIT President Charles Vest added prefaces to the report before it was published in the faculty newsletter. Vest commented, “I have always believed that contemporary gender discrimination within universities is part reality and part perception. True, but I now understand that reality is by far the greater part of the balance.”
Vest took an “engineers’ approach” to addressing the report’s findings, remarking “anything I can measure, I can fix.” He tasked Provost Robert Brown with establishing committees to produce reports on the status of women faculty for all five of MIT’s schools. The reports were published in 2002 and drew attention to the small number of women faculty in some schools, as well as discrepancies similar to those first documented in the School of Science.
In response, MIT implemented changes in hiring practices, updated pay equity reviews, and worked to improve the working environment for women faculty. On-campus day care facilities were built and leave policies were expanded for the benefit of all faculty members with families. To address underrepresentation of individuals of color, as well as the unique biases against women of color, Brown established the Council on Faculty Diversity with Hopkins and Philip Clay, then MIT’s chancellor and a professor in the Department of Urban Studies and Planning. Meanwhile, Vest spearheaded a collaboration with presidents of other leading universities to increase representation of women faculty.
MIT increased the numbers of women faculty by altering hiring procedures — particularly in the School of Engineering under Dean Thomas Magnanti and in the School of Science under Birgeneau, and later Associate Dean Hazel Sive. MIT did not need to alter its standards for hiring to increase the number of women on its faculty: Women hired with revised policies at the Institute have been equally successful and have gone on to important leadership roles at MIT and other institutions.
In the wake of the 1999 report the press thrust MIT — and Hopkins — into the national spotlight. The careful documentation in the report and first Birgeneau’s and then Vest’s endorsement of and proactive response to its findings were persuasive to many reporters and their readers. The reports and media coverage resonated with women across academia, resulting in a flood of mail to Hopkins’s inbox, as well as many requests for speaking engagements. Hopkins would eventually undertake hundreds of talks across the United States and many other countries about advocating for the equitable treatment of women in science.
Her advocacy work continued after her retirement. In 2019, Hopkins, along with Hockfield and Sangeeta Bhatia, the John J. and Dorothy Wilson Professor of Health Sciences and Technology and of the Department of Electrical Engineering and Computer Science, founded the Boston Biotech Working Group — which later evolved into the Faculty Founder Initiative — to increase women’s representation as founders and board members of biotech companies in Massachusetts.
Hopkins, however, believes she became “this very visible person by chance.”
“An almost uncountable number of people made this happen,” she continues. “Moreover, I know how much work went on before I even set foot on campus, such as by Emily Wick, Shirley Ann Jackson, Sheila Widnall, and Mildred Dresselhaus. I stood on the shoulders of a great institution and the long, hard work of many people that belong to it.”
The National Academy of Sciences will present the 2024 Public Welfare Medal to Hopkins in April at its 161st annual meeting. Hopkins is the recipient of many other awards and honors, both for her scientific achievements and her advocacy for women in science. She is a member of the National Academy of Sciences, the National Academy of Medicine, the American Academy of Arts and Sciences, and the AACR Academy. Other awards include the Centennial Medal from Harvard University, the MIT Gordon Y. Billard Award for “special service” to MIT, the MIT Laya Wiesner Community Award, the Maria Mitchell Women in Science Award, and the STAT Biomedical Innovation Award. In addition, she has received eight honorary doctorates, most recently from Rockefeller University, the Hong Kong University of Science and Technology, and the Weizmann Institute.
Simons Center’s collaborative approach propels autism research, at MIT and beyond
The secret to the success of MIT’s Simons Center for the Social Brain is in the name. With a founding philosophy of “collaboration and community” that has supported scores of scientists across more than a dozen Boston-area research institutions, the SCSB advances research by being inherently social.
SCSB’s mission is “to understand the neural mechanisms underlying social cognition and behavior and to translate this knowledge into better diagnosis and treatment of autism spectrum disorders.” When Director Mriganka Sur founded the center in 2012 in partnership with the Simons Foundation Autism Research Initiative (SFARI) of Jim and Marilyn Simons, he envisioned a different way to achieve urgently needed research progress than the traditional approach of funding isolated projects in individual labs. Sur wanted SCSB’s contribution to go beyond papers, though it has generated about 350 and counting. He sought the creation of a sustained, engaged autism research community at MIT and beyond.
“When you have a really big problem that spans so many issues — a clinical presentation, a gene, and everything in between — you have to grapple with multiple scales of inquiry,” says Sur, the Newton Professor of Neuroscience in MIT’s Department of Brain and Cognitive Sciences (BCS) and The Picower Institute for Learning and Memory. “This cannot be solved by one person or one lab. We need to span multiple labs and multiple ways of thinking. That was our vision.”
In parallel with a rich calendar of public colloquia, lunches, and special events, SCSB catalyzes multiperspective, multiscale research collaborations in two programmatic ways. Targeted projects fund multidisciplinary teams of scientists with complementary expertise to collectively tackle a pressing scientific question. Meanwhile, the center supports postdoctoral Simons Fellows with not one, but two mentors, ensuring a further cross-pollination of ideas and methods.
Complementary collaboration
In 11 years, SCSB has funded nine targeted projects. Each one, by design, involves a deep and multifaceted exploration of a major question with both fundamental importance and clinical relevance. The first project, back in 2013, for example, marshaled three labs spanning BCS, the Department of Biology, and The Whitehead Institute for Biomedical Research to advance understanding of how mutation of the Shank3 gene leads to the pathophysiology of Phelan-McDermid Syndrome by working across scales ranging from individual neural connections to whole neurons to circuits and behavior.
Other past projects have applied similarly integrated, multiscale approaches to topics ranging from how 16p11.2 gene deletion alters the development of brain circuits and cognition to the critical role of the thalamic reticular nucleus in information flow during sleep and wakefulness. Two others produced deep examinations of cognitive functions: how we go from hearing a string of words to understanding a sentence’s intended meaning, and the neural and behavioral correlates of deficits in making predictions about social and sensory stimuli. Yet another project laid the groundwork for developing a new animal model for autism research.
SFARI is especially excited by SCSB’s team science approach, says Kelsey Martin, executive vice president of autism and neuroscience at the Simons Foundation. “I’m delighted by the collaborative spirit of the SCSB,” Martin says. “It’s wonderful to see and learn about the multidisciplinary team-centered collaborations sponsored by the center.”
New projects
In the last year, SCSB has launched three new targeted projects. One team is investigating why many people with autism experience sensory overload and is testing potential interventions to help. The scientists hypothesize that patients experience a deficit in filtering out the mundane stimuli that neurotypical people predict are safe to ignore. Studies suggest the predictive filter relies on relatively low-frequency “alpha/beta” brain rhythms from deep layers of the cortex moderating the higher frequency “gamma” rhythms in superficial layers that process sensory information.
Together, the labs of Charles Nelson, professor of pediatrics at Boston Children’s Hospital (BCH), and BCS faculty members Bob Desimone, the Doris and Don Berkey Professor, and Earl K. Miller, the Picower Professor, are testing the hypothesis in two different animal models at MIT and in human volunteers at BCH. In the animals they’ll also try out a new real-time feedback system invented in Miller’s lab that can potentially correct the balance of these rhythms in the brain. And in an animal model engineered with a Shank3 mutation, Desimone’s lab will test a gene therapy, too.
“None of us could do all aspects of this project on our own,” says Miller, an investigator in the Picower Institute. “It could only come about because the three of us are working together, using different approaches.”
Right from the start, Desimone says, close collaboration with Nelson’s group at BCH has been essential. To ensure his and Miller’s measurements in the animals and Nelson’s measurements in the humans are as comparable as possible, they have tightly coordinated their research protocols.
“If we hadn’t had this joint grant we would have chosen a completely different, random set of parameters than Chuck, and the results therefore wouldn’t have been comparable. It would be hard to relate them,” says Desimone, who also directs MIT’s McGovern Institute for Brain Research. “This is a project that could not be accomplished by one lab operating in isolation.”
Another targeted project brings together a coalition of seven labs — six based in BCS (professors Evelina Fedorenko, Edward Gibson, Nancy Kanwisher, Roger Levy, Rebecca Saxe, and Joshua Tenenbaum) and one at Dartmouth College (Caroline Robertson) — for a synergistic study of the cognitive, neural, and computational underpinnings of conversational exchanges. The study will integrate the linguistic and non-linguistic aspects of conversational ability in neurotypical adults and children and those with autism.
Fedorenko said the project builds on advances and collaborations from the earlier language Targeted Project she led with Kanwisher.
“Many directions that we started to pursue continue to be active directions in our labs. But most importantly, it was really fun and allowed the PIs [principal investigators] to interact much more than we normally would and to explore exciting interdisciplinary questions,” Fedorenko says. “When Mriganka approached me a few years after the project’s completion asking about a possible new targeted project, I jumped at the opportunity.”
Gibson and Robertson are studying how people align their dialogue, not only in the content and form of their utterances, but using eye contact. Fedorenko and Kanwisher will employ fMRI to discover key components of a conversation network in the cortex. Saxe will examine the development of conversational ability in toddlers using novel MRI techniques. Levy and Tenenbaum will complement these efforts to improve computational models of language processing and conversation.
The newest Targeted Project posits that the immune system can be harnessed to help treat behavioral symptoms of autism. Four labs — three in BCS and one at Harvard Medical School (HMS) — will study mechanisms by which peripheral immune cells can deliver a potentially therapeutic cytokine to the brain. A study by two of the collaborators, MIT associate professor Gloria Choi and HMS associate professor Jun Huh, showed that when IL-17a reaches excitatory neurons in a region of the mouse cortex, it can calm hyperactivity in circuits associated with social and repetitive behavior symptoms. Huh, an immunologist, will examine how IL-17a can get from the periphery to the brain, while Choi will examine how it has its neurological effects. Sur and MIT associate professor Myriam Heiman will conduct studies of cell types that bridge neural circuits with brain circulatory systems.
“It is quite amazing that we have a core of scientists working on very different things coming together to tackle this one common goal,” Choi says. “I really value that.”
Multiple mentors
While SCSB Targeted Projects unify labs around research, the center’s Simons Fellowships unify labs around young researchers, providing not only funding, but a pair of mentors and free-flowing interactions between their labs. Fellows also gain opportunities to inform and inspire their fundamental research by visiting with patients with autism, Sur says.
“The SCSB postdoctoral program serves a critical role in ensuring that a diversity of outstanding scientists are exposed to autism research during their training, providing a pipeline of new talent and creativity for the field,” adds Martin, of the Simons Foundation.
Simons Fellows praise the extra opportunities afforded by additional mentoring. Postdoc Alex Major was a Simons Fellow in Miller’s lab and that of Nancy Kopell, a mathematics professor at Boston University renowned for her modeling of the brain wave phenomena that the Miller lab studies experimentally.
“The dual mentorship structure is a very useful aspect of the fellowship” Major says. “It is both a chance to network with another PI and provides experience in a different neuroscience sub-field.”
Miller says co-mentoring expands the horizons and capabilities of not only the mentees but also the mentors and their labs. “Collaboration is 21st century neuroscience,” Miller says. “Some our studies of the brain have gotten too big and comprehensive to be encapsulated in just one laboratory. Some of these big questions require multiple approaches and multiple techniques.”
Desimone, who recently co-mentored Seng Bum (Michael Yoo) along with BCS and McGovern colleague Mehrdad Jazayeri in a project studying how animals learn from observing others, agrees.
“We hear from postdocs all the time that they wish they had two mentors, just in general to get another point of view,” Desimone says. “This is a really good thing and it’s a way for faculty members to learn about what other faculty members and their postdocs are doing.”
Indeed, the Simons Center model suggests that research can be very successful when it’s collaborative and social.
Creating new skills and new connections with MIT’s Quantitative Methods Workshop
Starting on New Year’s Day, when many people were still clinging to holiday revelry, scores of students and faculty members from about a dozen partner universities instead flipped open their laptops for MIT’s Quantitative Methods Workshop, a jam-packed, weeklong introduction to how computational and mathematical techniques can be applied to neuroscience and biology research. But don’t think of QMW as a “crash course.” Instead the program’s purpose is to help elevate each participant’s scientific outlook, both through the skills and concepts it imparts and the community it creates.
“It broadens their horizons, it shows them significant applications they’ve never thought of, and introduces them to people whom as researchers they will come to know and perhaps collaborate with one day,” says Susan L. Epstein, a Hunter College computer science professor and education coordinator of MIT’s Center for Brains, Minds, and Machines, which hosts the program with the departments of Biology and Brain and Cognitive Sciences and The Picower Institute for Learning and Memory. “It is a model of interdisciplinary scholarship.”
This year 83 undergraduates and faculty members from institutions that primarily serve groups underrepresented in STEM fields took part in the QMW, says organizer Mandana Sassanfar, senior lecturer and director of diversity and science outreach across the four hosting MIT entities. Since the workshop launched in 2010, it has engaged more than 1,000 participants, of whom more than 170 have gone on to participate in MIT Summer Research Programs (such as MSRP-BIO), and 39 have come to MIT for graduate school.
Individual goals, shared experience
Undergraduates and faculty in various STEM disciplines often come to QMW to gain an understanding of, or expand their expertise in, computational and mathematical data analysis. Computer science- and statistics-minded participants come to learn more about how such techniques can be applied in life sciences fields. In lectures; in hands-on labs where they used the computer programming language Python to process, analyze, and visualize data; and in less formal settings such as tours and lunches with MIT faculty, participants worked and learned together, and informed each other’s perspectives.
Photo: Mandana Sassanfar
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And regardless of their field of study, participants made connections with each other and with the MIT students and faculty who taught and spoke over the course of the week.
Hunter College computer science sophomore Vlad Vostrikov says that while he has already worked with machine learning and other programming concepts, he was interested to “branch out” by seeing how they are used to analyze scientific datasets. He also valued the chance to learn the experiences of the graduate students who teach QMW’s hands-on labs.
“This was a good way to explore computational biology and neuroscience,” Vostrikov says. “I also really enjoy hearing from the people who teach us. It’s interesting to hear where they come from and what they are doing.”
Jariatu Kargbo, a biology and chemistry sophomore at University of Maryland Baltimore County, says when she first learned of the QMW she wasn’t sure it was for her. It seemed very computation-focused. But her advisor Holly Willoughby encouraged Kargbo to attend to learn about how programming could be useful in future research — currently she is taking part in research on the retina at UMBC. More than that, Kargbo also realized it would be a good opportunity to make connections at MIT in advance of perhaps applying for MSRP this summer.
“I thought this would be a great way to meet up with faculty and see what the environment is like here because I’ve never been to MIT before,” Kargbo says. “It’s always good to meet other people in your field and grow your network.”
QMW is not just for students. It’s also for their professors, who said they can gain valuable professional education for their research and teaching.
Fayuan Wen, an assistant professor of biology at Howard University, is no stranger to computational biology, having performed big data genetic analyses of sickle cell disease (SCD). But she’s mostly worked with the R programming language and QMW’s focus is on Python. As she looks ahead to projects in which she wants analyze genomic data to help predict disease outcomes in SCD and HIV, she says a QMW session delivered by biology graduate student Hannah Jacobs was perfectly on point.
“This workshop has the skills I want to have,” Wen says.
Moreover, Wen says she is looking to start a machine-learning class in the Howard biology department and was inspired by some of the teaching materials she encountered at QMW — for example, online curriculum modules developed by Taylor Baum, an MIT graduate student in electrical engineering and computer science and Picower Institute labs, and Paloma Sánchez-Jáuregui, a coordinator who works with Sassanfar.
Tiziana Ligorio, a Hunter College computer science doctoral lecturer who together with Epstein teaches a deep machine-learning class at the City University of New York campus, felt similarly. Rather than require a bunch of prerequisites that might drive students away from the class, Ligorio was looking to QMW’s intense but introductory curriculum as a resource for designing a more inclusive way of getting students ready for the class.
Instructive interactions
Each day runs from 9 a.m. to 5 p.m., including morning and afternoon lectures and hands-on sessions. Class topics ranged from statistical data analysis and machine learning to brain-computer interfaces, brain imaging, signal processing of neural activity data, and cryogenic electron microscopy.
“This workshop could not happen without dedicated instructors — grad students, postdocs, and faculty — who volunteer to give lectures, design and teach hands-on computer labs, and meet with students during the very first week of January,” Saassanfar says.
Photo: Mandana Sassanfar
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The sessions surround student lunches with MIT faculty members. For example, at midday Jan. 2, assistant professor of biology Brady Weissbourd, an investigator in the Picower Institute, sat down with seven students in one of Building 46’s curved sofas to field questions about his neuroscience research in jellyfish and how he uses quantitative techniques as part of that work. He also described what it’s like to be a professor, and other topics that came to the students’ minds.
Then the participants all crossed Vassar Street to Building 26’s Room 152, where they formed different but similarly sized groups for the hands-on lab “Machine learning applications to studying the brain,” taught by Baum. She guided the class through Python exercises she developed illustrating “supervised” and “unsupervised” forms of machine learning, including how the latter method can be used to discern what a person is seeing based on magnetic readings of brain activity.
As students worked through the exercises, tablemates helped each other by supplementing Baum’s instruction. Ligorio, Vostrikov, and Kayla Blincow, assistant professor of biology at the University of the Virgin Islands, for instance, all leapt to their feet to help at their tables.
Photo: David Orenstein
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At the end of the class, when Baum asked students what they had learned, they offered a litany of new knowledge. Survey data that Sassanfar and Sánchez-Jáuregui use to anonymously track QMW outcomes, revealed many more such attestations of the value of the sessions. With a prompt asking how one might apply what they’ve learned, one respondent wrote: “Pursue a research career or endeavor in which I apply the concepts of computer science and neuroscience together.”
Enduring connections
While some new QMW attendees might only be able to speculate about how they’ll apply their new skills and relationships, Luis Miguel de Jesús Astacio could testify to how attending QMW as an undergraduate back in 2014 figured into a career where he is now a faculty member in physics at the University of Puerto Rico Rio Piedras Campus. After QMW, he returned to MIT that summer as a student in the lab of neuroscientist and Picower Professor Susumu Tonegawa. He came back again in 2016 to the lab of physicist and Francis Friedman Professor Mehran Kardar. What’s endured for the decade has been his connection to Sassanfar. So while he was once a student at QMW, this year he was back with a cohort of undergraduates as a faculty member.
Michael Aldarondo-Jeffries, director of academic advancement programs at the University of Central Florida, seconded the value of the networking that takes place at QMW. He has brought students for a decade, including four this year. What he’s observed is that as students come together in settings like QMW or UCF’s McNair program, which helps to prepare students for graduate school, they become inspired about a potential future as researchers.
“The thing that stands out is just the community that’s formed,” he says. “For many of the students, it’s the first time that they’re in a group that understands what they’re moving toward. They don’t have to explain why they’re excited to read papers on a Friday night.”
Or why they are excited to spend a week including New Year’s Day at MIT learning how to apply quantitative methods to life sciences data.
The Truth Behind Apex Legends’ Revenant Rework
Apex Legends, like all live-service titles, is no stranger to balancing updates. Weapons and playable characters alike undergo acute surges and declines based on several factors, with the most prevalent being player behavior. Years ago, Pathfinder reigned supreme across casual and competitive matches; his grapple hook-centric mobility and inconsistent hitbox made him an unrivaled duelist until his ability cooldowns and physique were tweaked. Similarly, the Prowler SMG once rivaled its light ammo counterparts before the Selectfire Receiver – a legendary hop-up that converted the weapon’s burstfire to automatic – was removed from the loot pool. These changes, in addition to many others, morphed the meta in significant ways, but one particular update trumped the rest: Revenant’s rework.
The nefarious simulacrum (robots based on humans) was first introduced in Season 4: Assimilation, and despite capturing the fascination of lore enthusiasts and aggression-focused players, his unremarkable pick rate left a lot to be desired. Revenant’s original kit made him a stealthy assassin: a “Stalker” passive that accelerated crouch walk speed/extended climbing height all while silencing his feet, a “Silence” tactical ability that, when flung at unsuspecting adversaries, dealt damage and disabled enemies for a few seconds, and a “Death Totem” ultimate which prevented death or incapacitation by sending injured users back to the Totem’s location with 50HP instead. Despite these interesting skills, Revenant never reached the same popularity heights as other Skirmisher legends.
Apex Legends Season 18 Trailer:
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Apex Legends design director Devan McGuire told me Revenant’s second coming (or “Rebirth,” as some call it) that launched in the aptly named Season 18: Resurrection was implemented to satisfy the core fantasy of the character and carve a space in the meta for him. Simply put, he needed stronger, more viable abilities.
“You played Revenant, sat back, and lobbed shadow balls [or Silence] at people and hoped you hit someone around the corner to maybe make a push on them,” McGuire began. “But even if you did, you had no idea what type of person got affected by it, what the Silence did, and whether or not it was still safe to push. And if you wanted to use your ultimate, you had to coordinate with your team and make sure everyone grouped up to make an effective push. It wasn’t the healthiest thing for the game; we had an Octane-Revenant meta that showed us the dangers of that. So, we looked at it from the ground up and went after a hyper-aggressive/very selfish playstyle and tried to make Revenant fit the game in the way he was meant to. Having that payoff is so rewarding/encouraging when we look back at older legends who have fallen behind or maybe never hit the mark. Not saying that we’re going to be doing a lot of that in the future, but we’ll look for those kinds of opportunities again because they can breathe new life into a character who has sat by the wayside.”
According to Esports Illustrated, after the rework, Revenant became the most selected legend in the game, his pick rate increasing by a whopping 98 percent! Of course, the fun narrative beats that accompanied S18 helped the character appeal to a broader audience. But his new abilities were nothing to scoff at either. These days, the Revenant we know and love can “Shadow Pounce,” or leap a maximum of 50m, to ambush low-health enemies highlighted with the “Assassin’s Instinct” passive. And his new ultimate, “Forged Shadows,” creates a 75HP shroud that blocks damage and slowly regenerates over time. Thankfully (or dreadfully?), Revenant is living up to his namesake; the guy’s a bonafide predator who can initiate and win fights as well as any legend in the frontier.
If, like me, Apex suits your fancy, be sure to check out our list of the top 10 shooters to play right now for more gun-toting options! What other legend reworks would you like to see in Apex Legends? Give us the details below.
How will AI impact the gambling industry?
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