Q&A: Phillip Sharp and Amy Brand on the future of open-access publishing

Q&A: Phillip Sharp and Amy Brand on the future of open-access publishing

Providing open access to scholarly publications is a long-running issue with new developments on the horizon. Last year, the U.S. federal government’s Office of Science and Technology Policy mandated that starting in 2026 publishers must provide open access to publications stemming from federal funding. That provides more impetus for the open-access movement in academia.

Meanwhile, other trends are changing academic publishing, including consolidation of journal titles and provision of access by having authors (and their home institutions) pay for publication costs. With these developments unfolding, a group of MIT scholars is releasing a new white paper about academic open-access publishing. The paper gathers information, identifies outstanding questions, and calls for further research and data to inform policy on the subject.

The group was chaired by Institute Professor Emeritus Phillip A. Sharp, of the Department of Biology and Koch Institute of Integrative Cancer Research, who co-authored the report along with William B. Bonvillian, senior director of special projects at MIT Open Learning; Robert Desimone, director of the McGovern Institute for Brain Research; Barbara Imperiali, the Class of 1922 Professor of Biology; David R. Karger, professor of electrical engineering; Clapperton Chakanetsa Mavhunga, professor of science, technology, and society; Amy Brand, director and publisher of the MIT Press; Nick Lindsay, director for journals and open access at MIT Press; and Michael Stebbins of Science Advisors, LLC.

MIT News spoke with Sharp and Brand about the state of open-access publishing.

Q: What are the key benefits of open access, as you see it?

Amy Brand: As an academic publisher running the MIT Press, we have embraced open access in both books and journals for a long time because it is our mission to support our authors and get their research out into the world. Whether it’s completely removing paywalls and barriers, or keeping prices low, we do whatever we can to disseminate the content that we publish. Even before we were talking about federal policies, this was a priority at the MIT Press.

Phillip Sharp: As a scientist, I’m interested in having my research make the largest impact it can, to help solve some of the challenges of society. And open access, making research available to people around the world, is an important aspect of that. But the quality of research is dependent upon peer review. So, I think open access policies need to be considered and promoted in the context of a very valuable and vigorous peer-review publication process.

Q: What are the key elements of this report?

Brand: The first part of the report is a history of open access, and the second part is a list of questions driving toward evidence-based policy. On the one hand, there are questions such as: How does policy impact the day-to-day work of researchers and their students? What are the impacts on the lab? Other questions have to do with the impacts on the publishing industry. One reason I was invested in doing this is concerns about the impact on nonprofit publishers, on university presses, on scientific societies that publish. Some of the questions we raise have to do with understanding the impact on smaller, nonprofit publishers and ultimately knowing how to protect their viability.

Sharp: The current policies for open access being required by OSTP’s Nelson Memo dramatically change who is paying for publication, where the resources come from for publication. It puts a lot of emphasis on the research institute or other sources to cover that. And that raises another issue in open access: Will this limit publications from researchers at institutes that cannot afford the charge? The scientific community is very international, and the impact of science in many countries is incredibly important. So dealing with the [impact of] open access is something that needs to be developed with evidence and policy.

The report notes that if open access was covered by an institution for all publications at $3,000 per article, MIT’s total cost would be $25 million per year. That’s going to be a challenge. And if it’s a challenge for MIT, it’s going to be an enormous challenge in a number of other places.

Q: What are some additional points about open access that we should keep in mind?

Brand: The Nelson Memo also provides that self-archiving is one of the ways to comply with the policy — which means authors can take an earlier version of an article and put it in an institutional repository. Here at MIT we have the DSpace repository that contains many of the papers that faculty publish. The economics of that are very different, and it’s also a little unclear how that’s going to play out. We recently saw one scientific society decide to implement a charge around that, something the community has never seen before.

But as we essentially have a system that already creates incentives for publishers to increase these article processing charges, the publication charges, there are a lot of questions about how publishers who do high-quality peer review will be sustained, and where that money is going to come from.

Sharp: When you come to the data side of the issue, it’s complicated because of the value of the data itself. It’s important that data is collected and has metadata about the research process that’s been made available to others. It’s also time to talk about this in the academic community.

Q: The report makes clear that there are multiple trends here: consolidation in for-profit publishing, growth of open-access publications, fiscal pressure on university libraries, and now the federal mandate. Complicated as the present may be, it does seem that MIT wants to look ahead on this issue.

Brand: I do think in the publishing community, and certainly in the university press community, we’ve been way out in front on this for a while, and with some of the business models we helped implement and test and create, we’re finding other publishers are following suit and they are interested. But right now, with the new federal policy, most publishers have no choice but to begin asking: What does sustainable high-quality publishing mean if, as a publisher, I have to distribute all or some of this content in open digital form?

Sharp: The purpose of this report is to stimulate that conversation: more numbers, every bit of evidence. Communities have been responsible for the quality of science in different disciplines, and sharing the repsonsbility of peer review is something that motivates a lot of engagement. Sustaining that is important for the discipline. Without that sustainability, there will be slower progress in science, in my opinion.

With a quantum “squeeze,” clocks could keep even more precise time, MIT researchers propose

With a quantum “squeeze,” clocks could keep even more precise time, MIT researchers propose

The practice of keeping time hinges on stable oscillations. In a grandfather clock, the length of a second is marked by a single swing of the pendulum. In a digital watch, the vibrations of a quartz crystal mark much smaller fractions of time. And in atomic clocks, the world’s state-of-the-art timekeepers, the oscillations of a laser beam stimulate atoms to vibrate at 9.2 billion times per second. These smallest, most stable divisions of time set the timing for today’s satellite communications, GPS systems, and financial markets.

A clock’s stability depends on the noise in its environment. A slight wind can throw a pendulum’s swing out of sync. And heat can disrupt the oscillations of atoms in an atomic clock. Eliminating such environmental effects can improve a clock’s precision. But only by so much.

A new MIT study finds that even if all noise from the outside world is eliminated, the stability of clocks, laser beams, and other oscillators would still be vulnerable to quantum mechanical effects. The precision of oscillators would ultimately be limited by quantum noise.

But in theory, there’s a way to push past this quantum limit. In their study, the researchers also show that by manipulating, or “squeezing,” the states that contribute to quantum noise, the stability of an oscillator could be improved, even past its quantum limit.

“What we’ve shown is, there’s actually a limit to how stable oscillators like lasers and clocks can be, that’s set not just by their environment, but by the fact that quantum mechanics forces them to shake around a little bit,” says Vivishek Sudhir, assistant professor of mechanical engineering at MIT. “Then, we’ve shown that there are ways you can even get around this quantum mechanical shaking. But you have to be more clever than just isolating the thing from its environment. You have to play with the quantum states themselves.”

The team is working on an experimental test of their theory. If they can demonstrate that they can manipulate the quantum states in an oscillating system, the researchers envision that clocks, lasers, and other oscillators could be tuned to super-quantum precision. These systems could then be used to track infinitesimally small differences in time, such as the fluctuations of a single qubit in a quantum computer or the presence of a dark matter particle flitting between detectors.

“We plan to demonstrate several instances of lasers with quantum-enhanced timekeeping ability over the next several years,” says Hudson Loughlin, a graduate student in MIT’s Department of Physics. “We hope that our recent theoretical developments and upcoming experiments will advance our fundamental ability to keep time accurately, and enable new revolutionary technologies.”

Loughlin and Sudhir detail their work in an open-access paper published in the journal Nature Communications.

Laser precision

In studying the stability of oscillators, the researchers looked first to the laser — an optical oscillator that produces a wave-like beam of highly synchronized photons. The invention of the laser is largely credited to physicists Arthur Schawlow and Charles Townes, who coined the name from its descriptive acronym: light amplification by stimulated emission of radiation.

A laser’s design centers on a “lasing medium” — a collection of atoms, usually embedded in glass or crystals. In the earliest lasers, a flash tube surrounding the lasing medium would stimulate electrons in the atoms to jump up in energy. When the electrons relax back to lower energy, they give off some radiation in the form of a photon. Two mirrors, on either end of the lasing medium, reflect the emitted photon back into the atoms to stimulate more electrons, and produce more photons. One mirror, together with the lasing medium, acts as an “amplifier” to boost the production of photons, while the second mirror is partially transmissive and acts as a “coupler” to extract some photons out as a concentrated beam of laser light.

Since the invention of the laser, Schawlow and Townes put forth a hypothesis that a laser’s stability should be limited by quantum noise. Others have since tested their hypothesis by modeling the microscopic features of a laser. Through very specific calculations, they showed that indeed, imperceptible, quantum interactions among the laser’s photons and atoms could limit the stability of their oscillations.

“But this work had to do with extremely detailed, delicate calculations, such that the limit was understood, but only for a specific kind of laser,” Sudhir notes. “We wanted to enormously simplify this, to understand lasers and a wide range of oscillators.”

Putting the “squeeze” on

Rather than focus on a laser’s physical intricacies, the team looked to simplify the problem.

“When an electrical engineer thinks of making an oscillator, they take an amplifier, and they feed the output of the amplifier into its own input,” Sudhir explains. “It’s like a snake eating its own tail. It’s an extremely liberating way of thinking. You don’t need to know the nitty gritty of a laser. Instead, you have an abstract picture, not just of a laser, but of all oscillators.”

In their study, the team drew up a simplified representation of a laser-like oscillator. Their model consists of an amplifier (such as a laser’s atoms), a delay line (for instance, the time it takes light to travel between a laser’s mirrors), and a coupler (such as a partially reflective mirror).

The team then wrote down the equations of physics that describe the system’s behavior, and carried out calculations to see where in the system quantum noise would arise.

“By abstracting this problem to a simple oscillator, we can pinpoint where quantum fluctuations come into the system, and they come in in two places: the amplifier and the coupler that allows us to get a signal out of the oscillator,” Loughlin says. “If we know those two things, we know what the quantum limit on that oscillator’s stability is.”

Sudhir says scientists can use the equations they lay out in their study to calculate the quantum limit in their own oscillators.

What’s more, the team showed that this quantum limit might be overcome, if quantum noise in one of the two sources could be “squeezed.” Quantum squeezing is the idea of minimizing quantum fluctuations in one aspect of a system at the expense of proportionally increasing fluctuations in another aspect. The effect is similar to squeezing air from one part of a balloon into another.

In the case of a laser, the team found that if quantum fluctuations in the coupler were squeezed, it could improve the precision, or the timing of oscillations, in the outgoing laser beam, even as noise in the laser’s power would increase as a result.

“When you find some quantum mechanical limit, there’s always some question of how malleable is that limit?” Sudhir says. “Is it really a hard stop, or is there still some juice you can extract by manipulating some quantum mechanics? In this case, we find that there is, which is a result that is applicable to a huge class of oscillators.”

This research is supported, in part, by the National Science Foundation.

AWS and NVIDIA Announce New Strategic Partnership

In a notable announcement at AWS re:Invent, Amazon Web Services (AWS) and NVIDIA unveiled a major expansion of their strategic collaboration, setting a new benchmark in the realm of generative AI. This partnership represents a pivotal moment in the field, marrying AWS’s robust cloud infrastructure with…

The role of blockchain in IoT security – CyberTalk

The role of blockchain in IoT security – CyberTalk

By Zac Amos, Features Editor, Rehack.com.

While many people are aware of blockchain technology on account of cryptocurrency, they are unfamiliar with the fact that it can serve as a valuable solution for securing IoT devices. Since blockchains rely on a decentralized system, they are essentially very difficult to compromise.

This can make blockchains a strong choice for enhancing IoT security. In this article, learn more about blockchain technology and how it can play a crucial role in making IoT devices more secure.

What is blockchain technology?

As the name suggests, blockchain technology is comprised of different blocks of information connected through a chain. One of the most famous examples of this type of technology is cryptocurrency (such as Bitcoin). Blockchains are very secure and are incredibly difficult to tamper with.

Once information is stored on a blockchain, changing it becomes a complex process. To understand blockchain technology, it is essential to know that each block contains three things:

  • Data: As mentioned, each block is comprised of information. The type of data that it holds depends on the type of blockchain technology in-use.
  • Hash: A hash is essentially a way to identify it and is unique to that block. Think of an identification number or a fingerprint. If the information inside changes, the block’s identity will also change, meaning it is no longer the same block.
  • Previous block’s hash: This is the hash — identification number — of the last block in the chain. This acts like a reference of sorts.

The way in which these parts operate together is one reason as to why they are so secure. However, as technology has evolved over the years, in-built security alone is not enough to deter hackers.

These blocks also have another factor called proof of work. This procedure slows down the generation of new blocks. This process takes time. If one block is hacked and the information is altered, all of the corresponding blocks will also need to be changed.

The last aspect of why blockchain technology is so secure is that it relies on a peer-to-peer (P2P) network to manage and control the chain, decentralized. This creates a consensus on the network and verifies whether or not the blocks are legitimate.

How can blockchain technology help with securing IoT devices?

The idea behind consumer-grade IoT devices is that everyday objects, including home appliances, can  connect to the internet. This allows for many unique features and functionalities.

According to research, there are about 50 billion IoT devices in circulation. The problem is that these objects lack security. Currently, many IoTs are susceptible to hacking, which can compromise an entire network.

However, if they become blockchain IoT devices, they are much more challenging to hack. This process will make it almost impossible for cyber criminals to exploit a single vulnerability. The reason for this is that blockchain technology is decentralized.

In other words, it does not rely on one entity to verify that everything is correct, but rather, it relies on an entire network. This process will increase the privacy of the data stored on these devices and make compromising it a challenge. Here are a few more specific ways blockchain tech can improve IoT security.

Smart contracts

First, blockchain technology can better secure IoT devices with the help of smart contracts. Smart contracts are algorithms that run on blockchains if specific requirements are reached.

For example, in the case of IoT devices, these algorithms can look for authorized users and provide access to them. Additionally, they can also limit what authorized users can do once they obtain access to a device or network.

This process will only allow legitimate users to control IoT devices and access personal information. With smart contracts, hackers will have a much more difficult time trying to compromise the device’s security than otherwise.

Blockchain cryptography

IoT devices connect and communicate with each other. Blockchain cryptography can make communications more secure. These networks rely on private and public keys. The chain uses these keys to decrypt and encrypt the communications.

Blockchain digital signatures can be implemented to verify that it is an authorized device, stopping cyber criminals from compromising the object and obtaining access. This process can serve as a crucial component in blockchain IoT security.

Record past interactions

Blockchain IoT can create a list of past interactions with the device. This record of information makes it extremely difficult for cyber criminals to exploit the security.

The blockchain can use the recorded information to prevent threat actors from accessing the device. It also prevents them from making changes that compromise a given device’s security.

Blockchains securing IoT devices

Consumers and cyber security professionals alike often find IoT devices difficult to secure. However, with blockchain technology, this could change. Factors that could help make these devices more secure include cryptography, recording device interactions, smart contracts and the blockchain’s decentralized network. With all of the security advantages this offers for IoT devices, blockchain could become widely implemented in the future.

For more cyber security insights from Zac Amos, please see our past coverage. Lastly, to receive timely cyber security insights, exclusive interviews, and cutting-edge analyses, please sign up for the cybertalk.org newsletter.

Pushing the frontiers of art and technology with generative AI

Pushing the frontiers of art and technology with generative AI

Many people are scrambling to predict how AI will impact society. But living in a world of ubiquitous computing has already changed us in ways we might not fully appreciate. Generative AI-aided art — like all art — can be a powerful tool to visualize those changes, broaden our perceptions, and inspire us all.

That was the message of a keynote talk by artist Refik Anadol on the first day of MIT’s Generative AI Week. Anadol walked the audience through his studio’s body of work, which includes public art displays and other digital creations that visualize human and machine intelligence around the world.

“I’m inspired by the idea of how our perceptions of physical and virtual worlds are transforming us,” Anadol explained to a packed Kresge Auditorium.

The presentation was part of a full day of events that also included panels on generative AI’s potential applications and impact on society, with opening presentations from iRobot founder Rodney Brooks and MIT President Sally Kornbluth. The goal of the week of events is to bring together MIT’s community to spotlight insights from MIT’s researchers, stimulate thoughtful analysis, and engage in critical dialogues on the implications and possibilities of generative AI. Other days feature symposia on generative AI and education, creativity, and commerce.

Anadol’s work uses generative AI-based aesthetics on top of data from things like real-time weather data, changing climates and landscapes, historic architecture, and more. Some of his projects even incorporate AI-generated smells. A growing portion of Anadol’s work uses generative AI to visualize data and the physical world in new ways and change people’s perspectives of their surroundings and themselves. Part of that work leverages hallucinations — or creations by machines that are often a source of frustration for computer scientists.

“It’s really inspiring to see how we can reconstruct this information through AI’s hallucinations to compose a new form of art-making and space-making,” Anadol said.

For one of Anadol’s projects, he combined a dataset of approximately 100 million images of coral reefs with generative AI and visual art techniques to show vibrant, morphing coral images based on actual corals found in nature. The project sought to raise awareness of climate change by emphasizing the importance of coral preservation.

Another project Anadol discussed used real-time climate data in Barcelona to generate an array of digital patterns that were projected onto the famous Casa Batlló created by renowned architect Antoni Gaudí. The display was later sold as a nonfungible digital token, or NFT, with a portion of proceeds donated to institutions that work with neurodiverse adults and children.

“I believe light, data, and AI, when connected, can create a new form of architecture, which I call sensing architecture,” Anadol explained.

A third project was sparked by Anadol’s experience watching his uncle struggle with Alzheimer’s disease. The experience led the artist to consider new ways of visualizing neurological data in a way that provokes fundamental questions about the human brain and mental health. Anadol later received permission from patients to use their datasets, collected by electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), to create a multisensory, immersive art exhibit and to promote mental health through art.

“Our fundamental goal is to find dreams of reality and concepts of reality,” Anadol said. “It’s about trying to find new ways of speculating, and I think the future of imagination, with neural networks and the integration of materials, [offers] a lot of room for creatives to recombine and explore connections between humanity.”

Through each of the projects, Anadol seeks to enhance our ability to express ourselves and find meaning.

“I believe by using AI, whether generative or otherwise, we have the opportunity to find the language of humanity,” Anadol said.

Speaking in front of a large screen displaying each of the projects, Anadol’s presentation gave the audience vivid examples of how generative AI technology is changing the world of art. Speaking in roundtable discussions after the talk, MIT professors gave more examples of how the technology could transform other fields, from transportation and manufacturing to health care, finance, and music.

One of those presenters was Cathy Wu, an assistant professor in the Department of Civil and Environmental Engineering. Wu described how generative AI could be used to create synthetic data to help prepare self-driving cars for rare events, better model traffic patterns, and improve zoning regulations to ease housing shortages.

In conducting her research, Wu said she was surprised to find so many promising applications for generative AI, and said she’s cautiously optimistic it will contribute to some of the transportation industry’s hardest problems.

“Longstanding issues are longstanding issues, and generative AI by itself will not move the needle, but it adds one very powerful tool to the toolbox,” Wu said. “I’m very encouraged that for some of these challenges, generative AI might just give us the push we need to make an impact.”

Another speaker was Marzyeh Ghassemi, an assistant professor in the Department of Electrical Engineering and Computer Science. Ghassemi showed how some models can perpetuate unequal outcomes by recommending African Americans exhibiting violent behavior be sent to jail while recommending their white counterparts be sent to a hospital.

Still, Ghassemi showed that the way decision makers interact with models ultimately determines if they exacerbate biases.

“Maybe we can get to safe integration [of these tools] without perfect models, as some other industries like aviation have done,” Ghassemi said. “If we want to move forward with AI in health care, we need to recognize that this is an ongoing process and it’s going to require diverse data and [consideration of diverse] needs.”

All of the examples presented in the afternoon described a technology whose ultimate effect on society should be determined by the people it impacts most.

“The impact of bringing generative AI to different fields is captivating,” Anadol said toward the end of his presentation. “By co-creating with musicians, other artists, and the public, there’s a beautiful, positive future to explore.”

What does the future hold for generative AI?

What does the future hold for generative AI?

Speaking at the “Generative AI: Shaping the Future” symposium on Nov. 28, the kickoff event of MIT’s Generative AI Week, keynote speaker and iRobot co-founder Rodney Brooks warned attendees against uncritically overestimating the capabilities of this emerging technology, which underpins increasingly powerful tools like OpenAI’s ChatGPT and Google’s Bard.

“Hype leads to hubris, and hubris leads to conceit, and conceit leads to failure,” cautioned Brooks, who is also a professor emeritus at MIT, a former director of the Computer Science and Artificial Intelligence Laboratory (CSAIL), and founder of Robust.AI.

“No one technology has ever surpassed everything else,” he added.

The symposium, which drew hundreds of attendees from academia and industry to the Institute’s Kresge Auditorium, was laced with messages of hope about the opportunities generative AI offers for making the world a better place, including through art and creativity, interspersed with cautionary tales about what could go wrong if these AI tools are not developed responsibly.

Generative AI is a term to describe machine-learning models that learn to generate new material that looks like the data they were trained on. These models have exhibited some incredible capabilities, such as the ability to produce human-like creative writing, translate languages, generate functional computer code, or craft realistic images from text prompts.

In her opening remarks to launch the symposium, MIT President Sally Kornbluth highlighted several projects faculty and students have undertaken to use generative AI to make a positive impact in the world. For example, the work of the Axim Collaborative, an online education initiative launched by MIT and Harvard, includes exploring the educational aspects of generative AI to help underserved students.

The Institute also recently announced seed grants for 27 interdisciplinary faculty research projects centered on how AI will transform people’s lives across society.

In hosting Generative AI Week, MIT hopes to not only showcase this type of innovation, but also generate “collaborative collisions” among attendees, Kornbluth said.

Collaboration involving academics, policymakers, and industry will be critical if we are to safely integrate a rapidly evolving technology like generative AI in ways that are humane and help humans solve problems, she told the audience.

“I honestly cannot think of a challenge more closely aligned with MIT’s mission. It is a profound responsibility, but I have every confidence that we can face it, if we face it head on and if we face it as a community,” she said.

While generative AI holds the potential to help solve some of the planet’s most pressing problems, the emergence of these powerful machine learning models has blurred the distinction between science fiction and reality, said CSAIL Director Daniela Rus in her opening remarks. It is no longer a question of whether we can make machines that produce new content, she said, but how we can use these tools to enhance businesses and ensure sustainability. 

“Today, we will discuss the possibility of a future where generative AI does not just exist as a technological marvel, but stands as a source of hope and a force for good,” said Rus, who is also the Andrew and Erna Viterbi Professor in the Department of Electrical Engineering and Computer Science.

But before the discussion dove deeply into the capabilities of generative AI, attendees were first asked to ponder their humanity, as MIT Professor Joshua Bennett read an original poem.

Bennett, a professor in the MIT Literature Section and Distinguished Chair of the Humanities, was asked to write a poem about what it means to be human, and drew inspiration from his daughter, who was born three weeks ago.

The poem told of his experiences as a boy watching Star Trek with his father and touched on the importance of passing traditions down to the next generation.

In his keynote remarks, Brooks set out to unpack some of the deep, scientific questions surrounding generative AI, as well as explore what the technology can tell us about ourselves.

To begin, he sought to dispel some of the mystery swirling around generative AI tools like ChatGPT by explaining the basics of how this large language model works. ChatGPT, for instance, generates text one word at a time by determining what the next word should be in the context of what it has already written. While a human might write a story by thinking about entire phrases, ChatGPT only focuses on the next word, Brooks explained.

ChatGPT 3.5 is built on a machine-learning model that has 175 billion parameters and has been exposed to billions of pages of text on the web during training. (The newest iteration, ChatGPT 4, is even larger.) It learns correlations between words in this massive corpus of text and uses this knowledge to propose what word might come next when given a prompt.

The model has demonstrated some incredible capabilities, such as the ability to write a sonnet about robots in the style of Shakespeare’s famous Sonnet 18. During his talk, Brooks showcased the sonnet he asked ChatGPT to write side-by-side with his own sonnet.

But while researchers still don’t fully understand exactly how these models work, Brooks assured the audience that generative AI’s seemingly incredible capabilities are not magic, and it doesn’t mean these models can do anything.

His biggest fears about generative AI don’t revolve around models that could someday surpass human intelligence. Rather, he is most worried about researchers who may throw away decades of excellent work that was nearing a breakthrough, just to jump on shiny new advancements in generative AI; venture capital firms that blindly swarm toward technologies that can yield the highest margins; or the possibility that a whole generation of engineers will forget about other forms of software and AI.

At the end of the day, those who believe generative AI can solve the world’s problems and those who believe it will only generate new problems have at least one thing in common: Both groups tend to overestimate the technology, he said.

“What is the conceit with generative AI? The conceit is that it is somehow going to lead to artificial general intelligence. By itself, it is not,” Brooks said.

Following Brooks’ presentation, a group of MIT faculty spoke about their work using generative AI and participated in a panel discussion about future advances, important but underexplored research topics, and the challenges of AI regulation and policy.

The panel consisted of Jacob Andreas, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS) and a member of CSAIL; Antonio Torralba, the Delta Electronics Professor of EECS and a member of CSAIL; Ev Fedorenko, an associate professor of brain and cognitive sciences and an investigator at the McGovern Institute for Brain Research at MIT; and Armando Solar-Lezama, a Distinguished Professor of Computing and associate director of CSAIL. It was moderated by William T. Freeman, the Thomas and Gerd Perkins Professor of EECS and a member of CSAIL.

The panelists discussed several potential future research directions around generative AI, including the possibility of integrating perceptual systems, drawing on human senses like touch and smell, rather than focusing primarily on language and images. The researchers also spoke about the importance of engaging with policymakers and the public to ensure generative AI tools are produced and deployed responsibly.

“One of the big risks with generative AI today is the risk of digital snake oil. There is a big risk of a lot of products going out that claim to do miraculous things but in the long run could be very harmful,” Solar-Lezama said.

The morning session concluded with an excerpt from the 1925 science fiction novel “Metropolis,” read by senior Joy Ma, a physics and theater arts major, followed by a roundtable discussion on the future of generative AI. The discussion included Joshua Tenenbaum, a professor in the Department of Brain and Cognitive Sciences and a member of CSAIL; Dina Katabi, the Thuan and Nicole Pham Professor in EECS and a principal investigator in CSAIL and the MIT Jameel Clinic; and Max Tegmark, professor of physics; and was moderated by Daniela Rus.

One focus of the discussion was the possibility of developing generative AI models that can go beyond what we can do as humans, such as tools that can sense someone’s emotions by using electromagnetic signals to understand how a person’s breathing and heart rate are changing.

But one key to integrating AI like this into the real world safely is to ensure that we can trust it, Tegmark said. If we know an AI tool will meet the specifications we insist on, then “we no longer have to be afraid of building really powerful systems that go out and do things for us in the world,” he said.

The Challenging Climb To Make Jusant

Jusant is all about climbing a mountain, and Don’t Nod’s superb execution of this premise has propelled this small, meditative adventure to stand among the year’s finest titles. In my review, I wrote that the game’s “ingenious climbing system, beautiful art direction, and intriguing world-building, inching toward the top is worth the effort.” That effort can be attributed to Don’t Nod honing in on the game’s central mechanic, climbing, and building a fascinating world and lore around it. I spoke to the game’s lead designer, Sofiane Saheb, and art director, Edouard Caplain, to better understand how Don’t Nod spent over three years bringing Jusant to life. 

Caplain statesJusant’s development began after Don’t Nod finished work on Life is Strange 2. After releasing another narrative-heavy experience with heavy, often depressing themes, the small team was eager to tackle something more lighthearted, smaller, and, most of all, different from the studio’s usual output. Don’t Nod turned to a few games for inspiration, the primary title being Journey. The 2012 adventure’s whimsical, enigmatic vibe and singular focus – walking to a mountain – provided a great example of the atmosphere and scope the studio aimed to achieve.

“Journey…it’s kind of a dreamy kind of game, it’s not reality,” says Caplain. “Everything is kind of chill…and it’s very positive. And next to the idea of climbing a big tower, we also wanted to make a game which [has] a good positive vibe. [Life is Strange] has some very heavy, heavy subjects which are hard to treat, and which are kind of heavy to even play. I wanted to make something much more lighter, much more positive.” 

The Challenging Climb To Make Jusant

Don’t Nod drew atmospheric and mechanical inspiration from games such as Shadow of Colossus and Grow Up, but it also turned to literature. Saheb tells me Jusant’s premise is partly inspired by La Horde du Contrevent (The Backwind Horde), a French book written by author Alain Damasio, who also happens to be one of Don’t Nod’s founders. The book centers on a group of specialized explorers who embark on a search for the origin of the wind in an unforgiving landscape. Jusant centers on the protagonist’s search for water in a world that has mysteriously lost it, so the parallel is clear.

Saheb and Caplain state that Don’tNod developed Jusant’s climbing mechanics first, then formed the simple pitch of having players scale a tall tower. Everything else, such as the narrative, lore, and art direction, spun out of this core idea. Even though the mechanics lean towards realism, no one on the team had any real climbing experience at the start of development. It wasn’t until the game was in production that some designers began learning how to climb, which provided helpful insight into best/worst practices. But beyond this, Don’t Nod didn’t consult professional climbers because the goal was never to make Jusant a fully realistic simulation of mountain climbing. “We tried to have [a] balance between some arcade-y feels and something more involved,” says Saheb. He cites Getting Over It With Bennett Foddy as an example the team examined to achieve the right balance of simplicity and complexity in its climbing mechanics. 

This focus resulted in Don’t Nod cutting ideas that, while cool on paper, proved too mechanically cumbersome. Saheb tells me that at one point, players could ride and control the beetle that appears after players reach the giant solar dial at the end of chapter three. The creature would whisk players to the caves in chapter four, but introducing totally new mechanics to facilitate this interrupted the game’s delicate pacing. Your watery companion Ballast, whose echo pulse transforms organic elements to players’ advantage, once had an ability that let players aim and fire a ball of its energy to trigger distant objects. After toying with this feature, the team concluded that climbing and shooting was too complicated and abandoned the idea. Saheb, in particular, took nailing the pacing and balancing very seriously, and as a result, it’s one of the elements he’s most proud of in the final product. 

jusant climbing gameplay

Jusant’s warm, flat, colorful palette and smooth geometry were another inspiration spurred by Journey, and Caplain refers to it as “simplified reality.” Landing on the look was a mission to ensure the environment clearly communicated climbing points such as ledges and handholds without pointing them out too obviously, which would take away the problem-solving process. Don’t Nod avoided the usual eye-catching platforming tricks, such as highlighting climbing points with something artificial like paint, and instead utilized more natural color shades to make important elements pop. Interestingly, despite the colorful look and stylized yet simplified graphics, Caplain states the team was adamant the game not look like a cartoon. 

“Usually, when you simplify things, you can stylize it so it looks for kids and everything,” Caplain says “And we didn’t want to do a game that looks [like it’s] for kids.”

Setting Jusant in a fictional world allowed the team to get creative when it came to designing its desert environment, a biome that has the potential to be very one note from a presentational standpoint. It could use a variety of colors instead of the expected yellows, oranges, and reds while also populating areas with playful elements such as cute furry critters or bubble-like grass that float away when players step on them. The game is technically post-apocalyptic, which typically equates to a more dreary presentation, so Caplain says this is why the presence of nature, from the strange flora to the wildlife, was an important element of maintaining a sense of uplifting whimsy.  

From the beginning, Don’t Nod wanted Jusant’s story to be open to interpretation. Much of its storytelling is told indirectly through diaries and lore notes players must largely seek out for themselves. The protagonist doesn’t emote beyond grunts; all you know about them is they’re a traveler, a clearly skilled climber, and, somehow, have a strange magical pet. 

That leaves a lot of room for players’ imaginations to run wild, and because of this, Caplain says the team doesn’t have the answers to those questions either. “It’s just a traveler,” says Caplain. “The main point was a character you can easily relate to. Like, he had to be very bland so you can imagine it’s you and that you could be this protagonist.” Despite that somewhat disappointing answer, Caplain and Sahed are visibly amused when I share my theories about the protagonist’s origins and purpose. They’re just glad that people care enough to theorize in the first place.

Jusant has been well-received since its launch, garnering an 83 critical response on Metacritic. That’s an impressive feat for a more experimental title released in a year stacked with so many big triple-A hits, and it arrived at the end of a very crowded October, no less. For Saheb and Caplain, who have worked at Don’t Nod for a decade, the response has clearly moved them

“We are so happy,” says Caplain. “It’s overwhelming for us. It is very hard to release your game with all those studios releasing huge games. We were so happy.”

Don’t Nod recently released an update that added new approachability and accessibility options. That includes playing without the stamina meter and climbing using only the joysticks instead of gripping with the triggers. These helpful tools make an already chill experience even easier to grasp for those who need or desire it, which means more people are able to try their hand at reaching Jusant’s summit. 

Saheb and Caplain say they’ve learned a lot of lessons making Jusant, but whether or not they’ve walked away with a newfound desire to scale a real mountain themselves remains to be seen. 

“I had a little son in between, so no time for that,” Saheb laughs.

The Big List Of Upcoming Video Game Remakes

The Big List Of Upcoming Video Game Remakes

Remakes tend to be more exciting than remasters because the improvements often go beyond mere bumps in resolution or framerate. At best, studios reimagine classic experiences in exciting new ways, sand away rough edges, and somehow retain the intangible x-factors that made fans fall in love with these titles in the first place. At the very least, remakes offer a great way to play antiquated or less accessible experiences on modern hardware. 

The remake boom has been in full swing in recent years to the point that it’s starting to get tough to keep track of all the projects in the works. Thankfully, we’ve gathered as many of the announced remakes (not remasters) that we could find and gathered them in one neat list, arranged chronologically by release window. This will be an evolving list that will be updated as new remakes are announced and released, so be sure to keep an eye on it over the coming months. 

Zephyr: Direct Distillation of LLM Alignment

The ability and performance of smaller, open large language models have advanced significantly in recent years, and we have witnessed the progress from early GPT-2 models to more compact, accurate, and effective LLM frameworks that make use of a considerably larger amount of tokens that the…