With research projects - including one that recently received a $1.3 million grant - and an upcoming course, Prof. Robert Soul is looking at new ways to make computing more sustainable.

Working with Prof. Noa Zilberman from Oxford University, Soul has received a grant jointly funded by the United Kingdoms Engineering and Physical Sciences Research Council (EPSRC) and United States National Science Foundation (NSF) for work that aims to reduce the energy consumption of computing. Specifically, it sets its sights on computer networks, which consume an estimated one-and-a-half times the energy of all data centers, according to some reports. In contrast to other large scale computer infrastructures, accounting for the carbon emissions of the network is extremely hard.

The project is designed to collect information about the power consumption of network devices, specifically the computer hardware involved in connecting users to computer networks. This includes switches, which connect different computers together, and the network interface cards in computers or servers that connect users to the network. Traditional computer networks try to optimize the paths to reduce latency and achieve the fastest response possible.

But what we're hypothesizing is that you could actually instead choose paths that would result in the lowest amount of power consumed, or maybe the greenest path, said Soul, associate professor of computer science & electrical engineering. We want to measure how much power they are consuming and the quality of the power that they're consuming. For example, did they come from a green energy source? So were collecting the data that would allow you to make these informed decisions, and designing the network algorithms that would change a routing behavior in order to reduce the overall carbon footprint.

One possible way to do that is to develop systems that send computer traffic to a path that consumes energy from a green energy source. Another is a system that chooses a path that minimizes overall power consumption.

Another component to Souls work in this area is a collaboration with Prof. Rajit Manohar, the John C. Malone Professor of Electrical Engineering and Computer Science. Theyre developing network hardware that can go into idle mode when its inactive, very much like some cars with engines that automatically turn off at red lights.

There's a problem with current network hardware in that its not really able to go into idle mode because a part of it is always running to see if information is arriving, he said. So Rajit and I have been looking at whether we can design hardware devices - a new network switch - that would consume energy in proportion to the amount of traffic that it's seeing. And if it did see less traffic, it would go into idle mode

Soul is also co-teaching a course next year on sustainable computing with Dr. Eve Schooler, an IEEE Fellow and Yale alum. The course, they said, takes a broader view of the subject.

We're trying to do more of a survey of different approaches to improving the carbon efficiency of computer networks in general, Soul said. But even beyond that, we're also looking at a broader discussion at the policy level, where the intersection of sustainability and technology meet.

Schooler said the course will cover a large swath of topics. For instance, it might explore issues like the role that computing can play in the Intergovernmental Panel on Climate Change or how large institutions perform carbon accounting.

We'll also focus on networking, and on topics around the streaming infrastructure, the content distribution networks, she said. Other topics will be about large algorithms, like large language models - the ChatGPTs of the world - and Bitcoin or some of the crypto currencies that are also large consumers of electricity.

Read more:

Making Computing Sustainable, With Help from NSF Grant - Yale University

After spending many hours grinding through my work, theres nothing I find more refreshing than opening up my laptop and scrolling through Reddit in the evening. My 2022 Reddit Recap affirmed that I spent the most time scrolling through the Northeastern subreddit, which makes sense considering how much I use it to navigate my academic journey.

Besides all the sh*t posts and yet another entertaining complaint about finding rats in an apartment, I take advantage of the fact that many Northeastern students go on Reddit to describe their experiences there. Hence, when building my schedule or figuring out which professors best align with how I learn, I read through subreddit posts meticulously.

Even though I use Reddit to, supposedly, relieve my stress about the unknowns of my college career, I have come to a point where I got so caught up in the opinions of other students about various classes that I lost my sense of identity and confidence about the path I could pursue in college. I let my potential be defined by the experiences of people on a social media platform.

Particularly, when I was stressed about which major I wanted to pursue after deciding that a path toward the medical field would be too stressful, I decided to browse through Reddit to learn about peoples experiences with other majors at Northeastern. If youre an avid visitor of the Northeastern subreddit, you would know that there are countless posts about peoples frustrations with Northeasterns computer science classes. The idea of spending at least 10 hours of work on classes with unsupportive professors, combined with the fact that computer science did not come naturally to me in high school, made me immediately dismiss the major as an option.

I didnt even bother to talk to people in real life about their experiences with the major, let alone discuss the major with an academic advisor from Khoury College of Computer Sciences. I had let the fear I felt from seeing many people complain about Fundamentals of Computer Science 1, or Fundies, on Reddit prevent me from potentially pursuing the field. In high school, there was no subreddit to prevent me from taking four AP classes during my senior year. I had a slight glimmer of confidence to get me through that pursuit.

Looking back at my initial doubts about Fundies, I realize I shouldve been more open toward my friend from another school who affirmed I would be fine, considering my strong work ethic. I consulted with my friend, a computer science and behavioral neuroscience major, over the summer about what she thought about the Fundies posts on Reddit, and talking to her just reaffirmed the fact that people tend to only post online only if they have strong opinions.

It seems that people tend to post on Reddit, and even TRACE, another online resource I spend too much time stressing over, if they have extremely positive or (more likely) extremely negative experiences with a class or professor. Reddit and TRACE are double-edged swords. On one hand, they are accessible resources on which to gather up-to-date information about classes Im interested in from a large pool of students. On the other hand, the opinions contained in those resources are biased and seem to often come out of spitefulness.

As a data science and psychology combined major, I remember feeling distraught when I learned I had to take Discrete Structures. Discrete is another computer science class that gets complained about on Reddit. I mentally prepared myself to receive a bad grade in the class but found that I was able to be much more successful in the class than expected. I definitely do not think that Discrete is an easy class. Still, I found it manageable if youre willing to review the lecture videos as needed, go to office hours as early and as much as needed, attend recitations and generally just work hard and responsibly.

After completing Discrete, I truly started to contemplate what my life would have been like if I had chosen to become a computer science major instead. I adore data science, but sometimes I do wonder what it would have been like if I had been a computer science and music technology combined major instead.

Northeasterns Reddit community does have its empowering moments. About a month ago, a Northeastern student posted alleging the school had commented out code that would have enabled students to automatically donate their leftover meal swipes for a week. I also often see posts about people expressing mental health concerns that receive heartwarming and reassuring comments. And the infinite comedic posts complaining about the quality of Snells study environment always release any tensions I feel after a rough workday.

Social media sites such as Reddit can be fun and even uplifting, but its important to establish boundaries with them and not let them control the trajectory of your life.

Even though Im fortunate enough to be majoring in a field I can see myself enjoying in the future, I worry for other people who have the potential to excel at computer science, or other fields with a reputation for being difficult at Northeastern, but end up letting biased online opinions deteriorate their confidence.

Reddit and TRACE are accessible resources to gauge the difficulty of a class, but just because an overwhelming amount of students complain about a class does not mean you wont turn out fine. Northeastern is a school that encourages students to engage in exploratory learning, and I dont wish for peoples journeys in this school to be tailored by what they have seen on the internet by other students. Talk to your friends, advisors and other in-person resources if youre worried about what kind of path you want to pursue at this school. Once youve looked at a post, after youve read it, try not to dwell on it.

Jethro R. Lee is a third-year data science and psychology combined major. He can be reached at [emailprotected].

See the rest here:

Op-ed: Remember moderate opinions exist but are often concealed ... - The Huntington News

With 3D inkjet printing systems, engineers can fabricate hybrid structures that have soft and rigid components, like robotic grippers that are strong enough to grasp heavy objects but soft enough to interact safely with humans.

These multimaterial 3D printing systems utilize thousands of nozzles to deposit tiny droplets of resin, which are smoothed with a scraper or roller and cured with UV light. But the smoothing process could squish or smear resins that cure slowly, limiting the types of materials that can be used.

Researchers from MIT, the MIT spinout Inkbit, and ETH Zurich have developed a new 3D inkjet printing system that works with a much wider range of materials. Their printer utilizes computer vision to automatically scan the 3D printing surface and adjust the amount of resin each nozzle deposits in real-time to ensure no areas have too much or too little material.

Since it does not require mechanical parts to smooth the resin, this contactless system works with materials that cure more slowly than the acrylates which are traditionally used in 3D printing. Some slower-curing material chemistries can offer improved performance over acrylates, such as greater elasticity, durability, or longevity.

In addition, the automatic system makes adjustments without stopping or slowing the printing process, making this production-grade printer about 660 times faster than a comparable 3D inkjet printing system.

The researchers used this printer to create complex, robotic devices that combine soft and rigid materials. For example, they made a completely 3D-printed robotic gripper shaped like a human hand and controlled by a set of reinforced, yet flexible, tendons.

Our key insight here was to develop a machine-vision system and completely active feedback loop. This is almost like endowing a printer with a set of eyes and a brain, where the eyes observe what is being printed, and then the brain of the machine directs it as to what should be printed next, says co-corresponding author Wojciech Matusik, a professor of electrical engineering and computer science at MIT who leads the Computational Design and Fabrication Group within the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

He is joined on the paper by lead author Thomas Buchner, a doctoral student at ETH Zurich, co-corresponding author Robert Katzschmann PhD 18, assistant professor of robotics who leads the Soft Robotics Laboratory at ETH Zurich; as well as others at ETH Zurich and Inkbit. The research appears today in Nature.

Contact free

This paper builds off a low-cost, multimaterial 3D printer known as MultiFab that the researchers introduced in 2015. By utilizing thousands of nozzles to deposit tiny droplets of resin that are UV-cured, MultiFab enabled high-resolution 3D printing with up to 10 materials at once.

With this new project, the researchers sought a contactless process that would expand the range of materials they could use to fabricate more complex devices.

They developed a technique, known as vision-controlled jetting, which utilizes four high-frame-rate cameras and two lasers that rapidly and continuously scan the print surface. The cameras capture images as thousands of nozzles deposit tiny droplets of resin.

The computer vision system converts the image into a high-resolution depth map, a computation that takes less than a second to perform. It compares the depth map to the CAD (computer-aided design) model of the part being fabricated, and adjusts the amount of resin being deposited to keep the object on target with the final structure.

The automated system can make adjustments to any individual nozzle. Since the printer has 16,000 nozzles, the system can control fine details of the device being fabricated.

Geometrically, it can print almost anything you want made of multiple materials. There are almost no limitations in terms of what you can send to the printer, and what you get is truly functional and long-lasting, says Katzschmann.

The level of control afforded by the system enables it to print very precisely with wax, which is used as a support material to create cavities or intricate networks of channels inside an object. The wax is printed below the structure as the device is fabricated. After it is complete, the object is heated so the wax melts and drains out, leaving open channels throughout the object.

Because it can automatically and rapidly adjust the amount of material being deposited by each of the nozzles in real time, the system doesnt need to drag a mechanical part across the print surface to keep it level. This enables the printer to use materials that cure more gradually, and would be smeared by a scraper.

Superior materials

The researchers used the system to print with thiol-based materials, which are slower-curing than the traditional acrylic materials used in 3D printing. However, thiol-based materials are more elastic and dont break as easily as acrylates. They also tend to be more stable over a wider range of temperatures and dont degrade as quickly when exposed to sunlight.

These are very important properties when you want to fabricate robots or systems that need to interact with a real-world environment, says Katzschmann.

The researchers used thiol-based materials and wax to fabricate several complex devices that would otherwise be nearly impossible to make with existing 3D printing systems. For one, they produced a functional, tendon-driven robotic hand that has 19 independently actuatable tendons, soft fingers with sensor pads, and rigid, load-bearing bones.

We also produced a six-legged walking robot that can sense objects and grasp them, which was possible due to the systems ability to create airtight interfaces of soft and rigid materials, as well as complex channels inside the structure, says Buchner.

The team also showcased the technology through a heart-like pump with integrated ventricles and artificial heart valves, as well as metamaterials that can be programmed to have non-linear material properties.

This is just the start. There is an amazing number of new types of materials you can add to this technology. This allows us to bring in whole new material families that couldnt be used in 3D printing before, Matusik says.

The researchers are now looking at using the system to print with hydrogels, which are used in tissue-engineering applications, as well as silicon materials, epoxies, and special types of durable polymers.

They also want to explore new application areas, such as printing customizable medical devices, semiconductor polishing pads, and even more complex robots.

This research was funded, in part, by Credit Suisse, the Swiss National Science Foundation, the U.S. Defense Advanced Research Projects Agency, and the U.S. National Science Foundation.

Original post:

This 3D printer can watch itself fabricate objects - MIT News

In Pennsylvania, where 13 percent of the bridges have been classified as structurally deficient, engineers are using artificial intelligence to create lighter concrete blocks for new construction. Another project is using A.I. to develop a highway wall that can absorb noise from cars and some of the greenhouse gas emissions that traffic releases as well.

At a time when the federal allocation of billions of dollars toward infrastructure projects would help with only a fraction of the cost needed to repair or replace the nations aging bridges, tunnels, buildings and roads, some engineers are looking to A.I. to help build more resilient projects for less money.

These are structures, with the tools that we have, that save materials, save costs, save everything, said Amir Alavi, an engineering professor at the University of Pittsburgh and a member of the consortium developing the two A.I. projects in conjunction with the Pennsylvania Department of Transportation and the Pennsylvania Turnpike Commission.

The potential is enormous. The manufacturing of cement alone makes up at least 8 percent of the worlds carbon emissions, and 30 billion tons of concrete are used worldwide each year, so more efficient production of concrete would have immense environmental implications.

And A.I. essentially machines that can synthesize information and find patterns and conclusions much as the human mind can could have the ability to speed up and improve tasks like engineering challenges to an incalculable degree. It works by analyzing vast amounts of data and offering options that give humans better information, models and alternatives for making decisions.

It has the potential to be both more cost effective one machine doing the work of dozens of engineers and more creative in coming up with new approaches to familiar tasks.

But experts caution against embracing the technology too quickly when it is largely unregulated and its payoffs remain largely unproven. In particular, some worry about A.I.s ability to design infrastructure in a process with several regulators and participants operating over a long period of time. Others worry that A.I.s ability to draw instantly from the entirety of the internet could lead to flawed data that produces unreliable results.

American infrastructure challenges have become all the more apparent in recent years Texas power grid failed during devastating ice storms in 2021 and continues to grapple with the states needs; communities across the country from Flint, Mich., to Jackson, Miss., have struggled with failing water supplies; and more than 42,000 bridges are in poor condition nationwide.

A vast majority of the countrys roadways and bridges were built several decades ago, and as a result infrastructure challenges are significant in many dimensions, said Abdollah Shafieezadeh, a professor of civil, environmental and geodetic engineering at Ohio State University.

The collaborations in Pennsylvania reflect A.I.s potential to address some of these issues.

In the bridge project, engineers are using A.I. technology to develop new shapes for concrete blocks that use 20 percent less material while maintaining durability. The Pennsylvania Department of Transportation will use the blocks to construct a bridge; there are more than 12,000 in the state that need repair, according to the American Road & Transportation Builders Association.

Engineers in Pittsburgh are also working with the Pennsylvania Turnpike Commission to design a more efficient noise-absorbing wall that will also capture some of the nitrous oxide emitted from vehicles. They are planning to build it in an area that is disproportionately affected by highway sound pollution. The designs will save about 30 percent of material costs.

These new projects have not been tested in the field, but they have been successful in the lab environment, Dr. Alavi said.

In addition to A.I.s speed at developing new designs, one of its largest draws in civil engineering is its potential to prevent and detect damage.

Instead of investing large sums of money in repair projects, engineers and transportation agencies could identify problems early on, experts say, such as a crack forming in a bridge before the structure itself buckled.

This technology is capable of providing an analysis of what is happening in real time in incidents like the bridge collapse on Interstate 95 in Philadelphia this summer or the fire that shut down a portion of Interstate 10 in Los Angeles this month, and could be developed to deploy automated emergency responses, said Seyede Fatemeh Ghoreishi, an engineering and computer science professor at Northeastern University.

But, as in many fields, there are increasingly more conversations and concerns about the relationship between A.I., human work and physical safety.

Although A.I. has proved helpful in many uses, tech leaders have testified before Congress, pushing for regulations. And last month, President Biden issued an executive order for a range of A.I. standards, including safety, privacy and support for workers.

Experts are also worried about the spread of disinformation from A.I. systems. A.I. operates by integrating already available data, so if that data is incorrect or biased, the A.I. will generate faulty conclusions.

It really is a great tool, but it really is a tool you should use just for a first draft at this point, said Norma Jean Mattei, a former president of the American Society of Civil Engineers.

Dr. Mattei, who has worked in education and ethics for engineering throughout her career, added: Once it develops, Im confident that well get to a point where youre less likely to get issues. Were not there yet.

Also worrisome is a lack of standards for A.I. The Occupational Safety and Health Administration, for example, does not have standards for the robotics industry. There is rising concern about car crashes involving autonomous vehicles, but for now, automakers do not have to abide by any federal software safety testing regulations.

Lola Ben-Alon, an assistant professor of architecture technology at Columbia University, also takes a cautionary approach when using A.I. She stressed the need to take the time to understand how it should be employed, but she said that she was not condemning it" and that it had many great potentials.

Few doubt that in infrastructure projects and elsewhere, A.I. exists as a tool to be used by humans, not as a substitute for them.

Theres still a strong and important place for human existence and experience in the field of engineering, Dr. Ben-Alon said.

The uncertainty around A.I. could cause more difficulties for funding projects like those in Pittsburgh. But a spokesman for the Pennsylvania Department of Transportation said the agency was excited to see how the concrete that Dr. Alavi and his team are designing could expand the field of bridge construction.

Dr. Alavi said his work throughout his career had shown him just how serious the potential risks from A.I. are.

But he is confident about the safety of the designs he and his team are making, and he is excited for the technologys future.

After 10, 12 years, this is going to change our lives, Dr. Alavi said.

Originally posted here:

New Tool for Building and Fixing Roads and Bridges: Artificial ... - The New York Times