Enlarge / Warehouse workers at the STL8 Amazon Fulfillment Center marched on the boss Wednesday to demand a $25 an hour minimum wage for all workers. (credit: via Justice Speaks)
Amazon currently faces disgruntled workers in every direction.
Office workers are raging against CEO Andy Jassy's return to office mandate, Fortune reported—which came just as a leaked document reportedly showed that Amazon is also planning to gut management, Business Insider reported. Drivers by the hundreds are flocking to join a union to negotiate even better work conditions, CNBC reported, despite some of the biggest concessions in Amazon's history. And hundreds more unionized warehouse workers are increasingly banding together nationwide to demand a $25 an hour minimum wage. On Wednesday, workers everywhere were encouraged to leave Jassy a voicemail elevating workers' demands for a $25 minimum wage.
This momentum has been building for years after drivers unionized in 2021. And all this collective fury increasingly appears to be finally pressuring Amazon into negotiating better conditions for some workers.
Four decades after the first IEEE International Conference on Robotics and Automation (ICRA) in Atlanta, robotics is bigger than ever. Next week in Rotterdam is the IEEE ICRA@40 conference, “a celebration of 40 years of pioneering research and technological advancements in robotics and automation.” There’s an ICRA every year, of course. Arguably the largest robotics research conference in the world, the 2024 edition was held in Yokohama, Japan back in May.
ICRA@40 is not just a second ICRA conference in 2024. Next week’s conference is a single track that promises “a journey through the evolution of robotics and automation,” through four days of short keynotes from prominent roboticists from across the entire field. You can see for yourself, the speaker list is nuts. There are also debates and panels tackling big ideas, like: “What progress has been made in different areas of robotics and automation over the past decades, and what key challenges remain?” Personally, I’d say “lots” and “most of them,” but that’s probably why I’m not going to be up on stage.
There will also be interactive research presentations, live demos, an expo, and more—the conference schedule is online now, and the abstracts are online as well. I’ll be there to cover it all, but if you can make it in person, it’ll be worth it.
Forty years ago is a long time, but it’s not that long, so just for fun, I had a look at the proceedings of ICRA 1984 which are available on IEEE Xplore, if you’re curious. Here’s an excerpt of the forward from the organizers, which included folks from International Business Machines and Bell Labs:
The proceedings of the first IEEE Computer Society International Conference on Robotics contains papers covering practically all aspects of robotics. The response to our call for papers has been overwhelming, and the number of papers submitted by authors outside the United States indicates the strong international interest in robotics.
The Conference program includes papers on: computer vision; touch and other local sensing; manipulator kinematics, dynamics, control and simulation; robot programming languages, operating systems, representation, planning, man-machine interfaces; multiple and mobile robot systems.
The technical level of the Conference is high with papers being presented by leading researchers in robotics. We believe that this conference, the first of a series to be sponsored by the IEEE, will provide a forum for the dissemination of fundamental research results in this fast developing field.
Technically, this was “ICR,” not “ICRA,” and it was put on by the IEEE Computer Society’s Technical Committee on Robotics, since there was no IEEE Robotics and Automation Society at that time; RAS didn’t get off the ground until 1987.
1984 ICR(A) had two tracks, and featured about 75 papers presented over three days. Looking through the proceedings, you’ll find lots of familiar names: Harry Asada, Ruzena Bajcsy, Ken Salisbury, Paolo Dario, Matt Mason, Toshio Fukuda, Ron Fearing, and Marc Raibert. Many of these folks will be at ICRA@40, so if you see them, make sure and thank them for helping to start it all, because 40 years of robotics is definitely something to celebrate.
Big-name makers of processors, especially those geared toward cloud-based AI, such as AMD and Nvidia, have been showing signs of wanting to own more of the business of computing, purchasing makers of software, interconnects, and servers. The hope is that control of the “full stack” will give them an edge in designing what their customers want.
Amazon Web Services (AWS) got there ahead of most of the competition, when they purchased chip designer Annapurna Labs in 2015 and proceeded to design CPUs, AI accelerators, servers, and data centers as a vertically-integrated operation. Ali Saidi, the technical lead for the Graviton series of CPUs, and Rami Sinno, director of engineering at Annapurna Labs, explained the advantage of vertically-integrated design and Amazon-scale and showed IEEE Spectrum around the company’s hardware testing labs in Austin, Tex., on 27 August.
Saidi and Sinno on:
What brought you to Amazon Web Services, Rami?
Rami SinnoAWS
Rami Sinno: Amazon is my first vertically integrated company. And that was on purpose. I was working at Arm, and I was looking for the next adventure, looking at where the industry is heading and what I want my legacy to be. I looked at two things:
One is vertically integrated companies, because this is where most of the innovation is—the interesting stuff is happening when you control the full hardware and software stack and deliver directly to customers.
And the second thing is, I realized that machine learning, AI in general, is going to be very, very big. I didn’t know exactly which direction it was going to take, but I knew that there is something that is going to be generational, and I wanted to be part of that. I already had that experience prior when I was part of the group that was building the chips that go into the Blackberries; that was a fundamental shift in the industry. That feeling was incredible, to be part of something so big, so fundamental. And I thought, “Okay, I have another chance to be part of something fundamental.”
Does working at a vertically-integrated company require a different kind of chip design engineer?
Sinno: Absolutely. When I hire people, the interview process is going after people that have that mindset. Let me give you a specific example: Say I need a signal integrity engineer. (Signal integrity makes sure a signal going from point A to point B, wherever it is in the system, makes it there correctly.) Typically, you hire signal integrity engineers that have a lot of experience in analysis for signal integrity, that understand layout impacts, can do measurements in the lab. Well, this is not sufficient for our group, because we want our signal integrity engineers also to be coders. We want them to be able to take a workload or a test that will run at the system level and be able to modify it or build a new one from scratch in order to look at the signal integrity impact at the system level under workload. This is where being trained to be flexible, to think outside of the little box has paid off huge dividends in the way that we do development and the way we serve our customers.
“By the time that we get the silicon back, the software’s done” —Ali Saidi, Annapurna Labs
At the end of the day, our responsibility is to deliver complete servers in the data center directly for our customers. And if you think from that perspective, you’ll be able to optimize and innovate across the full stack. A design engineer or a test engineer should be able to look at the full picture because that’s his or her job, deliver the complete server to the data center and look where best to do optimization. It might not be at the transistor level or at the substrate level or at the board level. It could be something completely different. It could be purely software. And having that knowledge, having that visibility, will allow the engineers to be significantly more productive and delivery to the customer significantly faster. We’re not going to bang our head against the wall to optimize the transistor where three lines of code downstream will solve these problems, right?
Do you feel like people are trained in that way these days?
Sinno: We’ve had very good luck with recent college grads. Recent college grads, especially the past couple of years, have been absolutely phenomenal. I’m very, very pleased with the way that the education system is graduating the engineers and the computer scientists that are interested in the type of jobs that we have for them.
The other place that we have been super successful in finding the right people is at startups. They know what it takes, because at a startup, by definition, you have to do so many different things. People who’ve done startups before completely understand the culture and the mindset that we have at Amazon.
What brought you to AWS, Ali?
Ali SaidiAWS
Ali Saidi: I’ve been here about seven and a half years. When I joined AWS, I joined a secret project at the time. I was told: “We’re going to build some Arm servers. Tell no one.”
We started with Graviton 1. Graviton 1 was really the vehicle for us to prove that we could offer the same experience in AWS with a different architecture.
The cloud gave us an ability for a customer to try it in a very low-cost, low barrier of entry way and say, “Does it work for my workload?” So Graviton 1 was really just the vehicle demonstrate that we could do this, and to start signaling to the world that we want software around ARM servers to grow and that they’re going to be more relevant.
Graviton 2—announced in 2019—was kind of our first… what we think is a market-leading device that’s targeting general-purpose workloads, web servers, and those types of things.
It’s done very well. We have people running databases, web servers, key-value stores, lots of applications... When customers adopt Graviton, they bring one workload, and they see the benefits of bringing that one workload. And then the next question they ask is, “Well, I want to bring some more workloads. What should I bring?” There were some where it wasn’t powerful enough effectively, particularly around things like media encoding, taking videos and encoding them or re-encoding them or encoding them to multiple streams. It’s a very math-heavy operation and required more [single-instruction multiple data] bandwidth. We need cores that could do more math.
We also wanted to enable the [high-performance computing] market. So we have an instance type called HPC 7G where we’ve got customers like Formula One. They do computational fluid dynamics of how this car is going to disturb the air and how that affects following cars. It’s really just expanding the portfolio of applications. We did the same thing when we went to Graviton 4, which has 96 cores versus Graviton 3’s 64.
How do you know what to improve from one generation to the next?
Saidi: Far and wide, most customers find great success when they adopt Graviton. Occasionally, they see performance that isn’t the same level as their other migrations. They might say “I moved these three apps, and I got 20 percent higher performance; that’s great. But I moved this app over here, and I didn’t get any performance improvement. Why?” It’s really great to see the 20 percent. But for me, in the kind of weird way I am, the 0 percent is actually more interesting, because it gives us something to go and explore with them.
Most of our customers are very open to those kinds of engagements. So we can understand what their application is and build some kind of proxy for it. Or if it’s an internal workload, then we could just use the original software. And then we can use that to kind of close the loop and work on what the next generation of Graviton will have and how we’re going to enable better performance there.
What’s different about designing chips at AWS?
Saidi: In chip design, there are many different competing optimization points. You have all of these conflicting requirements, you have cost, you have scheduling, you’ve got power consumption, you’ve got size, what DRAM technologies are available and when you’re going to intersect them… It ends up being this fun, multifaceted optimization problem to figure out what’s the best thing that you can build in a timeframe. And you need to get it right.
One thing that we’ve done very well is taken our initial silicon to production.
How?
Saidi: This might sound weird, but I’ve seen other places where the software and the hardware people effectively don’t talk. The hardware and software people in Annapurna and AWS work together from day one. The software people are writing the software that will ultimately be the production software and firmware while the hardware is being developed in cooperation with the hardware engineers. By working together, we’re closing that iteration loop. When you are carrying the piece of hardware over to the software engineer’s desk your iteration loop is years and years. Here, we are iterating constantly. We’re running virtual machines in our emulators before we have the silicon ready. We are taking an emulation of [a complete system] and running most of the software we’re going to run.
So by the time that we get to the silicon back [from the foundry], the software’s done. And we’ve seen most of the software work at this point. So we have very high confidence that it’s going to work.
The other piece of it, I think, is just being absolutely laser-focused on what we are going to deliver. You get a lot of ideas, but your design resources are approximately fixed. No matter how many ideas I put in the bucket, I’m not going to be able to hire that many more people, and my budget’s probably fixed. So every idea I throw in the bucket is going to use some resources. And if that feature isn’t really important to the success of the project, I’m risking the rest of the project. And I think that’s a mistake that people frequently make.
Are those decisions easier in a vertically integrated situation?
Saidi: Certainly. We know we’re going to build a motherboard and a server and put it in a rack, and we know what that looks like… So we know the features we need. We’re not trying to build a superset product that could allow us to go into multiple markets. We’re laser-focused into one.
What else is unique about the AWS chip design environment?
Saidi: One thing that’s very interesting for AWS is that we’re the cloud and we’re also developing these chips in the cloud. We were the first company to really push on running [electronic design automation (EDA)] in the cloud. We changed the model from “I’ve got 80 servers and this is what I use for EDA” to “Today, I have 80 servers. If I want, tomorrow I can have 300. The next day, I can have 1,000.”
We can compress some of the time by varying the resources that we use. At the beginning of the project, we don’t need as many resources. We can turn a lot of stuff off and not pay for it effectively. As we get to the end of the project, now we need many more resources. And instead of saying, “Well, I can’t iterate this fast, because I’ve got this one machine, and it’s busy.” I can change that and instead say, “Well, I don’t want one machine; I’ll have 10 machines today.”
Instead of my iteration cycle being two days for a big design like this, instead of being even one day, with these 10 machines I can bring it down to three or four hours. That’s huge.
How important is Amazon.com as a customer?
Saidi: They have a wealth of workloads, and we obviously are the same company, so we have access to some of those workloads in ways that with third parties, we don’t. But we also have very close relationships with other external customers.
So last Prime Day, we said that 2,600 Amazon.com services were running on Graviton processors. This Prime Day, that number more than doubled to 5,800 services running on Graviton. And the retail side of Amazon used over 250,000 Graviton CPUs in support of the retail website and the services around that for Prime Day.
The AI accelerator team is colocated with the labs that test everything from chips through racks of servers. Why?
Sinno: So Annapurna Labs has multiple labs in multiple locations as well. This location here is in Austin… is one of the smaller labs. But what’s so interesting about the lab here in Austin is that you have all of the hardware and many software development engineers for machine learning servers and for Trainium and Inferentia [AWS’s AI chips] effectively co-located on this floor. For hardware developers, engineers, having the labs co-located on the same floor has been very, very effective. It speeds execution and iteration for delivery to the customers. This lab is set up to be self-sufficient with anything that we need to do, at the chip level, at the server level, at the board level. Because again, as I convey to our teams, our job is not the chip; our job is not the board; our job is the full server to the customer.
How does vertical integration help you design and test chips for data-center-scale deployment?
Sinno: It’s relatively easy to create a bar-raising server. Something that’s very high-performance, very low-power. If we create 10 of them, 100 of them, maybe 1,000 of them, it’s easy. You can cherry pick this, you can fix this, you can fix that. But the scale that the AWS is at is significantly higher. We need to train models that require 100,000 of these chips. 100,000! And for training, it’s not run in five minutes. It’s run in hours or days or weeks even. Those 100,000 chips have to be up for the duration. Everything that we do here is to get to that point.
We start from a “what are all the things that can go wrong?” mindset. And we implement all the things that we know. But when you were talking about cloud scale, there are always things that you have not thought of that come up. These are the 0.001-percent type issues.
In this case, we do the debug first in the fleet. And in certain cases, we have to do debugs in the lab to find the root cause. And if we can fix it immediately, we fix it immediately. Being vertically integrated, in many cases we can do a software fix for it. We use our agility to rush a fix while at the same time making sure that the next generation has it already figured out from the get go.
Enlarge (credit: Getty Images)
Researchers still don’t know the cause of a recently discovered malware infection affecting almost 1.3 million streaming devices running an open source version of Android in almost 200 countries.
Security firm Doctor Web reported Thursday that malware named Android.Vo1d has backdoored the Android-based boxes by putting malicious components in their system storage area, where they can be updated with additional malware at any time by command-and-control servers. Google representatives said the infected devices are running operating systems based on the Android Open Source Project, a version overseen by Google but distinct from Android TV, a proprietary version restricted to licensed device makers.
Although Doctor Web has a thorough understanding of Vo1d and the exceptional reach it has achieved, company researchers say they have yet to determine the attack vector that has led to the infections.
Enlarge / Union members cheer during a news conference following a vote count on the union contract at the IAM District 751 Main Union Hall in Seattle, Washington, US, on Thursday, Sept. 12, 2024. (credit: Bloomberg / Contributor | Bloomberg)
More than 33,000 unionized Boeing workers went on strike Friday, rejecting what they say were unfair terms of a deal the embattled aerospace company tentatively reached with their union.
The rejected deal tried and failed to win over workers by offering a 25 percent wage increase and promised to build Boeing's next jet in the Puget Sound region in Washington, which Boeing claimed offered "job security for generations to come."
But after International Association of Machinists and Aerospace Workers (IAM) District 751 president Jon Holden urged the union to accept the deal—which Boeing said was the "largest-ever general wage increase" in the company's history—hundreds of Boeing employees immediately began resisting ahead of a Thursday vote that ultimately doomed the deal.
Enlarge (credit: Getty | George Frey)
While supplies of Adderall and its generic versions are finally recovering after a yearslong shortage, the Drug Enforcement Administration is now working to curb the short supply of another drug for attention-deficit/hyperactivity disorder: Vyvanse (lisdexamfetamine) and its generic versions.
This week, the DEA said it will increase the allowed production amount of lisdexamfetamine by roughly 23.5 percent, increasing the current 26,500 kg quota by 6,236 kg, for a new total of 32,736 kg. The DEA also allowed for a corresponding increase in d-amphetamine, which is needed for production of lisdexamfetamine.
"These adjustments are necessary to ensure that the United States has an adequate and uninterrupted supply of lisdexamfetamine to meet legitimate patient needs both domestically and globally," the DEA said.
This cool tool plays an intrinsic role in education: it helps provide space for learning. Lambent Spaces Occupancy Analytics platform helps higher education space planning professionals see their physical campus spaces in entirely new ways with powerful insights for decisions related to utilization, student experiences, classroom planning, scheduling and maintenance. It is a highly efficient and effective alternative to capital-intensive and intrusive solutions such as sensors, and it works with existing Wi-Fi infrastructure to get users up and running quickly while reducing costs.
Key capabilities include:
Users can view utilization rates over time, compare registrations to reservations, identify underutilized spaces to reassign students and employees during build/maintenance projects, and make lease renewal and facility budget decisions with hard data.
Eastern Tennessee State, George Mason, Purdue, University of Southern Florida, University of Tennessee-Knoxville and William & Mary are a few of the institutions using the platform. For these reasons and more, Lambent Spaces was named “Best Occupancy Analytics for Space Optimization Solution” as part of The EdTech Awards 2024 from EdTech Digest. Learn more.
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ClassLink Academy is a comprehensive online training platform designed to provide technical administrators, educational leaders, instructors, and students with top-notch resources. The primary goal is to elevate their proficiency and comprehension in utilizing ClassLink’s suite of products effectively.
All courses are organized by anthologies. The ClassLink product anthologies are organized into fundamental and advanced content. and teach employees and users how to navigate, utilize, and configure ClassLink products like LaunchPad, OneSync, RosterServer, Analytics, Analytics+, and the CMC.
The platform was designed around proven pedagogy and utilizes multimedia to support learners through product simulations, knowledge checks, short voice-over videos, and quizzes to solidify knowledge. It keeps learning light through the use of conversational, friendly tones, emojis, and humor. It’s updated and improved regularly as new products are added or altered so that learners have the best, most accurate information possible.
Thanks to ClassLink Academy, users have comprehensive onboarding and orientation training for students, educators, administrators, and staff. It provides step-by-step guidance on how to navigate and effectively utilize the ClassLink platform, ensuring a smooth transition and minimizing the learning curve for new users.
Additionally, ClassLink Academy empowers users through troubleshooting guides and resources to help them resolve common issues they may encounter while using products. It equips users with the knowledge and skills to independently troubleshoot problems, reducing the reliance on technical support and minimizing disruptions to their workflow. For these reasons and more, ClassLink Academy was named “Best Customer Training Solution” as part of The EdTech Awards 2024 from EdTech Digest. Learn more.
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IEEE Collabratec has made it easier for volunteers to display their IEEE positions. The online networking platform released a new benefit this year for its users: digital certificates for IEEE volunteering. They reflect contributions made to the organization, such as leading a committee or organizing an event.
Members can download the certificates and add them to their LinkedIn profile or résumé. Volunteers also can print their certificates to frame and display in their office.
Each individualized document includes the person’s name, the position they’ve held, and the years served. Every position held has its own certificate. The member’s list of roles is updated annually.
The feature is a result of a top recommendation to improve volunteer recognition made by delegates at the 2023 IEEE Sections Congress, according to Deepak Mathur. The senior member is vice president of IEEE Member and Geographic Activities. The new feature “respects the time and effort of our volunteers and is a testament to the power and versatility of the Collabratec platform,” Mathur said in an announcement.
Members can download their certificates by selecting the Certificates tab on their Collabratec page and scrolling to each of their positions.
To learn more about IEEE Collabratec, check out the user guide, FAQs, and users’ forum.
Educators working in Special Education have a new friend in this very cool tool. In axis3, Creatively Focused connects special education teams on one user-friendly platform to help simplify their workflows and enhance their access to training, education, and professional development resources. Educators know exactly what needs to be worked on, and when it needs to be completed by without having to search, wonder, or worry.
Within axis3, special educators understand exactly where they are at on crucial timelines and paperwork which leads to increased visibility and compliance. A combination of achievable tasks that are relevant to the students each educator serves, along with the paperwork needed and any associated learning are provided and customized by role.
Creatively Focused is empowering educators with the time and resources they need for a fulfilling, lifelong career. In axis3, educators can connect with the people who are going to support their role the best. Sometimes that might be a person within the district, or it might be a person from the Creatively Focused team. But ultimately, it’s a person who understands that educator’s workday changes quickly. This reduces the feeling of isolation, and an environment to learn in the flow of work on topics that are relevant.
“Creatively Focused embodies what it means to be a true partner,” says Sara Pratt, Director of Special Services at Northfield Public Schools. “The platform has been incredibly simple to both implement and use, making it easy for our staff to get up and running.” For these reasons and many more, axis3 by Creatively Focused was named “Best Workflow Management for Special Educators” as part of The EdTech Awards 2024 from EdTech Digest. Learn more.
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IEEE TryEngineering has partnered with Keysight Technologies to develop lesson plans focused on electronics and power simulation. Keysight provides hardware, software, and services to a wide variety of industries, particularly in the area of electronic measurement.
IEEE TryEngineering, an IEEE Educational Activities program, empowers educators to foster the next generation of technology innovators through free, online access to culturally relevant, developmentally appropriate, and educationally sound instructional resources for teachers and community volunteers.
The lesson plans cover a variety of STEM topics, experience levels, and age ranges. Educators should be able to find an applicable topic for their students, regardless of their grade level or interests.
There are already a number of lesson plans available through the Keysight partnership that introduce students to electrical concepts, with more being developed. The most popular one thus far is Series and Parallel Circuits, which has been viewed more than 100 times each month. Teams of pupils predict the difference between a parallel and serial circuit design by building examples using wires, light bulbs, and batteries.
“TryEngineering is proud to be Keysight’s partner in attaining the ambitious goal of bringing engineering lessons to 1 million students in 2024.” —Debra Gulick
The newest of the Keysight-sponsored lesson plans, Light Up Name Badge, teaches the basics of circuitry, such as the components of a circuit, series and parallel circuits, and electronic component symbols. Students can apply their newfound knowledge in a design challenge wherein they create a light-up badge with their name.
“Keysight’s commitment to workforce development through preuniversity STEM outreach makes it an ideal partner for IEEE TryEngineering,” says Debra Gulick, director of student and academic education programs for IEEE Educational Activities.
In addition, Keysight’s corporate social responsibility vision to build a better planet by accelerating innovation to connect and secure the world while employing a global business framework of ethical, environmentally sustainable, and socially responsible operations makes it a suitable IEEE partner.
“TryEngineering is proud to be Keysight’s partner in attaining the ambitious goal of bringing engineering lessons to 1 million students in 2024,” Gulick says.
The IEEE STEM Summit, a three-day virtual event in October for IEEE volunteers and educators, is expected to include a session highlighting Keysight’s lesson plans.
Educators and volunteers engaged in outreach activities with students can learn more on the Keysight TryEngineering partnership page.
The arrangement with Keysight was made possible with support from the IEEE Foundation.
A new, tunable smart surface can transform a single pulse of light into multiple beams, each aimed in different directions. The proof-of-principle development opens the door to a range of innovations in communications, imaging, sensing, and medicine.
The research comes out of the Caltech lab of Harry Atwater, a professor of applied physics and materials science, and is possible due to a type of nano-engineered material called a metasurface. “These are artificially designed surfaces which basically consist of nanostructured patterns,” says Prachi Thureja, a graduate student in Atwater’s group. “So it’s an array of nanostructures, and each nanostructure essentially allows us to locally control the properties of light.”
The surface can be reconfigured up to millions of times per second to change how it is locally controlling light. That’s rapid enough to manipulate and redirect light for applications in optical data transmission such as optical space communications and Li-Fi, as well as lidar.
“[The metasurface] brings unprecedented freedom in controlling light,” says Alex M.H. Wong, an associate professor of electrical engineering at the City University of Hong Kong. “The ability to do this means one can migrate existing wireless technologies into the optical regime. Li-Fi and LIDAR serve as prime examples.”
Manipulating and redirecting beams of light typically involves a range of conventional lenses and mirrors. These lenses and mirrors might be microscopic in size, but they’re still using optical properties of materials like Snell’s Law, which describes the progress of a wavefront through different materials and how that wavefront is redirected—or refracted—according to the properties of the material itself.
By contrast, the new work offers the prospect of electrically manipulating a material’s optical properties via a semiconducting material. Combined with nano-scaled mirror elements, the flat, microscopic devices can be made to behave like a lens, without requiring lengths of curved or bent glass. And the new metasurface’s optical properties can be switched millions of times per second using electrical signals.
“The difference with our device is by applying different voltages across the device, we can change the profile of light coming off of the mirror, even though physically it’s not moving,” says paper co-author Jared Sisler—also a graduate student in Atwater’s group. “And then we can steer the light like it’s an electrically reprogrammable mirror.”
The device itself, a chip that measures 120 micrometers on each side, achieves its light-manipulating capabilities with an embedded surface of tiny gold antennas in a semiconductor layer of indium tin oxide. Manipulating the voltages across the semiconductor alters the material’s capacity to bend light—also known as its index of refraction. Between the reflection of the gold mirror elements and the tunable refractive capacity of the semiconductor, a lot of rapidly-tunable light manipulation becomes possible.
“I think the whole idea of using a solid-state metasurface or optical device to steer light in space and also use that for encoding information—I mean, there’s nothing like that that exists right now,” Sisler says. “So I mean, technically, you can send more information if you can achieve higher modulation rates. But since it’s kind of a new domain, the performance of our device is more just to show the principle.”
The principle, says Wong, suggests a wide array of future technologies on the back of what he says are likely near-term metasurface developments and discoveries.
“The metasurface [can] be flat, ultrathin, and lightweight while it attains the functions normally achieved by a series of carefully curved lenses,” Wong says. “Scientists are currently still unlocking the vast possibilities the metasurface has available to us.
“With improvements in nanofabrication, elements with small feature sizes much smaller than the wavelength are now reliably fabricable,” Wong continues. “Many functionalities of the metasurface are being routinely demonstrated, benefiting not just communication but also imaging, sensing, and medicine, among other fields... I know that in addition to interest from academia, various players from industry are also deeply interested and making sizable investments in pushing this technology toward commercialization.”
Archipel Academy was born as the Managed Learning Services business line of Schouten & Nelissen. As learning consultants, the people behind it become very familiar with the challenges in the Learning & Development community and in 2019 their founder and CEO Omar Fouab decided to make learning more personal, more impactful and more accessible.
That is how their Learning Management System with LXP capabilities (Learning tracks and skill management) and the biggest content marketplace in Europe was born. Since then, they kept adding features to keep their customers as well as employees everywhere fit for future: the “search & book” function is AI-driven, learners can access an AI-powered job coach that helps them further develop in their current role or grow towards a different position, engagement is kept high through the use of gamification and more recently they added in-real-time learning through the Archi chatbot.
All of these developments have at their core the company’s strong motivation to keep employees and organizations what they call “fit for future.”
Since becoming their customer, VodafoneZiggo has managed to achieve the following numbers:
• Employees followed an average of 2.3 trainings/ year/ per person, which is 4x more than before
• 31% decrease in voluntary resignation
• In 2022 savings of 1.5 milion euros on learning costs, excluding the 5 administrative FTEs that were repurposed to focus on high-level people strategy
• Becoming an employer of choice- with 1 in 3 people applying at VodafoneZiggo doing so because of the learning culture
• Filling 60% of vacancies from within and adressing knowledge gaps through learning
For these reasons and more, Archipel Academy was named “Best All-in-One Learning Platform” as part of The EdTech Awards 2024 from EdTech Digest. Learn more.
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When Amazon Web Services paid US $650 million in March for another data center to add to its armada, the tech giant thought it was buying a steady supply of nuclear energy to power it, too. The Susquehanna Steam Electric Station outside of Berick, Pennsylvania, which generates 2.5 gigawatts of nuclear power, sits adjacent to the humming data center and had been directly powering it since the center opened in 2023.
After striking the deal, Amazon wanted to change the terms of its original agreement to buy 180 megawatts of additional power directly from the nuclear plant. Susquehanna agreed to sell it. But third parties weren’t happy about that, and their deal has become bogged down in a regulatory battle that will likely set a precedent for data centers, cryptocurrency mining operations, and other computing facilities with voracious appetites for clean electricity.
Putting a data center right next to a power plant so that it can draw electricity from it directly, rather than from the grid, is becoming more common as data centers seek out cheap, steady, carbon-free power. Proposals for co-locating data centers next to nuclear power have popped up in New Jersey, Texas, Ohio, and elsewhere. Sweden is considering using small modular reactors to power future data centers.
However, co-location raises questions about equity and energy security, because directly-connected data centers can avoid paying fees that would otherwise help maintain grids. They also hog hundreds of megawatts that could be going elsewhere.
“They’re effectively going behind the meter and taking that capacity off of the grid that would otherwise serve all customers,” says Tony Clark, a senior advisor at the law firm Wilkinson Barker Knauer and a former commissioner at the Federal Energy Regulatory Commission (FERC), who has testified to a U.S. House subcommittee on the subject.
The dust-up over the Amazon-Susquehanna agreement started in June, after Amazon subsidiary Amazon Web Services filed a notice to change its interconnection service agreement (ISA) in order to buy more nuclear power from Susquehanna’s parent company, Talen Energy. Amazon wanted to increase the amount of behind-the-meter power it buys from the plant from 300 MW to 480 MW. Shortly after it requested the change, utility giants Exelon and American Electric Power (AEP), filed a protest against the agreement and asked FERC to hold a hearing on the matter.
Their complaint: the deal between Amazon and the nuclear plant would hurt a third party, namely all the customers who buy power from AEP or Exelon utilities. The protest document argues that the arrangement would shift up to $140 million in extra costs onto the people of Pennsylvania, New Jersey, and other states served by PJM, a regional transmission organization that oversees the grid in those areas. “Multiplied by the many similar projects on the drawing board, it is apparent that this unsupported filing has huge financial consequences that should not be imposed on ratepayers without sufficient process to determine and evaluate what is really going on,” their complaint says.
Susquehanna dismissed the argument, effectively saying that its deal with Amazon is none of AEP and Exelon’s business. “It is an unlawful attempt to hijack this limited [ISA] amendment proceeding that they have no stake in and turn it into an ad hoc national referendum on the future of data center load,” Susquehanna’s statement said. (AEP, Exelon, Talen/Susquehanna, and Amazon all declined to comment for this story.)
More disputes like this will likely follow as more data centers co-locate with clean energy. Kevin Schneider, a power system expert at Pacific Northwest National Laboratory and research professor at Washington State University, says it’s only natural that data center operators want the constant, consistent nature of nuclear power. “If you look at the base load nature of nuclear, you basically run it up to a power level and leave it there. It can be well aligned with a server farm.”
Data center operators are also exploring energy options from solar and wind, but these energy sources would have a difficult time matching the constancy of nuclear, even with grid storage to help even out their supply. So giant tech firms look to nuclear to keep their servers running without burning fossil fuels, and use that to trumpet their carbon-free achievements, as Amazon did when it bought the data center in Pennsylvania. “Whether you’re talking about Google or Apple or Microsoft or any of those companies, they tend to have corporate sustainability goals. Being served by a nuclear unit looks great on their corporate carbon balance sheet,” Clark says.
Yet such arrangements could have major consequences for other energy customers, Clark argues. For one, directing all the energy from a nuclear plant to a data center is, fundamentally, no different than retiring that plant and taking it offline. “It’s just a huge chunk of capacity leaving the system,” he says, resulting in higher prices and less energy supply for everyone else.
Another issue is the “behind-the-meter” aspect of these kinds of deals. A data center could just connect to the grid and draw from the same supply as everyone else, Clark says. But by connecting directly to the power plant, the center’s owner avoids paying the administrative fees that are used to maintain the grid and grow its infrastructure. Those costs could then get passed on to businesses and residents who have to buy power from the grid. “There’s just a whole list of charges that get assessed through the network service that if you don’t connect through the network, you don’t have to pay,” Clark says. “And those charges are the part of the bill that will go up” for everyone else.
Even the “carbon-free” public relations talking points that come with co-location may be suspect in some cases. In Washington State, where Schneider works, new data centers are being planted next to the region’s abundant hydropower stations, and they’re using so much of that energy that parts of the state are considering adding more fossil fuel capacity to make ends meet. This results in a “zero-emissions shell game,” Clark wrote in a white paper on the subject.
These early cases are likely only the beginning. A report posted in May from the Electric Power Research Institute predicts energy demand from data centers will double by 2030, a leap driven by the fact that AI queries need ten times more energy than traditional internet searches. The International Energy Agency puts the timeline for doubling sooner–in 2026. Data centers, AI, and the cryptocurrency sector consumed an estimated 460 terawatt-hours (TWh) in 2022, and could reach more than 1000 TWh in 2026, the agency predicts.
New data centers can be built in a matter of months, but it takes years to build utility-scale power projects, says Poorvi Patel, manager of strategic insights at Electric Power Research Institute and contributor to the report. The potential for unsustainable growth in electricity needs has put grid operators on alert, and in some cases has sent them sounding the alarm. Eirgrid, a state-owned transmission operator in Ireland, last week warned of a “mass exodus” of data centers in Ireland if it can’t connect new sources of energy.
There’s only so much existing nuclear power to go around, and enormous logistical and regulatory roadblocks to building more. So data center operators and tech giants are looking for creative solutions. Some are considering small modular reactors (SMRs)–which are advanced nuclear reactors with much smaller operating capacities than conventional reactors. Nano Nuclear Energy, which is developing microreactors–a particularly small type of SMR–last month announced an agreement with Blockfusion to explore the possibility of powering a currently defunct cryptomining facility in Niagara Falls, New York.
“To me, it does seem like a space where, if big tech has a voracious electric power needs and they really want that 24/7, carbon-free power, nuclear does seem to be the answer,” Clark says. “They also have the balance sheets to be able to do some of the risk mitigation that might make it attractive to get an SMR up and running.”
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Author and leadership expert John C. Maxwell famously said, “The single biggest way to impact an organization is to focus on leadership development. There is almost no limit to the potential of an organization that recruits good people, raises them up as leaders, and continually develops them.”
Experts confirm that there are clear benefits to fostering leadership by encouraging employees’ professional growth and nurturing and developing company leaders. A culture of leadership development and innovation boosts employee engagement by 20 percent to 25 percent, according to an analysis in the Journal of Applied Psychology. Companies are 22 percent more profitable, on average, when they engage their employees by building a culture of leadership, innovation, and recognition, according to Zippia research.
Developing professionals into strong leaders can have a lasting impact on a company, and the IEEE Professional Development Suite can help make it possible. The training programs in the suite help aspiring technology leaders who want to develop their essential business and management skills. Programs include IEEE Leading Technical Teams, the IEEE | Rutgers Online Mini-MBA for Engineers and Technical Professionals, and the Intensive Wireless Communications and Advanced Topics in Wireless courses offered by the IEEE Communications Society. IEEE also offers topical courses through its eLearning Library.
IEEE Leading Technical Teams is a live, six-hour course offered both in person and virtually. Addressing challenges that come with leading groups, it is designed for team leaders, managers, and directors of engineering and technical teams.
“Participating benefited me and my employer by enhancing my leadership skills in inspiring others to achieve the goals of our organization,” says Stephen Wilkowski, a system test engineer at CACI International in Reston, Va., who completed the training. “I found the leadership practices assessment to be very valuable, as I appreciated the anonymous feedback received from those who I work with. I would recommend the training to anyone desiring to improve their leadership skills.”
Attendees participate in the 360° Leadership Practices Inventory, a tool that solicits confidential feedback on the participant’s strengths and opportunities for improvement from their team members and managers. The program encompasses instructor-led exercises and case studies demonstrating the application of best practices to workplace challenges.
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The 12-week IEEE | Rutgers Online Mini-MBA for Engineers and Technical Professionals program covers business strategy, new product development management, financial analysis, sales and marketing, and leadership. It includes a combination of expert instruction, peer interaction, self-paced video lessons, interactive assessments, live office hours, and hands-on capstone project experience. The program offers flexible learning opportunities for individual learners as well as customized company cohort options.
Developing professionals into strong leaders can have a lasting impact on a company, and the IEEE Professional Development Suite can help make that possible.
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The Intensive Wireless Communications and the Advanced Topics in Wireless course series are exclusively presented by the IEEE Communications Society.
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Tailored for professionals, faculty, and students, the IEEE eLearning Library taps into a wealth of expertise from the organization’s global network of more than 450,000 industry and academia members. Courses cover a wide variety of disciplines including artificial intelligence, blockchain technology, cyber and data security, power and energy, telecommunications, and IEEE standards.
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Een recent onderzoek van de Vrije Universiteit Amsterdam en de Universiteit van Amsterdam heeft nieuwe inzichten opgeleverd over het verband tussen het studiekeuzeproces van aankomende studenten, de aansluiting met hun gekozen bacheloropleiding, en hun studiesucces in het eerste jaar.
Het onderzoek, gepubliceerd in het tijdschrift Learning and Individual Differences, richtte zich op twee belangrijke ontwikkelingstaken die jongeren doorlopen bij het kiezen van een studie: het verkennen van zichzelf en studierichtingen, en het vinden van een opleiding die goed bij hen past. De onderzoekers wilden beter begrijpen hoe deze taken samenhangen en hoe ze leiden tot meer studiesucces. De onderzoekers stellen dat goede voorlichting aan aankomende studenten kan helpen bij het terugdringen van de uitval in het eerste jaar.
Aanleiding voor het onderzoek zijn de hoge uitvalcijfers onder eerstejaarsstudenten in Nederland. Ongeveer 30 procent van de studenten stopt in het eerste jaar, vaak vanwege een verkeerde studiekeuze of tegenvallende verwachtingen. De onderzoekers wilden daarom onderzoeken of een beter studiekeuzeproces kan leiden tot een betere aansluiting met de opleiding en uiteindelijk meer studiesucces.
Om de hoge uitval aan te pakken, zijn instellingen voor hoger onderwijs in Nederland verplicht om vóór de start van het studiejaar te beoordelen of studenten een weloverwogen studiekeuze hebben gemaakt via de Studiekeuzecheck (SKC). Instellingen nemen doorgaans een vragenlijst af of organiseren activiteiten voor toekomstige studenten om dit proces te ondersteunen. Na deze activiteiten ontvangen studenten een vrijblijvend advies over hun studiekeuze. Uit eerder onderzoek blijkt echter dat studenten zelden hun voorgenomen studiekeuze wijzigen, zelfs niet na een negatief advies.
Voor het onderzoek werden gegevens verzameld van 1965 aankomende studenten aan een Nederlandse universiteit, welke universiteit werd niet nader gespecificeerd. Voorafgaand aan de start van hun bacheloropleiding vulden zij vragenlijsten in over hun studiekeuzeproces, interesses en motivatie. Na het eerste semester werd een deel van de studenten opnieuw bevraagd over hun tevredenheid. Na het eerste jaar werden gegevens over studieprestaties en -uitval opgevraagd uit de universitaire administratie.
De onderzoekers gebruikten geavanceerde statistische methoden om de gegevens te analyseren. Ze identificeerden drie verschillende studiekeuzeprofielen onder de studenten. Vervolgens onderzochten ze hoe deze profielen samenhingen met de aansluiting met de opleiding en studiesucces.
Uit de analyses kwamen drie kenmerkende studiekeuzeprofielen naar voren. Allereerst een ‘achievement/foreclosure’ profiel: studenten die veel hadden verkend en zich sterk committeerden aan hun keuze. Een ‘undifferentiated’ profiel: studenten die gemiddeld scoorden op alle aspecten van het keuzeproces. En tot slot een ‘troubled diffusion’ profiel: studenten die weinig hadden verkend, zich weinig committeerden, maar wel veel piekerden over hun keuze.
Een belangrijke bevinding van de Amsterdamse onderzoekers was dat studenten met het achievement/foreclosure profiel een betere aansluiting ervoeren met hun gekozen opleiding. Ze rapporteerden meer autonome motivatie, wat betekent dat ze de opleiding kozen vanuit eigen interesses en waarden. Studenten met het troubled diffusion profiel ervoeren juist een minder goede aansluiting en meer gecontroleerde motivatie, wat duidt op externe druk of schuldgevoelens.
De onderzoekers vonden ook dat een betere aansluiting tussen student en opleiding samenhing met meer studiesucces. Studenten wier interesses beter aansloten bij de opleiding (de zogenaamde ‘objectieve fit’) behaalden meer studiepunten en vielen minder vaak uit. Studenten die een betere aansluiting ervoeren (de ‘subjectieve fit’) waren ook tevredener met hun opleiding.
Een opvallende uitkomst was dat er geen direct verband was tussen de studiekeuzeprofielen en studiesucces. Het verband liep indirect via de ervaren aansluiting met de opleiding. Studenten die meer hadden verkend en zich sterker committeerden aan hun keuze, ervoeren een betere aansluiting, wat vervolgens leidde tot meer tevredenheid.
De onderzoekers bekeken ook of de gevonden verbanden verschilden tussen mannen en vrouwen, en tussen eerstegeneratiestudenten en andere studenten. Er bleken geen verschillen te zijn voor eerstegeneratiestudenten. Omdat er geen verschillen werden gevonden in het studiekeuzeproces en de aansluiting met de opleiding, suggereren de onderzoekers dat de hogere uitvalpercentages onder eerstegeneratiestudenten mogelijk te maken hebben met andere factoren. Ze noemen als mogelijkheden het gebrek aan sociaal kapitaal en relevante eerdere ervaringen.
Wel waren er verschillen tussen mannen en vrouwen in hoe het studiekeuzeproces samenhing met tevredenheid. Vrouwen waren volgens de onderzoekers waarschijnlijk meer toegewijd in hun studiekeuze, wat ook zorgt voor minder uitval.
Het onderzoek geeft volgens de onderzoekers nieuwe inzichten in hoe aankomende studenten tot een passende studiekeuze komen. De bevindingen van het onderzoek onderstrepen het belang van een grondig studiekeuzeproces, waarbij jongeren zichzelf en verschillende opties verkennen om zich zo uiteindelijk te committeren aan een keuze. Dit leidt tot een betere ervaren aansluiting met de opleiding en ook meer tevredenheid tijdens de studie en dus minder uitval.
Middelbare scholen en universiteiten zouden studenten daarom beter kunnen ondersteunen door hen aan te moedigen verschillende opties te verkennen voordat ze een keuze maken. Daarom moeten er op maat gemaakte programma’s komen voor aankomende studenten zowel in het voortgezet onderwijs als op de universiteit, zodat deze jongeren weloverwogen een besluit kunnen nemen over een studie. Open dagen en specifieke programma’s zoals een dag een studie volgen kunnen daarbij essentieel zijn.
De studie heeft volgens de onderzoekers enkele beperkingen. Zo keken de Amsterdamse onderzoekers alleen naar algemene indicatoren van studiesucces, zoals behaalde studiepunten. In vervolgonderzoek zou ook gekeken kunnen worden naar uitkomsten die specifieker te maken hebben met de aansluiting tussen student en opleiding, zoals de intentie om van studie te wisselen.
The post Studiesucces kan worden verbeterd door betere voorlichting aan aankomende studenten first appeared on ScienceGuide.
Het bericht Studiesucces kan worden verbeterd door betere voorlichting aan aankomende studenten verscheen eerst op ScienceGuide.
The Mystery Science service is a K-5 ready-to-use multimedia science and STEM curriculum resource used in more than 50% of United States’ elementary schools each month and 3+ million students to help educators turn the conventional approach of answering children’s questions on its head. This simple student-centered approach, and the services’ ease of use, sets a new trend in science education
Discovery Education acquired Mystery Science in 2020 and the service is now available on the Discovery Education K-12 platform. This puts all the tools needed to create engaging digital learning environments at educators’ fingertips.
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