In December 2016, soon after advisers to President Donald Trump threatened to shut off NASA’s climate-observing satellites, California Governor Jerry Brown made a famous promise: “If Trump turns off the satellites,” he said while addressing a geoscience meeting, “California will launch its own damn satellites.” That promise is now a reality, with California and partners set to launch by 2023 two satellites to spot and monitor plumes of planet-warming carbon dioxide (CO2) and methane. If all goes right, dozens more could follow.
The $100 million Carbon Mapper project, announced today and financed by private philanthropists including Michael Bloomberg, will advance efforts to track concentrated emissions of greenhouse gases, which rise from fossil fuel power plants, leaky pipelines, and abandoned wells. Previous satellites have lacked the resolution and focus to monitor point sources rigorously. “We’re going after the big emitters,” says Riley Duren, Carbon Mapper’s CEO and a remote-sensing scientist at the University of Arizona. He says the ultimate goal is to be “like the weather service for methane and CO2.”
Waymo, Alphabet’s self-driving car subsidiary, is reshuffling its top executive lineup. On April 2, John Krafcik, Waymo’s CEO since 2015, declared that he will be stepping down from his role. He will be replaced by Tekedra Mawakana and Dmitri Dolgov, the company’s former COO and CTO. Krafcik will remain as an advisor to the company.
“[With] the fully autonomous Waymo One ride-hailing service open to all in our launch area of Metro Phoenix, and with the fifth generation of the Waymo Driver being prepared for deployment in ride-hailing and goods delivery, it’s a wonderful opportunity for me to pass the baton to Tekedra and Dmitri as Waymo’s co-CEOs,” Krafcik wrote on LinkedIn as he declared his departure.
Toyota Industries Corporation (TICO) announces the creation of a new company called T-Hive. The new company is a partnership between Toyota L&F, Bastian Solutions, Toyota Forklifts, Vanderlande, Toyota Material Handling and Raymond. T-Hive B.V. will be based in The Netherlands and be led by Léon Jansen.
T-Hive’s main focus will be to provide a seamless control system over all autonomous vehicles (AVs) within TICO, such as automated guided forklifts (AGFs), automated guided vehicles (AGVs), and autonomous mobile robots (AMRs). The combined solution portfolio will be introduced at logistics sites around the world enabling TICO’s customers to enjoy the seamless movement, storage and distribution of goods throughout their entire supply chains.
Governor Murphy is advocating for a “Garden State Guarantee” in which students from families with adjusted gross incomes of $65,000 or less can choose between the first two years at a four-year public college or university for free, or a two-plus-two in which they’d get two years at a community college followed by two years at a four-year college for free. It’s a last-dollar program, so the grants would fill in the gaps left after Pell and other resources have been tapped. … In the very same week, the Bloomberg foundation decided that it would support diversity in higher education by giving $20 million to … Princeton University.
The provision would make higher-ed institutions subject to review by a little-known interagency group that vets international private-sector deals for national-security concerns
n the letter, higher-ed groups say they are concerned that the “sweeping” provision could subject colleges to expensive and time consuming reporting and review. The governmental agency isn’t “designed or equipped” to carry out a review of universities, they say
The University of Toronto has launched the Acceleration Consortium (AC), a new global coalition of academia, industry and government that will use artificial intelligence (AI) and robotics to accelerate the design and discovery of materials that don’t yet exist. These advanced materials will make technologies more affordable and eco-friendly with applications ranging from renewable energy and consumer electronics to drugs.
By leveraging the power of AI, robotics, engineering and chemistry, the AC will make U of T a global centre for materials science innovation.
The Graduate School of Biomedical Sciences at the Icahn School of Medicine at Mount Sinai will offer a new PhD concentration in Artificial Intelligence and Emerging Technologies in Medicine (AIET) as part of its PhD in Biomedical Sciences program. Hayit Greenspan, PhD and Alan C. Seifert, PhD are the newly appointed AIET Co-Directors. Application will be open from late August through December 1, 2021 for enrollment in the fall of 2022.
The BMW Group is publishing an anonymisation solution based on artifi- cial intelligence (AI)that can anonymise objects in photos and videos. Building on the BMW labelling tool Lite, these algorithms (github.com/BMW-InnovationLab) en- able targeted protection of relevant information: The user-friendly software tool uses AI to block out or blur objects or people. The granularity and degree of anony- misation can be intuitively adjusted.
“AI applications supports us with quality assurance, such as inspection of parts and components, as well as development of our autonomous, smart logistics robots. The AI anonymisation algorithms now published also ensure optimal data privacy and information protection,” explains Markus Grüneisl, head of Production System, Digitalisation at the BMW Group. “Making the anonymisation solution intuitive to operate was an important aspect of development for us, to ensure it can easily be used for a wide range of applications.”
A few years ago researchers using the radio-based Event Horizon Telescope (EHT) performed an extraordinary observation, the likes of which remains a dream for most other astronomers. The EHT team announced in April 2019 that it had successfully imaged the shadow of a supermassive black hole in a nearby galaxy by combining observations from eight different radio telescopes spread across our planet. This technique, called interferometry, effectively gave the EHT the resolution, or the ability to distinguish sources in the sky, of an Earth-sized telescope. At the optical wavelengths underpinning the gorgeous pictures from the Hubble Space Telescope and many other famed facilities, today’s interferometers can only combine light from instruments that are a few hundred meters apart at most. That may be set to change as astronomers turn to quantum physicists for help to start connecting optical telescopes that are tens, even hundreds, of kilometers away from one another.
Such optical interferometers would rely on advances being made in the field of quantum communications—particularly the development of devices that store the delicate quantum states of photons collected at each telescope.
One of the first to come out against Google’s plan was the EFF, which in March wrote a blog post called, “Google’s FLoC is a Terrible Idea.” The EFF seems to be against user tracking for ads entirely, saying Google’s framing of the issue “is based on a false premise that we have to choose between ‘old tracking’ and ‘new tracking.'”
“It’s not either-or,” the EFF writes. “Instead of re-inventing the tracking wheel, we should imagine a better world without the myriad problems of targeted ads.” The EFF worries that FLoC won’t stop advertisers from personally identifying people and that the API will serve up full profile data on first contact with a site, saving tracking companies from having to do the work of building a profile themselves over time. It also argues that “the machinery of targeted advertising has frequently been used for exploitation, discrimination, and harm.”
Cerebras Systems, the Sunnyvale, California startup that stunned the world in 2019 by introducing a chip taking up almost the entirety of a twelve-inch semiconductor wafer, on Tuesday unveiled the second version of the part, the Wafer Scale Engine 2, or WSE-2.
The chip, measuring he same forty-six square millimeters, holds 2.6 trillion transistors, which is more than double the count of the original WSE chip. It is also 48 times the number of transistors of the world’s biggest GPU, the “A100” from Nvidia.
The University of Virginia School of Data Science on Tuesday announced a gift of $2 million from Capital One’s Center for Machine Learning to name the central hub for the school’s new building, set for groundbreaking in the fall at the corner of Emmet Street and Ivy Road.
Spring has officially sprung. That might mean you’ve been spending a lot more time noticing things, like the songs of sparrows outside your apartment window, the purple crocuses bursting into bloom in a nearby park, or even asteroids shooting across the night sky.
But did you know those kinds of observations could actually be helpful to scientists? In fact, during the pandemic — as many people have been forced to stay close to home — there’s been a growing number of people participating in something called citizen or community science. That’s when people voluntarily collect data out in the world, or in their own backyards, to help professional scientists study everything from the migratory patterns of butterflies to neighborhood air quality.
For more on all this, The Takeaway spoke to Katy Prudic, assistant professor of citizen and data science at the University of Arizona. [audio, 9:29]
From sample preparation to image acquisition, electron microscopy (EM) requires precise and time-consuming steps to produce the clarity and detail needed to visualize small cell structures with high resolution. Moreover, once EM images are created, extracting the biological information out of them through analysis can be an even more laborious and time intensive task. Especially because current EM analysis software often requires the skilled eye of a scientist to manually review hundreds of images.
With a bit of ingenuity and the application of cutting-edge neural networks, an interdisciplinary team of scientists at the Max Planck Florida Institute for Neuroscience (MPFI) have created a new powerful analysis software aimed at streamlining part of the lengthy process. In collaboration with the Electron Microscopy Core Facility and the Christie Lab, the project tasked two high school students with dramatically improving upon established computer-based techniques for the analysis of protein distribution in EM images. Unlike traditional light microscopy that uses fluorescent labeling, EM requires proteins to be labeled with gold nanoparticles in order to visualize them within a cell. Playfully named “Gold Digger”, the software uses a deep learning approach to identify gold particles bound to specific proteins of interest.
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The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.
The world has been a busy place for a while now. No wonder somewhere deep inside people recognize the need to stay healthy amidst all this, now that the pandemic has shaken things up even more.
Many people realized stay-at-home fitness was a thing, while others found a trusty friend in their smartwatch as they started running for stress relief. Fitness and activity tracking apps are indeed the dominant segments. Yet some find refuge in a meditation app, and the rest is being tucked in by a sleep tracker. The market is growing, especially in the Asia Pacific region. It might turn out to be true that many more people will adopt a technology-related job to not be so vulnerably tied to their workplace. Whether or not a surge in tech stabilizes, fitness applications are here to stay. Safe to say now is the best time to get into fitness app development. For a step-by-step on how to do that, read on. This guide gives you five steps from an idea to post-rollout maintenance.
In the March/April 2021 issue, CiSE is proud to feature several articles showcasing Jupyter in computational science. The showpiece is an invited article by Jupyter co-founders Brian Granger and Fernando Pérez (Granger 2021). They shift the focus of our conversation about problem-solving environments to the human angle: the researcher interactively exploring a scientific question or analyzing data, and the community of people collaborating and advancing their field. Jupyter derives from the IPython Notebook, a browser-based application to compose documents that add computable content to all the other kinds of content that a browser can display: formatted text, images, video, equations, etc. It is a concept inspired by the Mathematica notebook interface, introduced in 1988, and translated to the Python world by the Sage Notebook, starting in 2006. The powerful idea of the Sage Notebook that lives on in Jupyter is connecting a web application serving as a graphical user interface—where the user’s text inputs and the computational outputs are shown—to a back-end that runs the Python interpreter. While the server is running, the state is available to continue interactively computing. On shutting it down, the notebook document can be saved thereby preserving the inputs and outputs, together with any text and multi-media content added by the user. Jupyter took these ideas into the modern web era by employing open formats, protocols and applications that work equally on a laptop and on remote cloud or HPC systems. The communication protocol between the web application and the back-end is language-agnostic, which quickly led to Notebook support for other languages, like Julia and R (and the new name Jupyter). Dozens of so-called Jupyter kernels now allow computing in many different languages (including interactive use of Fortran and C++), though Python continues to be the most popular by far. Serving Jupyter to multiple-users in a corporation or university became possible with JupyterHub (https://jupyter.org/hub), which removes the need for users to install any software on their local machine while delivering a uniform environment to them. This provides an ideal solution for academic settings, where large-scale computing and data science education initiatives have always been hampered by individual students’ software and hardware needs. Jupyter was rapidly adopted by tech giants like Google, Amazon and Netflix; by financial behemoths like Bloomberg; by NASA and the LIGO collaboration, which released Jupyter notebooks with the analysis that proved the existence of gravitational waves (https://www.gw-openscience.org/events/GW150914/); and by computing and data science educators everywhere. On being awarded the ACM Software System Award in 2017, the citation reads that the tools of Project Jupyter “have become a de facto standard for data analysis in research, education, journalism, and industry” (https://awards.acm.org/award_winners/perez_9039634). Like Granger and Pérez note in the previous issue of CiSE, Jupyter now has many millions of users worldwide and many thousands of organizations use Jupyter in their day-to-day operations. They explain the project’s success by virtue of being a tool of thought, a new medium for communication (via computational narratives), and a community of practice.
Seeed’s new development, the reTerminal, is a multi-function device operated by the Raspberry Pi’s latest Compute Module 4 system-on-module (SOM). It includes four Arm Cortex-A72 processing cores operating at 1.5GHz, a Broadcom VideoCore-VI graphics processor with hardware encode and decode, and an option of 1GB, 2GB, 4GB, or 8GB LPDDR4 memory and up to 32GB of eMMC ram. It has a 5″ capacitive touch monitor, cryptographic authentication hardware, accelerometer, a real-time clock, light and proximity sensor, passive cooling, a high-speed expansion socket, and more.
This IoT and cloud-ready Human-Machine Interface (HMI) device will interact with IoT and cloud systems to enable limitless scenarios at the edge. For increased expandability, reTerminal has a high-speed expansion interface and rich I/O. reTerminal has a Gigabit Ethernet port and dual USB 2.0 Type-A ports for faster network connections. The reTerminal’s 40-pin Raspberry Pi compliant header allows it to be used in various IoT applications.
