Lasers Enable Internet Backbone via Sat

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Lasers Enable Internet Backbone via Satellite

ETH Zurich (Switzerland), Daniel Meierhans

June 20, 2023

Scientists at Switzerland's ETH Zurich, French aerospace laboratory ONERA, and French space company Thales Alenia Space transmitted several dozen terabits per second between a mountain peak and the Swiss city of Bern using optical data communications lasers. The researchers supported a 1-terabit/second optical communication link between the High Altitude Research Station on the Jungfraujoch peak and the University of Bern's Zimmerwald Observatory, which are 53 kilometers (33 miles) apart. ONERA implemented a microelectromechanical system chip with 97 adjustable mirrors to improve signals about 500-fold by correcting the phase shift of the beam on its intersection surface along the currently measured gradient 1,500 times per second.

Ethereum Closes Security Hole with Energy-Saving Update

Interesting example of Security problem.

Ethereum Closes Security Hole with Energy-Saving Update

By New Scientist,May 26, 2023.

Running an Ethereum node allows a user to create transactions and broadcast them across the network without relying on a third party.

An update rolled out by the Ethereum cryptocurrency reduced the energy needed to produce it by 99.99% by transitioning from "proof of work" to "proof of stake," and also fixed a security flaw in the Go Ethereum software used to run Ethereum nodes.

Massimiliano Taverna at ETH Zurich in Switzerland explained that combining the attacks would have reduced the required computing resources to launch the attacks to only 5 graphics processing units.

Ethereum Classic developers patched the vulnerability after being notified by the researchers, but the researchers said the Ethereum POW cryptocurrency has not been updated.

From New Scientist

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Metal Detecting from the Air

Recall a DOD project looking a a related problem.   Hope this does not become an issue in greater Europe.

Metal-Detecting Drone Could Autonomously Find Land Mines A drone with 5 degrees of freedom can safely detect buried objects from the air.  By Evan Ackerman 

Several stitched-together photographs of gray three-propellered drones with metal detectors hovering just above grass

This composite photo shows how a tricopter drone with a lidar and metal detector can fly around an obstacle close to the ground.

Metal detecting can be a fun hobby, or it can be a task to be completed in deadly earnest—if the buried treasure you’re searching for includes land mines and explosive remnants of war. This is an enormous, dangerous problem: Something like 12,000 square kilometers worldwide are essentially useless and uninhabitable because of the threat of buried explosives, and thousands and thousands of people are injured or killed every year.

While there are many different ways of detecting mines and explosives, none of them are particularly quick or easy. For obvious reasons, sending a human out into a minefield with a metal detector is not the safest way of doing things. So, instead, people send anything else that they possibly can, from machines that can smash through minefields with brute force to well-trained rats that take a more passive approach by sniffing out explosive chemicals.

Because the majority of mines are triggered by pressure or direct proximity, it may seem that a drone would be the ideal way to detect them nonexplosively. However, unless you’re only detecting over a perfectly flat surface (and perhaps not even then) your detector won’t be positioned ideally most of the time, and you might miss something, which is not a viable option for mine detection.

But now a novel combination of a metal detector and a drone with 5 degrees of freedom is under development at the Autonomous Systems Lab at ETH Zurich. It may provide a viable solution to remote land-mine detection, by using careful sensing and localization along with some twisting motors to keep the detector reliably close to the ground.  ...' 

Computer Scientists Help Build a Wooden Dome Made from Waste

Multiple challenging uses of computing to address a complex problem. 

Computer Scientists Help Build a Wooden Dome Made Solely from Waste

ETH Zurich (Switzerland), Rahel Künzler, April 26, 2022

A team of architects, engineers, and computer scientists at Switzerland's ETH Zurich built a geodesic dome using demolition waste. The team members salvaged plywood panels, wooden beams, steel girders, and plastic piping from an old car depot in Geneva before its demolition. One student programmed an algorithm to calculate the geometry and dimensions of the desired dome based on the available timber, with the goal of utilizing as much of the scrap wood as possible. Another created an online platform for building materials that serves as a digital material passport, with each piece of wood marked with a QR code that links to the platform. Said team leader Catherine De Wolf, “Projects like this one can only succeed if all the stakeholders are on the same page.”   ... ' 

Autonomous Robotic Excavator

Impressive.

Autonomous Walking Excavator Can Build Walls, Dig Trenches  By New Scientist

A construction vehicle can operate autonomously on rough terrain, thanks to a team of Swiss-German engineers that adapted a walking excavator to perform various tasks.

Researchers at ETH Zurich in Switzerland made the prototype Hydraulic Excavator for an Autonomous Purpose (HEAP) autonomous through the use of algorithms, control mechanisms, and Light Detection and Ranging (LiDAR).

The 12-ton HEAP was programmed to use an excavator bucket and a two-finger gripper, and was able to construct a four-meter (13-foot)-high stone wall, grab trees for mock forestry work, and dig out a trench containing live ammunition from World War II.

ETH Zurich's Dominic Jud said one of the biggest challenges in switching the excavator from human operation to a computer running open source Ubuntu software was reengineering the cabin controls to drive the hydraulic pumps.

Jud said HEAP is roughly as accurate as human operators in executing tasks, although not yet as quick.

Virtual Reality at a Touch

A new kind of interaction with your reality.     Perhaps easier and more productive. 

Virtual Reality at Your Fingertips

ETH Zurich (Switzerland), Leo Herrmann, March 16, 2021

Researchers at ETH Zurich in Switzerland have developed a dual-sensor wristband that facilitates intuitive free-hand interaction within virtual productivity spaces. The prototype TapID technology incorporates two acceleration sensors in a rubber wristband, which detect when the hand touches a surface and which finger the user has employed. This design senses tiny differences in the vibration profile on the wrist and differentiates between each unique finger movement, while a custom machine learning pipeline processes the data in real time. TapID generates extremely precise input when used with cameras embedded within virtual reality (VR) glasses, which capture hand positions. The researchers designed a virtual keyboard and piano to demonstrate TapID's capabilities, and ETH Zurich's Christian Holz said the portable technology "has the potential to make VR systems suitable for productivity work on the go."

Computing Turbulence with Competitive AI

 We used turbulence analysis in roasting applications. Could have used this as a means to do better predictions in simulations.

Intriguing application I had not seen yet.  

ETH Researchers Compute Turbulence With AI

ETH Zurich (Switzerland), Simone Ulmer, January 4, 2021

The modeling of turbulence has been automated by researchers at ETH Zurich in Switzerland by merging reinforcement learning (RL) algorithms with turbulent flow simulations on the Swiss National Supercomputing Centre's (CSCS) "Piz Daint" supercomputer. The two major approaches for simulating turbulent flows are direct numerical simulation (DNS) and large eddy simulation (LES). The researchers used artificial intelligence (AI) to determine the best turbulent closure models from DNS and apply them to LES. Their RL algorithm uses the grid points that resolve the flow field as AI agents, which observed thousands of flow simulations to learn turbulence closure models. Said ETH's Petros Koumoutsakos, "The machine 'wins' when it succeeds to match LES with DNS results, much like machines learning to play a game of chess or GO.” Koumoutsakos added that the new methodology “offers a new and powerful way to automate multiscale modeling and advance science through a judicious use of AI."

Causality is Important for Machine Learning

Have always thought causal thinking and learning was a major consideration for the future of AI in general.  Here a step in the right direction.  But overall its still a hard question.

Understanding Causality Is the Next Challenge for Machine Learning

Teaching robots to understand "why" could help them transfer their knowledge to other environments  By Payal Dhar

“Causality is very important for the next steps of progress of machine learning,” said Yoshua Bengio, a Turing Award-wining scientist known for his work in deep learning, in an interview with IEEE Spectrum in 2019. So far, deep learning has comprised learning from static datasets, which makes AI really good at tasks related to correlations and associations. However, neural nets do not interpret cause-and effect, or why these associations and correlations exist. Nor are they particularly good at tasks that involve imagination, reasoning, and planning. This, in turn, limits AI from being able to generalize their learning and transfer their skills to another related environment.

The lack of generalization is a big problem, says Ossama Ahmed, a master’s student at ETH Zurich who has worked with Bengio’s team to develop a robotic benchmarking tool for causality and transfer learning. “Robots are [often] trained in simulation, and then when you try to deploy [them] in the real world…they usually fail to transfer their learned skills. One of the reasons is that the physical properties of the simulation are quite different from the real world,” says Ahmed. The group’s tool, called CausalWorld, demonstrates that with some of the methods currently available, the generalization capabilities of robots aren’t good enough—at least not to the extent that “we can deploy [them] safely in any arbitrary situation in the real world,” says Ahmed.

The paper on CausalWorld   , available as a preprint, describes benchmarks in a simulated robotics manipulation environment using the open-source TriFinger robotics platform. The main purpose of CausalWorld is to accelerate research in causal structure and transfer learning using this simulated environment, where learned skills could potentially be transferred to the real world. Robotic agents can be given tasks that comprise pushing, stacking, placing, and so on, informed by how children have been observed to play with blocks and learn to build complex structures. There is a large set of parameters, such as weight, shape, and appearance of the blocks and the robot itself, on which the user can intervene at any point to evaluate the robot’s generalization capabilities. ...  '

Blueprint for Tools to Manage a Pandemic

Like the process and requirements statement for a specific set of goals.  Often not done rigorously enough.

Blueprint for the Perfect Coronavirus App
ETH Zurich (Switzerland)
Felix Wursten
July 20, 2020

Researchers at the Swiss Federal Institute of Technology in Zurich (ETH Zurich) have outlined the ethical and legal challenges of developing and implementing digital tools for managing the Covid-19 pandemic. The authors highlighted contact-tracing applications, programs for assessing an infection's presence based on symptoms, apps to check compliance of quarantine regulations, and flow models like those Google uses for mobility reports. ETH Zurich's Effy Vayena said rigorous scientific validation must ensure digital tools work as intended, and confirm their efficacy and reliability. Ethical issues include ensuring data collected by apps is not used for any other purpose without users' prior knowledge, and deploying tools for limited periods to deter their misuse for population surveillance. Vayena said, "The basic principles—respecting autonomy and privacy, promoting healthcare and solidarity, and preventing new infections and malicious behavior—are the same everywhere."

An Intuitive Language for Quantum Computers

Is it better t have a coding method devoted to an innovation like quantum, or one that provides the greatest accessibility?

The First Intuitive Programming Language for Quantum Computers
ETH Zurich
Florian Meyer
June 15, 2020

Computer scientists at ETH Zurich in Switzerland have created the first intuitive high-level quantum programming language, a coding mechanism that they say is as simple, reliable, and as safe as classical computer languages. ETH Zurich's Benjamin Bichsel described Silq as a programming language keyed toward the mindset of programmers when they want to solve a problem, rather than on hardware construction and functionality. Silq's most significant advancement is its ability to automatically identify and delete intermediate or temporary values that are no longer needed, a process called uncomputation, using only programming commands that lack any special quantum operations. ETH Zurich's Martin Vechev said, "Silq is a major breakthrough in terms of optimizing the programming of quantum computers; it is not the final phase of development."

Augmented Paper as a New Media

Good illustrations at the link. Clever thought,  we still will use paper (and other media)  How can we effectively get important virtual content there too.  Saw this presented one time as a means for advertising in AR spaces.

The Virtual Made Real—New Technology for the Media of the Future
ETH Zurich
Florian Meyer

Researchers at the Swiss Federal Institute of Technology, Zurich's Media Technology Center (MTC) are developing future media technologies to transform journalism. One project is "augmented paper" that would allow anyone wearing augmented reality (AR) glasses to see moving images on a page that would display correctly even when the pages bend. MTC is using Zurich's city center to test the concept's practical legibility, with wearers of AR glasses able to see local information like tram departure times, ads for shops, or related newspaper articles. MTC's Severin Klingler said, "Our tool means users no longer have to grapple with the difficult question of how to get their virtual content into the right real place."  ... ' 

An Internet from Space

Satellites and Network design that would cover the earth with an Internet.

A Network Design for the 'Internet from Space'
ETH Zurich
Florian Meyer
December 10, 2019

Researchers at ETH Zurich in Switzerland are proposing a network design that could double the network capacity of low-flying satellites to create an "Internet from Space." The proposed system would use thousands of satellites linked to each other via laser light to form a network, providing coverage that could reach remote regions that currently have no or very limited access to the Internet. The design concept is based on the high temporal dynamics of low Earth orbit satellites. The researchers decided to make the connections between satellites based on specialized, repetitive patterns, with the most suitable pattern depending on the satellite constellation's geometry and the network's input traffic. Said Ankit Singla of ETH Zurich, "To implement satellite-based broadband Internet, we have to rethink virtually all aspects of the way in which the Internet is currently designed to function."  .... '

Flight Simulator Eye Tracking

More advances in eye tracking and associated  uses:

Tracking the Eye of the Pilot
ETH Zurich
Michael Keller
November 25, 2019

Researchers at the Swiss Federal Institute of Technology (ETH) Zurich, Swiss International Air Lines, the U.S. National Aeronautics and Space Administration, and others have developed and tested eye-tracking software to train pilots. The Instructor Assistant System (iAssyst) software lets instructors analyze the gaze patterns of trainees in the cockpit of a flight simulator to see how they monitor the automated systems of modern passenger planes. iAssyst combines video, audio, and simulator recordings, while displaying pilots' gaze patterns. iAssyst permitted trainers to analyze pilots' flying performance with greater precision, enabling instructors to better evaluate the causes of potential pilot errors, and appropriately adjust the training regimen. ETH researchers Martin Raubal and David Rudi said the software also could be used for medical training. ... " 

AI Improving Biomedical Imaging

It is notable how modern AI is doing best in 'vision' spaces.    As opposed to what I would call conversational interaction and process logic.   Not what we would have expected in the earlier applications of AI.  Is this because the training data is more available and concise, or because the underlying deep learning models are closer to the underlying human intelligence?   Or both?

Artificial intelligence improves biomedical imaging in TechXplore
by Fabio Bergamin, ETH Zurich

ETH researchers use artificial intelligence to improve quality of images recorded by a relatively new biomedical imaging method. This paves the way towards more accurate diagnosis and cost-effective devices.

Scientists at ETH Zurich and the University of Zurich have used machine learning methods to improve optoacoustic imaging. This relatively young medical imaging technique can be used for applications such as visualizing blood vessels, studying brain activity, characterizing skin lesions and diagnosing breast cancer. However, quality of the rendered images is very dependent on the number and distribution of sensors used by the device: the more of them, the better the image quality. The new approach developed by the ETH researchers allows for substantial reduction of the number of sensors without giving up on the resulting image quality. This makes it possible to reduce the device cost, increase imaging speed or improve diagnosis. .... "

Storing Data in Music

Intriguing idea, in theory not that hard.   Why might it be used?  A kind of Steganography?

Storing Data in Music 
ETH Zurich
By Fabio Bergamin

Researchers at ETH Zurich in Switzerland have developed a method for embedding data in music in a way that is imperceptible to the human ear, and transmitting it to a smartphone. The researchers found that under ideal conditions, the technique can transfer up to 400 bits per second without the average listener noticing. The researchers used the dominant notes in a piece of music, overlaying each of them with two marginally deeper and two marginally higher notes that are quieter than the dominant note. The team also used the harmonics of the strongest note, inserting slightly deeper and higher notes there as well. The data is stored in these additional notes. Said ETH’s Simon Tanner, “What we’re doing is embedding the data in the music itself; transmitting data from the loudspeaker to the mic.”  .... ' 

Quantum Transmission from ETH

This, from ETH, seems quite the breakthrough.  What will this ultimately mean for computing, encryption,  combinatorial computation?    Beam me up?

Quantum Transfer at the Push of a Button 

ETH Zurich   By Oliver Morsch

Scientists at ETH Zurich in Switzerland have transmitted information between two solid-state quantum bits (qubits) about a meter apart, with high fidelity. The team, led by ETH Zurich's Andreas Wallraff, linked two superconducting qubits with a coaxial cable. The first qubit's quantum state was initially transferred to a microwave photon of a resonator via precisely controlled microwave pulses, before being sent through the cable to a second resonator, where microwave pulses passed its quantum state on to the second qubit. "The transmission of the quantum state is deterministic, which means that it works at the push of a button," says ETH Zurich's Philipp Kurpiers. Wallraff notes the process' transmission rate for quantum states is among the highest ever achieved. The team's next challenge is using two qubits each as transmitter and receiver, to enable entanglement swapping. ... "

Facebook Open Source AI

What Facebook is Doing for Open-Source AI.   Technical details and detailed pointers to resources.  Announces what they call Tensor Comprehensions.

Announcing Tensor Comprehensions

By: Nicolas Vasilache, Oleksandr Zinenko - Inria & DI ENS, Theodoros Theodoridis - ETH Zürich, Priya Goyal, Zachary DeVito, William S. Moses - MIT CSAIL, Sven Verdoolaege, Andrew Adams, Albert Cohen - Inria & DI ENS & FAIR

Today, Facebook AI Research (FAIR) is announcing the release of Tensor Comprehensions, a C++ library and mathematical language that helps bridge the gap between researchers, who communicate in terms of mathematical operations, and engineers focusing on the practical needs of running large-scale models on various hardware backends. The main differentiating feature of Tensor Comprehensions is that it represents a unique take on Just-In-Time compilation to produce the high-performance codes that the machine learning community needs, automatically and on-demand.  ....

What to expect next

This release will allow researchers and programmers to write layers in a notation that is similar to the maths they use in their papers and communicate concisely the intent of their program. They will also be able to take that notation and translate it easily into a fast implementation in a matter of minutes rather than days. As the toolchain grows, we expect usability and performance to increase and benefit the whole community.

We will release PyTorch integration for Tensor Comprehensions at a later date.

We are grateful for frequent exchanges with and feedback from the frameworks teams and are looking forward to bringing this exciting new technology to your favorite ML framework.

FAIR is committed to open science and working with the machine learning community to push AI research further. Tensor Comprehensions is already a collaboration between Facebook, Inria, ETH Zurich and MIT. Our work is in the early stages and we’re excited to share it early and look forward to improving it with feedback from the community.

Get started:
Tensor Comprehensions is available under the Apache 2.0 license.
Documentation
On ArXiv
On Slack
Email: tensorcomp@fb.com