Lifeboat Foundation

Korea Zinc buys wind and solar developer Epuron, delivering a wind and solar portfolio of up to 9GW for its green metals and hydrogen ambitions.

Korean Zinc, the world’s biggest zinc, lead and silver producer, has bought Australian-based renewable energy developer Epuron as part of its move towards 100 per cent renewables, green metals and green hydrogen.

The purchase is a significant move, and underlines the determination of some of the world’s biggest metals companies to switch to green products, in moves that will surely turbo-charge the development of wind and solar projects in Australia and across the globe.

Continue reading “Zinc giant buys wind and solar developer in major green metals and hydrogen play” »

The Air Force Research Laboratory’s (AFRL)and Northrop Grumman’s Space Solar Power Incremental Demonstrations and Research (SSPIDR) Project announced that they are one step closer to collecting solar energy in space and transmitting it to Earth using radio frequency (RF). The team has successfully conducted the first end-to-end demonstration of key hardware for the Arachne flight experiment.

A ground demonstration of novel components for the “sandwich tile” was used to successfully convert solar energy to radiofrequency (RF) – a fundamental step required to pave the way for a large-scale solar power collection system in space. For this to work, it is necessary to use receiving antennas on Earth to convert RF energy into usable power.

Space solar power is a key focus of AFRL, which awarded Northrop Grumman a $100 million contract in 2018 for the development of a payload to demonstrate the key components of a prototype space solar power system. The sandwich tile is currently under development as an essential payload component for Arachne and as a building block for a large-scale operational system.

In a bit of good news, the spot price for solar grade polysilicon is dropping quite rapidly. If the trend holds, the cost of solar panels in Australia should follow suit soon-ish.

Polysilicon is used in the manufacture of conventional photovoltaic cells used in solar panels. The sought-after stuff was as cheap as chips in July last year, when it was below USD $7/kg. But a series of events including impacts from the pandemic and a couple of factory fires saw it skyrocket.

Polysilicon spot prices were as high as US$36.64/kg at the beginning of this month. But here’s what’s happened in the last few weeks as reported by Bernreuter Research.

KEAR (Knowledgeable External Attention for commonsense Reasoning) —along with recent milestones in computer vision and neural text-to-speech —is part of a larger Azure AI mission to provide relevant, meaningful AI solutions and services that work better for people because they better capture how people learn and work—with improved vision, knowledge understanding, and speech capabilities. At the center of these efforts is XYZ-code, a joint representation of three cognitive attributes: monolingual text (X), audio or visual sensory signals (Y), and multilingual (Z). For more information about these efforts, read the XYZ-code blog post.

Last month, our Azure Cognitive Services team, comprising researchers and engineers with expertise in AI, achieved a groundbreaking milestone by advancing commonsense language understanding. When given a question that requires drawing on prior knowledge and five answer choices, our latest model— KEAR, Knowledgeable External Attention for commonsense Reasoning —performs better than people answering the same question, calculated as the majority vote among five individuals. KEAR reaches an accuracy of 89.4 percent on the CommonsenseQA leaderboard compared with 88.9 percent human accuracy. While the CommonsenseQA benchmark is in English, we follow a similar technique for multilingual commonsense reasoning and topped the X-CSR leaderboard.

Continue reading “Azure AI milestone: Microsoft KEAR surpasses human performance on CommonsenseQA benchmark” »

The contemporaneous development in recent years of deep neural networks, hardware accelerators with large memory capacity and massive training datasets has advanced the state-of-the-art on tasks in fields such as computer vision and natural language processing. Today’s deep learning (DL) systems however remain prone to issues such as poor robustness, inability to adapt to novel task settings, and requiring rigid and inflexible configuration assumptions. This has led researchers to explore the incorporation of ideas from collective intelligence observed in complex systems into DL methods to produce models that are more robust and adaptable and have less rigid environmental assumptions.

In the new paper Collective Intelligence for Deep Learning: A Survey of Recent Developments, a Google Brain research team surveys historical and recent neural network research on complex systems and the incorporation of collective intelligence principles to advance the capabilities of deep neural networks.

Collective intelligence can manifest in complex systems as self-organization, emergent behaviours, swarm optimization, and cellular systems; and such self-organizing behaviours can also naturally arise in artificial neural networks. The paper identifies and explores four DL areas that show close connections with collective intelligence: image processing, deep reinforcement learning, multi-agent learning, and meta-learning.

A research team, led by Assistant Professor Desmond Loke from the Singapore University of Technology and Design (SUTD), has developed a new type of artificial synapse based on two-dimensional (2D) materials for highly scalable brain-inspired computing.

Brain-inspired computing, which mimics how the human brain functions, has drawn significant scientific attention because of its uses in artificial intelligence functions and low energy consumption. For brain-inspired computing to work, synapses remembering the connections between two neurons are necessary, like human brains.

In developing brains, synapses can be grouped into functional synapses and silent synapses. For functional synapses, the synapses are active, while for silent synapses, the synapses are inactive under normal conditions. And, when silent synapses are activated, they can help to optimize the connections between neurons. However, as artificial synapses built on digital circuits typically occupy large spaces, there are usually limitations in terms of hardware efficiency and costs. As the human brain contains about a hundred trillion synapses, it is necessary to improve the hardware cost in order to apply it to smart portable devices and internet-of things (IoTs).

Defense industries in both the countries will look to complement their technologies to build a powerful engine and other combative capabilities.

Autonomous weapon systems—commonly known as killer robots—may have killed human beings for the first time ever last year, according to a recent United Nations Security Council report on the Libyan civil war. History could well identify this as the starting point of the next major arms race, one that has the potential to be humanity’s final one.

The United Nations Convention on Certain Conventional Weapons debated the question of banning autonomous weapons at its once-every-five-years review meeting in Geneva Dec. 13–17, 2021, but didn’t reach consensus on a ban. Established in 1983, the convention has been updated regularly to restrict some of the world’s cruelest conventional weapons, including land mines, booby traps and incendiary weapons.

Continue reading “UN fails to agree on ‘killer robot’ ban as nations pour billions into autonomous weapons research” »

In collaboration with an international team of researchers, Michigan State University (MSU) has helped create the world’s lightest version—or isotope—of magnesium to date.

Forged at the National Superconducting Cyclotron Laboratory at MSU, or NSCL, this isotope is so unstable that it falls apart before scientists can measure it directly. Yet this isotope that isn’t keen on existing can help researchers better understand how the atoms that define our existence are made.

Led by researchers from Peking University in China, the team included scientists from Washington University in St. Louis, MSU, and other institutions.