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Jan 12, 2021

Scientists ‘program’ living bacteria to store data

Posted by in category: biotech/medical

Researchers have come up with a way to electronically write data into the DNA of living bacteria, a storage option unlikely to go obsolete any time soon.


New method enables electronic conversion of data into DNA.

Jan 12, 2021

Father of the Web Tim Berners-Lee prepares ‘do-over’

Posted by in categories: computing, internet

Sir Tim Berners-Lee, the British computer scientist who was knighted for inventing the internet navigation system known as the World Wide Web, wants to re-make cyberspace once again.


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Jan 12, 2021

The new ‘gold rush’ for green lithium

Posted by in categories: climatology, computing, mobile phones, solar power, sustainability

All the clean technologies that we need to combat climate change – whether that’s wind turbines, solar panels or batteries, they’re all really, really mineral intensive.


Cornwall, 1864. A hot spring is discovered nearly 450m (1485ft) below ground in the Wheal Clifford, a copper mine just outside the mining town of Redruth. Glass bottles are immersed to their necks in its bubbling waters, carefully sealed and sent off for testing. The result is the discovery of so great a quantity of lithium – eight or 10 times as much per gallon as had been found in any hot spring previously analysed – that scientists suspect “it may prove of great commercial value”.

But 19th-Century England had little need for the element, and this 50C (122F) lithium-rich water continued steaming away in the dark for more than 150 years.

Continue reading “The new ‘gold rush’ for green lithium” »

Jan 12, 2021

Samsung’s Bot Handy is kind of like a first generation robot butler

Posted by in categories: habitats, robotics/AI

This robot will vacuum and serve you a martini all with one hand…ignore the dust in your glass please.


Two of the new robots are more futuristic, but one of Samsung’s new Bots will be available in the US this year — a robot vacuum that doubles as a home monitoring device.

Jan 12, 2021

The Rise of SpaceX

Posted by in categories: Elon Musk, engineering, space travel

The Rise of # SpaceX Elon Musk’s Engineering Masterpiece.

Jan 12, 2021

Verizon, UPS, and Skyward announce connected drone delivery at CES 2021

Posted by in categories: business, drones, internet

PORTLAND, Ore. — Skyward, A Verizon company, and UPS Flight Forward today announced collaborative efforts to deliver retail products with drones connected to Verizon 4G LTE, as well as 5G testing and integration for delivery. The companies aim to deliver retail products via connected drones at The Villages in Florida.

“We will need the ability to manage and support multiple drones, flying simultaneously, dispatched from a centralized location, operating in a secure and safe environment. To do this at scale, alongside Verizon and Skyward, we’ll need the power of 5G,” said Carol B. Tomé, CEO of UPS.

“We’re just beginning to see how the power of 5G Ultra Wideband will transform the way businesses operate,” said Rima Qureshi, Chief Strategy Officer at Verizon. “By partnering with UPS and other innovative companies, we can learn from each other’s expertise and collaborate to create solutions that help move the world forward.”

Jan 12, 2021

New Species of Wild Bee Discovered in Israel

Posted by in category: futurism

An international team of scientists has discovered a new species of the bee genus Lasioglossum living in sand dunes in Israel.

It is the largest of all bee genera, containing over 1700 species in numerous subgenera worldwide.

Jan 12, 2021

One in Five Brain Cancers Fueled by Overactive Mitochondria

Posted by in categories: biotech/medical, neuroscience

Summary: 20% of glioblastoma brain cancers are fueled by overactive mitochondria. Researchers say these cases may be treatable by drugs currently under trial.

Source: Columbia University.

A new study has found that up to 20% of glioblastomas–an aggressive brain cancer–are fueled by overactive mitochondria and may be treatable with drugs currently in clinical trials.

Jan 12, 2021

Diffractive networks improve optical image classification accuracy

Posted by in categories: information science, robotics/AI

Recently, there has been a reemergence of interest in optical computing platforms for artificial intelligence-related applications. Optics is ideally suited for realizing neural network models because of the high speed, large bandwidth and high interconnectivity of optical information processing. Introduced by UCLA researchers, Diffractive Deep Neural Networks (D2NNs) constitute such an optical computing framework, comprising successive transmissive and/or reflective diffractive surfaces that can process input information through light-matter interaction. These surfaces are designed using standard deep learning techniques in a computer, which are then fabricated and assembled to build a physical optical network. Through experiments performed at terahertz wavelengths, the capability of D2NNs in classifying objects all-optically was demonstrated. In addition to object classification, the success of D2NNs in performing miscellaneous optical design and computation tasks, including e.g., spectral filtering, spectral information encoding, and optical pulse shaping have also been demonstrated.

In their latest paper published in Light: Science & Applications, UCLA team reports a leapfrog advance in D2NN-based image classification accuracy through ensemble learning. The key ingredient behind the success of their approach can be intuitively understood through the experiment of Sir Francis Galton (1822–1911), an English philosopher and statistician, who, while visiting a livestock fair, asked the participants to guess the weight of an ox. None of the hundreds of participants succeeded in guessing the weight. But to his astonishment, Galton found that the median of all the guesses came quite close—1207 pounds, and was accurate within 1% of the true weight of 1198 pounds. This experiment reveals the power of combining many predictions in order to obtain a much more accurate prediction. Ensemble learning manifests this idea in machine learning, where an improved predictive performance is attained by combining multiple models.

In their scheme, UCLA researchers reported an ensemble formed by multiple D2NNs operating in parallel, each of which is individually trained and diversified by optically filtering their inputs using a variety of filters. 1252 D2NNs, uniquely designed in this manner, formed the initial pool of networks, which was then pruned using an iterative pruning algorithm, so that the resulting physical ensemble is not prohibitively large. The final prediction comes from a weighted average of the decisions from all the constituent D2NNs in an ensemble. The researchers evaluated the performance of the resulting D2NN ensembles on CIFAR-10 image dataset, which contains 60000 natural images categorized in 10 classes and is an extensively used dataset for benchmarking various machine learning algorithms. Simulations of their designed ensemble systems revealed that diffractive optical networks can significantly benefit from the ‘wisdom of the crowd’.

Jan 12, 2021

Machine learning accelerates discovery of materials for use in industrial processes

Posted by in categories: materials, robotics/AI

New research led by researchers at the University of Toronto (U of T) and Northwestern University employs machine learning to craft the best building blocks in the assembly of framework materials for use in a targeted application.