Lifeboat Foundation: Safeguarding Humanity
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Isaac Asimov won the Hugo award for Best All-Time Series for his Foundation books, which follow a future human civilization through an apparently inevitable upheaval. The story begins amid a vast galactic empire in decline. Hari Seldon, a mathematician, develops the practice of psychohistory, a method of predicting future events using statistics.

Seldon predicts the fall of the galactic empire lasting 300,000 years. By his calculations, there’s no preventing the oncoming storm, but they can shift its trajectory. With a few small changes, humanity can reduce the period of recovery to just 1,000 years. Seldon is confident enough in his predictions that he convinces the authorities to let him create two gatherings of minds. Collections of scientists who will preserve humanity’s collected knowledge and lift future generations out of the looming dark age, known as the Foundations.

These stories have enjoyed enduring popularity among sci-fi readers, enough that they were recently adapted for television by Apple TV+, but the question remains: Can statistics really predict future events?

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Every year, a few hundred scientists in the United Kingdom try to establish new labs from scratch; globally, thousands of researchers become heads of their own labs. From the outset, it’s a chase for money and a time of intense pressure as scientists try to build research programmes while juggling teaching, fundraising, publishing and family life. Ali began her lab with just £15,000 in grants to cover equipment and experiments; Dan had £20,000. Both need to recruit PhD students, and Dan must also devise and deliver a programme of lectures.

Two researchers. Three years. One pandemic.

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The firm worked with UK weather forecasters to create a model that was better at making short term predictions than existing systems.

First protein folding, now weather forecasting: London-based AI firm DeepMind is continuing its run applying deep learning to hard science problems. Working with the Met Office, the UK’s national weather service, DeepMind has developed a deep-learning tool called DGMR that can accurately predict the likelihood of rain in the next 90 minutes—one of weather forecasting’s toughest challenges.

In a blind comparison with existing tools, several dozen experts judged DGMR’s forecasts to be the best across a range of factors—including its predictions of the location, extent, movement, and intensity of the rain—89% of the time. The results were published in a Nature paper today.

DeepMind’s new tool is no AlphaFold, which cracked open a key problem in biology that scientists had been struggling with for decades. Yet even a small improvement in forecasting matters.

Continue reading “DeepMind’s AI predicts almost exactly when and where it’s going to rain” | >

“DeepGreen is offering a false or dystopian choice,” Deep Sea Conservation Coalition cofounder Matthew Gianni told The Guardian.

Dangling the possibility of widespread electric vehicle adoption by securing the resources necessary to manufacture more and better batteries is certainly tantalizing. But scientists told The Guardian that getting those metals from the seafloor — especially with machines that would cause a poorly-understood environmental impact in an area that’s nearly impossible to monitor and regulate — would come at too great a cost.

“There are some very significant questions being raised by scientists about the impacts of ocean mining,” University of California, Santa Barbara researcher Douglas McCauley told The Guardian. “How much extinction could be generated? How long will it take these extremely low-resilience systems to recover? What impact will it have on the ocean’s capacity to capture carbon?”

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Nonlinearity induced by a single photon is desirable because it can drive power consumption of optical devices to their fundamental quantum limit, and is demonstrated here at room temperature.

The recent progress in nanotechnology1,2 and single-molecule spectroscopy3–5 paves the way for emergent cost-effective organic quantum optical technologies with potential applications in useful devices operating at ambient conditions. We harness a π-conjugated ladder-type polymer strongly coupled to a microcavity forming hybrid light–matter states, so-called exciton-polaritons, to create exciton-polariton condensates with quantum fluid properties. Obeying Bose statistics, exciton-polaritons exhibit an extreme nonlinearity when undergoing bosonic stimulation6, which we have managed to trigger at the single-photon level, thereby providing an efficient way for all-optical ultrafast control over the macroscopic condensate wavefunction. Here, we utilize stable excitons dressed with high-energy molecular vibrations, allowing for single-photon nonlinear operation at ambient conditions.

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We’ve been eagerly following the development of the WiFiWart for some time now, as a quad-core Cortex-A7 USB phone charger with dual WiFi interfaces that runs OpenWrt sounds exactly like the sort of thing we need in our lives. Unfortunately, we’ve just heard from [Walker] that progress on the project has been slowed down indefinitely by crippling chip shortages.

At this point, we’ve all heard how the chip shortage is impacting the big players out there. It makes sense that automakers are feeling the pressure, since they are buying literally millions of components at a clip. But stories like this are a reminder that even an individual’s hobby project can be sidelined by parts that are suddenly 40 times as expensive as they were when you first put them in your bill of materials.

In this particular case, [Walker] explains that a power management chip you could get on DigiKey for $1.20 USD a few months ago is now in such short supply that the best offer he’s found so far is $49.70 a pop from an electronics broker in Shenzhen. It sounds like he’s going to bite the bullet and buy the four of them (ouch) that he needs to build a working prototype, but obviously it’s a no go for production.

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The Conti ransomware gang has developed novel tactics to demolish backups, especially the Veeam recovery software.

Good at identifying and obliterating backups? Speak Russian? The notorious Conti ransomware group may find you a fine hiring prospect.

That’s according to a report published on Wednesday by cyber-risk prevention firm Advanced Intelligence, which details how Conti has honed its backup destruction to a fine art – all the better to find, crush and kill backed-up data. After all, backups are a major obstacle to encouraging ransomware payment.

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China’s new rules on auto data require car companies to store important data locally.

Cars today offer high-tech features and gather troves of data to train algorithms. As China steps up controls over new technologies, WSJ looks at the risks for Tesla and other global brands that are now required to keep data within the country. Screenshot: Tesla China.

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Continue reading “What China’s New Data Rules Mean for Tesla and Other Auto Makers | WSJ” | >