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 toolis 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.
Forecasting rain, especially heavy rain, is crucial for a lot of industries, from outdoor events to aviation to emergency services. But doing it well is hard. Figuring out how much water is in the sky, and when and where it’s going to fall, depends on a number of weather processes, such as changes in temperature, cloud formation, and wind. All these factors are complex enough by themselves, but they’re even more complex when taken together.
The best existing forecasting techniques use massive computer simulations of atmospheric physics. These work well for longer-term forecasting but are less good at predicting what’s going to happen in the next hour or so, known as nowcasting. Previous deep-learning techniques have been developed, but these typically do well at one thing, such as predicting location, at the expense of something else, such as predicting intensity.
Comparison of DGMR with actual radar data and two rival forecasting techniques for heavy rainfall over the eastern US in April 2019DEEPMIND
“The nowcasting of precipitation remains a substantial challenge for meteorologists,” says Greg Carbin, chief of forecast operations at the NOAA Weather Prediction Center in the US, who was not involved in the work.
The DeepMind team trained their AI on radar data. Many countries release frequent snapshots throughout the day of radar measurements that track the formation and movement of clouds. In the UK, for example, a new reading is released every five minutes. Putting these snapshots together provides an up-to-date stop-motion video that shows how rain patterns are moving across a country, similar to the forecast visuals you see on TV.
The researchers fed this data to a deep generative network, similar to a GAN—a kind of AI that is trained to generate new samples of data that are very similar to the real data it was trained on. GANs have been used to generate fake faces, even fake Rembrandts. In this case, DGMR (which stands for “deep generative model of rainfall”) learned to generate fake radar snapshots that continued the sequence of actual measurements. It’s the same idea as seeing a few frames of a movie and guessing what’s going to come next, says Shakir Mohamed, who led the research at DeepMind.
To test the approach, the team asked 56 weather forecasters at the Met Office (who were not otherwise involved in the work) to rate DGMR in a blind comparison with forecasts made by a state-of-the-art physics simulation and a rival deep-learning tool; 89% said that they preferred the results given by DGMR.
“Machine-learning algorithms generally try and optimize for one simple measure of how good its prediction is,” says Niall Robinson, head of partnerships and product innovation at the Met Office, who coauthored the study. “However, weather forecasts can be good or bad in lots of different ways. Perhaps one forecast gets precipitation in the right location but at the wrong intensity, or another gets the right mix of intensities but in the wrong places, and so on. We went to a lot of effort in this research to assess our algorithm against a wide suite of metrics.”
DeepMind’s collaboration with the Met Office is a good example of AI development done in collaboration with the end user, something that seems like an obviously good idea but often does not happen. The team worked on the project for several years, and input from the Met Office’s experts shaped the project. “It pushed our model development in a different way than we would have gone down on our own,” says Suman Ravuri, a research scientist at DeepMind. “Otherwise we might have made a model that was ultimately not particularly useful.”
DeepMind is also eager to demonstrate that its AI has practical applications.. For Shakir, DGMR is part of the same story as AlphaFold: the company is cashing in on
By: Will Douglas Heaven
Title: DeepMind’s AI predicts almost exactly when and where it’s going to rain
Sourced From: www.technologyreview.com/2021/09/29/1036331/deepminds-ai-predicts-almost-exactly-when-and-where-its-going-to-rain/
Published Date: Wed, 29 Sep 2021 15:00:00 +0000
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LATAM crypto exchange Bitso and FMF launch NFT of Mexico’s National Team jerseys
Bitso, a leading cryptocurrency platform operating in Latin America, and the Mexican Football Federation (FMF), today announced the joint launch of the first collectible NFT of the Mexico National Team’s jerseys that was acquired in cryptocurrencies.
This morning through their social media platforms, the FMF and Bitso announced the opportunity to acquire the new official National Team fan jerseys ahead of the team’s participation in the 2022 World Cup. In just 20 minutes, the entire collection sold out.
The NFTs of the jerseys have an exclusive design for the metaverse – each is unique on the blockchain and can be resold by its owner in subsequent transactions.
The collection consisted of 100 official physical jerseys, each with a corresponding NFT version of the jersey that fans’ avatars can wear within the Decentraland metaverse. Each physical and NFT jersey set sold for the equivalent of $1,800 MXN in ethers.
“Our mission is to make cryptocurrency useful in the everyday life of Mexicans; we are committed to spreading the technology through innovative opportunities that help people throughout the country familiarize themselves with this new world. We are very excited to offer the incredible, historic opportunity for the fans of our National Team so that through their Bitso account, they can wear the colors of the National Team on and ‘off’ the field in the metaverse.”
– Bárbara González Briseño, General Director of Bitso México
Created by Bitso, the virtual jersey sports the official colors of Mexico and the new National Team shield, characteristics that will make it stand out when users wear it in the virtual world of Decentraland.
The post LATAM crypto exchange Bitso and FMF launch NFT of Mexico’s National Team jerseys appeared first on CryptoNinjas.
Title: LATAM crypto exchange Bitso and FMF launch NFT of Mexico’s National Team jerseys
Sourced From: www.cryptoninjas.net/2022/07/29/latam-crypto-exchange-bitso-and-fmf-launch-nft-of-mexicos-national-team-jerseys/
Published Date: Fri, 29 Jul 2022 15:19:02 +0000
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Long-running crypto exchange EXMO unveils “lively” rebrand amidst growth
EXMO, a crypto exchange platform operating since 2014, announced this week a rebranded visual identity with includes a new logo, brand colors, and design features. This new branding comes as EXMO continues to grow its crypto platform while also seeking to expand its presence in other jurisdictions.
Some new developments underway at EXMO:
Soon, users will be able to earn passive income from EXMO’s new staking platform.Plans to launch an EXMO crypto debit card.Expansion of its services in international markets with the opening of offices in Poland and Lithuania.
EXMO’s new logo
The rationale for the re-brand:
“At EXMO, we have a vision of a world where crypto is in every wallet. Hassle-free. We want to achieve this by making crypto as simple and accessible to everyone as possible. And we know that you already appreciate EXMO for offering user-friendly services and helpful support. Also for the opportunity to trade anywhere and anytime, closing deals in just a few taps. Such important changes required a rethinking of our corporate style, which has long needed a massive upgrade. So today we are introducing a new brand identity for EXMO with a completely new visual concept. We are launching a new logo, brand colors, and design elements. Our key design principles are simplicity, boldness, and a pinch of fun. But most importantly, we have changed our logo. Simple and easily recognizable, it represents the humanity of our brand. The logo stands out due to the wavy letter ‘m’ which symbolizes exchange rate charts and also resembles a spring that will launch you into the crypto world.”
– The EXMO Team regarding the re-branding
The post Long-running crypto exchange EXMO unveils “lively” rebrand amidst growth appeared first on CryptoNinjas.
Title: Long-running crypto exchange EXMO unveils “lively” rebrand amidst growth
Sourced From: www.cryptoninjas.net/2022/07/26/long-running-crypto-exchange-exmo-unveils-lively-rebrand-amidst-growth/
Published Date: Tue, 26 Jul 2022 08:10:38 +0000
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Stitching together the grid will save lives as extreme weather worsens
The blistering heat waves that set temperature records across much of the US in recent days have strained electricity systems, threatening to knock out power in vulnerable regions of the country.
The electricity has largely stayed online so far this summer, but there have been scattered problems and close calls already.
Heavy use of energy-sucking air-conditioners is the biggest problem. But intense heat can also reduce the output of power plants, blow transformers, and force power lines to sag. Severe droughts across large parts of the country have also significantly reduced the availability of hydroelectric power, according to the North American Electric Reliability Corporation (NERC).
It’s unlikely to get better soon. A number of grid operators may struggle to meet peak summer demand, creating the risk of rolling blackouts, the NERC report notes.
The nation’s isolated and antiquated grids are in desperate need of upgrades to keep the lights, heat, and air-conditioning on in the midst of extreme weather events that climate change is making more common, severe, and dangerous. One clear way to ease many of these issues is to more tightly integrate the country’s regional grids, stitching them together with more long-range transmission lines.
If electricity generated in one area can be more easily shared across much wider regions, power can simply flow to where it’s needed at those moments when customers crank up air-conditioners en masse, or when power plants or fuel supply lines fail amid soaring temperatures, wildfires, hurricanes, or other events, says Liza Reed, a research manager focused on transmission at the Niskanen Center, a Washington, DC, think tank.
The problem is it’s proved difficult to build more long-range transmission and grid interconnections for a variety of reasons, including the permitting challenges of erecting wires through private and public lands across cities, counties, and states and the reluctance of local authorities to forfeit control or submit to greater federal oversight.
The case of Texas
The unreliability of the US grid is not a new problem. Severe heat and winter storms have repeatedly exposed the frailty of electricity systems in recent years, leaving thousands to millions of people without power as temperatures spiked or plunged.
One of the fundamental challenges is that the grids today are highly fragmented. There are three main electricity networks within the US: the Eastern Grid, the Western Grid, and the Electric Reliability Council of Texas (ERCOT). But there are numerous regional transmission organizations within those first two systems, including the California Independent System Operator, Southwest Power Pool, PJM Interconnection, New York ISO, and more.
These grids form a complex web of networks operating under different regulators, rules and market structures, and often with limited connections between them.
A variety of regional transmission organizations oversee different parts of the nation’s aging and fragmented grids, which operate under different rules and with often limited connections between them.
ERCOT is especially isolated, in part because of the desire among local politicians, citizens, and power companies to avoid added competition, the hassle of following other states’ rules, and oversight from the Federal Energy Regulatory Commission (FERC). But the state offers a case study in why that can be a serious problem amid increasingly harsh climate conditions, Reed says.
The Texas grid operator pleaded with customers several times earlier this month to cut electricity use as blistering summer temperatures created demand surges that threatened to outstrip supply and require rolling blackouts. Low wind conditions, cloud cover, and outages at fossil-fuel power plants added to the strains.
Shutting off the electricity needed to run air-conditioning in triple-digit temperatures
By: James Temple
Title: Stitching together the grid will save lives as extreme weather worsens
Sourced From: www.technologyreview.com/2022/07/28/1056483/stitching-together-the-grid-will-save-lives-as-extreme-weather-worsens/
Published Date: Thu, 28 Jul 2022 08:00:00 +0000
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