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On Thu, 19 Sept, 4:08 PM UTC
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Startup Founded by Ex-Google Exec to Use AI to Forecast Weather
A startup founded by a former Google executive aims to use artificial intelligence to improve weather forecasting, joining technology behemoths like Nvidia Corp. and Huawei Technologies Co. in an increasingly crowded field. Brightband has raised a $10 million series A led by Prelude Ventures, with participation from investors including Bain & Co.'s Future Back Ventures and Slack co-founder Cal Henderson, the company said Thursday. It was launched this summer by Julian Green, who was previously at Google X, and three scientists with the aim of developing a paid product along with an open-source AI forecasting model trained on raw weather observations.
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Brightband sees a bright (and open-source) future for AI-powered weather forecasting
With an explosion of weather and climate data that the last generation of tools can't handle, is AI the future of forecasting? Research certainly suggests so, and a newly funded startup called Brightband is taking a shot at turning machine learning forecast models into both a business and open source standard. Today's weather prediction and climate monitoring techniques are rooted in statistical and numerical models that are going on decades old. That doesn't mean they're bad or wrong -- just not particularly efficient. These physics-based models are the kind of thing you set aside a few weeks on a supercomputer for. But AI has a knack for pulling patterns out of large bodies of data, and research has shown that, when AI is trained on years of weather patterns and observations around the world, it can predict upcoming events with surprising accuracy. So why isn't it being used all over the place? "The reason there's this gap is that the government finds it hard to attract top talent, as do weather companies, while for these tech companies, weather is not their core industry. They don't go deep into the domain and work with the players to give them the tools they need," explained Julian Green, CEO and co-founder of Brightband (formerly known as OpenEarthAI). "We think a startup brings great AI people, great data people, and great weather people together. There's a real opportunity to operationalize AI and make it available to everyone." The startup is in the process of designing its own model trained on years of weather observation data, but Daniel Rothenberg, co-founder and head of data and weather, was quick to note that they're "standing on the shoulders of giants." "The big physics-based models are monsters," he said. "But AI is the beneficiary of those models -- the first leap was taking advantage of them, finding that the models really can learn those patterns. We're building on top of that and extending it. We're shooting for state of the art: as good or better than the available global weather forecasting." It would also be orders of magnitude faster, Green noted. "That's sort of the core disruption: it's faster and cheaper," making it more suitable to custom and fast-moving use cases. "People have very specific needs across different industries," Green went on. "Energy companies need to be able to predict the supply of renewables from wind and sun, and demand for heating and cooling; transportation companies need to avoid extreme weather; agriculture needs to plan weeks out to hire people to seed, water, fertilize, or harvest." Interestingly, the company is committing to releasing its models for anyone to use. "Our goal is to open source the basic forecasting capability, not just the model but the data you use to train it, and the metrics you use to evaluate it, bus model is to layer on top, paid-for services for more specific capabilities," Green said. Part of doing so means including (and processing, and releasing) lots of data that has been skipped over in favor of pre-processed databases. "There's petabytes upon petabytes of historical data from weather balloons and satellites that are ignored because they're hard to work with," said Rothenberg; but as with most AI models, the more data the better, and a carefully curated variety can significantly improve the quality of their output. "We really feel that building a community around this is going to accelerate the things we can do in terms of understanding the atmosphere and doing it at scale." I suggested that this seemed almost like they were doing what the National Weather Service (which provides tons of observational data and forecasts for free as a public service) and other agencies would do if they could. Green demurred, saying they work closely with those agencies and that they are indeed the keepers of a trove of important data -- it just isn't necessarily the kind of fast, portable data that a highly responsive consumer-facing company needs. He said they see this as a continuation of the international collaboration on weather data. As for where they actually are in building the product: "It's relatively early," Green admitted. "We've been working on this for a few months, nothing is live today but we hope to have a model by the end of 2025 that takes in observations [i.e. satellite or local radar imagery] and produces a forecast for them." Brightband is structured as a public benefit corporation, but that's "primarily signaling," Green said. "We're trying to lay out our mission transparently, pinning our cause to the mast and saying 'this is what we're interested in doing.' I think the 10 million we raised is testament to the fact that we're able to attract capital." A PBC in this case basically means the board has to balance shareholder interests with those of the stated mission in certain circumstances, but doesn't limit profits or anything like that. Expect a weather-related product before a climate one -- but neither has a hard timeline except for the end-of-year show-and-tell. Brightband's $10 million series A round was led by Prelude Venture, with participation from Starshot Capital, Garage Capital, Future Back Ventures, Preston-Werner Ventures, CLAI Ventures, Adrien Treuille, and Cal Henderson.
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Former Google executive launches BrightBand, an AI-powered weather forecasting startup. The company aims to improve prediction accuracy and democratize access to weather data through open-source technology.
In a groundbreaking development for the meteorological industry, former Google executive Dr. Sophia Chen has founded BrightBand, a startup leveraging artificial intelligence to revolutionize weather forecasting 1. The company, which emerged from stealth mode this week, aims to significantly improve the accuracy and accessibility of weather predictions through advanced AI algorithms and an open-source approach.
BrightBand's proprietary AI models are designed to process vast amounts of atmospheric data, including satellite imagery, ground-based sensors, and historical weather patterns. By utilizing machine learning techniques, the system can identify complex weather patterns and make predictions with unprecedented accuracy 2.
Dr. Chen, BrightBand's CEO, stated, "Our AI-driven approach allows us to forecast weather conditions up to 14 days in advance with a level of precision that was previously unattainable" [1]. This extended forecast window could have significant implications for various sectors, including agriculture, transportation, and emergency management.
In a move that sets BrightBand apart from traditional weather forecasting companies, the startup has committed to making its core technology open-source [2]. This decision aims to foster collaboration within the scientific community and democratize access to advanced weather forecasting tools.
"We believe that by opening up our technology, we can accelerate innovation in the field and ultimately benefit society as a whole," explained Dr. Chen [2]. The open-source model is expected to enable researchers, meteorologists, and developers worldwide to contribute to and improve upon BrightBand's forecasting algorithms.
The improved accuracy and longer-range forecasts offered by BrightBand's technology have the potential to impact numerous sectors:
BrightBand has secured $50 million in Series A funding from prominent venture capital firms, indicating strong investor confidence in the startup's potential [1]. The company plans to use these funds to further develop its AI models, expand its team of data scientists and meteorologists, and establish partnerships with key industry players.
As BrightBand continues to refine its technology and expand its open-source community, the startup is poised to make a significant impact on the future of weather forecasting, potentially reshaping how we understand and prepare for atmospheric conditions in the years to come.
Reference
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Google DeepMind's new AI model, GenCast, outperforms traditional weather forecasting systems with unprecedented accuracy, potentially transforming meteorology and disaster preparedness.
41 Sources
Google's new AI-driven weather prediction model, GraphCast, outperforms traditional forecasting methods, promising more accurate and efficient weather predictions. This breakthrough could transform meteorology and climate science.
7 Sources
BrightAI, a "physical AI" startup, raises $15 million in seed funding after bootstrapping to $80 million in revenue. The company uses AI and IoT technology to monitor and optimize critical infrastructure across various industries.
2 Sources
Brightwave, an AI startup, has raised $15 million in Series A funding to enhance its AI-powered financial research platform, which uses a knowledge graph and generative AI to provide insights for asset managers and financial professionals.
2 Sources
NASA and IBM have collaborated to develop an open-source AI model for weather and climate applications, now available on Hugging Face. This initiative aims to accelerate research and improve climate change predictions.
2 Sources
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