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An anonymous reader quotes a report from Ars Technica: In April, GitHub announced that it was moving subscribers from request-based billing to a usage-based model for its AI-powered Copilot service. As that new pricing model goes into effect today, many GitHub Copilot users are reporting some extreme sticker shock as they realize just how quickly their previous "normal" usage is burning through their newly limited monthly allotment of AI credits. Across social media and forums, many Copilot users are sharing personal statistics showing how just a few hours of AI usage can now account for a large chunk of their new monthly subscription caps. For some users, it reportedly took less than a day to use up a month's usage quota. That's a big change from previous months, when GitHub Copilot subscribers were allocated a certain number of "requests" and "premium requests" based on their payment tier. GitHub said that the old system meant that "a quick chat question and a multi-hour autonomous coding session [could] cost the user the same amount," forcing Copilot itself to "absorb much of the escalating inference cost behind that usage." [...] Indeed, some Copilot users have been sharing estimates from GitHub's own tool showing that their previous monthly usage would rack up bills in the thousands of dollars under the new pricing plan. Under GitHub's new usage-based pricing system, paid Copilot subscriptions instead grant users a certain number of AI "credits" each month, with one credit corresponding to $0.01 of usage. Subscribers also get bonus credits depending on their subscription level: the $10/month Pro plan includes 1,500 credits ($15 worth); the $39 Pro+ plan includes 7,000 credits ($70 worth); and the $100/month Copilot Max plan includes 20,000 credits ($200 worth). The precise number of Copilot credits used by a given prompt is determined by the number of input and output tokens used and the rates charged by the underlying large language model. That means pricing is highly dependent not just on the type of request but on the specific model that a user chooses. One million output tokens from OpenAI's GPT-5.4 nano would run just $1.25 on GitHub Copilot, but that same level of output would run $30 on the frontier GPT-5.5 model (Copilot users who rely on "Auto" mode to pick the most appropriate available model for any request should be extremely careful, as some users report it can switch to expensive models for extremely simple queries).

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Google has asked the EPA for permission to release up to 32 million sterile male mosquitoes in California and Florida over two years. The effort is part of the company's Debug program, which uses Wolbachia-infected males to reduce populations of disease-spreading Aedes aegypti mosquitoes. Google cites a similar approach in Singapore that helped suppress mosquito populations and reduce dengue cases. The Guardian reports: As part of its successful "Debug" program, Google is tapping into its tech expertise to raise an army of sterile male mosquitoes to lower the number of illness-spreading bugs. Mosquitoes -- the world's deadliest animal -- kill more people than any other creature in the world every year by spreading lethal diseases such as dengue, West Nile virus, Zika, chikungunya and malaria. A notice (PDF) from the federal register shows the US Environmental Protection Agency (EPA) is reviewing Google's request to release up to 16 million mosquitoes annually, in Florida and California, over the span of two years. The EPA will decide whether to greenlight Google's request for an experimental use permit after a public comment period, which ends on 5 June. Male mosquitoes don't bite or carry disease. One of the main approaches Google is testing involves rearing male mosquitoes with a naturally occurring bacteria, called wolbachia, which stops them from having offspring with wild female mosquitoes. When an infected male tries to mate with a wild female, her eggs won't hatch; Google explains in a blog post: "the population gets smaller with each generation."

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