# Sustainability Published articles for Sustainability. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## MIT spinout turns plastic waste into resilient building materials DevFeed: [MIT spinout turns plastic waste into resilient building materials]() Original publisher: [Read original article]() Author: Zach Winn | MIT News Published: 2026-09-14T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [systems]() Tags: [3-d-printing](), [ai](), [aj-perez](), [alumni-ae](), [artificial-intelligence](), [atlas-composites](), [cleaner-industry](), [engineering](), [homes](), [housing](), [manufacturing](), [materials-science-and-engineering](), [matt-pouliot](), [mechanical-engineering](), [platform](), [pollution](), [production](), [recycled-plastic-building-materials](), [robotics](), [school-of-engineering](), [startups](), [sustainability](), [u-s-army](), [water]() ### AI overview MIT spinout Atlas Building Composites is commercializing an AI-powered robotic manufacturing platform that recycles single-use and low-grade plastic into durable building components. Its waterless process has been used for structures including a bridge supplied to the U.S. Army Corps of Engineers. ### Source excerpt Atlas Building Composites is commercializing MIT research to turn plastic waste into parts for buildings and other infrastructure. ## Powering the AI era: How wave energy can complement a 24/7 energy mix DevFeed: [Powering the AI era: How wave energy can complement a 24/7 energy mix]() Original publisher: [Read original article]() Author: Elias Habbar-Baylac Published: 2026-09-10T15:20:22Z Content type: article Language: en Sources: [Cisco Blogs]() Topics: [AI Infrastructure](), [data centers](), [datacenter](), [Artificial Intelligence]() Tags: [ai](), [ai-infrastructure](), [chief-sustainability-office](), [cisco-purpose](), [data-center](), [data-centers](), [energy](), [environmental-sustainability](), [generation](), [infrastructure](), [megawatt](), [our-corporate-purpose](), [sustainability]() ### AI overview The article explains how wave energy could complement solar, wind, and batteries in meeting the continuous electricity needs of AI-era data centers. It discusses a modeled 100 MW flat-load data center and energy portfolios evaluated for cost, reliability, emissions, and round-the-clock availability. ### Source excerpt CorPower Ocean, a Cisco Investments portfolio company, has explored how wave energy technology could complement other sources for 24/7 energy needs. ## Generating scenarios for extreme events, without extreme data DevFeed: [Generating scenarios for extreme events, without extreme data]() Original publisher: [Read original article]() Author: Jennifer Chu | MIT News Published: 2026-08-24T18:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Machine learning](), [Algorithms](), [Critical Infrastructure](), [data]() Tags: [algorithm](), [algorithms](), [artificial-intelligence](), [center-for-computational-science-and-engineering](), [climate](), [climate-risk-assessment](), [computer-modeling](), [critical-infrastructure](), [data](), [extreme-event-aware](), [extreme-weather](), [fire](), [heat](), [idss](), [kai-chang](), [learning-fefb62e9fa83](), [machine-learning](), [mechanical-engineering](), [mit-meche](), [mit-schwarzman-college-of-computing](), [natural-disasters](), [research](), [risk](), [school-of-engineering](), [storm](), [sustainability](), [themis-sapsis](), [weather](), [weather-prediction]() ### AI overview MIT engineers developed a machine-learning algorithm that generates plausible future extreme-event scenarios without requiring past extreme events in the training data. It learns from available records, filters out implausible weather scenarios, and estimates events' frequency, size, intensity, duration, and area of impact to help planners prepare. ### Source excerpt A new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for. ## Paving the way for greener ammonia production DevFeed: [Paving the way for greener ammonia production]() Original publisher: [Read original article]() Author: David L. Chandler | Department of Materials Science and Engineering Published: 2026-08-20T18:45:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [Materials science and engineering](), [acid]() Tags: [agriculture](), [ai-for-materials-science](), [artificial-intelligence](), [bilge-yildiz](), [catalysts](), [chemistry](), [cleaner-fertilizer](), [cleaner-industry](), [computational-materials-science](), [computer-modeling](), [dmse](), [electrochemical-ammonia-production](), [emissions](), [energy](), [fertilizer-production](), [food](), [fossil-fuel](), [green-ammonia](), [greener-fertilizer](), [haber-bosch-process](), [industry](), [machine-learning](), [materials-science-and-engineering](), [mit-dmse](), [nitrogen-dissociation](), [nuclear-science-and-engineering](), [pollution](), [research](), [school-of-engineering](), [school-of-science](), [science](), [sustainability](), [transition-metal-nitrides]() ### AI overview MIT researchers developed an approach to predict promising catalyst materials for electrochemical ammonia production. The method could speed the search for alloys that may help make this lower-emissions process more competitive with the fossil-fuel-dependent Haber-Bosch process. ### Source excerpt New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that's essential to fertilizer and other products. ## Community Day 2026: Save the date! DevFeed: [Community Day 2026: Save the date!]() Original publisher: [Read original article]() Author: Missy Quarry Published: 2026-08-13T00:00:01Z Content type: article Language: en Sources: [Home Assistant]() Topics: [Home Assistant](), [hosting](), [Discord]() Tags: [2026](), [blog](), [community](), [discord](), [events](), [hosting](), [sustainability]() ### AI overview The article announces that Home Assistant Community Day 2026 will take place on Saturday, November 7. It describes changes based on the first event, including more planning time, broader participation from Open Home Foundation projects such as ESPHome and Music Assistant, updated branding centered on sustainability, and additional support for meetup hosts through Discord and a planned dynamic website. ### Source excerpt You've been asking all year, and the wait is over... Mark your calendars, because Community Day 2026 will be held on Saturday, November 7! 🎉 ## How Amazon tracks carbon intensity across its operations DevFeed: [How Amazon tracks carbon intensity across its operations]() Original publisher: [Read original article]() Author: Kerry Constabile Published: 2026-07-01T15:56:42Z Content type: news Language: en Sources: [Amazon Science homepage]() Topics: [amazon](), [data](), [Cloud](), [Routing (disambiguation)]() Tags: [amazon](), [amazon-sustainability-report](), [cloud-services](), [data](), [decarbonization](), [energy](), [operations](), [renewable-energy](), [routing](), [scale](), [sustainability](), [the-climate-pledge](), [transportation]() ### AI overview Amazon describes its use of sector-specific carbon-intensity metrics to track decarbonization across diverse operations. For retail, it measures emissions per unit shipped and reports a 39% reduction from 2019 to the end of 2025, attributing progress to carbon-free energy, routing improvements, lighter packaging, lower-carbon fuels, alternative transportation, and electric vehicles. ### Source excerpt Amazon is developing precise, sector-specific approaches to measuring decarbonization progress -- starting with emissions per unit shipped. ## Community feedback: How can corporations improve support for open source maintainers? DevFeed: [Community feedback: How can corporations improve support for open source maintainers?]() Original publisher: [Read original article]() Author: Google Open Source (noreply@blogger.com) Published: 2026-06-30T18:30:00Z Content type: opinion Language: en Sources: [Google Open Source Blog]() Topics: [Maintainers](), [Open Source](), [Google](), [Pull Request]() Tags: [community](), [conference](), [funding](), [maintainers](), [open-source](), [open-source-communities](), [procurement](), [sponsorship](), [sustainability](), [transparency]() ### AI overview Google Open Source reports community feedback on how corporations can better support open source maintainers. Suggestions include predictable financial support, contribution-based payments, procurement and support services, conference travel sponsorships, respect for community norms, and consistency between documentation and practice. ### Source excerpt by Sophia Vargas, Google Open Source We know that AI is actively transforming the sustainability and socio-technical dynamics of OSS communities. Google Open Source is committed to partnering with open source communities and ecosystems to learn together how we should update our own models for engagement and support. During an open meetup for GitHub Maintainer Month, I led a session to gather community feedback on how corporations can more effectively support open source maintainers. Paying maintainers takes creativity Many maintainers would appreciate consistent financial support. However, facilitating payments to individuals without established contractual relationships remains a complex challenge, particularly across diverse international jurisdictions. Fiscal hosts and programs such as Open Collective, GitHub Sponsors, and the LFX Mentorship Program can simplify components of this process, but they do not resolve the underlying issues of funding sustainability and predictability. While initiatives like the Open Source Endowment are working toward long-term funding sustainability, individual maintainers also had a few ideas: Pay per meaningful contribution vs gameable metrics: Avoid payment models based on easily manipulated units like pull request counts or review volume. A proposed alternative is 'pay per report,' encouraging maintainers to document their achievements and upcoming roadmaps. Commitment-based purchasing: Corporate policies might make procurement simpler (or more complex) than sponsorships, so maintainers could benefit from offering structured support services alongside traditional sponsorship opportunities. Fund conference attendance: In-person networking can be a boon for solo maintainers but it's often cost-prohibitive. For some corporations, travel sponsorship may be a simpler alternative to direct payments. Challenge for Corporations and Fiscal Hosts: How can we assist maintainers in understanding any and all prerequisites and documentation ne ## Expanding our Heat Resilience data to 50+ global cities DevFeed: [Expanding our Heat Resilience data to 50+ global cities]() Original publisher: [Read original article]() Published: 2026-06-30T17:03:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Earth AI](), [datasets](), [Artificial Intelligence](), [Google](), [App](), [data](), [Resilience]() Tags: [ai](), [app](), [climate-sustainability](), [data](), [datasets](), [earth-ai](), [google](), [heat](), [mapping](), [open](), [open-source-models-datasets](), [research](), [resilience](), [sustainability](), [tools]() ### AI overview Google Research is expanding its building-level rooftop reflectivity dataset to cover more than 50 global cities. The data is available through a high-resolution Heat Resilience Earth Engine App and is intended to help urban planners prioritize cool-roof interventions that reduce heat exposure and protect vulnerable communities. ### Source excerpt Climate & Sustainability ## Improving the speed and energy-efficiency of AI agents DevFeed: [Improving the speed and energy-efficiency of AI agents]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-06-25T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [agentic workflows](), [Loop Engineering](), [Green Software](), [Cloud](), [Microsoft](), [microsoft-azure]() Tags: [adam-belay](), [agentic-workflows](), [agents](), [ai](), [ai-agents](), [algorithms](), [artificial-intelligence](), [cloud](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [data](), [data-centers](), [defense-advanced-research-projects-agency-darpa](), [deployment](), [efficiency](), [electrical-engineering-and-computer-science-eecs](), [electronics](), [energy](), [energy-efficiency](), [gohar-chaudhry](), [machine-learning](), [microsoft](), [microsoft-azure](), [mit-schwarzman-college-of-computing](), [murakkab](), [research](), [school-of-engineering](), [software](), [sustainability](), [sustainable-computing](), [workflows]() ### AI overview MIT and Microsoft researchers developed Murakkab, a system that automatically designs and deploys agentic workflows by selecting models, tools, hardware configurations, and computational resources according to user priorities. Tests found that it reduced computational requirements, energy use, and costs without reducing performance. ### Source excerpt A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications. ## The fuel of the future is already here: Why TRISO matters DevFeed: [The fuel of the future is already here: Why TRISO matters]() Original publisher: [Read original article]() Author: Katy Huff Published: 2026-06-24T19:57:09Z Content type: article Language: en Sources: [Amazon Science homepage]() Topics: [AI Infrastructure](), [amazon](), [cloud-computing]() Tags: [advanced-nuclear-reactors](), [advanced-reactor-fuel-fabrication](), [ai-infrastructure](), [amazon](), [amazon-nuclear-energy](), [clean-energy-data-centers](), [cloud-computing](), [decarbonization](), [durability](), [energy](), [haleu](), [integrity](), [modular-nuclear-reactors](), [nuclear-energy-for-ai](), [physical-science](), [renewable-energy](), [resilience](), [safety](), [science](), [sustainability](), [triso-fuel](), [triso-particles](), [x-energy-xe-100]() ### AI overview Amazon explains how TRISO nuclear fuel particles use layered carbon and ceramic coatings to contain radioactive byproducts and withstand extreme temperatures. The article connects the technology to rising energy demands from AI infrastructure and cloud computing, citing testing that found no detectable failures at 1600°C for 300 hours. ### Source excerpt Millimeter-scale particles of nuclear-reactor fuel are encased in four layers of different materials that act as a "miniature containment system". ## From pixels to planning: Earth AI for nature restoration DevFeed: [From pixels to planning: Earth AI for nature restoration]() Original publisher: [Read original article]() Published: 2026-06-16T17:30:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Earth AI](), [Artificial Intelligence](), [dataset](), [Deep learning](), [Google](), [data]() Tags: [ai](), [climate-sustainability](), [data](), [deep-learning](), [earth-ai](), [google](), [machine-intelligence](), [open-source-models-datasets](), [research](), [resource](), [sustainability](), [uk](), [vector]() ### AI overview Google Research describes a high-resolution deep learning approach that converts pixel-based maps of fine-scale ecological features into a vectorized dataset. The resource is intended to support nature restoration, carbon accounting, and biodiversity efforts across working landscapes in the UK while considering food security. ### Source excerpt Climate & Sustainability ## A low-carbon computing platform from your retired phones DevFeed: [A low-carbon computing platform from your retired phones]() Original publisher: [Read original article]() Published: 2026-06-12T17:37:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Green Software](), [cloud-computing](), [datacenter](), [Hardware](), [cpu](), [Google]() Tags: [climate-sustainability](), [cloud](), [cloud-computing](), [compute](), [datacenter](), [distributed-systems-parallel-computing](), [efficiency](), [energy](), [energy-efficiency](), [google](), [hardware](), [memory](), [performance](), [servers](), [smartphones](), [storage](), [sustainability]() ### AI overview Researchers at the University of California San Diego, with Google's support, are developing a low-carbon cloud computing platform from retired smartphones. A planned datacenter using 2,000 Pixel smartphones aims to provide low-cost computing while reducing the need for newly manufactured hardware and its associated emissions. ### Source excerpt Climate & Sustainability ## Startup's nuclear-inspired cooling system could make data centers more sustainable DevFeed: [Startup's nuclear-inspired cooling system could make data centers more sustainable]() Original publisher: [Read original article]() Author: Zach Winn | MIT News Published: 2026-06-10T04:00:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [data centers](), [Artificial Intelligence](), [cloud-infrastructure](), [Computer science]() Tags: [ai](), [ai-data-centers](), [artificial-intelligence](), [computer-science-and-technology](), [cooling](), [data-center-cooling](), [data-center-sustainability](), [data-centers](), [efficiency](), [energy](), [energy-efficiency](), [energy-storage](), [ferveret](), [matteo-bucci](), [nuclear-science-and-engineering](), [power](), [reza-azizian](), [school-of-engineering](), [startups](), [sustainability](), [sustainable-computing](), [technology-and-society](), [water]() ### AI overview Ferveret, a startup founded by two MIT researchers, is adapting nuclear-reactor heat-transfer methods to cool AI data-center servers with a specialized liquid. Its Adaptive Phase Cooling system uses small, frequently detaching bubbles to improve heat transfer without water and with less electricity. ### Source excerpt Founded by two researchers from MIT, Ferveret reduces the amount of energy and water required to cool the chips that power AI. ## The next chapter in flood resilience: Open sourcing Google's hydrology framework DevFeed: [The next chapter in flood resilience: Open sourcing Google's hydrology framework]() Original publisher: [Read original article]() Published: 2026-06-03T18:37:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Google](), [Artificial Intelligence](), [AI Models](), [Resilience](), [Open Source](), [GitHub](), [Earth AI](), [Python](), [PyTorch](), [Google AI]() Tags: [ai](), [ai-models](), [architecture](), [climate-sustainability](), [data](), [earth-ai](), [generative-ai](), [github](), [google](), [open-source](), [open-source-models-datasets](), [python](), [pytorch](), [research](), [resilience](), [sustainability](), [training]() ### AI overview Google Research is open-sourcing a Python and PyTorch hydrology framework for AI-based riverine flood forecasting, enabling meteorological and hydrological agencies to use local data, train models, and improve flood warnings. ### Source excerpt Climate & Sustainability ## BEGA joins Works with Home Assistant DevFeed: [BEGA joins Works with Home Assistant]() Original publisher: [Read original article]() Author: Miranda Bishop Published: 2026-05-05T00:00:01Z Content type: news Language: en Sources: [Home Assistant]() Topics: [Home Assistant]() Tags: [community](), [devices](), [ecosystem](), [energy](), [offline](), [safety](), [smart](), [smart-home](), [sustainability](), [tech](), [works-with-home-assistant]() ### AI overview BEGA has joined the Works with Home Assistant program, bringing a large portfolio of certified architectural lighting products. Its BEGA Smart system uses Zigbee, supports flexible expansion, and works offline without an internet connection. The article also highlights BEGA's repairable fixtures and replaceable components, including outdoor lighting options. ### Source excerpt How do you more or less double the number of Works with Home Assistant-certified devices available to our community? Have BEGA join the program! This German firm has spent more than 75 years designing a wide range of architectural lighting that sets the industry standard: and now they're bringing that expertise to your smart home. Bright BEGA-nnings If you haven't heard of BEGA before, you may have admired their work without realizing it. That's because they produce the kind of beautifully engineered fixtures you see gracing the facades of fancy hotels, elegant public buildings, and stylish modern homes worldwide. They're probably better known for this kind of work than for smart home tech, which is precisely what makes their joining the Works with Home Assistant program so exciting. Because BEGA aren't just dipping a toe in: they're bringing what's almost certainly the largest single addition of certified devices we've ever had in one go: enough to very nearly double the number of certified products in the program! And it's not just the volume that impresses. BEGA Smart - their Zigbee-powered smart lighting system - is flexible, expandable, and designed to work entirely offline, with no internet connection required. BEGA: putting the smart into smart home lighting. "With BEGA Smart, we aim to combine high-quality architectural lighting with intelligent control. Integrating with Home Assistant allows us to bring our lighting solutions into an open and flexible smart home ecosystem that many of our customers already value. By doing so, we enhance comfort, safety, and energy efficiency while enabling new ways to experience light. We're excited to support the community and be part of this ecosystem." - Heinrich Gantenbrink, Managing Partner at BEGA Beyond beautiful design BEGA's premium positioning isn't only about aesthetics. Their commitment to repairability also aligns well with the Open Home Foundation's sustainability principles. Rather than treating a luminaire a ## ubisys joins Works with Home Assistant DevFeed: [ubisys joins Works with Home Assistant]() Original publisher: [Read original article]() Author: Miranda Bishop Published: 2026-04-23T00:00:01Z Content type: news Language: en Sources: [Home Assistant]() Topics: [Home Assistant](), [Automation](), [Hardware](), [interoperability](), [Network]() Tags: [automation](), [battery](), [community](), [devices](), [hardware](), [home-automation](), [innovation](), [integration](), [interoperability](), [mesh](), [network](), [open](), [partnership](), [standards](), [sustainability](), [updates](), [wireless](), [works-with-home-assistant](), [zigbee]() ### AI overview The article announces that ubisys has joined Works with Home Assistant. It describes ubisys's Zigbee smart home devices for retrofitting, their long hardware and software support, and the company's involvement in developing open standards and improving interoperability with Home Assistant. ### Source excerpt We're thrilled to welcome ubisys to Works with Home Assistant! This German company has been dedicated to smart home automation for more than 20 years, and offers a range of Zigbee devices designed to help you retrofit your home. If retrofitting is conjuring up images of avocado bathrooms 🥑 and artexed ceilings, fear not - it just means upgrading what you already have, rather than ripping it out and starting again. Better for your home, and the planet 🌍. Here today, here tomorrow Founded in Düsseldorf in 2005, ubisys build devices that last. They back their hardware with a five-year warranty and software updates for the long term, meaning the device you buy today won't end up obsolete in a few years' time - in fact, they're still shipping feature updates for hardware designed in 2010! That kind of longevity aligns closely with the Open Home Foundation's own sustainability principle, and is just one reason why they're such a great (retro)fit for the program! Zigbee is another... Zigbee to the bone If you're scratching your head at the mention of Zigbee, allow me to explain: it's a wireless standard that lets smart home devices communicate with each other, regardless of who made them. Unlike WiFi, it's a mesh network, meaning Zigbee devices "talk" to each other, as well as to a central hub (like your Home Assistant setup), strengthening the connection across your whole home. It runs entirely locally, with no cloud dependency, and is optimized for long battery life. For retrofit devices that need to just get on with their jobs in the background, these qualities really count, and explains why ubisys refer to Zigbee as the backbone of everything they build. And they don't just use the standard, they help shape it: ubisys are active members of the Connectivity Standards Alliance (the organization responsible for maintaining and developing Zigbee), sitting on working groups and committees at the highest level - helping improve the standard for the benefit of the whole communi ## Protecting cities with AI-driven flash flood forecasting DevFeed: [Protecting cities with AI-driven flash flood forecasting]() Original publisher: [Read original article]() Published: 2026-03-12T13:03:15Z Content type: news Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Google](), [Machine Learning & Artificial Intelligence](), [Resilience](), [data]() Tags: [ai](), [ai-training](), [climate-sustainability](), [data](), [earth-ai](), [flash](), [generative-ai](), [google](), [machine-learning](), [news](), [open-source-models-datasets](), [research](), [resilience](), [sustainability]() ### AI overview Google Research announces urban flash flood forecasts that use an AI-powered methodology to provide up to 24 hours of advance warning. The article describes the forecasting challenge posed by rapidly developing floods, limited ground-truth data, and the need to expand early-warning coverage for vulnerable communities. ### Source excerpt Climate & Sustainability ## Introducing Groundsource: Turning news reports into data with Gemini DevFeed: [Introducing Groundsource: Turning news reports into data with Gemini]() Original publisher: [Read original article]() Published: 2026-03-12T10:42:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [datasets](), [Ground truth / benchmark quality](), [data](), [Resilience](), [Google]() Tags: [climate-sustainability](), [datasets](), [flash](), [gemini](), [generative-ai](), [natural-language-processing](), [open-source-models-datasets](), [research](), [resilience](), [sustainability]() ### AI overview Google Research introduces Groundsource, a scalable methodology that uses Gemini to convert unstructured global news reports into verified historical data. Its first open-access dataset contains 2.6 million flash-flood records from more than 150 countries, supporting research, forecasting, and urban crisis resilience. ### Source excerpt Climate & Sustainability ## Where wild things roam: Identifying wildlife with SpeciesNet DevFeed: [Where wild things roam: Identifying wildlife with SpeciesNet]() Original publisher: [Read original article]() Published: 2026-03-06T17:59:38Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Earth AI](), [Artificial Intelligence](), [Google](), [Open Source](), [Deep learning](), [Data analysis](), [data](), [migration]() Tags: [ai](), [ai-models](), [analysis](), [climate-sustainability](), [data](), [datasets](), [deep-learning](), [earth-ai](), [generative-ai](), [google](), [migration](), [open-source](), [open-source-models-datasets](), [sustainability]() ### AI overview Google Research describes SpeciesNet, an open-source AI model that identifies nearly 2,500 animal categories in camera-trap images. Trained on 65 million labelled images, it is being used by research groups worldwide to support wildlife monitoring, conservation, and analysis of animal populations and patterns. ### Source excerpt Climate & Sustainability ## Project Odin: Supporting the Sustainability of Critical Ethereum Infrastructure DevFeed: [Project Odin: Supporting the Sustainability of Critical Ethereum Infrastructure]() Original publisher: [Read original article]() Author: Raul Romanutti; Funding Coordination Team Published: 2026-02-27T00:00:00Z Content type: opinion Language: en Sources: [Ethereum Foundation Blog]() Topics: [Ethereum](), [Open Source](), [Blockchain](), [Resilience](), [Tooling]() Tags: [blockchain](), [ethereum](), [funding](), [funding-coordination](), [infrastructure](), [open-source](), [sustainability]() ### AI overview Project Odin is a structured support program for selected Ethereum Foundation grantees. It provides embedded strategic advisors to help critical infrastructure teams plan and test revenue opportunities, with the goal of improving financial sustainability and reducing dependence on a single funding source. ### Source excerpt The commons called. It wants a runway. Every so often, in the blockchain world's usual cycle of funding scares, a team maintaining a widely used open source public good declares mayday. Libp2p is a core infrastructure stack that powers multiple Ethereum clients (among others) and a large part of... ## Join the Python Security Response Team! DevFeed: [Join the Python Security Response Team!]() Original publisher: [Read original article]() Author: Seth Larson Published: 2026-02-17T00:00:00Z Content type: article Language: en Sources: [Python Insider]() Topics: [psrt](), [Python](), [Security](), [vulnerability](), [ecosystem-security](), [Maintainers](), [Open Source]() Tags: [ecosystem-security](), [github](), [maintainers](), [onboarding](), [onboarding-and-offboarding](), [open-source](), [process](), [psrt](), [python](), [security](), [sustainability](), [vulnerability]() ### AI overview The Python Security Response Team (PSRT) has adopted a public governance document, PEP 811, that defines member responsibilities, onboarding and offboarding processes, and its relationship with the Python Steering Council. The team is adding members and coordinates vulnerability reports, remediations, advisories, and security workflows across the Python ecosystem. ### Source excerpt The Python Security Response Team now has an approved public governance document (PEP 811) and is welcoming new members. ## How AI trained on birds is surfacing underwater mysteries DevFeed: [How AI trained on birds is surfacing underwater mysteries]() Original publisher: [Read original article]() Published: 2026-02-09T18:38:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [foundation-models](), [Google](), [dataset](), [Cloud](), [Monitoring]() Tags: [agile](), [ai](), [climate-sustainability](), [deep-dive](), [embedding](), [google](), [google-cloud](), [models](), [open-source-models-datasets](), [research](), [sound-accoustics](), [sustainability](), [tutorial]() ### AI overview Google Research describes how Perch 2.0, a bioacoustics foundation model trained primarily on birds and other terrestrial animals, transfers effectively to underwater audio tasks. The article highlights whale-vocalization classification, marine-ecosystem research, and a Google Colab tutorial using NOAA acoustic data through Google Cloud. ### Source excerpt Climate & Sustainability ## NeuralGCM harnesses AI to better simulate long-range global precipitation DevFeed: [NeuralGCM harnesses AI to better simulate long-range global precipitation]() Original publisher: [Read original article]() Published: 2026-01-12T17:52:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Machine Learning & Artificial Intelligence](), [Artificial Intelligence](), [Neural Network](), [Google](), [Earth AI](), [AI Research]() Tags: [ai](), [climate-sustainability](), [earth-ai](), [general-science](), [global](), [google](), [machine-intelligence](), [machine-learning](), [nasa](), [open](), [open-source-models-datasets](), [research](), [science](), [sustainability]() ### AI overview Google Research presents NeuralGCM, a hybrid atmospheric model that combines physics-based modeling with a neural network trained on NASA satellite precipitation observations. The model improves global precipitation simulations, including average rainfall, extreme events, and daily weather cycles, while supporting longer-range weather and climate research. ### Source excerpt Climate & Sustainability ## Separating natural forests from other tree cover with AI for deforestation-free supply chains DevFeed: [Separating natural forests from other tree cover with AI for deforestation-free supply chains]() Original publisher: [Read original article]() Published: 2025-11-13T19:04:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Google](), [dataset](), [data](), [Monitoring]() Tags: [ai](), [climate-sustainability](), [data](), [global](), [google](), [monitoring](), [open-source-models-datasets](), [research](), [responsible-ai](), [sustainability]() ### AI overview Google Research and Google DeepMind are releasing Natural Forests of the World 2020, an AI-powered map and dataset that distinguishes natural forests from other tree cover. The globally consistent 10-meter-resolution map is intended to support deforestation and degradation monitoring, supply-chain due diligence, and compliance with deforestation-free goals, including the European Union's regulation on deforestation-free products. ### Source excerpt Climate & Sustainability [Next page]()