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The Klarna AI for Climate Resilience Program funds organizations developing practical AI solutions to help vulnerable communities in lower-middle-income countries adapt to climate change.
The program supports three categories of projects: (1) harnessing and elevating local knowledge by using AI to organize and analyze community insights into concise, actionable information; (2) developing novel AI applications for climate adaptation in real-world settings such as smartphone-based AI advisory systems for smallholder farmers and AI-powered climate-risk assessments for vulnerable regions; and (3) enhancing existing AI climate solutions through improved adoption, cost-effectiveness, sustainability, or by contributing open datasets and benchmarks.
The program is administered through Milkywire and encourages early-stage ideas that need support to refine technical or implementation details. Currently funded projects include disaster resilience and compensation systems, water security and quality improvement using AI, agricultural adaptation and precision irrigation, climate advisory services, environmental data collection, and conservation access.
The program represents a significant corporate commitment to deploying AI technology for climate adaptation where it is most needed.
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Or search similar grants →According to the current listing, eligibility includes: Organizations working to reduce community vulnerability to climate-related risks in lower-middle-income countries. Projects must develop or deploy practical AI solutions for climate adaptation and resilience. Early-stage ideas are encouraged. Both nonprofit and for-profit organizations appear eligible. Confirm the full requirements in the official notice before applying.
The current listing shows up to $300,000 per project. Supports both early-stage concept development and scaling of existing solutions. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Klarna AI for Climate Resilience Program for AI-Powered Climate Adaptation in Developing Countries is funded by Klarna (via Milkywire). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The Sony Research Award Program is Sony's principal channel for funding external academic research, and the Focused Research Award is its collaborative track: up to 150,000 dollars for focused joint research between a university or research institute and Sony. The 2026 research areas are unusually broad for a corporate program and cover most of the modern AI stack alongside Sony's hardware interests - AI and large language models, computer vision, machine learning, robotics, human-computer interaction, affective computing, speech and language technologies, audio technologies, RF sensing, wireless communications, cybersecurity, sports technology, digital humans, generative AI, content creation and neural rendering, plus device-level areas including MicroLED and optical metasurfaces. For AI and robotics groups this makes it one of the wider corporate calls available, though the breadth is deceptive: Sony funds work that connects to its own research agenda, and proposals are strongest when there is an identifiable Sony research counterpart for the collaboration. Eligibility is tightly drawn around the principal investigator rather than the institution. The PI must be a full-time faculty member or researcher at a recognized institution - Assistant Professor, Associate Professor, Professor or equivalent researcher - and must be able to supervise PhD students. Co-PIs are permitted but must be from the same institution and meet the same requirements, which rules out the cross-institutional consortia common in public funding. The 2026 deadline is 15 September 2026 at 11:59pm Pacific, with a separate India-specific time given as 16 September 2026. Submission guidelines are on the Sony Research Award Program site.
The Meta Research PhD Fellowship supports doctoral students conducting research in areas central to Meta's technical agenda, with several of its annual award tracks dedicated to artificial intelligence and machine learning. Current AI-relevant tracks include AI System Hardware/Software Co-Design (high-performance AI algorithms spanning model compression, numerical optimization, benchmarking, and distributed inference and training), Applied Statistics (bias and variance estimation and correction in models and datasets, uncertainty quantification), AR/VR Human Understanding (efficient ML techniques that run on AR/VR devices), and Programming Languages (program synthesis, probabilistic and differentiable programming). Recipients receive two years of paid tuition and fees, a $42,000 annual stipend covering living expenses and conference travel, and a paid visit to Meta headquarters for the annual Fellowship Summit; the award carries no intellectual property claim on the student's research. The 2027 cycle opened August 3, 2026 with applications closing September 20, 2026, reference letters due in October 2026, and winners notified in January 2027.
OpenAI's AI and Teen Development Research Grant Program makes up to 5,000,000 US dollars available in grants of up to 1,000,000 dollars for independent research on how AI affects adolescent development and wellbeing. Applications opened 8 September 2026 at 8:00 AM PDT and close 6 October 2026 at 11:59 PM PST, with notifications by 13 November 2026, and submission is through the SurveyMonkey Apply platform. The published scope has four strands: teen usage patterns and developmental outcomes; AI's potential effects on young people's lives; the factors that cause those effects to differ across populations and contexts; and design interventions and safety mechanisms. The inclusion of the fourth strand is what separates this from a pure effects-measurement programme, since it invites work that proposes and tests product-level safeguards rather than only documenting harm or benefit. The third strand is equally notable: OpenAI is asking specifically about heterogeneity of effect, which is an implicit acknowledgement that aggregate findings about teen AI use have limited policy value. Review is rolling and conducted by internal researchers and outside experts. Non-profit applicants are preferred and for-profit organisations are explicitly not prioritised, and indirect costs are capped at 10 percent of the grant, both of which shape who can realistically compete.