# Green Software A software-engineering discipline focused on reducing the carbon emissions of software through carbon, energy, and hardware efficiency. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## 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. ## New chip could help tiny robots traverse complex environments DevFeed: [New chip could help tiny robots traverse complex environments]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-06-23T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Hardware](), [Algorithms](), [3D](), [navigation](), [real-time](), [Green Software](), [Computer science]() Tags: [3d](), [aeronautical-and-astronautical-engineering](), [algorithms](), [artificial-intelligence](), [assembly](), [augmented-and-virtual-reality](), [autonomous-vehicles](), [computer-chips](), [computer-science-and-technology](), [efficiency](), [electrical-engineering-and-computer-science-eecs](), [energy](), [energy-efficiency](), [gleanmer](), [hardware](), [inside](), [laboratory-for-information-and-decision-systems-lids](), [low-power](), [machine-learning](), [memory](), [mit-schwarzman-college-of-computing](), [national-science-foundation-nsf](), [navigation](), [peter-zhi-xuan-li](), [real-time](), [research](), [research-laboratory-of-electronics](), [robotics](), [school-of-engineering](), [sertac-karaman](), [system-on-a-chip](), [trajectory-planning](), [vivienne-sze](), [zih-sing-fu]() ### AI overview MIT researchers developed a low-power chip that combines an efficient mapping algorithm with dedicated hardware to generate detailed 3D maps for robot navigation in real time. The system-on-a-chip uses about 6 milliwatts and is intended for tiny autonomous robots and other battery-limited devices. ### Source excerpt Researchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power. ## 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 ## Improving Compute Sustainability: A Case Study DevFeed: [Improving Compute Sustainability: A Case Study]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2024-10-07T20:45:28Z Content type: article Language: en Sources: [Two Sigma Engineering]() Topics: [Green Software](), [Computing](), [cpu](), [Hardware](), [Software]() Tags: [case-study](), [compute](), [computing](), [cpu](), [efficiency](), [emissions](), [energy](), [hardware](), [software](), [sustainability]() ### AI overview Two Sigma describes a sustainability program examining how to improve the efficiency of its compute resources. A case study focuses on using a routine server refresh to reconfigure resources, increase server utilization, reduce hardware, and lower power consumption while maintaining performance. ### Source excerpt The post Improving Compute Sustainability: A Case Study appeared first on Two Sigma.