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GSF Standards Working Group
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2024.02.15 #102

Closed seanmcilroy29 closed 6 months ago

seanmcilroy29 commented 7 months ago

2024.02.15 Agenda/Minutes

Time 1600 (GMT) - See the time in your timezone

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Agenda

GreenAI - Discussion Continued - Henry / Thomas

WG Project - Dashboard

Project Review updates

Project Updates

ISO - Sean

Use cases

Article R&A peer review

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Future meeting Agenda submissions

Next Meeting

Adjourn

Meeting Action Items / Standing Agenda / Future Agenda submissions

Henry-WattTime commented 7 months ago

Attended

llhardy1A commented 7 months ago

attended

seanmcilroy29 commented 7 months ago

Attended

filga commented 7 months ago

Attended

tholewis commented 7 months ago

Attended!

marcoshidalgonunes-avanade commented 7 months ago

Attended

GadhuNTTDATA commented 7 months ago

Attended

kapokasa commented 7 months ago

Attended

navveenb commented 7 months ago

attended

seanmcilroy29 commented 7 months ago

Meeting summary

AI project scope and article development. Thomas and Henry discussed the green AI project, including prioritising and scoping the project's goals and timeline. The SC provided feedback and insights on the project, including questions and concerns about tooling and content. Thomas: Cross-working group committee formed to develop new standards, with input from different membership levels and cultures. Thomas suggests bringing in other experts to support the project and ensure everyone is involved and engaged. Sean provided an update on the article for the standards WG, which will be publicized and shared with other WGs.

Benchmarking large language models for efficiency. Chris and Sean ‘O’ discussed collaborating on an AI initiative. They explored the existing solutions in the market and identified the gaps that need to be filled. Chris also talked about the potential use of SCI standards in the energy sector and how they could focus on Iran to implement them. Additionally, Chris proposed using a standardised benchmarking workload to measure the carbon footprint of large language models, which could be a valuable tool for organisations to track their impact on the environment.

Energy consumption and carbon footprint of AI models. Thomas and Gadhu talked about a new AI model that focuses on energy consumption by using large language models. They also discussed the challenges of training and deploying AI models on edge devices. Thomas pointed out the limitations of current language models, such as slow performance and the inability to run on edge devices due to GPU limitations. Chris mentioned the high upfront cost of building and training a language model and the ongoing cost of running it.

AI model development and benchmarking. Gadhu and Chris discussed the standardisation of measuring AI models on reference platforms. Gadhu shared a list of benchmark workloads and tasks for AI research during the meeting, which will be available to the public. Chris and Henry expressed their interest in using this information for their research, and Gadhu agreed to share the link with them.

Project scope and technical feasibility. Thomas highlights the challenge of scoping milestones for the project, focusing on technical feasibility and sustainability.

Developing a framework for green software in organisations. Pindy provided an overview of a project aimed at assisting organisations in using data to make better decisions and achieve net-zero targets. Pindy has also provided detailed information regarding project timelines and milestones for new audiences, which includes delivery managers, change managers, and project managers. In addition, Pindy and Henry have discussed the use of a maturity matrix for organizational change management and have focused on the target audience and messaging approach.

Standardising software efficiency measurement. Sean O proposed labelling software with energy efficiency ratings to help consumers make informed choices. WG aims to create a standard for AI initiatives, with a proposed next step of joining hands on the sheer standard for Iran.

Software carbon footprint measurement. Sean ‘O’ emphasizes the importance of understanding the unit of software function when measuring energy consumption, as different categories have different energy requirements. The group discusses the idea of creating a mock label to inform consumers about software efficiency and reward producers for creating efficient software within their category. Sean ‘O’ discusses the importance of measuring both relative intensity and absolute intensity in software development, and how they plan to prototype different ways to present this information to users. Sean ‘O’ shares their research on the carbon footprint of different programming languages, including Java, Python, and Rust, and how this could impact software development in the future.

Software carbon footprint and labelling. Chris highlights the benefits of customizable labels in software certification, driving better behaviour and efficiency. The discussion revolves around the use of AI in software development, focusing on the importance of understanding the context and requirements of the project. Chris discussed the relativity of time in AI language models and how it impacts their performance.

Software efficiency testing and benchmarking. Sean ‘O’ discusses defining workload and environment for rating tests to ensure constant factors. Navveen adds comments to the spec, highlighting standard components across categories.