Day 1 & Day 2 Time Table (Sep. 12 & 13)

NOTE: For presenters, please either have Lark installed on your laptop to share your screen during your presentation OR send us your slides to use the shared laptop during the event.

You need to login with your LFID to edit the confluence page. If you don't have one, you can create one here:

Individual Dashboard | The Linux Foundation

Day1 (Sep. 12)

Lark Meeting: Join a Lark video meeting

YouTube Live: AI for Developers Meeting Invited Talks, Day1

Summary

The meeting discussed AI and edge computing, the main contents included:

• AI applications: in various fields like Auto SE Kim, WASM runtime, and China Mobile's strategic planning.

• Challenges and opportunities: in model coupling, edge computing, and industry collaboration.

• Demonstrations: showcasing the capabilities of these technologies.

• Open source projects and tools: such as ByteDance's Babid Multimedia Framework and BMF libraries integrated with Hugging Face Library.

• AI networking innovations: and the role of telcos in hosting AI services.

• Upcoming event: "futures in Taipei".

Chapters

00:00 Advances and Applications of AI in Edge Computing and Distributed Cloud

This section features presentations on AI agent building and capabilities. Gary from codes discusses its various uses and how to build one. Tina Tsou elaborates on bridging the gap between edge AI and distributed cloud computing, covering challenges, tools, security, and future prospects. There's also mention of related workstreams, projects, and opportunities for collaboration.

38:21 Edge and Cloud Collaborative Support and Security for Large Language Models

This section focuses on the deployment and optimization of edge and cloud inferences for large language models. It covers various deployment models, model conversion and optimization, reduction of model size for edge devices, scheduling for fast execution, and a framework for attestation and evidence support. Different techniques and challenges are discussed along with solutions.

01:20:19 The Future of Network and Computing Infrastructure: Insights and Initiatives by Harohisa Fukano from Fujitsu

This section is about Harohisa Fukano from Fujitsu presenting on the future of network and computing infrastructure for the 2030s. He covers LFH projects, computing challenges like power consumption and flexibility, the bottleneck disaggregated computer, joint efforts with the Ion Global Forum, and potential use cases including generative AI plus robotics and green energy data processing, along with upcoming POC phases.

01:50:24 Edge Computing, IoT, and Function Calling in AI Projects Presentation and Demos

This section presents edge computing, IoT, and function calling. Tom introduces Shifu for IoT, detailing its architecture, use cases like with the California Strawberry Commission and a supermarket chain. CC discusses Geo distributed computing, function calling, and related improvements. Demos of Shifu integration and function calling are shown. Questions and discussions follow.

02:30:31 Discussions on Various Topics including Technology, Business, and Education

This section is a complex and lengthy discussion covering various topics including lunch and networking plans, business models, technology applications like TikTok, issues related to code and software development, legal aspects in certain fields, and experiences with different systems and services. The conversation also touches on teams, support, and various challenges and opportunities.

03:32:20 Overview of Auto SE and Comparisons in AI Application Workflow

This section mainly focuses on various discussions related to Auto SE and its features. Li Chuan presents on Auto SE, including its capabilities, comparison with Github Pilot, key highlights like link and live features, switch setup actions, direct support, standing in SMB benchmark leaderboard, and cost savings compared to SMB agent. Also, there are mentions of future discussions and ongoing targeting.

04:14:53 The Need for Tightly Coupled Language Models and Web Assembly in Applications

This section is mainly presented by Michael Yu Yan. He discusses the need for tightly coupling large language models with specific knowledge bases and applications. He gives examples like the chemistry and Rust programming demos, highlighting issues with Python and cross-platform compatibility. He also mentions web assembly as a solution and showcases a cross-GPU demo. Everything presented is open source.

04:56:05 Discussions on AI Applications and Open Source Projects in Various Contexts

This section includes various discussions on AI-related topics. It covers China Mobile's strategic planning in the AI era, such as AI in operation services, creativity, new quality productivity, and strategic decision making. It also features ByteDance's open source projects and their potential in addressing AI challenges. Sujata Tibrewala from ByteDance discussed AI's impact on jobs and the environment.

06:38:08 Advancement and Comparison of AI Networking Technologies and Protocols

This section discusses advancements in AI networking, focusing on scale up and scale out networking. It explores protocols like TCPIP and RDMA, links such as NV Link and CXL, and the need for efficient data transfer in GPU clusters. The presenter also compares different technologies, emphasizing low latency and high performance, and considers future positions regarding networking architectures and protocols.

07:12:51 Overview and Use Cases of Ion Global Forum and Upcoming Event

This section involves Rintaro Harada from NTT presenting about the Ion Global Forum. He introduces its overview, including the aim to create a sustainable society, its founding by NTT, Intel, and Sony. Discusses goals, technical aspects, POC activities, use cases like Smart City, and potential applications in various industries. Also announces an upcoming event in Taipei next month.

Day2 (Sep. 13)

Lark Meeting: https://www.us.larkoffice.com/calendar/share?token=e8edd94e9827b518b68b279ca5120824

Youtube Live: AI for Developers Meeting Invited Talks, Day2

Summary

The meeting discussed the development and application of artificial intelligence, as well as related technologies and challenges, the main contents included:

• Edge Lake: A software enabling AI at the edge, with features and potential applications.

• Graftino: A unified metadata layer to handle data silos in the AG era.

• Language models: Used in identifying drivers of political polarization and reducing it through deliberative polling.

• Interoperable chatbot: Its features, ability to participate in teams, and handling of security concerns.

• AI in data analysis, speech recognition, and intelligent assistants: Research results and experiences shared.

• Challenges and solutions in AI development: Such as data privacy, model performance, and energy consumption.

• Open source projects and initiatives: To promote the development and application of AI.

Chapters

00:00 Meeting Kickoff

Meeting Kickoff

03:45 Edge Lake: Enabling AI at the Edge and Addressing Challenges

This section is a meeting transcript mainly discussing issues related to Lark, including someone's inability to join, the use of AI transcription feature, and account purchase. It also covers an overview and demonstration of Edge Lake, a platform for managing data at the edge, along with questions on data protection and handling single point of failure.

33:31 Edge Lake: Enabling AI and Federated Learning with Virtualization and Security

This section discusses Edge Lake, its use of blockchain for virtualization and metadata sharing, enabling synchronized operation of nodes. It covers Edge Lake's role in AI, including data collection, model generation, and distribution, comparing traditional and federated learning. Security and challenges of federated learning are also addressed. The presentation is a work in progress, welcoming input and contributions.

55:39 Discussions on Various Technical and Operational Issues in TikTok and Related Fields

This section contains a somewhat chaotic and diverse discussion. It covers topics such as breaks, TikTok, data and security issues related to AI products, login problems, various musical mentions, and scattered remarks about different technologies and experiences. The conversation is fragmented and lacks a clear central theme.

01:14:06 Introducing Graptino: A Unified Metadata Lake for Data Management

This section focuses on the introduction of Graptino, a unified metadata lake project. It discusses the evolution of data management architectures and the challenges they pose. Graptino aims to unify metadata to solve data silo problems, support various data types and scenarios, and is presented with its architecture, features, usage scenarios, and community aspects. Different from similar projects, Graptino is an open source solution with a focus on real-time operation and a distinct scope.

01:57:02 Research on Reducing Political Polarization with AI and Deliberative Polling

This section mainly focuses on Josh Joseph's presentation on using AI tools to address political polarization. He explains the concept of deliberative polling and its challenges, presents a new model with Bert and GPT-4 components, shows its training and results, and discusses applications and future work. It also covers issues like data analysis, synthetic noise addition, and potential expansions to other domains.

02:31:40 Discussions and Thoughts on Various Topics

This section is a rather chaotic and diverse discussion involving lunch preparations, presentations, various topics such as TikTok, personal experiences, and random thoughts. Participants like Wilson Wang and others contribute sporadically with no clear central theme or concrete decisions reached.

03:11:06 Discussions on AI-related Projects and Technologies

This section contains discussions from multiple speakers on various AI-related topics. It includes talks about Grog's focus on inference part in AI, Jose's presentation on its capabilities, and alivedaru's introduction to the Open Platform for Enterprise AI project with its components, challenges, and ways to get involved like hackathons. There were also questions and exchanges on related aspects.

03:56:20 Challenges and Solutions in Real-Time Speech Recognition for Robotics and First Responders

This section is mainly about Signal Logic's participation in various projects related to speech recognition for robotics and edge computing. It discusses challenges such as sound alike errors, background noise, and the need for real-time processing without relying on the cloud. The company is working on post-processing and using reduced language models to improve accuracy, and they are exploring different hardware and algorithms to meet functional requirements.

04:33:33 Updates on ETA and Conversational Technologies in Data and AI

This section features presentations from Wilson Wang and Zebra Doll. Wilson Wang represents the ETA team, discussing their project addressing data-related challenges and the use of LM agents. Zebra Doll presents on the Open Voice Interoperability Initiative, aiming to enable seamless interaction among conversational AI systems and outlining their progress and future work. There were also technical issues and limited questions.

05:19:06 Various Topics and Experiences Shared

This section contains various remarks from different speakers. It mentions the happy hour at 4:30 and driving directions. There are also discussions about events, TikTok connections, work experiences, and the growth of a company from 29 to over 25 people. Speakers share diverse and somewhat disjointed information.