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Part of IBM Community - 118 groups

Data, Cloud and AI in Beijing (大数据交流社区－北京)

Beijing, CN

2,245 members · Public group

Organized by IBM Community

What we’re about

欢迎来到IBM赞助的大数据交流社区。我们旨在为大数据开发人员，数据科学家，及所有大数据爱好者，提供一个亲手感受我们的大数据解决方案和工具的机会。

To see all meetups in this group: https://www.meetup.com/pro/ibm-community/

This is an IBM sponsored Meetup group geared towards developers, data scientists, data engineers, and ALL Big Data, Cloud and AI enthusiasts. Our meetups provide an opportunity to work hands on with the solutions and tools in our Big Data portfolio and to interact and share knowledge with experts at IBM and in our extended community.

我们的每次交流聚会通常包含一个最多45至60分钟的针对某一大数据技术的介绍性报告。之后，会有约3小时的交流时间用来和与会的开发人员共同应用大数据技能。

Our Meetups typically include a 45-60 min (max) presentation that serves as an introduction and overview for a specific Big Data technology. It is followed by ~3 hours to collaborate with fellow developers and apply your Big Data skills.

我们会提供一个“免费”的大数据云平台供您用您的手提电脑上的浏览器登录使用。We provide a cloud environment that you can run through the browser of your laptop at NO cost to you.

我们的交流聚会也是“免费”的。Our meetups are FREE.

聚会议题包括，但不局限于：Meetup topics include, but not limited to:

- 基于Hadoop的数据分析 Hadoop-based analytics

- 流计算 Stream Computing

- 文本分析 Text Analytics

- 大数据可视化及探索工具 Visualization and Discovery tools for Big Data

- 大数据应用开发 Big Data App Development

- 大数据分析流程中的关键技术深探 Deep dives into the technologies that makes big data processing possible

- 大数据业界方案选例 Big Data industry solution case studies

- 任何与大数据相关的议题 Anything and everything about Big Data

敬请参与并亲身体验大数据开发和应用的乐趣！

Join us today and enjoy a hands-on software development and application experience.

Upcoming events (3)

See all

Network event
93 attendees from 109 groups hosting
Thu, May 15, 2025, 2:00 PM UTC[AI Alliance Materials] Discrete State-Space Diffusion and Flow Models
Link visible for attendees
External registration
https://44725920.hs-sites.com/ai-alliance-material-chemistry-webinar-5-15

Unlocking Guidance for Discrete State-Space Diffusion and Flow Models
Many scientific tasks, such as protein engineering and small-molecule drug discovery, can be formulated as conditional generation problems over discrete spaces. This talk introduces a new approach that enables tractable classifier and classifier-free guidance on discrete state-space diffusion and flow models. I will demonstrate how this method can be applied for conditional generation tasks in protein sequence, small-molecule graph, and DNA sequence design.

Speaker
Hunter Nisanoff recently graduated from his PhD in Computational Biology from UC Berkeley where he was advised by Professor Jennifer Listgarten. His research focuses on machine learning methods for protein engineering. Prior to his PhD, Hunter worked at D. E. Shaw Research developing machine learning and simulation-based methods for small-molecule drug discovery.

Research publication
https://arxiv.org/abs/2406.01572

About the AI Alliance

The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.
1 attendee from this group
Network event
142 attendees from 111 groups hosting
Thu, May 15, 2025, 4:00 PM UTC[AI Alliance] Model and Agent Evaluation with Unitxt
Link visible for attendees
Description
Evaluating the performance of language models and AI agents can be challenging, especially across diverse tasks and domains. In this session, we'll introduce Unitxt, an open-source framework for unified text evaluation, and explore how it simplifies the process of benchmarking LLMs and agents using a standardized format.

We'll walk through the core ideas behind LLM evaluation—what to measure, how to measure it, and why it matters—and then dive into hands-on examples of evaluating LLMs for quality, reliability, safety and more, as well as evaluating multi-modalities and agentic tool invocation.
Whether you're just getting started with evaluation or looking for a powerful and flexible tool to streamline your workflows, this session will offer practical insights and code-based demos to help you get up and running.

Bring your questions, ideas, or examples—we’ll have time for discussion and Q&A at the end!

Speaker Bio
Elron Bandel (LinkedIn) works to redefine how language models are tested and used at scale. At IBM Research, he leads projects that enhance researchers' abilities to test and utilize language models at transformative scales. Elron co-authored IBM's standard evaluation platform for large language models and spearheads the development of Unitxt, an open-source Python library for AI performance assessment. His academic record supervised by Prof. Yoav Goldberg included work on developing AlephBERT and its innovative evaluation suite, and research into robust language model testing.

About the AI Alliance

The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.
Network event
237 attendees from 111 groups hosting
Thu, May 22, 2025, 4:00 PM UTC[AI Alliance] Knowledge Graphs for Enterprise AI
Link visible for attendees
Description
Proscenium is an emerging library of composable glue focused on enterprise AI applications. It prioritizes support for domains where the creation and use of structured data is critical. This talk will walk through the construction an application for the legal domain built with Proscenium that involves:

Document enrichment

Entity resolution

Knowledge Graph construction

Query handling

Chat integration

Finally, we'll cover the future roadmap and ways that you could contribute!

Speaker Bio
Adam Pingel (LinkedIn, GitHub) is IBM's Head of Open Tools and Applications for the AI Alliance. Adam has been fascinated by AI and chatbots since playing with Racter in the 80’s. But the “winters” were long and frequent. The stars aligned in 2015 when he became VPE at Ravel Law. Ravel was building AI-powered tools for the legal industry and was working with Harvard Law School on what is now known as the Caselaw Access Project. After an acquisition by LexisNexis in 2017, he moved his family to Raleigh (in 2019) to take the role of CTO of Global Platforms. In 2022 he joined IBM to work on domain-specific applications of generative AI. Adam holds an MS and BS in CS from UCLA and Stanford, respectively. When not at a keyboard, he enjoys spending time with his family.

About the AI Alliance

The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.