- Network event138 attendees from 111 groups hostingAI Alliance Online Office Hours: “How the RAISE Act Affects You”Link visible for attendees
Learn how New York’s RAISE Act would impact open-source AI innovation, and how you can get involved. Hear from industry experts, participate in Q&A, and share your own experiences with AI development. You can learn more about the RAISE Act in this message from the AI Alliance Association.
Register now to reserve your spot!Every Thursday at 12 PM ET, we spotlight emerging tools, frameworks, and best practices that are shaping open-source AI ecosystems. Whether you're contributing code, deploying models, or just exploring, you’ll find practical insights and community connection.
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.Join the community
Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord. - Network event306 attendees from 111 groups hosting[AI Alliance] Open Trusted Data Initiative (OTDI)Link visible for attendees
![[AI Alliance] Open Trusted Data Initiative (OTDI) cover photo](https://secure.meetupstatic.com/photos/event/a/f/7/f/event_528224927.webp "[AI Alliance] Open Trusted Data Initiative (OTDI)")
The AI Alliance brings together over 170 organizations to promote open source AI technologies across the globe.
Please join us learn about the Open Trusted Data Initiative (OTDI), which seeks to address a common challenge for organizations that need datasets for AI pre-training, tuning, RAG, and other purposes. While lots of useful datasets are available, it is not always clear which ones are licensed for free and unlimited use, with clear provenance for their history, and suitable governance to be sure the claimed licenses and provenance are in fact valid for the whole dataset. Don't miss this important AI Alliance update and learn how you can get involved!
About the presenter
Joe Olson, IBM - Network event292 attendees from 111 groups hosting[AI Alliance] ITBench - New Open-Source Benchmark Suite for AI AgentsLink visible for attendees
![[AI Alliance] ITBench - New Open-Source Benchmark Suite for AI Agents cover photo](https://secure.meetupstatic.com/photos/event/f/7/5/event_528483957.webp "[AI Alliance] ITBench - New Open-Source Benchmark Suite for AI Agents")
ITBench is a new open-source benchmark suite designed to evaluate AI agents in real-world IT environments across 3 key areas:
- Site Reliability Engineering (#SRE)
- Financial Operations (#FinOps)
- Compliance & Security Operations (#CISO)
The ITBench SaaS offering covers the entire workflow – from environment deployment, scenario setup, and agent evaluations, making it easy to test and compare your AI solutions.
See the public leaderboards on GitHub here: https://github.com/IBM/ITBench-Leaderboard
Hear IBM Distinguished Engineer and Master Inventor, Ruchi Mahindru, explain how IT Bench can help businesses mitigate risk across large-scale systems.
Join the community
- Subscribe to the AI Alliance community newsletter (see sign-up form at the bottom of the homepage)
- Join the AI Alliance Discord: https://discord.gg/ntG3yqSr
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 event166 attendees from 108 groups hosting[AI Alliance] Trust and Safety Evaluations Initiative (TSEI)Link visible for attendees
![[AI Alliance] Trust and Safety Evaluations Initiative (TSEI) cover photo](https://secure.meetupstatic.com/photos/event/a/c/b/0/event_528224208.webp "[AI Alliance] Trust and Safety Evaluations Initiative (TSEI)")
Please join us to learn about the Trust and Safety Evaluations Initiative (TSEI), which is focused on evaluating AI models and applications. Evaluations cover not only safety concerns, like avoiding hate speech, but the emerging challenge of evaluating that the system as a whole is “aligned” with the requirements for the domain and use cases supported. We call this the “last mile” of evaluation, a challenge that most development teams don’t know how to address. You will learn about our efforts to meet all these needs and how you can get involved!
About the presenter
Dean Wampler, IBM - Network event318 attendees from 111 groups hosting[AI Alliance] Introducing RAGme-aiLink visible for attendees
![[AI Alliance] Introducing RAGme-ai cover photo](https://secure.meetupstatic.com/photos/event/a/e/8/1/event_528224673.webp "[AI Alliance] Introducing RAGme-ai")
RAGme-ai is a personalized RAG agent for the web sites you visit and care about.
Use cases include:
- Interractive personal RAG adding web sites and documents and using an LLM agent to query
- Collecting web sites or documents on a particular topic and RAGing and searching them
- Collecting posts from a blog and RAGing and searching them
- Collecting visited sites from a user's daily activities and RAGing and searching them
- Collecting documents from a user and RAGing and searching them
RAGing and searching refers to adding documents into a Vector database using some appropriate embedding (process to RAG) and then using an LLM agent to query and use that database as source of knowledge.
About the presenter
Max. Hacker.
IBM Research.
LinkedIn, GitHub - Network event427 attendees from 110 groups hosting[AI Alliance] Knowledge Graphs for Enterprise AILink visible for attendees
![[AI Alliance] Knowledge Graphs for Enterprise AI cover photo](https://secure.meetupstatic.com/photos/event/c/c/7/e/event_527692350.webp "[AI Alliance] Knowledge Graphs for Enterprise AI")
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.
- Network event215 attendees from 111 groups hosting[AI Alliance] Model and Agent Evaluation with UnitxtLink visible for attendees
![[AI Alliance] Model and Agent Evaluation with Unitxt cover photo](https://secure.meetupstatic.com/photos/event/e/5/7/a/event_527818746.webp "[AI Alliance] Model and Agent Evaluation with Unitxt")
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 event142 attendees from 107 groups hosting[AI Alliance Materials] Discrete State-Space Diffusion and Flow ModelsLink visible for attendees
![[AI Alliance Materials] Discrete State-Space Diffusion and Flow Models cover photo](https://secure.meetupstatic.com/photos/event/5/e/6/5/event_527784165.webp "[AI Alliance Materials] Discrete State-Space Diffusion and Flow Models")
External registration
https://44725920.hs-sites.com/ai-alliance-material-chemistry-webinar-5-15Unlocking 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/2406.01572About 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 event322 attendees from 110 groups hosting[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at ScaleLink visible for attendees
![[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at Scale cover photo](https://secure.meetupstatic.com/photos/event/1/6/9/1/event_527645777.webp "[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at Scale")
Details
IBM recently released GneissWeb, a large dataset yielding around 10 trillion tokens that caters to the data quality and quantity requirements of training Large Language Models. In this talk i will do a deep dive on the philosophy behind this dataset, where it stands w.r.t the other datasets out there, how to recreate it based on the tools IBM has open sourced and some performance figures with it. This talk will be a followup of the talk given by Shahrokh Daijavad of IBM in the month of March.Prerequisites
This is a follow up to our March 6, 2025 session “Introducing GneissWeb - a state-of-the-art LLM pre-training dataset“:- Check the GitHub show notes
- Re-watch on YouTube
About the presenter
Bishwaranjan Bhattacharjee (LinkedIn), Senior Technical Staff Member and Master Inventor, IBM ResearchAbout 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 event156 attendees from 109 groups hosting[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materialsLink visible for attendees
![[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materials cover photo](https://secure.meetupstatic.com/photos/event/4/3/c/1/event_527777345.webp "[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materials")
External registration
https://44725920.hs-sites.com/ai-alliance-material-chemistry-webinar-51-0———
MatExpert: Decomposing Materials Discovery by Mimicking Human Experts
For accelerated inorganic materials design, a framework capable of AI-driven exploration of the vast materials spaces across the periodic table is required. In this talk, I will introduce MatAgent, a generative AI agent for inorganic materials design mimicking the reasoning process of human experts. It combines tool-assisted LLM-driven reasoning for material composition proposals with a generative model for crystal structure estimation and a predictive model for material property prediction, enabling feedback-driven targeted materials generation in an interpretable manner.Speaker
Qianggang Ding, currently completing my Ph.D. in Computer Science at the University of Montreal and Mila, with a focus on topics of AI for Science.Research publication
https://arxiv.org/abs/2410.21317About 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.
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- Network event138 attendees from 111 groups hostingAI Alliance Online Office Hours: “How the RAISE Act Affects You”Link visible for attendees
- Network event306 attendees from 111 groups hosting[AI Alliance] Open Trusted Data Initiative (OTDI)Link visible for attendees
- Network event292 attendees from 111 groups hosting[AI Alliance] ITBench - New Open-Source Benchmark Suite for AI AgentsLink visible for attendees
- Network event166 attendees from 108 groups hosting[AI Alliance] Trust and Safety Evaluations Initiative (TSEI)Link visible for attendees
- Network event318 attendees from 111 groups hosting[AI Alliance] Introducing RAGme-aiLink visible for attendees
- Network event427 attendees from 110 groups hosting[AI Alliance] Knowledge Graphs for Enterprise AILink visible for attendees
- Network event215 attendees from 111 groups hosting[AI Alliance] Model and Agent Evaluation with UnitxtLink visible for attendees
- Network event142 attendees from 107 groups hosting[AI Alliance Materials] Discrete State-Space Diffusion and Flow ModelsLink visible for attendees
- Network event322 attendees from 110 groups hosting[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at ScaleLink visible for attendees
- Network event156 attendees from 109 groups hosting[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materialsLink visible for attendees