What we’re about
This is an IBM sponsored Meetup group geared towards developers, data scientists, data engineers, and ALL Big Data, Cloud and AI enthusiasts. Our events 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.
Developers interested in joining IBM to learn about big data for social media and log analytics. Get jump started with Hadoop scripting and text analytics and address the full spectrum of Big Data business challenges.
Upcoming events (4+)
See all- Network event144 attendees from 110 groups hosting[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materialsLink visible for attendees
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. - Network event296 attendees from 111 groups hosting[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at ScaleLink visible for attendees
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 event7 attendees from 111 groups hosting[AI Alliance Materials] Discrete State-Space Diffusion and Flow ModelsLink visible for attendees
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 event1 attendee from 111 groups hosting[AI Alliance] Model and Agent Evaluation with UnitxtLink 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.
![[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materials cover photo](https://secure.meetupstatic.com/photos/event/4/3/9/f/event_527777311.webp "[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materials")
![[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at Scale cover photo](https://secure.meetupstatic.com/photos/event/1/6/2/a/event_527645674.webp "[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at Scale")
![[AI Alliance Materials] Discrete State-Space Diffusion and Flow Models cover photo](https://secure.meetupstatic.com/photos/event/5/e/4/8/event_527784136.webp "[AI Alliance Materials] Discrete State-Space Diffusion and Flow Models")
![[AI Alliance] Model and Agent Evaluation with Unitxt cover photo](https://secure.meetupstatic.com/photos/event/e/5/3/6/event_527818678.webp "[AI Alliance] Model and Agent Evaluation with Unitxt")
Past events (2)
See all- Network event244 attendees from 109 groups hosting[AI Alliance] Chat with your website using an LLMThis event has passed