Wat we doen
Welcome to the IBM Developer Netherlands meetup group.
We're running a series of hands-on workshops (BYOD*) on a variety of technologies:
- Internet of Things
- Artificial Intelligence and Machine Learning
- Data Science
- Blockchain
- Cloud Native Development and Containers
Each of these tracks will be split in to several workshops diving deeper in to the subject each time.
What you can expect during our Meetups: Hands-on, talks, networking, food and drinks!
Have a question for our developer advocates? Visit their profiles and areas of expertise here.
Get instant access to numerous code patterns.
We hope to see you at our events!
IBM Developer Advocacy team
* Bring Your Own Device
Aankomende evenementen (4+)
Alles weergeven- Netwerkevenement139 deelnemers van 110 groepen die hosten[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materialsKoppeling zichtbaar voor deelnemers
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. - Netwerkevenement294 deelnemers van 111 groepen die hosten[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at ScaleKoppeling zichtbaar voor deelnemers
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. - Netwerkevenement7 deelnemers van 111 groepen die hosten[AI Alliance Materials] Discrete State-Space Diffusion and Flow ModelsKoppeling zichtbaar voor deelnemers
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.
- Netwerkevenement1 deelnemer van 111 groepen die hosten[AI Alliance] Model and Agent Evaluation with UnitxtKoppeling zichtbaar voor deelnemers
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 omslagfoto](https://secure.meetupstatic.com/photos/event/4/3/f/0/event_527777392.webp "[AI Alliance Materials] MatExpert, a generative AI agent for inorganic materials")
![[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at Scale omslagfoto](https://secure.meetupstatic.com/photos/event/1/6/8/3/event_527645763.webp "[AI Alliance] GneissWeb: Preparing High Quality Data for LLMs at Scale")
![[AI Alliance Materials] Discrete State-Space Diffusion and Flow Models omslagfoto](https://secure.meetupstatic.com/photos/event/5/e/8/5/event_527784197.webp "[AI Alliance Materials] Discrete State-Space Diffusion and Flow Models")
![[AI Alliance] Model and Agent Evaluation with Unitxt omslagfoto](https://secure.meetupstatic.com/photos/event/e/5/4/e/event_527818702.webp "[AI Alliance] Model and Agent Evaluation with Unitxt")
Afgelopen evenementen (104)
Alles weergeven- Netwerkevenement244 deelnemers van 109 groepen die hosten[AI Alliance] Chat with your website using an LLMDit evenement is verstreken
