talk-data.com talk-data.com

Filter by Source

Select conferences and events

People (237 results)

See all 237 →

Companies (23 results)

See all 23 →
IBM 40 speakers
AI Ethics Market Strategy Lead Architect Associate Partner
IBM APAC 1 speaker
IBM Haifa 1 speaker
Cloud Research Engineer

Activities & events

Title & Speakers Event

Do you work with tabular data? Learn how to clean, prepare, and organise datasets properly in Python.

Data Cleaning with Python Pandas

Working with real data means dealing with missing values, errors, duplicates, and inconsistent formats. Before any analysis or machine learning, data must be cleaned and prepared properly. Data cleaning is one of the most important and time-consuming tasks in data work. This session gives a clear and practical introduction to data cleaning using Python and Pandas. It focuses on common real-world problems and shows simple, correct ways to fix them.

Who is this for?

Students, developers, and anyone who works with data and needs to clean and prepare datasets using Python. This session is useful if you work with messy files such as CSV or Excel, want to understand how Pandas handles missing or incorrect data, and want to build reliable data analysis pipelines.

Who is leading the session?

The session is led by Dr. Stelios Sotiriadis, CEO of Warestack and Associate Professor and MSc Programme Director at Birkbeck, University of London.

He works in data processing, distributed systems, cloud computing, and Python-based analytics. He holds a PhD from the University of Derby, completed a postdoctoral fellowship at the University of Toronto, and has worked with Huawei, IBM, Autodesk, and several startups. Since 2018, he has been teaching at Birkbeck and founded Warestack in 2021.

What we will cover

This is a hands-on introduction with real examples and short exercises. Topics include loading data with Pandas, inspecting datasets, handling missing values, fixing data types, removing duplicates, cleaning text data, filtering and transforming columns, combining datasets, and common data cleaning mistakes to avoid.

Requirements

A laptop with Python installed (Windows, macOS, or Linux), Visual Studio Code, and Python pip. Lab computers can be used if needed.

Format

A 1.5-hour live session with short explanations, live coding, and guided exercises. The session runs in person, with streaming available for remote participants.

Prerequisites

Basic to intermediate Python knowledge, including functions, loops, and basic data structures. Some familiarity with Pandas is helpful but not required.

Data Cleaning with Python Pandas

Parallel Processing with Python

Modern software often needs to do many things at the same time to run faster and scale better. This includes data processing, web services, and machine learning workloads. Understanding parallel and concurrent execution is now an important skill for Python developers. This session gives a clear and practical introduction to parallel processing in Python. It focuses on the main ideas and shows when and how to use different approaches correctly.

Who is this for?

Students, developers, and anyone who wants to understand how Python programs can run faster by doing work in parallel. This session is useful if you want to speed up Python programs, understand the difference between threads and processes, and build more efficient and scalable applications.

Who is leading the session?

The session is led by Dr. Stelios Sotiriadis, CEO of Warestack and Associate Professor and MSc Programme Director at Birkbeck, University of London.

He works in distributed systems, cloud computing, operating systems, and Python-based data processing. He holds a PhD from the University of Derby, completed a postdoctoral fellowship at the University of Toronto, and has worked with Huawei, IBM, Autodesk, and several startups. Since 2018, he has been teaching at Birkbeck and founded Warestack in 2021. What we will cover

Requirements

A laptop with Python installed (Windows, macOS, or Linux), Visual Studio Code, and Python pip. Lab computers can be used if needed.

Format

This is a hands-on introduction with examples and short exercises. Topics include what concurrency and parallelism mean, threads vs processes in Python, the Global Interpreter Lock explained simply, using threading for I/O-heavy tasks, using multiprocessing for CPU-heavy tasks, basic use of concurrent.futures, common problems like race conditions, and when parallelism is not the right choice.

A 1.5-hour live session with short theory explanations, live coding, and guided exercises. The session runs in person, with streaming available for remote participants.

Prerequisites

Basic to intermediate Python knowledge, including functions, loops, and basic data structures.

Parallel Processing with Python

--------------------------------------------------------------------------------- If you are already registered in Luma: https://luma.com/u2x2ysie please do not register again. --------------------------------------------------------------------------------- This event runs in a hybrid format: face to face and online. ---------------------------------------------------------------------------------

Who is this for?

​Relational databases and SQL remain the foundation of nearly all modern software systems, from web apps and SaaS platforms to analytics pipelines.

​Students, developers, and anyone interested in getting started with the theory and practice of relational databases, SQL, Supabase, and Python.

​Who is leading the session?

​The session is led by Dr. Stelios Sotiriadis, CEO of Warestack, Associate Professor and MSc Programme Director at Birkbeck, University of London. His expertise includes cloud computing, distributed systems, data engineering, and AI engineering.

Stelios holds a PhD from the University of Derby, completed a postdoctoral fellowship at the University of Toronto, and has worked with Huawei, IBM, Autodesk, and several startups. Since 2018 he has taught at Birkbeck and, in 2021, founded Warestack, building software for startups globally.

​What we’ll cover

​A practical introduction to the core concepts of relational databases, including how to build and manage databases using SQL and modern tools like Supabase and Python. ​You will learn:

  • ​What relational databases are and why they matter
  • ​SQL fundamentals
  • ​Joins, constraints, keys, indexing, and schemas
  • ​Hands-on database design and normalisation
  • ​Using Supabase as a modern PostgreSQL backend
  • ​Querying databases with Python
  • ​Building a simple CRUD application

Requirements

  • ​A laptop with Python (Windows, macOS, or Linux)
  • ​Visual Studio Code installed
  • ​Python pip installed
  • ​A free Supabase account
  • ​Basic internet access

​If you don’t have a suitable laptop, you may use the lab computers. ​ Why Supabase and Python?

​Supabase has become one of the most popular modern PostgreSQL platforms, widely adopted by startups and developers for its speed and simplicity. Python is one of the most used programming languages in the world, especially for data and backend development. Together, they form a highly popular and practical stack for building real applications.

Format

​A 2-hour live session including:

  • ​Interactive theory
  • ​Hands-on SQL practice
  • ​Step-by-step coding exercises

Prerequisites

​You should be comfortable writing simple Python scripts (basic to intermediate level). No prior SQL experience is required.

Modern SQL Essentials with Supabase and Python

THIS IS A PAID EVENT PLEASE COMPLETE REGISTRATION HERE: https://luma.com/b9wy77ys

Who is this for?

This workshop is designed for complete beginners and anyone who wants to learn Python from the ground up. Whether you're new to programming, switching careers, or building your confidence before moving into data, AI, or software development, this series will guide you step by step. By the end of the programme, you’ll understand the fundamentals of Python and how real code works inside modern applications.

Who is leading the session?

The session is led by Dr. Stelios Sotiriadis, CEO of Warestack and Associate Professor & MSc Programme Director at Birkbeck, University of London. Stelios teaches cloud computing, distributed systems, data engineering, and AI engineering, and has extensive experience working with Huawei, IBM, Autodesk, and multiple startups.

He holds a PhD from the University of Derby, completed a postdoctoral fellowship at the University of Toronto, and has been teaching at Birkbeck since 2018. In 2021 he founded Warestack, building developer tools and automation software for startups around the world.

About the Series

Python for Beginners: From Zero to Hero is a live coding workshop split into 5 sessions (10 hours total). You will write code with me in real time, learning Python through hands-on exercises rather than slides. This is a limited-space, interactive workshop, ideal if you prefer learning by doing.

What we’ll cover (Part 1)

A practical workshop to Python, including:

  • What programming is and how Python works
  • Writing your first scripts step by step
  • Variables, input/output, data types, and operators
  • Logic and decision making (if/else)
  • Loops (for/while) and how to control program flow
  • Best practices for beginners
  • Small hands-on challenges to build confidence

Each exercise builds directly on the previous one, so by the end you’ll already feel comfortable writing real code.

Requirements

You just need:

  • A laptop (Windows, macOS, or Linux)
  • A Gmail account to access Google's Colab (if you don't have one please create)

Why Python?

Python is one of the most widely used programming languages in the world. It's the foundation of:

  • AI and machine learning
  • Data science
  • Web development
  • Automation
  • Scripting and DevOps
  • Modern backend systems

This workshop gives you the skills to move confidently toward all of these areas.

Format

A 2-hour live session including:

  • Interactive explanations
  • Live coding demonstrations
  • Step-by-step guidance
  • Hands-on exercises you complete during the session
  • Time for questions and practical help
  • Homework and exercises

This is a beginner-friendly, supportive learning environment.

Cost

The first session costs only £20, so you can get a flavour of the material and the teaching style. Each session after that is £40, making the total cost for all 5 sessions £180.

By the end of the 5 sessions, you will be able to confidently write Python code and build your own programs from scratch. You’ll understand how to work with data, automate tasks, and apply Python to real-world problems — giving you a strong foundation for further study in AI, data science, and software development.

Prerequisites

No prior programming experience or Python installation required. I’ll guide you through everything from scratch.

Introduction to programming with Python (Part 1)

Overview

​Students, developers, and anyone interested in getting started with theory and practice on building LLM-based applications with Python.

Who is this for?

​Undeniably, large language models (LLMs) are at the centre of a modern gold-rush in technology.

Students, developers, and anyone interested in getting started with theory and practice on building LLM-based applications with Python.

​Who is leading the session?

​The session is led by Dr. Stelios Sotiriadis, CEO of Warestack, Associate Professor and MSc Programme Director at Birkbeck, University of London. His expertise includes cloud computing, distributed systems, and AI engineering.

Stelios holds a PhD from the University of Derby, completed a postdoctoral fellowship at the University of Toronto, and has worked with Huawei, IBM, Autodesk, and several startups. Since 2018 he has taught at Birkbeck and, in 2021, founded Warestack, building software for startups globally.

​What we’ll cover

​A practical introduction on the basics of local models and cloud APIs to build real software systems. ​You will learn:

  • ​Introduction to natural language processing
  • ​LLMs theory and intuition
  • ​Agents are and how to build them
  • ​Running local models with Ollama (free and offline)
  • ​Calling local models using Python
  • ​Building a ChatGPT-like chatbot with Python libraries

Requirements

  • ​A laptop with Python (Windows, macOS, or Linux)
  • Visual Studio Code installed
  • ​Python pip installed
  • ​At least 10 GB free disk space
  • ​At least 8 GB RAM

​This space is needed for running local models.

You may also use the lab computers if your device doesn’t meet the requirements.

Format

​A 1.5-hours live session including:

  • ​Interactive theory
  • ​Hands-on coding
  • ​Step-by-step exercises

The session will run in person, with streaming available for remote attendees.

Prerequisites ​You should be comfortable writing Python scripts (basic to intermediate level).

Building LLM applications with Python

REGISTER BELOW FOR MORE AVAILABLE DATES! ↓↓↓↓↓ https://luma.com/stelios

-----------------------------------------------------------------------------------

Who is this for?

​Students, developers, and anyone interested in using Large Language Models (LLMs) to build real software solutions with ** Python.

Tired of vibe coding with AI tools? Want to actually understand and own your code, instead of relying on black-box magic? This session shows you how to build LLM systems properly, with full control and clear engineering principles. Who is leading the session?

​The session is led by Dr. Stelios Sotiriadis, CEO of Warestack, Associate Professor and MSc Programme Director at Birkbeck, University of London, specialising in cloud computing, distributed systems, and AI engineering.

Stelios holds a PhD from the University of Derby, completed a postdoctoral fellowship at the University of Toronto, and has worked on industry and research projects with Huawei, IBM, Autodesk, and multiple startups. Since moving to London in 2018, he has been teaching at Birkbeck. In 2021, he founded Warestack, building software for startups around the world. What we’ll cover?

​A hands-on introduction to building software with LLMs using Python, Ollama, and LiteLLM, including:

  • ​How LLMs, embeddings, and agents work.
  • ​Calling local models with Ollama or cloud models (OpenAI, Gemini and more).
  • ​Using LiteLLM for custom prompts and tool-calling.
  • ​Building simple agents from scratch.
  • ​Introduction to RAG (Retrieval-Augmented Generation).
  • ​Working with vector databases (ChromaDB) and vector similarity search library (FAISS).
  • ​Storing, searching, and retrieving embeddings.
  • ​Introduction to Streamlit for interactive data apps.
  • ​End-to-end examples you can run on your own machine.

​This session focuses on theory, fundamentals and real code you can re-use.

​Why LiteLLM?

LiteLLM gives you low-level control to build custom LLM solutions your own way, without a heavy framework like LangChain, so you understand how everything works and design your own architecture. A dedicated LangChain session will follow for those who want to go further.

​What are the requirements?

​Bring a laptop with Python installed (Windows, macOS, or Linux), along with Visual Studio Code or a similar IDE, with at least 10GB of free disk space and 8GB of RAM.

This space is needed for running local models during the workshop.If you don’t have a suitable laptop, please contact Stelios ([email protected]) before registering.

​What is the format?

​A 3-hour live session with:

  • ​Interactive theory blocks
  • ​Hands-on coding
  • ​Step-by-step exercises
  • ​Small group support
  • ​Three 10-minute breaks
  • ​Q&A and class quizzes

​This is a highly practical, hands-on class focused on code and building working LLM systems.

​What are the prerequisites?

​A good understanding of programming with Python is required (basic to intermediate level). I assume you are already comfortable writing Python scripts.

​What comes after?

​Participants will receive an optional mini capstone project with one-to-one personalised feedback.

​Is it just one session?

​This is the first session in a new sequence on applied AI, covering agents, RAG systems, vector databases, and production-ready LLM workflows. Later sessions will dive deeper into topics such as embeddings with deep neural networks, LangChain, advanced retrieval, and multi-agent architectures.

You can decide afterwards whether you’d like to join future sessions.

​How many participants?

​To keep this interactive, only 15 spots are available. Please register as soon as possible.

Hands-On LLM Engineering with Python (Part 1)
Open Source AI in NYC 2025-12-15 · 21:30

If you work in banking, insurance, or financial services, do consider attending.

To attend: Please enroll here https://luma.com/jz7km6pb

We have an awesome line-up of topics around building AI agents, and a host of open source tools to help level up your AI game including:

  • ​Open Leaderboard for Financial LLMs and Agents
  • ​When agents act on your behalf: Enterprise Identity Considerations
  • ​An Agentic AI Powered Mobile Banking Application with ​Langflow
  • ​Unlocking Document Intelligence with ​Docling
  • ​​Data Prep Kit : Data Engineering for LLMs ​

​Speakers will include:

  • ​Kelly Abuelsaad - Architect & Engineer, AI Platform at IBM
  • ​Santosh Borse - Senior Engineer, watsonx Data Engineering at IBM
  • ​Gil Isaacs - Software & Cloud Solutions Architect at IBM
  • ​Dr Yanglet Liu - SecureFinAI Lab at Columbia University
  • ​Kathryn McAvoy – Financial Services Account Technical Leader at IBM
  • ​Ming Zhao - Open Technology at IBM
Open Source AI in NYC

👉 Register and subscribe to my calendar to join more free sessions.

Who is this for?

​Students, developers, and professionals who want a practical introduction to Machine Learning with Python, without the hype, just practical explanations and hands-on coding.

If you’re confused by ML being explained with buzzwords or abstract theory, this session gives you the Python fundamentals you actually need to build and use basic machine learning models from scratch.

​Who is leading the session?

​The session is led by Dr. Stelios Sotiriadis, CEO of Warestack, Associate Professor and MSc Programme Director at Birkbeck, University of London, specialising in cloud computing, distributed systems, and AI engineering.

​​Stelios holds a PhD from the University of Derby, completed a postdoctoral fellowship at the University of Toronto, and has worked on industry and research projects with Huawei, IBM, Autodesk, and multiple startups. Since moving to London in 2018, he has been teaching at Birkbeck. In 2021, he founded Warestack, building software for startups around the world.

What we’ll cover

​A practical introduction to core machine learning concepts and how to implement them with Python and scikit-learn:

  • ​The fundamentals of machine learning
  • ​Understanding datasets, features, and target variables
  • ​Data preprocessing and normalization
  • ​Training common ML models for classification and regression using Python libraries.
  • ​Evaluating models for accuracy
  • ​Visualising results with Python
  • ​Hands-on examples you can run directly in Google Colab

​This session focuses on real code, clear understanding, and practical ML engineering.

​What are the requirements?

​Bring a laptop and ensure you have a Gmail account. The session will run entirely on Google Colab, so no local installation is required.

Format

​A 2-hour live hands-on class, structured around:

  • ​Interactive explanations
  • ​Guided coding
  • ​Step-by-step exercises
  • ​Mini challenges
  • ​Q&A

​This is a practical, code-first session, suitable for both beginners and intermediate Python users wanting to level up.

​In-person or online?

​The class will run in person, with streaming available for remote attendees.

Please note: In-person participation is strongly preferred, as the session includes hands-on coding, live troubleshooting, and personalised support that cannot be fully provided to remote participants.

Prerequisites

​You should be comfortable writing basic Python scripts (variables, loops, functions, imports). No prior machine learning experience is required.

A link will be shared to participants after registration.Are there going to be more sessions?

​Yes, this is the first session in a new series on practical Machine Learning and applied AI with Python. Additional sessions will be scheduled afterwards, covering further machine learning and AI algorithms.

​What comes after?

​Participants will receive an optional mini ML assignment and recommended next steps for deeper learning.

Introduction to Machine Learning with Python (Part 1)

REGISTER HERE https://luma.com/h1pbvd9o

Who is this for?

This workshop is designed for complete beginners and anyone who wants to learn Python from the ground up. Whether you're new to programming, switching careers, or building your confidence before moving into data, AI, or software development, this series will guide you step by step. By the end of the programme, you’ll understand the fundamentals of Python and how real code works inside modern applications.

Who is leading the session?

The session is led by Dr. Stelios Sotiriadis, CEO of Warestack and Associate Professor & MSc Programme Director at Birkbeck, University of London. Stelios teaches cloud computing, distributed systems, data engineering, and AI engineering, and has extensive experience working with Huawei, IBM, Autodesk, and multiple startups.

He holds a PhD from the University of Derby, completed a postdoctoral fellowship at the University of Toronto, and has been teaching at Birkbeck since 2018. In 2021 he founded Warestack, building developer tools and automation software for startups around the world.

About the Series

Python for Beginners: From Zero to Hero is a live coding workshop split into 5 sessions (10 hours total). You will write code with me in real time, learning Python through hands-on exercises rather than slides. This is a limited-space, interactive workshop, ideal if you prefer learning by doing.

What we’ll cover (Part 1)

A practical workshop to Python, including:

  • What programming is and how Python works
  • Writing your first scripts step by step
  • Variables, input/output, data types, and operators
  • Logic and decision making (if/else)
  • Loops (for/while) and how to control program flow
  • Best practices for beginners
  • Small hands-on challenges to build confidence

Each exercise builds directly on the previous one, so by the end you’ll already feel comfortable writing real code.

Requirements

You just need:

  • A laptop (Windows, macOS, or Linux)
  • A Gmail account to access Google's Colab (if you don't have one please create)

Why Python?

Python is one of the most widely used programming languages in the world. It's the foundation of:

  • AI and machine learning
  • Data science
  • Web development
  • Automation
  • Scripting and DevOps
  • Modern backend systems

This workshop gives you the skills to move confidently toward all of these areas.

Format

A 2-hour live session including:

  • Interactive explanations
  • Live coding demonstrations
  • Step-by-step guidance
  • Hands-on exercises you complete during the session
  • Time for questions and practical help
  • Homework and exercises

This is a beginner-friendly, supportive learning environment.

Cost

The first session costs only £20, so you can get a flavour of the material and the teaching style. Each session after that is £40, making the total cost for all 5 sessions £180.

By the end of the 5 sessions, you will be able to confidently write Python code and build your own programs from scratch. You’ll understand how to work with data, automate tasks, and apply Python to real-world problems — giving you a strong foundation for further study in AI, data science, and software development.

Prerequisites

No prior programming experience or Python installation required. I’ll guide you through everything from scratch.

Introduction to programming with Python (Part 1)

Weave-cli is a fast CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes. Join us in this session and hear how why Max decided to create it and learn about its strengths and weaknesses for powering vector search for RAG, similarity search and other workloads

About the presenter Michael Maximilien (aka ‘Max’ or 'Dr. Max') is the founder and CEO of a “stealth” AI Agents startup in Silicon Valley. Before that he was an IBM Distinguished Engineer leading Open Source teams for AI agents and multi-agent systems. His career focused on pioneering software platforms, from early web services, to cloud computing, and more recently multi-agent systems. Max was a key OSS leader in the development of Cloud Foundry and Knative — the Kubernetes serverless platform. His expertise in distributed systems is backed by over 100 published papers and 20 patents; and his PhD in computer science in 2005 was focused on multi-agent systems. Max is also a retired Ironman triathlete and an award-winning photographer.

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.

[AI Alliance] Introducing weave-cli - A fast CLI for vector search

Weave-cli is a fast CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes. Join us in this session and hear how why Max decided to create it and learn about its strengths and weaknesses for powering vector search for RAG, similarity search and other workloads

About the presenter Michael Maximilien (aka ‘Max’ or 'Dr. Max') is the founder and CEO of a “stealth” AI Agents startup in Silicon Valley. Before that he was an IBM Distinguished Engineer leading Open Source teams for AI agents and multi-agent systems. His career focused on pioneering software platforms, from early web services, to cloud computing, and more recently multi-agent systems. Max was a key OSS leader in the development of Cloud Foundry and Knative — the Kubernetes serverless platform. His expertise in distributed systems is backed by over 100 published papers and 20 patents; and his PhD in computer science in 2005 was focused on multi-agent systems. Max is also a retired Ironman triathlete and an award-winning photographer.

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.

[AI Alliance] Introducing weave-cli - A fast CLI for vector search

Weave-cli is a fast CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes. Join us in this session and hear how why Max decided to create it and learn about its strengths and weaknesses for powering vector search for RAG, similarity search and other workloads

About the presenter Michael Maximilien (aka ‘Max’ or 'Dr. Max') is the founder and CEO of a “stealth” AI Agents startup in Silicon Valley. Before that he was an IBM Distinguished Engineer leading Open Source teams for AI agents and multi-agent systems. His career focused on pioneering software platforms, from early web services, to cloud computing, and more recently multi-agent systems. Max was a key OSS leader in the development of Cloud Foundry and Knative — the Kubernetes serverless platform. His expertise in distributed systems is backed by over 100 published papers and 20 patents; and his PhD in computer science in 2005 was focused on multi-agent systems. Max is also a retired Ironman triathlete and an award-winning photographer.

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.

[AI Alliance] Introducing weave-cli - A fast CLI for vector search

Weave-cli is a fast CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes. Join us in this session and hear how why Max decided to create it and learn about its strengths and weaknesses for powering vector search for RAG, similarity search and other workloads

About the presenter Michael Maximilien (aka ‘Max’ or 'Dr. Max') is the founder and CEO of a “stealth” AI Agents startup in Silicon Valley. Before that he was an IBM Distinguished Engineer leading Open Source teams for AI agents and multi-agent systems. His career focused on pioneering software platforms, from early web services, to cloud computing, and more recently multi-agent systems. Max was a key OSS leader in the development of Cloud Foundry and Knative — the Kubernetes serverless platform. His expertise in distributed systems is backed by over 100 published papers and 20 patents; and his PhD in computer science in 2005 was focused on multi-agent systems. Max is also a retired Ironman triathlete and an award-winning photographer.

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.

[AI Alliance] Introducing weave-cli - A fast CLI for vector search

Weave-cli is a fast CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes. Join us in this session and hear how why Max decided to create it and learn about its strengths and weaknesses for powering vector search for RAG, similarity search and other workloads

About the presenter Michael Maximilien (aka ‘Max’ or 'Dr. Max') is the founder and CEO of a “stealth” AI Agents startup in Silicon Valley. Before that he was an IBM Distinguished Engineer leading Open Source teams for AI agents and multi-agent systems. His career focused on pioneering software platforms, from early web services, to cloud computing, and more recently multi-agent systems. Max was a key OSS leader in the development of Cloud Foundry and Knative — the Kubernetes serverless platform. His expertise in distributed systems is backed by over 100 published papers and 20 patents; and his PhD in computer science in 2005 was focused on multi-agent systems. Max is also a retired Ironman triathlete and an award-winning photographer.

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.

[AI Alliance] Introducing weave-cli - A fast CLI for vector search

Weave-cli is a fast CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes. Join us in this session and hear how why Max decided to create it and learn about its strengths and weaknesses for powering vector search for RAG, similarity search and other workloads

About the presenter Michael Maximilien (aka ‘Max’ or 'Dr. Max') is the founder and CEO of a “stealth” AI Agents startup in Silicon Valley. Before that he was an IBM Distinguished Engineer leading Open Source teams for AI agents and multi-agent systems. His career focused on pioneering software platforms, from early web services, to cloud computing, and more recently multi-agent systems. Max was a key OSS leader in the development of Cloud Foundry and Knative — the Kubernetes serverless platform. His expertise in distributed systems is backed by over 100 published papers and 20 patents; and his PhD in computer science in 2005 was focused on multi-agent systems. Max is also a retired Ironman triathlete and an award-winning photographer.

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.

[AI Alliance] Introducing weave-cli - A fast CLI for vector search

Weave-cli is a fast CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes. Join us in this session and hear how why Max decided to create it and learn about its strengths and weaknesses for powering vector search for RAG, similarity search and other workloads

About the presenter Michael Maximilien (aka ‘Max’ or 'Dr. Max') is the founder and CEO of a “stealth” AI Agents startup in Silicon Valley. Before that he was an IBM Distinguished Engineer leading Open Source teams for AI agents and multi-agent systems. His career focused on pioneering software platforms, from early web services, to cloud computing, and more recently multi-agent systems. Max was a key OSS leader in the development of Cloud Foundry and Knative — the Kubernetes serverless platform. His expertise in distributed systems is backed by over 100 published papers and 20 patents; and his PhD in computer science in 2005 was focused on multi-agent systems. Max is also a retired Ironman triathlete and an award-winning photographer.

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.

[AI Alliance] Introducing weave-cli - A fast CLI for vector search

Weave-cli is a fast CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes. Join us in this session and hear how why Max decided to create it and learn about its strengths and weaknesses for powering vector search for RAG, similarity search and other workloads

About the presenter Michael Maximilien (aka ‘Max’ or 'Dr. Max') is the founder and CEO of a “stealth” AI Agents startup in Silicon Valley. Before that he was an IBM Distinguished Engineer leading Open Source teams for AI agents and multi-agent systems. His career focused on pioneering software platforms, from early web services, to cloud computing, and more recently multi-agent systems. Max was a key OSS leader in the development of Cloud Foundry and Knative — the Kubernetes serverless platform. His expertise in distributed systems is backed by over 100 published papers and 20 patents; and his PhD in computer science in 2005 was focused on multi-agent systems. Max is also a retired Ironman triathlete and an award-winning photographer.

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.

[AI Alliance] Introducing weave-cli - A fast CLI for vector search
docling presentation 2025-12-10 · 18:30
Panos Vagenas – Core Developer @ Docling / IBM Research

Presentation about contributing to Docling.

docling Python
Sponsor presentation 2025-12-10 · 18:30
Senthilnathan Natarajan – Senior Research Scientist @ IBM Research

In this meetup, we will provide an overview of the Fabric-X-Committer architecture and share performance evaluation results that highlight its scalability and efficiency.

hyperledger fabric fabric-x distributed systems blockchain performance
Fabric-X-Committer: A Microservices-Based Architecture for Ultra-High Throughput