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

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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.

** Important RSVP HERE (Due to limited room capacity, you must pre-register at the link for admission).

Welcome to the AI meetup in London, in collaboration with HPE. Join us for deep dive tech talks on AI, GenAI, LLMs and machine learning, food/drink, networking with speakers and fellow developers.

Tech Talk 1: Lessons learned from building a generalist agent Speaker: Sergei Petrov (Meta) Abstract: In this session, I'd like to share the experience of building a generalist agent to secure a spot on the GAIA leaderboard. I'll talk about what worked for us and what didn’t and what architecture we arrived at.

Tech Talk 2: What they don't tell you about using Vector Databases Speaker: Daniel Phiri (Weaviate) Abstract: Cool, I have a Vector database, now what? This talk answers this question, as get into implementation details that can help you scale your project and make the best out of the technology without burning a hole in your pocket.

Tech Talk 3: Coming soon Speaker: Alex Podmore (HPE)

Tech Talk 3: Coming soon

Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Venue: HPE, 1 Aldermanbury Square EC2V 7HR

Sponsors: We are actively seeking sponsors to support AI developers community. Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 15,000+ AI developers in London or 400K+ worldwide.

Community on Slack/Discord

• Event chat: chat and connect with speakers and attendees
• Sharing blogs, events, job openings, projects collaborations *

** Important RSVP here (Due to room capacity and building security, you must pre-register at the link for admission.)

Description: Welcome to our in-person AI meetup in New York. Join us for deep dive tech talks on AI, GenAI, LLMs and ML, hands-on workshops, food/drink, networking with speakers and fellow developers.

Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Tech Talk: Unleashing Data Magic: Vector Databases and RAG Demystified Speaker: Art Anderson (Aerospike) Abstract: Dive into the world of vector databases and Retrieval Augmented Generation (RAG) as we explore how we built a practical application and the challenges we faced. Discover how semantic search can enrich data, enabling recommendation engines, fraud detection, and more. Learn how these technologies can fit into your current applications and data, sparking new ideas for innovation.

Tech Talk: Step-by-Step RAG 101 Speaker: Tim Spann (Zilliz) Abstract: In this tutorial, we describe and show every step in building your own local RAG application using Milvus, LangChain, Ollama and Llama 3.x. At the end of the talk, you will have a working RAG application. We will also cover tips and techniques to upgrade to more advanced RAG apps.

Tech Talk: Generative AI Orchestration: Unlocking Creative Potential Speaker: Ram Durbha (Orkes) Abstract: Managing complex workflows in autonomous systems poses significant challenges as they scale. This talk explores strategies for optimizing agent-based architectures, where multiple agents interact and adapt in dynamic environments. Key topics include: 1) Distributed decision-making and coordination; 2) Bottlenecks; 3) Adaptive workflow reconfiguration and resilience; and 4) Real-world applications.

Sponsors: We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsor. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 20,000+ AI developers in New York or 400K+ worldwide.

Community on Slack/Discord

• Event chat: chat and connect with speakers and attendees
• Sharing blogs, events, job openings, projects collaborations

** RSVP here (Due to room capacity and venue security, it is required to pre-register at the link for admission)

Description: Welcome to the AI workshop in Berlin, in collaboration with Weaviate. Join us for deep dive tech talks, hands-on workshops on AI, GenAI, LLMs and machine learning, food/drink, networking with speakers and fellow developers

What's AI got to do with databases? As it turns out, quite a lot. The right database - spoiler alert! “an AI-native database” - can help your application, business, or customer get more out of ML models. An AI-native database is built from the ground up with AI use cases and tooling in mind – i.e. working with ML models is not a feature. It is its core purpose. An AI-native database enables you to build awesome AI-native projects.

This is a hands-on workshop where you will work with Weaviate, so bring your laptop with Python and Jupyter ready to go. You will learn:

• - embedding and generative models\,
• - how to vectorise and query your data using embedding models\,
• - how to combine vector and keyword search\, to run hybrid queries\,
• - how to extend search with a generative model to run RAG requests
• - if time allows\, we will dive into vector compression – to reduce the required RAM for vector embeddings.

Speakers/Instructors: - Sebastian Witalec\, Weaviate - Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community\, we invite you to submit topics for consideration: Submit Topics

Sponsors: We are actively seeking sponsors to support AI developers community. Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 10,000+ AI developers in Berlin or 400K+ worldwide.

Community on Slack/Discord

• Event chat: chat and connect with speakers and attendees
• Sharing blogs, events, job openings, projects collaborations *

** Important RSVP here (Due to room capacity and building security, you must pre-register at the link for admission.)

Description: Welcome to our in-person AI meetup in New York. Join us for deep dive tech talks on AI, GenAI, LLMs and ML, hands-on workshops, food/drink, networking with speakers and fellow developers.

Tech Talk: Unstructured Data and Vector Databases Speaker: Tim Spann (Zilliz) Abstract: In this session, I will discuss the unstructured data and the world of vector databases, we will see how they different from traditional databases. In which cases you need one and in which you probably don’t. I will also go over Similarity Search, where do you get vectors from and an example of a Vector Database Architecture. Wrapping up with an overview of Milvus.

Tech Talk: Tailoring Foundation Models for Generative AI Applications Speaker: Suman Debnath (AWS) Abstract: In this session, we will focus on fine-tuning, continuous pretraining, and retrieval-augmented generation (RAG) to customize foundation models using Amazon Bedrock. Attendees will explore and compare strategies such as prompt engineering, which reformulates tasks into natural language prompts, and fine-tuning, which involves updating the model's parameters based on new tasks and use cases. The session will also highlight the trade-offs between usability and resource requirements for each approach. Participants will gain insights into leveraging the full potential of large models and learn about future advancements aimed at enhancing their adaptability.

Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors: We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsor. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 20,000+ AI developers in New York or 400K+ worldwide.

Community on Slack/Discord

• Event chat: chat and connect with speakers and attendees
• Sharing blogs, events, job openings, projects collaborations

Register for the Zoom:

https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-sept-12-2024/

Reducing Hallucinations in ChatGPT and Similar AI Systems

LLMs are prone to producing hallucinations, largely due to their limited content and knowledge base. One of the most widely used techniques to reduce hallucinations is incorporating external knowledge sources. Among these, using knowledge graphs has shown particularly impressive results in enhancing the accuracy and reliability of the results produced by LLMs. In this talk, we will explore what knowledge graphs are, why they are important, and how to utilize the Neo4j graph database to improve the reliability of LLMs.

About the Speaker

Abhimanyu Aryan started in VR industry, then worked as an ML Engineer (Vision) for the Indian Air Force and contributed to Julia’s open-source web ecosystem( mostly Genie). Currently, building an AI stealth startup.

Update: Data-Centric AI Competition on Hugging Face Spaces

Are you ready to challenge the status quo in AI development? Then join Voxel51’s Harpreet Sahota for the latest updates, plus tips and tricks on the first-ever Data-Centric AI competition on Hugging Face Spaces, focusing on the often-overlooked yet crucial aspect of AI: data curation. Learn more about the competition, rules and prizes.

About the Speaker

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.

It's in the Air Tonight. Sensor Data in RAG

I will do a quick overview of the basics of Vector Databases and Milvus and then dive into a practical example of how to use one as part of an application. I will demonstrate how to consume air quality data and ingest it into Milvus as vectors and scalars. We will then use our vector database of Air Quality readings to feed our LLM and get proper answers to Air Quality questions. I will show you how to all the steps to build a RAG application with Milvus, LangChain, Ollama, Python and Air Quality Reports. Preview the demo on Medium.

About the Speaker

Tim Spann is a Principal Developer Advocate for Zilliz and Milvus. He works with Milvus, Generative AI, HuggingFace, Python, Big Data, IoT, and Edge AI. Tim has over twelve years of experience with the IoT, big data, distributed computing, messaging, machine learning and streaming technologies.

Register for the Zoom:

https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-sept-12-2024/

Reducing Hallucinations in ChatGPT and Similar AI Systems

LLMs are prone to producing hallucinations, largely due to their limited content and knowledge base. One of the most widely used techniques to reduce hallucinations is incorporating external knowledge sources. Among these, using knowledge graphs has shown particularly impressive results in enhancing the accuracy and reliability of the results produced by LLMs. In this talk, we will explore what knowledge graphs are, why they are important, and how to utilize the Neo4j graph database to improve the reliability of LLMs.

About the Speaker

Abhimanyu Aryan started in VR industry, then worked as an ML Engineer (Vision) for the Indian Air Force and contributed to Julia’s open-source web ecosystem( mostly Genie). Currently, building an AI stealth startup.

Update: Data-Centric AI Competition on Hugging Face Spaces

Are you ready to challenge the status quo in AI development? Then join Voxel51’s Harpreet Sahota for the latest updates, plus tips and tricks on the first-ever Data-Centric AI competition on Hugging Face Spaces, focusing on the often-overlooked yet crucial aspect of AI: data curation. Learn more about the competition, rules and prizes.

About the Speaker

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.

It's in the Air Tonight. Sensor Data in RAG

I will do a quick overview of the basics of Vector Databases and Milvus and then dive into a practical example of how to use one as part of an application. I will demonstrate how to consume air quality data and ingest it into Milvus as vectors and scalars. We will then use our vector database of Air Quality readings to feed our LLM and get proper answers to Air Quality questions. I will show you how to all the steps to build a RAG application with Milvus, LangChain, Ollama, Python and Air Quality Reports. Preview the demo on Medium.

About the Speaker

Tim Spann is a Principal Developer Advocate for Zilliz and Milvus. He works with Milvus, Generative AI, HuggingFace, Python, Big Data, IoT, and Edge AI. Tim has over twelve years of experience with the IoT, big data, distributed computing, messaging, machine learning and streaming technologies.

Register for the Zoom:

https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-sept-12-2024/

Reducing Hallucinations in ChatGPT and Similar AI Systems

LLMs are prone to producing hallucinations, largely due to their limited content and knowledge base. One of the most widely used techniques to reduce hallucinations is incorporating external knowledge sources. Among these, using knowledge graphs has shown particularly impressive results in enhancing the accuracy and reliability of the results produced by LLMs. In this talk, we will explore what knowledge graphs are, why they are important, and how to utilize the Neo4j graph database to improve the reliability of LLMs.

About the Speaker

Abhimanyu Aryan started in VR industry, then worked as an ML Engineer (Vision) for the Indian Air Force and contributed to Julia’s open-source web ecosystem( mostly Genie). Currently, building an AI stealth startup.

Update: Data-Centric AI Competition on Hugging Face Spaces

Are you ready to challenge the status quo in AI development? Then join Voxel51’s Harpreet Sahota for the latest updates, plus tips and tricks on the first-ever Data-Centric AI competition on Hugging Face Spaces, focusing on the often-overlooked yet crucial aspect of AI: data curation. Learn more about the competition, rules and prizes.

About the Speaker

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.

It's in the Air Tonight. Sensor Data in RAG

I will do a quick overview of the basics of Vector Databases and Milvus and then dive into a practical example of how to use one as part of an application. I will demonstrate how to consume air quality data and ingest it into Milvus as vectors and scalars. We will then use our vector database of Air Quality readings to feed our LLM and get proper answers to Air Quality questions. I will show you how to all the steps to build a RAG application with Milvus, LangChain, Ollama, Python and Air Quality Reports. Preview the demo on Medium.

About the Speaker

Tim Spann is a Principal Developer Advocate for Zilliz and Milvus. He works with Milvus, Generative AI, HuggingFace, Python, Big Data, IoT, and Edge AI. Tim has over twelve years of experience with the IoT, big data, distributed computing, messaging, machine learning and streaming technologies.

Register for the Zoom:

https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-sept-12-2024/

Reducing Hallucinations in ChatGPT and Similar AI Systems

LLMs are prone to producing hallucinations, largely due to their limited content and knowledge base. One of the most widely used techniques to reduce hallucinations is incorporating external knowledge sources. Among these, using knowledge graphs has shown particularly impressive results in enhancing the accuracy and reliability of the results produced by LLMs. In this talk, we will explore what knowledge graphs are, why they are important, and how to utilize the Neo4j graph database to improve the reliability of LLMs.

About the Speaker

Abhimanyu Aryan started in VR industry, then worked as an ML Engineer (Vision) for the Indian Air Force and contributed to Julia’s open-source web ecosystem( mostly Genie). Currently, building an AI stealth startup.

Update: Data-Centric AI Competition on Hugging Face Spaces

Are you ready to challenge the status quo in AI development? Then join Voxel51’s Harpreet Sahota for the latest updates, plus tips and tricks on the first-ever Data-Centric AI competition on Hugging Face Spaces, focusing on the often-overlooked yet crucial aspect of AI: data curation. Learn more about the competition, rules and prizes.

About the Speaker

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.

It's in the Air Tonight. Sensor Data in RAG

I will do a quick overview of the basics of Vector Databases and Milvus and then dive into a practical example of how to use one as part of an application. I will demonstrate how to consume air quality data and ingest it into Milvus as vectors and scalars. We will then use our vector database of Air Quality readings to feed our LLM and get proper answers to Air Quality questions. I will show you how to all the steps to build a RAG application with Milvus, LangChain, Ollama, Python and Air Quality Reports. Preview the demo on Medium.

About the Speaker

Tim Spann is a Principal Developer Advocate for Zilliz and Milvus. He works with Milvus, Generative AI, HuggingFace, Python, Big Data, IoT, and Edge AI. Tim has over twelve years of experience with the IoT, big data, distributed computing, messaging, machine learning and streaming technologies.

** Important RSVP here (Due to room capacity and building security, you must pre-register at the link for admission)

Description: Welcome to our in-person AI meetup in New York. Join us for deep dive tech talks on AI, GenAI, LLMs and ML, hands-on workshops, food/drink, networking with speakers and fellow developers.

Tech Talk: Unstructured Data and Vector Databases Speaker: Tim Spann (Zilliz) Abstract: In this session, I will discuss the unstructured data and the world of vector databases, we will see how they different from traditional databases. In which cases you need one and in which you probably don’t. I will also go over Similarity Search, where do you get vectors from and an example of a Vector Database Architecture. Wrapping up with an overview of Milvus.

Tech Talk 2: Unstructured Data Processing Speaker: George Portillo (ChainFuse) Abstract: In this session, we will discuss how to identify high stakes data, and share different ways of refining high-stakes unstructured data into meaningful, actionable data, and leverage the AI, LLMs to detect churn, high quality leads, and map a user's message to a user's journey and fill in the blanks.

Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors: We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsor. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 20,000+ AI developers in New York or 350K+ worldwide.

Community on Slack/Discord

• Event chat: chat and connect with speakers and attendees
• Sharing blogs, events, job openings, projects collaborations

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔

Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications. Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔 Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications.

Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔 Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications.

Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔

Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications.

Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔

Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications.

Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔

Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications.

Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔 Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications.

Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔 Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications.

Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

Are you interested in building custom Large Language Models (LLMs) on your enterprise data? 🤔 Join us for a live information session where we'll unveil details about our upcoming Large Language Models Bootcamp. Gain valuable insights, ask questions, and interact with instructors as we reveal exciting details. Online version launching soon!

What to expect: 📋 Gain insights into the bootcamp structure and curriculum details. 🧠 Dive deep into core topics including Canonical Architectures, Embeddings and Vector Databases, LangChain and Llama Index, and much more. 🛠️ Engage in hands-on projects & real-world applications.

Who Should Attend? Whether you're an AI enthusiast, a tech professional, a creative thinker, or simply someone eager to explore the possibilities of large language models, this event is tailored for you. No prior experience is required.

Talk to advisor \|\| Link to webpage

*** RSVP: https://www.aicamp.ai/event/eventdetails/W2024031309 (Due to room capacity and building security, it's required to pre-register at the link for admission).

Welcome to the monthly in-person AI meetup in Berlin, in collaboration with Weaviate. Join us for deep dive tech talks on AI, GenAI, LLMs and machine learning, networking with speakers and fellow developers.

Agenda: * 6:00pm\~7:00pm: Checkin and networking * 7:00pm\~9:00pm: Tech talks and Q&A * 9:00pm: Open discussion and Mixer

Tech Talk: Understand Social Media with Vector Search Speaker: Adam Chan (Weaviate) Abstract: In this talk, I will discuss and demo in real time some automation that is used to augment social media analytics through the power of vector databases and large language models.

Tech Talk: Cognee - semantic LLM context and chatbot integration Speaker: Vasilije Markovic (Topoteretes) Abstract: We will show how to use cognee to enrich LLM context and explain how LLMs, vector stores, graph databases and relational databases can be used together to decompose text, understand underlying semantic layers, connect them and provide LLMs with better context.

Tech Talk: The Power of Context: Exploring Google Gemini 1.5 Speaker: Gerard Sans (Google Developer Expert) Abstract: In this talk, get an exclusive first look at Google's groundbreaking Gemini 1.5 in action! This multimodal language model features a Mixture of Experts (MoE) architecture and a revolutionary 1 million token context window, allowing it to understand complex inputs with exceptional depth. We'll explore live demos showcasing how this translates to vastly improved AI assistance for users and its impact on RAG systems.

Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors: We are actively seeking sponsors to support AI developers community. Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 8,000+ AI developers in Berlin or 300K+ worldwide.

Community on Slack/Discord - Event chat: chat and connect with speakers and attendees - Sharing blogs\, events\, job openings\, projects collaborations

• Join Slack/Discord (link is at the bottom of the page) *