GroningenML @ Klippa

When:
September 26th, 2024

Location:
Klippa
Laan Corpus Den Hoorn 1
9728 JM Groningen

Notice:
Please sign up with your actual, full name for the meetup, as you will be signed in by the organisers to enter the building.

Dietary restrictions:
Please reach out as soon as possible if you have any dietary restrictions. Klippa will organise a walking dinner by an actual caterer!

Agenda:
17:30 - Walk in and food
18:20 - Welcome by GroningenML and Klippa
18:30 - Presentation 1: Detecting Product Defects with Deep Computer Vision: A Real-World Application by Chris van Riemsdijk (AI Consultant at DataNorth)
19:00 - Presentation 2: Beyond RAG and Single Tool Calls: What Chained Tool Calling (and Agents) Can Do For You, by Atakan Tekparmak (Software & AI Developer at Symbiotic)
19:30 - Break
20:00 - Presentation 3: AI-Driven Customer Intelligence by Richard Fisher (AI Engineer at DataNorth)
20:30 - Closing statements
20:35 - Drinks and networking

Detecting Product Defects with Deep Computer Vision: A Real-World Application
This case study examines how deep computer vision techniques can be effectively used to detect product defects in a factory environment, enhancing both quality control and operational efficiency. By utilizing advanced image processing and deep learning models, manufacturers can achieve high-accuracy defect detection, minimizing waste and ensuring consistent product quality.

Keywords: Computer Vision, Defect Detection, Quality Control

Beyond RAG and Single Tool Calls: What Chained Tool Calling (and Agents) Can Do For You
The industry is quite excited about the potential of tool use with the latest SOTA LLMs all being trained or tuned on some form of tool use, but the current landscape and the conventions are still very limiting. Chained function calling enables models to express their agentic potential in one user-assistant turn instead of over several turns.

Keywords: Tool Use, Agents, Chained Function Calling

AI-Driven Customer Intelligence
From Web Scraping to Insights explores how businesses can leverage AI to better understand their customers. By combining LLM-based web scraping with Retrieval Augmented Generation (RAG), we transform publicly available data into actionable insights, enabling companies to identify customer industries, trends, and needs in real time.

Keywords: Web Scraping, Retrieval Augmented Generation (RAG), Customer Insights