ML6team

We are a team of AI experts and the fastest growing AI company in Belgium. With offices in Ghent, Amsterdam, Berlin and London, we build and implement self learning systems across different sectors to help our clients operate more efficiently. Find out more via www.ml6.eu

Editors
Matthias Feys

Data geek @ml6team by day & GDE for ML and @googlecloud by night

Juta Staes

Machine Learning Engineer @ ML6

Robbe Sneyders

Principal ML Engineer @ ML6

Thomas Uyttenhove

Machine Learning Engineer at ML6

Jules Talloen

Machine Learning Engineer at ML6

Jérémy Keusters

Machine Learning Engineer at ML6

Ruwan Lambrichts

Machine Learning Engineer @ ML6

Matthias Cami

Working @ML6 as ML engineer. I like problem solving & experimenting.

Andres Vervaecke

Data Engineer at ML6.

Michiel De Koninck

Mathematical Engineer with a healthy affinity for the world of (generative) AI.

Jens Bontinck

OCTO @ ML6

Nicholas Cointepas

Consultant, innovation enthusiast, neurodiversity advocate

Pieter Coussement

PhD Biotech turned into Data Engineer. Give me challenges and I’ll do my best. https://pietercoussement.netlify.app/

Latest Posts

Advancements in Protein Design

For avid followers of the Protein design space, you’ll likely have come across our earlier blog detailing the ins and outs of the current…

The landscape of LLM guardrails: intervention levels and techniques

The capacity of the latest Large Language Models (LLMs) to process and produce highly coherent human-like texts opens up a large potential…

How LLMs access real-time data from the web

Unravelling web access for modern large language models

Unsupervised Evaluation of Semantic Retrieval by Generating Relevance Judgments with an LLM Judge

Written by Till Wenke & Fabian Bergmann — February 13, 2024

Tuning the RAG Symphony: A guide to evaluating LLMs

Over the last year, chatbots leveraging the capabilities of Large Language Models (LLMs) have become a very popular solution for…

Promoting Code Across Environments for Reliable and Efficient Model Deployment

In this blogpost we present ML6’s recommended CI/CD pattern for machine learning models and take you on a detailed walkthrough of the…

Elevating Your Retrieval Game: Insights from Real-world Deployments

Exploring the world of Retrieval Augmented Generation (RAG) can be both fascinating and confusing. With the promise of discovering amazing…

Unlocking the Secrets of Life: AI Protein Models Demystified

This blogpost is aimed at those who want to understand how artificial intelligence is being implemented in the field of biology…

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