AI

Artificial Intelligence will be the next general purpose technology. This core belief is what has been driving us at Merantix since our foundation, and we have been exploring what this means for various industries. In these articles, want to highlight the current roles of AI in various industries.

To navigate the quickly evolving landscape of Large Language Models (LLM), we create a comprehensive guide the decision making of you and your company.

Konstantin Ditschuneit and Julien Siems, ML Engineers at Merantix Momentum, shared their experience in winning a Kaggle challenge on energy demand forecasting

Key takeaways from our Generative AI Breakfast with the topic "Productising Generative AI"

At the Merantix Research Day 2023, Pierre Salvy, Head of Engineering at Cambrium, discussed how his team has been using mixed integer linear programming to diagnose productivity drops in cell factories.

GPT4 has launched, here's our first take on the exciting things ahead

Large Language Models are increasingly combined with conventional software solutions - this leads to exciting new systems.

New necessities for government spending and upcoming regulations make political involvement one of the major trends for AI.

The issue of many startups calling themselves AI startups when the major part of their value proposition is calling APIs.

The democratization of foundation models has arrived, changing the game for businesses looking to build AI-first products.

As AI becomes increasingly crucial for national defense and energy independence, the pursuit of sovereignty constitutes a major trend in AI and highlights the interdependence of semiconductor technology, energy supply, and AI capabilities.

2022 was another astonishing year for AI - let's see how many predictions we made turned out to be true.

In this article we will zoom in on the technology and business applications of GPT-3, since it is the most prominent large model and has been deployed the most

Europe has all the ingredients to build AI, and migration policies that enable it to quickly assemble the brightes minds to do so.

Many consider data privacy regulation as bad for businesses. But taking into consideration recent trends, it could turn out to be an advantage.

We believe four main domains need to be adressed in order to pave the way for even more AI made in Europe (Part 1 of2)

LEAM represents the opportunity to create Large Models, made in Europe. In the following, we will outline why Europe needs to face the changes in the AI field.

In our latest blog series, we want to highlight how 'AI made in Europe' is actually a lot stronger than often perceived.

A look into Large AI Models, their impact and why leading European institutions in the field of AI will now cooperate in building their own Large Models.

Find out how to patent your AI solution with these quick hacks

As an early stage startup your most valuable asset is your idea, this guide will help you patent your AI solution

Why we believe that in order to build AI, a more collaborative approach is needed.

#AI22 - No. 10 of 10

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30% of all screening centres in Germany actively use the Vara platform and we’re the first company in the world with large-scale real-world evidence from clinical routine. This comes down to our full-stack approach: We’re reimagining the entire workflow instead of integrating AI as a standalone plug-in.

#AI22 - No. 7 of 10

Breast cancer is a devastating and deadly disease, yet it doesn’t need to be. When caught early, the vast majority of women survive. AI is ready to take on this fight now. But it requires a new approach to democratise access to early detection worldwide.

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The use of AI technologies like computer vision is rapidly increasing in the retail industry. AI-enhanced retail holds the promise to eliminate operational inefficiencies and provide shoppers with frictionless in-store experiences. In this article, we’ve put together a list of the most innovative computer vision startups in the retail space.

Enabling flexible data selection with the SiaSearch API

From hiring the right entrepreneurs, to identifying a second-to-none business opportunity, to validation with our network of advisors and industry partners.

Causal inference techniques along with business analytics approaches unravel what truly changes your KPIs, while predictive modeling falls flat.