Hey there 👋

I'm Marian Lambert

AI & Software Consultant

I enjoy building software solutions that create real value for people and businesses, in particular by leveraging the power of AI and LLMs. I am also a guest lecturer in the field of AI and Data Science.

Let's connect on LinkedIn!

Current projects

Undisclosed Project #3

This project focused on building a proof of concept (PoC) for an AI-powered system to improve the efficiency of creating medical assessments. The solution integrated transcription, generative AI, and user-friendly tools, all under tight time and resource constraints.

Negami

Negami is a mobile application that uses augmented reality and gamification to treat patients suffering from neglect after a stroke.

See all projects

Recent Talks

Me, Myself & AI

e-fellows.net Career Evening IT | Online | Oct 17, 2024

The keynote, targeted at young professionals in the field of AI, focused on the latest advancements in the field of artificial intelligence, as well as achievements, current challenges, and future developments. It also provided advice on what individuals could do to thrive in a world shaped by AI.

e-fellows Programm LinkedIn Post Slides

Build Your own LLMs: Customization and Hosting of AI Models

IT After Work | Pforzheim, Germany | Dec 6, 2023

In this talk, I discussed the customization and hosting of Large Language Models (LLMs) in the business context. The presentation highlighted strategies for personalization of LLMs, including retrieval-augmented generation and fine-tuning.

LinkedIn Post XPACE Blog Post Slides (German)

Evaluating Large Language Models and Prompt Variants on the Task of Detecting Cease and Desist Violations in German Online Product Descriptions

DataMod 2023 | Eindhoven, Netherlands | Nov 6, 2023

As part of the KIVEDU project, this talk demonstrated the results of our research on the evaluation of Large Language Models (LLMs) and prompt variants on the task of detecting cease and desist violations.

LinkedIn Post Program

Robustness Analysis of Machine Learning Models using Domain-Specific Test Data Perturbation

EPIA 2023 | Azores, Portugal | Sep 8, 2023

In this talk, I presented our research on robustness testing machine learning models in the image, audio and text domain. The presentation highlighted the importance of domain-specific test data perturbation for the evaluation of robustness.

LinkedIn Post Program

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Latest Blog Posts

What I learned from interviewing at 2 early-stage YC startups (and many other companies)

Insights from the intense interview processes at top-tier YC companies and what it takes to succeed in early-stage startups.

startups

interviews

career

tech

Submitting Apps to the Google Play Store is a terrible experience

A candid look at the frustrating process of submitting an augmented reality app to the Google Play Store compared to the much smoother experience with the Apple App Store.

Google Play

App Store

mobile dev

app development

Deploying a Complex Data Pipeline on Azure: Dagster vs. Prefect

Exploring the best options for deploying a complex data pipeline on Azure, comparing Dagster and Prefect.

Azure

Data Pipeline

Dagster

Prefect

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Do the simplest thing that could possibly work (by Sean Goedecke)

A good article about why starting simple in software development is often the best approach. It cautions against building overly complex systems and suggests adding complexity only when absolutely needed, rather than aiming for an 'ideal' system from day one.

software design

simplicity

engineering

Everything I know about good API design (by Sean Goedecke)

This post discusses good API design, emphasizing that successful APIs are often 'boring' and familiar to users. It covers common pitfalls like breaking changes, the complexities of API versioning, and how an API's success is tied to the underlying product's value. The author also offers practical advice on authentication, idempotency, rate limiting, and pagination.

software development

API design

Everything I know about good system design (by Sean Goedecke)

This post argues that good system design often looks simple and unimpressive, avoiding unnecessary complexity. It covers essential topics like state management, databases, caching, events, and handling system failures.

system design

software engineering

architecture

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