Blog - Articles around AI, ML, DL and more
Tools for Deep Learning, importance of machine learning, Java and artificial intelligence - these and much more are topics our blog is dedicated to. We encounter new challenges every day and want to share our experience and insights with you. On this overview page you can see teasers of all previous blog posts. Feel free to click through, browse our current series of topics on MLOps and get excited about the posts to come! If you have any feedback, experiences, or topic requests, please feel free to contact us - we look forward to hearing from you.
- Amazon DJL - a new DL framework for Java
- BGL symposium 2019 - lecture 'AI and Magic'
- ChatGPT for Teams: Privacy-Compliant Use in the Workplace
- Deep Fakes - How to spot faked Images
- Deep Java Learning Introduction - Part 1: NDManager & NDArray
- DL4J Workshop at the ML Summit in Berlin
- Enterprise Tensorflow - Java vs. Python
- Enterprise TensorFlow 2 - Saving a trained model
- Enterprise TensorFlow 3 - Loading a SavedModel in Java
- Enterprise TensorFlow 4 - Executing a TensorFlow Session in Java
- Enterprise Tensorflow: Code Examples
- Git as a management tool for training data and experiments in ML
- Jax 2018 - Talks about DL4J and more
- Jax 2019 Recap
- ML Conference 2017 in Berlin
- MLOps: Establishment and operation of an AI
- Neural networks - The five most common mistakes
- NLP, NLU and NLG: AI and text
- Recap: ML Conference 2019 in Munich
- TensorFlow and Java - An interview with entwickler.de
- Types of Artificial Neural Networks
- Understanding AI - Part 1: What is AI?
- Understanding AI - Part 2: Symbolic AI, Neural Networks and Deep Learning
- Understanding AI - Part 3: Methods of symbolic AI
- Understanding AI - Part 4: The basics of Machine Learning
- Understanding AI - Part 5: Supervised & Unsupervised Learning in ML
- What are Neural Networks and how do they work?
- Whisper 3 Large for JAVA
Blog Articles
Deep Fakes - How to spot faked Images
A (fairly) new kind of neural networks, so-called Generative Adversarial Networks or GANs, are nowadays capable of generating deceptively real images of people that do not actually exist. These fake images are indistinguishable from real photos at first glance. Fortunately, you might still uncover them if you look closely – if you know what to look for!
Recap: ML Conference 2019 in Munich
On 17.06. another round of the semi annual ML Conference started in Munich. As usual, it started with a day-long workshop with joint live coding, giving the participants an approachable introduction into Machine Learning and Deep Learning.
Supervised & Unsupervised Learning in ML
In the previous article we introduced the basic concepts of Machine Learning and how the training of an ML model works, using a simple but practical algorithm. Next, we want to take a closer look at the different types of Machine Learning.
BGL symposium 2019 - lecture 'AI and Magic'
“Any sufficiently advanced technology is indistinguishable from magic.” – Arthur C. Clarke JAX 2019 is barely over, but Christoph is already on the podium for the next talk. At the symposium of the BLG (Federal Association of Industrial Photographic Laboratories), his lecture will cover “AI and Magic – How does Artificial Intelligence work?
Jax 2019 - How do Neural Networks work?
JAX 2019 is approaching and once again Christoph is contributing two sessions. This year he’s focussing on Neural Networks and explains how to use TensorFlow-Training while working with JVM.
The basics of Machine Learning
After shedding some light onto Symbolic AI in the previous article, we’re now moving on to take a closer look at Machine Learning (ML). When it comes to Symbolic AI, breaking down a problem as minutely as possible is key for successfully solving it.
Methods of symbolic AI
In the previous article we added two distinctions to our initial definition of AI: On the one hand we distinguish between strong and weak AI (Terminator & Science Fiction vs. the scientific status quo). Also we pointed out the difference between symbolic AI and Machine Learning.
Symbolic AI, Neural Networks and Deep Learning
Artificial Intelligence (AI) is as old as computer science itself. Calculations, logical deductions, complex assignments… all this was once restricted to humans, until computers came forth.
What is AI?
From household help to doomsday scenario - there’s hardly a topic where public perception, state of research and reality seem so incongruent as with artificial intelligence. Reason enough to shed some light onto this subject with a series of articles.
DL4J Workshop at the ML Summit in Berlin
On October 1st and 2nd the first ML Summit takes place in Berlin. In 12 workshops in three parallel tracks, experts impart practical knowledge on the topics Applications for Business, Machine Learning Basics & Tools and Specialized Topics.