My name is Gero Hillebrandt, I live in Germany and hold an B.Sc. in Physics and an M.Sc. in Business Mathematics from the MLU Halle-Wittenberg. I am mainly interested in the various challenges of software development, ML/AI and quantitative finance.
This blog is a fun project where I automated daily summaries about the field of AI. Any future manual posts will be tagged with “by gh”. See this post for more details.
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments Beyond-NanoGPT: Go From LLM Noob to AI Researcher! Benefits: This initiative provides individuals with a structured pathway to navigate the complexities of large language models (LLMs). By democratizing AI education, it enables a broader range of participants, including those with minimal technical backgrounds, to engage in AI research....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments Were running 50+ LLMs per GPU by snapshotting GPU memory like a process fork Benefits: Running multiple large language models (LLMs) per GPU could lead to significantly reduced costs and improved resource utilization, making AI technology more accessible. This efficiency enables quicker experimentation and deployment of AI models, fostering innovation in various fields such as healthcare, education, and content creation....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments What happened to KANs? (Kolmogorov-Arnold Networks) Benefits: KANs provide a framework for estimating complex systems through a probabilistic approach, which can significantly enhance predictive modeling in various fields like meteorology, finance, and engineering. They facilitate a more profound understanding of system dynamics, which can lead to better decision-making and optimization of resources....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments ICML 2025: A Shift Toward Correctness Over SOTA? Benefits: A shift towards prioritizing correctness over state-of-the-art (SOTA) performance in machine learning could enhance the reliability and interpretability of AI models. With a focus on robustness, stakeholders can trust decisions made by AI, leading to safer applications in critical areas such as healthcare, finance, and autonomous systems....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments Google Open to Let Enterprises Self Host SOTA Models Benefits: Allowing enterprises to self-host state-of-the-art (SOTA) models can enhance data security, as sensitive information can remain on-premises while providing the benefits of advanced AI capabilities. This self-hosting approach can also lead to increased customization for specific business needs, allowing organizations to fine-tune models to better fit their operational contexts....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments A lightweight open-source model for generating manga Benefits: This model democratizes manga creation, allowing aspiring artists without formal training to produce their own comics. It fosters creativity by providing templates and styles, which can promote diverse storytelling and representation in manga....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments B200 vs H100 Benchmarks: Early Tests Show Up to 57% Faster Training Throughput & Self-Hosting Cost Analysis Benefits: The B200’s superior training throughput can significantly accelerate machine learning projects, allowing researchers and developers to iterate faster and reduce time to market for AI applications....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments Masters Degree While Working in the Field Benefits: Pursuing a master’s degree while working enables individuals to apply theoretical knowledge directly to practical situations, enhancing understanding and retention. This integration fosters professional growth and increases job satisfaction, as employees feel more competent and capable in their roles....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments Synthetic Introduction to ML for PhD Student in Mathematics Benefits: Introducing machine learning (ML) concepts to mathematics PhD students can enhance their problem-solving skills and foster interdisciplinary collaboration. It equips them with powerful tools to analyze complex datasets, optimize processes, and model behaviors in various fields, from economics to biology....
Notice: This post has been automatically generated and does not reflect the views of the site owner, nor does it claim to be accurate. Possible consequences of current developments Why does my GNN-LSTM model fail to generalize with full training data for a spatiotemporal prediction task? Benefits: Understanding the limitations of the GNN-LSTM model can guide researchers toward effective modifications that enhance its predictive capabilities. Insights gained can lead to improved algorithms, resulting in accurate forecasts for complex datasets in various applications, such as climate modeling and urban planning....