Deep-Learning

Date: April 2023 Locations: Stuttgart · Tübingen · Zurich The Cyber Valley AI Startup Bootcamp is one of Europe’s most prestigious AI entrepreneurship programs, organized by Cyber Valley — Germany’s largest research consortium for artificial intelligence, headquartered across Stuttgart and Tübingen. About the Program The bootcamp brought together researchers, engineers, and entrepreneurs from across Europe to explore the intersection of cutting-edge AI research and real-world product development. Sessions spanned Stuttgart and Tübingen (home to the Max Planck Institute and University of Tübingen) before culminating in Zurich, giving participants exposure to both the academic and startup ecosystems in the DACH region. ...

A diffusion model learns to generate data by reversing a controlled corruption process. During training, clean examples are mixed with noise at different intensities. A neural network learns what noise was added—or, in equivalent parameterizations, what clean sample or velocity produced the noisy input. During generation, the model begins with random noise and repeatedly transforms it into a structured sample. That description is simple, but three details matter: Training does not run the entire noising chain for every example. Any noise level can be sampled directly. The reverse transition is learned because the exact reverse distribution depends on the unknown data distribution. Generation is iterative. Computation within one step is parallelizable, but the denoising steps themselves are sequential. The formulation was introduced by Sohl-Dickstein et al. and made practical for high-quality image synthesis by Ho, Jain, and Abbeel. This article develops the discrete-time DDPM formulation first, then connects it to modern architectures and samplers. ...

Date: April 2023 Location: Stuttgart, Germany MESH is a Stuttgart-based innovation and entrepreneurship platform that brings together students, researchers, and industry professionals to tackle real-world challenges through intensive hackathons. Format Over an intensive weekend, teams collaborated to build working AI prototypes addressing practical problems in areas ranging from healthcare and sustainability to finance and productivity. The hackathon format pushed participants to move fast — from ideation to demo-ready product within 48 hours. ...

Attention lets a model construct a new representation of each token by mixing information from other tokens. The mixing weights depend on the current input, so the same word can use different context in different sentences. That description is useful but incomplete. Attention does not inherently know token order. A causal mask is not a positional encoding. A key-value (KV) cache is not long-term memory. Retrieval-augmented generation (RAG) and mixture-of-experts (MoE) are not attention variants. Attention maps can also be informative without being faithful explanations of a prediction. ...