This article details the integration of Docker Model Runner with the NVIDIA DGX Spark, enabling faster and simpler local AI model development. It covers setup, usage, and benefits like data privacy, offline availability, and ease of customization.
This article explains the internal workings of vector databases, highlighting that they don't perform a brute-force search as commonly described. It details algorithms like HNSW, IVF, and PQ, the tradeoffs between recall, speed, and memory, and how different RAG patterns impact vector database usage. It also discusses production challenges like filtering, updates, and sharding.
Preliminary, alphabetically ordered list of papers accepted for inclusion in the DX’25 proceedings as full papers.
The papers cover a range of topics within the field of diagnosis and prognosis, including:
* **LLM Applications:** Exploring the potential of Large Language Models for diagnostic concepts and fault detection.
* **Fault Diagnosis & Isolation:** Techniques for identifying and locating faults in systems like HVAC, control systems, and radiotherapy equipment, utilizing methods like dynamic slicing, spectrum-based fault localization, and data-driven approaches.
* **Prognosis & Remaining Useful Life:** Predicting future system behavior and estimating remaining useful life, including approaches using particle filters and spectral fault receptive fields.
* **Hybrid Systems & Machine Learning:** Utilizing one-shot learning and deep learning clustering for system identification and predictive maintenance.
* **Competition & Benchmarks:** Details about the DX 2025 competition and its associated benchmarks.
* **Model-Based Diagnosis:** Using qualitative simulation models and fusing temporal logic with probabilistic diagnosis.
The list includes 15 accepted papers with authors and titles provided. The conference will be held from September 22-24, 2025, in Nashville, Tennessee.
The papers cover a range of topics within the field of diagnosis and prognosis, including:
* **LLM Applications:** Exploring the potential of Large Language Models for diagnostic concepts and fault detection.
* **Fault Diagnosis & Isolation:** Techniques for identifying and locating faults in systems like HVAC, control systems, and radiotherapy equipment, utilizing methods like dynamic slicing, spectrum-based fault localization, and data-driven approaches.
* **Prognosis & Remaining Useful Life:** Predicting future system behavior and estimating remaining useful life, including approaches using particle filters and spectral fault receptive fields.
* **Hybrid Systems & Machine Learning:** Utilizing one-shot learning and deep learning clustering for system identification and predictive maintenance.
* **Competition & Benchmarks:** Details about the DX 2025 competition and its associated benchmarks.
* **Model-Based Diagnosis:** Using qualitative simulation models and fusing temporal logic with probabilistic diagnosis.
The list includes 15 accepted papers with authors and titles provided. The conference will be held from September 22-24, 2025, in Nashville, Tennessee.
This article details how to enable full eGPU acceleration on the Raspberry Pi 500+ with a 15-line patch, resulting in significant performance improvements for gaming and local LLMs. It covers the necessary hardware, software modifications, and benchmark results.
Italo Calvino's 'literature machine' is a prescient vision of the perils and promise of artificial intelligence. This article explores Calvino's thoughts on the future of literature in the age of computers, his embrace of fantasy as a way to represent the modern world, and why his work remains relevant today.
Delegate it a task, and coding agent can independently write, run, and test code. Here’s how you can make the most of it.
Google DeepMind research reveals a fundamental architectural limitation in Retrieval-Augmented Generation (RAG) systems related to fixed-size embeddings. The research demonstrates that retrieval performance degrades as database size increases, with theoretical limits based on embedding dimensionality. They introduce the LIMIT benchmark to empirically test these limitations and suggest alternatives like cross-encoders, multi-vector models, and sparse models.
An encyclopedia where everything can be an article, and every article is generated on the spot. Articles are often full of hallucinations and nonsense, especially with lower parameter models. The project uses Ollama and Go to generate content.
Fernando J. Corbató was a Professor Emeritus at MIT, renowned for his pioneering work in the development of time-sharing and resource-sharing computer systems. He was instrumental in creating the Compatible Time-Sharing System (CTSS) and Multics, both influential systems that laid the groundwork for modern operating systems. Corbató's contributions have been widely recognized through numerous awards and fellowships, including the Turing Award (1990) and the Computer Pioneer Award (1982). He was a long-time member of the MIT Computation Center and the Laboratory for Computer Science, and held leadership positions within the department. His work significantly impacted the field of computer science and the evolution of computing technology.
A forum dedicated to bug-lispm, a project related to the Lisp Machine. The page lists recent threads with their creation dates, titles, and number of posts/days spanned.
