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This is part 3 of my new multi-part series 🐍 Towards Mamba State Space Models for Images, Videos and Time Series.Mamba, the model to be said…
The success of ANNs stems from mimicking simplified brain structures. Neuroscience reveals that neurons interact through various connectivity patterns, known as circuit motifs, which are crucial…
Large Language Models (LLMs) have gained significant prominence in recent years, driving the need for efficient GPU utilization in machine learning tasks. However, researchers face a…
The mining industry is undergoing a large transformation with new technologies such as artificial intelligence (AI). As more companies seek to enhance their operations, AI is…
Text-to-image generation has evolved rapidly, with significant contributions from diffusion models, which have revolutionized the field. These models are designed to produce realistic and detailed images…
Graph learning focuses on developing advanced models capable of analyzing and processing relational data structured as graphs. This field is essential in various domains, including social…
Cardinality estimation (CE) is crucial in optimizing query performance in relational databases. It involves predicting the number of intermediate results a database query will return, directly…
Revisiting CPU for ML in an Era of GPU ScarcityPhoto by Quino Al on UnsplashThe recent successes in AI are often attributed to the emergence and…
A deep dive into stochastic decoding with temperature, top_p, top_k, and min_p10 min read·18 hours agoWhen calling the OpenAI API with the Python SDK, have you…
Large Language Models (LLMs) have revolutionized natural language processing but face significant challenges in handling very long sequences. The primary issue stems from the Transformer architecture’s…