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To Demis Hassabis and John Jumper, from DeepMind, and to David Baker, leader of the Institute for Protein DesignFigure from the Royal Swedish Academy of Sciences…
Multimodal Large Language Models (MLLMs) have made significant progress in various applications using the power of Transformer models and their attention mechanisms. However, these models face…
Retrieval-augmented generation (RAG) has become a key technique in enhancing the capabilities of LLMs by incorporating external knowledge into their outputs. RAG methods enable LLMs to…
CLASSIFICATION ALGORITHMBell-shaped assumptions for better predictions⛳️ More CLASSIFICATION ALGORITHM, explained: · Dummy Classifier · K Nearest Neighbor Classifier · Bernoulli Naive Bayes ▶ Gaussian Naive Bayes…
Storm chasing for data scientists: A Hurricane Milton case studyImage created by the author using Midjourney.On Wednesday, October 9, 2024, Hurricane Milton made landfall. The storm…
Generating accurate and aesthetically appealing visual texts in text-to-image generation models presents a significant challenge. While diffusion-based models have achieved success in creating diverse and high-quality…
While writing the code for any program or algorithm, developers can struggle to fill gaps in incomplete code and often make mistakes while trying to fit…
Accounting is evolving, and AI is leading the charge. With the AI accounting market set to hit $26.66 billion by 2029, tools like ChatGPT are transforming…
The field of multimodal artificial intelligence (AI) revolves around creating models capable of processing and understanding diverse input types such as text, images, and videos. Integrating…
Some weeks ago, I published a post on LinkedIn.The post was based on the following figure, comparing the predictions made by two models: Linear Regression, and…