OpenAI and journalism

Powered by cloudfront.net In the News Top Artificial Intelligence AI Books to Read in 2024 AI has been making significant strides over the past few years, with the emergence of LLMs marking a major milestone in its growth. marktechpost.com Sponsor Discover what the most trusted industry experts are reading Use the Power of AI to…

Mathematical reasoning, part of our advanced thinking, reveals the complexities of human intelligence. It involves logical thinking and specialized knowledge, not just in words but also in pictures, crucial for understanding abilities. This has practical uses in AI. However, current AI datasets often focus narrowly, missing a full exploration of combining visual language understanding with…

Powered by global.ntt In the News AI Companies Lose $190 Billion After Dismal Financial Reports Following disappointing quarterly earnings results by Microsoft and Google owner Alphabet, Reuters reports that AI-related companies lost a whopping $190 billion in stock market value. futurism.com Sponsor GenAI can transform business operations GenAI presents immense opportunities for innovation, personalized customer…

Powered by onehouse.ai Welcome Bridging AI, Vector Embeddings and the Data Lakehouse Innovative leaders such as NielsenIQ are increasingly turning to a data lakehouse approach to power their Generative AI initiatives amidst rising vector database costs. Join us for a technical deep dive into the pivotal role of vector embeddings in AI and a demo…

In recent years, notable advancements in the design and training of deep learning models have led to significant improvements in image recognition performance, particularly on large-scale datasets. Fine-Grained Image Recognition (FGIR) represents a specialized domain focusing on the detailed recognition of subcategories within broader semantic categories. Despite the progress facilitated by deep learning, FGIR remains…

One of the main hurdles in achieving high forecast accuracy is dealing with data with multiple seasonality patterns. This means that the data might show variations daily, weekly, monthly, or yearly, making it tricky to predict future trends accurately. Some tools and libraries are already available to address this issue. They work by analyzing the…