Sam Altman returns as CEO, OpenAI has a new initial board

With its structured format, Tabular data dominates the data analysis landscape across various sectors such as industry, healthcare, and academia. Despite the surge in the use of images and texts for machine learning, tabular data’s inherent simplicity and interpretability have kept it at the forefront of analytical methods. However, while effective, the traditional and deep…

Self-supervised learning (SSL) has proven to be an indispensable technique in AI, particularly in pretraining representations on vast, unlabeled datasets. This significantly reduces the dependency on labeled data, often a major bottleneck in machine learning. Despite the merits, a major challenge in SSL, particularly in Joint Embedding (JE) architectures, is evaluating the quality of learned…

Introducing Horizons … Artificial Intelligence Weekly Powered by name.com Welcome Interested in sponsorship opportunities? Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News Inside Elon Musk’s messy breakup with OpenAI As OpenAI was ironing out a new deal with Microsoft in 2016 — one that would nab…

In the enchanting world of language models and attention mechanisms, picture a daring quest to accelerate decoder inference and enhance the prowess of large language models. Our tale unfolds with the discovery of multi-query attention (MQA), a captivating technique that promises speedier results. Multi-query attention (MQA) expedites decoder inference through the employment of a single…

Large Language Models (LLMs) have gathered a massive amount of attention and popularity among the Artificial Intelligence (AI) community in recent months. These models have demonstrated great capabilities in tasks including text summarization, question answering, code completion, content generation, etc.  LLMs are frequently trained on inadequate web-scraped data. Most of the time, this data is…