A machine learning researcher is claiming to have knowledge of kinky drug-fueled orgies in Silicon Valley's storied hacker houses and appears to be linking those parties, and the culture surrounding them, to OpenAI. "The thing about being active in the hacker house scene is you are accidentally signing up for a career as a shadow politician in the Silicon Valley startup scene," begins the lengthy X-formerly-Twitter post by Sonia Joseph, a former Princeton ML researcher who's now affiliated with the deep learning institute Mila Quebec. What follows is a vague and anecdotal diatribe about the "dark side" of startup culture made particularly explosive by Joseph's reference to so-called "consensual non-consent" sex parties that she says took place within the artificial general intelligence (AGI) enthusiast community in the valley

Source: Wright Studio / Shutterstock.com The next phase of technology has been established: machine learning and AI will revolutionize the world for the better.

Retrieval Augmented Generation (RAG) models have emerged as a promising approach to enhance the capabilities of language models by incorporating external knowledge from large text corpora. However, despite their impressive performance in various natural language processing tasks, RAG models still face several limitations that need to be addressed. Naive RAG models face limitations such as missing content, reasoning mismatch, and challenges in handling multimodal data

Slack trains machine-learning models on user messages, files and other content without explicit permission. The training is opt-out, meaning your private data will be leeched by default. Making matters worse, youll have to ask your organizations Slack admin (human resources, IT, etc.) to email the company to ask it to stop