Vimarsana
Biggest News Aggregation in the World

Jacob Devlin News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Stay updated with breaking news from Jacob Devlin. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.

Top News In Jacob Devlin Today - Breaking & Trending Today

Google Gemini AI explained, vs. Bard and Assistant - Vimarsana News

Google Gemini AI explained, vs. Bard and Assistant

Google Bard has become Google Gemini, and the generative AI has some new tricks to go with the rebranding. Here's how to access it, whether or not you should pay for Gemini Advanced, and whether or no

AI Research Blog - The Transformer Blueprint: A Holistic Guide to the Transformer Neural Network Architecture - Vimarsana News

AI Research Blog - The Transformer Blueprint: A Holistic Guide to the Transformer Neural Network Architecture

A deep dive into Transformer a neural network architecture that was introduced in the famous paper “attention is all you need” in 2017, its applications, impacts, challenges and future directions

VB Transform 2023: Announcing the nominees for VentureBeat's 5th Annual AI Innovation Awards - Vimarsana News

VB Transform 2023: Announcing the nominees for VentureBeat's 5th Annual AI Innovation Awards

Announcing our nominees for the VB Transform AI Innovation awards multiple generative AI categories.

A|I: The AI Times – Can Québec's Quantum Innovation Zone fill Canada's D-Wave-sized hole? - Vimarsana News

A|I: The AI Times – Can Québec's Quantum Innovation Zone fill Canada's D-Wave-sized hole?

The AI Times is a weekly newsletter covering the biggest AI, machine learning, big data, and automation news from around the globe.

Notes on training BERT from scratch on an 8GB consumer GPU - Vimarsana News

Notes on training BERT from scratch on an 8GB consumer GPU

I trained a BERT model (Devlin et al, 2019) from scratch on my desktop PC (which has a Nvidia 3060 Ti 8GB GPU). The model architecture, tokenizer, and trainer all came from Hugging Face libraries, and my contribution was mainly setting up the code, setting up the data (~20GB uncompressed text), and leaving my computer running. (And making sure it was working correctly, with good GPU utilization.)