Crypto Briefing

Reiner Pope: Batch size dramatically impacts AI latency and cost, kv cache is key for autoregressive models, and efficient inference can save resources | Dwarkesh

Batch size has a significant impact on both latency and cost in AI model training and inference. Estimating inference time ...
VentureBeat

New transformer architecture can make language models faster and resource-efficient

Large language models like ChatGPT and Llama-2 are notorious for their extensive memory and computational demands, making them costly to run. Trimming even a small fraction of their size can lead to ...
Android Police

Transformers: Everything you need to know about the deep learning model

I’ve been covering Android since 2023, when I joined Android Police, mostly focusing on AI and everything around Pixel and Galaxy phones. I’ve got a bachelor’s in IT with a major in AI, so I naturally ...
Communications of the ACM

Beyond LLMs: A Post-Transformer World Emerges

The rapid ascent of large language models (LLMs)—and their growing role in everyday life—masks a fundamental problem: ...
Searchenginejournal.com

Google DeepMind RecurrentGemma Beats Transformer Models

Google DeepMind published a research paper that proposes language model called RecurrentGemma that can match or exceed the performance of transformer-based models while being more memory efficient, ...

The AI industry’s massive bet on transformer models may not be enough for true AGI

As Big Tech pours unprecedented resources into scaling large language models, critics argue that transformer-based systems ...