GIGAZINE

Why AI language models become difficult to operate when there are too many tokens to process; computational cost is proportional to the square of the input size

Generative AI, such as ChatGPT, which interprets information obtained from humans and responds to them in a way that is easy for humans to understand, recognizes and processes information in units ...
GIGAZINE

'Meaning Machine' visualizes how large-scale language models break words down into tokens and process them

Generative AI using large-scale language models such as ChatGPT, Claude, and Grok respond appropriately to user words just like a human. However, there is a big difference between how large-scale ...
Ars Technica

Why AI language models choke on too much text

Large language models represent text using tokens, each of which is a few characters. Short words are represented by a single token (like “the” or “it”), whereas larger words may be represented by ...
Ars Technica

Are LLMs capable of non-verbal reasoning?

Large language models have found great success so far by using their transformer architecture to effectively predict the next words (i.e., language tokens) needed to respond to queries. When it comes ...
ksn.com

Groq Sets New Large Language Model Performance Record of 300 Tokens per Second per User on Meta AI Foundational LLM, Llama-2 70B

The Groq Language Processing Unit™ system is the AI assistance enablement technology poised to provide real-time, "low lag" experiences for users with its inference performance. An LPU™ system is ...
Forbes

Salesforce Introduces XGen-7B, A Large Language Model With Longer Context Support

The race to release open source generative AI models is heating up. Salesforce has joined the bandwagon by launching XGen-7B, a large language model that supports longer context windows than the ...