NextBigFuture

Tokens and Tokenization are an Important for Fundamental LLM Understanding

Tokens are the fundamental units that LLMs process. Instead of working with raw text (characters or whole words), LLMs convert input text into a sequence of numeric IDs called tokens using a ...
VentureBeat

Fine-tuning vs. in-context learning: New research guides better LLM customization for real-world tasks

Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...
InfoWorld

The limitations of model fine-tuning and RAG

The hype and awe around generative AI have waned to some extent. “Generalist” large language models (LLMs) like GPT-4, Gemini (formerly Bard), and Llama whip up smart-sounding sentences, but their ...
Geeky Gadgets

How to Fine Tune your own LLM using LoRA (on a Custom dataset)

Imagine unlocking the full potential of a massive language model, tailoring it to your unique needs without breaking the bank or requiring a supercomputer. Sounds impossible? It’s not. Thanks to ...
Forbes

The Surprising Idea That Generative AI Might Be Better Off Using Visual Images Of Text Rather Than Pure Text As Tokens

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. For anyone versed in the technical underpinnings of LLMs, this ...
eWeek

How to Train an LLM: A Simple, User-Friendly Guide

In this episode of eSpeaks, Jennifer Margles, Director of Product Management at BMC Software, discusses the transition from traditional job scheduling to the era of the autonomous enterprise. eSpeaks’ ...
TechCrunch

Instead of fine-tuning an LLM as a first approach, try prompt architecting instead

Amid the generative AI eruption, innovation directors are bolstering their business’ IT department in pursuit of customized chatbots or LLMs. They want ChatGPT but with domain-specific information ...
SiliconANGLE

Thinking Machines makes its Tinker AI fine-tuning service generally available

Thinking Machines Lab Inc. today launched its Tinker artificial intelligence fine-tuning service into general availability. San Francisco-based Thinking Machines was founded in February by Mira Murati ...
InfoWorld

Databricks’ TAO method to allow LLM training with unlabeled data

Test-time Adaptive Optimization can be used to increase the efficiency of inexpensive models, such as Llama, the company said. Data lakehouse provider Databricks has unveiled a new large language ...
VentureBeat

Nvidia researchers boost LLMs reasoning skills by getting them to 'think' during pre-training

Researchers at Nvidia have developed a new technique that flips the script on how large language models (LLMs) learn to reason. The method, called reinforcement learning pre-training (RLP), integrates ...