QLoRA revolutionizes LLM fine-tuning with efficient quantization and low-rank adaptation, reducing resource needs without loss.

LLM inferencing uses pre-trained models to process inputs and generate outputs, leveraging AI's power for real-time text and data analysis.

LoRA: A game-changing technique for fine-tuning LLMs like GPT-4, using low-rank matrices for efficient, scalable, and cost-effective AI.

Graph RAG combines knowledge graphs with retrieval-augmented generation, enriching LLMs with accurate, contextual, and relational data for b

LightRAG: A dual-level retrieval breakthrough in RAG, using graph-based indexing for complex, precise AI responses. A leap in dynamic AI syn

The Turing test, proposed by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behavior equivalent to, or...

Anthropic has unveiled Claude 3.5 Sonnet, the latest addition to their AI model family, setting a new benchmark in the industry. This...

The impact of large language models (LLMs) such as GPT-4 on marketing and sales is profound and multifaceted. This article will explore...

Google Gemini is a set of large language models (LLMs) that leverage training techniques from AlphaGo, such as tree search and...

What is Prompt Engineering? Prompt engineering is a process of creating a set of prompts, or questions, that are used to guide the user...