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In simple terms, retrieval-augmented fine-tuning, or RAFT, is an advanced AI technique in which retrieval-augmented generation is joined with fine-tuning to enhance generative responses from a large language model for specific applications in that particular domain. It allows the large language models to provide more accurate, contextually relevant, and robust results, especially for targeted sectors […]
What is RAFT? RAG + Fine-Tuning Read More »
Large Multimodal Models (LMMs) are a revolution in artificial intelligence (AI). Unlike traditional AI models that operate within a single data environment such as text, images, or audio, LMMs are capable of creating and processing multiple modalities simultaneously. Hence the generation of outputs with context-aware multimedia information. The purpose of this article is to unravel
What are Large Multimodal Models (LMMs)? Read More »
RAG (Retrieval-Augmented Generation) is a recent way to enhance LLMs in a highly effective way, combining generative power and real-time data retrieval. RAG allows a given AI-driven system to produce contextual outputs that are accurate, relevant, and enriched by data, thereby giving them an edge over pure LLMs. RAG optimization is a holistic approach that
Optimizing RAG with Better Data and Prompts Read More »
Large Language Models (LLMs) such as GPT-4 and Llama 3 have affected the AI landscape and performed wonders ranging from customer service to content generation. However, adapting these models for specific needs usually means choosing between two powerful techniques: Retrieval-Augmented Generation (RAG) and fine-tuning. While both these approaches enhance LLMs, they are articulate towards different
RAG vs. Fine-Tuning: Which One Suits Your LLM? Read More »
Imagine you have an x-ray report and you need to understand what injuries you have. One option is you can visit a doctor which ideally you should but for some reason, if you can’t, you can use Multimodal Large Language Models (MLLMs) which will process your x-ray scan and tell you precisely what injuries you
What Are Multimodal Large Language Models? Applications, Challenges, and How They Work Read More »
When I started working in the medical device industry almost 20 years ago, static analysis tools had captured the spotlight and attention of the medical device industry. This was apparent in a 2007 press article, which highlighted the United States Food and Drug Administration (FDA) Center for Devices and Radiological Health (CDRH)’s substantial investment in
Amid a push toward AI agents, with both Anthropic and OpenAI shipping multi-agent tools this week, Anthropic is more than ready to show off some of its more daring AI coding experiments. But as usual with claims of AI-related achievement, you’ll find some key caveats ahead. On Thursday, Anthropic researcher Nicholas Carlini published a blog
Sixteen Claude AI agents working together created a new C compiler Read More »
On Thursday, Anthropic and OpenAI shipped products built around the same idea: instead of chatting with a single AI assistant, users should be managing teams of AI agents that divide up work and run in parallel. The simultaneous releases are part of a gradual shift across the industry, from AI as a conversation partner to
AI companies want you to stop chatting with bots and start managing them Read More »
Last year was a big one for AI – especially regarding agents, large language models (LLMs) and digital twins. With every new advancement that changed our lives for the better came something equally complicating (trust and governance, for example), but I firmly believe AI is steering us in the right […] The post Retro vibes
Retro vibes to futuristic leaps: 4 predictions for the year ahead Read More »
Manufacturers operate some of the most complex machinery on the planet – from CNC machines and industrial robots to gas turbines with over 20,000 components. Keeping these assets running smoothly is mission-critical, yet maintenance teams are often buried under vague alerts, scattered documentation and time-consuming root cause analysis. Much of […] The post Why predictive
Why predictive maintenance needs more than retrieval Read More »
