Exploring multi-agent AI systems
AI systems are evolving beyond single models handling tasks in isolation. Instead, intelligent multi-agent AI systems are emerging as a means to distribute work across multiple specialized agents, enabling collaboration, iterative refinement, and more dynamic decision-making. Rather than relying on a single model to generate and verify outputs independently, multi-agent systems introduce structured interactions where […]
What is RLHF? Reinforcement learning from human feedback for AI alignment
On this page What is RLHF? Why RLHF is important How RLHF works Training a reward model Key steps in RLHF training Conclusion Reinforcement learning from human feedback (RLHF) is a machine learning approach that leverages human insights to train models, particularly large language models (LLMs), for better alignment with human preferences. Instead of just using […]
LLM observability: Your guide to monitoring AI in production
Large language models likeGPT-4o andLLaMAare powering a new wave of AI applications, from chatbotsand coding assistantsto research tools. However, deploying these LLM-powered applications in production is far more challenging than traditional software or even typical machine learning systems. LLMs are massive and non-deterministic, often behaving as black boxes with unpredictable outputs. Issues such as false […]
Fraud detection: Machine learning techniques, methods and strategies
On this page What is fraud detection? Enhancing fraud detection with machine learning and AI Benefits of predictive analytics for fraud prevention Role of behavioral analytics in fraud prevention Advantages of real-time transaction monitoring Advanced fraud detection using machine learning algorithms Conclusion Fraud detection techniques employ methods such as real-time transaction monitoring, behavioral analytics, and […]
Generative AI in banking and finance
Generative AI is revolutionizing the financial services industries by automating complex tasks, enhancing customer interactions, and bolstering security. In banking, generative AI models can generate predictive insights, assist in credit assessments, and streamline processes, introducing new levels of efficiency and personalization. As financial institutions embrace this technology, generative AI promises to reshape the way they […]
What are AI agents? Key concepts, benefits, and risks
On this page What are AI agents? Risks of AI Agents How do AI agents work? The future of AI agents Conclusion AI agents are reshaping how humans solve complex problems, enabling intelligent decision-making and dynamic task execution beyond traditional AI systems like chatbots. Unlike chatbots, which follow scripted workflows, AI agents operate autonomously, learning […]
Responsible AI: A guide to guardrails and scorers
The rapid adoption of generative AI and large language models has transformed industries, enabling powerful applications in domains like customer service, content creation, and research. However, this innovation introduces risks related to misinformation, bias, and privacy breaches. To ensure AI operates within ethical and functional boundaries, organizations must implement AI guardrails – structured safeguards that […]
Generative AI in retail
Generative AI is reshaping the retail industry, ushering in a new era of personalization, operational efficiency, and innovation. As this technology advances, retailers are leveraging it to anticipate customer needs, enhance service quality, and streamline their operations—all of which are crucial in today’s competitive landscape. By delivering tailored experiences and automating complex processes, generative AI […]
Current best practices for training LLMs from scratch
Download the PDF On this page Introduction The scaling laws Hardware Dataset collection Dataset pre-processing Pre-training steps Model evaluation Bias and toxicity Instruction tuning RLHF Conclusion References Appendix Introduction Although we’re only a few years removed from the transformer breakthrough, LLMs have already grown massively in performance, cost, and promise. At W&B, we’ve been fortunate […]
What is retrieval augmented generation?
Retrieval-Augmented Generation (RAG) is a powerful technique in AI that combines large language models with real-time access to external data sources, allowing for more accurate, relevant, and timely responses. By dynamically retrieving authoritative information, RAG enables generative models to overcome the limitations of static, pre-trained knowledge, making them more effective for applications where precision and […]