Shelf Blog
Get weekly updates on best practices, trends, and news surrounding knowledge management, AI and customer service innovation.
It’s estimated that $1 trillion in healthcare spending is wasted each year in the U.S. By automating routine tasks and making more use of clinical data, GenAI is a new opportunity to optimize healthcare expenditures and unlock part of the money lost to inefficiencies. It could organize...
Large language models are skilled at generating human-like content, but they’re only as valuable as the data they pull from. If your knowledge source contains duplicate, inaccurate, irrelevant, or biased information, the LLM will never behave optimally. In fact, poor data quality is so inhibiting...
AI hallucinations refer to instances where AI systems, particularly language models, generate outputs that are inconsistent, nonsensical, or even entirely fabricated. This issue is especially prevalent in AI systems that rely on external data sources, such as Retrieval-Augmented Generation (RAG)...
While large language models excel in mimicking human-like content generation, they also pose risks of producing confusing or erroneous responses, often stemming from poor data quality. Poor data quality is the primary hurdle for companies embarking on generative AI projects, according to...
The AI Weekly Breakthrough | Issue 6 | April 17, 2024 Welcome to The AI Weekly Breakthrough, a roundup of the news, technologies, and companies changing the way we work and live Meta Breaks Silence, Announces Llama 3 Meta, relatively quiet as of late, breaks its silence this week to make two...
Reinforcement Learning from Human Feedback (RLHF) is a cutting-edge approach in artificial intelligence (AI) that blends human intelligence with machine learning to teach computers how to perform complex tasks. This method is particularly exciting because it represents a shift from traditional...
Extract, Transform, and Load, or ETL, is a crucial data management process, especially in the AI and machine learning space. It’s like a data-moving team that takes information from various sources, cleans it up, and organizes it neatly in one place. This process is vital for businesses and...
The AI Weekly Breakthrough | Issue 5 | April 9, 2024 Welcome to The AI Weekly Breakthrough, a roundup of the news, technologies, and companies changing the way we work and live. More Agents Is All You Need A study using a simple sampling-and-voting method showed that LLM performance scales with...
Data augmentation is a pivotal technique in the realm of Natural Language Processing (NLP). It’s used to expand and diversify training datasets, thereby enhancing the performance and robustness of AI models. This technique is crucial for AI practitioners, data scientists, and technologists who aim...
Foundation models are a cornerstone in how we approach, develop, and implement AI technologies. These models, with their ability to learn from vast datasets and adapt to a multitude of tasks, represent a significant leap in AI’s evolution. Whether you’re an IT professional looking to deepen...
Navigating the multifaceted nature of human language is a unique challenge for machines. Ambiguous words, phrases, sentences, and contexts make language models struggle to understand and interpret human language with nuance and precision. Addressing ambiguity, therefore, is crucial for modern...
Augmented Shelf | Issue 4 | April 3, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Street Fighting LLMs Ready for a digital brawl like no other? In a groundbreaking experiment, cutting-edge Language Models (LLMs)...