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GenAI in Banking Is a Double-edged Sword of Risk and Reward

In the banking sector, every percentage point in efficiency can translate to billions in revenue. According to McKinsey, GenAI could potentially add $340 billion in revenue to the sector’s annual global revenues. This represents a 4.7% increase in total industry revenues – a surge comparable...

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Continuously Monitor Your RAG System to Neutralize Data Decay

Poor data quality is the largest hurdle for companies who embark on generative AI projects. If your LLMs don’t have access to the right information, they can’t possibly provide good responses to your users and customers. In the previous articles in this series, we spoke about data enrichment,...

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Fix RAG Content at the Source to Avoid Compromised AI Results

While Retrieval-Augmented Generation (RAG) significantly enhances the capabilities of large language models (LLMs) by pulling from vast sources of external data, they are not immune to the pitfalls of inaccurate or outdated information. In fact, according to recent industry analyses, one of the...

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Generative AI in Healthcare: A Balance between Benefits and Ethics

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...

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Strategic Data Filtering for Enhanced RAG System Accuracy and Compliance

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...

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Evil Geniuses Attack, The LLM Forgettery, Character Consistency and More

Augmented Shelf | Issue 2 | March 19, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Evil Geniuses Vs. ChatDev To evaluate the vulnerability of LLM-based agents, researchers at Tsinghua University in Beijing, China, have...

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Forget LLM Memory – Why LLMs Need Adaptive Forgetting

Large Language Models (LLMs) rely on extensive memory to store and manipulate vast datasets, a key factor that allows them to learn from past inputs and improve their linguistic abilities over time. But what if, alongside remembering, LLMs could also benefit from adaptive forgetting? The notion of...

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Self Aware LLMs, Election AI-ffliction, India’s AI Reckoning and More

Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Is Claude 3 Opus Self-Aware? In a remarkable display of potential self-awareness, Anthropic’s newly released Claude 3 Opus AI showcased an unexpected response during an...

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Ethical AI Uncovered: 10 Fundamental Pillars of AI Transparency

Artificial intelligence (AI) is a transformative force, reshaping industries, revolutionizing how we interact with the world, and redefining the boundaries of what machines can do. As AI systems increasingly make decisions that affect our lives, the call for AI transparency has never been louder...

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Metadata Unlocks AI’s Superpowers

For the successful implementation of Artificial Intelligence (AI), the significance of properly integrating content metadata in AI with Large Language Models (LLMs) cannot be overstated. LLMs, such as Llama, Mistral and Claude, have become instrumental in a myriad of applications, ranging from...

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Text Becomes Insight with Vectorization

Computers are great at understanding numbers, but not with words. In order to help machines understand, manipulate, and produce words, we have to convert those words to numbers using a process called text vectorization. Text vectorization is the process of turning words and documents into...

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Master NLP History: From Then to Now

From its inception in the theoretical halls of mid-20th century academia to the sophisticated, AI-driven algorithms of today, the evolution of NLP has not only advanced our understanding of language processing but also pushed the frontiers of what’s possible, transforming how we interact...

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