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Bias, Toxicity, and Jailbreaking Large Language Models (LLMs)
A review of recent research on concerning characteristics of LLMs Continue reading on Towards Data Science » Towards Data Science – Medium
Evaluate large language models for quality and responsibility
The risks associated with generative AI have been well-publicized. Toxicity, bias, escaped PII, and hallucinations negatively impact an organization’s reputation and damage customer trust. Research shows that not only do risks for bias and toxicity transfer from pre-trained foundation models (FM) to task-specific generative AI services, but that tuning an FM for specific tasks, on…
Large Language Models: DeBERTa — Decoding-Enhanced BERT with Disentangled Attention
Large Language Models: DeBERTa — Decoding-Enhanced BERT with Disentangled Attention Exploring the advanced version of the attention mechanism in Transformers Introduction In recent years, BERT has become the number one tool in many natural language processing tasks. Its outstanding ability to process, understand information and construct word embeddings with high accuracy reach state-of-the-art performance. As a well-known…
LMQL — SQL for Language Models
LMQL — SQL for Language Models Yet another tool that could help you with LLM applications Image by DALL-E 3 I’m sure you’ve heard about SQL or even have mastered it. SQL (Structured Query Language) is a declarative language widely used to work with database data. According to the annual StackOverflow survey, SQL is still one of the most popular…
A Comprehensive List of Resources to Master Large Language Models
Large Language Models (LLMs) have now become an integral part of various applications. This article provides an extensive list of resources for anyone interested to dive into the world of LLMs. KDnuggets
Build a Language Model on your WhatsApp Chats
Build a Language Model on Your WhatsApp Chats A visual guide through the GPT architecture with an application Photo by Volodymyr Hryshchenko on Unsplash Chatbots have undeniably transformed our interaction with digital platforms. Despite the impressive advancements in the capabilities of underlying language models to handle complex tasks, the user experience often falls short, feeling impersonal and…
Large Language Models, StructBERT — Incorporating Language Structures into Pretraining
Large Language Models, StructBERT — Incorporating Language Structures into Pretraining Making models smarter by incorporating better learning objectives Introduction After its first appearance, BERT has shown phenomenal results in a variety of NLP tasks including sentiment analysis, text similarity, question answering, etc. Since then, researchers notoriously tried to make BERT even more performant by either modifying its…
Detecting Obfuscated Command-lines with a Large Language Model
In the security industry, there is a constant, undeniable fact that practitioners must contend with: criminals are working overtime to constantly change the threat landscape to their advantage. Their… Read more on Cisco Blogs Cisco Blogs
How to Make Large Language Models Play Nice with Your Software using LangChain
Beyond simply chatting with an AI model and how LangChain elevates LLM interactions with humans. KDnuggets