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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…
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
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
ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models
Large Language Models (LLMs) with billions of parameters have drastically transformed AI applications. However, their demanding computation during inference has raised significant challenges for deployment on resource-constrained devices. Despite recent trends favoring alternative activation functions such as GELU or SiLU, known for increased computation, this study strongly advocates for reinstating ReLU activation in LLMs. We…
Striking Performance: Large Language Models up to 4x Faster on RTX With TensorRT-LLM for Windows
Generative AI is one of the most important trends in the history of personal computing, bringing advancements to gaming, creativity, video, productivity, development and more. And GeForce RTX and NVIDIA RTX GPUs, which are packed with dedicated AI processors called Tensor Cores, are bringing the power of generative AI natively to more than 100 million…