Remove Large Language Models Remove Prompt Engineering Remove Webinar
article thumbnail

LogLLM: Leveraging Large Language Models for Enhanced Log-Based Anomaly Detection

Marktechpost

LLMs, like GPT-4 and Llama 3, have shown promise in handling such tasks due to their advanced language comprehension. Current LLM-based methods for anomaly detection include prompt engineering, which uses LLMs in zero/few-shot setups, and fine-tuning, which adapts models to specific datasets.

article thumbnail

13 Free AI Courses on AI Agents in 2025

Marktechpost

Foundations of Prompt Engineering Offered by AWS, this course delves into crafting effective prompts for AI agents, ensuring optimal performance and accuracy. LLM Agents Learning Platform A unique course focusing on leveraging large language models (LLMs) to create advanced AI agents for diverse applications.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Ivo Everts, Databricks: Enhancing open-source AI and improving data governance

AI News

One of Databricks’ notable achievements is the DBRX model, which set a new standard for open large language models (LLMs). “Upon release, DBRX outperformed all other leading open models on standard benchmarks and has up to 2x faster inference than models like Llama2-70B,” Everts explains. .”

article thumbnail

Optimizing Large Language Models for Concise and Accurate Responses through Constrained Chain-of-Thought Prompting

Marktechpost

They introduced a refined prompt engineering strategy, Constrained-Chain-of-Thought (CCoT), which limits output length to improve accuracy and response time. These extended outputs can cause hallucinations, where the model generates plausible but incorrect information and overly lengthy explanations that obscure key information.

article thumbnail

Microsoft Researchers Combine Small and Large Language Models for Faster, More Accurate Hallucination Detection

Marktechpost

Large Language Models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks. However, they face a significant challenge: hallucinations, where the models generate responses that are not grounded in the source material. If you like our work, you will love our newsletter.

article thumbnail

Pace of innovation in AI is fierce – but is ethics able to keep up?

AI News

Indeed, as Anthropic prompt engineer Alex Albert pointed out, during the testing phase of Claude 3 Opus, the most potent LLM (large language model) variant, the model exhibited signs of awareness that it was being evaluated. The company says it has also achieved ‘near human’ proficiency in various tasks.

article thumbnail

IBM Research Introduced Conversational Prompt Engineering (CPE): A GroundBreaking Tool that Simplifies Prompt Creation with 67% Improved Iterative Refinements in Just 32 Interaction Turns

Marktechpost

Artificial intelligence, particularly natural language processing (NLP), has become a cornerstone in advancing technology, with large language models (LLMs) leading the charge. However, the true potential of these LLMs is realized through effective prompt engineering.