Architectural Enhancements in Recent Open LLMs

Driving Performance, Efficiency, and Developer-Friendly Features As someone who frequently leverages large language models (LLMs) to build solutions, I find the recent advancements in the field both exciting and promising. The release of Databricks DBRX, Meta Llama 3, and Snowflake Arctic highlights the priorities of LLM creators in delivering powerful, efficient, and developer-friendly solutions. TheContinue reading “Architectural Enhancements in Recent Open LLMs”

Balancing Act: LLM Priors and Retrieved Information in RAG Systems

In the evolving landscape of AI, Large Language Models (LLMs) have emerged as powerful tools for generating human-like text. However, their reliance on internal knowledge, or “priors,” can lead to limitations in applications requiring up-to-date, accurate information. Retrieval Augmented Generation (RAG) systems aim to address this by augmenting LLMs with external knowledge retrieved from variousContinue reading “Balancing Act: LLM Priors and Retrieved Information in RAG Systems”

Generative AI: Insights from the Frontlines

A recent survey of large enterprises reveals a significant shift towards in-house application development, driven by the rise of foundation models offering accessible APIs. This move away from reliance on external vendors for AI-driven solutions has major implications for the industry. For instance, companies that once relied on third-party chatbots and custom recommenders can nowContinue reading “Generative AI: Insights from the Frontlines”

Judicial AI: A Legal Framework to Manage AI Risks

Constitutional AI (CAI), pioneered by Anthropic, is an approach to training AI systems that leverages a set of principles, akin to a constitution, to guide the AI’s behavior. This method prioritizes implementation of human value through these established principles, supplemented by minimal examples for fine-tuning prompts. It aims to reduce reliance on extensive human labelingContinue reading “Judicial AI: A Legal Framework to Manage AI Risks”

GenAI and LLMs: Insights from TikTok and KPMG

Subscribe • Previous Issues Generative AI: Insights from the Frontlines A recent survey of large enterprises reveals a significant shift towards in-house application development, driven by the rise of foundation models offering accessible APIs. This move away from reliance on external vendors for AI-driven solutions has major implications for the industry. For instance, companies that once reliedContinue reading “GenAI and LLMs: Insights from TikTok and KPMG”

Intel’s Gaudi 3: A Promising Contender in the AI Accelerator Arena

Intel’s Gaudi 3 is the latest generation of AI accelerators designed to provide high-performance, cost-effective solutions for AI training and inference tasks, particularly for large language models (LLMs) and generative AI applications. According to Intel, Gaudi 3 offers several practical benefits for AI teams, including: Increased performance: Gaudi 3 delivers 4x AI compute for BF16,Continue reading “Intel’s Gaudi 3: A Promising Contender in the AI Accelerator Arena”

Open LLMs: A Tale Of Two Licenses

Databricks Open Model License Llama 2 License   Differences in Restrictions Modification: The Databricks license explicitly requires stating that modifications have been made, while the Llama 2 license does not. Updates: The Databricks license requires making reasonable efforts to use the latest version of the model, which the Llama 2 license does not mention. IfContinue reading “Open LLMs: A Tale Of Two Licenses”