Post
1521
xLLM: New Generation of Large Language Models for Enterprise
Read full article at https://mltblog.com/4ftTko9
In this article, you will find my PowerPoint presentation describing the most recent features of xLLM, a CPU-based, full context, secure multi-LLM with real-time fine-tuning & explainable AI. It includes several new diagrams describing the innovative architecture, upcoming developments, new features and different use cases.
Content
➡️Enterprise use case: corporate corpus of a Fortune 100 company.
➡️Original version dealing with large websites such as Wolfram and Wikipedia. Comparison with OpenAI.
➡️xLLM for clustering and predictive analytics. Use case: unstructured text (articles) from a media company.
➡️Integration of our game-changing NoGAN tabular data synthesizer, and state-of-the-art model evaluation technology.
➡️Integration of external tools, for instance to solve math problems.
➡️Upcoming version for auto-indexing and cataloging large repositories.
➡️Demo: enterprise xLLM in action, featuring the modern user interface (full web API, not just a prompt box) with command menu and numerous options not found in other LLMs, including debugging, suggested prompts, choice of agents, and fine-tuning in real time.
➡️Relevancy score displayed to the user, for each returned item. I call it the new PageRank for RAG/LLM, using a technology radically different from Google search. See picture.
New startup coming soon!
We will be launching soon (January) a new startup focusing on GenAI at scale for Enterprises; xLLM will be part of the offer with exclusive features. We are looking for early adopters to partner with us on the Journey. The co-founder and CEO, to be announced soon, is Senior Director of GenAI at a Fortune 100 company, where the first version of Enterprise xLLM was implemented. More to come!
Read more, and access the PPT, at https://mltblog.com/4ftTko9
Read full article at https://mltblog.com/4ftTko9
In this article, you will find my PowerPoint presentation describing the most recent features of xLLM, a CPU-based, full context, secure multi-LLM with real-time fine-tuning & explainable AI. It includes several new diagrams describing the innovative architecture, upcoming developments, new features and different use cases.
Content
➡️Enterprise use case: corporate corpus of a Fortune 100 company.
➡️Original version dealing with large websites such as Wolfram and Wikipedia. Comparison with OpenAI.
➡️xLLM for clustering and predictive analytics. Use case: unstructured text (articles) from a media company.
➡️Integration of our game-changing NoGAN tabular data synthesizer, and state-of-the-art model evaluation technology.
➡️Integration of external tools, for instance to solve math problems.
➡️Upcoming version for auto-indexing and cataloging large repositories.
➡️Demo: enterprise xLLM in action, featuring the modern user interface (full web API, not just a prompt box) with command menu and numerous options not found in other LLMs, including debugging, suggested prompts, choice of agents, and fine-tuning in real time.
➡️Relevancy score displayed to the user, for each returned item. I call it the new PageRank for RAG/LLM, using a technology radically different from Google search. See picture.
New startup coming soon!
We will be launching soon (January) a new startup focusing on GenAI at scale for Enterprises; xLLM will be part of the offer with exclusive features. We are looking for early adopters to partner with us on the Journey. The co-founder and CEO, to be announced soon, is Senior Director of GenAI at a Fortune 100 company, where the first version of Enterprise xLLM was implemented. More to come!
Read more, and access the PPT, at https://mltblog.com/4ftTko9