Jean-Luc Jackson, PE

Wow! Thank you Ariana Mendible for writing this lovely piece about your QSIDE experience for Mathematical Association of America's "Math Values" blog. We're so honored that you've been part of our quantitative justice journey! #data #datascience #mathematics #quantitativejustice #socialjustice https://lnkd.in/g_TEVq76

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Explore José Antonio Siqueira de Cerqueira's efforts in enhancing language models for greater safety and reliability. Dive into this article to discover his significant contributions to the field - https://lnkd.in/dA-EWMu2! 📚👨‍💻 #research #languagemodels

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We're thrilled to share our latest study, "Prompt-Time Ontology-Driven Symbolic Knowledge Capture with Large Language Models," on arXiv. This research explores innovative methods to enhance large language models (LLMs) with the ability to learn personal information—directly from user prompts—using ontology and knowledge-graph approaches. By fine-tuning LLMs with a predefined ontology, we improve their capability to incorporate user-specific information efficiently, leading to more personalized interactions. Our findings indicate that this approach significantly advances the personalization of AI technologies, bringing us closer to developing systems that adapt to each user's unique needs. Find the full preprint at https://lnkd.in/d2qJrAxf or https://lnkd.in/dnUvBH9g

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NYC Data Science Academy alumni and friends: Today (8/8/2024) at 11:00am will be our weekly Live Learning: Building LLM Powered Systems (part 2 of N). Our focus will be on: - situations where plain LLMs are insufficient for performing a particular task - handling guardrails and routing for black/white listing behavior and conversation paths - using LLMs to accomplish tasks on their own - how various functionality in commercial products (e.g. ChatGPT's web search) are implemented We will pick up where we left off, having models that talk to each other, and extend that to more practical applications. The code we ended with last time and will start with today is attached. There is no way we can cover all of this in one session, so we will continue this topic for a few weeks. In preparation, if you have not done so already, please watch https://lnkd.in/ecPHkDYn where we go over setting up https://lnkd.in/eA63wUU7 to run open source LLMs on your machine. Please also install Llama 3.1 8B Instruct, as that will be the model I will be demonstrating with. While this is by no means the only way to do this, it will be the method I use during our session. Additionally, if you need an introduction or refresher on function calling, you can watch https://lnkd.in/eNJx9vZW, as we will be putting some of this to use here. Zoom Link for Live Learning (please message me if you are not able to enter the room): https://lnkd.in/eScKr6kJ Meeting ID: 946 1359 3549 Passcode: 100607

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