The Limits of Retrieval Augmentation, 8 AI Research Labs Worth Exploring, and Supercharging LLMs with LangChain
Is RAG All You Need? A Look at the Limits of Retrieval Augmentation
While retrieval augmentation can be a silver bullet in certain applications, it’s not always the best fit. Here’s a bit more on why that’s the case.
8 AI Research Labs Pushing the Boundaries of Artificial Intelligence
These eight AI research labs are designing the future of the field of data science, ranging from developing new LLMs to using AI to improve quality of life.
Supercharging Large Language Models With Langchain
In this tutorial, we will build a system that focuses on natural-language-based knowledge tasks, i.e. interacting with different knowledge resources via natural language.
Troubleshooting Large Language Models with Amber Roberts
This podcast with Amber Roberts of Arize AI examines recent research on ways to measure vector/embedding drift for image and language models, and the insights gained from testing different approaches.
Take a deep dive into Machine Learning, NLP, Large Language Models, Generative AI, MLOps, and more with 250+ experts, core contributors, and practitioners shaping the future of AI.
Industry, Opinion, Career Advice
What Dagster Believes About Data Platforms
The beliefs that organizations adopt about the way their data platforms should function influence their outcomes.
How Dash Enterprise 5.2 Enables Data Science Teams to Influence Mission-Critical Decisions
Here, the author shares her thoughts on how Dash Enterprise 5.2 will bring unrivaled speed, convenience, and efficiency to data app development.
Data Science & AI News
ODSC’s AI Weekly Recap: Week of February 16th
This week’s AI Weekly Recap is about NVIDIA’s RTX Chatbot and Notre Dame’s new consortium on responsible artificial intelligence.
Disney Hoping AI Can Help Match Commercials With Content
Disney is transforming streaming advertising with the AI tool Magic Words, which matches commercials with appropriate scenes in movies or shows.
NVIDIA Launches, RTX, Personalized GPT Models
With RTX, NVIDIA is allowing users to create their very own GPT LLM model based on their own files, such as docs and photos.
Researchers Use Machine Learning to Aid in Early Dementia Diagnosis
Researchers are hoping to be able to predict future dementia in healthy adults using machine learning algorithms.
Google DeepMind Introduces MusicRL Model
Google DeepMind has introduced MusicRL, a sophisticated MusicLM model that introduces a novel method of aligning music generation with human preferences through reinforcement learning.
University of Notre Dame Joins AI Safety Institute Consortium
Notre Dame is shaping the future of AI by contributing to the AISIC, focusing on developing safe and trustworthy AI technologies.
ODSC Highlights
Announcing the First Speakers for the 2024 Data Engineering Summit
Featuring topics like data-centric AI, Apache tools, and more, these are the first sessions announced for the Data Engineering Summit this April.
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New Podcast Episode: Guiding the Narrative: Shaping the Accuracy of LLM-Generated Content with Outlines
In this episode of ODSC’s Ai X Podcast, you’ll explore guided outputs for Large Language Models. Casual users of LLMs expect the responses they receive to be clear, understandable answers or engaging dialogue, which is achievable without special guidance.
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Upcoming Webinars:
Interview “No-Code and Low-Code AI: The New Era of Inclusive Tech Development”
Fri, Feb 23, 2024 12:00 PM — 1:00 PM EST
In the upcoming interview on February 23rd, we will speak with Gwendolyn Denise Stripling, PhD, and Artificial Intelligence and Machine Learning Content Developer at Google Cloud and Michael Abel PhD, both authors of the book “Low-Code AI: A Practical Project-Driven Introduction to Machine Learning.” In this interview, we’ll discuss what low-code and no-code AI is, how these topics can make AI more inclusive, and some examples of how to make it work in the real world. We’ll also touch upon details of their book and what went into writing it.
Inference Benchmarking of Prominent Open-Source LLMs
Tue, Feb 27, 2024 12:00 PM — 1:00 PM EST
In the upcoming webinar, we delve into the inference benchmarking of prominent open-source Large Language Models such as the 13B and 70B Llama-2. We have used a diverse range of compute shapes available in Oracle Cloud Infrastructure (OCI), like Intel, AMD, ARM CPUs, and NVIDIA GPUs.
Demo Tutorial: Customizable RAG workflows with your own Data
Wed, Mar 6, 2024 12:00 PM — 1:00 PM EST
Join us for a Python demo tutorial on building a customizable RAG (Retrieval Augmented Generation) stack using OSS Milvus vector database, LangChain, Ragas, HuggingFace, and optional Zilliz cloud and OpenAI.
The Promise of Edge ML: Bringing Your Model to Your Data
Tue, Mar 12, 2024 12:00 PM — 1:00 PM EDT
This talk will explore the new opportunity in processing data with ML where it’s generated. We’ll discuss the advantages of edge ML, including immediate insights, privacy preservation, and reduced network demands.
