Prompt Engineering: 7 Tricks to Solve Problems with AI - Part 4
Master prompt engineering techniques to enhance AI problem-solving. Learn 7 key tricks and explore practical applications using LangChain for building AI-powered solutions.
3 Ways to Make a Custom AI Assistant: RAG, Tools, and Fine-tuning
Explore three methods to create custom AI assistants using OpenAI: GPTs, Assistants API, and Fine-tuning API. Learn to build a YouTube comment responder through practical demonstrations.
QLoRA - How to Fine-tune an LLM on a Single GPU with Python Code
Learn to fine-tune large language models on a single GPU using QLoRA. Explore quantization techniques, LoRA, and practical implementation with Python code for custom YouTube comment responses.
Alzheimer's Prediction: QML for Neuroimaging and Other Biomarkers
Explore quantum machine learning applications in Alzheimer's prediction, focusing on language impairment, blood/CSF biomarkers, and neuroimaging. Discover potential QML advantages in early detection and diagnosis.
Advancing Quantum Algorithms for Brain Images Neuroradiology - Live Demo
Explore quantum algorithms for neuroradiology through live demos in IBM Qiskit and Pennylane. Learn about hybrid networks, recent advancements, and their potential impact on brain image processing.
Parallel Quantum Algorithms Innovation: PyTorch, Keras, and QiML
Explore parallel quantum algorithms for machine learning using PyTorch and Keras. Enhance model accuracy and efficiency by incorporating quantum layers in neural networks.
Quantum Machine Learning Parameters for Breakthrough Parallel Algorithms
Explore breakthrough parallel quantum algorithms for machine learning, improving performance and efficiency. Learn key benefits and optimal parameter settings for quantum-classical hybrid models.
Cancer Drug Discovery AI Agentic Workflow R&D
Explore AI agentic workflows for cancer drug discovery, leveraging advanced automation techniques to enhance compound lead generation and streamline the R&D process.
Speed-ups for State-of-the-Art Generative AI Drug Discovery Applications
Explore cutting-edge generative AI techniques for drug discovery, including VAEs, Hugging Face pipelines, and LLM comparisons. Learn to accelerate inference times using C++ and cloud platforms.
SliceGPT Explained - Compressing Large Language Models
Explore SliceGPT's innovative approach to compressing large language models by deleting rows and columns, maintaining high performance while reducing parameters significantly.
The Era of 1-bit LLMs Explained - BitNet b1.58 and New Scaling Laws
Explore groundbreaking research on BitNet b1.58, a ternary parameter model matching full-precision Transformers while offering improved cost-effectiveness and defining new LLM scaling laws.
Building a Chatbot with Unify - Webinar 01
Learn to build an interactive ChatBot using Unify, exploring Synchronous and Asynchronous clients and integrating with various LLMs for dynamic AI conversations.
YOCO: Decoder-Decoder Architectures for Language Models Explained
Explore YOCO, a decoder-decoder architecture for LLMs that improves inference memory, prefill latency, and throughput by caching key-value pairs once across context lengths and model sizes.
Unify and Baseten - Boosting LLM Deployment
Supercharge LLM deployment by integrating Baseten model endpoints into Unify Platform. Learn dynamic routing, open-source model usage, and practical demonstrations for optimized AI workflows.
Influential Data Retrieval Explained
Explore RapidIn, a scalable framework for estimating training data influence in large language models. Learn about token-wise retrieval and its two-stage approach.
Efficient Multi-Prompt Evaluation Explained
Explore PromptEval, a novel method for estimating LLM performance across multiple prompts, enhancing evaluation accuracy within practical budgets. Gain insights from University of Michigan researcher Felipe Polo.
Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences
Explore EvalGen, an interface for automated assistance in generating evaluation criteria and implementing assertions for LLM outputs aligned with human preferences.
The Janus Interface - Privacy Risks in Fine-Tuning Large Language Models
Explore how fine-tuning in large language models can amplify privacy risks, focusing on the novel Janus attack that recovers forgotten personal information from pre-training data.
Libraries and Nursing Science - Accessing Nursing Inquiry Resources
Discover nursing inquiry resources and access methods with Johns Hopkins' Lead Informationist Stella Seal in this informative presentation from the 2023 SHINE Conference.
Ethics of AI in Healthcare Informatics - Grand Rounds Lecture
Explore ethical considerations of AI in healthcare with Dr. Michael Abramoff, covering FDA approval, bias, health equity, and policy implications for medical practice.
Machine Learning in Congenital Heart Disease - From Information to Intelligence
Explore machine learning applications in congenital heart disease, transforming cardiac imaging data into intelligent diagnostic and treatment tools.