Lessons from Building LLM-based Social Media Products
Explore Gen AI product development for social media: from ideation to success measurement. Learn efficient strategies for user-centric AI products, hardware planning, and building user trust.
Building Conversational AI Agents with Voice
Discover tips for creating conversational AI agents with voice, focusing on user experience. Learn from a Deepgram product manager about building effective speech-to-text interactions.
Explaining ChatGPT to Anyone in 10 Minutes
Learn to effectively communicate the complexities of ChatGPT and generative AI to diverse audiences using a simple three-part framework, enhancing public understanding and fostering responsible AI development.
LLMOps and GenAI at Enterprise Scale - Challenges and Opportunities
Explore challenges and opportunities in deploying GenAI solutions at enterprise scale. Learn about LLMOps, model selection, emerging stacks, and best practices for robust implementation.
The Role of ML Engineers in the Era of GPT-4 and BARD
Explore the evolving role of ML engineers amid the rise of large language models. Learn to evaluate API suitability, address privacy concerns, and adapt skills for future projects.
Solving LLM Data Problems with Vector Databases - Part 2
Explore vector databases' role in LLM apps, focusing on solving data issues and democratizing access to this technology for efficient billion-scale vector search.
Navigating Through the Generative AI Landscape
Explore the latest trends in Generative AI, gaining practical insights for startups to leverage advancements and enhance products in this dynamic field.
Enabling Defense Missions with Local LLMs - Part 2
Explore LeapfrogAI, an open-source toolkit for deploying and managing LLMs in sensitive, regulated environments, addressing challenges in defense missions and air-gapped systems.
Taming AI Product Development Through Test-driven Prompt Engineering
Explore test-driven development's crucial role in prompt engineering for AI systems. Learn to create reliable, predictable AI products through effective TDD practices.
LLMs vs LMs in Production - Key Differences in Using 100M vs 100B Parameter Models
Explore key differences between using 100M vs 100B parameter models in production, covering MLOps processes, prompt testing, automated training, and real-time inference for conversational AI.
Product Strategy for LLM Features When LLM Isn't Your Product
Discover strategies for integrating LLM features into existing products, focusing on practical use cases beyond chatbots. Learn to plan, roadmap, and measure success of LLM implementations in various industries.
Building a Python-Centric Feature Platform to Power Production AI Applications
Explore Tecton's journey in developing a Python-based platform for powering large-scale real-time AI applications. Learn about reliable solutions for productionizing AI using only Python skills.
From Robotics to AI NPCs - Embodied AI Agents in Games
Explore the fusion of robotics and AI in creating dynamic NPCs for games. Learn how multi-modal LLMs enable interactive virtual characters through simulation-based training techniques.
Fine-Tuning ViT Classifier with Custom Data - Inference for Images and Videos
Fine-tune a ViT model with custom data and perform inference on images and videos. Learn practical techniques for image and video classification using advanced machine learning.
Installing WSL with CUDA Support and PyTorch for Data Science and Machine Learning
Aprenda a instalar WSL con soporte CUDA y PyTorch para potenciar sus proyectos de aprendizaje automático y ciencia de datos en Windows.
Creating a QA Tool Using Langchain, OpenAI, and Neo4J
Develop a QA tool using Langchain, Neo4J, and OpenAI models for advanced data science and machine learning applications.
Counting Tokens with OpenAI's Tiktoken Library for API Usage
Learn to count tokens consumed by OpenAI's API using the Tiktoken library, optimizing your usage and costs.
Microsoft AI: Introduction to the Semantic Kernel SDK in C#
Explore Microsoft's Semantic Kernel SDK for integrating LLMs with C#. Learn to combine AI models with traditional programming for enhanced applications.
Document Similarity: Langchain, Ollama Mistral 7B, and Chroma for Machine Learning and Data Science
Explore document similarity using Langchain, Ollama with Mistral 7B or LLama 2, and Chromadb as VectorStore for machine learning and data science applications.
Whisper OpenAI Speech-to-Text and Translation Model
Aprende a utilizar Whisper, el modelo de reconocimiento de voz de OpenAI, para transcribir y traducir audio con precisión.
Computer Vision: OCR Tesseract for Different Formats and File Types
Extract text from various image and document formats using OCR Tesseract. Learn practical techniques for optical character recognition in data science and machine learning applications.