You’re not alone if the term “embeddings” has ever left you scratching your head or feeling lost in a sea of technical jargon.

Join the AI Writing Contest by Bright Data and HackerNoon! Share your insights on AI, LLMs, and web scraping for a chance to win from a $2500 prize pool.

'Innovate with Confidence: Expert Guidance in Advanced LLM Development' explores the strategies and insights for making the most of Language Learning Models.

Humanizing AI text is surely a challenge many people try to solve. Let me share how I found a solution to this riddle.

Learn how you can test an LLM with a handful of queries to assess how well it fits your project requrements

How to fix LLMs and chat bots with Langchain and Langgraph.

Enterprises will need to understand how they will use customer data and how it will get processed through AI models that are trained with the latest innovation.

I want the AI chatbot to help me with my job, not mess with my child’s mind.

Manage short-term memory in chatbots, using a combination of storage techniques and automatic summarization to optimize conversational context.

Learn to use Coze shortcuts for creating user-friendly buttons and Telegram commands to enhance your chatbot's efficiency and user experience

Build a Graph-RAG agent using Neo4j and Milvus to combine graph and vector search, delivering accurate, context-rich answers to complex queries.

Customer feedback can be a goldmine, full of insights about what people love and what could be improved. But with thousands of reviews, finding meaningful takeaways is like searching for needles in a haystack. That’s where Retrieval-Augmented Generation (RAG)…

Our online feeds are broken and large language models have the power to fix them.

In this paper, we present DREAMLLM, a comprehensive framework for developing MLLMs that not only understands but also creates multimodal content

AI works to keep prices high, even without instruction to do so

12/3/2024: Top 5 stories on the HackerNoon homepage!

AI-generated code can feel revolutionary—until it fails you. Why does this happen? Often, the issue isn't with the AI itself, but with the inputs we provide.

You can create sophisticated AI assistants that seamlessly handle everything from reversing strings to querying internal databases.

Building Vertical SaaS in an Old School Industry: AI That Fits, Not Fights

RAG - Retrieval Augmented Generation, Vector Database, Database Pipeline, Product Development