Stay updated with best practices for technical writers. Includes an API documentation course for technical writers and engineers learning how to document APIs. The course includes sections on what an API is, API reference documentation, OpenAPI specification and Swagger, docs-as-code publishing and workflows, conceptual topics, tutorials, API documentation jobs, and more.

Predictive Text Using only 13KB of JavaScript. No LLM. permy.gif Try it here | Code | Permy This is a simple POC of using Permy with a simple JSON dictionary for predictive text that is surprisingly …

Papers With Code highlights trending Machine Learning research and the code to implement it.

A complete GPT2 implementation as a single SQL query in PostgreSQL.

Starter-kit to build constrained agents with Nextjs, FastAPI and Langchain - BCG-X-Official/agentkit

Fundamental concepts to get you going and get the most from the latest craze in the generative AI community: vector databases.

An introduction to Phi-2, a compact language model that is similar to Gemini Nano. The limits of LLM, and how to fix in engineering.

Connery - Plugin infrastructure for AI. Contribute to connery-io/connery development by creating an account on GitHub.

Part 3 of the LLM University module on Chat with Retrieval-Augmented Generation.

Nomic releases a 8192 Sequence Length Text Embedder that outperforms OpenAI text-embedding-ada-002 and text-embedding-v3-small.

Swyx’s watershed essay “The Rise of the AI Engineer” revealed the need for evolving your talents to seize the opportunities of the future; but how can you ra...

Machine Learning Engineering Open Book. Contribute to stas00/ml-engineering development by creating an account on GitHub.

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Transformers are a new development in machine learning that have been making a lot of noise lately. They are incredibly good at keeping…

A Comprehensive Overview of Prompt Engineering

Vector embeddings have become an essential component of Generative AI applications. These embeddings encapsulate the meaning of the text, thus enabling AI models to understand which texts are semantically similar. The process of extracting the most similar texts from your database to a user’s request is known as nearest neighbors or vector search. pgvector is […]

Thanks to the explosion of ChatGPT, several terms that are used in the field of AI meant for researchers are getting thrown out into more…

Rerankers have been a common component of retrieval pipelines for many years. They allow us to add a final "reranking" step to our retrieval pipelines — like...

Join, Pinecone Developer Advocate, @jamesbriggs as he delves into retrieval augmented generation (RAG) and explores its role in enhancing Large Language Mode...

In this Video I will show you multiple techniques to improve RAG Applications. We will have a look at ParentDocumentRetrievers, MultiQueryRetrievers, Ensembl...

Colab: https://drp.li/PZG2tBlog Post: https://towardsdatascience.com/forget-rag-the-future-is-rag-fusion-1147298d8ad1Original Code: https://github.com/Raudas...

In this post, I will go over the concept of simple linear regression, delve into the underlying mathematical principles of the algorithm, and explore its practical application in the field of machine learning.

The paper presents the Transformer, an innovative attention-based model for sequence transduction that sets new benchmarks for efficiency and performance.

Essential ML papers:1. Transformers: Attention is All You Needhttps://t.co/oA5TGGqu9s2. BERT: Pre-training of Deep Bidirectional Transformers for Language Understandinghttps://t.co/9ekAqIRQxs3. GPT: Language Models are Few-Shot Learnershttps://t.co/oBVEwfOoLB4. CNNs:…— James Lin (@jlinbio) January 6, 2024

Stay informed about important new AI/ML arXiv research papers.