LangChain is a framework for developing applications powered by language models. It enables applications that:

Are context-aware: connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response in, etc.)
Reason: rely on a language model to reason (about how to answer based on provided context, what actions to take, etc.)
This framework consists of several parts.

LangChain Libraries: The Python and JavaScript libraries. Contains interfaces and integrations for a myriad of components, a basic run time for combining these components into chains and agents, and off-the-shelf implementations of chains and agents.
LangChain Templates: A collection of easily deployable reference architectures for a wide variety of tasks.
LangServe: A library for deploying LangChain chains as a REST API.
LangSmith: A developer platform that lets you debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain.

Mobile applications development has been enhanced by Machine Learning (ML) and Artificial Intelligence (AI). The integration of ML models in applications in order to classify or predict events allows the creation of applications able to understand and recognise user’s behaviour and make their experience more intelligent and interesting. An easement to understand example is the next words suggested to user based on the previous content typed while texting messages. So, this article will analyse the integration of a ML model into a mobile flutter application to audio recognition.

Destacamos la liberación por Google bajo código abierto de su sistema de aprendizaje automático, TensorFlow; el de Apple liberando el código detrás del lenguaje de programación Swift; Facebook añadiendo una gran cantidad de proyectos de código abierto incluyendo React Native y Relay; la creación de la empresa sin ánimo de lucro dedicada a la investigación y desarrollo de Inteligencia Artificial, OpenAI; la entrega por Tesla Motors de la totalidad de su cartera de patentes bajo código abierto y otros que triunfan en las grandes empresas (Docker, Kubernetes, Hyperledger, Hadoop, MongoDB, Vault…).