Ricardo Ferreira
@riferrei.com
Genius, billionaire, playboy, and philanthropist. This is Tony Stark. I'm Ricardo, one who believes this 💩 is chocolate yogurt.
https://riferrei.com
https://riferrei.com
October 1, 2025 at 4:07 PM
If you're interested in understanding how I implemented this demo, here is the GitHub repository:
github.com/redis-develo...
github.com/redis-develo...
GitHub - redis-developer/my-jarvis-alexa-skill: My Jarvis is an Alexa skill that can remember and recall memories from users, providing more contextual answers. It utilizes the Redis Agent Memory Serv...
My Jarvis is an Alexa skill that can remember and recall memories from users, providing more contextual answers. It utilizes the Redis Agent Memory Server as a memory layer to provide instant-like ...
github.com
October 1, 2025 at 4:07 PM
If you're interested in understanding how I implemented this demo, here is the GitHub repository:
github.com/redis-develo...
github.com/redis-develo...
Come to the Redis Released event in San Francisco. My friends David Patlut and Sallie Gamboa from the education team at Redis created a great workshop that will be offered to attendees for free. You know what else is free? The registration:
August 19, 2025 at 1:47 PM
Come to the Redis Released event in San Francisco. My friends David Patlut and Sallie Gamboa from the education team at Redis created a great workshop that will be offered to attendees for free. You know what else is free? The registration:
💡 Do you want to learn how to develop these things with Redis?
August 19, 2025 at 1:47 PM
💡 Do you want to learn how to develop these things with Redis?
Another interesting usage of Redis with LLMs is as the memory layer of your agents, so that they can "remember" details from your users within the same thread (a.k.a short-term memory) and between threads (a.k.a long-term memory).
August 19, 2025 at 1:47 PM
Another interesting usage of Redis with LLMs is as the memory layer of your agents, so that they can "remember" details from your users within the same thread (a.k.a short-term memory) and between threads (a.k.a long-term memory).
One way is using semantic caching with Redis. By storing answered LLM calls in memory and using vector embeddings to find semantically similar queries, you can serve cached answers to users really fast, even if their prompt is not precisely the same as the original question.
August 19, 2025 at 1:47 PM
One way is using semantic caching with Redis. By storing answered LLM calls in memory and using vector embeddings to find semantically similar queries, you can serve cached answers to users really fast, even if their prompt is not precisely the same as the original question.
🎤 Great lineup of speakers, including legends of the AI space
⚡️ Get to know what is coming on Redis, the most loved database
⚡️ Get to know what is coming on Redis, the most loved database
August 18, 2025 at 12:15 PM
🎤 Great lineup of speakers, including legends of the AI space
⚡️ Get to know what is coming on Redis, the most loved database
⚡️ Get to know what is coming on Redis, the most loved database