https://raphaeldelio.com | https://youtube.com/raphaeldelio | https://linktr.ee/raphaeldelio
Come and share any awesome work you’ve done with @kotlinlang.org! Good luck 👍
sessionize.com/kotlinconf-2...
Come and share any awesome work you’ve done with @kotlinlang.org! Good luck 👍
sessionize.com/kotlinconf-2...
One virtually with Camille Nigon from Red Hat and the second one at the Kotlin MeetUp in Eindhoven!
At both I'll talk about how Redis can help your agentic applications save on time and cost using vector search.
Don't forget to RSVP! #java #kotlin
Link: www.arcofai.com/cfp
Submission deadline: Dec 20, 2025
Speaker Notification: Jan 10, 2026
Conference dates: Apr 13-16, 2026
Looking forward to your submissions and/or participation at the conf.
Link: www.arcofai.com/cfp
Submission deadline: Dec 20, 2025
Speaker Notification: Jan 10, 2026
Conference dates: Apr 13-16, 2026
Looking forward to your submissions and/or participation at the conf.
🔧 Better MCP Integration ... 🔐MCP OAuth2 server protection 🔄 Recursive Advisors ...📦 Developer Experience: ... Over 850+ commits
Kudos to the entire Spring AI community! 🙌
Find more: spring.io/blog/2025/11...
@spring-ai.bsky.social
🔧 Better MCP Integration ... 🔐MCP OAuth2 server protection 🔄 Recursive Advisors ...📦 Developer Experience: ... Over 850+ commits
Kudos to the entire Spring AI community! 🙌
Find more: spring.io/blog/2025/11...
@spring-ai.bsky.social
Evaluating LLM output is challenging. Traditional metrics fall short, and human evaluation doesn't scale.
LLM-as-a-Judge uses LLMs to evaluate AI-generated content, matching human judgment
📖 spring.io/blog/2025/11...
🛠️ github.com/spring-proje...
Evaluating LLM output is challenging. Traditional metrics fall short, and human evaluation doesn't scale.
LLM-as-a-Judge uses LLMs to evaluate AI-generated content, matching human judgment
📖 spring.io/blog/2025/11...
🛠️ github.com/spring-proje...
I delivered a talk at JFall yesterday about three strategies that can be implemented with vector DBs to reduce LLM calls. But the truth is that there are many more! #java
github.com/redis-develo...
I delivered a talk at JFall yesterday about three strategies that can be implemented with vector DBs to reduce LLM calls. But the truth is that there are many more! #java
github.com/redis-develo...
I was listening to Anthropic's recent video "How AI Models Think" based on their research on interpretability and found a few insights very interesting. One for example is that there's evidence that LLMs can do simple math (addition).
I was listening to Anthropic's recent video "How AI Models Think" based on their research on interpretability and found a few insights very interesting. One for example is that there's evidence that LLMs can do simple math (addition).
That's the message I got when running "FLUSHALL" on my production Redis instance. 😮💨
My team and I developed an internal platform for us to track our work. The chosen database? Redis, of course.
#redis @redis.io
If you're in London, please join me at the London Java Community (LJC) meet up on Monday August 18th: www.eventbrite.co.uk/e/ljc-meet-u...
If you're in London, please join me at the London Java Community (LJC) meet up on Monday August 18th: www.eventbrite.co.uk/e/ljc-meet-u...
ProRLv2: Expanding LLM reasoning boundaries through 3,000+ RL steps across five domains, setting a new state-of-the-art among 1.5B reasoning models.
ProRLv2: Expanding LLM reasoning boundaries through 3,000+ RL steps across five domains, setting a new state-of-the-art among 1.5B reasoning models.
My biggest problem is that it moves too fast. Sure, it eventually gets to the result I want, but it’s hard to follow the design choices along the way. That makes it way too easy to end up with messy, hard-to-maintain code
My biggest problem is that it moves too fast. Sure, it eventually gets to the result I want, but it’s hard to follow the design choices along the way. That makes it way too easy to end up with messy, hard-to-maintain code
In particular, it ships the new TrieMap implementation I wrote with Henk Oordt, as part of @mainmatter.com's ongoing collaboration with Redis.
In particular, it ships the new TrieMap implementation I wrote with Henk Oordt, as part of @mainmatter.com's ongoing collaboration with Redis.
It’s still the GPT-Image-1 model released in April of this year that is generating the images.
It’s still the GPT-Image-1 model released in April of this year that is generating the images.
Great example of the unreasonable effectiveness of simple algorithms leveraging the human intelligence innate to an app with a follow graph and likes.
Conclusive proof you don't need a team of ML engineers and custom models to make a highly engaging algorithm.
It finds people who liked the same posts as you, and shows you what else they've liked recently.
📌 Pin to add it to your top bar
❤️ Like the feed and repost to spread the goodness
Great example of the unreasonable effectiveness of simple algorithms leveraging the human intelligence innate to an app with a follow graph and likes.
Conclusive proof you don't need a team of ML engineers and custom models to make a highly engaging algorithm.