Saying that a vector database reaches a given recall percentage is more marketing than anything, HNSWs are more complicated than that. Let's explore why in this video. www.youtube.com/watch?v=LG3q...

Finally YouTube is going to improve the dubbing feature with lipsync and potentially (looking at this example video) voice matching. That's great in general, and I'm very happy for my YouTube channel that can be better experienced by english speakers. www.youtube.com/watch?v=8W3n...

Who are the designers of the new iPhone UI? Would love to hire them in order to create the hardest escape room in the world.

VRANGE was merged into Redis unstable and will be likely back-ported. It allows to get lex ranges of elements in vector sets, which is useful as iterator and for other tasks.

It's a few days that I'm writing a blog post on HNSWs. As usually, writing about a subject raises new questions, that trigger new searches, and in the goal of explaining what you understood, you understand more. Blogging may no longer be cool but surely remains useful.

New EN video: Inspecting LLM embeddings in GGUF format with gguflib.c and Redis www.youtube.com/watch?v=ugba...

ADV: my C course on YouTube is free and can be watched without problems with subtitles or dubbed audio by non Italian speakers :)

We should likely put a large LLM weights and the explanation of how to do inference in some hard-to-degradate material, inside N bunkers in different parts of the world. So that humans are more likely to be able to restart civilization in case of fatal events.

At this stage AI will provide a huge boost to balanced people that don't jump in any extreme hype / anti-hype train, and will create issues to the folks that don't see that judicious application of LLMs is the key. One of those historical moments when wisdom is an advantage.

Playing with adding LLMs embeddings into Redis vector sets, to explore relationships and differences with embedding words models like Word2Vec. Will make a YouTube video and/or blog post.

Why the "declare AI help in your PR" is useless, courtesy of 3000 years ago logic: - If you can't tell without the disclaimer, it's useless: people will not tell. - If you can tell, it's useless: you can tell. Just evaluate quality, not process.

When you use coding agents for something that produces the bulk of the code of an application that will be used for years, also factor in the technical debt that you are happily accumulating. When you use LLMs an an aid, you could, on the contrary, improve your coding culture.

New blog post: AI is different. antirez.com/news/155

GPT-5 seems good at code reviews. The first model from OpenAI in a *long* time I'll likely start using constantly for such an activity, together with the others.

LLM evaluation: only trust people with hard problems. Today models perform decently on most trivial task: this is a win of the technology, but also means that evaluation is more and more a realm of sprcislists.

Prediction: the OpenAI release for GPT OSS 120/20 will weaken the position of US AI OSS in comparison to the Chinese movement and results. And this is happening after the Llama4 fiasco: multiplicative effects.

It's a real shame there are no LLM benchmarks on hallucinating creativity, since GPT OSS 120b is wild in what it invents out of thin air, and would score really high on such a benchmark.

It is possible to do C programming safely. You just need the right gear

This AWS European Sovereign Cloud just does not make much sense, for an Europe POV. Why to pay AWS to run a cloud in Europe? Running software in part written by europeans like Linux, MySQL, Python and many others? If you are from Europe consider buying services from EU companies

My YouTube channel reached 25k subscribers. 5k watch it from outside Italy, with subtitles / dubbed audio, regardless of the fact 80% of the videos are in Italian (soon or later I'll explain the why of this choice). I'm happy about this: YouTube is becoming a cultural media.

I just posted this on Linked In, but @codinghorror.bsky.social talked about this many times. In 2025, it is still so relevant. In fact @antirez.bsky.social live solved this in his YouTube channel. The question remains: why so many developers cannot write code?

In recent years, in applied computer science there is this phenomenon that repeats itself slowly ruining everything we have: 1. Many years ago a well designed system was created: simplicity and orthogonality of ideas are often part of the system. Such system is well understood.

[new Youtube video] Writing Redis VRANGE using AI: how I prepare the context, and how the human in the loop is crucial to obtain good results: www.youtube.com/watch?v=3Z7T...

In order to implement the Redis Vector Sets VRANGE, I used AI to show better my point about the latest blog post and why vibe coding is *not* the way. Soon I'll release a video in my YouTube channel (in English) to see how Claude and Gemini perform and how the human is the key.

Blog post: Coding with LLMs in the summer of 2025 (an update) antirez.com/news/154

Just published a new video about Vector Sets: how is VRANDMEMBER implemented? What is its distribution? And how do you extract a random element out of an HNSW graph? www.youtube.com/watch?v=Xreg...

For my YouTube C course weeks ago I created an intro with some music. People liked it and asked what song it was so yesterday night I turned it into a full song: youtu.be/HzBqda0Jg3E?...

I just want to tell everybody that I don't care what price BTC will reach. For me it's a 🤡 level speculation and I will never invest into it.

Do you like Daft Punk? I do. Many years before, in 1979, a few Italian composers created what later inspired many later musicians: the Rondò Veneziano. en.wikipedia.org/wiki/Rond%C3... www.youtube.com/watch?v=Y4Fr...

People attribute to Cursor / Windsurf (and its failed deal) a lot of weight but these technologies are worth zero in the big story of AI. The LLM is what matters, or better: the fact that massive NNs with relatively simple layouts generalize so well with SUL.

Quite happy with vector sets VRANDMEMBER distribution. HNSWs help a lot, with their structure.

Don't ask me why sometimes I need to reach such a point.

A repository with two of the very early Redis versions and some email digging to reconstruct the very first days history: github.com/antirez/hist...

If you are interested to use the new Redis Vector Sets, I just uploaded a YouTube video with the first introduction. More will follow, to progressive details up to the implementation level: www.youtube.com/watch?v=kVAp...

Preparing the YouTube video series on Redis Vector Sets I just discovered a fancy mxbai-large embedding model "issue". It over-expresses a specific component in every output I tested. This may be some very generic/ubiquitous feature the model needed to model based on training.

About the recent XOR article in Hacker News.

Profiling is always an eyes-opening activity.

P.S. with "prompt caching" I didn't mean KV caching, I wanted to refer to the practice of caching the answers associated to the embedding of the question, and then providing it as it is to some user that asked a similare question. "Answer caching" may be a better terminology that does not collide

Prompt caching is ruining LLMs. Now Gemini does it even in the middle of the chat if the question looks generic and is cached, even if it is quite obviously related to the previous context.

LLMs peek performance: having to review shitty code written by somebody else, something that was always horrific to do for the (almost) active effort in such code to hide how things work / complicate stuff. Poo for the mind. Now LLMs can do it for us \o/

About the recente Apple paper: many of us believe CoT is a form of sampling/search in the representations the model possesses: this allows to "ground" the reply with a large context of related ideas/info. No surprise that the Tower of Hanoi is a problem where sampling does not help.

Been thinking of revisiting C just to get a change of pace / for fun. It's been a long time. @antirez.bsky.social (Redis author) just started doing C lessons: www.youtube.com/watch?v=HjXB... Watched 1st video & it's kinda a deep dive of an intro (e.g. showing asm output), which is perfect for me

I'm sorry to inform you and your optimism on coding agents that our technology is based on things like the Linux kernel, or a modern browser: completely outside of today's possibilities. When you analyze AI, think at the Linux kernel.

Are you from Malta? My uncle moved there years ago and now he is reinvented himself restoring wood doors, windows, and so forth. If you need his services please drop me a DM or an email and I'll reply with his phone number.

One of the most embarrassing things in today software: I have the same folder with thousands of .crt games in my Commodore 64 Kung-Fu II card and in my MacOS M3 Max computer. The former opens the directory faster than the latter.

Prompt caching is affecting LLM user experience in a severe way. A few weeks of this issue with Gemini regurgitating instantaneously a reply slightly related to my question.

Human coders are still better than LLMs: antirez.com/news/153

Every time you use BambuStudio, PrusaSlicer, OrcaSlicer, and the other evolutions of Slic3r, remember that all started with the italian Alessandro Ranellucci doing all the initial work needed: teamdigitale.governo.it/it/people/al...

I'm seeing that many of the best use cases Redis users are applying vector sets to, are not related to learned embeddings. For instance, I have a friend that is doing a huge scale molecular search application, and they encode the molecule representation directly.

I understand that in Germany / Austria those waters are very popular. I tried to understand what's the point but then realized it and I'm providing with an improved version here. From a discussion with my brother living in Vienna.