Ivan Yurchenko

I'm hiring Apache #Kafka and Apache #Flink experts (esp. on the ops side) and engineers experienced with Python for the Kafka & Flink team in @aiven_io. Helsinki 🇫🇮, Berlin 🇩🇪 and also remote in some European 🇪🇺 countries. RT please 😉

Also very impressive how quickly this came together. After @MichaelDell got the right people at Dell and Intel engaged, it was just a few weeks before we had solved everything, and could ship the final solution. Founder urgency since 1984 🤘

In celebration of Omarchy 3.5 being the first distro to ship with complete Linux compatibility for the new XPS Panther Lake laptops, @Dell made me a special unit with super + omarchy keys instead of Windows and Copilot. So damn cool!

We're excited to announce the Limited Availability launch of Aiven Apps! Unify your code and data, and deploy stateless applications inside your secure Aiven data perimeter. Stop paying the integration tax and minimize costly egress fees. Learn more and get started today: aiven.io/apps?utm_sourc… #AivenApps #CloudNative #DevOps

llama.cpp at 100k stars now that 90% of the code worldwide is being written by AI agents, I predict that within 3-6 months, 90% of all AI agents will be running locally with llama.cpp 😄 Jokes aside, I am going to use this small milestone as an opportunity to reflect a bit on the project and the state of AI from the perspective of local applications. There is a lot to say and discuss and yet it feels less and less important to try to make a point. Opinions about viability of local LLMs are strongly polarized, details are overlooked, the scientific approach is lacking. Arguments are predominantly based on vibes and hype waves. One thing is clear though - local LLMs are used more and more. I expect this trend to continue and likely 2026 will end up being one of the most important years for the local AI movement. I admit that I didn't expect the agentic era to come so quickly to the local LLM space. One year ago, the available models were too computationally expensive for doing long-context tasks. There wasn't an obvious path towards meaningful agentic applications. The memory and compute requirements were huge. Last summer, with the release of gpt-oss, things started to change. It was the first time we saw a glimpse of tool calling that actually works well within the resource constraints of our daily devices. Later in the year, even better models were released and by now, useful local agentic workflows are a reality. Comparing local vs hosted capabilities at a given moment of time is pointless. To try put things into perspective: - We don't need frontier intelligence to automate searches and sending emails - We don't need trillion parameter models to be able to summarize articles or technical documents - We don't need massive GPU data centers to control our home appliances or turn the lights off in the garage I believe that there is a certain level of intelligence we as humans can comprehend and meaningfully utilize to improve our working process. Beyond that level, access to more intelligence becomes unnecessary at best and counterproductive at worst. I also believe that that level of useful artificial intelligence is completely within reach locally and it has always been just a matter of implementing the right software stack to bring it to the end user. With llama.cpp, I am confident that we continue to be on the right track of building that software stack! The llama.cpp project is going stronger than ever. With more than 1500 contributors, the project keeps growing steadily. From technical point of view, I think that llama.cpp + ggml is the only solution that actually makes sense. That is, the software stack must run efficiently on every possible device, hardware and operating system. The technology is too important to be vendor-locked. It has to be developed in the open, by the community, together with the independent hardware vendors. This is the only right way to build something that will truly make a difference in the long run. I won't try to convince you about what is currently and will be possible with local AI. We will just continue to build as usual. I am confident that after the smoke clears and we look objectively at what we have built together, the benefits will be obvious to everyone. Big shoutout to all llama.cpp maintainers. I feel extremely lucky to be able to work together with so many talented contributors. Every day I learn something new and I feel there is so much more cool stuff that we are going to build. Also, I am really thankful that the project continues to have reliable partners to support it! Cheers!

lmao, @KagiHQ supports text to LinkedIn now

I'm dying. With this translate tool, I'm finally able to effectuate ideation synergies

✨🇨🇳This is the customized parking feature of XPeng Motors from China. You mark where you want to park, and it will automatically park there precisely.

7 years BTW

Bro pulled off the best video of his life

Inkless clusters are ready for Aiven Cloud! This open-source fork of Apache Kafka allows you to run classic and diskless topics side-by-side. Experience up to 10x faster scaling and 90% faster recovery times while maintaining 100% Kafka API compatibility. Learn how to eliminate disk bottlenecks and leverage KIP-1150 here: aiven.io/blog/announcin…

@nicebadger Думкодинг

🤔

Today ggml.ai joins Hugging Face Together we will continue to build ggml, make llama.cpp more accessible and empower the open-source community. Our joint mission is to make local AI easy and efficient to use by everyone on their own hardware.

Uh, changed my mind…

Next version of Omarchy will color coordinate the Asus ROG RGB keyboard backlighting with your chosen theme.

This is cool, but the agentic part is even cooler

To the stars! @SpaceX & @xAI are now one company

I've been doing open source since I was a teenager (over 20yrs). And for the first time ever, I'm considering closing external PRs to my OSS projects completely. This will throw the baby out with the bathwater and I hate that, but we close auto-opened slop PRs every single day.

Native lock profiling, latency filter, stronger crash protection, and more in async-profiler 4.3: github.com/async-profiler…

@philipto @dim1boi @badgercat Думаю, большинство по инерции продолжают платить. (Я так-то с Evernote сбежал, конечно)

@dim1boi @badgercat а что это за модель у Bending Spoons - скупать более-менее живые бизнесы с большим количеством пользователей, увольнять команду, и безнадежно портить сервисы? В какой момент они на этом зарабатывают? Что-то типа схемы гл.героя "9,5 недель"?