AI Breakthroughs and Security: OpenAI’s New Chip, Microsoft Play Store Changes

Blog All Posts News Performance Networking Tips Privacy AI We’re making Bunny DNS free: because a faster internet won’t build itself Posted by: Dejan Grofelnik Pelzel Joe Connolly June 24, 2026 At bunny.net, our mission has always been ambitious but focused: help make the internet hop faster.

To do that, we’ve built a massive global network spanning 119 locations and counting. Today, this network powers over 1.5 million websites and consistently delivers some of the fastest content delivery around the globe. But while deploying thousands of servers globally is an impressive feat on its own, the hardware itself does not explain how bunny.net is able to deliver such an impressive level of performance.

The real secret hides under the hood, embedded in the routing engine that directs every request, every user, and sends traffic exactly where it needs to go. That engine is Bunny DNS.

Originally, Bunny DNS was built with one simple goal: to build the most advanced routing engine possible, capable of analyzing every DNS query and directing it to the optimal destination for serving your content. Even to this day, it’s what makes Bunny CDN achieve it’s exceptional performance.

Four years ago, we took everything we had learned from designing and running this system and turned it into a product our users could use themselves. With Bunny DNS, we’ve upgraded DNS from being a basic record lookup table into a globally distributed, smart routing engine.

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On Wednesday, OpenAI unveiled its first custom-built inference processor, designed and manufactured in collaboration with Broadcom. Named Jalapeño, the new processor was designed specifically for the unique needs of OpenAI’s inference systems. OpenAI’s own AI models assisted in the development of the chip, the company said.

While the chip is still being tested, OpenAI says early results show significantly better performance-per-watt than current state-of-the-art alternatives.

The partnership was officially announced in October , but OpenAI’s chip plans have long been rumored as a way to reduce the company’s dependence on Nvidia’s GPUs. Google and Amazon have both built custom chips to serve a similar purpose, often called “AI accelerators” — silicon designed specifically to speed up machine learning workloads.

RubyLLM is a new framework that allows developers to easily integrate and utilize APIs from major AI providers in their Ruby projects.

With this tool, integrating cutting-edge AI capabilities into applications becomes more straightforward and accessible.

Release page Official website Hugging Face Weights & license GitHub Code & license Try it now via Krea Image tool The model weights and inference are released under a permissive license .

To address these limitations, we present Krea 2 , a series of foundation models focused on creative exploration. Krea 2’s models are built on the belief that image generation should be an exploratory medium: expressive enough to span many aesthetics, and controllable enough for creators to navigate them.

We built a large-scale data infrastructure and distributed training framework from scratch to curate a comprehensive pretraining dataset with broad world knowledge and style coverage.

A strong base model is only useful if users can reliably reach the parts of its distribution they care about. In training, the model learns from rich, carefully constructed captions that describe images with dense visual detail. In practice, user inputs are often shorter, more ambiguous, and shaped by many different habits of expression.

Together, these components define Krea 2 as a foundation model for exploratory generation. Instead of optimizing only for a single polished default, Krea 2 is designed to expose a broad visual space and give users practical ways to move through it, using both text and image-based control.

Google is making good on its commitment to lower fees for app developers by introducing changes to the Play Store.

Developers can now use alternative billing systems, reducing transaction costs and providing more competitive pricing options.