fidzu : mobile

Now that 2025 is over, it's time to look back and feel proud of the path we've walked. Last year has been really exciting in terms of contributions to GStreamer and WebKit for the Igalia Multimedia team.

With more than 459 contributions along the year, we've been one of the top contributors to the GStreamer project, in areas like Vulkan Video, GstValidate, VA, GStreamer Editing Services, WebRTC or H.266 support.

In Vulkan Video we've worked on the VP9 video decoder, and cooperated with other contributors to push the AV1 decoder as well. There's now an H.264 base class for video encoding that is designed to support general hardware-accelerated processing.

GStreaming Editing Services, the framework to build video editing applications, has gained time remapping support, which now allows to include fast/slow motion effects in the videos. Video transformations (scaling, cropping, rounded corners, etc) are now hardware-accelerated thanks to the addition of new Skia-based GStreamer elements and integration with OpenGL. Buffer pool tuning and pipeline improvements have helped to optimize memory usage and performance, enabling the edition of 4K video at 60 frames per second. Much of this work to improve and ensure quality in GStreamer Editing Services has also brought improvements in the GstValidate testing framework, which will be useful for other parts of GStreamer.

Regarding H.266 (VVC), full playback support (with decoders such as vvdec and avdec_h266, demuxers and muxers for Matroska, MP4 and TS, and parsers for the vvc1 and vvi1 formats) is now available in GStreamer 1.26 thanks to Igalia's work. This allows user applications such as the WebKitGTK web browser to leverage the hardware accelerated decoding provided by VAAPI to play H.266 video using GStreamer.

Igalia has also been one of the top contributors to GStreamer Rust, with 43 contributions. Most of the commits there have been related to Vulkan Video.

In addition to GStreamer, the team also has a strong presence in WebKit, where we leverage our GStreamer knowledge to implement many features of the web engine related to multimedia. We've made 323 multimedia contributions to WebKit last year. Nearly one third of them have been related to generic multimedia playback, and the rest have been on areas such as WebRTC, MediaStream, MSE, WebAudio, a new Quirks system to provide adaptations for specific hardware multimedia platforms at runtime, WebCodecs or MediaRecorder.

We're happy about what we've achieved along the year and look forward to maintaining this success and bringing even more exciting features and contributions in 2026.

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26 Jan 2026 9:34am GMT

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25 Jan 2026 4:30pm GMT

Posted by Georgia Doyle, Senior UX Writer and Content Designer, and Kanu Tibrewal, Software Engineer

How it works

In the 'Changes not yet sent for review' section of the Publishing overview page, select 'Save for later' on the groups of changes that you don't want to include in your next review. You can view and edit the list of saved changes, and return them to the Publishing overview if you change your mind. Once the review has started, your saved changes will be added back to 'Changes not yet sent for review'.

Integration with our pre-review checks

• If issues are isolated to an individual track, we'll show you an error beside that change, so you know what to save for later in order to proceed to review with your other changes.
• If you have issues that affect your whole app, for example, App content issues, Save for later will be unavailable and you will need to fix them before you can send any changes for review.

Greater flexibility in your workflows

Our goal for Save for later is to give you greater flexibility over your release schedule. With this feature you can manage what changes you send for review, and address issues affecting individual tracks without holding up ready-to-release changes, so you can iterate faster and minimize the impact of rejections on your release timeline.

21 Jan 2026 5:00pm GMT

Posted by Sandhya Mohan, Senior Product Manager and Trevor Johns, Developer Relations Engineer

We are excited to announce that Android Studio Otter 3 Feature Drop is now stable! This feature-packed release brings a huge update to your agentic workflows in Android Studio, and offers you more flexibility and control for how you use AI to help you build Android apps.

• Bring Your Own Model: You can now use any LLM to power the AI functionality in Android Studio.
• Agent Mode Enhancements: You can now more easily have Agent Mode interact with your app on devices, review and accept suggested changes, and have multiple conversations threads.
• Run user journey tests using natural language: with Journeys in Android Studio.
• Enable Agent Mode to connect to more tools: including the ability to connect to remote servers via MCP.
• Build, iterate and test your UI: with UI agentic experiences in Android Studio.
• Build deep links using natural language: with the new app links assistant.
• Debug R8 optimized code: with Automatic Logcat retracing.
• Simplify Android library modules: with the Fused library plugin.

Here's a deep dive into what's new:

Bring Your Own Model (BYOM)

Every developer has a unique workflow when using AI, and different companies have different policies on AI model usage. With this release, Android Studio now brings you more flexibility by allowing you to choose the LLM that powers the AI functionality in Android Studio, giving you more control over performance, privacy, and cost.

Use a remote model

You can now integrate remote models-such as OpenAI's GPT, Anthropic's Claude, or a similar model-directly into Android Studio. This allows you to leverage your preferred model provider without changing your IDE. To get started, configure a remote model provider in Settings by adding your API endpoint and key. Once configured, you can select your custom model directly from the picker in the AI chat window.

Enter the remote model provider information.

Use a local model

If you have limited internet connectivity, strict data privacy requirements, or a desire to experiment with open-source research, Android Studio now supports local models via providers like LM Studio or Ollama. While Gemini in Android Studio remains the default recommendation-tuned specifically for Android development with full context awareness-if you have a specific model preference, Android Studio supports it.

Model picker in Android Studio.

A local model offers an alternative to the LLM support built into Android Studio, and typically requires significant local system RAM and hard drive space to run well. However, Gemini in Android Studio provides the best Android development experience because Gemini is tuned for Android and supports all features of Android Studio. With Gemini, you can choose from a variety of models for your Android development tasks, including the no-cost default model or models accessed with a paid Gemini API key.

Use your Gemini API key

While Android Studio includes access to a default Gemini model with generous quotas at no cost, some developers need more. By adding your Gemini API key, Android Studio can directly access all the latest Gemini models available from Google.

For example, this allows you to use the most recent Gemini 3 Pro and Gemini 3 Flash models (among others) with expanded context windows and quota. This is especially useful for developers who are using Agent Mode for extended coding sessions, where this additional processing power can provide higher fidelity responses.

You can also read more about how we're rolling out Gemini 3 to all Android Studio users, including Gemini Code Assist subscribers and developers accessing the default Gemini in Android Studio model at no-cost.

Agent Mode enhancements

Agent Mode is the semi-autonomous AI assistant in Android Studio that aids in your software development, used by many developers, including the Ultrahuman team. Get more out of Agent Mode with these new updates.

Run your app and interact with it on devices

Agent Mode can now deploy an application to the connected device, inspect what is currently shown on the screen, take screenshots, check Logcat for errors, and interact with the running application. This lets the agent help you with changes or fixes that involve re-running the application, checking for errors, and verifying that a particular update was made successfully (for example, by taking and reviewing screenshots).

Agent mode uses device actions to deploy and verify changes.

Find and review changes using the changes drawer

You can now see and manage all changes made by the AI agent using the changes drawer. When the agent makes changes to your codebase, you can see the files that were edited in Files to review. From there, you can keep or revert the changes individually or all together. Click an individual file in the drawer to see the code diff in the editor and make refinements if needed. With the changes drawer, you can keep track of edits made by the agent during your chat and revisit specific changes without scrolling back through your conversation history.

See all the files that the agent has proposed edits to in the changes drawer.

Note: If the Don't ask to edit files setting is disabled in Agent Options , Agent Mode will request permission for every individual change. Each change must be accepted before it appears in the changes drawer. To allow multiple file edits to appear in the drawer simultaneously, enable the Don't ask to edit files option.

Accept a change to add it to the changes drawer.

Manage multiple conversation threads

You can now organize your conversations with Gemini in Android Studio into multiple threads. This lets you create a new chat or agent thread when you need to start with a clean slate, and you can go back to older conversations in the history tab. Using separate threads for each distinct task can improve response quality by limiting the scope of the AI's context to only the topic at hand.

To start a new thread, click New Conversation . To see your conversation history, click Recent Chats.

See prior conversations in the "Recent Chats" tab.

Your conversation history is saved to your account, so if you have to sign out or switch accounts you can resume right where you left off when you come back.

Journeys for Android Studio

Running end-to-end UI tests can improve confidence that you're shipping a high-quality app to production, but writing and maintaining those tests can be difficult, brittle, and limited in what you're able to test. Journeys for Android Studio leverages the reasoning and vision capabilities of Gemini to enable you to write and maintain end-to-end UI tests using natural language instructions-and it's now available in the latest stable release of Android Studio when you enable it from Studio Labs in your Android Studio Settings.

Journeys for Android Studio.

These natural language instructions are converted into interactions that Gemini performs directly on your app. This not only makes your tests easier to write and understand, but also enables you to define complex assertions that Gemini evaluates based on what it "sees" on the device screen. Because Gemini reasons about how to achieve your goals, these tests are more resilient to subtle changes in your app's layout, significantly reducing flaky tests when running against different app versions or device configurations.

Journeys for Android Studio.

You can write and run journeys directly from Android Studio against any local or remote device. The IDE provides a new editor experience for crafting your test steps in an XML file, using either a code view or a dedicated design view. When you run a journey, Android Studio provides rich, detailed results that help you follow Gemini's execution. The test panel breaks down the entire journey into its discrete steps, showing you screenshots for each action, what action was taken, and Gemini's reasoning for why it took that action, making debugging and validation clearer than ever. And because journeys are run as Gradle tasks, you can run them from the command line after you authenticate with a Google Cloud Project.

Support for remote MCP servers

Android Studio now lets you connect directly to remote Model Context Protocol (MCP) servers such as Figma, Notion, Canva, Linear, and more. This significantly reduces your context switching since it enables the AI agent in Android Studio to leverage external tools, helping you stay in your flow. For example, you can connect to Figma's remote MCP server to access files and provide this information to Agent Mode, generating more accurate code from your designs. To learn more about how to add an MCP server, see Add an MCP server.

Connect to the Figma remote MCP server in Android Studio Settings.

Quickly add a screen to your app using the Figma remote MCP server.

Supercharge your UI development with Agent Mode

Gemini in Android Studio is now integrated into the UI development workflow directly from within the Compose Preview panel, helping you go from design to a high-quality implementation faster. These new agentic capabilities are designed to assist you at every stage of development, from initial code generation to iteration, refinement, and debugging, with entry points in the context of your work.

Create new UI from a design mock

Accelerate your initial UI implementation by generating Compose code directly from a design mock. Simply click Generate Code From Screenshot in an empty Preview panel, and Gemini will use the image to generate a starting implementation, saving you from writing boilerplate from scratch.

Generate code from a screenshot in an empty Preview panel.

Example turning design into Compose code.

Match your UI with a target image

Once you have an initial implementation, you can iteratively refine it to be pixel-perfect. Right-click your Compose Preview and select AI Actions > Match UI to Target Image. Upload a reference design, and the agent will suggest code changes to make your UI match the design as closely as possible.

Example of using "Match UI to Target Image"

Iterate on your UI with natural language

For more specific or creative changes, right-click on your preview and use the AI Actions > Change UI. This capability now leverages Agent Mode to validate the results, making it more powerful and accurate. You can use natural language prompts like "change the button color to blue" or "add padding around this text," and Gemini will apply the code modifications instantly.

Example of using "Change UI"

Find and fix UI quality issues

Verifying your UI is high-quality and more accessible is a critical final step. The AI Actions > Fix all UI check tool audits your UI for common problems, such as accessibility issues. The agent will then propose and apply fixes to resolve the detected issues.

Entry point to trigger "Fix all UI check issues"

You can also find the same functionality by using the Fix with AI button in Compose UI check mode:

"Fix with AI" in UI Check mode

The features mentioned above are also accessible by the toolbar icon in the Preview panel:

Second entry point to UI development AI features

Beyond iterating on your UI, Gemini also helps streamline your development environment.

To accelerate your setup, you can:

• Generate Compose Previews: This feature is now enhanced by Agent Mode to provide more accurate results. When working in a file that has Composable functions but no @Preview annotations, you can right-click on the Composable and select Gemini > Generate [Composable name] Preview. The agent will now better analyze your Composable to generate the necessary boilerplate with correct parameters, to help verify that a successfully rendered preview is added.

Entry point to generate Compose Preview

• Fix Preview rendering errors: When a Compose Preview fails to render, Gemini can now analyze the error message and your code to find the root cause and apply a fix.

Using "Fix with AI" on Preview render error

App Links Assistant

The App Links Assistant now integrates with Agent Mode to automate the creation of deep link logic, simplifying one of the most time-consuming steps of implementation. Instead of manually writing code to parse incoming intents and navigate users to the correct screen, you can now let Gemini generate the necessary code and tests. Gemini presents a diff view of the suggested code changes for your review and approval, streamlining the process of handling deep links and ensuring users are seamlessly directed to the right content in your app.

To get started, open the App Links Assistant through the tools menu, then choose Create Applink. In the second step, Add logic to handle the intent, select Generate code with AI assistance. If a sample URL is available, enter it, and then click Insert Code.

App Links Assistant

Automatic Logcat Retracing

Debugging R8-optimized code just became seamless. Previously, when R8 was enabled (minifyEnabled = true in your build.gradle.kts file), it would obfuscate stack traces, changing class names, methods, and line numbers. To find the source of a crash, developers had to manually use the R8 retrace command line tool.

Starting with Android Studio Otter 3 Feature Drop with AGP versions 8.12 and above, this extra step is no longer necessary. Logcat now automatically detects and retraces R8-processed stack traces, so you can see the original, human-readable stack trace directly in the IDE. This provides a much-improved debugging experience with no extra work required.

Logcat now automatically detects and retraces R8-processed stack traces

Fused Library Plugin: Publish multiple Android libraries as one

The new Fused Library plugin bundled with Android Gradle Plugin 9.0 allows you to package multiple Android library modules into a single, publishable Android Library (AAR). This was one of the most requested features for Android Gradle Plugin, and we are making it available for you today. This plugin enables you to modularize your code and resources internally while simplifying the integration process for your users by exposing only a single dependency. In addition to streamlining project setup and version management, distributing a fused library can help reduce library size through improved code shrinking and offer better control over your internal implementation details. To learn more about the Fused Library plugin see Publish multiple Android libraries as one with Fused Library.

Get started

Ready to dive in and accelerate your development? Download Android Studio Otter 3 Feature Drop and start exploring these powerful new features today!

As always, your feedback is crucial to us. Check known issues, report bugs, and be part of our vibrant community on LinkedIn, Medium, YouTube, or X. Let's build the future of Android apps together!

15 Jan 2026 5:18pm GMT

Posted by Amrit Sanjeev, Developer Relations Engineer and Trevor Johns, Developer Relations Engineer

Ultrahuman is a consumer health-tech startup that provides daily well-being insights to users based on biometric data from the company's wearables, like the RING Air and the M1 Live Continuous Glucose Monitor (CGM). The Ultrahuman team leaned on Gemini in Android Studio's contextually aware tools to streamline and accelerate their development process.

Ultrahuman's app is maintained by a lean team of just eight developers. They prioritize building features that their users love, and have a backlog of bugs and needed performance improvements that take a lot of time. The team needed to scale up their output of feature improvements, and also needed to handle their performance improvements, without increasing headcount. One of their biggest opportunities was reducing the amount of time and effort for their backlog: every hour saved on maintenance could be reinvested into working on features for their users.

Solving technical hurdles and boosting performance with Gemini

The team integrated Gemini in Android Studio to see if the AI enhanced tools could improve their workflow by handling many Android tasks. First, the team turned to the Gemini chat inside Android Studio. The goal was to prototype a GATT Server implementation for their application's Bluetooth Low Energy (BLE) connectivity.

As Ultrahuman's Android Development Lead, Arka, noted, "Gemini helped us reach a working prototype in under an hour-something that would have otherwise taken us several hours." The BLE implementation provided by Gemini worked perfectly for syncing large amounts of health sensor data while the app ran in the background, improving the data syncing process and saving battery life on both the user's Android phone and Ultrahuman's paired wearable device.

Beyond this core challenge, Gemini also proved invaluable for finding algorithmic optimizations in a custom open-source library, pointing to helpful documentation, assisting with code commenting, and analyzing crash logs. The Ultrahuman team also used code completion to help them breeze through writing otherwise repetitive code, Jetpack Compose Preview Generation to enable rapid iteration during UI design, and Agent Mode for managing complex, project-wide changes, such as rendering a new stacked bar graph that mapped to backend data models and UI models.

Transforming productivity and accelerating feature delivery

These improvements have saved the team dozens of hours each week. This reclaimed time is being used to deliver new features to Ultrahuman's beta users 10-15% faster. For example, the team built a new in-app AI assistant for users, powered by Gemini 2.5 Flash. The UI design, architecture, and parts of the user experience for this new feature were initially suggested by Gemini in Android Studio-showcasing a full-circle AI-assisted development process.

Accelerate your Android development with Gemini

Gemini's expert Android advice, closely integrated throughout Android Studio, helps Android developers spend less time digging through documentation and writing boilerplate code-freeing up more time to innovate.

Learn how Gemini in Android Studio can help your team resolve complex issues, streamline workflows, and ship new features faster.

08 Jan 2026 10:00pm GMT

Some years ago I had mentioned some command line tools I used to analyze and find useful information on GStreamer logs. I've been using them consistently along all these years, but some weeks ago I thought about unifying them in a single tool that could provide more flexibility in the mid term, and also as an excuse to unrust my Rust knowledge a bit. That's how I wrote Meow, a tool to make cat speak (that is, to provide meaningful information).

The idea is that you can cat a file through meow and apply the filters, like this:

cat /tmp/log.txt | meow appsinknewsample n:V0 n:video ht: \
ft:-0:00:21.466607596 's:#([A-za-z][A-Za-z]*/)*#'

which means "select those lines that contain appsinknewsample (with case insensitive matching), but don't contain V0 nor video (that is, by exclusion, only that contain audio, probably because we've analyzed both and realized that we should focus on audio for our specific problem), highlight the different thread ids, only show those lines with timestamp lower than 21.46 sec, and change strings like Source/WebCore/platform/graphics/gstreamer/mse/AppendPipeline.cpp to become just AppendPipeline.cpp", to get an output as shown in this terminal screenshot:

Cool, isn't it? After all, I'm convinced that the answer to any GStreamer bug is always hidden in the logs (or will be, as soon as I add "just a couple of log lines more, bro" 0 0

05 Dec 2025 11:16am GMT

• Release announcement on itch.io

1 0

15 Oct 2025 11:31am GMT

I've mentioned some of my various retronetworking projects in some past blog posts. One of those projects is Osmocom Community TDM over IP (OCTOI). During the past 5 or so months, we have been using a number of GPS-synchronized open source icE1usb interconnected by a new, efficient but strill transparent TDMoIP protocol in order to run a distributed TDM/PDH network. This network is currently only used to provide ISDN services to retronetworking enthusiasts, but other uses like frame relay have also been validated.

So far, the central hub of this OCTOI network has been operating in the basement of my home, behind a consumer-grade DOCSIS cable modem connection. Given that TDMoIP is relatively sensitive to packet loss, this has been sub-optimal.

Luckily some of my old friends at noris.net have agreed to host a new OCTOI hub free of charge in one of their ultra-reliable co-location data centres. I'm already hosting some other machines there for 20+ years, and noris.net is a good fit given that they were - in their early days as an ISP - the driving force in the early 90s behind one of the Linux kernel ISDN stracks called u-isdn. So after many decades, ISDN returns to them in a very different way.

Side note: In case you're curious, a reconstructed partial release history of the u-isdn code can be found on gitea.osmocom.org

But I digress. So today, there was the installation of this new OCTOI hub setup. It has been prepared for several weeks in advance, and the hub contains two circuit boards designed entirely only for this use case. The most difficult challenge was the fact that this data centre has no existing GPS RF distribution, and the roof is ~ 100m of CAT5 cable (no fiber!) away from the roof. So we faced the challenge of passing the 1PPS (1 pulse per second) signal reliably through several steps of lightning/over-voltage protection into the icE1usb whose internal GPS-DO serves as a grandmaster clock for the TDM network.

The equipment deployed in this installation currently contains:

• a rather beefy Supermicro 2U server with EPYC 7113P CPU and 4x PCIe, two of which are populated with Digium TE820 cards resulting in a total of 16 E1 ports

• an icE1usb with RS422 interface board connected via 100m RS422 to an Ericsson GPS03 receiver. There's two layers of of over-voltage protection on the RS422 (each with gas discharge tubes and TVS) and two stages of over-voltage protection in the coaxial cable between antenna and GPS receiver.

• a Livingston Portmaster3 RAS server

• a Cisco AS5400 RAS server

For more details, see this wiki page and this ticket

Now that the physical deployment has been made, the next steps will be to migrate all the TDMoIP links from the existing user base over to the new hub. We hope the reliability and performance will be much better than behind DOCSIS.

In any case, this new setup for sure has a lot of capacity to connect many more more users to this network. At this point we can still only offer E1 PRI interfaces. I expect that at some point during the coming winter the project for remote TDMoIP BRI (S/T, S0-Bus) connectivity will become available.

18 Sep 2022 10:00pm GMT

Almost one year after my post regarding first steps towards a V5 implementation, some friends and I were finally able to visit Wobcom, a small German city carrier and pick up a lot of decommissioned POTS/ISDN/PDH/SDH equipment, primarily V5 access networks.

This means that a number of retronetworking enthusiasts now have a chance to play with Siemens Fastlink, Nokia EKSOS and DeTeWe ALIAN access networks/multiplexers.

My primary interest is in Nokia EKSOS, which looks like an rather easy, low-complexity target. As one of the first steps, I took PCB photographs of the various modules/cards in the shelf, take note of the main chip designations and started to search for the related data sheets.

The results can be found in the Osmocom retronetworking wiki, with https://osmocom.org/projects/retronetworking/wiki/Nokia_EKSOS being the main entry page, and sub-pages about

• Node Control Unit

• 16x BRI Uk0 Line Card

• 32x POTS Line Card

• Line Measurement Unit

• Shelf

In short: Unsurprisingly, a lot of Infineon analog and digital ICs for the POTS and ISDN ports, as well as a number of Motorola M68k based QUICC32 microprocessors and several unknown ASICs.

So with V5 hardware at my disposal, I've slowly re-started my efforts to implement the LE (local exchange) side of the V5 protocol stack, with the goal of eventually being able to interface those V5 AN with the Osmocom Community TDM over IP network. Once that is in place, we should also be able to offer real ISDN Uk0 (BRI) and POTS lines at retrocomputing events or hacker camps in the coming years.

08 Sep 2022 10:00pm GMT

If you have ever worked with Digium (now part of Sangoma) digital telephony interface cards such as the TE110/410/420/820 (single to octal E1/T1/J1 PRI cards), you will probably have seen that they always have a timing connector, where the timing information can be passed from one card to another.

In PDH/ISDN (or even SDH) networks, it is very important to have a synchronized clock across the network. If the clocks are drifting, there will be underruns or overruns, with associated phase jumps that are particularly dangerous when analog modem calls are transported.

In traditional ISDN use cases, the clock is always provided by the network operator, and any customer/user side equipment is expected to synchronize to that clock.

So this Digium timing cable is needed in applications where you have more PRI lines than possible with one card, but only a subset of your lines (spans) are connected to the public operator. The timing cable should make sure that the clock received on one port from the public operator should be used as transmit bit-clock on all of the other ports, no matter on which card.

Unfortunately this decades-old Digium timing cable approach seems to suffer from some problems.

08 Sep 2022 10:00pm GMT