NEW Google Edge Update is INSANE!

New Google Edge update is insane. Google just dropped something massive. And I'm talking about AI running directly on your phone. No cloud, no internet, just pure power in your pocket. And the crazy part, this is in private preview right now. You need to sign up to request access during private preview. But once you're in, this is going to change everything for developers and businesses. And I'm about to show you exactly why you need to pay attention to this right now. Let's go. Trust me, this is a big deal because right now your AI apps probably need the cloud to work. They need internet. They need servers. But what if I told you that Google just made it possible to run full AI models on your phone with zero internet connection. And it's faster, more private, and works anywhere. That's what

Google AI Edge does. It takes AI models from frameworks like TensorFlow, PyTorch, Jax, and Caris and runs them directly on your device. No cloud needed. And the best part, it works across Android, iOS, web, and even tiny microcontrollers. Same model, every platform. That's insane. This is a total game changer for developers because before this, optimizing AI for edge devices was a nightmare. You'd build your model, deploy it, hope it works, and then find out it runs slow on certain phones. Now, you know exactly how it performs before you even ship it. You can compare CPU versus GPU performance, see which accelerators work best, and optimize everything before your users ever touch it. And here's the kicker. This isn't some fake cloud simulation. These are real physical devices in Google's testing labs. Real performance data, real memory usage, real battery drain, everything you need to make smart decisions. Hey, if we haven't met already, I'm the digital avatar of Julian Goldie, CEO of SEO agency Goldie Agency. Whilst he's helping clients get more leads and customers, I'm here to help you get the latest AI updates. Julian Goldie reads every comment, so make sure you comment below. Let me break down what Google AI

Edge actually includes because this is a full stack. First, you've got media pipe tasks. These are low code APIs for vision, text, audio, and generative AI. You want object detection, done, image segmentation, easy run, and LLM on device. No problem. You don't need to be an AI expert. You just use the API and it works. Then there's light RT. This is the runtime that actually executes your models. It's optimized for CPU, GPU, and MPU. So your AI runs fast no matter what hardware your user has and it's efficient. We're talking about running models on phones without killing the battery. Now, here's something most people miss. Google AI Edge has a tool called Model Explorer. This thing lets you visualize your entire model. You can see how it converts, how quantization affects it, where the bottlenecks are. You can debug and benchmark everything locally before you even upload it to AI edge portal. This saves you so much time because you're not guessing. You're seeing exactly what's happening inside your model. and if something's wrong, you catch it early. The big trend right

now is small language models running on your phone. Google is pushing hard on this with Gemma. These are LLMs that are small enough to run locally, but still powerful enough to be useful. And with Google AI Edge, you can now add vision and audio to these models. So, imagine you're building an app. Your user takes a photo. The AI analyzes it, answers questions about it, all without sending anything to the cloud. Or they speak into the phone. Speech to text happens instantly on device. No lag, no privacy concerns. This is the future and it's here now. And here's what makes this even crazier. Google AI Edge Gallery already has over 500,000 downloads. People are hungry for this technology. They want AI that works offline, that's private, that's fast, and developers are building it right now. The gallery shows you real examples of what you can build. Object detection apps, image generation, text classification, audio processing, it's all there. You can download the APKs, see how they work, learn from real code. This isn't theory. This is production ready stuff. And if you want to learn how to scale your business and save hundreds of hours with AI automation tools like Google AI Edge, you need to check out my AI profit boardroom. This is where we show you exactly how to use cuttingedge AI tools to get more customers and automate your entire workflow. Whether you're building ondevice AI apps or just want to leverage the latest tech to grow faster, we cover it all. Link is in the description. Now, let me show you why this matters even more. Now, let's talk

about why AI Edge Portal is such a breakthrough. When you upload your model, you can test it on over a 100 different Android devices. These aren't random phones either. Google has carefully selected devices that represent the market. Different chipsets, different RAM configurations, different Android versions. So, you're testing on what your real users actually have. And the dashboard gives you visual reports. You see heat maps of performance charts comparing devices, lists of which phones struggle and which ones fly. It's all right there. No guesswork. And the process is simple. You upload your model through the UI or you can link it from Google Cloud Storage. Then you pick your accelerators, CPU, GPU, and soon MPU support is coming. You choose which devices to test on and you run the benchmark. Google handles everything else. The models get deployed to real devices. Tests run automatically. Results come back to you and you can compare different versions of your models side by side. So if you optimize something, you see the exact impact immediately. Here's why this matters for businesses. Testing is timeconuming. If you're building an AI app, you need to know it works well for everyone, not just people with flagship phones. With AI edge portal, you can test on budget devices, mid-range devices, flagships, all at once. You catch problems early. You optimize for the devices that matter and you ship with confidence. That's huge because one bad review about your app being slow can kill your momentum. Now you prevent that before launch. Let me tell you about the developer tools that come with this. The Media Pipe framework lets you build custom pipelines. You can chain multiple models together. Add pre-processing, add post-processing, and it all runs on GPU or MPU. No CPU overhead. So you get maximum performance. And you can visualize these pipelines in model explorer. You see exactly how data flows, where compute happens, how long each step takes. This level of visibility is insane. Most tools give you nothing. Google gives you everything. And the low code APIs make this accessible to everyone. You don't need a PhD in machine learning. You just call an API, pass in your image or text or audio, get results back. It's that simple. But under the hood, Google is doing all the heavy lifting. Optimizing for your hardware, managing memory, handling edge cases. You get professional-grade AI without the complexity. Now, here's something that

blew my mind. You can run generative AI on device. Now, we're talking about diffusion models for image generation, small LLMs for text, all running locally, and with the benchmarking from AI edge portal. You can optimize these models to run fast enough for real use. Imagine a photo editing app that generates images in seconds. No cloud latency, just instant results. That's what this enables. And the multimodal support is next level. You can combine vision and language or audio and text. Build an app that listens to your voice, looks at what you're pointing at, and answers questions about it. All on device, all private. This wasn't possible before or it was so slow it wasn't practical. Now it's fast and you can prove it's fast before you even launch. Let's talk about the real world impact. Privacy is huge right now. People don't want their photos sent to the cloud. They don't want their voice recordings stored on servers with ondevice AI. None of that happens. Everything stays local. And you can market that. You can tell your users that their data never leaves their phone. That's a massive selling point. And with Google AI Edge, you get that privacy without sacrificing performance. Offline functionality is another game changer. Your app works on planes, in remote areas, anywhere without internet. Users love this because they're not dependent on connectivity. And for businesses, this opens up new markets. You can serve users in places with poor internet. You can build apps for field workers who are away from Wi-Fi. The use cases are endless. Now let me show you

how the benchmarking actually works. You upload your light RT model. That's the format Google AI edge uses. If you have a TensorFlow or PyTorch model, you convert it first. Model Explorer helps you with that. Then in AI edge portal, you select your test configuration. You can test different quantization levels, different input sizes, different batch sizes, whatever matters for your use case. And Google runs all those tests in parallel. You get results fast. The results show you latency. That's how long inference takes. You see average, minimum, and maximum times. You see variation across devices. Some phones might be super consistent. Others might have spikes. You need to know this. Memory usage is tracked to peak memory, average memory. This tells you if your model will crash on low-end devices. And you see all this broken down by device, model, and chipset. So, you can make informed decisions about which hardware to optimize for. And here's the smart part. You can set performance targets. Say you need inference under 100 milliseconds. AI edge portal highlights which devices hit that target and which don't. You can filter results, focus on the problem areas, and iterate. This feedback loop is so much faster than manual testing. You go from guessing to knowing in minutes instead of weeks. The community around this is growing fast. Developers are sharing benchmarks, comparing models, helping each other optimize, and Google is actively supporting this. They're releasing tutorials, sample code, best practices, everything you need to succeed. And because this is in private preview for AI edge portal, you're getting in early. You're learning before the masses. That's an advantage. And if you want to learn how to scale your business and

save hundreds of hours with AI automation tools like Google AI Edge, you need to check out my AI profit boardroom. This is where we show you exactly how to use cuttingedge AI tools to get more customers and automate your entire workflow. Whether you're building ondevice AI apps or just want to leverage the latest tech to grow faster, we cover it all. Link is in the description. And if you want the full process, SOPs, and over a 100 AI use cases like this one, join the AI Success Lab links in the comments and description. You'll get all the video notes from there, plus access to our community of 38,000 members who are crushing it with AI. All right, thanks for watching. Hit the like and subscribe button and I will see you in the next