Get a soar on the way forward for Google’s UX design: Materials 3 Expressive. Discover ways to use new emotional design patterns to spice up engagement, usability, and want on your product within the Construct Subsequent-Degree UX with Materials 3 Expressive session and take a look at the expressive replace on Materials.io.
Keep updated with Android Accessibility Updates, highlighting accessibility options launching with Android 16: enhanced darkish themes, choices for these with movement illness, a brand new method to enhance textual content distinction, and extra.
Catch the Mastering textual content enter in Compose session to study extra about how partaking strong textual content experiences are constructed with Jetpack Compose. It covers Autofill integration, dynamic textual content resizing, and customized enter transformations. It is a nice session to look at to see what’s potential when designing textual content inputs.
Considering throughout type elements
These design sources and periods may help you design throughout extra Android type elements or replace your present experiences.
Preview Gemini in-car, imagining seamless navigation and personalised leisure within the New In-Automotive App Experiences session. Then discover the brand new Automotive UI Design Package to carry your app to Android Automotive platforms and pace up your course of with the most recent Android type issue equipment.
Partaking with customers on Google TV with glorious TV apps session discusses new methods the Google TV expertise is making it simpler for customers to seek out and interact with content material, together with enchancment to out-of-box options and updates to Android TV OS.
Go to the I/O 2025 web site, construct your schedule, and interact with the group. In case you are on the Shoreline come say howdy to us within the Android tent at our cubicles.
We will not wait to see what you create with these new instruments and insights. Joyful I/O!
Discover this announcement and all Google I/O 2025 updates on io.google beginning Could 22.
Posted by Thomas Ezan – Developer Relations Engineer, Rebecca Franks – Developer Relations Engineer, and Avneet Singh – Product Supervisor
We’re bringing again Androidify later this 12 months, this time powered by Google AI, so you possibly can customise your very personal Android bot and share your creativity with the world. At the moment, we’re releasing a brand new open supply demo app for Androidify as an incredible instance of how Google is utilizing its Gemini AI fashions to boost app experiences.
On this submit, we’ll dive into how the Androidify app makes use of Gemini fashions and Imagen by way of the Firebase AI Logic SDK, and we’ll present some insights discovered alongside the best way that can assist you incorporate Gemini and AI into your individual tasks. Learn extra in regards to the Androidify demo app.
App circulate
The general app features as follows, with varied components of it utilizing Gemini and Firebase alongside the best way:
Gemini and picture validation
To get began with Androidify, take a photograph or select a picture in your gadget. The app must make it possible for the picture you add is appropriate for creating an avatar.
Gemini 2.5 Flash by way of Firebase helps with this by verifying that the picture incorporates an individual, that the particular person is in focus, and assessing picture security, together with whether or not the picture incorporates abusive content material.
val jsonSchema = Schema.obj(
properties = mapOf("success" to Schema.boolean(), "error" to Schema.string()),
optionalProperties = listOf("error"),
)
val generativeModel = Firebase.ai(backend = GenerativeBackend.googleAI())
.generativeModel(
modelName = "gemini-2.5-flash-preview-04-17",
generationConfig = generationConfig {
responseMimeType = "utility/json"
responseSchema = jsonSchema
},
safetySettings = listOf(
SafetySetting(HarmCategory.HARASSMENT, HarmBlockThreshold.LOW_AND_ABOVE),
SafetySetting(HarmCategory.HATE_SPEECH, HarmBlockThreshold.LOW_AND_ABOVE),
SafetySetting(HarmCategory.SEXUALLY_EXPLICIT, HarmBlockThreshold.LOW_AND_ABOVE),
SafetySetting(HarmCategory.DANGEROUS_CONTENT, HarmBlockThreshold.LOW_AND_ABOVE),
SafetySetting(HarmCategory.CIVIC_INTEGRITY, HarmBlockThreshold.LOW_AND_ABOVE),
),
)
val response = generativeModel.generateContent(
content material {
textual content("You're to investigate the supplied picture and decide whether it is acceptable and applicable primarily based on particular standards.... (extra particulars see the total pattern)")
picture(picture)
},
)
val jsonResponse = Json.parseToJsonElement(response.textual content)
val isSuccess = jsonResponse.jsonObject["success"]?.jsonPrimitive?.booleanOrNull == trueval error = jsonResponse.jsonObject["error"]?.jsonPrimitive?.content material
Within the snippet above, we’re leveraging structured output capabilities of the mannequin by defining the schema of the response. We’re passing a Schema object by way of the responseSchema param within the generationConfig.
We need to validate that the picture has sufficient info to generate a pleasant Android avatar. So we ask the mannequin to return a json object with success = true/false and an elective error message explaining why the picture would not have sufficient info.
Structured output is a strong characteristic enabling a smoother integration of LLMs to your app by controlling the format of their output, much like an API response.
Picture captioning with Gemini Flash
As soon as it is established that the picture incorporates enough info to generate an Android avatar, it’s captioned utilizing Gemini 2.5 Flash with structured output.
val jsonSchema = Schema.obj(
properties = mapOf(
"success" to Schema.boolean(),
"user_description" to Schema.string(),
),
optionalProperties = listOf("user_description"),
)
val generativeModel = createGenerativeTextModel(jsonSchema)
val immediate = "You're to create a VERY detailed description of the principle particular person within the given picture. This description will likely be translated right into a immediate for a generative picture mannequin..."val response = generativeModel.generateContent(
content material {
textual content(immediate)
picture(picture)
})
val jsonResponse = Json.parseToJsonElement(response.textual content!!)
val isSuccess = jsonResponse.jsonObject["success"]?.jsonPrimitive?.booleanOrNull == trueval userDescription = jsonResponse.jsonObject["user_description"]?.jsonPrimitive?.content material
The opposite possibility within the app is to begin with a textual content immediate. You possibly can enter in particulars about your equipment, coiffure, and clothes, and let Imagen be a bit extra inventive.
Android technology by way of Imagen
We’ll use this detailed description of your picture to counterpoint the immediate used for picture technology. We’ll add further particulars round what we wish to generate and embrace the bot colour choice as a part of this too, together with the pores and skin tone chosen by the person.
val imagenPrompt = "A 3D rendered cartoonish Android mascot in a photorealistic fashion, the pose is relaxed and easy, dealing with instantly ahead [...] The bot seems as follows $userDescription [...]"
We then name the Imagen mannequin to create the bot. Utilizing this new immediate, we create a mannequin and name generateImages:
// we provide our personal fine-tuned mannequin right here however you should use "imagen-3.0-generate-002" val generativeModel = Firebase.ai(backend = GenerativeBackend.googleAI()).imagenModel(
"imagen-3.0-generate-002",
safetySettings =
ImagenSafetySettings(
ImagenSafetyFilterLevel.BLOCK_LOW_AND_ABOVE,
personFilterLevel = ImagenPersonFilterLevel.ALLOW_ALL,
),
)
val response = generativeModel.generateImages(imagenPrompt)
val picture = response.pictures.first().asBitmap()
And that’s it! The Imagen mannequin generates a bitmap that we are able to show on the person’s display.
Finetuning the Imagen mannequin
The Imagen 3 mannequin was finetuned utilizing Low-Rank Adaptation (LoRA). LoRA is a fine-tuning method designed to cut back the computational burden of coaching giant fashions. As a substitute of updating your entire mannequin, LoRA provides smaller, trainable “adapters” that make small adjustments to the mannequin’s efficiency. We ran a positive tuning pipeline on the Imagen 3 mannequin typically accessible with Android bot belongings of various colour mixtures and completely different belongings for enhanced cuteness and enjoyable. We generated textual content captions for the coaching pictures and the image-text pairs have been used to finetune the mannequin successfully.
The present pattern app makes use of a regular Imagen mannequin, so the outcomes might look a bit completely different from the visuals on this submit. Nevertheless, the app utilizing the fine-tuned mannequin and a customized model of Firebase AI Logic SDK was demoed at Google I/O. This app will likely be launched later this 12 months and we’re additionally planning on including assist for fine-tuned fashions to Firebase AI Logic SDK later within the 12 months.
The unique picture… and Androidifi-ed picture
ML Package
The app additionally makes use of the ML Package Pose Detection SDK to detect an individual within the digicam view, which triggers the seize button and provides visible indicators.
To do that, we add the SDK to the app, and use PoseDetection.getClient(). Then, utilizing the poseDetector, we take a look at the detectedLandmarks which are within the streaming picture coming from the Digital camera, and we set the _uiState.detectedPose to true if a nostril and shoulders are seen:
non-public droop enjoyablerunPoseDetection() {
PoseDetection.getClient(
PoseDetectorOptions.Builder()
.setDetectorMode(PoseDetectorOptions.STREAM_MODE)
.construct(),
).use { poseDetector ->
// Since picture evaluation is processed by ML Package asynchronously in its personal thread pool,// we are able to run this instantly from the calling coroutine scope as a substitute of pushing this// work to a background dispatcher.
cameraImageAnalysisUseCase.analyze { imageProxy ->
imageProxy.picture?.let { picture ->
val poseDetected = poseDetector.detectPersonInFrame(picture, imageProxy.imageInfo)
_uiState.replace { it.copy(detectedPose = poseDetected) }
}
}
}
}
non-public droop enjoyable PoseDetector.detectPersonInFrame(
picture: Picture,
imageInfo: ImageInfo,
): Boolean {
val outcomes = course of(InputImage.fromMediaImage(picture, imageInfo.rotationDegrees)).await()
val landmarkResults = outcomes.allPoseLandmarks
val detectedLandmarks = mutableListOf()
for (landmark in landmarkResults) {
if (landmark.inFrameLikelihood > 0.7) {
detectedLandmarks.add(landmark.landmarkType)
}
}
return detectedLandmarks.containsAll(
listOf(PoseLandmark.NOSE, PoseLandmark.LEFT_SHOULDER, PoseLandmark.RIGHT_SHOULDER),
)
}
The digicam shutter button is activated when an individual (or a bot!) enters the body.
Get began with AI on Android
The Androidify app makes an in depth use of the Gemini 2.5 Flash to validate the picture and generate an in depth description used to generate the picture. It additionally leverages the particularly fine-tuned Imagen 3 mannequin to generate pictures of Android bots. Gemini and Imagen fashions are simply built-in into the app by way of the Firebase AI Logic SDK. As well as, ML Package Pose Detection SDK controls the seize button, enabling it solely when an individual is current in entrance of the digicam.
To get began with AI on Android, go to the Gemini and Imagen documentation for Android.
Discover this announcement and all Google I/O 2025 updates on io.google beginning Might 22.
The wants of consumers are evolving quicker than ever — and Cisco is evolving with them.
As you already know, we’re re-architecting the way in which we design options and ship them to market — with a One Cisco strategy throughout our portfolio and AI technique — as a result of yesterday’s approaches now not assist at present’s actuality.
Prospects at present count on quicker innovation, seamless experiences, and higher impression from their know-how investments.
That’s why we’re constructing the Cisco 360 Associate Program — designed to drive actual buyer outcomes, acknowledge various companion enterprise fashions, and reward worth creation by way of functionality constructing, go-to-market energy, and deeper engagement.
Along with you — our companions — we’re creating one thing essentially new to satisfy the challenges and alternatives forward.
Bringing Prospects Alongside
You’ve advised us loud and clear: We have to begin bringing prospects alongside now.
And we couldn’t agree extra.
We’re excited to share that we’ve formally launched a buyer consciousness marketing campaign to assist prospects perceive the evolution underway — and the way Cisco and our companions are higher positioned than ever to assist them obtain their enterprise objectives.
This website helps prospects study extra in regards to the Cisco 360 Associate Program — with out disrupting their present expertise.
It reinforces the ability of our companion ecosystem to ship outcomes, not simply merchandise, particularly within the AI period.
What This Means for You
We all know that prospects’ expectations are altering. They want trusted guides who may help them modernize infrastructure, deploy AI options, safe their operations, and ship measurable enterprise outcomes. The Cisco 360 Associate Program — and this buyer marketing campaign — are designed to place you on the middle of that chance.
Acknowledged for worth creation: Not simply transactions, however the outcomes you assist prospects obtain.
Rewarded for functionality constructing and engagement: Targeted on the abilities and experience prospects are looking for.
Aligned for progress: With a framework constructed for at present’s wants and tomorrow’s prospects.
We’re dedicated to supporting you each step of the way in which as we transfer towards the official launch on February 1, 2026 — supplying you with the instruments to have interaction prospects confidently and present the distinctive worth you deliver.
Thank You
Thanks on your continued partnership, innovation, and dedication to buyer success.
Collectively, we’re main a metamorphosis that may drive mutual progress and ship higher outcomes for patrons all over the world.
We’d love to listen to what you assume. Ask a Query, Remark Under, and Keep Related with #CiscoPartners on social!
Posted by Rebecca Franks – Developer Relations Engineer
Androidify is a brand new pattern app we constructed utilizing the most recent finest practices for cellular apps. Beforehand, we lined all of the completely different options of the app, from Gemini integration and CameraX performance to adaptive layouts. On this publish, we dive into the Jetpack Compose utilization all through the app, constructing upon our base information of Compose so as to add pleasant and expressive touches alongside the best way!
Materials 3 Expressive
Materials 3 Expressive is an enlargement of the Materials 3 design system. It’s a set of latest options, up to date parts, and design techniques for creating emotionally impactful UX.
In Androidify, we’ve utilized Materials 3 Expressive in a couple of alternative ways throughout the app. For instance, we’ve explicitly opted-in to the brand new MaterialExpressiveTheme and chosen MotionScheme.expressive() (that is the default when utilizing expressive) so as to add a little bit of playfulness to the app:
A number of the new componentry is used all through the app, together with the HorizontalFloatingToolbar for the Immediate sort choice:
The app additionally makes use of MaterialShapes in varied places, that are a preset record of shapes that enable for simple morphing between one another. For instance, try the lovable cookie form for the digital camera seize button:
Digicam button with a MaterialShapes.Cookie9Sided form
Animations
Wherever potential, the app leverages the Materials 3 Expressive MotionScheme to acquire a themed movement token, making a constant movement feeling all through the app. For instance, the dimensions animation on the digital camera button press is powered by defaultSpatialSpec(), a specification used for animations that transfer one thing throughout a display screen (comparable to x,y or rotation, scale animations):
val interactionSource = keep in mind { MutableInteractionSource() }
val animationSpec = MaterialTheme.motionScheme.defaultSpatialSpec()
Spacer(
modifier
.indication(interactionSource, ScaleIndicationNodeFactory(animationSpec))
.clip(MaterialShapes.Cookie9Sided.toShape())
.measurement(measurement)
.drawWithCache {
//.. and so on
},
)
Digicam button scale interplay
Shared ingredient animations
The app makes use of shared ingredient transitions between completely different display screen states. Final yr, we showcased how one can create shared parts in Jetpack Compose, and we’ve prolonged this within the Androidify pattern to create a enjoyable instance. It combines the brand new Materials 3 Expressive MaterialShapes, and performs a transition with a morphing form animation:
To do that, we created a customized Modifier that takes within the goal and resting shapes for the sharedBounds transition:
Then, we apply a customized OverlayClip to supply the morphing form, by tying into the AnimatedVisibilityScope supplied by the LocalNavAnimatedContentScope:
val animatedProgress =
animatedVisibilityScope.transition.animateFloat(targetValueByState = targetValueByState)
val morph = keep in mind {
Morph(restingShape, targetShape)
}
val morphClip = MorphOverlayClip(morph, { animatedProgress.worth })
returnthis@sharedBoundsRevealWithShapeMorph
.sharedBounds(
sharedContentState = sharedContentState,
animatedVisibilityScope = animatedVisibilityScope,
boundsTransform = boundsTransform,
resizeMode = resizeMode,
clipInOverlayDuringTransition = morphClip,
renderInOverlayDuringTransition = renderInOverlayDuringTransition,
)
With the most recent launch of Jetpack Compose 1.8, we added the flexibility to create textual content composables that routinely alter the font measurement to suit the container’s accessible measurement with the brand new autoSize parameter:
That is used entrance and heart for the “Customise your personal Android Bot” textual content:
“Customise your personal Android Bot” textual content with inline GIF
This textual content composable is attention-grabbing as a result of it wanted to have the enjoyable dancing Android bot in the course of the textual content. To do that, we use InlineContent, which permits us to append a composable in the course of the textual content composable itself:
With Compose 1.8, a brand new modifier, Modifier.onLayoutRectChanged, was added. This modifier is a extra performant model of onGloballyPositioned, and contains options comparable to debouncing and throttling to make it performant inside lazy layouts.
In Androidify, we’ve used this modifier for the colour splash animation. It determines the place the place the transition ought to begin from, as we connect it to the “Let’s Go” button:
var buttonBounds by keep in mind {
mutableStateOf(null)
}
var showColorSplash by keep in mind {
mutableStateOf(false)
}
Field(modifier = Modifier.fillMaxSize()) {
PrimaryButton(
buttonText = "Let's Go",
modifier = Modifier
.align(Alignment.BottomCenter)
.onLayoutRectChanged(
callback = { bounds ->
buttonBounds = bounds
},
),
onClick = {
showColorSplash = true
},
)
}
We use these bounds as a sign of the place to begin the colour splash animation from.
Study extra pleasant particulars
From enjoyable marquee animations on the outcomes display screen, to animated gradient buttons for the AI-powered actions, to the trail drawing animation for the loading display screen, this app has many pleasant touches so that you can expertise and be taught from.
Try the total codebase at github.com/android/androidify and be taught extra in regards to the newest in Compose from utilizing Materials 3 Expressive, the brand new modifiers, auto-sizing textual content and naturally a few pleasant interactions!
Discover this announcement and all Google I/O 2025 updates on io.google beginning Might 22.
WannaCry. NotPetya.EternalBlue. These names mark a number of the most devastating cyberattacks in historical past, they usually all exploited flaws in Server Message Block (SMB). Figuring out methods to detect and defend towards SMB vulnerabilities isn’t simply good cybersecurity—it’s important for anybody severe a few profession within the discipline.
Why SMB exploits matter
SMB is a community protocol used primarily by Microsoft for sharing recordsdata, printers, and different sources throughout the community. It permits customers to learn, create, and replace recordsdata on distant servers and talk with different packages over the community. The shift to distant work led many organizations to reveal inner providers like SMB over the web, usually with out satisfactory safety controls, considerably growing the danger of exploitation.
An SMB exploit is a method utilized by cybercriminals to make the most of vulnerabilities within the SMB protocol. For instance, in WannaCry, the assault appeared for uncovered SMB ports (mostly port 445). On this case, they have been uncovered resulting from misconfiguration. As soon as an uncovered port was discovered, the chain of exploits continued. EternalBlue was exploited on susceptible programs to unfold a worm all through the community, in the end deploying ransomware on contaminated machines. The WannaCry ransomware worm unfold to greater than 200,000 computer systems in over 150 nations.
As proven on this instance, when attackers exploit SMB vulnerabilities, they acquire unauthorized entry to programs, run malicious code, and trigger widespread disruption.
Why our Operation SMB Exploit problem issues
Our newest Seize the Flag: Operation SMB Exploit problem in Cisco U. hones the talents you’ll want to determine the SMB vulnerabilities in working programs (reminiscent of Home windows and Linux) that depart your community open to those assaults.
To higher equip your self for a job in offensive safety with this vital talent set, you’ll get hands-on apply analyzing community safety from an attacker’s perspective:
Discover password cracking and vulnerability scanning methods.
Try a brute-force assault towards SSH to uncover any SMB vulnerabilities.
Enumerate SMB shares.
The tip consequence: Perceive potential impacts and the way they can be utilized to determine SMB vulnerabilities that may be exploited in providers like Microsoft’s.
The very best information: When you efficiently full our newest Seize the Flag problem, you’re positive to return out a winner by studying methods to proactively crush any possibilities of exploits in your simulated assault.
New to the Cisco Certificates in Moral Hacking program?
Proceed full steam forward and be a part of a group of like-minded friends and consultants within the Cisco Certificates in Moral Hacking Neighborhood. They may help make sure you maintain your momentum going and end sturdy.
It’s the problem that retains on giving badges—gather ‘em all
Plus, you may proceed to gather extra badges with extra Seize the Flag challenges in Cisco U. They’re launched each 90 days. It’s a enjoyable and interesting solution to present you’re all the time a step forward of menace actors within the newest cyberthreat panorama.
