Google’s Android Update Pushes Smartphones Into the AI-First Era


After years of sprinkling AI into its mobile products, Google’s fully leaning in.

The company is integrating Gemini more deeply into Android, allowing its AI assistant to manage a wider range of everyday tasks across apps — a move that could fundamentally reshape how people interact with their phones. Google shared the update last week, ahead of its I/O developer conference on Tuesday, during which it’s expected to dive deeper into its AI ambitions.

Rather than you having to bounce between apps for routine tasks like filling out forms, scheduling appointments and making reservations, Gemini will soon be able to handle it all for you. Google wants this upgraded capability, called Gemini Intelligence (not to be confused with Apple Intelligence), to feel like a true assistant — one that proactively does its job without needing constant instruction.

“The difference between the technology of yesterday and the technology of Gemini Intelligence is that it’s there with you,” Ben Greenwood, a director and product manager for Android Core Experiences, told me in an interview. “I really just want one assistant that I’m working with who understands me and knows me personally. Having that experience [be] consistent across the products I’m using is really important to build trust and ease of use.”

Google shared the AI updates during its Android Show presentation on Tuesday. Gemini Intelligence will carry out routine actions like creating a shopping order from the grocery list in your notes app. It can autofill complex forms using information stored in connected apps such as Google Drive, like your driver’s license or passport number. You can snap a picture of a brochure and ask Gemini to find a tour for a group of six. It can even generate custom widgets based on a simple prompt, such as displaying the temperature in both Fahrenheit and Celsius. You can read CNET’s more detailed breakdown of what’s coming to Android here.

Watch this: Android’s Biggest AI Update: Everything to Know About Gemini Intelligence

These capabilities add to the handful of Gemini-powered tasks that arrived on Pixel 10 and Samsung Galaxy S26 handsets earlier this year. Gemini Intelligence will also work on Android Auto, Wear OS and Google’s smart glasses for a unified experience across devices. 

Gemini Intelligence will first come to Samsung Galaxy and Google Pixel phones later this summer. Google didn’t specify which upcoming Galaxy devices will be compatible, but Samsung is expected to unveil the next generation of its foldables in the coming months. Google is also set to debut new Pixel phones in the summer. 

Bringing Gemini Intelligence to premium Android devices could give Google an edge over competitors like Apple, which has yet to bring a more intuitive and helpful Siri to the iPhone — though Google’s Gemini models will soon help to power that update as well. 

Android’s AI-centric shift likely spells the beginning of what’s to come for the wider industry. 

A glimpse of the AI-first smartphone future

For years, tech companies have pointed to a future in which AI will fundamentally transform the way we use our phones. As digital assistants become more capable, they could soon tackle more of the everyday grunt work. 

Some experts have even predicted that AI will replace the apps on our phones entirely, supplanted by interactive, generative AI platforms that respond to our every command. Why juggle siloed apps for playing music, hailing a ride and sending messages if a virtual assistant can take care of all of that and more?

AI Atlas

Signs of that transition are beginning to emerge, with reports that OpenAI may be developing its own AI-powered smartphone. If all goes to plan, the company could begin mass production in the first half of next year. Amazon is also reportedly eyeing a reentry into the smartphone market, this time with a handset focused on AI features rather than traditional apps.

“Users are not trying to use a pile of apps,” industry analyst Ming-Chi Kuo said in a report on the OpenAI news last month. “They are trying to get tasks done and fulfill needs through the phone. This fundamentally changes how people think about smartphones.” 

Gemini Intelligence on Android doesn’t go as far as eliminating apps on your phone — at least not yet. But it is designed to curb the amount of time you spend manually completing individual tasks. Google hopes that even people who are weary of the constant stream of AI features will be enticed to try Gemini Intelligence. 

“We’re all a little fatigued of the ‘Times Square-AI’ kind of experience,” Greenwood said, nodding to the growing exhaustion surrounding splashy AI announcements. “How the team has approached this has been to look at, what are real problems that people have and encounter, and how can we help?”

He points to a Gemini Intelligence feature called Rambler as an example. On Gboard, Google’s Android keyboard, the speech-to-text tool can now filter out self-corrections, repetitions and filler words. For example, if you’re texting someone a grocery list and say, “Can you get toast, cereal and bananas — actually no bananas,” it’ll only jot down the toast and cereal. Rambler can also tap into Gemini’s multilingual model to switch between languages within a single message — catering to those of us who often mix languages as we speak. 

“You’re not trying to teach a new behavior,” Greenwood notes. People who already use the microphone function on their keyboard might not have to think about how AI is optimizing the experience. Autofill is another example of AI quietly handling a task like filling out forms without commanding much attention. 

Ultimately, it’s about getting more things done automatically, without having to spell out what you want. The bigger question is how comfortable people are with letting Google’s AI take the wheel a little more often. Either way, the broader shift toward AI-driven smartphones is seemingly well underway.





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What is a Mapplet?

A Mapplet is an object that can be reused. It will be created in the Mapplet Designer. It includes a set of transformations and allows us to reuse transformation logic in more than one Mapping. Let us understand Mapplets with an example. Consider you have some fact tables which need a series of dimension keys. We can create a Mapplet with a series of Lookup transformations to find every dimension key. We can use this Mapplet in every fact table Mapping instead of recreating the same search logic in every Mapping. As a reusable transformation, any changes to the Mapplet are inherited from every instance of the Mapplet. A Reusable transformation refers to any rule or transition logic defined on the data that will be transformed from source to destination via Mapping, and it can be provided more than once with various methods and logic. it can be used for other transformations.

Mapplet is applicable to mapped data. The source object and the target object will be defined and stored in the database. A logic to be transformed is defined by offering a Mapplet Input that transmits the data from Mapping to Mapplet. After that, a desired Mapplet output transform transmits the Mapplet data to Mapping. So the Input-Output transformations will evolve into cyclic Mapping, transaction logic and reused data without any impact on the data.

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Why Mapplets?

The Mapplets are created to serve two primary purposes:

Whenever we load new data into a table, some space occurs in the source system, and whenever a new transformation is required to be configured on each Mapping. Mapplets are created to prevent this repetition of the creation of the transformation expressions and to end the unwanted space that is formed in the source system. 
On each workflow that is running in the system, a batch id will be formed according to the timestamp of the session using a Mapplet.

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Informatica Mapplet features: 

  • A Mapplet is used to define key data source definitions as well as a source qualifier for providing the data for Mapping.
  • A Mapplet may not have the source definition of the data. Mapplet may accept this data as well from a mapping process via Mapplet input ports.
  • A Mapplet may have several transformations. 
  • The data may be transformed into several pipelines. A Mapplet may include several groups of output ports/groups which may be connected to one another via various pipelines in the Mapping.


Mapplet Components:

For using a Mapplet in Mapping, we must configure the Mapplet for input and output. Apart from the transformation logic we are configuring, a Mapplet includes the following components:

  • Mapplet ports
  • Mapplet input
  • Mapplet output 
Mapplet Ports:

It will be available only in the Mapping Designer. The Mapplet ports comprise the input ports of the input transformations and the output ports of the output transformations.

Mapplet Input:

The Mapplet input may come from the source definition or from the Input transformation within the Mapplet. Several pipelines can be created in a Mapplet. Utilize several source definitions as well as the input transformations or source qualifiers. Alternatively, you can use a mixture of input transformations and source definitions.

Mapplet Output:

The Mapplet output consists of transformation for passing the data through the Mapplet into the Mapping. At Least one output transformation is included in the Mapplet that includes at least one connected port in the Mapplet. Every port connected in the output transformation displays as a Mapplet output port in the Mapping. Every output transformation in the Mapplet is displayed as the output group in the Mapping. The output group may transmit data to several pipelines within the Mapping.

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Creation of a Mapplet in Informatica:

The creation of Mapplets involves three steps.

  • First, we must add, connect and then configure the transformations using a transformation logic.
  • Then we need to save the Mapplet using a unique name.
  • Now we can use this Mapplet in the Mapping.
     

When dealing with the Mapplets, mistakes can be avoided by:

  • One of the best ways to avoid mistakes in Mapplets is to comment on every input as well as output transformation that is made in Mapplets so that they will remind us why we have made them.
  • Avoid making modifications to source data datatype, data accuracy or select ports that are connected in the I/O transformation, from the passive to active Mapplet.
     

Follow the rule and guidelines while adding transformations to the Mapplet:

  • When you are using the sequence generator transformation, you should use the reusable sequence generator transformation.
  • When you are using the stored procedure transformation, you should configure the stored procedure Type as Normal.
  • The PowerMart, 3.5 style LOOKUP functions, cannot be included in a Mapplet.
     

Following are the objects that cannot be included in a Mapplet:

  • COBOL sources
  • Normalizer transformations
  • Other Mapplets
  • Target definitions
  • XML sources
  • XML source qualifier transformations
  • Pre and post-session stored procedures
  • Non-reusable sequence generator transformation
     

While reusable shortcuts and transformations in the Mapplet can be used, for protecting the Mapplet validity, use a copy of the transformation rather. Reusable transformations or shortcuts inherit modifications to their original transformations. This could disable the Mapplet and Mapping, which utilizes the Mapplet.

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Conclusion:

In this blog, we have learned about Mapplets, why we use Mapplets, Mapplets features, components of a Mapplet and how to create a Mapplet. We hope you found this information helpful!. For more blogs like this, stay tuned to HKR Trainings. 

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