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Google I/O 2016 Day 1- Review

The Google I/O 2016 is done for the year. We knew Google I/O 2016 would be hot, but this hot? The conference has been on fire since the keynote kicked off on Wednesday morning, and shows no signs of cooling down.

The Google I/O 2016 was mix of unexpected and expected announcements. There were a ton of cool announcements nestled inside of it that will hit market in soon future. The 8 major highlights of the Google’s I/O 2016 were:

Google Assistant, Google Home, Allo app, Duo apps, Android N, Google Daydream, Android Wear 2.0, Android Instant Apps, Firebase, Studio 2.2

From Android N, to the just-debuted Google Home, we’ve tried to put together the biggest moments from today’s keynotes:

Android N, Google Daydream, Android Wear 2.0, Google Home and the new Allo and Duo apps were the stars of the opening keynote, which were followed by other announcements which got atmosphere even hotter.

[section_tc][column_tc span=’12’][youtube_tc id=’https://www.youtube.com/watch?v=S8exfLwoHKA’][/youtube_tc][/column_tc][/section_tc]

  1. Google Assistant:
    The first major reveal of I/O 2016 was Google Assistant, a new personal AI for users. It lets users ask queries as much as they would do in the search engine, but in a Siri-like set-up. Google Assistant is the natural extension of search, supporting “conversational understanding” to make search more natural and to better support voice searches.

You can ask for Pablo Picasso’s first name, sports scores and to play a song you’ve had stuck in your head for all day.google-assistant-100661757-large

  1. Google Home:
    Just where Google Assistant ended, it was taken by Google Home, of course.

Pichai gave a shout out to Amazon Echo in announcing the new device, which is a white-and-gray Wi-Fi speaker that helps you handle everyday tasks. It plays music and lets you control smart home devices, including Nest products.

The Google Home speaker will be released later this year, and it will service as a portal into the Google Assistant experience. It will also let you control connected devices within the home, and you’ll be able to cast content with the speaker as well. Say “play Fast and Furious on my TV” and the movie will appear on your screen.

The entire experience is hands-free, powered entirely by voice. In fact, it doesn’t even have any buttons. Simple voice commands will control every aspect of the Home, as is the case with the Amazon Echo. Home even integrates with third-party services, allowing you to do things like call an Uber car or book a restaurant reservation using OpenTable.

You can, of course, ask Google Home anything you want to know, like you do in Google search.

Search is built in, drawing on 17 years of innovation to “answers questions that are difficult for other assistants to handle.”google-home-1024x513

  1. Google Allo:
    Meet Google’s new messaging app, Allo.

Google has fallen way behind top rivals like Facebook in the messaging space. Allo is the company’s new offering that includes a number of features Google hopes will help set its new app apart.

For example, the app has a whisper/shout feature that changes the size of the text you send using a slider to help communicate volume. Want to “yell” something? This feature lets you enlarge the text instead of using caps. Feel like “whispering” instead? Shrink text down with the same slider.

Another cool feature is smart replies, which create canned responses that evolve over time based on your conversations. Smart replies are even generated in response to photos thanks to Google’s photo analysis capabilities.

Also included, of course, is bot support. From right within the app, users can interact with a wide range of bots. For example, an OpenTable bot will allow users to choose a restaurant and book a reservation without ever leaving an Allo chat. And of course, there’s also a Google Assistant search bot. Want to search for a cute cat GIF from within a chat? No problem.

Lastly, Allo includes an incognito mode. All Allo chats are encrypted but incognito mode offers end-to-end encryption and an option to send messages that self-destruct. Additionally, once you close a chat, the entire conversation is deleted forever.

The app launches this summer on Android and iOS.Allo App

  1. Duo App:
    Then came the announcement of Duo, a simple one-to-one video calling app for everyone.

Duo is the video companion to Allo, and includes a feature called Knock-Knock that lets you see a stream of whomever is calling you before you answer. That way, Google says, you can see who’s calling you and what they’re doing before you start a conversation.

Duo also switches seamlessly between cellular and Wi-Fi connections, and it manages video and audio in real-time to adjust quality on the fly when available bandwidth increases or decreases.

Duo will be available later this summer for iOS and Android.google-duo-video-chat-8011

  1. Android N:
    Google’s next major mobile software release is Android N, and it’s going to be a huge update when it’s released later this year.

Still not decided on the name, calling it Android N, the new Android OS has improved graphics, reduced battery consumption and storage and security enhancements.

It is more secure than before with media framework hardening, file based encryption and seamless updates. Users can now quick switch to the previous app by double tapping the recent button in Android N. Multi-window mode comes to Android N, too. Split screen along with picture in picture modes are available.

Vulcan is the software that powers these improvements on the graphics side, while a series of software optimizations boost performance elsewhere.

Most impressively perhaps, Android N will download and install system updates automatically.

Moving on to the app switcher screen, Android will automatically remove apps from the UI when it determines the app is no longer needed. This way, the app switcher UI is decluttered and it’s easier to find the app you’re looking for. There’s also a new quick switch function accessed by double-tapping the recent button on a phone or tablet.

N’s window management framework has also been redesigned to support both split-screen apps (side by side) and picture in picture (a small windows in the corner of the screen). The former will work across phones and tablets while the latter is for Android TV only.

Where notifications are concerned, Android N has a new direct reply feature that lets users reply to messages right from the notification. Unicode 9 emoji will also be supported in Android N, complete with support for all skin tones.

Android N will be released to the public later this summer, but a beta has already been pushed out. Check out more details on our Blog “Android N- Developers Review”.android-n-update-hero-970-80

  1. Google DayDream:
    Google then announced Daydream, a new VR platform built on Android N that will arrive this autumn. Similar to the home view you find inside of Oculus Rift, Daydream is an all-in-one experience that brings games, apps, movies and even the Google Play Store in its entirety into a VR headset.

There was no Android VR headset to show off, though Google has come up with a reference design for other manufacturers to build off. It also displayed a small, Wii-like controller that provides motion control.

Several Daydream-ready devices will be launching this year from the likes of Samsung, HTC and other popular manufacturers.

Virtual reality is a huge component of Android N, and the new VR platform is what Google call Google Daydream.screen-shot-2016-05-19-at-9-33-44-am-png

  1. Android Wear 2.0:
    The next major announcement was Android Wear 2.0. Developers can download a preview of it starting today, and it will come to all users in the fall.

Some improvements include the ability to show any app data on any watch face, improved handwriting recognition, and a big update for Google Fitness. Even better news for fitness fans is Google will now allow apps to talk to one another – so if you bring in calories in your nutrition app, you can offset that with your running app.

In other words, apps no longer need a connected smartphone in order to function. With a phone completely powered off or even left behind, apps can function and even communicate without a phone, as long as the wearable device is connected to the internet via cellular or Wi-Fi.bb275e40f42852dccfa8ce310f1d55240990e1ed

  1. Instant Android Apps:
    The I/O 2016 was steaming atmosphere with every announcement.

Google announced Instant Android Apps, which lets you instantly access an app without needing to download it.

Android Instant Apps takes Google’s concept of Accelerated Mobile Pages, which loads webpages near-instantly, to Android apps. Users will no longer need to download an app in order to use its features.
With Android Instant Apps, users will be able to run any app with one tap, no installation needed.

It is Google’s answer to the pain of installing phone apps you know you’ll use just once or twice, like for shopping. With this approach, the app runs on Google’s servers instead of your phone. It also has compatibility all the way back to Jellybean OS.

It’s only in preview as Google says it will take a lot of time to get right, but it holds exciting possibilities.Google-Android-Instant-Apps-03

The Google had something in store for developers as well:

  1. Firebase
    Google launched an expansion of Firebase at IO 2016.Going beyond a mobile backend, the platform helps developers quickly build high-quality apps, grow their user base, and earn more money across iOS, Android and the mobile web.firebase_cloud
  1. Studio 2.2
    Google launched Android Studio 2.2 preview, the latest version of its integrated development environment (IDE). It has a new layout designer and a firebase plugin adding services like Analytics, Authentication, Notifications, and AdMob.Studio 2.2 will be better for developers who are aiming emerging.The first day of the Google I/O 2016 was full of future tech realities, from Android N, to the just-debuted Google Home. They had some or the other thing stored for everyone from user to developers. android-studio-2-2

The 2nd day expectations are also high. For updates of 2nd day stay with Mantra Labs.

If any queries approach us on hello@mantralabsglobal.com

 

 

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AI Code Assistants: Revolution Unveiled

AI code assistants are revolutionizing software development, with Gartner predicting that 75% of enterprise software engineers will use these tools by 2028, up from less than 10% in early 2023. This rapid adoption reflects the potential of AI to enhance coding efficiency and productivity, but also raises important questions about the maturity, benefits, and challenges of these emerging technologies.

Code Assistance Evolution

The evolution of code assistance has been rapid and transformative, progressing from simple autocomplete features to sophisticated AI-powered tools. GitHub Copilot, launched in 2021, marked a significant milestone by leveraging OpenAI’s Codex to generate entire code snippets 1. Amazon Q, introduced in 2023, further advanced the field with its deep integration into AWS services and impressive code acceptance rates of up to 50%. GPT (Generative Pre-trained Transformer) models have been instrumental in this evolution, with GPT-3 and its successors enabling more context-aware and nuanced code suggestions.

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  • Adoption rates: By 2023, over 40% of developers reported using AI code assistants.
  • Productivity gains: Tools like Amazon Q have demonstrated up to 80% acceleration in coding tasks.
  • Language support: Modern AI assistants support dozens of programming languages, with GitHub Copilot covering over 20 languages and frameworks.
  • Error reduction: AI-powered code assistants have shown potential to reduce bugs by up to 30% in some studies.

These advancements have not only increased coding efficiency but also democratized software development, making it more accessible to novice programmers and non-professionals alike.

Current Adoption and Maturity: Metrics Defining the Landscape

The landscape of AI code assistants is rapidly evolving, with adoption rates and performance metrics showcasing their growing maturity. Here’s a tabular comparison of some popular AI coding tools, including Amazon Q:

Amazon Q stands out with its specialized capabilities for software developers and deep integration with AWS services. It offers a range of features designed to streamline development processes:

  • Highest reported code acceptance rates: Up to 50% for multi-line code suggestions
  • Built-in security: Secure and private by design, with robust data security measures
  • Extensive connectivity: Over 50 built-in, managed, and secure data connectors
  • Task automation: Amazon Q Apps allow users to create generative AI-powered apps for streamlining tasks

The tool’s impact is evident in its adoption and performance metrics. For instance, Amazon Q has helped save over 450,000 hours from manual technical investigations. Its integration with CloudWatch provides valuable insights into developer usage patterns and areas for improvement.

As these AI assistants continue to mature, they are increasingly becoming integral to modern software development workflows. However, it’s important to note that while these tools offer significant benefits, they should be used judiciously, with developers maintaining a critical eye on the generated code and understanding its implications for overall project architecture and security.

AI-Powered Collaborative Coding: Enhancing Team Productivity

AI code assistants are revolutionizing collaborative coding practices, offering real-time suggestions, conflict resolution, and personalized assistance to development teams. These tools integrate seamlessly with popular IDEs and version control systems, facilitating smoother teamwork and code quality improvements.

Key features of AI-enhanced collaborative coding:

  • Real-time code suggestions and auto-completion across team members
  • Automated conflict detection and resolution in merge requests
  • Personalized coding assistance based on individual developer styles
  • AI-driven code reviews and quality checks

Benefits for development teams:

  • Increased productivity: Teams report up to 30-50% faster code completion
  • Improved code consistency: AI ensures adherence to team coding standards
  • Reduced onboarding time: New team members can quickly adapt to project codebases
  • Enhanced knowledge sharing: AI suggestions expose developers to diverse coding patterns

While AI code assistants offer significant advantages, it’s crucial to maintain a balance between AI assistance and human expertise. Teams should establish guidelines for AI tool usage to ensure code quality, security, and maintainability.

Emerging trends in AI-powered collaborative coding:

  • Integration of natural language processing for code explanations and documentation
  • Advanced code refactoring suggestions based on team-wide code patterns
  • AI-assisted pair programming and mob programming sessions
  • Predictive analytics for project timelines and resource allocation

As AI continues to evolve, collaborative coding tools are expected to become more sophisticated, further streamlining team workflows and fostering innovation in software development practices.

Benefits and Risks Analyzed

AI code assistants offer significant benefits but also present notable challenges. Here’s an overview of the advantages driving adoption and the critical downsides:

Core Advantages Driving Adoption:

  1. Enhanced Productivity: AI coding tools can boost developer productivity by 30-50%1. Google AI researchers estimate that these tools could save developers up to 30% of their coding time.
IndustryPotential Annual Value
Banking$200 billion – $340 billion
Retail and CPG$400 billion – $660 billion
  1. Economic Impact: Generative AI, including code assistants, could potentially add $2.6 trillion to $4.4 trillion annually to the global economy across various use cases. In the software engineering sector alone, this technology could deliver substantial value.
  1. Democratization of Software Development: AI assistants enable individuals with less coding experience to build complex applications, potentially broadening the talent pool and fostering innovation.
  2. Instant Coding Support: AI provides real-time suggestions and generates code snippets, aiding developers in their coding journey.

Critical Downsides and Risks:

  1. Cognitive and Skill-Related Concerns:
    • Over-reliance on AI tools may lead to skill atrophy, especially for junior developers.
    • There’s a risk of developers losing the ability to write or deeply understand code independently.
  2. Technical and Ethical Limitations:
    • Quality of Results: AI-generated code may contain hidden issues, leading to bugs or security vulnerabilities.
    • Security Risks: AI tools might introduce insecure libraries or out-of-date dependencies.
    • Ethical Concerns: AI algorithms lack accountability for errors and may reinforce harmful stereotypes or promote misinformation.
  3. Copyright and Licensing Issues:
    • AI tools heavily rely on open-source code, which may lead to unintentional use of copyrighted material or introduction of insecure libraries.
  4. Limited Contextual Understanding:
    • AI-generated code may not always integrate seamlessly with the broader project context, potentially leading to fragmented code.
  5. Bias in Training Data:
    • AI outputs can reflect biases present in their training data, potentially leading to non-inclusive code practices.

While AI code assistants offer significant productivity gains and economic benefits, they also present challenges that need careful consideration. Developers and organizations must balance the advantages with the potential risks, ensuring responsible use of these powerful tools.

Future of Code Automation

The future of AI code assistants is poised for significant growth and evolution, with technological advancements and changing developer attitudes shaping their trajectory towards potential ubiquity or obsolescence.

Technological Advancements on the Horizon:

  1. Enhanced Contextual Understanding: Future AI assistants are expected to gain deeper comprehension of project structures, coding patterns, and business logic. This will enable more accurate and context-aware code suggestions, reducing the need for extensive human review.
  2. Multi-Modal AI: Integration of natural language processing, computer vision, and code analysis will allow AI assistants to understand and generate code based on diverse inputs, including voice commands, sketches, and high-level descriptions.
  3. Autonomous Code Generation: By 2027, we may see AI agents capable of handling entire segments of a project with minimal oversight, potentially scaffolding entire applications from natural language descriptions.
  4. Self-Improving AI: Machine learning models that continuously learn from developer interactions and feedback will lead to increasingly accurate and personalized code suggestions over time.

Adoption Barriers and Enablers:

Barriers:

  1. Data Privacy Concerns: Organizations remain cautious about sharing proprietary code with cloud-based AI services.
  2. Integration Challenges: Seamless integration with existing development workflows and tools is crucial for widespread adoption.
  3. Skill Erosion Fears: Concerns about over-reliance on AI leading to a decline in fundamental coding skills among developers.

Enablers:

  1. Open-Source Models: The development of powerful open-source AI models may address privacy concerns and increase accessibility.
  2. IDE Integration: Deeper integration with popular integrated development environments will streamline adoption.
  3. Demonstrable ROI: Clear evidence of productivity gains and cost savings will drive enterprise adoption.
  1. AI-Driven Architecture Design: AI assistants may evolve to suggest optimal system architectures based on project requirements and best practices.
  2. Automated Code Refactoring: AI tools will increasingly offer intelligent refactoring suggestions to improve code quality and maintainability.
  3. Predictive Bug Detection: Advanced AI models will predict potential bugs and security vulnerabilities before they manifest in production environments.
  4. Cross-Language Translation: AI assistants will facilitate seamless translation between programming languages, enabling easier migration and interoperability.
  5. AI-Human Pair Programming: More sophisticated AI agents may act as virtual pair programming partners, offering real-time guidance and code reviews.
  6. Ethical AI Coding: Future AI assistants will incorporate ethical considerations, suggesting inclusive and bias-free code practices.

As these trends unfold, the role of human developers is likely to shift towards higher-level problem-solving, creative design, and AI oversight. By 2025, it’s projected that over 70% of professional software developers will regularly collaborate with AI agents in their coding workflows1. However, the path to ubiquity will depend on addressing key challenges such as reliability, security, and maintaining a balance between AI assistance and human expertise.

The future outlook for AI code assistants is one of transformative potential, with the technology poised to become an integral part of the software development landscape. As these tools continue to evolve, they will likely reshape team structures, development methodologies, and the very nature of coding itself.

Conclusion: A Tool, Not a Panacea

AI code assistants have irrevocably altered software development, delivering measurable productivity gains but introducing new technical and societal challenges. Current metrics suggest they are transitioning from novel aids to essential utilities—63% of enterprises now mandate their use. However, their ascendancy as the de facto standard hinges on addressing security flaws, mitigating cognitive erosion, and fostering equitable upskilling. For organizations, the optimal path lies in balanced integration: harnessing AI’s speed while preserving human ingenuity. As generative models evolve, developers who master this symbiosis will define the next epoch of software engineering.

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