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Apple WWDC 2021, Facebook f8, Microsoft Build: What’s in it for Developers and Consumers this year

14 minutes read

Apple WWDC 2021 is the second all-virtual conference hosted by the company this year, one that will see both hardware announcements and software updates. WWDC 2021, which begins June 7 with the traditional Apple keynote will run the whole week long and will contain pavilions, daily recaps available to revisit, and more in this free-for-all developers virtual meet. 

WWDC 2021 is bringing big changes to iOS 15 and iPad OS 15, along with a new more powerful M2 chip and a redesigned MacBook Pro that gets rid of its maligned features like the Touch Bar, to re-introduce the HDMI port and MagSafe. 

Apple CEO Tim Cook began the keynote address welcoming “familiar” faces back again in the audience, virtual avatars aka Memoji instead of real people, given the ongoing pandemic. 

ALSO READ: Google I/O 2021: What’s in it for Developers and Consumers this Year

Here’s everything we noticed at the Apple WWDC 2021 keynote: 

iOS 15 

The new iOS update will come with a series of improvements including a better Facetime experience. FaceTime will now include features like Spatial Audio making calls more comfortable and natural, like you and the person on the other end are in the same room. The mic gets a Voice Isolation update, which, through the use of Machine Learning will block ambient noise and prioritize your voice. Another noticeable update is Wide Spectrum, to capture your voice and everything around you.  

The software update also introduces Portrait mode to blur backgrounds, and a grid view to enable multi-conversations with a highlighted tile to know who the speaker is. Users can also schedule individual FaceTime calls with Facetime links, similar to Zoom. Additionally, users can share their screen, music, TV show, or movie through a new feature called ShareTime, to enable a Watch Party of their own. FaceTime will, with this update, be supported on Android and Windows through a web browser.

iMessage, the messaging platform, available only on Apple devices, will now come with features that group similar images into galleries. A brand-new feature called “shared with you” will save links that people sent you and collects them in one place. It works across Safari, Apple Music, Apple TV, and Apple Podcasts.

ALSO READ: Here’s what a tech-enabled world will look like for future pandemic phases

Notifications will now have an updated design on the lock screen, featuring a clearer look. Titled the Focus feature, users can choose to go on Do Not Disturb mode or choose Work, Life hours to be able to receive notifications depending on their preferences, much like the OnePlus Zen Mode and Work-Life Balance feature that came with the OnePlus 7 series in 2019. 

Live Text, a new camera feature, will automatically identify and scan text or visuals in photographs. Another feature called Memories will use Machine Learning and AI to combine photos into galleries and add music from Apple Music. 

Apple Maps software is also updated with 3D data with this release. It now includes lanes, clearer city details, AR-led detailed directions, and more. The Weather app gets an interactive update where data and layout will change according to weather conditions. 

A new feature is also coming to AirPods called “conversation boost” which will help people better understand who they are talking to in real-time. Siri will be able to announce messages and read out your shopping list as well. Apple Wallet adds a new functionality which now includes corporate badges.

Quicknote is a fast and easy way to get to a note saved for later, while also allowing a user to jot notes using the Apple Pencil. Consumers can now add tags to organize their notes better and even mention others in shared notes.  

With iPadOS 15, Apple is adding features for multi-tasking, bringing widgets and app library to the iPad as well. Apple has also announced an iCloud+ subscription service with a focus on privacy. 

Privacy and Security: 

New privacy features, and a subscription-based iCloud+ was also announced at the keynote. Apple is now adding new privacy features across its devices. The Mail App, for instance, will have a feature called tracker-blockers to hide your IP address, location and other information that help building a digital personality for third-party apps. An App Tracker Report section in the Settings will allow users to see how often apps have used their info in the last seven days.

iCloud+ will also include a key feature called Private Relay, which essentially helps route web traffic through two separate servers, just like VPN.

Siri, on the other hand, has some new features including availability on third-party apps, and users can also request tasks from the Voice Assistant without an active internet connection. 

Speaking of legacy contacts, Apple has introduced a Digital Legacy Program that will help your trusted contacts to manage your account, close them et al, even when you’re no longer around. 

Digital Health: 

The latest Apple Watch software allows more interaction possibilities while also connecting health trackers that monitors everything from your gait to the sleep patterns via the Breathe app called Mindfulness and let’s you know as soon as it finds something out of the ordinary which can be addressed promptly. This is possible through Apple’s collaboration with a few electronic health record companies. If you’re away from your loved ones, the new software allows you to share health data too. 

New watch faces on Watch OS8 are available in Portrait mode and one also has the ability to write a text with their finger to send a text message. 

ALSO READ: What will ‘Behavioural Changes’ Mean for India’s Digital Health Future

Additionally, in the Workouts app, new workout types including TaiChi and Pilates have been added guided by popular names such as Jeanette Jenkins as well as a new Artist Spotlight series that offers workouts on the music of Lady Gaga, Keith Urban, and more.

macOS Monterey: 

At the WWDC 2021 keynote address last night, Apple announced a new version of macOS. Titled Monterey, after the pristine beach town in California’s central coast, the new macOS brings a number of features including multiple screen-usage while using the same mouse and keyboard across a Mac or an iPad. This feature is called Universal Control. 

iOS devices can (for the first time) beam their screen to a Mac, thanks to AirPlay. The Safari web browser has also got a redesign with new and improved features including tab grouping and tab bookmarking. 

What piqued your interest the most at this year’s Apple WWDC? Facebook f8, held earlier this month also had a few interesting announcements. Take a look. 

WIIFM at Facebook f8? 

Facebook f8, held on June 2 this year kicked off with a promise that Facebook was returning to its roots and focusing on the developer community for this year’s virtual event. 

“This year we are refocusing F8 on developers,” Mark Zuckerberg said. “Some of the most important services in the world started when someone looked at an existing issue, and just found a better way to build. And I’m optimistic that some of the next generation of services are going to start right here with you.”  

On the business messaging front, Facebook announced that its Messenger API for Instagram is available to all developers. The social media giant is also testing a way for people to opt into messaging with businesses through a new feature called Login Connect with Messenger. 

Through WhatsApp Business API, it’s now easier for businesses to get started with using the tool effectively for their businesses. Among its key updates, Facebook said it has reduced the entire API onboarding process from weeks to five minutes. The company also announced new WhatsApp messaging features with an aim to give people a quicker way to make a selection when interacting with a business’s chatbot on WhatsApp. 

Augmented Reality, AI and Machine Learning: 

Facebook’s development of its futuristic augmented reality glasses is still ongoing, but the company has exhibited broad ambitions in terms of its AR experiences built on its SparkAR software. In the near future, Facebook has said that it wants to make it easier for developers to build augmented reality effects for group calls via its new Multipeer API.  

The SparkAR platform now has 600,000 creators in 190 countries, with 2 million AR filters and effects created to date, according to Facebook. 

PyTorch, the deep learning framework co-developed by Facebook in 2016, is now becoming the default framework for building all its AI and machine learning models in the foreseeable future. 

“PyTorch not only makes our research and engineering work more effective, collaborative, and efficient, it also allows us to share our work as open-source PyTorch libraries and learn from the advances made by the thousands of PyTorch developers all over the world,” Facebook said in a blog post. 

Missed Microsoft Build? Here are key highlights tailor-made for you: 

Microsoft Build, also a developer conference, was also held virtually this year from May 25 to 27. 

Following his keynote address, Microsoft CEO Satya Nadella wrote on a LinkedIn post, “As computing becomes embedded in every aspect of our lives, there will be no longer such thing as the tech sector. The world will be transformed through tech intensity at scale. Every organization will need to not only adopt the latest technology, but more importantly, build their own unique digital technology, or be left behind.”

“We are building the platform for platform creators. It’s not about setting new rules or constraints that dictate how or what you should build. It’s not even about celebrating our own innovation. It’s about enabling your innovation and creating new opportunities for you,” he continued. 

From Microsoft Teams that allows users to complete projects from any location and at any time without needing to switch across different apps and data, to Windows Updates providing GUI support on Windows Subsystem for Linux (WSL), it will also allow seamless integrations with other workflows with Linux, GUI apps, and GPU-accelerated ML training.

In terms of privacy and security, Microsoft announced the integration of its Azure Security Center with GitHub. This integration will further enhance collaboration between the development and security teams. Interestingly, this collaborative effort will feature an update to enable security teams to be aware of the holistic development life-cycle instead of trying and fixing bugs only once the software is released. This measure will further allow the DevSecOps teams to run vulnerability scans, resolve findings, and visualize the security of workflows within their CI/CD pipeline.

The company also announced key updates to its Azure AI services, including Azure Bot Services, Azure Video Analyzer, and more. That’s not all, Microsoft also announced ML capabilities updates to accelerate its AI model deployment, namely Azure Machine Learning Managed Endpoints and Power Fx.

Automatic Aggregations was yet another feature that debuted at MS Build this year. Power BI dataflows that suitably handle streaming data sources, starting with Azure Event Hubs and Azure IoT Hubs, promises to make streaming data and real-time analytics accessible. 

Microsoft also introduced a low-code programming tool that allows users to write code without any prior coding knowledge. Called Power App Ideas, is the first-of-its-kind collaborative effort between Microsoft and artificial intelligence (AI) research company OpenAI. The app uses OpenAI’s Generative Pre-Trained Transformer-3 (GPT-3) AI model, among one of the highly advanced natural language AI models in the world today. 

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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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