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React 18: From A Developer’s PoV

React 18, the much-awaited version of React is out with exciting features like automatic batching, a new API –startTransition, and streaming server-side rendering with support for Suspense. What’s so special about this newer version is its unique “concurrent rendering” method. In the earlier versions of React, the rendering process was synchronous and non-interruptible where the UI would lock during long render processes and not respond to user input instantly. Using React 18, the rendering process can be made asynchronous and can be interrupted, paused, resumed, and even abandoned enabling developers to create a more fluid user experience.

How to update from React 17 to React 18?

React 18 is currently released in alpha and can be downloaded using the command 

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A component is usually rendered like this

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However, to utilize the latest features, components need to be rendered like this:

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What’s there in React 18?

Automatic Batching

Automatic Batching is the rendering that occurs at the same time whenever triggered to update with multiple states at once. The previous version of React could only batch updates inside React event handlers. If the multiple state updates are triggered by a promise or a callback, their responses are not rendered at the same time. But with React 18, all renders are batched, meaning they’ll occur at the same time, regardless of their trigger.

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Here’s an example with a promise:

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Suspense

With Suspense, React 18 makes major performance improvements to SSR by making serving parts of an app asynchronously possible. Suspense helps in specifying what React should show when a part of the tree isn’t ready to render. For instance, in case there are four components: a Header, a Sidebar, a Banner component, and the Main component. If all four of them are stacked on each other like this 

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Then, the server would try to render them at once, slowing the entire page down. If the Header, the Sidebar, and the Main are more important for the readers, one can prioritize these over the Banner by wrapping the Banner component in Suspense tags:

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As a result, the server would first serve the Header, Side Bar, and Main component, and then a spinner would be displayed while the Banner waits to load.

Transitions

React apps are interactive, however, to make an app update itself as people interact with it, constant updating might cause the app to slow down significantly and give a poor user experience. Transition is a new React feature that differentiates between urgent and non-urgent updates. Transition updates transform the UI from one view to the next.

  • Urgent updates are the direct interactions like typing, clicking, pressing, etc., that need immediate response to match one’s intuition about how physical objects behave. Otherwise, they feel “wrong”. However, transitions are different because the user doesn’t expect to see every intermediate value on the screen. 

Single-user input should typically result in both an urgent and a non-urgent update for the best user experience. StartTransition API can be used inside an input event to tell React which updates are urgent and which are “transitions”.

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  • Non-urgent updates are wrapped in ‘startTransition’ and would get interrupted if more urgent updates, such as clicks or keypresses, emerge. If a user interrupts a transition (for example, by typing multiple characters in a row), React will discard any stale rendering work and render only the most recent update.

New Hooks

  1. UseId

useId is a new hook for creating unique IDs on both the client and the server while avoiding hydration mismatches. It’s most beneficial for component libraries that need to integrate with accessibility APIs that require unique IDs. This addresses a major problem that existed in React 17 and in its previous versions, but it’s even more critical in React 18 because of how the new streaming server renderer delivers HTML out-of-order.

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  1. useTransition

‘useTransition’ and ‘startTransition’ would allow marking some state updates as not urgent. By default, other state updates are considered urgent. React would allow urgent state updates (for example, updating a text input) to interrupt the non-urgent state updates (for example, count results).

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  1. useSyncExternalStore

‘useSyncExternalStore’ is a new hook that enables external stores to support concurrent reads by forcing updates to the store to be synchronous. It eliminates the necessity for useEffect when implementing subscriptions to external data sources, and is recommended for any library that integrates with a state external to React.

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  1. useDeferredValue

‘useDeferredValue’ helps to delay re-rendering a non-urgent part of the tree. It works in the same way as debouncing, although it offers a few advantages. React will attempt the deferred render directly after the initial render is reflected on the screen because there is no predetermined time delay. The deferred render is interruptible and doesn’t block user input.

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  1. useInsertionEffect

‘useInsertionEffect’ is a new hook that allows CSS-in-JS libraries to address the performance difficulties of injecting styles in the render. Unless you’ve already built a CSS-in-JS library we don’t expect you to ever use this. This hook will activate after the DOM is mutated, but before layout effects read the new layout. useInsertionEffect is even more important in React 18 because React yields to the browser during concurrent rendering, giving it a chance to recalculate the layout.

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Conclusion

With the introduction of React 18, there has been a drastic change in the world of web applications because of its unique offerings like concurrent mode and server-side rendering. The latest feature would make it easier to develop and maintain a code as well as make apps faster and more responsive to user interactions.

About the author:

Manikandan is a Technical Lead at Mantra Labs working on React/Angular-related projects. He is interested in learning about stock analyst trading algorithms, and in his free time, he loves to swim, cook, and play cricket and chess.

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Smart Machines & Smarter Humans: AI in the Manufacturing Industry

We have all witnessed Industrial Revolutions reshape manufacturing, not just once, but multiple times throughout history. Yet perhaps “revolution” isn’t quite the right word. These were transitions, careful orchestrations of human adaptation, and technological advancement. From hand production to machine tools, from steam power to assembly lines, each transition proved something remarkable: as machines evolved, human capabilities expanded rather than diminished.

Take the First Industrial Revolution, where the shift from manual production to machinery didn’t replace craftsmen, it transformed them into skilled machine operators. The steam engine didn’t eliminate jobs; it created entirely new categories of work. When chemical manufacturing processes emerged, they didn’t displace workers; they birthed manufacturing job roles. With each advancement, the workforce didn’t shrink—it evolved, adapted, and ultimately thrived.

Today, we’re witnessing another manufacturing transformation on factory floors worldwide. But unlike the mechanical transformations of the past, this one is digital, driven by artificial intelligence(AI) working alongside human expertise. Just as our predecessors didn’t simply survive the mechanical revolution but mastered it, today’s workforce isn’t being replaced by AI in manufacturing,  they’re becoming AI conductors, orchestrating a symphony of smart machines, industrial IoT (IIoT), and intelligent automation that amplify human productivity in ways the steam engine’s inventors could never have imagined.

Let’s explore how this new breed of human-AI collaboration is reshaping manufacturing, making work not just smarter, but fundamentally more human. 

Tools and Techniques Enhancing Workforce Productivity

1. Augmented Reality: Bringing Instructions to Life

AI-powered augmented reality (AR) is revolutionizing assembly lines, equipment, and maintenance on factory floors. Imagine a technician troubleshooting complex machinery while wearing AR glasses that overlay real-time instructions. Microsoft HoloLens merges physical environments with AI-driven digital overlays, providing immersive step-by-step guidance. Meanwhile, PTC Vuforia’s AR solutions offer comprehensive real-time guidance and expert support by visualizing machine components and manufacturing processes. Ford’s AI-driven AR applications of HoloLens have cut design errors and improved assembly efficiency, making smart manufacturing more precise and faster.

2. Vision-Based Quality Control: Flawless Production Lines

Identifying minute defects on fast-moving production lines is nearly impossible for the human eye, but AI-driven computer vision systems are revolutionizing quality control in manufacturing. Landing AI customizes AI defect detection models to identify irregularities unique to a factory’s production environment, while Cognex’s high-speed image recognition solutions achieve up to 99.9% defect detection accuracy. With these AI-powered quality control tools, manufacturers have reduced inspection time by 70%, improving the overall product quality without halting production lines.

3. Digital Twins: Simulating the Factory in Real Time

Digital twins—virtual replicas of physical assets are transforming real-time monitoring and operational efficiency. Siemens MindSphere provides a cloud-based AI platform that connects factory equipment for real-time data analytics and actionable insights. GE Digital’s Predix enables predictive maintenance by simulating different scenarios to identify potential failures before they happen. By leveraging AI-driven digital twins, industries have reported a 20% reduction in downtime, with the global digital twin market projected to grow at a CAGR of 61.3% by 2028

4. Human-Machine Interfaces: Intuitive Control Panels

Traditional control panels are being replaced by intuitive AI-powered human-machine interfaces (HMIs) which simplify machine operations and predictive maintenance. Rockwell Automation’s FactoryTalk uses AI analytics to provide real-time performance analytics, allowing operators to anticipate machine malfunctions and optimize operations. Schneider Electric’s EcoStruxure incorporates predictive analytics to simplify maintenance schedules and improve decision-making.

5. Generative AI: Crafting Smarter Factory Layouts

Generative AI is transforming factory layout planning by turning it into a data-driven process. Autodesk Fusion 360 Generative Design evaluates thousands of layout configurations to determine the best possible arrangement based on production constraints. This allows manufacturers to visualize and select the most efficient setup, which has led to a 40% improvement in space utilization and a 25% reduction in material waste. By simulating layouts, manufacturers can boost productivity, efficiency and worker safety.

6. Wearable AI Devices: Hands-Free Assistance

Wearable AI devices are becoming essential tools for enhancing worker safety and efficiency on the factory floor. DAQRI smart helmets provide workers with real-time information and alerts, while RealWear HMT-1 offers voice-controlled access to data and maintenance instructions. These AI-integrated wearable devices are transforming the way workers interact with machinery, boosting productivity by 20% and reducing machine downtime by 25%.

7. Conversational AI: Simplifying Operations with Voice Commands

Conversational AI is simplifying factory operations with natural language processing (NLP), allowing workers to request updates, check machine status, and adjust schedules using voice commands. IBM Watson Assistant and AWS AI services make these interactions seamless by providing real-time insights. Factories have seen a reduction in response time for operational queries thanks to these tools, with IBM Watson helping streamline machine monitoring and decision-making processes.

Conclusion: The Future of Manufacturing Is Here

Every industrial revolution has sparked the same fear, machines will take over. But history tells a different story. With every technological leap, humans haven’t been replaced; they’ve adapted, evolved, and found new ways to work smarter. AI is no different. It’s not here to take over; it’s here to assist, making factories faster, safer, and more productive than ever.

From AR-powered guidance to AI-driven quality control, the factory floor is no longer just about machinery, it’s about collaboration between human expertise and intelligent systems. And at Mantra Labs, we’re diving deep into this transformation, helping businesses unlock the true potential of AI in manufacturing.

Want to see how AI-powered Augmented Reality is revolutionizing the manufacturing industry? Stay tuned for our next blog, where we’ll explore how AI in AR is reshaping assembly, troubleshooting, and worker training—one digital overlay at a time.

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