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iPhone 17 Series: The Future of 8K Video Recording

The iPhone 17 introduces 8K video recording, providing ultra-clear and sharp footage for filmmakers, vloggers, and content creators.
ProRes and HDR10+ support enable high-dynamic-range videos with true-to-life colors for better color grading and post-processing.
Upgraded sensor-shift stabilization technology ensures smooth, shake-free videos, even in motion.
The iPhone 17 Pro models feature a periscope zoom lens for up to 10x optical zoom and improved storage options and battery life for optimized video recording.

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Medium

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Racket Syntax Cheat Sheet

The define form in Racket is used to name variables, functions, and constants.
Racket's lambda creates anonymous functions without a name.
Racket's if statement is a basic conditional form similar to standard if-else in Java, Python, and C#.
The cond form in Racket is used for more than two branches and offers better readability than nested if statements.
Racket's let form creates temporary bindings limited to a specific code block.
Racket's let* form allows variables to refer to those defined before it.
Racket's letrec form is used for defining mutually recursive functions.
Quoting in Racket allows treating data as literal values rather than for evaluation.
Racket's set! is used to change a variable's value after it's defined.
Racket uses '#lang' at the top of files to specify the language module.
The 'require' statement in Racket is used to import functions or data from another module.
Racket supports keyword arguments for functions, making it easier to understand arguments.
The match form in Racket allows unpacking and analyzing data using patterns.
Racket's struct is used for defining custom data structures with constructors, accessors, and predicates.
Racket allows declaring modules in the language to group and isolate code.
Racket supports mutable structs by adding the #:mutable flag.
Racket's define-values form returns the result of the first expression in a sequence.
Racket has built-in support for returning multiple values from functions.
Racket's syntax may feel unfamiliar initially, but understanding it leads to a natural flow.

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Medium

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Don’t Pay for a Course to Learn HTTP

HTTP is just structured text sent over a TCP connection.
An HTTP request consists of a start line, headers, and an optional body.
An HTTP response consists of a start line, headers, and an optional body.
The empty line (

) indicates the end of headers.

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Medium

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To Be or Not to Be Commented: The Eternal Question for Coders

Code comments have always been a topic of debate among developers.
While comments can provide critical context and aid in understanding complex logic, some argue that comments can become outdated and introduce confusion.
Many teams prefer a middle path, using comments sparingly to clarify non-obvious aspects of the code.
The ultimate goal is to write code that is understandable and maintainable, regardless of the level of commenting.

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Dev

253

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Hibernate is Not a Web Framework!

Hibernate is not a web framework and should not be classified as one.
A web framework is responsible for handling requests, responses, routing, and sometimes templating.
Hibernate is an ORM framework that facilitates database interactions, not serving web requests.
For web development, frameworks like Spring Boot, Quarkus, Play!, or Jakarta EE are more suitable.

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Dev

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AWS Graviton 3 > Graviton 4 for Vector Similarity Search

AWS Graviton 3 outperforms Graviton 4 in vector similarity search scenarios, delivering better performance and cost efficiency.
Graviton4 has a smaller SVE SIMD register size of 128 bits compared to Graviton3's 256 bits, affecting vector search performance.
The difference in SIMD register width impacts the efficiency of distance calculations in vector similarity search.
Execution throughput comparisons between Graviton3 and Graviton4 show advantages for Graviton3 in loading data efficiently.
Latencies in the CPUs are similar, but Graviton4 incurs a higher latency cost due to the smaller register width.
Benchmarks reveal that Graviton3 performs better in various vector search scenarios, including IVF and HNSW indexes.
Raw distance calculations demonstrate Graviton4's superiority with NEON kernels but show Graviton3's advantage with SVE kernels.
The regression in SVE register width for Graviton4 raises questions about the trade-offs in microarchitecture design choice.
Choosing the right microarchitecture for vector search use cases can significantly impact performance and cost efficiency.
The decision to use Graviton 3 over Graviton 4 for vector search tasks with SVE support is recommended for better performance.
In conclusion, careful evaluation based on benchmarks and specific use case requirements is crucial for selecting the optimal microarchitecture.

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Medium

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Keras: The Library For Seamless Deep Learning Innovation

Keras is a Python-based open-source deep learning library that simplifies and streamlines the model-building process.
It provides a high-level API that abstracts away the complexity of creating deep learning models.
Keras offers adaptability, a straightforward interface, and resources for various applications like time series forecasting, image recognition, and NLP.
In 2017, Keras was officially integrated into TensorFlow as its official high-level API, enhancing its capabilities and popularity.

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Medium

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How to Estimate π in the Woods

This article provides instructions on how to estimate π without using a computer.
The method involves using basic geometry, such as the relationship between the area and circumference of a circle.
By creating a diagram with a circle and two squares, it is possible to get a rough estimate of π.
The article explains the calculations and procedures to follow in order to estimate π in the woods.

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Dev

360

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Clean your Memory: From Finalize to Cleaner

Garbage collection in Java manages memory but does not clean up non-memory resources like sockets or file handles, leading to resource leaks and performance issues.
Introduced in Java 9, the Cleaner API provides a modern mechanism for resource cleanup, addressing the limitations of the deprecated finalize() method.
The finalize() method was deprecated due to unpredictable execution, performance overhead, memory leaks, and finalization queue mechanism issues.
Java Reference classes include Strong, Weak, Soft, and Phantom References, managed based on the reachability concept.
Cleaner, similar to Java Reference classes, is more efficient in managing external resources like files.
The Cleaner internally uses a combination of PhantomReference and a background daemon thread for efficient resource cleanup.
A comparison between Cleaner and try-with-resources reveals their differences in immediate vs. deferred cleanup timing and resource type considerations.
It is recommended to use Cleaner judiciously and follow best practices to avoid issues with lambda capturing, concurrency, and delegation of cleaning actions.
Java's Cleaner API offers a reliable way to manage non-memory resources efficiently, improving application performance and memory usage.
Understanding when and how to utilize Cleaner can help developers build more robust and memory-efficient Java applications.

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Dev

300

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This is why AI can't takeover my engineering job

AI can't take over engineering jobs because human intuition and problem-solving logic are still crucial.
Coding tasks completed by AI may contain bugs that require human intervention for resolution.
LLMs (Large Language Models) can only provide solutions based on information available on the web.
The importance of human visualization and understanding of problems in the industry persists.

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Medium

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Integrating ML model in React js

TensorFlow Lite is a streamlined version of TensorFlow, designed for mobile and embedded devices.
This tutorial shows how to create a React/Next.js app that can interact with a TensorFlow Lite model to auto-capture passport images directly in the browser.
The setup involves creating custom hooks to load the TFLite model and handle the video feed from the user's device.
Helper methods are provided to process frames from the video feed, draw bounding boxes, capture and crop the passport images.

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Medium

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Lambda Expressions in Java: Say Goodbye to Verbose Code!

Java lambda expressions provide a way to write cleaner and more concise code.
Lambda expressions in Java replace anonymous classes and provide a more efficient approach.
Functional interfaces in Java are essential for working with lambda expressions.
Examples of functional interfaces include Consumer and Predicate.

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Dev

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Emerging Trends in Java Garbage Collection

Efficient garbage collection is crucial for Java application performance as outdated algorithms can't cope with the demands of modern computing.
Java garbage collection has evolved over the years to keep up with evolving IT trends, including hardware advancements and changing software requirements.
There are now multiple garbage collection (GC) algorithms in Java, each designed for specific purposes, including Serial, Parallel, CMS, G1, Z, and Shenandoah.
Future developments in GC include improved features for Z GC, throughput enhancements for G1 GC, footprint reduction, and the implementation of a new algorithm called N2GC.

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Dev

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All React Concepts in One Read: Interview Insights

Components are the building blocks of React, representing parts of the UI like buttons or pages.
JSX in React allows for HTML-like syntax in JavaScript code, improving readability.
Using curly braces in JSX enables the injection of dynamic values and expressions.
Fragments in React help avoid unnecessary DOM elements, allowing you to return multiple elements.
Props enable data passing from parent to child components in React.
Passing components as props using the children prop aids in composing UI elements.
Keys are crucial in React for identifying elements efficiently in lists.
Rendering in React involves updating the Virtual DOM for efficient updates.
Event handling in React allows responses to user interactions like clicks or key presses.
State management in React involves using useState hook for dynamic data handling.

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Dev

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🎓💻 Is College Still Worth It for Aspiring Software Engineers? 💻🎓

In the tech-driven world, the debate on the value of college for software engineers has intensified.
Options include traditional degrees, coding bootcamps, online platforms, and self-teaching.
Pros of a college degree: comprehensive education, networking, credibility, and long-term growth.
Cons include high costs, time commitment, and outdated curricula for some.
Alternative pathways offer cost-effectiveness, focused learning, flexibility, and rapid entry into the workforce.
However, they may lack depth, credibility, networking opportunities, and quality assurance.
Consider career goals, financial situation, learning style, and industry trends when choosing.
Foundational knowledge, soft skills, and adaptability are crucial for success in the evolving tech landscape.
Strategies for success include building a portfolio, networking, staying updated, and interview preparation.
Choosing between college and alternative paths depends on one's preferences and goals in the tech industry.

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