Abdullah Al Osman Sajid

The Gap Between Processor and Software Industries and the Role of AI in Bridging It.  -------------------------------------------- The Backbone of Modern Innovation Processors and software are two fundamental pillars of the digital age. Together, they power everything from our smartphones and laptops to advanced robotics and cloud-based solutions. However, the interplay between these two fields reveals a striking imbalance: processors are advancing at an extraordinary rate, while software often struggles to keep pace with this evolution. This disparity creates a "technology gap" that limits the exploitation of processors' full potential. This article explores the root causes of this gap, focusing on how artificial intelligence (AI) can act as a bridge to close it. We will examine examples of processor specialization, highlight the challenges faced by software startups, and provide insights into the future of programming languages. Additionally, we will discuss the vital roles played by governments and academic institutions, along with the growing impact of climate change on the electronics industry. Finally, we will explore how AI and software innovations can address these global challenges. Read more ... https://lnkd.in/dxCvi_RK

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Why not JetPack Compose with DiffUtil? 🤔 In the world of Android development, DiffUtil has long been a go-to tool for efficiently managing dynamic lists in RecyclerView. But what happens when you switch to Jetpack Compose? 🤔 🔗 Full Article: https://ylnk.xyz/@NVJXVF I just wrote an in-depth article where I break down how you can create a custom DiffUtil-like function for Jetpack Compose, allowing you to efficiently update lists in LazyColumn and LazyRow. I also dive into the space and time complexities of this approach, discussing whether it's truly optimal for Compose or if you should stick to Compose's built-in list handling techniques. If you’re dealing with dynamic lists in Compose and are curious about the best practices for ensuring smooth performance and minimal re-compositions, this article is for you! 💡 Check it out and let me know your thoughts! #android #jetpack #compose #recyclerview #diffutil #kotlinmultiplatform #kmp #ios #cmm #techarticle #androiddevelopment #iosdevelopment #softwareengineerning #softwareengineer #rommansabbir

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🚀 Exciting News! 🚀 I'm thrilled to announce the launch of my latest npm package, antd-date-picker-nepali! 📅✨ I've been working with Ant Design (antd) for a while now. Recently, I needed a calendar in Nepali date format (BS). While there are existing packages for this, they aren't integrated with antd. Using them would mean inconsistent styles compared to the rest of the application. That's why I created a custom antd Nepali Date Picker, which seamlessly integrates Nepali dates into the antd UI. 🔗 Check it out on npm: antd-date-picker-nepali (https://lnkd.in/d7w8yxDC) Key Features: - Provides Nepali date picker functionality within the antd framework. - Ensures consistent styling with the rest of your antd-based application. Whether you're building applications with a Nepali user base or looking to enrich your UI with cultural diversity, antd-date-picker-nepali is designed to simplify your development process. Feel free to explore, contribute, and integrate it into your projects today! #React #NPM #OpenSource #AntDesign #TypeScript #UIComponents #DeveloperTools #NepaliDatePicker #JavaScript

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There's a massive scarcity of quality tech content which are free in Bengali, especially in fields like system design, competitive programming, distributed systems etc. That's why I started my own YouTube channel (Programming Masterclass - https://lnkd.in/gGVAw96q). The first video I made is on CAP Theorem, which is a very interesting topic in System design and Distributed systems. Here's the link: https://lnkd.in/gd4XA5Uy

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Dispatchers in Kotlin are essential for controlling the way coroutines are executed because they choose which thread or thread pool to use for each coroutine. When utilizing dispatchers in Kotlin pipelines, keep the following points in mind: Dispatcher Types: 1️⃣ Dispatchers.Default: This is used for CPU-intensive tasks. It uses a shared pool of background threads. 2️⃣ Dispatchers.IO: Optimized for IO-bound operations like network or disk access. It uses a shared pool of threads designed for blocking IO tasks. 3️⃣ Dispatchers.Main: Confines the coroutine to the main thread, typically used for updating the UI in Android applications. 4️⃣ Dispatchers.Unconfined: Starts the coroutine in the caller thread, but only until the first suspension point. The suspending function then determines which thread it resumes in. #dispatcher #coroutineKotlin

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5 Kotlin Interview Questions with Answers: Questions: 1. lateinit vs lazy in Kotlin 2. Difference between == and === in Kotlin 3. What is a JvmStatic Annotation in Kotlin? 4. What is a reified keyword in Kotlin? 5. Suspending vs Blocking in Kotlin Coroutines 1. lateinit vs lazy: `lateinit` is used for non-null, late-initialized vars, ideal for dependencies that cannot be initialized in the constructor. `lazy` is for vals, initializing them upon first access, useful for resource-intensive objects.   2. Difference between == and ===: `==` checks structural equality (via the equals method), while `===` checks referential equality, seeing if two references point to the same object. 3. JvmStatic annotation: This Kotlin annotation makes a member function of an object or companion object accessible as a static method from Java code, facilitating smoother Java-Kotlin interoperability. 4. Reified keyword: Used with inline functions, it allows type parameters to be accessed at runtime, which is normally not possible due to type erasure in generics. 5. Suspending vs Blocking: Suspending functions in coroutines free up the thread to do other tasks, unlike blocking, which keeps the thread occupied until the operation completes, leading to potential performance issues. #kotlin #android

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In this episode, we discuss Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization by Mohammad Samragh, Iman Mirzadeh, Keivan Alizadeh Vahid, Fartash Faghri, Minsik Cho, Moin Nabi, Devang Naik, Mehrdad Farajtabar. The paper presents HyperCloning, a technique for initializing large language models with smaller, pre-trained models to leverage their predictive power. This method allows large models to require less training time and fewer GPU hours by scaling up small models while preserving their functionalities. HyperCloning offers a viable solution to efficiently manage the high costs and time investments in training large language models.

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The interviewer starts by asking about my previous work experience and the projects I have worked on. They also ask why I want to join their company. Then, they move on to technical questions: 1. What is the document object and window.document in JavaScript? 2. What is Webpack, why do we use it, and can you mention any alternatives? 3. What are array functions in JavaScript? 4. What is event delegation? 5. What is debounce? 6. What is the difference between the put and patch methods? 7. what is Eslint and why use it? 8. What is oop? Could you tell me about abstraction? 9. What technologies are you currently using in your office projects, and what is your role in those projects? 10. Do you have any questions about our company? I can't recall all the questions they asked at the moment. About me: Medium: https://lnkd.in/dE6YtX9H Github: https://lnkd.in/duznyRW9 Frontend tricks page: https://lnkd.in/dHDH_6Ke #js #reactjs #web #interview #frontend #developer

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Amidst all the AI and machine learning hype, I wanted to create something simple and relaxing instead of using OpenAi API in my app and calling it an "AI" app :)) So, me and my friend Bilal Kashif built "Quotopia". it is a simple application built using Flutter that let you scroll through quotes, create and share your quotes too. Took it from the initial idea to posting it on the Play Store. Honestly, it made me realize that even a simple app comes with its challenges and edge cases, but that's what made it fun. We designed the UI using Figma and used quotes we found and scraped online. It was incredibly satisfying to finally scroll through the quotes in the app, and see it all come together. We stored around 300k quotes in a single SQFlite database and used Bloc Pattern for the architecture. The whole process was so enjoyable. It taught me that: "Sometimes, it's better to complete something simple than to chase cutting-edge projects that never get finished." #Flutter #Android #Figma #Design Do check it out: https://lnkd.in/dp7kQSjF

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LinkedIn Post: Day 11/365 DSA 🚀 💡 Problem: Find Maximum and Minimum Frequency of Numbers in an Array in C++ 🔍Task:   Given an array of numbers, our goal is to find and print: 1. A number with maximum frequency (occurs the most). 2. A number with minimum frequency (occurs the least). 🛠️ Unoptimized (Brute Force) Approach: In the brute force method, we: - Iterate over the array and count how many times each number appears. - Use nested loops to compare each element with all others. void bruteForce(vector<int> nums) {   int n = nums.size();   int max_freq = 0, min_freq = n + 1;   int max_elem = 0, min_elem = 0;   for (int i = 0; i < n; i++) {     int count = 0;     for (int j = 0; j < n; j++) {       if (nums[i] == nums[j]) count++;     }     if (count > max_freq) {       max_freq = count;       max_elem = nums[i];     }     if (count < min_freq) {       min_freq = count;       min_elem = nums[i];     }   }   cout << "Max Frequency: " << max_elem << " Min Frequency: " << min_elem; } ⏳ Time Complexity: O(n²) - Why?   We are using two loops, one to iterate over the array and another to count the occurrences of each number, resulting in O(n²) time complexity. 🚀 Optimized Approach: In the optimized solution, we: - Use a hash map (unordered_map) to store the frequency of each number in a single pass. - With this, we can easily find the maximum and minimum frequencies in linear time. #include <bits/stdc++.h> using namespace std; void optimizedApproach(vector<int> nums) {   unordered_map<int, int> freq_map;   int max_elem, min_elem;   int max_freq = 0, min_freq = INT_MAX;   // Count frequency of each element   for (int num : nums) {     freq_map[num]++;   }   // Find max and min frequency elements   for (auto &pair : freq_map) {     if (pair.second > max_freq) {       max_freq = pair.second;       max_elem = pair.first;     }     if (pair.second < min_freq) {       min_freq = pair.second;       min_elem = pair.first;     }   }   cout << "Max Frequency: " << max_elem << " occurs " << max_freq << " times\n";   cout << "Min Frequency: " << min_elem << " occurs " << min_freq << " times\n"; } int main() {   vector<int> nums = {3, 1, 4, 4, 5, 2, 6, 1, 1};   optimizedApproach(nums); } ⏳ Time Complexity: O(n) - Why?  By using a hash map, we reduce the problem to two single-pass traversals: one to count frequencies and another to find the maximum and minimum values. 💡Why Optimized is Better? 1. Efficiency:    - Brute Force: O(n²) is inefficient for large datasets since it checks every pair of elements.   - Optimized: O(n) drastically reduces computation by using a hash map for direct lookups and updates. 2. Space Complexity:    - Brute Force: O(1), but inefficient in time.   - Optimized: O(n) extra space for the hash map, but it saves time, making it ideal for real-world usage. #Day11 #DSA #DataStructures #Algorithms #CPP #ProblemSolving #Hashing #Frequency

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Apple's development environment often involves working with both Swift and Objective-C code. Navigating Apple's development environment often means juggling both Swift and Objective-C code. To make this easier for Swift developers, Apple sometimes introduces Swift-specific structs that mirror existing Objective-C classes. What are Mirror Structs? Mirror structs serve as Swift-specific counterparts to Objective-C classes, providing a more intuitive interface for Swift developers. Purpose: They act as a Swift-friendly layer, mirroring the functionality of Objective-C classes while aligning with Swift's syntax and principles. Design: These structs retain the core functionalities of their Objective-C equivalents but are expressed in a way that fits seamlessly into Swift's design ethos. Why Use Mirror Structs? 1/ Improved Readability Mirror structs leverage Swift's modern language features, making the code more concise and easier to read. Swift's emphasis on value types, properties, and methods contributes to this readability. 2/ Enhanced Safety Swift's robust type system offers additional safety checks, reducing the risk of errors that might arise when dealing directly with Objective-C classes. This safety net helps prevent common pitfalls and bugs. 3/ Better Integration By using mirror structs, developers can integrate existing Objective-C code into Swift projects more smoothly. This seamless integration fosters better code maintainability and collaboration between Swift and Objective-C codebases. Mirror structs facilitate a harmonious coexistence of Swift and Objective-C, enabling developers to harness the strengths of both languages while ensuring a consistent and developer-friendly coding experience. #Swift #iOS #Apple

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Learning new things always excite me. As a part of that, below is the minor achievement of this field. There is lot more to dive in. https://lnkd.in/g5S5MZnx Github Repo: https://lnkd.in/gEdkGiFR

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Lots of refactoring according to the gradle version catalog and material 3 in addition Kotlin 2.0.0 🙂. #jetpackcompoe #android #mvvm #movedb #opensource #weekendcoding Ref: https://lnkd.in/g2sZJ9wr

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Using MutableLiveData for Single-Shot Events Handling single-shot events in Android apps is a common challenge. This is another common issue I have seen at multiple places. Single-shot events are typically one-time notifications like showing a Toast, SnackBar, or dialog Using MutableLiveData for these types of events can lead to problems Why this is a problem? - MutableLiveData is designed to hold data and notify observers whenever the data changes. This makes it unsuitable for single-shot events, as it can lead to multiple notifications for the same event if not handled correctly. -  If MutableLiveData is used to trigger UI changes like showing Toast messages, there’s a risk of spamming the user interface if the observer is notified multiple times. Solution: Use Channel or SharedFlow for Single-Shot Events - A coroutine-based channel is a good option for sending single-shot events. It provides a way to handle one-time events and ensures that the event is consumed only once. - StateFlow or SharedFlow, use MutableSharedFlow with replay = 0 to handle single-shot events efficiently. This allows you to emit one-time events and collect them in a lifecycle-aware manner. By following these practices, you can avoid common pitfalls associated with single-shot events and ensure a smoother and more predictable user experience in your Android applications. Need help with Android Architecture or App Performance optimization ?? Contact me. #AndroidDevelopment #LiveData #Channel #SharedFlow #Kotlin #SingleShotEvents #UIHandling #ArchitectureComponents #Kotlin #LifecycleManagement #MemoryLeaks #ViewModel #BestPractices #AndroidDevelopers #SoftwareDevelopment #AndroidDev #SoftwareEngineer #AppPerformance #Android #PerformanceOptimization

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Android, Compose, Multiplatform & Server - Inject them all with Koin #koin #kotlin #compose #multiplatform #kmm #kmp #android #iOS

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🚀Embarking on the 100 Days of Code Challenge: Day 83🚀 1. Maximum Product Subarray Key idea: Keep track of both max and min products Why? Negative numbers can turn a min product into a max product Time complexity: O(n), Space complexity: O(1) 2. Maximum of All Subarrays of Size K Technique: Sliding window with a deque Maintains a decreasing order of elements in the window Time complexity: O(n), Space complexity: O(k) 3. Subarray Sum Equals K Approach: Prefix sum with hash map Counts cumulative sum frequencies Time complexity: O(n), Space complexity: O(n) Github: https://lnkd.in/gNvcvXQw https://lnkd.in/gPtRm5Pi https://lnkd.in/gzvfzn65

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🚀 iOS Interview Prep: Mastering Memory Management! 🧠 Whether you're a budding iOS developer or a seasoned pro, understanding memory management is crucial. I recently explored an insightful article by Dmytro Chumakov that breaks down key concepts like RAM vs. Storage and Swift’s value and reference types. 💡 Value types (structs, enums) make copies, while reference types (classes) share memory addresses. Understanding these distinctions is essential for optimizing code performance! 🔥 Check out the full article for more details: [Read Here](https://lnkd.in/d57SHGrD) 💻 #iOSDevelopment #Swift #InterviewTips

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