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How to Work with AI, Not Against It, as a Developer

AI is here to work with developers, not replace them.
Tools like GitHub Copilot and ChatGPT can enhance speed, but human thinking is essential in decision-making.
AI can handle repetitive tasks like boilerplate code, allowing developers to focus on architecture and user needs.
Developers should see AI as a learning tool, leverage it for explanations, code breakdowns, and different approaches while honing human skills of communication, empathy, design, and judgment.

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Medium

291

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The Strategic Advantage of Custom Software Development in 2025

Custom software development offers precise alignment with company goals, user needs, and operational workflows, providing competitive advantages that off-the-shelf tools lack.
Companies in 2025 are prioritizing flexibility, leading to a growing demand for bespoke software that delivers real value.
Investing in custom software development in 2025 can lead to improved productivity, customer satisfaction, and profitability for businesses.
Choosing a skilled software development company like Ashlar in the U.S. ensures high-performance, custom-built software that evolves with your business goals, making custom development a driver of innovation and competitive differentiation.

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Towards Data Science

382

How Would I Learn to Code with ChatGPT if I Had to Start Again

The article discusses the author's coding journey and various programming approaches learned over time.
Key strategies shared include choosing the right framework, breaking down projects, Googling each step, and systematic coding.
Strategies for troubleshooting bugs are detailed, involving checking documentation, searching on Google/Stack Overflow, intuition, and testing.
The shift in new coders using ChatGPT as a study buddy is noted, along with its benefits and limitations in the coding learning process.
A scenario of debugging a Python script using ChatGPT is presented, highlighting how it can offer personalized guidance and concept clarifications.
The advantages of using ChatGPT in coding, such as efficient troubleshooting and concept clarification, are outlined.
The limitations of relying solely on ChatGPT, including lack of real-time interaction and potential extra debugging time, are discussed.
Recommendations are provided, including leveraging VScode extensions for auto code-completion tasks and balancing ChatGPT assistance with traditional learning methods.
The importance of diverse learning methods, collaboration for problem-solving, and practical coding practice is emphasized.
The author's reflections on the coding journey stress the importance of integrating traditional practices with innovative tools like ChatGPT and auto code-completion tools.
Overall, the article explores the role of ChatGPT in coding education and the need for a balanced approach to learning and problem-solving in programming.

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Medium

216

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Just Stop Writing Python Functions Like This!!!

Python functions packed with flags, messy logic, and unclear responsibilities can lead to chaotic code.
It's important to avoid writing functions that rely heavily on flags for different functionalities.
Instead of using multiple flags, focus on writing functions that have clear, singular purposes for better code maintainability.
By following best practices such as using type hints for clarity and ensuring functions perform only one task, you can write cleaner and more readable Python functions.

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Medium

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The Future Is Loud: How Tech Is Rewriting the Rules of Music

Technology has revolutionized the music industry, making it more accessible for artists to create music from home.
Independent artists are now able to share their music directly with global audiences, bypassing traditional gatekeepers.
The incorporation of smart tech like machine learning is enabling artists to experiment with new sounds and collaborate in innovative ways.
Despite challenges like fair pay and burnout, the music industry is experiencing a moment of increased accessibility, wider audiences, and enhanced creative freedom.

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Towards Data Science

450

Modern GUI Applications for Computer Vision in Python

Computer vision engineers often need visual feedback for image processing tasks, and interactive GUI applications can be helpful for this purpose.
OpenCV provides basic interactive elements for creating GUIs in Python for computer vision projects.
The article outlines setting up the environment with required packages, building a GUI application using OpenCV and customtkinter for real-time image processing.
It demonstrates displaying webcam feed, using keyboard inputs for filters, adding captions to images, implementing sliders for filter selection, and applying various image processing filters like grayscale, blur, threshold, edge detection.
To enhance the GUI appearance and user experience, a modern GUI using customtkinter is introduced.
The article also discusses multithreading to separate image processing from the UI to prevent blocking the main thread during heavy processing tasks.
A queue is utilized for synchronization between threads to ensure smooth updating of frames without flickering in the GUI.
The code examples and steps provided offer a comprehensive guide to building interactive GUI applications for computer vision projects in Python.
The article concludes by emphasizing the combination of Tkinter and OpenCV for creating modern GUI applications, with a Github repository link for the demo code.
The interactive GUI applications enable efficient iteration and visualization for computer vision tasks, enhancing the development process and user experience.
Overall, the article highlights practical techniques and considerations for developing modern GUI applications tailored to computer vision projects.

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Towards Data Science

248

Why Are Convolutional Neural Networks Great For Images?

The Universal Approximation Theorem states that a neural network with a single hidden layer and a nonlinear activation function can approximate any continuous function.
Different neural network architectures are developed for various tasks, such as using transformers for natural language processing and convolutional networks for image classification.
Neural network architectures are inspired by the structure in the data, particularly from a physics perspective that involves symmetry and invariance.
Convolutional neural networks work well with images by preserving local information through kernels with learnable parameters, reducing the need to flatten all pixels and saving memory and computational resources.

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Towards Data Science

Beyond Glorified Curve Fitting: Exploring the Probabilistic Foundations of Machine Learning

Machine learning involves distributing probabilities across all possible outcomes, showing how confident models are in their predictions.
Understanding the probabilistic view helps in making better decisions under uncertainty and increasing trust in model predictions.
Probabilistic models treat uncertainty as random variables and focus on learning probability distributions instead of fixed predictions.
Supervised learning involves making predictions based on known examples, while unsupervised learning focuses on understanding data structure without labels.
Reinforcement learning involves learning from feedback by taking actions and receiving rewards or punishments.
The probabilistic view in machine learning helps in capturing uncertainty, diversifying explanations, and making adaptable models.
Machines learn policies under uncertainty in reinforcement learning to maximize long-term rewards.
Probabilistic machine learning is more robust, adaptable, and interpretable, providing transparent and trustworthy models.
Understanding the probabilistic view is essential for dealing with uncertainty and making informed decisions in various fields.
References and resources for further learning on probabilistic machine learning are provided for those interested in exploring the topic.

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Knowridge

328

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How tiny iron crystals are turning ordinary wood into a super-strong steel alternative

Engineers discovered a way to make ordinary wood stronger by adding tiny iron particles known as ferrihydrite to red oak.
The breakthrough could lead to eco-friendly alternatives to steel and concrete in construction, furniture, and flooring.
The research involved strengthening hardwood at the cellular level without changing its weight or flexibility by infusing it with iron-based minerals.
The study was a collaboration involving researchers from Florida Atlantic University, the University of Miami, and Oak Ridge National Laboratory, with findings published in ACS Applied Materials and Interfaces.

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Medium

437

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How I Earned $500 a Week with AI Voice Cloning

Discover how a content creator increased their income by $500 a week using AI voice cloning technology.
The journey began with skepticism but led to the adoption of an app utilizing the 'Vocal Identity Matrix' for personalized voice cloning.
The app transformed content creation by providing emotionally engaging voiceovers that resonated well with audiences.
By saving time, enhancing authenticity, and boosting viewer engagement, the user successfully earned $500 a week with dynamic content creation.

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Pymnts

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Report: Circle Rejects Ripple’s $4 Billion to $5 Billion Takeover Bid

Circle Internet Group rejected a $4 billion to $5 billion takeover bid from Ripple, citing the amount as too low.
Ripple is still interested in a deal with Circle but has not decided whether to make another offer. Circle is focusing on its initial public offering (IPO).
Ripple acquired prime brokerage Hidden Road for $1.25 billion, becoming the first cryptocurrency company to own and operate a multi-asset prime broker.
An $8.2 billion wave of crypto deals, including Ripple's acquisition of Hidden Road, was initiated by the cryptocurrency-friendly White House.

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Towards Data Science

361

Turning Product Data into Strategic Decisions

Product Analytics involves tracking, analyzing, and interpreting customer engagement to drive adoption and retention.
Product-Market Fit (PMF) signifies a product solving a meaningful problem for customers, with indicators like cohort retention trends and PMF surveys.
Segmentation, Targeting, and Positioning (STP) framework helps in aligning product development and growth strategy based on user segments identified through analytics.
The 4Ps framework (Product, Price, Place, Promotion) combined with product analytics informs decisions on optimizing features, pricing, distribution, and marketing.
Core metrics for product health include retention rate, engagement, Net Promoter Score (NPS), activation rate, and conversion rate.
Aligning product analytics with business goals involves linking metrics to strategic objectives, using data for decisions, and tracking market trends.
Institutionalizing a data-driven culture and communication ensures data fluency across teams and enhances decision-making based on insights.
Product analytics, when integrated strategically, provides a source of truth, feedback loop, and shared compass for building products with lasting value.
To leverage product analytics effectively, track the right metrics, adopt analytics frameworks, align data with business objectives, and foster a culture of data-informed action.
By combining evidence and judgment at the intersection of analytics and leadership, real progress in product development and growth can be achieved.

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Siliconangle

122

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OpenText expands restructuring initiative after larger-than-expected sales drop

OpenText Corp. plans to cut 1,200 roles as part of a restructuring effort aimed at reducing annual expenses by up to $550 million.
The company reported a sales drop to $1.254 billion in the third quarter, down from $1.44 billion a year earlier, attributing much of it to the sale of its AMC business unit.
OpenText's cloud sales increased by 1.8% year-over-year to $463 million, a bright spot amidst the revenue decline.
The expanded restructuring plan now aims to save between $490 million and $550 million annually, with the company intending to cut 1,200 roles and reduce its real estate footprint.

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Engadget

180

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Meta is a mulling ads and a 'premium' version of its AI assistant, Mark Zuckerberg says

Meta is planning to monetize its generative AI assistant by showing product recommendations, ads, and offering a premium subscription service for additional functionality, according to Mark Zuckerberg.
Currently, the focus is on growing Meta AI's usage with an emphasis on scaling and deepening engagement for at least a year before building out the business aspect.
Zuckerberg aims for Meta AI to be the most used AI assistant globally and highlighted the importance of the recently introduced standalone app for attracting US users.
Meta's approach to monetizing the assistant aligns with its strategy for Threads, with efforts to enhance user engagement through recommendations systems and exploring AI models for content recommendations.

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Medium

401

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From Software Engineer to Head of Product: 5 Lessons I Wish I Knew Sooner

Transitioning from Software Engineer to Head of Product involves a shift in mindset towards creating great products and leading teams.
Moving from focusing solely on writing code to considering the bigger picture is crucial for success in product management.
The journey from Software Engineer to Head of Product is challenging yet rewarding, requiring a different approach to problem-solving.
While there's no perfect guidebook for this transition, there are valuable lessons to be learned along the way for those considering or already in this career shift.

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