CodeLink’s Substack

CodeLink's Substack is a technical blog focusing on emerging technologies, UX/UI design, and practical applications of AI/ML. It provides insights on software development practices, from prototyping to deployment, and explores innovations in image generation, search optimization, GDPR compliance, and cost-effective solutions in technology.

Software Development UX/UI Design Artificial Intelligence Machine Learning Technological Innovation Data Protection and Compliance Performance and Scalability Optimization

Top posts of the year

And their main takeaways

AImagine: Pioneering Hyperrealistic AI Image Generation

19 implied HN points • 18 May 23
🕹 Technology AI Image Generation DevOps Security Privacy
  1. AI technology is revolutionizing image generation and manipulation, offering new creative possibilities and demand
  2. AImagine app by CodeLink stands out for its hyperrealistic results and high level of customization in generating unique images
  3. Utilizing innovative technologies like the stable diffusion model, Flutter, and Python, AImagine offers a seamless user experience and efficient server-side processing
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Cost-Saving Machine Learning Deployment Tips!

0 implied HN points • 11 May 23
🕹 Technology Machine Learning Kubernetes Cost Optimization Implementation
  1. Deploying machine learning models on GPU cores can be costly due to server prices and lack of scalability.
  2. Using Kubernetes and KEDA for autoscaling GPU nodes can significantly reduce costs and improve scalability.
  3. Implementing cost-optimized ML on production can be achieved by using K8s and autoscaling GPU nodes, resulting in substantial cost savings.

Báo Nói Application: A Guide to Building High-Quality Text-to-Speech Datasets

0 implied HN points • 28 Jun 23
🕹 Technology AI Data Collection Open Source Text-to-Speech
  1. High-quality data is essential for training accurate and natural-sounding text-to-speech AI models.
  2. Cutting-edge tools like annotation software and ASR services are pivotal for efficient data collection in developing text-to-speech AI models.
  3. Collaboration and data sharing drive innovation in the AI community, enhancing the representation of diverse perspectives and voices in AI-generated speech.

How to Use AI/ML Models for Your Projects

0 implied HN points • 24 Nov 23
🕹 Technology Integration Model optimization Frontend Development
  1. AI is accessible even if you don't have a background in it, thanks to tools and platforms available.
  2. Integrating AI into projects can be done conveniently through API services like those offered by OpenAI, Google Cloud Platform, Azure, and AWS.
  3. Bringing AI to the frontend, optimizing model size and latency, and exploring resources like HuggingFace and TensorFlow.js are key in leveraging AI's potential in development projects.

ML & AI: From Problem Framing to Integration

0 implied HN points • 20 Sep 23
🕹 Technology Machine Learning Artificial Intelligence Integration
  1. Effective problem framing is crucial in ML engineering to avoid complex solutions that don't deliver results.
  2. For model selection, consider using pre-trained models for common tasks and build custom datasets for niche problems.
  3. During model training, focus on evaluating performance, optimizing latency, and documenting the model for integration into existing systems.