AI Engineering & Systems Design
Hands-on AI engineering and systems design: large language models, retrieval-augmented generation, data infrastructure, model experimentation, architecture, and technical implementation.
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Running Voicebox Backend End-to-End on Google Colab with GPU-Based Audio Transcription
The Voicebox backend was successfully deployed and tested end-to-end within a Google Colab environment using a GPU runtime. After setting up the repository, installing required dependencies, and starting the…
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The Rise of Agentic SQL in Modern Data Infrastructure
Database Is No Longer Passive Why Agentic SQL Changes the Role of Data Infrastructure For the last decade, databases were treated like storage engines. Passive systems. You inserted data.Queried…
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The 243-Line GPT: Why a Tiny Script Is Changing How People Understand AI
In the world of artificial intelligence, models are usually associated with enormous complexity. Billions of parameters.Distributed GPU clusters.Massive training pipelines. But recently, a remarkably small piece of code has…
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How Convin Built Its Contact Center LLM
Convin took a bold step: instead of relying on GPT-style APIs, it built its own 7-billion-parameter LLM, trained on 200B tokens with deep coverage of Indic and code-mixed languages.…
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Grok 3: The Next Leap in AI by xAI
Elon Musk’s xAI has just unveiled Grok 3, a major evolution in AI capabilities, marking a significant milestone in the competition with OpenAI, Google DeepMind, and Anthropic. With an…
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Integrating RAG API with Vertex AI Vector Search for Enhanced LLM Grounding
Retrieval-Augmented Generation (RAG) combines the power of retrieval systems with generative models to answer queries based on both pre-trained knowledge and external datasets. By pairing the RAG API with…
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Generative AI with Vertex AI: Best Practices in Prompt Design
Generative AI is transforming how we approach natural language processing and content creation. Google Cloud’s Vertex AI platform offers robust tools for leveraging generative AI models, with a strong…
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Engineering the Future of AI: Practical Use Cases and Technical Workflows
As AI continues to evolve, the scope of its application expands. Below, we dive into practical use cases, breaking down technical workflows, core algorithms, and the components required to…
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How to Build an AI Application with Next.js, Cursor, and Fal.ai
In today’s digital world, building AI-driven web applications has become significantly easier with a multitude of tools and frameworks available at our fingertips. In this guide, we’ll walk through…
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The Essential Guide to Prompt Engineering for AI Success
Generative AI models, such as GPT-4, are at the forefront of technological innovation, transforming industries from healthcare to creative writing. These models have shown an incredible capacity for tasks…
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Unlocking the Power of Hugging Face for AI and ML
In the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML), few platforms have made as significant an impact as Hugging Face. Originally recognized for its innovations…
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Advanced Prompt Engineering: 5 ChatGPT Frameworks to Drive Better Outputs
AI tools like ChatGPT have revolutionized the way businesses operate, especially in content creation, marketing strategy, and product management. However, to truly harness the power of these models, the…
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Healthcare AI · Agentic AI · AI Engineering · Product Strategy