Reactive AI vs Proactive (Agentic) AI: Architectural Differences that Matter
Introduction: Artificial intelligence has been developing quickly, but still a lot of systems function reactively and can only respond to a situation once it has occurred. This reactive AI usage has a major drawback, as it only takes the present into account and nothing else. Moreover, it is not able to predict the future and…
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Priyadharshini
Integrating AI into CI/CD Pipelines
Introduction: Everyone in software talks about CI/CD these days. Continuous integration and continuous delivery merge code often, run some tests, and ship updates quickly. Sounds simple, right? In reality, it’s a headache. Builds blow up for reasons you can’t predict, half the tests are flaky, pipelines take forever, and when something goes wrong in deployment,…
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Priyadharshini
The Role of Quantum Computing in Cybersecurity: Hype or Reality
Introduction: Cybersecurity is built on an insecure foundation; the assumption is that certain mathematical problems are so hard that no computer can resolve them in a reasonable time. For decades, this assumption has kept online banking, private communications, e-commerce, and government systems secure. But the emergence of quantum computing challenges this very foundation. Quantum computers,…
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Priyadharshini
Autonomous Multi-Agent Systems vs Single Intelligent Agents – What’s More Scalable?
Introduction: Artificial Intelligence has reached a point where scalability defines competitive advantage. From self-driving cars to enterprise automation, there is an ever-growing need for intelligent systems that can learn, adapt, and execute autonomously. Traditionally, single-agent AI systems formed the basis of this evolution. These are independent entities capable of executing specified tasks using programmed intelligence.…
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Priyadharshini
Recent Advances in Computer Vision and their Business Applications
Introduction: Not long ago, the idea of computers recognizing people, objects, or entire environments seemed futuristic—something you’d expect in sci-fi movies rather than boardrooms or factory floors. Yet today, computer vision has slipped into our everyday lives almost unnoticed. From unlocking smartphones with a glance to self-checkout systems that let shoppers walk out of a…
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Priyadharshini
Top Ways Payoda’s AI Prevents Security Risks
Introduction: In the current day of a super-connected digital economy, cyber threats are developing faster than the suppliers can react most times. Sophisticated ransomware campaigns, insider data leaks, and AI-generated phishing attacks have all contributed to the complexity and unpredictability of the threat landscape, which is now more intelligent than ever. As per the 2024…
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Priyadharshini
How Payoda’s AI Automation Outperforms Outdated Tools
Introduction: Automation has been a major driver of digital transformation for a long time. It has been eliminating repetitive tasks and making operations more efficient. Moreover, many organizations have come to the realization that traditional automation tools, which have been a major breakthrough, can barely cope with the current dynamic business environments. These legacy systems…
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Priyadharshini
Payoda Insights: From Promise to Production in Agentic AI Frameworks
Introduction: When it comes to automation, autonomy, and intelligence, the introduction of Agentic AI has changed the game for enterprises. Unlike traditional AI that just follows the commands, Agentic AI has a high IQ that can interact and decide all by itself. The goal is a scalable, self-improving system capable of taking on the intricacies…
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Priyadharshini
Unlocking the Power of Sentence Transformers and Text Embeddings in LLMs
Introduction: Large Language Models (LLMs) have dramatically transformed the field of natural language processing (NLP). At the heart of their effectiveness lies one powerful concept: text embeddings. These text embeddings—dense vector representations of language—enable machines to understand, compare, and generate human-like text with remarkable precision. One of the most reliable tools for generating high-quality text…
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Priyadharshini
Fine-Tuning LLMs with LoRA Adapters: A Comprehensive Guide
Introduction Fine-tuning large language models (LLMs) can be computationally expensive and resource-intensive. Low-Rank Adaptation (LoRA) provides a more efficient and affordable way to fine-tune these models. In this blog, we’ll explore what Low-Rank Adaptation (LoRA) is, how it works, and how to apply it for fine-tuning an LLM. What is LoRA? Low-Rank Adaptation (LoRA) is…
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