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Agile Career Development Methodologies Team Management
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AI/ML Big Data Data Databases IoT
Software Design and Architecture
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Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

Generative AI has transformed nearly every industry. How can you leverage GenAI to improve your productivity and efficiency?

SBOMs are essential to circumventing software supply chain attacks, and they provide visibility into various software components.

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Bhala Ranganathan

DZone Core CORE

Principal Software Engineer at Microsoft

US

Joined Feb 2024

About

Seasoned software engineer and technical leader with more than a decade of expertise in cloud services and infrastructure especially Data and AI infrastructure. (Statements made in my articles represent my personal views and should not be interpreted as those of my employer.)

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Reputation: 1363
Pageviews: 58.3K
Articles: 15
Comments: 6
  • Articles
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Articles

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Synergy of Event-Driven Architectures With the Model Context Protocol
Event-driven systems, combined with the Model Context Protocol (MCP), result in more intelligent, scalable, and reliable AI-driven workflows.
June 25, 2025
· 1,870 Views · 2 Likes
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Evolution of Cloud Services for MCP/A2A Protocols in AI Agents
The adoption of MCP and A2A protocols is reshaping cloud service architectures by enabling the development of modular, interoperable, and scalable AI systems.
May 1, 2025
· 3,741 Views · 3 Likes
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Function Calling and Agents in Agentic AI
Function calling in agentic AI allows autonomous agents to dynamically execute tasks by invoking specific functions based on reasoning and goals.
April 1, 2025
· 1,738 Views
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The Impact of AI Agents on Modern Workflows
AI agents will transform traditional workflows, making them more dynamic, self-optimizing, and intelligent for greater efficiency and innovation.
March 13, 2025
· 3,445 Views · 1 Like
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Build a DIY AI Model Hosting Platform With vLLM
vLLM is an open-source tool that helps with hosting AI models using an efficient inference engine. It can be used to power LLMs in real products and services.
March 12, 2025
· 4,129 Views
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Improving Cloud Infrastructure for Achieving AGI
Achieving AGI requires improved cloud infrastructure, including more computational power, better algorithms, real-time data handling, and energy efficiency.
February 10, 2025
· 2,801 Views · 3 Likes
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Limitations of LLM Reasoning
This article provides an analysis of the reasoning limitations that exist in today's LLMs and the approaches to overcome them.
February 4, 2025
· 4,362 Views · 2 Likes
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Understanding Inference Time Compute
Inference time compute is a crucial factor in the deployment of machine learning models, where performance, efficiency, and user experience are key.
January 28, 2025
· 9,409 Views · 2 Likes
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Understanding HyperLogLog for Estimating Cardinality
Learn about the probabilistic algorithm designed to estimate the cardinality of a dataset with both high accuracy and low memory usage.
January 23, 2025
· 3,881 Views
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Serverless AI Inference
Serverless platforms abstract out the complexities involved in the deployment of machine learning models, handle compute demand and help reduce infrastructure costs.
January 22, 2025
· 5,972 Views · 1 Like
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Distributed Training at Scale
Distributed training accelerates machine learning training by splitting tasks across multiple devices or machines, improving performance and scalability.
January 15, 2025
· 2,880 Views
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The Importance of AI System Memory
The key to personalized AI intelligence is having scalable and controllable memory that can track and recall activities over a period of time.
January 14, 2025
· 3,347 Views · 1 Like
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Geo-Replication
Ensure business continuity and quick disaster recovery as you explore this overview of quorum, global quorum, and the two geo-replication types.
March 11, 2024
· 3,751 Views · 2 Likes
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Session Management in Distributed Databases
Session management in distributed databases is fundamental to ensuring data consistency. In this article, learn about session consistency and session tokens.
March 5, 2024
· 3,021 Views · 1 Like
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Model as a Service in the Generative AI Era
Learn about a cloud-based service where machine learning or Generative AI models are hosted in the cloud and are easily available for consumption through chat-based APIs.
February 28, 2024
· 3,977 Views · 1 Like

Comments

Limitations of LLM Reasoning

Feb 25, 2025 · Bhala Ranganathan

Indeed, the rapid evolution of AI is undeniable and the emergence of reasoning AI could potentially diminish the importance of prompt engineering. SDLC may need to undergo a transformation. It could involve integrating new methodologies focused on AI training and testing to ensure alignment with business objectives and regulatory requirements. The speed at which the industry adapts to these changes will be a fascinating development to observe.

Vector Storage, Indexing, and Search With MariaDB

Feb 04, 2025 · Alejandro Duarte

Nice! How does one get vectors for the given input prompt ? Another SQL query ?

Implement RAG With PGVector, LangChain4j, and Ollama

Jan 29, 2025 · Gunter Rotsaert

I had a good learning from this post. the step by step guide to try out is very useful. Do we need a machine with GPUs to try this end to end or is there a simulated environment ?

Top Tools for Object Storage and Data Management

Jan 28, 2025 · Vidyasagar (Sarath Chandra) Machupalli FBCS

Thank you! MinIO also has a kubernetes operator to support cloud deployments and would be interesting to know how other tools compare with this.

The Evolution of Conversational AI: From Chatbots to Coherent Conversations With GenAI and LLMs

Jan 27, 2025 · Caitlin Candelmo

Yes indeed, conversational AI has come a long way now with new LLMs introduced recently including the advent of AI agents.

Chain-of-Thought Prompting: A Comprehensive Analysis of Reasoning Techniques in Large Language Models

Jan 27, 2025 · Pier-Jean MALANDRINO

Thank you for analyzing the chain-of-thought prompting technique. It does enhance the reasoning capabilities of LLMs by breaking down complex problems into logical steps. There is also a parallel debate if LLMs can really think.

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