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Implementing Custom Evaluation Metrics in LangChain for Measuring AI Agent Performance

As AI and language models continue to advance at breakneck speed, the need to accurately gauge AI agent performance has never been more critical. LangChain, a go-to framework for building language model applications, comes equipped with its own set of evaluation tools. However, these off-the-shelf solutions often fall short when dealing with the intricacies of specialized AI applications. This article dives into the world of custom evaluation metrics in LangChain, showing you how to craft bespoke measures that truly capture the essence of your AI agent's performance.

Enhancing Quality Control with AI: Smarter Defect Detection in Manufacturing

In today's competitive manufacturing landscape, quality control is paramount. Traditional methods often struggle to maintain optimal standards. However, the integration of Artificial Intelligence (AI) is revolutionizing this domain. This article delves into the transformative impact of AI on quality control in manufacturing, highlighting specific use cases and their underlying architectures.

The Future of Budgeting: AI Assistants for Real-Time Financial Insights

AI-driven financial assistants are redefining personal finance. These intelligent tools offer real-time insights, automated tasks, and tailored financial advice. Let's delve into the future of budgeting and how AI is revolutionizing financial management.

Leveraging Databricks Feature Store for Machine Learning Feature Management

The rapid evolution of machine learning has underscored the critical role of effective feature management in the success of ML projects. As organizations increasingly leverage ML, the challenges of managing, sharing, and reusing features across diverse models and teams become more pronounced. Databricks Feature Store emerges as a powerful solution, streamlining feature management and accelerating ML development.

Implementing Task Planning and Execution Using LangChain for Complex Multi-Step Workflows

In order to apply LLM to the real world problems, the ability to handle complex, multi-step workflows has become increasingly crucial. LangChain is a powerful framework that has become very popular in the AI community for building complex workflows on top of the LLMs. Today, we're exploring how LangChain can be leveraged for implementing task planning and execution in complex scenarios.

How to Implement Custom Retrieval Strategies in LlamaIndex

This blog delves into the basics of retrieval in LlamaIndex, and then progresses to advanced techniques like recency-aware, context-aware, and hybrid retrieval strategies.

How to optimize TensorFlow models for Production

This guide outlines detailed steps and best practices for optimizing TensorFlow models for production. Discover how to benchmark, profile, refine architectures, apply quantization, improve the input pipeline, and deploy with TensorFlow Serving for efficient, real-world-ready models.

The Impact of Generative AI on Customer Data Platforms

In this blog, we explore the transformative impact of generative AI on Customer Data Platforms (CDPs), examining its role in personalizing customer experiences, enhancing predictive analytics, and driving dynamic customer journeys.

How to build a RAG Using Langchain, Ollama, and Streamlit

In this blog, we guide you through the process of creating RAG that you can run locally on your machine. This journey will not only deepen your understanding of how cutting-edge language works but also equip you with the skills to implement them in your own projects.

Introduction to Langchain Agents

In this blog, explore the potential of LangChain agents, a framework powered by large language models, to create intelligent applications that excel in natural language processing, text generation, and more.

Large Language Models: A Comprehensive Exploration

This blog explores large language models (LLMs), in natural language processing, covering their architecture, training methodologies, applications, ethical considerations, limitations, and future implications. It delves into the challenges of computational resources, bias, privacy, and environmental impact. By understanding LLMs and addressing these challenges, we can responsibly leverage their power for beneficial use.

Transforming Industries with Generative AI & Large Language Models

Generative AI and Large Language Models are transforming industries across the globe, offering unprecedented opportunities for innovation and growth. In this blog, we will explore the applications and use cases of Generative AI and LLMs in different industries along with the challenges & considerations associated with the technology.

How to optimize large deep learning models using quantization

Quantization is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we demonstrate optimization of large deep learning model using quantization.

Electron vs Tauri

Are you considering using either Tauri or Electron for your next project? If so, you’re probably wondering which one to go with. Tauri and Electron are both popular options for developing desktop and web applications, but they each have their advantages & disadvantages. In this blog post, we’ll compare the two and help you decide which one is best for your project.

Implementing Concurrent Data Updates with Optimistic Locking

Optimistic concurrency control (OCC), also known as optimistic locking, is a concurrency control method applied to transactional systems. In this blog, we talk about implementing concurrent data updates with Optimistic Locking.

Explainable AI with Shap

Explainable AI is a key concept in Machine Learning/AI to explain why your model is making the predictions. It helps us understand how good a model is. In this blog, we cover how you can use a game theory-based method called Shapley Values to explain what's happening inside the ML model.

Microservices Architecture

In recent years, we have seen the migrations from traditional monolithic to microservices, conducted by various tech giants and mid-sized businesses. Developers now, enjoy the freedom to work on the allocated microservice or microservices without the fear of breaking down the entire system. It is not only a boon for developers but for the organization as well, as they can make their applications highly scalable and ready for market faster. In this blog, you will get a detailed understanding about Microservices.

Saga microservice pattern

Data consistency across microservices in dispersed transaction scenarios can be managed with the help of the Saga design pattern. A saga is a series of transactions that updates each service and broadcasts a message or event to start the subsequent transaction step. The saga executes compensating transactions that cancel out the previous transactions if a step fails.

Marketing 2025: Impact of AI on Marketing & MarTech

AI integration on Marketing Strategies has been a trending topic for five straight years now, and it's meant to stay. The "ifs" and "buts" have already been replaced by "hows" in the realm of the AI-driven digital marketing industry. check the ways (as far we can predict) AI will be impacting the Marketing & MarTech industry in the near future

The Role Of AI In Customer Service

Artificial Intelligence provides 24/7 availability, quick response using Machine Learning, load scalable systems, etc in Customer Service.

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