News Aggregator

90% Cost Reduction With Prefix Caching for LLMs

Aggregated on: 2025-02-03 15:20:22

Do you know there’s a technique by which you could slash your LLM inference cost by up to 90%? Prefix caching is the idea that could save your application those much needed dollars. A game changing optimization technique that is not just for giants like Anthropic but also available to anyone using open- source LLMs. Let's pull back the curtain on this technique!

Building Neural Networks With Automatic Differentiation

Aggregated on: 2025-02-03 14:20:22

One of the biggest reasons for the fast pace of research and progress in modern AI is due to the availability of Python libraries such as PyTorch, TensorFlow, and JAX. Python itself is considered one of the easiest programming languages to pick up, and these ML/DeepLearning libraries make prototyping and testing sophisticated ML models much more accessible to engineers, researchers, and even enthusiasts. One key idea that has driven tremendous success in training large ML and neural network models is automatic differentiation (AD). It is the mechanism that enables backpropagation in neural networks. The main idea behind AD is to recursively calculate the partial derivatives (using the chain rule) for a neural network, which is represented as a directed acyclic graph (DAG). It’s a simple technique but very powerful.

Building RAG Apps With Apache Cassandra, Python, and Ollama

Aggregated on: 2025-02-03 13:20:22

Retrieval-augmented generation (RAG) is the most popular approach for obtaining real-time data or updated data from a data source based on text input by users. Thus empowering all our search applications with state-of-the-art neural search. In RAG search systems, each user request is converted into a vector representation by embedding model, and this vector comparison is performed using various algorithms such as cosine similarity, longest common sub-sequence, etc., with existing vector representations stored in our vector-supporting database.

Pydantic: Simplifying Data Validation in Python

Aggregated on: 2025-02-03 12:05:22

While exploring AI agents, I came across two interesting libraries - Pydantic and Logfire. In this article, you will learn about Pydantic with code examples and understand what Pydantic brings to the table in the world of Data validation for Python developers. Pydantic is a powerful Python library that uses type annotations to validate data structures. It's become an essential tool for many Python developers, especially those working on web applications, APIs, and data-intensive projects.

The Quest for HA and DR in Loki

Aggregated on: 2025-01-31 22:35:21

According to the 2016 Ponemon Institute research, the average downtime cost is nearly $9,000 per minute. These downtimes not only cost money, but also hurt the competitive edge and brand reputation. The organization can prepare for downtime by identifying the root causes. For that, they need information on how the software and infrastructure is running. Many software programs help aggregate this information, and one of the popular and most used tools is Loki. However, keeping Loki active under pressure is another problem. Recently, our team ran the single monolith instance of Loki as a private logging solution for our application microservices rather than for observing Kubernetes clusters. The logs were stored in the EBS filesystem. We wanted our system to be more robust and resilient, so we implemented High Availability (HA) and Disaster Recovery (DR) for our microservice application.

Building Custom Tools With Model Context Protocol

Aggregated on: 2025-01-31 21:20:21

Model Context Protocol (MCP) is becoming increasingly important in the AI development landscape, enabling seamless integration between AI models and external tools. In this guide, we'll explore how to create an MCP server that enhances AI capabilities through custom tool implementations. What Is Model Context Protocol? MCP is a protocol that allows AI models to interact with external tools and services in a standardized way. It enables AI assistants like Claude to execute custom functions, process data, and interact with external services while maintaining a consistent interface.

Web Scraping With LLMs, ScrapeGraphAI, and LangChain

Aggregated on: 2025-01-31 19:50:21

Now that we can scrape websites using Python and its libraries like BeautifulSoup, Requests, and Pandas, let’s take a step ahead and learn how we could simplify it further using LLM. Before we talk about the scraping part, let us understand the terminologies and what an LLM is. You are in the right place to learn about all these words if you are unfamiliar with LangChain, AI, or NLP. What Is LLM? LLM stands for large language model. It is a machine learning model trained on a large amount of data, referred to as a corpus, which consists of vast textual data. Large in the sense that there is a lot of data — terabytes — contained in the data. For example, an LLM may have seen terabytes of data, while a file on your computer system may be sized in gigabytes (GB). LLMs are able to respond to inquiries based on such textual data because of their thorough training. By utilizing them wisely, large language models may be applied to a variety of tasks, including summaries, Q&As, and translations. Just as Python provides libraries and frameworks, LLMs also have these resources.

Creating a Service for Sensitive Data With Spring and Redis

Aggregated on: 2025-01-31 18:28:56

Many companies work with user-sensitive data that can’t be stored permanently due to legal restrictions. Usually, this can happen in fintech companies. The data must not be stored for longer than a predefined time period and should preferably be deleted after it has been used for service purposes. There are multiple possible options to solve this problem. In this post, I would like to present a simplified example of an application that handles sensitive data leveraging Spring and Redis. Redis is a high-performance NoSQL database. Usually, it is used as an in-memory caching solution because of its speed. However, in this example, we will be using it as the primary datastore. It perfectly fits our problem’s needs and has a good integration with Spring Data.

Magic of Aspects: How AOP Works in Spring

Aggregated on: 2025-01-31 16:46:10

It is from modern applications that one expects a clean and maintainable codebase in order to be able to manage the growing complexity. This is where Aspect Oriented Programming (AOP) comes in. AOP is a paradigm that enables the developers to separate the cross-cutting concerns (such as logging, metrics, and security) from the business logic of the application, making the code both modular and easy to maintain. Why Is It Important to Know AOP? I’ll begin with a simple analogy: There are some things that you should do when building a house: you should think about the design of the house, about the rooms and the decor of the rooms.

Getting Started With Agentic AI

Aggregated on: 2025-01-31 15:31:10

Advancements in AI and automation have paved the way toward agentic automation. Integrating advanced AI techniques, agentic automation enables autonomous agents to handle complex, unstructured tasks with minimal human intervention. In this Refcard, you will learn about the key components of AI agents, design principles for building intelligent agents, and practical applications of agentic automation — all demonstrated via a real-world use case.

Page Transactions: A New Approach to Test Automation

Aggregated on: 2025-01-31 15:31:10

Guará is the Python implementation of the design pattern Page Transactions. It is more of a programming pattern than a tool. As a pattern, it can be bound to any driver other than Selenium, including the ones used for Linux, Windows, and Mobile automation. The intent of this pattern is to simplify test automation. It was inspired by Page Objects, App Actions, and Screenplay. Page Transactions focus on the operations (transactions) a user can perform on an application, such as Login, Logout, or Submit Forms.

CAP and PACELC Theorems in Plain English

Aggregated on: 2025-01-31 14:01:10

Modern distributed systems are all about tradeoffs. Performance, reliability, scalability, and consistency don't come for free — you always pay a price somewhere. That's where the CAP theorem comes in: it's the starting point for understanding the unavoidable compromises in distributed design. Why is the CAP theorem true? What does it actually explain? And, most importantly, is it enough? In this post, we'll explore the CAP theorem, its limitations, the critiques it has faced, and how newer ideas like PACELC are pushing the conversation forward. Let's dive in.

Front-End Debugging Part 3: Networking

Aggregated on: 2025-01-31 12:31:10

Debugging network communication issues is a critical skill for any front-end developer. While tools like Wireshark provide low-level insight into network traffic, modern browsers like Chrome and Firefox offer developer tools with powerful features tailored for web development. In this post, we will discuss using browser-based tools to debug network communication issues effectively. This is a far better approach than using Wireshark for the vast majority of simple cases.

Understanding the Two Schools of Unit Testing

Aggregated on: 2025-01-30 22:16:09

Unit testing is an essential part of software development. Unit tests help to check the correctness of newly written logic as well as prevent a system from regression by testing old logic every time (preferably with every build). However, there are two different approaches (or schools) to writing unit tests: Classical (a.k.a Detroit) and Mockists (or London) schools of unit testing. In this article, we’ll explore these two schools, compare their methodologies, and analyze their pros and cons. By the end, you should have a clearer understanding of which approach might work best for your needs.

How to Build a Data Dashboard Prototype With Generative AI

Aggregated on: 2025-01-30 20:16:09

This article is a tutorial that shows how to build a data dashboard to visualize book reading data taken from Goodreads. It uses a low-code approach to prototype the dashboard using natural language prompts to an open-source tool, Vizro-AI, which generates Plotly charts that can be added to a template dashboard. You'll see how to iterate prompts to build three charts then add the prompts to a Notebook to generate an interactive dashboard. Finally, the generated dashboard code is added to a shared project that can be tweaked to improve the prototype. It's still not complete and can definitely be extended and improved upon. Let me know in the comments if you try it out!

Develop Microservices Using Azure Functions, API Management

Aggregated on: 2025-01-30 19:16:09

Microservices are a popular architectural pattern for building scalable and modular applications. They allow developers to focus on building small, independent, and reusable services that interact with each other through APIs. This blog will guide you through creating a simple serverless microservice and deploying it to Azure Cloud. I have used this approach to start building simple prototypes of various products, get early feedback from customers, and iterate faster. Components Azure Functions: The Serverless Workhorse Azure Functions is a serverless compute service that lets you run code pieces (functions) in Azure Cloud without worrying about provisioning infrastructure. We will leverage the event-driven functionality of Azure Functions to execute some API logic based on an HTTP request trigger.

Building a Machine Learning Pipeline Using PySpark

Aggregated on: 2025-01-30 18:31:09

In this article, we will look at an example of a complete machine learning (ML) pipeline using Python and PySpark. This pipeline includes data loading, preprocessing, feature engineering, model training, and evaluation. The main idea here is to provide you with a jump start on building your own ML pipelines. We will use Spark capabilities to build the pipeline. PySpark offers ML libraries that are very powerful and efficient when it comes to processing large volumes of data.

Bridging Graphviz and Cytoscape.js for Interactive Graphs

Aggregated on: 2025-01-30 17:16:09

Visualizing complex digraphs often requires balancing clarity with interactivity. Graphviz is a great tool for generating static graphs with optimal layouts, ensuring nodes and edges don't overlap. On the flip side, Cytoscape.js offers interactive graph visualizations but doesn't inherently prevent overlapping elements, which can clutter the display. This article describes a method to convert Graphviz digraphs into interactive Cytoscape.js graphs. This approach combines Graphviz's layout algorithms with Cytoscape.js's interactive capabilities, resulting in clear and navigable visualizations.

SmartXML: An Alternative to XPath for Complex XML Files

Aggregated on: 2025-01-30 16:16:09

XML is one of the most widely used data formats, which in popularity can compete only with JSON. Still, very often, this format is used as an intermediate representation of data that needs to be transferred between two information systems. And like any intermediate representation the final storage point of XML is a database. Usually, XPath is used to parse XML because it represents a set of functions that allows you to extract data from an XML tree. However, not all XML files are formed correctly, which creates great difficulties when using XPath.

Structured Logging in Grails 6.2.3

Aggregated on: 2025-01-30 15:16:09

Traditionally, logging has been unstructured and relies on plain text messages to file. This approach is not suitable for large-scale distributed systems emitting tons of events, and parsing unstructured logs is cumbersome for extracting any meaningful insights. Structured logging offers a solution to the above problem by capturing logs in a machine-readable format such as JSON, and it becomes easier to query and analyze log data in a system where logs are aggregated into centralized platforms like ELK (ElasticSearch, Logstash, Kibana).

Secrets Management With Datadog Secret Backend Utility

Aggregated on: 2025-01-30 14:31:09

Datadog has 600+ out-of-the-box integrations that cover a variety of technologies, from web servers to databases to 3rd party SaaS services. For many of these integrations, there are agent configuration files that require storing credentials for the technology. The larger issue is around how to store those credentials. Many security-minded engineers would prefer not to store those secrets in plaintext in case of unauthorized access to their servers or shared access to Datadog configuration. What not everyone knows is that the Datadog agent has a mechanism to run an executable at agent startup in order to reach out to a secrets management tool of your choosing and decrypt those secrets, storing them in memory for use by the agent. Secrets Configuration If you want to utilize Datadog’s secrets management capabilities, there is a specific notation that the agent recognizes. Let’s take the Datadog MySQL integration as an example. While the integration, by default, only collects information from performance-related tables, you might grant additional access to other database tables to ingest more business-specific metrics into the platform via custom queries. This may require additional permissions for more sensitive data, so you might want to ensure that the credential is not stored in plaintext in the integration configuration.

Commonly Occurring Errors in Microsoft Graph Integrations and How To Troubleshoot Them (Part 7)

Aggregated on: 2025-01-30 13:16:09

Retrieving attachments from SharePoint lists is a key feature when integrating data from SharePoint into external applications. Microsoft offers two possible APIs: the SharePoint REST API and the Microsoft Graph API. Both approaches provide methods to access the desired data. We explain the steps for configuring and using these APIs to retrieve attachments from a SharePoint list. SharePoint Lists SharePoint provides different list types to suit various data management needs and applications.

Scaling Read Your Own Writes Consistency

Aggregated on: 2025-01-30 12:31:09

Building on the foundational understanding of Read Your Own Writes (RYW) consistency outlined in my previous article, this follow-up dives into advanced strategies for scaling RYW in distributed systems. As systems grow in complexity and handle millions of concurrent users, ensuring RYW consistency becomes a more nuanced challenge. This article will explore cutting-edge techniques, trade-offs, and case studies to help practitioners implement RYW at scale. Challenges in Scaling RYW 1. Geo-Distributed Systems In globally distributed systems, writes often need to propagate across data centers in different regions. Ensuring RYW consistency for users whose requests span multiple regions introduces latency and synchronization challenges. Strategies must balance performance with correctness.

Passing JSON Variables in Azure Pipelines

Aggregated on: 2025-01-29 22:16:09

When working with Azure DevOps pipelines, there are situations where you need to use JSON as a variable — whether it's for dynamically passing configurations, triggering APIs, or embedding JSON data into scripts. A common use case is creating a pipeline that triggers an API requiring a JSON payload. However, Azure DevOps treats all variables as plain strings, and when you attempt to pass JSON, it often results in malformed data due to improper escaping. This can break APIs or other components expecting valid JSON.

How to Split PDF Files into Separate Documents Using Java

Aggregated on: 2025-01-29 21:31:09

Asking our Java file-processing applications to manipulate PDF documents can only increase their value in the long run. PDF is by far the most popular, widely used file type in the world today, and that’s unlikely to change any time soon. Introduction In this article, we’ll specifically learn how to divide PDF files into a series of separate PDF documents in Java — resulting in exactly one new PDF per page of the original file — and we’ll discuss open-source and third-party web API options to facilitate implementing that programmatic workflow into our code. We’ll start with a high-level overview of how PDF files are structured to make this type of workflow possible.

Predicting Diabetes Types: A Deep Learning Approach

Aggregated on: 2025-01-29 20:16:09

Diabetes has become a significant health concern in India, particularly among young adults. In this article, we'll explore a comprehensive analysis of diabetes prediction using machine learning techniques, working with a dataset that contains various health and lifestyle factors of young adults in India. Understanding the Dataset The dataset comprises 100,000 records with 22 features, including demographic information, health metrics, and lifestyle factors. The key features include age, gender, BMI, family history of diabetes, genetic risk scores, and various lifestyle indicators such as physical activity level, dietary habits, and sleep patterns. What makes this dataset particularly interesting is its focus on young adults and the inclusion of both Type 1 and Type 2 diabetes cases.

Why You Don’t Need That New JavaScript Library

Aggregated on: 2025-01-29 19:16:09

Libraries can rise to stardom in months, only to crash and fade into obscurity within months. We’ve all seen this happen in the software development world, and my own journey has been filled with “must-have” JavaScript libraries, each claiming to be more revolutionary than the one before. But over the years, I’ve come to realize that the tools we need have been with us all along, and in this article, I’ll explain why it’s worth sticking to the fundamentals, how new libraries can become liabilities, and why stable, proven solutions usually serve us best in the long run.

Metal and the Simulated Annealing Algorithm

Aggregated on: 2025-01-29 18:31:09

In this article, I’ll walk you through Bryan Luke’s Simulated Annealing Algorithm, a powerful probabilistic approach to finding optimal solutions among numerous possibilities. We’ll explore its implementation using the classic N-Queens problem as an example. Unlike greedy algorithms, simulated annealing intelligently explores the solution space to avoid being trapped in poor solutions. What Is Simulated Annealing? Simulated annealing is inspired by the physical process of annealing metals, where a material is heated and then cooled slowly to improve its internal structure. The algorithm mimics this process to find solutions in complex problem spaces.

Using Custom React Hooks to Simplify Complex Scenarios

Aggregated on: 2025-01-29 17:16:09

In the world of React, hooks have revolutionized the way we build components and manage state. The introduction of hooks like useState, useEffect, and useContext gave developers more flexibility in writing clean and reusable code. However, there are scenarios where built-in hooks alone aren't enough to handle complex logic or provide the desired abstraction. That's where custom React hooks come in. Custom hooks allow you to encapsulate logic into reusable functions, making your codebase cleaner and more maintainable. In this article, let us explore advanced techniques and strategies for building custom React hooks to handle complex scenarios.

Expert Guide: How to Slash Cloud Cost in 2025

Aggregated on: 2025-01-29 16:16:09

Cloud computing has revolutionized the way companies scale and innovate, but cost control is one hurdle. According to Precedence Research, the cloud computing market size is going to increase to $2.3 trillion by 2032, which necessitates prioritizing cost optimizations as many organizations move to Cloud computing. Image: Cloud Computing Market Size Projections from 2022 to 2032

Gemini 2.0 Flash (Experimental): A Deep Dive for Developers

Aggregated on: 2025-01-29 15:16:09

Gemini 2.0 Flash, Google’s latest LLM, pushes the boundaries of AI capabilities. This blog delves deeper, focusing on key features and how they differentiate Gemini 2.0 Flash from other prominent models. Gemini distinguishes itself from other LLMs primarily through its multi-modal capabilities and advanced reasoning abilities. Unlike many LLMs that primarily focus on text, Gemini can process and generate various forms of data, including images, audio, and code. This multimedia nature allows Gemini to tackle a wider range of tasks and applications, such as image-based question answering, video summarization, and even generating creative content across different modalities.

Publishing Flutter Packages to JFrog Artifactory

Aggregated on: 2025-01-29 14:31:09

JFrog is a comprehensive package manager designed to centralize and secure all the packages required for internal development within an organization, including applications, libraries, and components. It also facilitates the management of open-source libraries with robust security guardrails. This centralized approach provides enterprises with a structured and transparent method for managing open-source software and securing internally developed packages. There is well-defined documentation available for incubating JFrog for Java Technology and JavaScript/npm. With respect to the Flutter packages, I didn’t find detailed documentation, so I thought of outlining the scenarios and the resolution that I came up with.

Scrape Amazon Product Reviews With Python

Aggregated on: 2025-01-29 13:16:09

Amazon is a well-known e-commerce platform with a large amount of data available in various formats on the web. This data can be invaluable for gaining business insights, particularly by analyzing product reviews to understand the quality of products provided by different vendors. In this guide, we will look into web scraping steps to extract Amazon reviews of a particular product and save them in Excel or CSV format. Since manually copying information online can be tedious, we’ll focus on scraping reviews from Amazon. This hands-on experience will enhance our practical understanding of web scraping techniques.

The Energy Efficiency of JVMs and the Role of GraalVM

Aggregated on: 2025-01-29 12:16:09

As the world becomes increasingly conscious of energy consumption and its environmental impact, software development is joining the movement to go green. Surprisingly, even the choice of runtime environments and how code is executed can affect energy consumption. This brings us to the world of Java Virtual Machines (JVMs), an integral part of running Java applications, and the rising star in the JVM world, GraalVM. In this article, we will explore how code performance and energy efficiency intersect in the JVM ecosystem and why GraalVM stands out in this domain.

Implement RAG With PGVector, LangChain4j, and Ollama

Aggregated on: 2025-01-28 22:31:08

In this blog, you will learn how to implement retrieval-augmented generation (RAG) using PGVector, LangChain4j, and Ollama. This implementation allows you to ask questions about your documents using natural language. Enjoy! Introduction In a previous blog, RAG was implemented using Weaviate, LangChain4j, and LocalAI. Now, one year later, it is interesting to find out how this has evolved. E.g.:

Soft Skills Are as Important as Hard Skills for Developers

Aggregated on: 2025-01-28 21:31:08

At the beginning of my career as a backend developer, I focused almost exclusively on hard skills. I believed that becoming a technically strong specialist was the key to success, and once I mastered that, job security would be guaranteed. After all, employers care about your ability to solve real problems, not how well you can articulate your thoughts, right? But over time, as my experience grew, I came to realize that technical skills alone aren't enough if you want to progress further in your career. Without soft skills, reaching a high level in your profession becomes a challenge. Soft skills open doors to exciting projects, enable you to take on responsibility for important decisions, and ultimately help you take top technical roles in reputable companies. Even brilliant code means little if you can't explain its value to your team, align changes with your colleagues, or understand what the business truly needs. Let's explore why soft skills are crucial for developers and how they can help you advance in your profession.

Stop Shipping Waste: Fix Your Product Backlog

Aggregated on: 2025-01-28 20:16:08

TL; DR: Stop Shipping Waste When product teams fail to establish stakeholder alignment and implement rigorous Product Backlog management, they get caught in an endless cycle of competing priorities, reactive delivery, and shipping waste. The result? Wasted resources, frustrated teams, and missed business opportunities. Success in 2025 requires turning your Product Backlog from a chaotic wish list into a strategic tool that connects vision to value delivery. Learn how to do so.

Next Generation Observability: An Architectural Introduction

Aggregated on: 2025-01-28 19:16:08

In my past life, I spent many hours researching, creating, explaining, and publishing portfolio architectures across a collection of application development, domain verticals, infrastructure solutions, and hybrid cloud domains. Most of these concentrated on the application layers and their usage of the infrastructure. Then, I transitioned into the cloud native observability space, and observability became the guiding light on my learning path. This quickly led to the realization that the same solution mapping that the previous portfolio architectures brought to organizations struggling with solving hard problems also applied to the observability world. It's just a matter of a different angle from which we look at those solutions.

Using Spring AI to Generate Images With OpenAI's DALL-E 3

Aggregated on: 2025-01-28 18:16:08

Hi, community! This is my first article in a series of introductions to Spring AI. Today, we will see how we can easily generate pictures using text prompts. To achieve this, we will leverage the OpenAI API and the DALL-E 3 model.

Implement a Geographic Distance Calculator Using TypeScript

Aggregated on: 2025-01-28 17:31:08

When developing educational games, providing accurate and meaningful feedback is crucial for user engagement. In this article, I'll share how we implemented a geographic calculation system for Flagle Explorer, a flag-guessing game that helps users learn world geography through interactive feedback. The Technical Challenge Our main requirements were:

Implementing and Testing Cryptographic Primitives With Go

Aggregated on: 2025-01-28 16:16:08

Implementing cryptographic primitives securely is crucial for maintaining the integrity, confidentiality, and authenticity of data in Go applications. This guide will walk you through the process of implementing and testing various cryptographic primitives using Go’s standard library and best practices. Understanding Cryptographic Primitives Cryptographic primitives are the building blocks of cryptographic protocols and systems. They include:

Understanding Inference Time Compute

Aggregated on: 2025-01-28 15:16:08

In the field of machine learning and artificial intelligence, inference is the phase where a trained model is applied to real world data to generate predictions or decisions. After a model undergoes training, which can be computationally intensive and time consuming, the inference process allows the model to make predictions with the goal of providing actionable results. Inference Time Compute Inference time compute refers to the amount of computational power required to make such predictions using a trained model. While training a model involves processing large datasets to learn patterns and relationships, inference is the process where the model is used to make predictions on new, unseen data. This phase is critical in real world applications such as image recognition, natural language processing, autonomous vehicles, and more.

How Apache Flink and Apache Paimon Influence Data Streaming

Aggregated on: 2025-01-28 14:16:08

Apache Paimon is made to function well with constantly flowing data, which is typical of contemporary systems like financial markets, e-commerce sites, and Internet of Things devices. It is a data storage system made to effectively manage massive volumes of data, particularly for systems that deal to analyze data continuously such as streaming data or with changes over time like database updates or deletions. To put it briefly, Apache Paimon functions similarly to a sophisticated librarian for our data. Whether we are operating a large online business or a little website, it keeps everything organized, updates it as necessary, and ensures that it is always available for use. An essential component of Apache Paimon's ecosystem, Apache Flink is a real-time stream processing framework that significantly expands its capabilities. Let's investigate how well Apache Paimon and Apache Flink work with each other so effectively.

Vector Storage, Indexing, and Search With MariaDB

Aggregated on: 2025-01-28 13:31:08

When you develop generative AI applications, you typically introduce three additional components to your infrastructure: an embedder, an LLM, and a vector database. However, if you are using MariaDB, you don't need to introduce an additional database along with its own SQL dialect — or even worse — its own proprietary API. Since MariaDB version 11.7 (and MariaDB Enterprise Server 11.4) you can simply store your embeddings (or vectors) in any column of any table—no need to make your applications database polyglots.

Why Use AWS Lambda Layers? Advantages and Considerations

Aggregated on: 2025-01-28 12:16:08

I'm originally a .NET developer, and the breadth and depth of this framework are impressive. You probably know the phrase, "When all you have is a hammer, everything looks like a nail." Nevertheless, although I wrote a few articles about .NET-based Lambda function, this time, I decided to leave the hammer aside and look for another tool to serve the purpose. Background Choosing Python was an easy choice; it is simple to program, has many prebuilt libraries, and is supported well by the AWS Lambda function. So, this challenge is accepted!

AWS Lambda Enhances Local IDE Experience With AI Support

Aggregated on: 2025-01-27 22:16:08

AWS Lambda is enhancing the local IDE experience to make developing Lambda-based applications more efficient. These new features enable developers to author, build, debug, test, and deploy Lambda applications seamlessly within their local IDE using Visual Studio Code (VS Code). Overview The improved IDE experience is part of the AWS Toolkit for Visual Studio Code. It includes a guided setup walkthrough that helps developers configure their local environment and install necessary tools. The toolkit also includes sample applications that demonstrate how to iterate on your code both locally and in the cloud. Developers can save and configure build settings to accelerate application builds and generate configuration files for setting up a debugging environment.

Working With Vision AI to Test Cloud Applications

Aggregated on: 2025-01-27 21:31:08

Recently, I’ve been looking into Tricentis Tosca to better understand how its testing suite can benefit my app development workflow. In my last article about Tosca, I wrote about some of the tool’s visual capabilities, such as QR code testing. Testing QR codes is great if you need an effective way to validate that specific part of your app. Then, I discovered Tosca’s Vision AI tools. Imagine giving your testing tool some simple visual cues for how your system should work and then building the functionality to make the tests pass. That’s what these tools are designed to do.

Get Started With Vector Search in Azure Cosmos DB

Aggregated on: 2025-01-27 20:31:08

This is a guide for folks who are looking for a way to quickly and easily try out the Vector Search feature in Azure Cosmos DB for NoSQL. This app uses a simple dataset of movies to find similar movies based on a given criteria. It's implemented in four languages — Python, TypeScript, .NET and Java. There are instructions that walk you through the process of setting things up, loading data, and then executing similarity search queries. A vector database is designed to store and manage vector embeddings, which are mathematical representations of data in a high-dimensional space. In this space, each dimension corresponds to a feature of the data, and tens of thousands of dimensions might be used to represent data. A vector's position in this space represents its characteristics. Words, phrases, or entire documents, and images, audio, and other types of data can all be vectorized. These vector embeddings are used in similarity search, multi-modal search, recommendations engines, large language models (LLMs), etc.

Top Tools for Object Storage and Data Management

Aggregated on: 2025-01-27 19:31:08

Whether you are a seasoned cloud architect or a newbie getting to understand the nuances of the cloud, at some point, you will come across an interesting storage option called object storage to store or archive your unstructured data. In this article, you will be introduced to object storage and key tools like MinIO, Cyberduck, and more. Understanding Object Storage Object storage is a data storage architecture that manages information as discrete units called objects, rather than as files in folders or blocks on servers. Each object typically includes the data itself, a variable amount of metadata, and a globally unique identifier. This approach offers several advantages over traditional storage methods, particularly when dealing with large volumes of unstructured data.

Comparing SDLC With and Without AI/ML Integration

Aggregated on: 2025-01-27 18:46:08

The software conception, development, testing, deployment, and maintenance processes have fundamentally changed with the use of artificial intelligence (AI) and machine learning (ML) in the software development life cycle (SDLC). Businesses today want to automate their development processes in any way they can with the goals of increasing efficiency, positively impacting time to market, improving the quality of software, and being data-driven in their approaches. AI/ML is instrumental in achieving these goals as it helps in automating repetitive work processes, assists with predictive analytics and empowers intelligent systems that respond to changing needs. This article discusses the role of AI/ML at each stage of the SDLC, how they are able to add value to it, and the challenges organizations face or will face in order to exploit them to the maximum.