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Researchers say Aardvark Weather uses thousands of times less computing power and is much faster than current systems. By Rachel Hall and Ian Sample.

A revolutionary AI system called Aardvark is poised to transform weather forecasting. Unlike traditional methods that rely on complex supercomputers and expert teams, Aardvark leverages machine learning to analyze vast amounts of raw weather data from various sources. This enables it to generate forecasts tens of times faster and with a fraction of the computing power, making accurate predictions accessible even on desktop computers.

Aardvark’s potential impact is immense. It could empower individuals and smaller organizations with customized, localized weather information for specific needs, democratizing access to this crucial data. Imagine farmers in Africa receiving precise temperature forecasts or renewable energy companies predicting wind speeds with high accuracy – all made possible by Aardvark.

Beyond its speed and accessibility, Aardvark also promises improved long-range forecasting, extending predictions beyond the current five days, and contributing to better understanding of natural disasters and climate change-related issues. This breakthrough represents a significant leap forward in weather prediction, ushering in a future of more accurate and readily available forecasts for everyone. Good read!

Using AI in software development is not about writing more code faster; it’s about building better software. It’s up to you as a leader to define what “better” means and help your team navigate how to achieve it. Treat AI as a junior team member that needs guidance. Train folks to not over-rely on AI; this can lead to skill erosion. Emphasize “trust but verify” as your mantra for AI-generated code. Leaders should upskill themselves and their teams to navigate this moment.Using AI in software development is not about writing more code faster; it’s about building better software. It’s up to you as a leader to define what “better” means and help your team navigate how to achieve it. Treat AI as a junior team member that needs guidance. Train folks to not over-rely on AI; this can lead to skill erosion. Emphasize “trust but verify” as your mantra for AI-generated code. Leaders should upskill themselves and their teams to navigate this moment. By Addy Osmani.

Key takeaways from this blog post:

• Leading engineering teams in the age of GenAI is about building better software, not just writing code faster.
• Leaders must define what “better” means for their teams and projects.
• Upskilling oneself and the team is crucial; focusing on AI usage best practices and ethical considerations.
• The role of leadership evolves to include strategic guidance, oversight, and fostering a culture that values both humans and AI.

The future leader will h ave to be adept at fostering a culture where AI is used effectively but isn’t seen as a replacement for human skills. It’s about finding that perfect balance between leveraging technology to augment human abilities and maintaining those qualities that make us uniquely valuable in the workplace—creativity, judgment, and empathy. Excellent read!

Java performance is a crucial aspect of software development. It affects how fast and efficiently Java programs run. Optimizing Java performance can lead to faster applications, reduced resource usage, and better user experiences. By Kacper Rafalski.

Key points on optimizing Java performance:

• Introduction to Java performance optimization
• Key areas of optimization
• Common performance issues
• Memory management techniques
• Code optimization strategies
• JVM tuning and tools
• Security and I/O efficiency
• Real-world applications
• Best practices

Optimizing Java performance involves a combination of efficient coding practices, leveraging modern JVM features, careful resource management, and effective use of profiling tools. By focusing on these areas, developers can enhance application speed, scalability, and user experience.

AI code generation promises a quick boost of productivity for programmers. To generate code using AI, first choose an AI-powered coding assistant tool. Then, provide a natural language description of your expected cod. The list of AI coding assistants compiled by Ayelet Slasky.

In the article you will find:

• Best AI for coding and ai coding assistants by category
  • AI-powered development assistants
  • Code intelligence & completion
  • Security & analysis
  • Cross-language & translation
  • Educational & learning tools
• How author selected the best AI coding tools in this list
• 15 Best AI Coding Assistants – 2025 List

Over the years, the developer has explored many AI-assisted coding tools but only a select few have proven to be truly effective. To ensure this list includes only the best, the developer has carefully evaluated each AI code helper based on its ability to address common challenges faced by developers. 10 factors were considered.

APIs (Application Programming Interfaces) are the backbone of modern software applications, enabling seamless communication between different systems. Whether you’re building a web app, or mobile service, or managing complex data, learning how to build an API is essential for creating scalable, efficient systems. APIs can be categorized into several types based on their architecture, such as REST, GraphQL, and SOAP, each with specific use cases. By @geeksforgeeks.org.

In this guide, authors will dive into API development, using Node.js, Django, and Spring Boot as examples. You’ll learn how to design, build, secure, and deploy your API effectively, making it accessible to users worldwide.

This long article covers:

• Planning your API
• API design
• Set up your development environment
• Building API endpoints
• Securing your API
• Testing your API
• Monitoring and optimizing your API

This tutorial has taken you through everything from setup to deployment, and by following this procedure, you will be well prepared for building and maintaining robust APIs for any application. As you grow your skill set, you can start adding advanced features like authentication, rate limiting, caching, and much more in order to make your APIs very efficient and secure. Nice one!

Event-driven architecture reacts to events, like user actions, allowing real-time, independent system responses and actions. This article explains event-driven architecture, its workings, types, and practical uses. By Vijay Kanade.

Further in the article:

• What is event-driven architecture?
• How does event-driven architecture work?
• Types of event-driven architecture
• Event-driven architecture vs. microservices
• Use cases of event-driven architecture
• Pros and cons of event-driven architecture

Event-driven architecture (EDA) is a software design pattern that structures a system’s components to respond to, produce, and process events. It promotes loose coupling, scalability, and real-time responsiveness, making it suitable for modern applications with dynamic and distributed interactions. Good read!

Are you struggling to understand how to build an API from scratch? This guide will equip you with everything you need to know about API development. APIs are the backbone of modern software, enabling applications to communicate, share data, and integrate seamlessly. From social media platforms to e-commerce websites, APIs are everywhere.Are you struggling to understand how to build an API from scratch? This guide will equip you with everything you need to know about API development. APIs are the backbone of modern software, enabling applications to communicate, share data, and integrate seamlessly. From social media platforms to e-commerce websites, APIs are everywhere. By @goodcore.co.uk.

The main content could be divided into:

• Introduction to API
• Types of APIs
• Benefits of using APIs
• Challenges in API development
• Best practices in API development

The article starts by explaining what an API is—a bridge that allows different applications to communicate and share data. It uses examples like social media platforms and e-commerce websites to illustrate the importance of APIs in modern software development.

The guide then discusses the various types of APIs, such as RESTful APIs for simple data exchanges, SOAP for enterprise-level integrations, GraphQL for flexible queries, and WebSocket for real-time communication. Each type is suited to different scenarios based on factors like simplicity, security requirements, and the need for real-time data.

Throughout the article, there’s a emphasis on best practices in API development, including planning, design, secure implementation, thorough testing, and ongoing maintenance. The authors suggest that building a robust API is crucial for expanding offerings, integrating systems, or streamlining operations within a company. They recommend considering custom solutions tailored to specific business needs. Interesting read!

GQL addresses the need for sophisticated queries that reflect the increasingly complex and connected nature of data in the real world. The benefits of graph databases not only exist in providing more intuitive and powerful ways to visualize and interrogate data relationships but also in storing and processing data more efficiently. By Jocelyn Hoppa.

Since the last major enhancement of Structured Query Language (SQL) decades ago, the database industry has introduced a new ISO/IEC standard language called Graph Query Language (opens in new tabGQL), marking a significant milestone.

In the article you will find:

• A brief history of SQL, from the beginning up to:
  • SQL:2016 – Year: 2016 – Standardization: ISO/IEC 9075:2016 – Details: Added JSON support and advanced sharding capabilities.
  • SQL:2019 – Year: 2019 – Standardization: ISO/IEC 9075:2019 – Details: Extended functionality with enhancements in JSON, property graph queries, and temporal data.
  • SQL:2023 – Year: 2023 – Standardization: ISO/IEC 9075:2023 – Details: New features for property graph queries over tables tables and improved JSON support.
• What is GQL?

GQL is a new standard marking the rise of graph queries alongside SQL’s evolution. Graph databases offer powerful ways to visualize and interrogate connected data, promising efficient storage and processing. Good read!

This article reflects on the state of JavaScript frameworks in 2024, concluding that the pursuit of simplicity hasn’t necessarily resulted in easier development. By Ryan Carniato.

Main Points:

• Server-First Momentum: The trend towards server-first architectures continues, with new frameworks like SvelteKit, Astro, Remix, and others offering solutions for improved performance and scalability.
• Complexity Remains: Despite advancements, the overall complexity of JavaScript development persists due to intricate tooling, compilation processes, and the nature of client-server interactions.
• The Rise of Compilers: Compilers are becoming increasingly vital in optimizing code and addressing language limitations. React Compiler and Svelte 5 Runes demonstrate this trend, pushing frameworks towards more sophisticated optimization strategies.
• AI’s Growing Impact: AI tools are starting to make inroads in developer workflows, offering assistance with tasks like performance analysis and code generation.

The author predicts a return to balanced approaches, incorporating elements of both client-side and server-side paradigms. Mature frameworks like Vue and Angular may gain traction due to their emphasis on stability and maintainability. Signals, while prevalent in many frameworks, are still evolving and will likely see refinements that address their inherent tradeoffs. Nice one!

Data floods in by the second, fueling every facet of business operations. Yet, raw data offers little value on its own — this is where big data analytics tools step in, transforming numbers into actionable insights. By Irina Prevalova.

In this guide, we will introduce you to big data analytics and will tell you about some of the most essential big data analytics tools for 2025, breaking down their key features, benefits, and what makes them stand out in a crowded market.

The article covers:

• What is big data analytics and how does it work?
• The importance of big data analytics for marketers and businesses
• Key factors to consider when selecting big data analytics tools
• 7 Best big data analytics tools to consider in 2025

In terms of leveraging data for the success of your business, big data analytics tools are a great help. From improving decision-making processes to optimizing marketing strategies, these tools provide the insights needed to stay competitive in today’s data-driven landscape. Nice one!