Small Language Models (SLMs) are efficient, resource-friendly AI models ideal for real-time tasks on devices with limited memory and processing power. Unlike Large Language Models (LLMs), which excel at complex, deep-context tasks, SLMs like DistilBERT and TinyBERT are faster, smaller, and more cost-effective. They’re often used in mobile apps, chatbots, and virtual assistants. With advancements in AI, SLMs are becoming vital for low-power, high-efficiency applications.

Google’s recent layoffs indicate where the industry is headed: AI, cloud infrastructure, and automation. For developers globally, these layoffs are more than just buzzwords: they’re a reality check for what it will take to get hired, and succeed, at Google. This blog will explore what's next for developers who are setting their sights on the company.

Discover how free AI resources are revolutionizing visual content creation by turning simple text prompts into stunning images and videos. With just a few words, these innovative platforms can generate high-quality visuals tailored to your needs, whether for imaginative storytelling or project design. Learn how to leverage this technology for practical applications, exploring its versatility and transformative potential in modern creative workflows.

AI isn't replacing any developer — it's an assistant that will help you do more. In fact, by reducing tedium, AI tools will help junior developers make a stronger impact, faster.

This blog explores Kolmogorov-Arnold Networks (KANs), an innovative neural network architecture that resembles traditional fully-connected neural networks but replaces weights and node-based activation functions with edge-based activation functions. We examine the learnability of these functions, compare KANs with traditional neural networks based on early experimental findings, and investigate their potential for greater interpretability and continual learning.

The Graph of Thoughts (GoT) is an advanced reasoning framework designed for large language models (LLMs), offering more flexible and complex cognitive structures than traditional methods like Chain-of-Thought (CoT) or Tree of Thoughts (ToT). Unlike linear (CoT) or hierarchical (ToT) representations, GoT organizes thoughts as interconnected nodes in a graph. This allows for non-linear, iterative, and multi-directional connections between ideas, mimicking the complexity of human cognition more closely.

This blog shows how mastering advanced prompt engineering, with techniques like Chain-of-Thought (CoT) and its variants, can significantly improve AI’s reasoning and problem-solving abilities.

AI agents, while powerful and autonomous, can malfunction due to software bugs, data quality issues, adversarial attacks, and goal misalignment. This blog explores the technical components of AI agents, real-world malfunction examples, and strategies to mitigate these risks. Understanding these aspects is crucial for developing reliable and safe AI systems.

This blog introduces you to the world of artificial intelligence through our free courses, designed specifically for beginners ready to unlock the power of AI. Learn to create chatbots, explore generative AI concepts, and harness the OpenAI API for natural language processing. Our blog features beginner-friendly courses, as listed below: Build Your First Chatbot in Python offers step-by-step guidance on crafting chatbots using Python, with no prior coding required. Generative AI Handbook helps you explore the basics of generative AI, exploring its applications in creating text, images, and more. Using OpenAI API for Natural Language Processing with Python/JavaScript teaches you how to implement AI-driven applications with real-world examples using OpenAI’s API. Whether you’re an aspiring developer or simply curious about AI, these courses offer the perfect launchpad to kickstart your journey. Start today, gain hands-on experience, and bring your AI ideas to life—for free! Begin your learning adventure with us