Author(s): Prineet Kaur 👩💻 Originally published on Towards AI. Image ownde by Author (generated using Google Gemini) Ijust describe what I want, run, tweak, repeat. — A rough paraphrase of how many newbie developers are now approaching “vibe coding” We’ve all been reading articles lately about “vibe coding” — a trend where code creation is less about writing every line and more about guiding AI tools through intent, feedback, and iteration. If traditional programming is...| Towards AI
Last Updated on October 15, 2025 by Editorial Team Author(s): Bran Kop, Engineer @Conformal, Founder of aiHQ Originally published on Towards AI. OpenAI’s AgentKit made a splash in late 2025, with some commentators hyping it as a potential “startup killer” for the AI agent space. It promises an integrated toolkit to build AI agents that can carry out complex tasks. But is AgentKit truly an all-in-one solution that renders other platforms obsolete? In reality, the AI agent ecosystem is va...| Towards AI
Last Updated on October 15, 2025 by Editorial Team Author(s): AIversity Originally published on Towards AI. AI Weekly Newsletter from AIversity The past week has been absolutely explosive for the AI industry, with groundbreaking partnerships, massive funding rounds, and revolutionary product launches that are reshaping how we interact with artificial intelligence. From OpenAI’s jaw-dropping hardware deals to INDIA emerging as a global AI powerhouse, here’s everything you need to know abou...| Towards AI
Last Updated on October 15, 2025 by Editorial Team Author(s): Rohan Mistry Originally published on Towards AI. The 47-Step Journey Your Message Takes From Your Keyboard to AI Response (And Why It Costs $0.03 You open ChatGPT. You type: “Explain quantum computing.” Source: Image by author.The article outlines the complex journey a query takes from when a user types it into ChatGPT until the AI generates a response, highlighting the numerous computational and infrastructural steps involved,...| Towards AI
Last Updated on October 15, 2025 by Editorial Team Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie After a frenetic period of product announcements, this week felt much slower on the release front. Following OpenAI’s DevDay deluge, Google offered its response with a slew of new enterprise features and new models. The standout was a new Gemini 2.5 Pro model for “Computer Use,” which looks to be a significant step forward in ...| Towards AI
Last Updated on October 15, 2025 by Editorial Team Author(s): Eivind Kjosbakken Originally published on Towards AI. Learn how to build production-ready systems using AI agents AI agents have quickly become an effective way of using LLMs for problem-solving. Almost weekly, you see a new large AI research lab releasing LLMs with specific agentic capabilities. However, building an effective agent for production is a lot more complicated than it appears. An agent needs guardrails, specific workfl...| Towards AI
Last Updated on October 15, 2025 by Editorial Team Author(s): Suraj Pandey Originally published on Towards AI. Learn How ReAct, Planning, and Reflection Form the Core of Next-Gen Intelligent Systems Imagine you’re planning a vacation. You don’t just Google “best hotels in Paris” and stop there. Instead, you think: “I need a hotel near the Louvre, check reviews, compare prices, maybe look at alternative neighborhoods if everything’s too expensive, and then book the one that fits my...| Towards AI
Last Updated on October 15, 2025 by Editorial Team Author(s): Hira Ahmad Originally published on Towards AI. When Transformers Multiply Their Heads: What Increasing Multi-Head Attention Really Does Transformers have become the backbone of many AI breakthroughs, in NLP, vision, speech, etc. A central component is multi-head self-attention: the notion that instead of one attention lens, a model uses several, each looking at different aspects of the input. But more heads isn’t always strictly ...| Towards AI
Last Updated on October 15, 2025 by Editorial Team Author(s): Amna Sabahat Originally published on Towards AI. You’ve cleaned your data, handled missing values, and are ready to build a powerful machine learning model. But there’s one critical step left: feature scaling. If you’ve ever wondered why your K-Nearest Neighbors model performs poorly or your Neural Network takes forever to train, unscaled data is likely the culprit. In this comprehensive guide, we’ll dive deep into Z-Score ...| Towards AI
Author(s): Chandra Prakash Bathula Originally published on Towards AI. Stacking Neurons: The Foundation of Deep Learning Now that we’ve understood what a Pe ...| towardsai.net
Author(s): Ali Oraji Originally published on Towards AI. Overfitting is when a neural network (or any ML model) captures noise and characteristics of the tr ...| towardsai.net
Author(s): Vlad Johnson Originally published on Towards AI. In the rapidly evolving field of Artificial Intelligence, multi-agent systems have emerged as a ...| towardsai.net
Author(s): Padmaja Kulkarni Originally published on Towards AI. When most teams talk about “AI or data risk,” the conversation always drifts toward accuracy ...| towardsai.net
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Author(s): Shubham Saboo Natural Language ProcessingGPT-3 for Corporates — Is Data Privacy an Issue?GPT-3 is transforming the way how businesses can leverag ...| towardsai.net
Author(s): Towards AI Editorial Team Originally published on Towards AI the World's Leading AI and Technology News and Media Company. If you are buildi ...| towardsai.net