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Large language models (LLMs) are rapidly evolving from simple text prediction systems into advanced reasoning engines capable of tackling complex challenges. Initially designed to predict the next word in a sentence, these models have now advanced to solving mathematical equations, writing functional code, and making data-driven decisions. The development of reasoning techniques is the key driver behind this transformation, allowing AI models to process information in a structured and logical ma
Recent advancements in reasoning models, such as OpenAI’s o1 and DeepSeek R1, have propelled LLMs to achieve impressive performance through techniques like Chain of Thought (CoT). However, the verbose nature of CoT leads to increased computational costs and latency. A novel paper published by Zoom Communications presents a new prompting technique called Chain of Draft […] The post Chain of Draft Prompting with Gemini and Groq appeared first on Analytics Vidhya.
Visual Studio Code (VSCode) is a powerful, free source-code editor that makes it easy to write and run Python code. This guide will walk you through setting up VSCode for Python development, step by step. Prerequisites Before we begin, make sure you have: Python installed on your computer An internet connection Basic familiarity with your computer’s operating system Step 1: Download and Install Visual Studio Code Windows, macOS, and Linux Go to the official VSCode website: [link] Click the
Imagine an AI that can write poetry, draft legal documents, or summarize complex research papersbut how do we truly measure its effectiveness? As Large Language Models (LLMs) blur the lines between human and machine-generated content, the quest for reliable evaluation metrics has become more critical than ever. Enter ROUGE (Recall-Oriented Understudy for Gisting Evaluation), a […] The post ROUGE: Decoding the Quality of Machine-Generated Text appeared first on Analytics Vidhya.
Start building the AI workforce of the future with our comprehensive guide to creating an AI-first contact center. Learn how Conversational and Generative AI can transform traditional operations into scalable, efficient, and customer-centric experiences. What is AI-First? Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
Bill Gates recently appeared on The Tonight Show with Jimmy Fallon. They talked about his new book Source Code, his childhood, and 50 years of Microsoft. But the most powerful part of the conversation was about the future, especially the rise of AI and what it means for our jobs. Gates shared his thoughts in […] The post 5 Jobs AI Can’t Replace According to Bill Gates appeared first on Analytics Vidhya.
Bill Gates recently appeared on The Tonight Show with Jimmy Fallon. They talked about his new book Source Code, his childhood, and 50 years of Microsoft. But the most powerful part of the conversation was about the future, especially the rise of AI and what it means for our jobs. Gates shared his thoughts in […] The post 5 Jobs AI Can’t Replace According to Bill Gates appeared first on Analytics Vidhya.
Large language models struggle to process and reason over lengthy, complex texts without losing essential context. Traditional models often suffer from context loss, inefficient handling of long-range dependencies, and difficulties aligning with human preferences, affecting the accuracy and efficiency of their responses. Tencents Hunyuan-T1 directly tackles these challenges by integrating a novel Mamba-powered architecture with advanced reinforcement learning and curriculum strategies, ensuring
Imagine bringing your coding ideas to life effortlessly, with AI guiding you every step of the way. Codeiums Windsurf turns software development into a smooth, intuitive process by streamlining coding, debugging, and optimization. The Windsurf Editor enhances productivity with code completion tools and smart IDE features, helping you refine code and solve problems before they […] The post Vibe Coding with Windsurf appeared first on Analytics Vidhya.
Large language models (LLMs) have become vital across domains, enabling high-performance applications such as natural language generation, scientific research, and conversational agents. Underneath these advancements lies the transformer architecture, where alternating layers of attention mechanisms and feed-forward networks (FFNs) sequentially process tokenized input.
Researchers have developed a new kind of artificial neuroncalled infomorphic neuronsthat can independently learn and self-organize with nearby neurons, mimicking the decentralized learning of biological brains.
Today’s buyers expect more than generic outreach–they want relevant, personalized interactions that address their specific needs. For sales teams managing hundreds or thousands of prospects, however, delivering this level of personalization without automation is nearly impossible. The key is integrating AI in a way that enhances customer engagement rather than making it feel robotic.
Supervised fine-tuning (SFT) is the standard training paradigm for large language models (LLMs) and graphic user interface (GUI) agents. However, SFT demands high-quality labeled datasets, resulting in extended training periods and high computational expenses. This dependence on extensive data creates bottlenecks in AI development workflows. Moreover, existing VLM-based GUI agents trained through SFT show performance deficiencies when confronted with out-of-domain scenarios, severely limiting th
Articles OLMo 2 32B The Allen Institute for AI (AI2) has released OLMo 2 32B , a Foundation Model in open-source language models. This model is the largest and most capable in the OLMo 2 family, building upon the foundation laid by its 7B and 13B predecessors. OLMo 2 32B is the first fully open model, with all data, code, weights, and training details publicly available, to outperform GPT-3.5-Turbo and GPT-4o mini on a range of academic benchmarks.
Gemini 2.5 Pro marks a significant leap forward for Google in the foundational model race not just in benchmarks, but in usability. Based on early experiments, benchmark data, and hands-on developer reactions, its a model worth serious attention from enterprise technical decision-makers, particularly those whove historically defaulted to OpenAI or Claude for production-grade reasoning.
The guide for revolutionizing the customer experience and operational efficiency This eBook serves as your comprehensive guide to: AI Agents for your Business: Discover how AI Agents can handle high-volume, low-complexity tasks, reducing the workload on human agents while providing 24/7 multilingual support. Enhanced Customer Interaction: Learn how the combination of Conversational AI and Generative AI enables AI Agents to offer natural, contextually relevant interactions to improve customer exp
Reinforcement Learning from Verifiable Rewards (RLVR) has recently emerged as a promising method for enhancing reasoning abilities in language models without direct supervision. This approach has shown notable success in mathematics and coding, where reasoning naturally aligns with structured problem-solving. While studies have demonstrated that RLVR alone can lead to self-evolved reasoning, research has largely been limited to these technical fields.
Apple announced WWDC25 earlier this week, taking place on June 9th. That means were just around the corner from seeing all of Apples annual software upgrades, including iOS 19, iPadOS 19, macOS 16, visionOS 3, tvOS 19, watchOS 12, and possibly even more.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
Recent advancements in AI scaling laws have shifted from merely increasing model size and training data to optimizing inference-time computation. This approach, exemplified by models like OpenAI o1 and DeepSeek R1, enhances model performance by leveraging additional computational resources during inference. Test-time budget forcing has emerged as an efficient technique in LLMs, enabling improved performance with minimal token sampling.
It's rarely a dull week in the world of tech, but the last seven days have been eventful to say the least surprises, controversies and Studio Ghibli-themed copyright debates, it's had the lot. Away from ChatGPT's new viral image generator, we had an action-packed Nintendo Direct event, Apple's announcement of its WWDC 2025 event, plus some quality time with Canon's new PowerShot V1 camera.
This post is divided into three parts; they are: Using DistilBERT Model for Question Answering Evaluating the Answer Other Techniques for Improving the Q&A Capability BERT (Bidirectional Encoder Representations from Transformers) was trained to be a general-purpose language model that can understand text.
The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
Speaker: Alexa Acosta, Director of Growth Marketing & B2B Marketing Leader
Marketing is evolving at breakneck speed—new tools, AI-driven automation, and changing buyer behaviors are rewriting the playbook. With so many trends competing for attention, how do you cut through the noise and focus on what truly moves the needle? In this webinar, industry expert Alexa Acosta will break down the most impactful marketing trends shaping the industry today and how to turn them into real, revenue-generating strategies.
When thinking about how artificial intelligence (AI) is taking the world by storm, my mind almost instantly begins to think about how the technology is impacting fields like data analytics or drug discovery.
Early signs of one of the most common reproductive cancers may now be spotted with near-perfect accuracy, thanks to a groundbreaking artificial intelligence model. For years, diagnosing endometrial cancer required invasive procedures, expert review, and weeks of waiting.
Agentic is the biggest buzzword in Silicon Valley, but tech companies and enterprises lack a common understanding of its meaning, and its causing problems The enterprise software industry gods have spoken and declared AI agents to be the next big thing.
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