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TL;DR: Enterprise AI teams are discovering that purely agentic approaches (dynamically chaining LLM calls) dont deliver the reliability needed for production systems. The prompt-and-pray modelwhere business logic lives entirely in promptscreates systems that are unreliable, inefficient, and impossible to maintain at scale. A shift toward structured automation, which separates conversational ability from business logic execution, is needed for enterprise-grade reliability.
The DeepSeek R1 has arrived, and it’s not just another AI modelit’s a significant leap in AI capabilities, trained upon the previously released DeepSeek-V3-Base variant. With the full-fledged release of DeepSeek R1, it now stands on par with OpenAI o1 in both performance and flexibility. What makes it even more compelling is its open weight […] The post DeepSeek R1 vs OpenAI o1: Which One is Faster, Cheaper and Smarter?
The world plunged headfirst into the AI revolution. Now many are admitting they werent quite ready. The 2024 Board of Directors Survey from Gartner , for example, found that 80% of non-executive directors believe their current board practices and structures are inadequate to effectively oversee AI. The 2024 Enterprise AI Readiness Radar report from Infosys , a digital services and consulting firm, found that only 2% of companies were fully prepared to implement AI at scale and that, despite the
In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. Although these capabilities are powerful, implementing them effectively in production environments presents unique challenges that require careful consideration. Consider a common scenario: A streaming pipeline continuously writes data to an Iceberg table while scheduled maintenance jobs perform compaction operations.
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
Announcing DataOps Data Quality TestGen 3.0: Open-Source, Generative Data Quality Software. Now With Actionable, Automatic, Data Quality Dashboards Imagine a tool that can point at any dataset, learn from your data, screen for typical data quality issues, and then automatically generate and perform powerful tests, analyzing and scoring your data to pinpoint issues before they snowball.
I recently completed the latest edition of our Business Planning Buyers Guide, which reviews and assesses the offerings of 14 providers of this software. One of the points that I look at is whether and to what extent the software provider offers out-of-the-box external data useful for forecasting, planning, analysis and evaluation. What I discovered is that the availability of this type of vital information is exceedingly slim.
Breaking into data science has never been easy. In this tutorial, well make your life easier by providing you with a step-by-step roadmap for data science beginners.
Breaking into data science has never been easy. In this tutorial, well make your life easier by providing you with a step-by-step roadmap for data science beginners.
It almost sounds pejorative, doesnt it? But the distinction between senior and junior software developers is built into our jobs and job titles. Whether we call it entry-level or something else, we distinguish between people who are just starting their careers and those who have been around for a while. Were all still learning (one hopes), but entry-level people are still learning the basics, and seniors have greater responsibility, along with the potential for making bigger mistakes.
In the era of AI, chatbots have revolutionized how we interact with technology. Perhaps one of the most impactful uses is in the healthcare industry. Chatbots are able to deliver fast, accurate information, and help individuals more effectively manage their health. In this article, we’ll learn how to develop a medical chatbot using Gemini 2.0, […] The post Building a Medical Chatbot with Gemini 2.0, Flask and Vector Embedding appeared first on Analytics Vidhya.
In this article, we dive into the concepts of machine learning and artificial intelligence model explainability and interpretability. We explore why understanding how models make predictions is crucial, especially as these technologies are used in critical fields like healthcare, finance, and legal systems. Through tools like LIME and SHAP, we demonstrate how to gain insights […] The post ML and AI Model Explainability and Interpretability appeared first on Analytics Vidhya.
Beam search is a powerful decoding algorithm extensively used in natural language processing (NLP) and machine learning. It is especially important in sequence generation tasks such as text generation, machine translation, and summarization. Beam search balances between exploring the search space efficiently and generating high-quality output. In this blog, we will dive deep into the […] The post What is Beam Search in NLP Decoding?
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
Qwen just released 8 new models as part of its latest family – Qwen3, showcasing promising capabilities. The flagship model, Qwen3-235B-A22B, outperformed most other models including DeepSeek-R1, OpenAI’s o1, o3-mini, Grok 3, and Gemini 2.5-Pro, in standard benchmarks. Meanwhile, the small Qwen3-30B-A3B outperformed QWQ-32B which has approximately 10 times the activated parameters as the new […] The post How to Build RAG Systems and AI Agents with Qwen3 appeared first on Analyt
Computer vision, a dynamic field blending artificial intelligence and image processing, is reshaping industries like healthcare, automotive, and entertainment. With advancements such as OpenAIs GPT-4 Vision and Metas Segment Anything Model (SAM), computer vision has become more accessible and powerful than ever. By 2025, the global computer vision market is projected to surpass $41 billion, fueled by innovations in […] The post 30 Must-Try Computer Vision Projects for 2025 appeared first o
Summary Introduction Generative AI (GenAI) has evolved from experimental research to enterprise-grade applications in record time. The rise of tools like ChatGPT, AI-powered copilots, and custom AI agents across industries, has led to the emergence of a bunch of new roles and teams in organizations. One such booming new career path is that of a […] The post Generative AI Data Scientist: A Booming New Job Role appeared first on Analytics Vidhya.
China is advancing rapidly in generative AI, building on successes like DeepSeek models and Kimi k1.5 in language models. Now, its leading the vision domain with OmniHuman and Goku excelling in 3D modeling and video synthesis. With Step-Video-T2V, China directly challenges top text-to-video models like Sora, Veo 2, and Movie Gen. Developed by Stepfun AI, […] The post Chinas New AI Video Star: Step-Video-T2V appeared first on Analytics Vidhya.
Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.
AI agents are changing how businesses operate, offering unprecedented opportunities for efficiency, scalability, and innovation. Major AI business organisations like Meta, Google, etc are rapidly implementing these AI agents into their workflows, while emerging players like CrewAI and LangChain are spearheading the agentic AI movement to create robust autonomous systems.
We’re already into the second month of 2025, and every passing day brings us closer to Artificial General Intelligence (AGI)AI that can tackle complex problems across multiple sectors at a human level. Take DeepSeek, for instance. Until recently, could you have imagined an organization before 2024 that could build a cutting-edge Generative AI model for […] The post A Comprehensive Guide to Pre-training LLMs appeared first on Analytics Vidhya.
You know how, back in the day, we used simple wordcount tricks to represent text? Well, things have come a long way since then. Now, when we talk about the evolution of embeddings, we mean numerical snapshots that capture not just which words appear but what they really mean, how they relate to each other […] The post 14 Powerful Techniques Defining the Evolution of Embedding appeared first on Analytics Vidhya.
In this Leading with Data, we explore the transformative journey of Navin Dhananjaya, Chief Solutions Officer at Merkle, as he shares key milestones, practical applications of generative AI, and future possibilities for AI agents. Discover how AI is reshaping customer experiences and the data science landscape. You can listen to this episode of Leading with […] The post Exploring AI Agents in Customer Experience with Navin Dhananjaya appeared first on Analytics Vidhya.
Speaker: Claire Grosjean, Global Finance & Operations Executive
Finance teams are drowning in data—but is it actually helping them spend smarter? Without the right approach, excess spending, inefficiencies, and missed opportunities continue to drain profitability. While analytics offers powerful insights, financial intelligence requires more than just numbers—it takes the right blend of automation, strategy, and human expertise.
DeepSeek has made significant strides in AI model development, with the release of DeepSeek-V3 in December 2024, followed by the groundbreaking R1 in January 2025. DeepSeek-V3 is a Mixture-of-Experts (MoE) model that focuses on maximizing efficiency without compromising performance. DeepSeek-R1, on the other hand, incorporates reinforcement learning to enhance reasoning and decision-making.
Fine-tuning large language models (LLMs) is an essential technique for customizing LLMs for specific needs, such as adopting a particular writing style or focusing on a specific domain. OpenAI and Google AI Studio are two major platforms offering tools for this purpose, each with distinct features and workflows. In this article, we will examine how […] The post Fine-tuning an LLM to Write Like You on OpenAI Platform vs Google AI Studio appeared first on Analytics Vidhya.
I still remember last year’s NVIDIA GTC, Jensen Huang with its visionary approach along with a touch of humour introduced the developers with promises to redefine technology. From Blackwell architecture, Generative AI with NIM, GB200 AI Chip to Project Groot and other things, we got a glimpse into the future of technology. Now the future […] The post 10 NVIDIA GTC 2025 Announements that You Must Know appeared first on Analytics Vidhya.
In many real-world applications, data is not purely textualit may include images, tables, and charts that help reinforce the narrative. A multimodal report generator allows you to incorporate both text and images into a final output, making your reports more dynamic and visually rich. This article outlines how to build such a pipeline using: The […] The post Multimodal Financial Report Generation (from a Slide Deck) using Llamaindex appeared first on Analytics Vidhya.
AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.
Deep learning GPU benchmarks has revolutionized the way we solve complex problems, from image recognition to natural language processing. However, while training these models often relies on high-performance GPUs, deploying them effectively in resource-constrained environments such as edge devices or systems with limited hardware presents unique challenges.
Microsoft’s Phi-4 model is available on Hugging Face, offering developers a powerful tool for advanced text generation and reasoning tasks. In this article, well walk you through the steps to access and use Phi-4, from creating a Hugging Face account to generating outputs with the model. Well also explore key features, including its optimized performance […] The post How to Access Phi-4 Using Hugging Face?
The human mind naturally perceives language, vision, smell, and touch, enabling us to understand our surroundings. We are particularly inclined toward linguistic thought and visual memory. As GenAI models continue to grow, researchers are now working on extending their capabilities by incorporating multimodality. Large Language models (LLMs) only accept text as input and produce text […] The post Empowering AI with Senses: A Journey into Multimodal LLMs Part 1 appeared first on Analytics V
The day OpenAI released the o1 model, there was chatter everywhere that we are now closer to AGI than ever. While AGI (Artificial General Intelligence) still looms somewhere in the future, we do have the o1 model. However, it isnt really accessible to many, thanks to its whopping ticket price of $200 per month. Now […] The post DeepSeek R1 vs OpenAI o1 vs Sonnet 3.5: Battle of the Best LLMs appeared first on Analytics Vidhya.
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.
Apache Iceberg is a modern table format designed to overcome the limitations of traditional Hive tables, offering improved performance, consistency, and scalability. In this article, we will explore the evolution of Iceberg, its key features like ACID transactions, partition evolution, and time travel, and how it integrates with modern data lakes. Well also dive into […] The post How to Use Apache Iceberg Tables?
yFiles is a powerful SDK designed to simplify the visualization of complex networks and data relationships. When combined with LlamaIndex, it becomes a powerful tool for visualizing and interacting with knowledge graphs in real time. This guide walks you through the integration process, highlights essential steps, and demonstrates key features for an impactful, useful and […] The post How to Integrate yFiles with LlamaIndex for Knowledge Graph Visualization?
Building an Agentic Retrieval-Augmented Generation (RAG) system with SmolAgents enables the development of AI agents capable of autonomous decision-making and task execution. SmolAgents, a minimalist library by Hugging Face, facilitates the creation of such agents in a concise and efficient manner. In this article, we will go step by step to build the Agentic RAG […] The post How to Build Agentic RAG with SmolAgents?
Elon Musks xAI has just completed the pretraining of Grok 3, a massive upgrade over its predecessor, Grok 2, with 10 times more computational power. But is this enough to outpace rivals like OpenAI and Google DeepMind? Lets break it down. Grok 3: 10X More Compute Power Than Grok 2 Grok 3 was trained on […] The post Elon Musks Grok 3: 10X Power, But Can it Beat ChatGPT?
GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
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