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Our previous guide discussed the first Agentic AI design pattern from the Reflection, Tool Use, Planning, and Multi-Agent Patterns list. Now, we will talk about the Tool Use Pattern in Agentic AI. Firstly, let us reiterate the Reflection Pattern article: That article sheds light on how LLMs can use an iterative generation process and self-assessment […] The post What is Agentic AI Tool Use Pattern?
Quantum computing , once a theoretical field, is now rapidly transforming into a groundbreaking technological frontier. At the heart of this revolution are Q uantum Processing Units (QPUs) — the engines powering quantum computers. Unlike classical processors that rely on binary logic (bits representing 0s or 1s), QPUs leverage the unique properties of quantum mechanics to process information in ways that classical computers cannot.
With this blog, I would like to show one small agent built-in with `LangGraph` and Google Gemini for research purposes. The objective is to demonstrate one research agent (Paper-to-Voice Assistant) who plans to summarize the research paper. This tool will use a vision model to infer the information. This method only identifies the step and […] The post Paper-to-Voice Assistant: AI Agent Using Multimodal Approach appeared first on Analytics Vidhya.
IBM has taken the wraps off its most sophisticated family of AI models to date, dubbed Granite 3.0, at the company’s annual TechXchange event. The Granite 3.0 lineup includes a range of models designed for various applications: General purpose/language: 8B and 2B variants in both Instruct and Base configurations Safety: Guardian models in 8B and 2B sizes, designed to implement guardrails Mixture-of-Experts: A series of models optimised for different deployment scenarios IBM claims that its
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 Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
In a significant development that underscores the explosive growth of artificial intelligence technologies, Perplexity AI is reportedly in discussions to secure approximately $500 million in new funding. The potential investment round could catapult the AI search company's valuation to $8 billion, marking a substantial increase from its previous valuation earlier this year.
In the age of relentless digital progression, businesses stand on the brink of a data renaissance. The proliferation of digital devices and interactions has resulted in an unparalleled influx of data, which businesses must navigate with precision and strategy. Enterprises require more than just traditional data management; they need to harness the momentum of advanced data intelligence solutions to help ensure innovative prowess and maintain market dominance.
In the age of relentless digital progression, businesses stand on the brink of a data renaissance. The proliferation of digital devices and interactions has resulted in an unparalleled influx of data, which businesses must navigate with precision and strategy. Enterprises require more than just traditional data management; they need to harness the momentum of advanced data intelligence solutions to help ensure innovative prowess and maintain market dominance.
In recent years, universities have seen a growing need to address incidents ranging from minor violations to serious criminal activities. As the volume of video evidence generated from sources like campus surveillance, mobile phones, and body-worn cameras continues to rise, colleges face new challenges in managing and analyzing this data effectively.
Adopting Generative AI (gen AI) is no longer a matter of future speculation. With the vast potential it offers, companies are already maximizing its use to streamline operations, boost productivity, and pass these benefits on to their clients. This transformation comes with new challenges. As clients begin implementing AI on premises, the first step is to evaluate whether their data centers are ready: upgrading the IT infrastructure involves adequate power and cooling, preparing the network to h
Converting speech to text in Java can present challenges due to the complexity of audio processing and the need for accurate speech recognition. However, modern libraries and cloud-based APIs have made it easier to implement these features in Java applications. This article focuses on how to convert speech to text using AssemblyAI's Java SDK, a powerful solution for high-accuracy transcription tasks.
NVIDIA is expanding its collaboration with Microsoft to support global AI startups across industries — with an initial focus on healthcare and life sciences companies. Announced today at the HLTH healthcare innovation conference, the initiative connects the startup ecosystem by bringing together the NVIDIA Inception global program for cutting-edge startups and Microsoft for Startups to broaden innovators’ access to accelerated computing by providing cloud credits, software for AI development and
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.
The NVIDIA AI Summit India, taking place October 23–25 at the Jio World Convention Centre in Mumbai, will bring together the brightest minds to explore how India is tackling the world’s grand challenges. A major highlight: a fireside chat with NVIDIA founder and CEO Jensen Huang on October 24. He’ll share his insights on AI’s pivotal role in reshaping industries and how India is emerging as a global AI leader, and be joined by the chairman and managing director of Reliance Industries, Mukesh Amb
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
Artificial intelligence is advancing rapidly, but enterprises face many obstacles when trying to leverage AI effectively. Organizations require models that are adaptable, secure, and capable of understanding domain-specific contexts while also maintaining compliance and privacy standards. Traditional AI models often struggle with delivering such tailored performance, requiring businesses to make a trade-off between customization and general applicability.
Model Predictive Control (MPC), or receding horizon control, aims to maximize an objective function over a planning horizon by leveraging a dynamics model and a planner to select actions. The flexibility of MPC allows it to adapt to novel reward functions at test time, unlike policy learning methods that focus on a fixed reward. Diffusion models learn world dynamics and action sequence proposals from offline data to improve MPC.
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
Computer vision is a branch of Artificial Intelligence (AI) that studies how machines can interpret and understand visual information, such as images and videos.
Accelerating inference in large language models (LLMs) is challenging due to their high computational and memory requirements, leading to significant financial and energy costs. Current solutions, such as sparsity, quantization, or pruning, often require specialized hardware or result in decreased model accuracy, making efficient deployment difficult.
The rapid progress of text-to-image (T2I) diffusion models has made it possible to generate highly detailed and accurate images from text inputs. However, as the length of the input text increases, current encoding methods, such as CLIP (Contrastive Language-Image Pretraining), encounter various limitations. These methods struggle to capture the full complexity of long text descriptions, making it difficult to maintain alignment between the text and the generated images which creates challenges
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.
Large language models (LLMs) can understand and generate human-like text across various applications. However, despite their success, LLMs often need help in mathematical reasoning, especially when solving complex problems requiring logical, step-by-step thinking. This research field is evolving rapidly as AI researchers explore new methods to enhance LLMs’ capabilities in handling advanced reasoning tasks, particularly in mathematics.
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.
As large language models (LLMs) become increasingly capable and better day by day, their safety has become a critical topic for research. To create a safe model, model providers usually pre-define a policy or a set of rules. These rules help to ensure the model follows a fixed set of principles, resulting in a model that works the same for everyone.
The dynamics of protein structures are crucial for understanding their functions and developing targeted drug treatments, particularly for cryptic binding sites. However, existing methods for generating conformational ensembles are plagued by inefficiencies or lack of generalizability to work beyond the systems they were trained on. Molecular dynamics (MD) simulations, the current standard for exploring protein movements, are computationally expensive and limited by short time-step requirements,
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