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In today’s world, as businesses face increasing pressure to adopt sustainable practices, the role of artificial intelligence in environmental monitoring has become paramount. Leveraging AI-powered tools for tracking greenhouse gas emissions, managing resources, and assessing environmental risks allows companies to make data-driven decisions that minimize their ecological footprint.
AI is the future and there’s no doubt it will make headway into the entertainment and E-sports industries. Given the extreme competitiveness of E-sports, gamers would love an AI assistant or manager to build the most elite team with maximum edge. Such tools could in theory use vast data and find patterns or even strategies […] The post Build an AI-Powered Valorant E-sports Manager with AWS Bedrock appeared first on Analytics Vidhya.
As more companies explore how AI can drive productivity, one crucial aspect is often overlooked: how employees are actually adopting and using these tools in their day-to-day work. The question isn’t whether AI can enhance productivity—it’s how companies can effectively support employees at every stage of AI engagement to maximize ROI. As CEO of Prodoscore, a leading provider of employee productivity and data intelligence software, I’ve seen firsthand how AI adoption—or the lack of it—plays out
Chatbots have evolved from simple question-answer systems to sophisticated, intelligent agents capable of handling complex conversations. As interactions in various fields become more nuanced, the demand for chatbots that can seamlessly manage multiple participants and complex workflows grows. Thanks to frameworks like AutoGen, creating dynamic multi-agent environments is now more accessible.
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 Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
AI burst onto the scene in record speed and hasn’t slowed down since. Initially an experimental leap toward internal efficiency, AI quickly transformed into a core pillar of product strategies across nearly every industry. The mounting pressure on businesses to adopt and integrate AI has never been greater—in fact, more than 90% of organizations already have.
Imagine waking up to an alarm that automatically changes based on your sleep quality, a digital assistant that understands your emotions to recommend the ideal breakfast, and a music selection that adapts to your morning activities. Doesn’t it seem like something out of a sci-fi movie? That is what we feel now, but soon enough […] The post Simplify Your Day With Generative AI appeared first on Analytics Vidhya.
Imagine waking up to an alarm that automatically changes based on your sleep quality, a digital assistant that understands your emotions to recommend the ideal breakfast, and a music selection that adapts to your morning activities. Doesn’t it seem like something out of a sci-fi movie? That is what we feel now, but soon enough […] The post Simplify Your Day With Generative AI appeared first on Analytics Vidhya.
Microsoft Research introduced AutoGen in September 2023 as an open-source Python framework for building AI agents capable of complex, multi-agent collaboration. AutoGen has already gained traction among researchers, developers, and organizations, with over 290 contributors on GitHub and nearly 900,000 downloads as of May 2024. Building on this success, Microsoft unveiled AutoGen Studio, a low-code interface that empowers developers to rapidly prototype and experiment with AI agents.
My new book Natural Language Generation has just been published. It takes a similar approach to my blog in many ways (indeed blog readers will find content from my blogs in the book). Its a book about NLG in the broad sense, including requirements, evaluation, and use cases, as well as technology; its not a book about how machine learning can be used for NLG (although this is of course discussed).
The rise of large language models (LLMs) and foundation models (FMs) has revolutionized the field of natural language processing (NLP) and artificial intelligence (AI). These powerful models, trained on vast amounts of data, can generate human-like text, answer questions, and even engage in creative writing tasks. However, training and deploying such models from scratch is a complex and resource-intensive process, often requiring specialized expertise and significant computational resources.
Robotics developers can greatly accelerate their work on AI-enabled robots, including humanoids , using new AI and simulation tools and workflows that NVIDIA revealed this week at the Conference for Robot Learning ( CoRL ) in Munich, Germany. The lineup includes the general availability of the NVIDIA Isaac Lab robot learning framework; six new humanoid robot learning workflows for Project GR00T , an initiative to accelerate humanoid robot development; and new world-model development tools for vi
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 emergence of generative AI has ushered in a new era of possibilities, enabling the creation of human-like text, images, code, and more. However, as exciting as these advancements are, data scientists often face challenges when it comes to developing UIs and to prototyping and interacting with their business users. Traditionally, building frontend and backend applications has required knowledge of web development frameworks and infrastructure management, which can be daunting for those with e
Author(s): Drewgelbard Originally published on Towards AI. Unlocking efficient legal document classification with NLP fine-tuning Image Created by Author Introduction In today’s fast-paced legal industry, professionals are inundated with an ever-growing volume of complex documents — from intricate contract provisions and merger agreements to regulatory compliance records and court filings.
The quest to strengthen national security has faced several challenges over the years, especially as the pace of technological advancement has far outstripped the speed of legislative and bureaucratic adaptation. With a growing dependence on technology, the need to protect sensitive information and secure communication channels is more pressing than ever.
Author(s): Nilesh Raghuvanshi Originally published on Towards AI. Improving Retrieval Augmented Generation (RAG) Systematically Choosing the right option — AI generated image Introduction Through my experience building an extractive question-answering system using Google’s QANet and BERT back in 2018, I quickly realized the significant impact that high-quality retrieval has on the overall performance of the system.
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
In recent years, generative AI has gained prominence in areas like content generation and customer support. However, applying it to complex systems involving decision-making, planning, and control is not straightforward. This paper explores how generative AI can be used in automating decision-making, such as in planning and optimization. It also highlights the challenges this approach […] The post Generative AI in Decision-Making: Potential, Pitfalls and Practical Solutions appeared first
Last Updated on November 6, 2024 by Editorial Team Author(s): Talha Nazar Originally published on Towards AI. Understanding student engagement is essential in the digital age of online education, internships, and competitions. But what if we could predict a student’s engagement level before they begin? This story explores CatBoost, a powerful machine-learning algorithm that handles both categorical and numerical data easily.
On Tuesday, two AI startups tried convincing the world their AI chatbots were good enough to be an accurate, real-time source of information during a high-stakes presidential election: xAI and Perplexity.
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
Chat.com now redirects to ChatGPT. On Wednesday, OpenAI CEO Sam Altman posted a simple URL on X: chat.com. It automatically routes to OpenAI’s popular chatbot, ChatGPT. Prior to this, the domain was owned by Dharmesh Shah, the founder and CTO of HubSpot. In early 2023, Shah purchased the chat.
Author(s): Nilesh Raghuvanshi Originally published on Towards AI. Improving Retrieval Augmented Generation (RAG) Systematically Fine-tuning for alignment— AI generated image Introduction In my last article, we saw that, while evaluating multiple embedding models on our domain-specific data, the huggingface/BAAI/bge-large-en-v1.5 model (1024 dimensions) showed competitive performance.
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.
The cofounder of Vero AI states, ‘You don’t need to become a data engineer to learn how to evaluate AI and other complex tools. You simply need to ask the right questions.’ There has never been a technology as conducive to BS as AI. Why?
Last Updated on November 6, 2024 by Editorial Team Author(s): Youssef Hosni Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. In the third article of the Building Multimodal RAG Application series, we explore the system architecture of building a multimodal retrieval-augmented generation (RAG) application.
Author(s): Nilesh Raghuvanshi Originally published on Towards AI. Improving Retrieval Augmented Generation (RAG) Systematically Evaluating the pipeline — AI generated image Introduction This is the third and final article in a short series on systematically improving retrieval-augmented generation (RAG). In earlier articles, we evaluated the performance of multiple embedding models on a domain-specific dataset and selected the optimal embedding model.
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.
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