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Confessions

Pandeyji is confused between the implication of that kiss and his very own pledge to remain a bachelor till 40. Meanwhile Neha dates a few more men and is confused about the 'one'.

Pandeyji and Neha spend more and more time with each other as he gears her up for the final push with only a handful of dates left. Neha forces Teetotaller Pandeyji to drink and soon and the night turns memorable.

Neha's job comes with a catch-22 situation and Pandeyji's weird dating tips are put to action as Neha starts the first of her many dates in search of a groom.

Neha and her girl-gang hit speed-dating that finally lands her a worthy date. At the same time Neha runs into Pandeyji, an astrologer by passion who pronounces no immediate marriage for Neha!

Neha Chawla, has kissed many a frogs but none that turned into her Prince Charming. On her 27th birthday when her current boyfriend dumps her, she makes a vow to get married in 3 months flat!

Neha's confession leads to chaos and confusion regarding her feelings. However, the girl-gang force her to meet the last, date#12, out of their choice; technically a blind date for Neha. What's in store for her?

Flightpath with Alok Aviation entrepreneur Alok Anand explores what makes the aircraft leasing business tick. He meets industry leaders on this journey and discovers their success secrets, and their career flightpath as well as understanding how different business models operate. Come along if aviation financing and leasing interests you and you are keen to learn from the practitioners of the industry. #assetmanagement #aviation #aircraftleasing #aviationfinance #flightpath #alok #flightpathwithalok Linkedin: https://www.linkedin.com/in/alokanand23/Watch our video podcasts here: https://...

Looking for real talk on the future of Oil, Gas, Chemicals and Energy? I am Anand Jha, with nearly two decades of experience, this show cuts through the noise around the industry as I chat with industry leaders about their journeys, breakthrough technologies, and what’s next in energy and business. Whether you’re building your career or just curious about the energy industry, this podcast clears up the confusion and delivers insights that matter. Tune in weekly for fresh perspectives and practical advice!

Vector Databases for Generative AI Applications" provides a comprehensive overview of how vector databases empower generative AI applications. It begins by explaining the core concepts of vector embeddings and vector databases, highlighting their advantages over traditional databases for storing and retrieving data based on similarity. The document then details the process of designing and implementing a vector database workflow, including data preprocessing, database selection, and integration with generative AI models. The document also discusses various applications of vector databases in t

A comprehensive guide to understanding and implementing generative AI in the field of drug safety. The document explains the fundamentals of generative AI and its application in pharmacovigilance, including its potential for improving adverse event detection, risk prediction, data augmentation, and signal detection. It also examines the ethical, legal, and regulatory considerations surrounding AI in this domain

Explores the emerging field of generative artificial intelligence, which focuses on creating new content like images, music, and text. The document examines its core concepts and technologies, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models. It then details how generative AI is transforming various industries, such as healthcare, finance, manufacturing, and retail, by automating creative processes, improving efficiency, and facilitating innovation

A Comprehensive Guide to Innovation, Implementation, and Continuous Improvement," is a guide to help organizations transition to a new standard or framework known as SGP 32. The document details the key aspects of SGP 32, including its historical context, benefits, challenges, and implementation strategies. It covers areas such as resource allocation, change management, performance metrics, and best practices for achieving a successful transition. The document also explores the future outlook of SGP 32, emphasizing the importance of innovation, continuous improvement, and adapting to evolving

Explains the security considerations for generative artificial intelligence (AI), which is a type of AI capable of creating new content, such as images and text. The document examines common threats to generative AI systems, such as adversarial attacks, data poisoning, and model theft, and presents techniques to mitigate these risks, such as robust training data, adversarial training, and secure data storage. The document also explores the ethical implications of generative AI, including issues of bias and discrimination, and offers guidelines for developing and deploying AI in a responsible

A guide for anyone preparing for interviews about large language models (LLMs). It covers the fundamentals of LLMs and their applications, including concepts like tokenization, embeddings, neural networks, and common NLP tasks. The guide also provides sample interview questions and coding challenges, broken down into basic, intermediate, and advanced categories. The document concludes with advice for interview preparation, including study resources, mock interview tips, and strategies for addressing behavioral questions.

A comprehensive guide to the rapidly developing field of generative artificial intelligence (AI). The document introduces the core concepts, techniques, and applications of generative AI, including its history and evolution, key terminology, and different types of generative models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and diffusion models. The text provides practical examples, code snippets, and step-by-step instructions to help readers develop their own generative AI systems. Furthermore, the document explores advanced techniques like fine-tuning

Acts as a comprehensive guide to the field of Large Language Model (LLM) training, covering various aspects from the basics of natural language processing (NLP) and LLM architecture to advanced techniques like transfer learning, reinforcement learning, and multi-task learning. The book also addresses practical considerations like data collection, preprocessing, and model evaluation while discussing ethical and privacy implications. Lastly, the text includes hands-on exercises an

Comprehensive guide to large language models (LLMs), artificial intelligence systems designed to understand and manipulate human language. It covers the history and evolution of LLMs, including key concepts like the Transformer architecture and attention mechanisms. The document then explores popular LLM models, such as GPT-3 and BERT, along with their use cases and applications in various industries, including business, finance, marketing, entertainment, and healthcare. The text further details the training process for LLMs, including data collection, preprocessing, and optimization technique

Overview of how to understand, train, and deploy large language models (LLMs), powerful AI systems capable of processing and generating human-like text. The guide begins by defining LLMs and their key concepts, then covers setting up an environment, collecting and preparing training data, selecting appropriate LLM architectures, and training the model itself. Further chapters explore how to fine-tune pre-trained LLMs for specific tasks, deploy these models for real-world applications, and evaluate their performance using various metrics

Algorithms that create new content like text, images, and music. The document explores key ethical issues like bias and fairness, transparency and explainability, privacy and data security, autonomy and control, and accountability and responsibility. It also discusses frameworks for responsible development and deployment, including guidelines, regulations, and stakeholder perspectives.

LLM Marketing: Harnessing AI to Revolutionize Customer Engagement explores the transformative power of Large Language Models (LLMs) in the marketing landscape. This book provides marketers, business leaders, and technologists with actionable insights into how AI-driven LLMs can optimize customer engagement strategies. It dives into the capabilities of LLMs in understanding customer behavior, crafting personalized content, automating responses, and delivering intelligent, real-time interactions.