Analytics Vidhya

JULY 13, 2024

Introduction Imagine you’re standing at the edge of a dense forest, each path leading in a different direction, and your goal is to find the most promising route to a hidden treasure. This scenario mirrors the fascinating approach of Tree of Thoughts in AI prompt engineering. Just like you’d weigh various trails, the Tree of […] The post Implementing the Tree of Thoughts Method in AI appeared first on Analytics Vidhya.

Prompt Engineer 300

Prompt Engineer Prompt Engineering AI AI 300

Marktechpost

JULY 13, 2024

Large Language Models (LLMs) like GPT-4 exhibit impressive capabilities in text generation tasks such as summarization and question answering. However, they often produce “hallucinations,” generating content that is factually incorrect or contextually irrelevant. The problem is particularly acute when the LLMs are provided with correct facts but still produce inaccurate outputs, termed “contextual hallucinations.” These errors undermine the reliability of LLMs in applicat

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LLM Large Language Models ML Artificial Intelligence 133

Analytics Vidhya

JULY 13, 2024

Introduction By incorporating visual capabilities into the potent language model GPT-4, ChatGPT-4 Vision, or GPT-4V, signifies a noteworthy breakthrough in the field of artificial intelligence. With this improvement, the model can now process, comprehend, and produce visual content, making it a flexible tool suitable for various uses. The primary functions of ChatGPT-4 Vision, such as […] The post All About ChatGPT-4 Vision’s Image and Video Capabilities appeared first on Analytics Vidhya.

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Marktechpost

JULY 13, 2024

Large Language Models (LLMs) have made significant strides in recent years, prompting researchers to explore the development of Large Vision Language Models (LVLMs). These models aim to integrate visual and textual information processing capabilities. However, current open-source LVLMs face challenges in matching the versatility of proprietary models like GPT-4, Gemini Pro, and Claude 3.

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Large Language Models Artificial Intelligence Artificial Intelligence ML 131

Speaker: David Warren and Kevin O'Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

Towards AI

JULY 13, 2024

Author(s): Mélony Qin (aka cloudmelon) Originally published on Towards AI. Decoding NVIDIA’s AI + HPC and software + hardware innovation strategy NVIDIA’s relentless pursuit of innovation and excellence in AI and high-performance computing (HPC) is underpinned by several hidden assets that collectively fuel its billion-dollar AI vision. If you’ve been reading my blogs, you’d know that I always speak highly of NVIDIA for their greatness at building the art and science of hardware and software pla

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Software Development AI AI Machine Learning 109

Towards AI

JULY 13, 2024

Author(s): Talib Originally published on Towards AI. I will start by describing why we need a vector search for RAG, and how vectors and vector databases work, and then focus on the Azure AI search. You might have used large language models like GPT-3.5, GPT-4o, or any of the other models, Mistral or Perplexity, and these large language models are awe-inspiring with what they can do and how much of a grasp they have of language.

Prompt Engineer 97

Prompt Engineer Prompt Engineering Large Language Models Generative AI 97

Marktechpost

JULY 13, 2024

Large language models (LLMs) have been crucial for driving artificial intelligence and natural language processing to new heights. These models have demonstrated remarkable abilities in understanding and generating human language, with applications spanning, but not limited to, healthcare, education, and social interactions. However, LLMs need to improve in the effectiveness and control of in-context learning (ICL).

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Large Language Models Natural Language Processing LLM Artificial Intelligence 126

Towards AI

JULY 13, 2024

Last Updated on July 13, 2024 by Editorial Team Author(s): Jonathan Bennion Originally published on Towards AI. Image created by the author Another of the dirty little secrets of AI systems (and the hype surrounding their future) are ongoing prompt injection issues. Not a new security issue, yet we will be dealing with this in every tool out there! How I hacked through Priceline’s AI tool It only took 2 minutes (and I have confirmation Priceline is currently fixing this).

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OpenAI Chatbots AI Chatbots Automation 91

Marktechpost

JULY 13, 2024

Scientific discovery has been a cornerstone of human advancement for centuries, traditionally relying on manual processes. However, the emergence of large language models (LLMs) with advanced reasoning capabilities and the ability to interact with external tools and agents has opened up new possibilities for autonomous discovery systems. The challenge lies in developing a fully autonomous system capable of generating and verifying hypotheses within the realm of data-driven discovery.

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LLM Large Language Models Automation Data Analysis 124

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Towards AI

JULY 13, 2024

Last Updated on July 13, 2024 by Editorial Team Author(s): Shenggang Li Originally published on Towards AI. Utilizing DDPG and SHAP for Pricing Strategies in RetailPhoto by Brooke Lark on Unsplash Retail pricing strategies are important for optimizing sales and profits. Effective pricing influences consumer behavior and maximizes revenue by considering demand, market conditions, and competition.

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Explainable AI Explainability Algorithm AI 91

Marktechpost

JULY 13, 2024

Large Language Models (LLMs) have become critical tools in various domains due to their exceptional ability to understand and generate human language. These models, which often contain billions of parameters, require extensive computational resources for training and fine-tuning. The primary challenge lies in efficiently managing the memory and computational demands to make these models accessible to various users & applications.

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Machine Learning Large Language Models LLM ML 119

Towards AI

JULY 13, 2024

Last Updated on July 13, 2024 by Editorial Team Author(s): Serop Baghdadlian Originally published on Towards AI. Read 10x more relevant articles by building the most efficient system for tracking and organizing machine learning & engineering articles.Photo by Fujiphilm on Unsplash Have you ever felt that you’re not staying up to date with the latest innovations, architecture designs, and new tech in machine learning?

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Machine Learning Data Science Generative AI AI 88

Marktechpost

JULY 13, 2024

Recent progress in Large Multimodal Models (LMMs) has demonstrated remarkable capabilities in various multimodal settings, moving closer to the goal of artificial general intelligence. By using large amounts of vision-language data, they enhance LLMs with visual abilities, by aligning vision encoders. However, most open-source LMMs have focused mainly on single-image scenarios, leaving the more complex multi-image scenarios mostly unexplored.

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Computer Vision LLM ML AI 118

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

Towards AI

JULY 13, 2024

Author(s): Louis-François Bouchard Originally published on Towards AI. Efficient Strategies to Balance Convenience, Privacy, and Cost Note: this post was written by 3 ML & AI engineers behind the High Learning Rate newsletter. Let’s talk about an important topic: the privacy concern with large language models (LLMs). We (authors, 3 ML/AI engineers, and owners of the High Learning Rate newsletter) see a lot of clients taking overkill solutions because of privacy concerns.

Large Language Models 88

Large Language Models AI Engineer ChatGPT Chatbots 88

Marktechpost

JULY 13, 2024

The Retrieval-Augmented Generation (RAG) pipeline includes four major steps— generating embeddings for queries and documents, retrieving relevant documents, analyzing the retrieved data, and generating the final response. Each of these steps. requires separate queries and tools, resulting in a cumbersome, time-consuming, and potentially error-prone process.

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Machine Learning Natural Language Processing NLP Python 116

Towards AI

JULY 13, 2024

Last Updated on July 13, 2024 by Editorial Team Author(s): Lorentz Yeung Originally published on Towards AI. Picture generated by Dall-E. Two digital llamas racing against each other, one labeled ‘Gen 2’ and the other ‘Gen 3’ When beginning LLM operations, a key question is which model to use. As a fan of LLaMA models, I wondered if LLaMA 3 is necessarily better than LLaMA 2.

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LLM AI AI Machine Learning 86

Marktechpost

JULY 13, 2024

In an effort to track its advancement towards creating Artificial Intelligence (AI) that can surpass human performance, OpenAI has launched a new classification system. According to a Bloomberg article , OpenAI has recently discussed a five-level framework to clarify its goal for AI safety and future improvements. Level 1: Conversational AI AI programs such as ChatGPT can converse intelligibly with people at a basic level.

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Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

Towards AI

JULY 13, 2024

Last Updated on July 13, 2024 by Editorial Team Author(s): John Loewen, PhD Originally published on Towards AI. Mapping historical shipwreck data from Harvard data set There are some terrific sources for data sets out there on the internet, including historical shipwreck data. One of the weekly updates I receive as part of expanding my knowledge on available datasets comes from Data is Plural: This site provides a weekly newsletter on interesting data sets.

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Python AI AI Machine Learning 85

Marktechpost

JULY 13, 2024

In robotics, understanding the position and movement of a sensor suite within its environment is crucial. Traditional methods, called Simultaneous Localization and Mapping (SLAM), often face challenges with unsynchronized sensor data and require complex computations. These methods must estimate the position at discrete time intervals, making it difficult to handle data from various sensors that do not sync perfectly.

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Robotics Artificial Intelligence Artificial Intelligence AI 111

Towards AI

JULY 13, 2024

Author(s): Satyajit Chaudhuri Originally published on Towards AI. Introduction Imagine if you could forecast future trends with the same ease that language models understand text. Whether you’re predicting stock prices, healthcare demands, or optimizing logistics, accurate time-series forecasting is crucial. Traditional methods like ARIMA struggle with modern data complexities, but deep learning has shown promise.

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Auto-complete Neural Network BERT Large Language Models 83

Marktechpost

JULY 13, 2024

A fundamental topic in computer vision for nearly half a century, stereo matching involves calculating dense disparity maps from two corrected pictures. It plays a critical role in many applications, including autonomous driving, robotics, and augmented reality, among many others. According to their cost-volume computation and optimization methodologies, existing surveys categorize end-to-end architectures into 2D and 3D classes.

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Deep Learning Computer Vision Categorization Robotics 110

Speaker: Simran Kaur, Founder & CEO at Tattva Health Inc.

The healthcare landscape is being revolutionized by AI and cutting-edge digital technologies, reshaping how patients receive care and interact with providers. In this webinar led by Simran Kaur, we will explore how AI-driven solutions are enhancing patient communication, improving care quality, and empowering preventive and predictive medicine. You'll also learn how AI is streamlining healthcare processes, helping providers offer more efficient, personalized care and enabling faster, data-driven

AI

Towards AI

JULY 13, 2024

Author(s): Mazen Ahmed Originally published on Towards AI. AI in Early Disease DetectionImage by Author I find it deeply fascinating how the development of mathematics, in particular algorithms, has touched almost every facet of human innovation. As we enter the era of Artificial Intelligence (AI), over very short time periods, new uses of the technology are being discovered.

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Algorithm Artificial Intelligence Artificial Intelligence AI 80

Bugra Akyildiz

JULY 13, 2024

Articles PyTorch team published a manual for torch.compile function, torch.compile is a complex and relatively new feature in PyTorch designed to optimize and accelerate model execution. It's primarily aimed at technical end-users who understand their models but may not be familiar with PyTorch's internals. I will cover this doc in a very detailed manner.

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Python ChatGPT LLM Affective Computing 52

Towards AI

JULY 13, 2024

Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Large Language Models Research Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers need to stay informed on the latest progress. This article summarizes some of the most important LLM papers published during the First Week of July 2024.

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Large Language Models LLM Data Science Machine Learning 78

Towards AI

JULY 13, 2024

Last Updated on July 14, 2024 by Editorial Team Author(s): Eram Khan Originally published on Towards AI. In this article I explore if it is actually possible to beat the blackjack dealer using strategic thought. Of course, the underlying idea here is to show the use of simulation and how a game can be modeled mathematically. (But please do feel to try out any of below mentioned strategies if interested!

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Python AI AI Data Science 74

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