Sun.Jul 07, 2024

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9 Free AI Courses from Stanford

Analytics Vidhya

Introduction Artificial Intelligence (AI) is transforming industries and creating new possibilities in various fields. Stanford University, renowned for its contributions to AI research, offers several free courses that can help you get started or advance your knowledge in this exciting domain. Whether you’re a beginner or an experienced professional, these courses provide valuable insights into […] The post 9 Free AI Courses from Stanford appeared first on Analytics Vidhya.

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5 Best AI Tools for the Construction Industry (July 2024)

Unite.AI

AI technologies are disrupting the construction industry. As construction projects become increasingly complex, project managers and construction professionals are turning to AI-powered tools to streamline processes, improve efficiency, and make data-driven decisions. In this piece, we will explore the best AI tools for construction, highlighting how these innovative solutions are reshaping project management and optimizing the entire construction process from planning to completion.

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What are the TCL Commands in SQL?

Analytics Vidhya

Introduction TCL (Transaction Control Language) commands are crucial in SQL overseeing changes enacted by DML (Data Manipulation Language) statements. These commands enable users and database administrators to manage transaction processes, maintaining data consistency and integrity. This article explores the main TCL commands, their functions, and their practical uses.

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InternLM2.5-7B-Chat: Open Sourcing Large Language Models with Unmatched Reasoning, Long-Context Handling, and Enhanced Tool Use

Marktechpost

InternLM has unveiled its latest advancement in open large language models, the InternLM2.5-7B-Chat , available in GGUF format. This model is compatible with llama.cpp, an open-source framework for LLM inference, can be utilized locally and in the cloud across various hardware platforms. The GGUF format offers half-precision and low-bit quantized versions, including q5_0, q5_k_m, q6_k, and q8_0.

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Usage-Based Monetization Musts: A Roadmap for Sustainable Revenue Growth

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

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Apple Goes Small and Super Multimodal

TheSequence

Created Using Ideogram Next Week in The Sequence: Edge 411: We dive into episodic memory and autonomous agents including the Larimar research by Princeton University. We also explore the Chroma database stack. Edge 412: We review three recent papers from Microsoft about privacy in generative AI. You can subscribe to The Sequence below: TheSequence is a reader-supported publication.

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Incorporight – Legal Blockchain Without The Hype

Artificial Lawyer

Remember the idea of using the blockchain for legal needs? Well, it’s still with us and legal tech startup Incorporight is based upon it.

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T-FREE: A Tokenizer-Free Approach for Efficient and Scalable Text Encoding in Large Language Models

Marktechpost

Natural language processing (NLP) drives researchers to develop algorithms that enable computers to understand, interpret, and generate human languages. These efforts cover various applications, such as machine translation, sentiment analysis, and intelligent conversational agents. The problem concerns the inefficiencies and limitations of tokenizers used in large language models (LLMs).

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Bytes Are All You Need: Transformers Operating Directly On File Bytes

Machine Learning Research at Apple

Modern deep learning approaches usually utilize modality-specific processing. For example, the most common deep learning approach to image classification involves decoding image file bytes into an RGB tensor which is passed into a neural network. Instead, we investigate modality-independent representation learning by performing classification directly on file bytes, without the need for decoding files at inference time.

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Policy Learning with Large World Models: Advancing Multi-Task Reinforcement Learning Efficiency and Performance

Marktechpost

Reinforcement Learning (RL) excels at tackling individual tasks but struggles with multitasking, especially across different robotic forms. World models, which simulate environments, offer scalable solutions but often rely on inefficient, high-variance optimization methods. While large models trained on vast datasets have advanced generalizability in robotics, they typically need near-expert data and fail to adapt across diverse morphologies.

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15 Modern Use Cases for Enterprise Business Intelligence

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?

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MIA-Bench: Towards Better Instruction Following Evaluation of Multimodal LLMs

Machine Learning Research at Apple

We introduce MIA-Bench, a new benchmark designed to evaluate multimodal large language models (MLLMs) on their ability to strictly adhere to complex instructions. Our benchmark comprises a diverse set of 400 image-prompt pairs, each crafted to challenge the models' compliance with layered instructions in generating accurate responses that satisfy specific requested patterns.

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How ChatGPT is Revolutionizing Customer Service in 2024

Marktechpost

In 2024, the landscape of customer service is undergoing a profound transformation, largely driven by the advancements in artificial intelligence (AI). Among these advancements, OpenAI’s ChatGPT has become a pivotal tool in revolutionizing how businesses interact with customers. This innovative technology enhances customer experiences and streamlines company operations across various industries.

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Free AI-Powered Proofreading

Robot Writers AI

Courtesy ChatGPT and Grammarly Among ChatGPT’s myriad editorial skills is its ability to proofread your text at an extremely high level of proficiency. And if all you’re looking for is an occasional proofread, you’ll find you can get help from ChatGPT — combined with similar AI tools — for free. I began using ChatGPT as a back-up proofer for my primary proofreading tool — Grammarly — after I saw it consistently catching errors in text that Grammarly was

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Top Free Artificial Intelligence AI Courses from Ivy League Colleges

Marktechpost

Ivy League Colleges such as Harvard, Stanford, and MIT offer a range of free online courses that make high-quality education accessible to a global audience. These courses span various fields, including computer science, data science, business, and the humanities, providing valuable learning opportunities regardless of geographical or financial constraints.

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From Diagnosis to Delivery: How AI is Revolutionizing the Patient Experience

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

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Search4LLM and LLM4Search: Improving Language Models and Search Engines

Marktechpost

The rise of the Internet has flooded with information, making search engines more important than ever for navigating this vast online world. However, as user queries become more complex and expectations for precise, relevant, and up-to-date answers increase, traditional search technologies face various challenges to meet the requirement. Significant progress has been made in natural language processing (NLP) and information retrieval (IR) technologies.

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Researchers at the University College London Unravel the Universal Dynamics of Representation Learning in Deep Neural Networks

Marktechpost

Deep neural networks (DNNs) come in various sizes and structures. The specific architecture selected along with the dataset and learning algorithm used, is known to influence the neural patterns learned. Currently, a major challenge faced in the theory of deep learning is the issue of scalability. Although exact solutions to learning dynamics exist for simpler networks, adjusting even a small part of the network architecture often requires significant changes to the analysis.

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Researchers at IT University of Copenhagen Propose Self-Organizing Neural Networks for Enhanced Adaptability

Marktechpost

Artificial neural networks (ANNs) traditionally lack the adaptability and plasticity seen in biological neural networks. This limitation poses a significant challenge for their application in dynamic and unpredictable environments. The inability of ANNs to continuously adapt to new information and changing conditions hinders their effectiveness in real-time applications such as robotics and adaptive systems.

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Autonomous Robot Navigation and Efficient Data Collection: Human-Agent Joint Learning and Reinforcement-Based Autonomous Navigation

Marktechpost

In recent years, advancements in robotic technology have significantly impacted various fields, including industrial automation, logistics, and service sectors. Autonomous robot navigation and efficient data collection are crucial aspects that determine the effectiveness of these robotic systems. Based on the content of two detailed research papers, let’s delve into two primary topics: human-agent joint learning for robot manipulation skill acquisition and reinforcement learning-based auto

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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WorldBench: A Dynamic and Flexible LLM Benchmark Composed of Per-Country Data from the World Bank

Marktechpost

Large language models (LLMs) have gained significant attention for their impressive performance across various tasks, from summarizing news to writing code and answering trivia questions. Their effectiveness extends to real-world applications, with models like GPT-4 successfully passing legal and medical licensing exams. However, LLMs face two critical challenges: hallucination and performance disparities.

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A Survey of Advanced Retrieval Algorithms in Ad and Content Recommendation Systems: Mechanisms and Challenges

Marktechpost

Researchers from the University of Toronto present an insightful examination of the advanced algorithms used in modern ad and content recommendation systems. These systems drive user engagement and revenue generation in digital platforms. It explores various retrieval algorithms and their applications in ad targeting and content recommendation, shedding light on the mechanisms that power these systems and the challenges they face.

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Accelerating LLM Inference: Introducing SampleAttention for Efficient Long Context Processing

Marktechpost

Large language models (LLMs) now support very long context windows, but the quadratic complexity of standard attention results in significantly prolonged Time-to-First-Token (TTFT) latency. Existing methods to tackle this complexity require extra pretraining or finetuning and often compromise model accuracy. The quadratic nature of the vanilla attention mechanism in these models significantly increases computational time, making real-time interactions challenging.

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