Fri.Jul 05, 2024

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SQL DESCRIBE: Unveiling the Secrets of Your Tables

Analytics Vidhya

Introduction In relational databases, where data is meticulously organized in tables, understanding their structure is essential. SQL’s DESCRIBE (or DESC in some database systems) command gives you to become a data detective, peering into the internal makeup of your tables and extracting valuable information. Overview What is DESCRIBE? DESCRIBE is a non-destructive statement used to […] The post SQL DESCRIBE: Unveiling the Secrets of Your Tables appeared first on Analytics Vidhya.

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Putting AI to work in finance: Using generative AI for transformational change

IBM Journey to AI blog

Finance leaders are no strangers to the complexities and challenges that come with driving business growth. From navigating the intricacies of enterprise-wide digitization to adapting to shifting customer spending habits, the responsibilities of a CFO have never been more multifaceted. Amidst this complexity lies an opportunity. CFOs can harness the transformative power of generative AI (gen AI) to revolutionize finance operations and unlock new levels of efficiency, accuracy and insights.

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How to Use DALL-E 3 API for Image Generation?

Analytics Vidhya

Introduction In Artificial Intelligence(AI), DALL-E 3 has emerged as a game-changing advancement in picture-generating technology. This current edition, developed by OpenAI, improves on previous iterations to generate increasingly sophisticated, nuanced, and contextually correct images from textual descriptions. As the third installment in the DALL-E series, it marks a substantial advancement in AI’s ability to grasp […] The post How to Use DALL-E 3 API for Image Generation?

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Full Guide on LLM Synthetic Data Generation

Unite.AI

Large Language Models (LLMs) are powerful tools not just for generating human-like text, but also for creating high-quality synthetic data. This capability is changing how we approach AI development, particularly in scenarios where real-world data is scarce, expensive, or privacy-sensitive. In this comprehensive guide, we'll explore LLM-driven synthetic data generation, diving deep into its methods, applications, and best practices.

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The AI Productivity Shift: Whats Working & Whats Next

85% of teams are using AI, but only 27% report clear productivity gains. Why? Because most are still stuck in surface-level adoption. In this expert panel, top voices in workplace strategy and remote innovation—Dr. Gleb Tsipursky, Phil Kirschner, Nadia Harris, and Eryn Peters—reveal how leading teams are cutting digital noise, training AI to fit their workflows, and building cultures that embrace change.

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Difference Between Method Overloading and Overriding

Analytics Vidhya

Introduction Method overloading and method overriding are two fundamental concepts in object-oriented programming (OOP) you must know. They can greatly enhance the flexibility and functionality of your code, especially in fields like data science and artificial intelligence, which require efficient and maintainable code. Although these two terms might sound similar, their underlying mechanisms are significantly […] The post Difference Between Method Overloading and Overriding appeared firs

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What is Few-Shot Prompting?

Analytics Vidhya

Introduction In machine learning, generating correct responses with minimum facts is essential. Few-shot prompting is an effective strategy that allows AI models to perform specific jobs by presenting only a few examples or templates. This approach is especially beneficial when the undertaking calls for limited guidance or a selected format without overwhelming the version with […] The post What is Few-Shot Prompting?

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Rajan Kohli, CEO of CitiusTech – Interview Series

Unite.AI

Rajan Kohli is the Chief Executive Officer of CitiusTech and is responsible for the strategic direction of the company and further CitiusTech’s mission of accelerating healthcare technology innovation and driving long-term value for clients. Rajan is a highly accomplished technology services industry executive with experience across digital transformation, application and engineering services.

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Mastering Python’s Maximum Integer Value

Analytics Vidhya

Introduction Python is an extremely capable programming language that works well with integers of any size. Although this special functionality helps developers, there are some possible drawbacks as well. This page offers a thorough explanation of Python’s maximum integer value, as well as helpful hints, examples, and typical difficulties. Overview How Python Handles Integers?

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Researchers at Princeton University Reveal Hidden Costs of State-of-the-Art AI Agents

Marktechpost

There has been a lot of development in AI agents recently. However, one single goal—accuracy—has dominated evaluation and is vital to agent development. According to a recent study out of Princeton University, agents that are unnecessarily complicated and costly to run are the result of focusing only on accuracy. The team suggests a change to an evaluation paradigm that takes cost into account, where accuracy and cost are optimized together.

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Speeding Robotics Automation with AI

The $53 trillion manufacturing economy in the US is undergoing a major automation paradigm shift due to Artificial Intelligence (AI). Thanks to new practical frameworks, automation projects that were once impossible or inefficient to implement are now being fast-tracked, and robotics automation is becoming increasingly relevant to a growing number of users and scenarios.

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Tips for Effective Feature Engineering in Machine Learning

Machine Learning Mastery

Feature engineering is an important step in the machine learning pipeline. It is the process of transforming data in its native format into meaningful features to help the machine learning model learn better from the data. If done right, feature engineering can significantly enhance the performance of machine learning algorithms. Beyond the basics of understanding […] The post Tips for Effective Feature Engineering in Machine Learning appeared first on MachineLearningMastery.com.

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How AI Scales with Data Size? This Paper from Stanford Introduces a New Class of Individualized Data Scaling Laws for Machine Learning

Marktechpost

Machine learning models for vision and language, have shown significant improvements recently, thanks to bigger model sizes and a huge amount of high-quality training data. Research shows that more training data improves models predictably, leading to scaling laws that explain the link between error rates and dataset size. These scaling laws help decide the balance between model size and data size, but they look at the dataset as a whole without considering individual training examples.

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World's Largest Fusion Reactor Delayed Again to 2039

Extreme Tech

The project will also need billions in additional funding.

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Meet Jockey: A Conversational Video Agent Powered by LangGraph and Twelve Labs API

Marktechpost

Recent developments in the field of Artificial Intelligence are completely changing the way humans engage with video material. The open-source chat video agent ‘ Jockey ‘ is a great example of this innovation. Jockey provides improved video processing and interaction by utilizing the potent powers of Twelve Labs APIs and LangGraph. Twelve Labs offers modern video understanding APIs that can extract comprehensive insights from video footage.

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Agentic AI Explained: Smarter Conversations, Better Experiences

AI has transformed how enterprises deliver customer service, enabling faster engagement, problem-solving, and cost savings. However, traditional AI Agents often rely on rigid conversation flows, risking customer trust when conversations stray from predefined paths. These limitations prevent businesses from fully realizing AI’s potential for cost-efficiency and productivity.

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Google May Use Ultrasonic Fingerprint Scanner in Pixel 9

Extreme Tech

The last few Pixels have used optical fingerprint scanners.

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Salesforce AI Research Unveils APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets

Marktechpost

Function-calling agent models, a significant advancement within large language models (LLMs), face the challenge of requiring high-quality, diverse, and verifiable datasets. These models interpret natural language instructions to execute API calls, which are critical for real-time interactions with various digital services. However, existing datasets often lack comprehensive verification and diversity, leading to inaccuracies and inefficiencies.

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Intel Discontinues Core i9-12900KS and Comet Lake CPUs

Extreme Tech

Pour one out for Intel's 14nm process.

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Memory3: A Novel Architecture for LLMs that Introduces an Explicit Memory Mechanism to Improve Efficiency and Performance

Marktechpost

Language modeling in artificial intelligence focuses on developing systems that can understand, interpret, and generate human language. This field encompasses various applications, such as machine translation, text summarization, and conversational agents. Researchers aim to create models that mimic human language abilities, allowing for seamless interaction between humans and machines.

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The AI Productivity Shift: How 3,000 Pros And 140K Users Are Transforming Work

Hubstaff’s new report, The AI Productivity Shift, highlights how 3,000+ professionals and 140,000+ users are transforming the way they work with AI. Adoption is high—85% are using AI—and the potential is just beginning. Teams that integrate AI into daily workflows report 77% faster task completion, 70% improved focus, and stronger results across the board.

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AdaBoost Explained From Its Original Paper

Towards AI

Last Updated on July 5, 2024 by Editorial Team Author(s): Christian Guerra Originally published on Towards AI. This publication is meant to show a very popular ML algorithm in complete detail, how it works, the math behind it, how to execute it in Python and an explanation of the proofs of the original paper. There will be math and code, but it is written in a way that allows you to decide which are the fun parts.

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Top 10 Use Cases of ChatGPT

Marktechpost

ChatGPT and other generative AI-powered tools have become indispensable in today’s business landscape. They offer various advantages that help businesses stay ahead of the competition, increase productivity, and improve their bottom line. Here are the top 10 ChatGPT use cases that professionals, CxOs, and business owners can widely adopt. Customer Support Automation: One of ChatGPT’s most impactful uses is automating customer support.

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Windows 11 'Government Edition' With Zero Bloatware Is Like a Dream Come True

Extreme Tech

It's not used by any governments, but we'd spend money on it if we could.

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Claude AI: A Comprehensive Overview Exploring the Advanced Capabilities and Ethical Design of Anthropic’s Leading Language Model

Marktechpost

Claude AI, a leading large language model (LLM) developed by Anthropic, represents a significant leap in artificial intelligence technology. Let’s explore Claude AI in detail, highlighting its development, capabilities, and comparisons with prominent AI models like ChatGPT. Development and Ethical Framework Claude AI was developed by Anthropic, a startup co-founded by former OpenAI employees.

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From Curiosity to Competitive Edge: How Mid-Market CEOs Are Using AI to Scale Smarter

Speaker: Lee Andrews, Founder at LJA New Media & Tony Karrer, Founder and CTO at Aggregage

This session will walk you through how one CEO used generative AI, workflow automation, and sales personalization to transform an entire security company—then built the Zero to Strategy framework that other mid-market leaders are now using to unlock 3.5x ROI. As a business executive, you’ll learn how to assess AI opportunities in your business, drive adoption across teams, and overcome internal resource constraints—without hiring a single data scientist.

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Semi- and Self-Supervised Learning Help Clinicians Minimize Manual Labeling in Medical Image…

NYU Center for Data Science

Semi- and Self-Supervised Learning Help Clinicians Minimize Manual Labeling in Medical Image Analysis A new AI pipeline developed by researchers at CDS significantly reduces the need for manual labeling in medical image analysis tasks, as detailed in the study titled “ Shifting to Machine Supervision: Annotation-Efficient Semi and Self-Supervised Learning for Automatic Medical Image Segmentation and Classification ,” published in Nature Scientific Reports.

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Top 5 Factors to Consider Whether To Buy or Build Generative AI Solutions

Marktechpost

The rise of generative AI (GenAI) technologies presents enterprises with a pivotal decision: should they buy a ready-made solution or build a custom one? This decision hinges on several critical factors, each influencing the investment’s outcome and the solution’s effectiveness. Below are the top five factors businesses should consider when making this decision. 1.

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Design Sprint, Design Thinking, or Lean Startup: How to Choose the Right Approach?

Dlabs.ai

Innovation is the cornerstone of modern business success. With various methodologies available, choosing the right one can be challenging. This article cuts through the confusion, offering a comprehensive comparison of three leading innovation frameworks: Design Sprint, Design Thinking, and Lean Startup. We’ll explore the unique strengths and applications of each methodology, equipping you with the knowledge to choose the right tool for your specific challenges.

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Qdrant Unveils BM42: A Cutting-Edge Pure Vector-Based Hybrid Search Algorithm Optimizing RAG and AI Applications

Marktechpost

Qdrant, a leading provider of vector search technology, has introduced BM42 , a new algorithm designed to revolutionize hybrid search. For the past four decades, BM25 has been the standard algorithm used by search engines, from Google to Yahoo. However, the advent of vector search and the introduction of Retrieval-Augmented Generation (RAG) have highlighted the need for a more advanced solution.

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Prospect, Personalize, Profit: The New Way Sales & Marketing Teams Are Aligning with AI

Speaker: Kevin Burke, Founder & Managing Director at Digital One and AI & Automation Consultant

AI and automation are currently transforming the way sales and marketing teams operate. Generative AI crafts personalized outreach at scale, while conversational AI bots are engaging prospects in real time. Robotic process automation streamlines manual workflows by triggering tasks the moment a prospect takes a key action, and advanced AI analytics surface hidden patterns in the pipeline, improve forecasting, and help teams make data-driven decisions with confidence.

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Rip Full-Length DVDs to Play on Your Devices With This $25 Deal

Extreme Tech

Convert your favorite DVDs to popular audio-visual formats compatible with computers and smart TVs.

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Beyond Deep Learning: Evaluating and Enhancing Model Performance for Tabular Data with XGBoost and Ensembles

Marktechpost

In solving real-world data science problems, model selection is crucial. Tree ensemble models like XGBoost are traditionally favored for classification and regression for tabular data. Despite their success, deep learning models have recently emerged, claiming superior performance on certain tabular datasets. While deep neural networks excel in fields like image, audio, and text processing, their application to tabular data presents challenges due to data sparsity, mixed feature types, and lack

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Role of Medical Image Annotation in Enhancing Healthcare

Becoming Human

Summary : Medical Data Annotation helps healthcare providers in making accurate diagnoses by enhancing the accuracy of diagnostic tools. It also ensures that customized treatment plans are created to cater to individual patients. Medical images provide the necessary hints for diagnosing health issues. These images are in turn used by computers for deciphering visual clues via medical image annotation.