Sun.Aug 11, 2024

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10 Best AI Social Listening Tools (August 2024)

Unite.AI

Understanding and analyzing social media conversations is crucial for today's businesses and organizations. AI-powered social listening tools are indispensable assets, offering advanced capabilities to monitor, interpret, and act upon social media data at scale. This article explores the top AI social listening tools that are improving how companies gain insights from online discussions, track brand sentiment, and engage with their audience effectively.

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Most Used 10 Power BI Charts

Analytics Vidhya

Introduction As the availability and importance of information as a robust asset increases in the modern global economy, it becomes essential to represent the information appropriately, especially to audiences with a non-technical background. Visualizations close the gap between big data and a more understandable realization of the data provided. Microsoft’s Power BI tool is an […] The post Most Used 10 Power BI Charts appeared first on Analytics Vidhya.

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Andrej Karpathy Coined a New Term ‘Jagged Intelligence’: Understanding the Inconsistencies in Advanced AI

Marktechpost

Andrej Karpathy coined a new term, ‘ Jagged Intelligence ‘ ‘ Jagged Intelligence ‘ refers to modern AI systems’ peculiar and often counterintuitive nature, particularly large language models (LLMs). These models have demonstrated remarkable capabilities in performing complex tasks, from solving intricate mathematical problems to generating coherent and contextually relevant text.

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Top 7 Algorithms for Data Structures in Python

Analytics Vidhya

Introduction Algorithms and data structures are the foundational elements that can also efficiently support the software development process in programming. Python, an easy-to-code language, has many features like a list, dictionary, and set, which are built-in data structures for the Python language. However, the wizards are unleashed by applying the algorithms in these structures.

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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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CodexGraph: An Artificial Intelligence AI System that Integrates LLM Agents with Graph Database Interfaces Extracted from Code Repositories

Marktechpost

Large Language Models (LLMs) have demonstrated exceptional performance on isolated code tasks, such as HumanEval and MBPP, but they struggle significantly when faced with the challenge of handling entire code repositories. The key difficulty lies in the inability of LLMs to manage long-context inputs and perform complex reasoning across intricate code structures within large projects.

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Qwen2-Audio Released: A Revolutionary Audio-Language Model Overcoming Complex Audio Challenges with Unmatched Precision and Versatile Interaction Capabilities

Marktechpost

Audio, as a medium, holds immense potential for conveying complex information, making it essential for developing systems that can accurately interpret & respond to audio inputs. The field aims to create models that can comprehend a wide range of sounds, from spoken language to environmental noise, and use this understanding to facilitate more natural interactions between humans & machines.

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ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities

Machine Learning Research at Apple

Recent large language models (LLMs) advancements sparked a growing research interest in tool assisted LLMs solving real-world challenges, which calls for comprehensive evaluation of tool-use capabilities.

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WaitGPT: Enhancing Data Analysis Accuracy by 83% with Real-Time Visual Code Monitoring and Error Detection in LLM-Powered Tools

Marktechpost

Data analysis has become increasingly accessible due to the development of large language models (LLMs). These models have lowered the barrier for individuals with limited programming skills, enabling them to engage in complex data analysis through conversational interfaces. LLMs have opened new avenues for extracting meaningful insights from data by simplifying the process of generating code for various analytical tasks.

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You Need to Know About Groq

TheSequence

Created Using DALL-E Next Week in The Sequence: Edge 421: We start a new ( and short) series about state space models which are considered the main viable alternative to transformers. This issue includes a reviews of the famous “Transformers are SSMs” paper and the DeepChecks framework for testing, evaluating monitoring SSMs. Edge 422: We dive into the fascinating NuminaMath model that just won first prize in the AI Math Olympiad.

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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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IBM Research Introduced Conversational Prompt Engineering (CPE): A GroundBreaking Tool that Simplifies Prompt Creation with 67% Improved Iterative Refinements in Just 32 Interaction Turns

Marktechpost

Artificial intelligence, particularly natural language processing (NLP), has become a cornerstone in advancing technology, with large language models (LLMs) leading the charge. These models, such as those used for text summarization, automated customer support, and content creation, are designed to interpret and generate human-like text. However, the true potential of these LLMs is realized through effective prompt engineering.

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AV-CPL: Continuous Pseudo-Labeling for Audio-Visual Speech Recognition

Machine Learning Research at Apple

*Work done during internship at Apple Audio-visual speech contains synchronized audio and visual information that provides cross-modal supervision to learn representations for both automatic speech recognition (ASR) and visual speech recognition (VSR). We introduce continuous pseudo-labeling for audio-visual speech recognition (AV-CPL), a semi-supervised method to train an audio-visual speech recognition (AVSR) model on a combination of labeled and unlabeled videos with continuously regenerated

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LLaVA-OneVision: A Family of Open Large Multimodal Models (LMMs) for Simplifying Visual Task Transfer

Marktechpost

A key goal in the development of AI is the creation of general-purpose assistants utilizing Large Multimodal Models (LMMs). Building AI systems that can work in tandem with people in various settings and with a wide variety of jobs is central to the general-purpose assistant concept. These helpers aren’t confined to just one area of expertise; they’re capable of easily handling customer service, creative projects, personal task management, and even difficult analytical jobs.

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APE: Active Prompt Engineering - Identifying Informative Few-Shot Examples for LLMs

Machine Learning Research at Apple

Prompt engineering is an iterative procedure that often requires extensive manual efforts to formulate suitable instructions for effectively directing large language models (LLMs) in specific tasks. Incorporating few-shot examples is a vital and efficacious approach to provide LLMs with precise and tangible instructions, leading to improved LLM performance.

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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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Revolutionizing AI with Mamba: A Survey of Its Capabilities and Future Directions

Marktechpost

Deep learning has revolutionized various domains, with Transformers emerging as a dominant architecture. However, Transformers must improve the processing of lengthy sequences due to their quadratic computational complexity. Recently, a novel architecture named Mamba has shown promise in building foundation models with comparable abilities to Transformers while maintaining near-linear scalability with sequence length.

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Best Practices for Fact Tables in Dimensional Models

Pickl AI

Summary: This blog discusses best practices for designing effective fact tables in dimensional models. It covers key considerations such as defining the grain, selecting dimensions, and determining metrics. Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance.

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BiomedGPT: A Versatile Transformer-Based Foundation Model for Biomedical AI with Enhanced Multimodal Capabilities and Performance

Marktechpost

Traditional biomedical AI models are often specialized and need more flexibility, making them less effective for real-world applications requiring integrating various data types. Generalist AI models, particularly those based on transformers, offer a versatile solution by handling textual and visual data. These models can streamline complex tasks like radiology interpretation and clinical summarization, overcoming the limitations of narrow, task-specific systems.

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Throwing Caution to the Wind

Robot Writers AI

Some Colleges Fully Integrate AI Into Coursework Dismissing concerns that AI is an automated cheating tool, some colleges have decided to fully integrate the tech into their curriculums. The rationale: AI skills have become so crucial to employment in many industries, it’s more important to skill-up students in the tech than to worry about AI’s other, nefarious uses.

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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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LiteLLM: Call 100+ LLMs Using the Same Input/Output Format

Marktechpost

Managing and optimizing API calls to various Large Language Model (LLM) providers can be complex, especially when dealing with different formats, rate limits, and cost controls. Creating consistent interfaces for diverse LLM platforms can often be a struggle, making it challenging to streamline operations, particularly in enterprise environments where efficiency and cost management are critical.

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Everything You Need to Know About Machine Learning OCR

How to Learn Machine Learning

Hello dear reader, hope you’re doing super well, whatever time of the day it is for you. In the following post we will be speaking about Machine Learning OCR, a topic we love, and that now with all the LLM Multimodality thing is evolving a lot. In this post we will be covering the basics, so lets get to it! Introduction Machine Learning OCR is an Optical Character Recognition technology embedded with machine learning algorithms.

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DistillGrasp: A Unique AI Method for Integrating Features Correlation with Knowledge Distillation for Depth Completion of Transparent Objects

Marktechpost

RGB-D cameras have a difficult time accurately capturing the depth of transparent objects because of the optical effects of reflection and refraction. Because of this, the depth maps these cameras produce frequently contain inaccurate or missing information. To overcome this problem, recent research has developed sophisticated network designs and advanced visual features intended to recreate the missing depth information.

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Integrating Stereoelectronic Effects into Molecular Graphs: A Novel Approach for Enhanced Machine Learning Representations and Molecular Property Predictions

Marktechpost

Traditional molecular representations, primarily focused on covalent bonds, have neglected crucial aspects like delocalization and non-covalent interactions. Existing machine learning models have utilized information-sparse representations, limiting their ability to capture molecular complexity. While computational chemistry has developed robust quantum-mechanical methods, their application in machine learning has been constrained by calculation challenges for complex systems.

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The Tumultuous IT Landscape Is Making Hiring More Difficult

After a year of sporadic hiring and uncertain investment areas, tech leaders are scrambling to figure out what’s next. This whitepaper reveals how tech leaders are hiring and investing for the future. Download today to learn more!

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Meet Reducto: An AI-Powered Startup Building Vision Models to Turn Complex Documents into LLM-Ready Inputs

Marktechpost

Unstructured file types include about 80% of all company data, such as spreadsheets and PDFs. PDFs constitute the de facto standard for corporate knowledge in almost every sector. Every week, dozens of hours are lost because their storage structure is completely unsuitable for usage in digital workflows. It is common practice for businesses to employ conventional methods when developing an extraction pipeline for each unique document layout.

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Understanding Language Model Distillation

Marktechpost

Knowledge Distillation (KD) has become a key technique in the field of Artificial Intelligence, especially in the context of Large Language Models (LLMs), for transferring the capabilities of proprietary models, like GPT-4, to open-source alternatives like LLaMA and Mistral. In addition to improving the performance of open-source models, this procedure is essential for compressing them and increasing their efficiency without significantly sacrificing their functionality.