Thu.Jun 13, 2024

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A Comprehensive Guide on Langchain

Analytics Vidhya

Introduction Large language models (LLMs) have revolutionized natural language processing (NLP), enabling various applications, from conversational assistants to content generation and analysis. However, working with LLMs can be challenging, requiring developers to navigate complex prompting, data integration, and memory management tasks. This is where Langchain comes into play, a powerful open-source Python framework designed to […] The post A Comprehensive Guide on Langchain appeared fir

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T-Mobile unlocks marketing efficiency with Adobe Workfront

IBM Journey to AI blog

With 109 million customers and counting, “uncarrier” T-Mobile is one of the top mobile communications providers in the U.S. The company always puts the customer first, which it achieves by delivering the right experiences and content to the right customers at the right time. But with different sub-brands and business units, T-Mobile’s marketing and content workflows were complex—and often inefficient and disconnected.

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How to Delete a File in Python?

Analytics Vidhya

Introduction This article offers a thorough tutorial on how to delete files in Python using a variety of modules and approaches. It goes over simple techniques like using os.remove() and os.unlink(), more complex techniques like pathlib.Path.unlink() and shutil.rmtree() for directories, and safer options like send2trash for putting files in the recycling bin.

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The Future of Cybersecurity: AI, Automation, and the Human Factor

Unite.AI

In the past decade, along with the explosive growth of information technology, the dark reality of cybersecurity threats has also evolved dramatically. Cyberattacks, once driven primarily by mischievous hackers seeking notoriety or financial gain, have become far more sophisticated and targeted. From state-sponsored espionage to corporate and identity theft, the motives behind cybercrime are increasingly sinister and dangerous.

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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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Debugging And Testing LLMs in LangSmith

Analytics Vidhya

Introduction With the advancements in Artificial Intelligence, developing and deploying large language model (LLM) applications has become increasingly complex and demanding. To address these challenges, let’s explore LangSmith. LangSmith is a new cutting-edge DevOps platform designed to develop, collaborate, test, deploy, and monitor LLM applications.

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Understanding DENSE_RANK in SQL

Analytics Vidhya

Introduction When working with databases and analyzing data, ranking records is very important for organizing information based on certain conditions. One ranking function called `DENSE_RANK()` is useful because it assigns ranks to rows without leaving any empty spaces or gaps. This guide explains what `DENSE_RANK()` is, how it operates, and when to use it effectively […] The post Understanding DENSE_RANK in SQL appeared first on Analytics Vidhya.

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Microcontrollers vs. microprocessors: What’s the difference?

IBM Journey to AI blog

Microcontroller units (MCUs) and microprocessor units (MPUs) are two kinds of integrated circuits that, while similar in certain ways, are very different in many others. Replacing antiquated multi-component central processing units (CPUs) with separate logic units, these single-chip processors are both extremely valuable in the continued development of computing technology.

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25 Ways AI Can Make Your Daily Life Easy

Analytics Vidhya

Introduction Imagine a world where your morning alarm adjusts to traffic conditions, your coffee brews to your exact preference before you even get out of bed, and your commute is planned with the perfect balance of speed and scenic detours. This sci-fi dream is becoming a reality thanks to Artificial Intelligence. AI is here to […] The post 25 Ways AI Can Make Your Daily Life Easy appeared first on Analytics Vidhya.

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Apple is reportedly getting free ChatGPT access

AI News

Apple’s newly-announced partnership with OpenAI – which brings ChatGPT capabilities to iOS 18, iPadOS 18, and macOS Sequoia – comes without any direct money exchange. According to a Bloomberg report by Mark Gurman, “Apple isn’t paying OpenAI as part of the partnership.” Instead, the Cupertino-based company is leveraging its massive user base and device ecosystem as currency. “Apple believes pushing OpenAI’s brand and technology to hundreds of millions of its d

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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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How to Line Break in Python?

Analytics Vidhya

Introduction For efficient file handling, data processing, and string manipulation in Python, mastering line breaks is a must. You can read and write files, handle data with ease, and format text output by knowing how to control and modify line breaks. This thorough tutorial covers print statements, file operations, string manipulation, and data handling situations […] The post How to Line Break in Python?

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Optimizing AI Workflows: Leveraging Multi-Agent Systems for Efficient Task Execution

Unite.AI

In the domain of Artificial Intelligence (AI) , workflows are essential, connecting various tasks from initial data preprocessing to the final stages of model deployment. These structured processes are necessary for developing robust and effective AI systems. Across fields such as Natural Language Processing (NLP) , computer vision , and recommendation systems , AI workflows power important applications like chatbots, sentiment analysis , image recognition, and personalized content delivery.

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All About Google’s NotebookLM

Analytics Vidhya

Introduction Google’s NotebookLM, an experimental AI-driven notebook, is designed to transform the way we interact with and utilize LLMs. Leveraging advanced language models, NotebookLM aims to help users extract valuable insights from their existing content, providing a virtual research assistant that can summarize facts, explain complex ideas, and generate new connections based on selected sources. […] The post All About Google’s NotebookLM appeared first on Analytics Vidhya.

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Bryon Jacob, CTO & Co-Founder of data.world – Interview Series

Unite.AI

Bryon Jacob is the CTO and co-founder of data.world – on a mission to build the world's most meaningful, collaborative, and abundant data resource. Prior to data.world, he spent ten years in roles of increasing responsibility at HomeAway.com , culminating in a VP of Tech / Technical fellow role. Bryon has also previously worked at Amazon, and is a long-time mentor at Capital Factory.

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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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ROW_NUMBER() Function in SQL

Analytics Vidhya

Introduction Let’s say you have a list of items like a shopping list. The ROW_NUMBER function is similar to appending numbers to the list for each item in the order you jotted them down. This means you can refer to individual entries by their digit instead of going through them again. In SQL, you work […] The post ROW_NUMBER() Function in SQL appeared first on Analytics Vidhya.

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Optimize LLM with DSPy : A Step-by-Step Guide to build, optimize, and evaluate AI systems

Unite.AI

As the capabilities of large language models (LLMs) continue to expand, developing robust AI systems that leverage their potential has become increasingly complex. Conventional approaches often involve intricate prompting techniques, data generation for fine-tuning, and manual guidance to ensure adherence to domain-specific constraints. However, this process can be tedious, error-prone, and heavily reliant on human intervention.

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Hyperparameter Optimization in Machine Learning Models

Analytics Vidhya

Introduction One of the toughest things about making powerful models in machine learning is fiddling with many levels. Hyperparameter optimization—adjusting those settings to end up with something that’s not horrible—might be the most important part of it all. In this blog post, complete with code snippets, we’ll cover what this means and how to do […] The post Hyperparameter Optimization in Machine Learning Models appeared first on Analytics Vidhya.

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AI-Driven Personalization: The Future of Consumer Packaging

Aiiot Talk

Packaging personalization is out of reach for most companies — it’s too expensive and time-consuming. However, artificial intelligence can make it more accessible. Numerous industries can use it to elevate their current offerings, affecting customer satisfaction, return rates and material waste. Could AI permanently impact consumer packaging? How Can AI Personalize Consumer Packaging?

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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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A Comprehensive Overview of Data Engineering Pipeline Tools

Marktechpost

The paper “ A Survey of Pipeline Tools for Data Engineering ” thoroughly examines various pipeline tools and frameworks used in data engineering. Let’s look into these tools’ different categories, functionalities, and applications in data engineering tasks. Introduction to Data Engineering Data Engineering Challenges: Data engineering involves obtaining, organizing, understanding, extracting, and formatting data for analysis, a tedious and time-consuming task.

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Introducing Databricks LakeFlow: A unified, intelligent solution for data engineering

databricks

Today, we are excited to announce Databricks LakeFlow, a new solution that contains everything you need to build and operate production data pipelines.

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Researchers at Stanford Introduce TEXTGRAD: A Powerful AI Framework Performing Automatic “Differentiation” via Text

Marktechpost

Artificial intelligence (AI) is experiencing a paradigm shift, with breakthroughs driven by systems orchestrating multiple large language models (LLMs) and other complex components. This progression has highlighted the need for effective optimization methods for these compound AI systems, where automatic differentiation comes into play. Automatic differentiation has revolutionized the training of neural networks, and now researchers seek to apply similar principles to optimize more complex AI sy

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Open Sourcing Unity Catalog

databricks

We are excited to announce that we are open sourcing Unity Catalog, the industry’s first open source catalog for data and AI governance.

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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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Luma Releases Dream Machine: Transforming Video Creation with AI-Generated High-Quality, Realistic, and Fantastical Scenes from Text and Images

Marktechpost

Luma has introduced Dream Machine , an innovative AI model designed to create high-quality, realistic, fantastical videos from text instructions and images. Built on a scalable, efficient, and multimodal transformer architecture, Dream Machine represents a significant leap in AI technology, specifically tailored for video generation. This groundbreaking model, now available to everyone for free at Luma Labs , has been trained directly on videos, producing physically accurate, consistent, and act

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Thomson Reuters: GenAI Tool Tested By Stanford DID ‘Leverage Casetext’

Artificial Lawyer

Thomson Reuters (TR) has confirmed that the AI-Assisted Research tool that Stanford HAI tested for accuracy ‘leverages innovation in Casetext’. This matters because TR paid.

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This AI Paper from China Propose ‘Magnus’: Revolutionizing Efficient LLM Serving for LMaaS with Semantic-Based Request Length Prediction

Marktechpost

Transformer-based generative Large Language Models (LLMs) have shown considerable strength in a broad range of Natural Language Processing (NLP) tasks. Numerous applications benefit from its wide applicability; however, for most developers, the expense of training and implementing these models is frequently prohibitive. For this, top AI firms like OpenAI, Google, and Baidu offer a language model-as-a-service (LMaaS) by granting access to their LLMs through APIs.

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Rotary Positional Embedding(RoPE): Motivation and Implementation

Towards AI

Last Updated on June 13, 2024 by Editorial Team Author(s): Harsh Maheshwari Originally published on Towards AI. Delve deeper into RoPE along with its code to understand the positional embedding in LLMs betterPhoto by Agence Olloweb on Unsplash Positional embedding plays a crucial role in transformer models by helping them distinguish the order of tokens in a sequence/sentence.

AI 102
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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Hamming AI: An AI Startup that Provides Fastest Way to Make Your Prompts, RAG, and AI Agents More Reliable

Marktechpost

It is challenging to implement RAG and AI agents effectively in multiple steps. The output of an LLM can be drastically altered by tweaking just a few parameters, such as the definition of a function call or the retrieval parameters. When you write prompts by hand, you have to do a lot of trial and error to get them to work well. Not to mention that updated models frequently render old prompts inoperable.

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Boeing Starliner Has Now Sprung 5 Helium Leaks

Extreme Tech

NASA is determining what impacts this might have on the mission, but it currently believes Starliner can return to Earth.

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ShiftAddLLM: Accelerating Pretrained LLMs through Post-Training Shift-and-Add Reparameterization: Creating Efficient Multiplication-Free Models

Marktechpost

Deploying large language models (LLMs) on resource-constrained devices presents significant challenges due to their extensive parameters and reliance on dense multiplication operations. This results in high memory demands and latency bottlenecks, hindering their practical application in real-world scenarios. For instance, models like GPT-3 require immense computational resources, making them unsuitable for many edge and cloud environments.