Analytics Vidhya

APRIL 7, 2024

Introduction The introduction of AI coding helpers has reached a crucial turning point in the constantly changing world of software development. These assistants, which use artificial intelligence (AI) capabilities, have revolutionized how engineers create and organize code. They now serve as vital resources for contemporary software development teams, offering astute assistance with various coding assignments. […] The post Best AI Coding Assistants in 2024 appeared first on Analytics Vidh

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Marktechpost

APRIL 7, 2024

In the data management and retrieval landscape, vector databases have emerged as a revolutionary force, transforming how businesses and tech enthusiasts harness the power of complex, high-dimensional data. Let’s delve into the intricacies of vector databases, shedding light on their real-world applications and their profound impact on various industries.

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Analytics Vidhya

APRIL 7, 2024

Google has always been synonymous with free search. However, the tech giant is contemplating a significant shift that could reshape how users access its services. Reports suggest that the company is exploring the possibility of charging for access to its AI-enhanced search features. This potential move, if implemented, could mark a significant change from Google’s […] The post Google Mulls Charging for AI-Enhanced Search: What You Need to Know appeared first on Analytics Vidhya.

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Marktechpost

APRIL 7, 2024

Machine Learning Operations (MLOps) refer to the set of practices for enhanced communication and collaboration during a machine learning project lifecycle. It involves principles like dataset validation, collaborative culture, application monitoring, reproducibility, etc., and ensures faster deployment, improved productivity, and reliability. With the rapid advancements in machine learning (ML), there has been an increase in the demand for MLOps specialists as well.

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Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

Analytics Vidhya

APRIL 7, 2024

Introduction In recent years, the field of artificial intelligence (AI) has witnessed a remarkable surge in the development of generative AI models. These models can generate human-like text, images, and even audio, pushing the boundaries of what was once thought impossible. Among these models, the Generative Pre-trained Transformer (GPT) stands out as a pioneering breakthrough […] The post What is GPT?

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Towards AI

APRIL 7, 2024

Author(s): Juliusnyambok Originally published on Towards AI. Building an End-to-End Machine Learning Project to Reduce Delays in Aggressive Cancer Care. After years of battling over control of the TV (sparked by my sister’s questionable obsession with true crime), my sister, the brilliant pharmacist Miss Nyambok Cynthia, and I decided to put our eternal sibling rivalry to good use.

Machine Learning 124

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Marktechpost

APRIL 7, 2024

Global feature effects methods, such as Partial Dependence Plots (PDP) and SHAP Dependence Plots, have been commonly used to explain black-box models by showing the average effect of each feature on the model output. However, these methods fell short when the model exhibits interactions between features or when local effects are heterogeneous, leading to aggregation bias and potentially misleading interpretations.

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Machine Learning Python Explainability Explainable AI 131

Towards AI

APRIL 7, 2024

Author(s): Jonte Dancker Originally published on Towards AI. ML models fail silently. A model might fail but still produce some output. We might not even get a signal of why or where our model fails. And there are many reasons for a model to fail. A model can fail due to bad data, bugs in the code, wrong hyperparameters, or a lack of predictive power of the model.

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Marktechpost

APRIL 7, 2024

The emergence of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) represents a significant leap forward in AI capabilities. These models have advanced to a point where they can generate text, interpret images, and even understand complex multimodal inputs with sophistication that closely mimics human intelligence. However, as the capabilities of these models have expanded, so too have the concerns regarding their potential misuse.

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

Generative AI

Towards AI

APRIL 7, 2024

Last Updated on April 7, 2024 by Editorial Team 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 Fifth Week of March 2024.

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LLM Large Language Models Data Science Machine Learning 105

Marktechpost

APRIL 7, 2024

In an era when data is as valuable as currency, many industries face the challenge of sharing and augmenting data across various entities without breaching privacy norms. Synthetic data generation allows organizations to circumvent privacy hurdles and unlock the potential for collaborative innovation. This is particularly relevant in distributed systems, where data is not centralized but scattered across multiple locations, each with its privacy and security protocols.

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Towards AI

APRIL 7, 2024

Last Updated on April 7, 2024 by Editorial Team Author(s): Prashant Kalepu Originally published on Towards AI. Photo by Lala Azizli on Unsplash Hey there, fellow learners! U+1F44B Welcome to another exciting journey in the realm of machine learning. Today, we’re going to discuss about the often overlooked but incredibly crucial aspect of Building ML models, i.e, Deploying machine learning models.

AI Modeling 105

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Marktechpost

APRIL 7, 2024

API (Application Programming Interface) strategies are pivotal in effective database management and integration. In today’s fast-paced digital landscape, where organizations operate across various databases and applications, seamlessly integrating these components is not just beneficial; it’s necessary for operational efficiency, insightful data analysis, and delivering superior customer experiences.

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Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Towards AI

APRIL 7, 2024

Last Updated on April 7, 2024 by Editorial Team Author(s): Vishnu Regimon Nair Originally published on Towards AI. Optimizing Emergency Response in Calgary Photo by Constante Lim on Unsplash Facing the Growing Challenge: Optimizing Emergency Response Times in Calgary With the ever-increasing population and evolving cities, the demand and need for emergency services grow stronger.

AI 105

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Marktechpost

APRIL 7, 2024

In today’s business world, the advent of artificial intelligence (AI) has revolutionized the way organizations communicate, particularly in handling and extracting value from documents. Meet AnythingLLM : an innovative open-sourced full-stack application that transforms how businesses interact with their documents through chatbot technology. Designed with efficiency, customization, and enterprise readiness in mind, AnythingLLM offers a comprehensive solution for turning any document or res

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Towards AI

APRIL 7, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 Statistics, regression model, algorithm validation, Random Forest, K Nearest Neighbors and Naïve Bayes— what in God’s name do all these complicated concepts have to do with you as a simple GIS analyst? You just want to create and analyze simple maps not to learn algebra all over again.

Machine Learning 105

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TheSequence

APRIL 7, 2024

Created Using Ideogram Next Week in The Sequence: Edge 385: Our series about autonomous agents continues by discussing the two biggest architecture approaches to build agents. We review the research behind Adept’s Fuyu-8B model which powers its agent platform and dive into Microsoft’s Augen framework for collaborative agents. Edge 386: We dive into Yi, the massive Chinese LLM that is matching up to top western alternatives.

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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

Data Analysis

Great Learning

APRIL 7, 2024

Data structures are fundamental to any programming language. The choice of a particular data structure has a significant impact on the functionality and performance of Java applications, thus it is worthwhile to master data structures in Java. This guide will help beginners to understand what is data structures, what is data structures in Java, the […] The post Data Structures in Java – A Beginners Guide 2024 appeared first on Great Learning Blog: Free Resources what Matters to shape

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Machine Learning Research at Apple

APRIL 7, 2024

On-device machine learning (ML) promises to improve the privacy, responsiveness, and proliferation of new, intelligent user experiences by moving ML computation onto everyday personal devices. However, today's large ML models must be drastically compressed to run efficiently on-device, a hurtle that requires deep, yet currently niche expertise. To engage the broader human-centered ML community in on-device ML experiences, we present the results from an interview study with 30 experts at Apple th

Machine Learning 52

Machine Learning ML 52

Robot Writers AI

APRIL 7, 2024

For writers, there’s gold in them VR Hills Imaginative writers looking for alternative job opportunities may want to check-out a new trend set by Victoria VR. It’s a virtual reality metaverse platform promising to add new tools to enable writers and others to create virtual worlds, games and apps using popular AI tools like ChatGPT. System requirements: A great imagination — and a great way with words.

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Towards AI

APRIL 7, 2024

Last Updated on April 7, 2024 by Editorial Team Author(s): Sujeeth Kumaravel Originally published on Towards AI. Keras Convolution layer — shapes of input, weights and output TensorFlow is one of the packages to develop solutions for machine learning problems. Keras is a module in TensorFlow that specifically offers tools to build neural network models.

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Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

Marktechpost

APRIL 7, 2024

Linear attention-based models are gaining attention for their faster processing speed and comparable performance to Softmax transformers. However, large language models (LLMs), due to their large size and longer sequence lengths, exert significant strain on contemporary GPU hardware because a single GPU’s memory confines a language model’s maximum sequence length.

Machine Learning 135

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Towards AI

APRIL 7, 2024

Last Updated on April 7, 2024 by Editorial Team Author(s): Abhinav Kimothi Originally published on Towards AI. Source : Image generated by author using Yarnit It is quite astonishing how Large Language Models or LLMs (GPT, Claude, Gemini etc.) have captured the world’s imagination. It’s a powerful technology that can tackle a variety of natural language tasks.

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Marktechpost

APRIL 7, 2024

Artificial intelligence is constantly advancing, and efforts to promote digital independence and language diversity have taken a significant step forward with the creation of Viking , a cutting-edge language model. Developed by Silo AI, Europe’s largest private AI lab, in collaboration with the TurkuNLP research group at the University of Turku and HPLT, Viking is designed to cater to Nordic languages, as well as English and programming languages.

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Marktechpost

APRIL 7, 2024

With the growing complexity of large language models (LLMs), making them easily runnable on everyday hardware is a notable challenge. This need is apparent for individuals and organizations that seek the benefits of LLMs without the high cost or technical barrier often associated with powerful computing resources. Several developers and companies have tried optimizing LLMs for various hardware platforms, but these solutions often catered to the higher end of the spectrum.

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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.

Artificial Intelligence

Marktechpost

APRIL 7, 2024

In document processing, particularly visually rich documents (VRDs), the need for efficient information extraction (IE) has become increasingly critical. VRDs, such as invoices, utility bills, and insurance quotes, are ubiquitous in business workflows, often presenting similar information in varying layouts and formats. Automating the extraction of pertinent data from these documents can significantly reduce the manual effort required for parsing.

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Marktechpost

APRIL 7, 2024

Artificial intelligence has witnessed remarkable advancements, with large language models (LLMs) emerging as fundamental tools driving various applications. However, the excessive computational costs of training these LLMs have created barriers, limiting accessibility and hindering wider development. Initiatives such as BLOOM, StarCoder, StarCoder-2, Pythia, and OLMo have emerged as open-source efforts to democratize access to pretrained LLMs, stimulating innovation and allowing researchers and

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