Analytics Vidhya

FEBRUARY 3, 2024

In a move to redefine online shopping, Amazon has introduced Rufus, its latest AI-powered shopping assistant. Rufus is designed to elevate the user experience by offering personalized and conversational interactions, marking a strategic evolution in the e-commerce giant’s approach. As AI increasingly becomes integral to various products and services, Amazon aims to revolutionize the way […] The post Shop Better on Amazon with AI appeared first on Analytics Vidhya.

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AI AI Conversational AI Artificial Intelligence 330

Marktechpost

FEBRUARY 3, 2024

Enhancing the receptive field of models is crucial for effective 3D medical image segmentation. Traditional convolutional neural networks (CNNs) often struggle to capture global information from high-resolution 3D medical images. One proposed solution is the utilization of depth-wise convolution with larger kernel sizes to capture a wider range of features.

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Convolutional Neural Networks Computer Vision Neural Network Artificial Intelligence 144

Analytics Vidhya

FEBRUARY 3, 2024

Introduction In a significant stride towards global technological cooperation, the UK and Canada have inked a dual set of agreements, underscoring their commitment to collaborative efforts in science, innovation, and artificial intelligence (AI). The Memorandum of Understanding on Compute stands out as a pivotal component, emphasizing the crucial role of computing power in advancing AI […] The post Canada and UK Sign AI Agreement appeared first on Analytics Vidhya.

Artificial Intelligence 317

Artificial Intelligence Artificial Intelligence AI AI 317

Marktechpost

FEBRUARY 3, 2024

In natural language processing, the quest for precision in language models has led to innovative approaches that mitigate the inherent inaccuracies these models may present. A significant challenge is the models’ tendency to produce “hallucinations” or factual errors due to their reliance on internal knowledge bases. This issue has been particularly pronounced in large language models (LLMs), which often need improvement despite their linguistic prowess when generating content

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Large Language Models Natural Language Processing Automation Algorithm 141

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

Analytics Vidhya

FEBRUARY 3, 2024

Introduction Python programming opens the door to a world of endless possibilities, and one fundamental task that often stands before us is extracting unique values from a list. Getting unique values from a list is a common task in Python programming. Just like each line of code has its unique purpose, so do the elements […] The post Get Unique Values from a List Using Python appeared first on Analytics Vidhya.

Python 319

Python Deep Learning Data Science Artificial Intelligence 319

Analytics Vidhya

FEBRUARY 3, 2024

Google Maps is set to revolutionize the way users explore and discover new places through its latest experiment with generative AI. The tech giant is testing a feature that leverages large language models (LLM) to provide detailed search results, catering to individual preferences and enhancing the overall user experience. While still in early access and […] The post Discover New Places on Google Maps with Generative AI appeared first on Analytics Vidhya.

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Generative AI Large Language Models LLM AI 313

Marktechpost

FEBRUARY 3, 2024

Numerous challenges underlying human-robot interaction exist. One such challenge is enabling robots to display human-like expressive behaviors. Traditional rule-based methods need more scalability in new social contexts, while the need for extensive, specific datasets limits data-driven approaches. This limitation becomes pronounced as the variety of social interactions a robot might encounter increases, creating a demand for more adaptable, context-sensitive solutions in robotic behavior progra

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Robotics Large Language Models Machine Learning ML 133

Analytics Vidhya

FEBRUARY 3, 2024

Introduction In the dynamic landscape of data science, staying connected with like-minded professionals is paramount. As we have entered 2024, the importance of vibrant online communities for knowledge sharing, collaborative learning, and networking has never been greater. This article talks about the top 10 data science communities that stand out, offering a glimpse into the platforms […] The post Top 10 Communities in Data Science in 2024 appeared first on Analytics Vidhya.

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Data Science 291

Marktechpost

FEBRUARY 3, 2024

With the growth of AI, large language models also began to be studied and used in all fields. These models are trained on vast amounts of data on the scale of billions and are useful in fields like health, finance, education, entertainment, and many others. They contribute to various tasks ranging from natural language processing and translation to many other tasks.

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AI Modeling Large Language Models Natural Language Processing Machine Learning 127

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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?

Business Intelligence

Towards AI

FEBRUARY 3, 2024

Last Updated on February 3, 2024 by Editorial Team Author(s): Harpreet Sahota Originally published on Towards AI. By Author In this post, you’ll learn about creating synthetic data, evaluating RAG pipelines using the Ragas tool, and understanding how various retrieval methods shape your RAG evaluation metrics. My journey with AI Makerspace’s LLMOps cohort (learn more here) has been instrumental in shaping my approach to these topics.

Large Language Models 118

Large Language Models OpenAI Metadata Automation 118

Marktechpost

FEBRUARY 3, 2024

Large-scale pre-trained vision-language models, exemplified by CLIP (Radford et al., 2021), exhibit remarkable generalizability across diverse visual domains and real-world tasks. However, their zero-shot in-distribution (ID) performance faces limitations on certain downstream datasets. Additionally, when evaluated in a closed-set manner, these models often struggle with out-of-distribution (OOD) samples from novel classes, posing safety risks in the open domain.

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AI AI Algorithm ML 130

Towards AI

FEBRUARY 3, 2024

Author(s): Stavros Theocharis Originally published on Towards AI. (Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. I also wrote a Medium article about this package in the past to illustrate its use with image classification models.

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Explainability Explainable AI Neural Network Algorithm 114

Marktechpost

FEBRUARY 3, 2024

Synthesizers, electronic instruments producing diverse sounds, are integral to music genres. Traditional sound design involves intricate parameter adjustments, demanding expertise. Neural networks aid by replicating input sounds, initially optimizing synthesizer parameters. Recent advances focus on optimizing sound directly for high-fidelity reproduction, requiring unsupervised learning for out-of-domain sounds.

Neural Network 126

Neural Network Automation Machine Learning ML 126

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

AI

Towards AI

FEBRUARY 3, 2024

Last Updated on February 3, 2024 by Editorial Team Author(s): Kamireddy Mahendra Originally published on Towards AI. “Learning is intrinsic to human nature, and innovating machines to learn is a testament to human ingenuity.” Photo by Markus Winkler on Unsplash Let’s get started: Machine Learning has become the most demanding and powerful tool in different domains of several industries in this digital era to solve many complex problems by revolutionizing the way of approaching those problems.

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Machine Learning Data Scientist NLP Categorization 112

Marktechpost

FEBRUARY 3, 2024

A team of researchers from the University of Washington has collaborated to address the challenges in the protein sequence design method by using a deep learning-based protein sequence design method, LigandMPNN. The model targets enzymes and small molecule binder and sensor designs. Existing physically based approaches like Rosetta and deep learning-based models like ProteinMPNN are unable to model non-protein atoms and molecules explicitly, which limitation hinders the accurate design of protei

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Deep Learning Neural Network ML Artificial Intelligence 121

Extreme Tech

FEBRUARY 3, 2024

Plus: Why are hurricanes so powerful? Are winds on other planets like they are on Earth? The answer, my friend, is blowin' in the wind.

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Marktechpost

FEBRUARY 3, 2024

The demand for intelligent and efficient digital assistants proliferates in the modern digital age. These assistants are vital for numerous tasks, including communication, learning, research, and entertainment. However, one of the primary challenges users face worldwide is finding digital assistants that can understand and interact effectively in multiple languages.

Large Language Models 115

Large Language Models Artificial Intelligence Artificial Intelligence AI 115

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.

Business Intelligence

Extreme Tech

FEBRUARY 3, 2024

The agency worries AI-powered voice cloning could supercharge phone scams and misinformation.

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AI AI 106

Viso.ai

FEBRUARY 3, 2024

Model accuracy is a well-known metric to gauge a model’s predictive power. However, it can be misleading and cause disastrous consequences. Here is where precision vs recall comes in. Imagine a computer vision (CV) model for diagnosing cancerous tumors with 99% accuracy. While the model’s performance seems impressive, it is still likely to miss 1% of tumor cases, leading to severe complications for specific patients.

Computer Vision 52

Computer Vision Machine Learning Categorization Deep Learning 52

Bugra Akyildiz

FEBRUARY 3, 2024

Articles Google wrote an article on the new graph based transformer architecture called Exphormer and how they scaled this model for their datasets. Graph transformers are a powerful architecture for machine learning on graph-structured data like molecules, social networks, and knowledge graphs. Existing graph transformers struggle with scaling to large graphs due to memory limitations and computational complexity of fully-connected attention mechanisms.

Neural Network 52

Neural Network Convolutional Neural Networks Deep Learning Large Language Models 52

Salmon Run

FEBRUARY 3, 2024

I have read Allen Downey's books on statistics in the past, when trying to turn myself from a Software Engineer into what Josh Wills says a Data Scientist is -- someone who is better at statistics than a Software Engineer and better at software than a statistician (with somewhat limited success in the first area, I will hasten to add).

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Software Engineer Data Scientist 45

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