Analytics Vidhya

JANUARY 14, 2024

Introduction The apt-get command is a powerful tool in Linux that allows users to manage software packages. Whether you want to install, update, remove, or search for packages, apt-get provides a simple and efficient way to handle these tasks. In this article, we will explore the various functionalities of apt-get and provide examples to help […] The post apt-get Command in Linux: Understanding with Examples appeared first on Analytics Vidhya.

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Marktechpost

JANUARY 14, 2024

Language models have revolutionized the way machines comprehend and produce human-like text. These intricate systems use neural networks to interpret and respond to linguistic inputs. Their aptitude to process and generate language has far-reaching consequences in multiple fields, from automated chatbots to advanced data analysis. Grasping the internal workings of these models is critical to improving their efficacy and aligning them with human values and ethics.

Large Language Models 140

Large Language Models AI Research AI Researcher Neural Network 140

Analytics Vidhya

JANUARY 14, 2024

Introduction The ever-evolving landscape of language model development saw the release of a groundbreaking paper – the Mixtral 8x7B paper. Released just a month ago, this model sparked excitement by introducing a novel architectural paradigm, the “Mixture of Experts” (MoE) approach. Departing from the strategies of most Language Models (LLMs), Mixtral 8x7B is a fascinating […] The post Discover the Groundbreaking LLM Development of Mixtral 8x7B appeared first on Analytics Vidhy

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LLM Neural Network 307

Marktechpost

JANUARY 14, 2024

In recent research, a team of researchers from Mistral AI has presented Mixtral 8x7B, a language model based on the new Sparse Mixture of Experts (SMoE) model with open weights. Licensed under the Apache 2.0 license and as a sparse network of a mixture of experts, Mixtral serves just as a decoder model. The team has shared that Mixtral’s feedforward block has been chosen from eight different parameter groups.

Machine Learning 135

Machine Learning AI AI ML 135

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

JANUARY 14, 2024

Ready to challenge your knowledge! This quiz features 10 thought-provoking questions on Data Structures in Python. Whether you’re an expert or a curious learner, our quizzes cater to all levels. Embark on this journey of continuous learning and test your knowledge across pivotal topics shaping the future of analytics and technology. Let’s Begin! Thanks for participating!

Python 300

Python Continuous Learning 300

Analytics Vidhya

JANUARY 14, 2024

Introduction Python, renowned for its versatility, introduces features to enhance code readability. Among these features, the ‘with’ statement stands out as an elegant solution for managing resources efficiently. This article delves into the intricacies of the ‘with’ statement, exploring its benefits, usage, common scenarios, advanced techniques, and best practices.

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Python 282

Marktechpost

JANUARY 14, 2024

Developing large-scale datasets has been critical in computer vision and natural language processing. These datasets, rich in visual and textual information, are fundamental to developing algorithms capable of understanding and interpreting images. They serve as the backbone for enhancing machine learning models, particularly those tasked with deciphering the complex interplay between visual elements in images and their corresponding textual descriptions.

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Computer Vision Natural Language Processing Machine Learning Automation 128

Towards AI

JANUARY 14, 2024

Last Updated on January 14, 2024 by Editorial Team Author(s): Peyman Kor Originally published on Towards AI. Data Science is the discipline of making data useful — But How? It has been now more than one decade since Thomas H. Davenport and DJ Patilthree wrote their famous Harvard Business Review article: “Data Scientist: The Sexiest Job of the 21st Century” The article made many discussions, and now, after a decade, we have thousands of job profiles titled “Data Scientist.

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Data Science Data Scientist Big Data AI 110

Marktechpost

JANUARY 14, 2024

Debugging performance issues in databases is challenging, and there is a need for a tool that can provide useful and in-context troubleshooting recommendations. Large Language Models (LLMs) like ChatGPT can answer many questions but often provide vague or generic recommendations for database performance queries. While LLMs are trained on vast amounts of internet data, their generic recommendations lack context and the multi-modal analysis required for debugging.

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Machine Learning Large Language Models LLM ChatGPT 123

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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

JANUARY 14, 2024

Author(s): Tim Cvetko Originally published on Towards AI. An Overview of Why LLM Benchmarks Exist, How They Work, and What’s Next LLMs are complex. Although most of us used ChatGPT to … Write me a 100-word paragraph about the history of Greek poetry. or give me a dirty joke about old people Image generated with Stable Diffusion. Obviously, we’re not there yet.

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LLM Large Language Models AI Engineer ChatGPT 107

Marktechpost

JANUARY 14, 2024

A pressing issue emerges in text-to-image (T2I) generation using reinforcement learning (RL) with quality rewards. Even though potential enhancement in image quality through reinforcement learning RL has been observed, the aggregation of multiple rewards can lead to over-optimization in certain metrics and degradation in others. Manual determination of optimal weights becomes a challenging task.

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OpenAI Algorithm ML Computer Vision 115

Towards AI

JANUARY 14, 2024

Last Updated on January 14, 2024 by Editorial Team Author(s): Eivind Kjosbakken Originally published on Towards AI. OCR is an important tool for understanding documents, which it does by extracting all text from an image, which can then be combined with models like LLMs to create powerful AI systems. Despite current OCRs performing well, they are not perfect and you need tools to measure the quality of your OCR.

Large Language Models 100

Large Language Models Machine Learning OpenAI ChatGPT 100

Marktechpost

JANUARY 14, 2024

When the camera and the subject move about one another during the exposure, the result is a typical artifact known as motion blur. Computer vision tasks like autonomous driving, object segmentation, and scene analysis can negatively impact this effect, which blurs or stretches the image’s object contours, diminishing their clarity and detail. To create efficient methods for removing motion blur, it is essential to understand where it comes from.

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Deep Learning Convolutional Neural Networks Neural Network Computer Vision 115

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

JANUARY 14, 2024

Author(s): Caden Ornt Originally published on Towards AI. AI is increasingly becoming a part of everyday life, but teaching it to make ethical decisions may be problematic without universal ethical rules.Photo by Brigitta Schneiter on Unsplash The Trolley Problem is a classic thought experiment that puts forth a multitude of ethical dilemmas involving life or death situations.

AI 100

AI AI Explainability Artificial Intelligence 100

Marktechpost

JANUARY 14, 2024

Language Model evaluation is crucial for developers striving to push the boundaries of language understanding and generation in natural language processing. Meet LLM AutoEval : a promising tool designed to simplify and expedite the process of evaluating Language Models (LLMs). LLM AutoEval is tailored for developers seeking a quick and efficient assessment of LLM performance.

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LLM Natural Language Processing Automation AI 114

TheSequence

JANUARY 14, 2024

Created Using DALL-E Next Week in The Sequence: Edge 361: Our current series about LLM reasoning explores the tree-of-thought method including its original paper. We also dive into LangChain’s LangSmith tool for LLM debugging and evaluation. Edge 362: We review one of my favorites papers of last year. DeepMind’s FunSearch is a method that was able to discover new math and computer science algorithms.

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Generative AI LLM AI AI 105

Marktechpost

JANUARY 14, 2024

Combining CLIP and the Segment Anything Model (SAM) is a groundbreaking Vision Foundation Models (VFMs) approach. SAM performs superior segmentation tasks across diverse domains, while CLIP is renowned for its exceptional zero-shot recognition capabilities. While SAM and CLIP offer significant advantages, they also come with inherent limitations in their original designs.

AI 110

AI AI ML Computer Vision 110

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

Towards AI

JANUARY 14, 2024

Last Updated on January 14, 2024 by Editorial Team Author(s): Gao Dalie (高達烈) Originally published on Towards AI. As technology booms, AI Agents are becoming game changers, quickly becoming partners in problem-solving, creativity, and innovation, and this is what makes CrewAI unique. Can you imagine? In just a few minutes, you can turn an idea into a complete landing page, which is exactly what we achieved together with CrewAI.

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Artificial Intelligence Artificial Intelligence AI AI 96

Marktechpost

JANUARY 14, 2024

Tax fraud, characterized by the deliberate manipulation of information in tax returns to reduce tax liabilities, poses a substantial challenge for governments globally. The resultant annual financial losses are immense, emphasizing the critical need for effective fraud detection measures. Tax authorities worldwide are turning to machine learning strategies to enhance their capabilities in identifying and preventing fraudulent activities, marking a crucial step in safeguarding government revenues

Machine Learning 106

Machine Learning AI Research AI Researcher Neural Network 106

Robot Writers AI

JANUARY 14, 2024

In a single lifetime, there are only a few moments that can be marked as truly pivotal — and the emergence of the wunderkind AI writer ChatGPT in 2023 was one of those. Just like the advent of the personal computer, the emergence of the Internet, the invention of the smartphone and the creation of social media, the arrival of ChatGPT has forced us to change how we think about the world.

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Auto-complete ChatGPT OpenAI AI 103

Marktechpost

JANUARY 14, 2024

The introduction of fifth-generation (5G) and sixth-generation (6G) networks has brought new possibilities. But, they need dynamic radio resource management (RRM). These networks are helpful in advanced technologies like drones and virtual or augmented reality. However, they need to track current indicators and be able to predict them to do this. Researchers have started using Artificial Intelligence (AI) and machine learning (ML) for accurately forecasting mobile network profiles using artifici

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Machine Learning Artificial Intelligence Artificial Intelligence ML 104

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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!

Mlearning.ai

JANUARY 14, 2024

Honoring Siegfried Gross through ML and AR Continue reading on MLearning.

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ML AI AI 97

Marktechpost

JANUARY 14, 2024

LLMs have had a significant impact in the fields of code generation and comprehension. These models, trained on extensive code datasets such as GitHub, excel in tasks like text-to-code conversion, code-to-code transpilation, and understanding code. However, many current models merely treat code as sequences of subword tokens, overlooking its structure.

Neural Network 104

Neural Network NLP Algorithm ML 104

Bugra Akyildiz

JANUARY 14, 2024

Articles Stanford wrote a blog post on Monarch Mixer(M2) that is promising to replace Transformers and improve the scaling properties of Transformers along two axes; sequence length and model dimension. Some of the other properties of M2 are: It can efficiently capture all sorts of structured linear transforms, including Toeplitz, Fourier, Hadamard, and more.

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LLM Software Engineer Large Language Models Algorithm 59

Marktechpost

JANUARY 14, 2024

Large Language Models (LLMs) have demonstrated exceptional capabilities in natural language processing and find their application in almost every field, with factual question-answering being one of the most common use cases. Unlike others, factual answers could be answered correctly at different levels of granularity. For example, “1961” and “August 4, 1961” are both correct responses to the question “When was Barack Obama born?

Large Language Models 103

Large Language Models Natural Language Processing AI AI 103

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.

Generative AI

Mlearning.ai

JANUARY 14, 2024

Increase in Data Dimensions Introduction: The Curse of Dimensionality and the Need for PCA Imagine you’re a data scientist working with a vast dataset of astronomical observations, aiming to uncover patterns and insights about distant galaxies. Each observation in your dataset contains hundreds of features: brightness levels in different wavelengths, distances, sizes, and many more.

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Explainability Data Science Data Analysis Data Scientist 52

Marktechpost

JANUARY 14, 2024

Researchers from Tel-Aviv University and Google Research introduced a new method of user-specific or personalized text-to-image conversion called Prompt-Aligned Personalization (PALP). Generating personalized images from text is a challenging task and requires the presence of diverse elements like specific location, style, or (/and) ambiance. Existing methods compromise personalization or prompt alignment.

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Prompt Engineer Prompt Engineering AI AI 103