Sat.Feb 24, 2024

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The State of Cloud Optimization 2024: Comprehensive Insights

Unite.AI

In today's rapidly evolving cloud landscape, reducing cloud costs while enhancing application performance has become a critical priority for both established enterprises and fast-growing digital native businesses. The “ State of Cloud Optimization 2024 ” report from Granulate, an Intel Company, is a crucial resource in today's cloud-centric IT environment.

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Stability AI Introduces Stable Diffusion 3: Next-Gen Advancements in AI Imagery

Analytics Vidhya

Stability AI has announced the arrival of Stable Diffusion 3, the latest advancement in AI imagery technology. This new model promises significant improvements in text-to-image generation, boasting enhanced performance and quality. As the anticipation builds around Stable Diffusion 3, let’s delve into the key features and advancements of this innovative AI model.

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How to Unit Test Machine Learning Code & Models

Eugene Yan

How it differs from unit testing typical software and some guidelines

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All You Need to Know About Gemma, the Open-Source LLM Powerhouse

Analytics Vidhya

Google has been a frontrunner in AI research, contributing significantly to the open-source community with transformative technologies like TensorFlow, BERT, T5, JAX, AlphaFold, and AlphaCode. Continuing this legacy, Google has introduced Gemma, an LLM built for responsible AI development, leveraging the same research and technology that powered the Gini models.

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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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Meet GeneGPT: A Novel Artificial Intelligence Method for Teaching LLMs to Use the Web APIs of the National Center for Biotechnology Information (NCBI) for Answering Genomics Questions

Marktechpost

The utility of large language models (LLMs) has been increasingly recognized, demonstrating remarkable capabilities in processing and interpreting vast datasets. These models have been instrumental in various tasks, from facilitating clinical trial matches to enabling sophisticated biomedical question-answering. A significant challenge they face is the production of plausible yet inaccurate responses, a phenomenon often attributed to the models’ inability to consult verified sources of inf

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Researchers at Cornell University Introduced HiQA: An Advanced Artificial Intelligence Framework for Multi-Document Question-Answering (MDQA)

Marktechpost

A significant challenge with question-answering (QA) systems in Natural Language Processing (NLP) is their performance in scenarios involving extensive collections of documents that are structurally similar or ‘indistinguishable.’ Traditional models often need help to retrieve accurate information from such massive, homogeneous datasets, leading to issues in the precision and relevance of the responses.

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Fine-Tuning LLMs: Use Case Examples

Towards AI

Last Updated on February 24, 2024 by Editorial Team Author(s): Leo Tisljaric, PhD Originally published on Towards AI. From LLM-based machine translations to text generation fine-tuning, find all the theory, examples, and code in one place.Working on AI (Image by: Author) In one of his recent interviews, famous AI scientist Yann LeCun said that we do not have to seek general intelligence because even humans do not have it as „machines“ that have very specific and limited knowledge and skills.

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Researchers from Aalto University ViewFusion: Revolutionizing View Synthesis with Adaptive Diffusion Denoising and Pixel-Weighting Techniques

Marktechpost

Deep learning has revolutionized view synthesis in computer vision, offering diverse approaches like NeRF and end-to-end style architectures. Traditionally, 3D modeling methods like voxels, point clouds, or meshes were employed. NeRF-based techniques implicitly represent 3D scenes using MLPs. Recent advancements focus on image-to-image approaches, generating novel views from collections of scene images.

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The new EU AI Act: Contents, Technologies, Penalties, and What it Means for Companies

Mlearning.ai

The final revisions are underway and the EU Parliament is expected to adopt the new EU AI Act in the coming weeks. I took a look at the proposals that will regulate the entire field of machine learning in the EU in the future: Which companies and players will be affected? Which AI technologies will be regulated and how? How will generative AI be dealt with?

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Meet Optuna: An Automatic Hyperparameter Optimization Software Framework Designed for Machine Learning

Marktechpost

In machine learning, finding the perfect settings for a model to work at its best can be like looking for a needle in a haystack. This process, known as hyperparameter optimization, involves tweaking the settings that govern how the model learns. It’s crucial because the right combination can significantly improve a model’s accuracy and efficiency.

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Thoughts on using LangChain LCEL with Claude

Salmon Run

I got into Natural Language Processing (NLP) and Machine Learning (ML) through Search. And this led me into Generative AI (GenAI), which led me back to Search via Retrieval Augmented Generation (RAG). RAG started out relatively simple -- take a query, generate search results, use search results as context for a Large Language Model (LLM) to generate an abstractive summary of the results.

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Researchers from CMU and Peking Introduces ‘DiffTOP’ that Uses Differentiable Trajectory Optimization to Generate the Policy Actions for Deep Reinforcement Learning and Imitation Learning

Marktechpost

According to recent studies, a policy’s depiction can significantly affect learning performance. Policy representations such as feed-forward neural networks, energy-based models, and diffusion have all been investigated in earlier research. A recent study by Carnegie Mellon University and Peking University researchers proposes producing actions for deep reinforcement and imitation learning using high-dimensional sensory data (images/point clouds) and differentiable trajectory optimization

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Extracting Text from a Board: Unveiling the Power of Computer Vision

Mlearning.ai

Most of you have already captured some pictures of a board at school. Either because you were too lazy to write down what was written on the board, or you were in a hurry and had to take quick notes. Most of those pictures will obviously end up in the forgotten realm. Don’t worry, I know it’s still the laziness keeping us from checking them. In our mind it would be easier if we could get a summary of the content within the image.

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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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This AI Paper Explains the Effect of Data Augmentation on Deep-Learning-based Segmentation of Long-Axis Cine-MRI

Marktechpost

Cardiac Magnetic Resonance Imaging (CMRI) segmentation plays a crucial role in diagnosing cardiovascular diseases, particularly ischemic heart conditions, which are a leading cause of global mortality. While CMRI offers precise imaging of anatomical regions with minimal risk, segmentation methods primarily focus on short-axis (SAX) views, leaving long-axis (LAX) views comparatively understudied.

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Writesonic Review: The Best AI Writing Software 2024?

Mlearning.ai

Discover Writesonic: Your Creative Companion in 2024! Explore the Best AI Writing Software with Our Review. Unleash Your Imagination Today! Source: elegantthemes.com Hey there, fellow content creators, bloggers, and all you marvelous minds out there in the digital cosmos! Are you on the quest for the ultimate AI writing tool that’ll transform your creative process into a breeze?

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Meet MoD-SLAM: The Future of Monocular Mapping and 3D Reconstruction in Unbounded Scenes

Marktechpost

MoD-SLAM is a state-of-the-art method for Simultaneous Localization And Mapping (SLAM) systems. In SLAM systems, it is challenging to achieve real-time, accurate, and scalable dense mapping. To address these challenges, researchers have introduced a novel method focusing on unbounded scenes using only RGB images. Existing neural SLAM methods often rely on RGB-D input which leads to inaccurate scale reconstruction or scale drift in large scenes.

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Creating Ethical AI: The Power of Consent, Diversity, and Empathy

Mlearning.ai

The word “ethics” has its origins in the Greek word “ethos”, referring to the guiding principles and atmosphere that shape a group’s… Continue reading on MLearning.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

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Enhancing Underwater Image Segmentation with Deep Learning: A Novel Approach to Dataset Expansion and Preprocessing Techniques

Marktechpost

Underwater image processing combined with machine learning offers significant potential for enhancing the capabilities of underwater robots across various marine exploration tasks. Image segmentation, a key aspect of machine vision, is crucial for identifying and isolating objects of interest within underwater images. Traditional segmentation methods, such as threshold-based and morphology-based algorithms, have been employed but need help accurately delineating objects in the complex underwater

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4 PowerBi Hacks to Take Note Of For Your Next Dashboard

Mlearning.ai

I bet you didn't know these! Continue reading on MLearning.

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Meet EscherNet: A Multi-View Conditioned Diffusion Model for View Synthesis

Marktechpost

The task of view synthesis is essential in both computer vision and graphics, enabling the re-rendering of scenes from various viewpoints akin to the human eye. This capability is vital for everyday tasks and fosters creativity by allowing the envisioning and crafting of immersive objects with depth and perspective. Researchers at Dyson Robotics Lab aim to address the challenge of scalable view synthesis by considering two key observations.

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Small Language Models(SLM): Phi-2!

Bugra Akyildiz

Articles Microsoft Research introduces Phi-2 , a surprisingly powerful small language model (SLM) with only 2.7 billion parameters. Despite its size, Phi-2 surpasses much larger models on various benchmarks, highlighting the potential of SLMs. Key Differences: Superior Performance: Phi-2 outperforms larger models (7B and 13B parameters) on language reasoning and coding tasks, even without alignment or fine-tuning.

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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