Analytics Vidhya

MARCH 23, 2024

Introduction Meet Devika AI: your new go-to buddy in the world of coding. It’s not your typical run-of-the-mill software; it’s here to shake things up! Picture this: you’ve got an idea, a spark of creativity, but you’re unsure how to translate it into code. That’s where Devika AI swoops in to save the day. You […] The post Devika AI: An Open Source Alternative to Devin AI appeared first on Analytics Vidhya.

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Marktechpost

MARCH 23, 2024

HuggingFace Researchers introduce Quanto to address the challenge of optimizing deep learning models for deployment on resource-constrained devices, such as mobile phones and embedded systems. Instead of using the standard 32-bit floating-point numbers (float32) for representing their weights and activations, the model uses low-precision data types like 8-bit integers (int8) that reduce the computational and memory costs of evaluating.

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Analytics Vidhya

MARCH 23, 2024

Introduction In the modern world, technology enables us to accomplish incredible feats, with Artificial Intelligence (AI) being a particularly thrilling aspect of this progress. AI tools are opening up fresh opportunities for individuals to earn money, regardless of whether they are business owners or seeking additional sources of income. Our guide demonstrates how you can […] The post How to Make Money Using AI Tools?

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Marktechpost

MARCH 23, 2024

Football has always been a game of tactical brilliance and strategic genius. From the dugouts of your local parks to the hallowed turf of the biggest stadiums, coaches are constantly tinkering with formations, set-piece routines, and game plans – all in pursuit of that elusive winning edge. But in the modern era, the battle for footballing supremacy is no longer just about the intuition of brilliant minds.

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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.

Extreme Tech

MARCH 23, 2024

Your most frequently asked questions about gravity, answered. Now with more spooky action at a distance!

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Salmon Run

MARCH 23, 2024

Drug Discovery is a field where biochemists (and more recently computer scientists) turn ideas into potential medications.

Machine Learning 45

Machine Learning Neural Network Computer Scientist Deep Learning 45

Marktechpost

MARCH 23, 2024

In the dynamic landscape of Artificial Intelligence, a longstanding debate questions the need for copyrighted materials in training top AI models. OpenAI’s bold assertion to the UK Parliament in 2023 that training such models without utilizing copyrighted content was ‘impossible’ sent shockwaves through the industry, sparking legal battles and ethical quandaries.

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LLM Large Language Models OpenAI Artificial Intelligence 128

Marktechpost

MARCH 23, 2024

In the dynamic realm of computer vision and artificial intelligence, a new approach challenges the traditional trend of building larger models for advanced visual understanding. The approach in the current research, underpinned by the belief that larger models yield more powerful representations, has led to the development of gigantic vision models.

Computer Vision 128

Computer Vision Artificial Intelligence Artificial Intelligence Robotics 128

Marktechpost

MARCH 23, 2024

Researchers and developers need to run large language models (LLMs) such as GPT (Generative Pre-trained Transformer) efficiently and quickly. This efficiency heavily depends on the hardware used for training and inference tasks. Central Processing Units (CPUs) and Graphics Processing Units (GPUs) are the main contenders in this arena. Each has strengths and weaknesses in processing the complex computations LLMs require.

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Large Language Models ML Machine Learning AI Researcher 119

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

LLM

Marktechpost

MARCH 23, 2024

Harnessing the strong language understanding and generation potential of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs) have been developed in recent years for vision-and-language understanding tasks. MLLMs have shown promising results in understanding general images by aligning a pre-trained visual encoder (e.g., the Vision Transformers) and the LLM with a Vision-toText (V2T) module.

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Large Language Models LLM ML Computer Vision 121

Marktechpost

MARCH 23, 2024

The term “text mining” refers to discovering new patterns and insights in massive amounts of textual data. Generating a taxonomy—a collection of structured, canonical labels that characterize features of the corpus—and text classification—the labeling of instances within the corpus using said taxonomy—are two fundamental and related activities in text mining.

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Marktechpost

MARCH 23, 2024

The relentless pursuit of refining artificial intelligence has led to the creation of sophisticated Large Language Models (LLMs) such as GPT-3 and GPT-4, significantly expanding the boundaries of machine understanding and interaction with human language. These models, developed by leading research institutions and tech giants, have showcased their potential by excelling in various reasoning tasks, from solving complex mathematical problems to understanding nuances in natural language.

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Marktechpost

MARCH 23, 2024

In academic research, particularly in computer vision, keeping track of conference papers can be a real challenge. Unlike journal articles, conference papers often lack easily accessible metadata such as DOI or ISBN, making them harder to find and cite. Researchers have to spend a lot of time manually searching for this information on platforms like Google Scholar or DBLP, which can be time-consuming and frustrating.

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AI Researcher AI Research Metadata Computer Vision 113

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

MARCH 23, 2024

The search for rapid discovery and materials characterization with tailored properties has recently intensified. One of the central aspects of this research is the understanding of crystal structures, which are inherently complex due to their periodic and infinite nature. This complexity presents a formidable challenge in accurately modeling and predicting material properties, a challenge that traditional computational and experimental methods need help to meet efficiently.

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Machine Learning Neural Network ML AI 106

Marktechpost

MARCH 23, 2024

Although AI is a rapidly growing industry, there are often many obstacles on the path from groundbreaking research to practical applications. Raising the quality of AI models to that of production is a big challenge. Although researchers can create robust models, making them suitable for practical applications can be time-consuming and arduous. Meet Reprompt AI , a cool-start startup with the ambitious goal of transforming how AI teams connect development and deployment.

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Artificial Intelligence Artificial Intelligence AI AI 90

Marktechpost

MARCH 23, 2024

Large language models like GPT-4 are incredibly powerful, but they sometimes struggle with basic tasks involving visual perception – like counting objects in an image. It turns out part of the issue may stem from how these models process high-resolution images. Most current multimodal AI systems can only perceive images at a fixed low resolution, like 224×224 pixels.

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Large Language Models ML AI AI 92

Marktechpost

MARCH 23, 2024

Deep features are pivotal in computer vision studies, unlocking image semantics and empowering researchers to tackle various tasks, even in scenarios with minimal data. Lately, techniques have been developed to extract features from diverse data types like images, text, and audio. These features serve as the bedrock for various applications, from classification to weakly supervised learning, semantic segmentation, neural rendering, and the cutting-edge field of image generation.

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