Analytics Vidhya

OCTOBER 11, 2024

Introduction The rise of large language models (LLMs), such as OpenAI’s GPT and Anthropic’s Claude, has led to the widespread adoption of generative AI (GenAI) products in enterprises. Organizations across sectors are now leveraging GenAI to streamline processes and increase the efficiency of their workforce. Integrating LLM agents into an organization requires thoughtful planning and […] The post Step-by-Step Guide to Integrate LLM Agents in an Organization appeared first on Analyti

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LLM Large Language Models OpenAI Generative AI 175

Unite.AI

OCTOBER 11, 2024

A new research collaboration between Singapore and China has proposed a method for attacking the popular synthesis method 3D Gaussian Splatting (3DGS). The new attack method uses crafted source data to overload the available GPU memory of the target system, and to make training so lengthy as to potentially incapacitate the target server, equivalent to a denial-of-service (DOS) attack.

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AssemblyAI

OCTOBER 11, 2024

AssemblyAI is now integrated with Langflow , a powerful low-code platform for building generative AI applications.  Langflow is a visual framework for building multi-agent and RAG (Retrieval-Augmented Generation) applications. It is open-source, Python-powered, fully customizable, and LLM and vector store agnostic. It allows for easy manipulation of AI building blocks, enabling developers to quickly prototype and turn their ideas into real-world solutions.

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Unite.AI

OCTOBER 11, 2024

While large language models (LLMs) like GPT-3 and Llama are impressive in their capabilities, they often need more information and more access to domain-specific data. Retrieval-augmented generation (RAG) solves these challenges by combining LLMs with information retrieval. This integration allows for smooth interactions with real-time data using natural language, leading to its growing popularity in various industries.

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Marktechpost

OCTOBER 11, 2024

In the rapidly evolving world of artificial intelligence, one pressing challenge that developers face is orchestrating complex multi-agent systems. These systems, involving multiple AI agents working collaboratively, often present significant difficulties in coordination, control, and scalability. Current solutions tend to be heavy, requiring extensive resource allocation, which complicates deployment and testing.

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Marktechpost

OCTOBER 11, 2024

Retrieval-augmented generation (RAG) has become a key technique in enhancing the capabilities of LLMs by incorporating external knowledge into their outputs. RAG methods enable LLMs to access additional information from external sources, such as web-based databases, scientific literature, or domain-specific corpora, which improves their performance in knowledge-intensive tasks.

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NVIDIA

OCTOBER 11, 2024

In 1999, fans lined up at Blockbuster to rent chunky VHS tapes of The Matrix. Y2K preppers hoarded cash and canned Spam, fearing a worldwide computer crash. Teens gleefully downloaded Britney Spears and Eminem on Napster. But amid the caffeinated fizz of turn-of-the-millennium tech culture, something more transformative was unfolding. The release of NVIDIA’s GeForce 256 twenty-five years ago today, overlooked by all but hardcore PC gamers and tech enthusiasts at the time, would go on to lay the

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Marktechpost

OCTOBER 11, 2024

Generating accurate and aesthetically appealing visual texts in text-to-image generation models presents a significant challenge. While diffusion-based models have achieved success in creating diverse and high-quality images, they often struggle to produce legible and well-placed visual text. Common issues include misspellings, omitted words, and improper text alignment, particularly when generating non-English languages such as Chinese.

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Extreme Tech

OCTOBER 11, 2024

The company appears to be mostly finished with its second-generation 'Battlemage' GPUs, even though they've yet to launch in discrete form.

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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

Marktechpost

OCTOBER 11, 2024

Information Retrieval (IR) systems for search and recommendations often utilize Learning-to-Rank (LTR) solutions to prioritize relevant items for user queries. These models heavily depend on user interaction features, such as clicks and engagement data, which are highly effective for ranking. However, this reliance presents significant challenges. User Interaction data can be noisy and sparse, especially for newer or less popular items, resulting in cold start problems where these items are rank

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Extreme Tech

OCTOBER 11, 2024

Intel even says AMD's 7800X3D will be slightly faster in gaming than its own just-announced Core Ultra 200 series.

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Marktechpost

OCTOBER 11, 2024

Large language models (LLMs) have emerged as powerful tools capable of performing complex tasks beyond text generation, including reasoning, tool learning, and code generation. These advancements have sparked significant interest in developing LLM-based language agents to automate scientific discovery processes. Researchers are exploring the potential of these agents to revolutionise data-driven discovery workflows across various disciplines.

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Automation Large Language Models Python LLM 111

Extreme Tech

OCTOBER 11, 2024

Sadly, room-temperature superconductors still aren't a thing. But one rare-earth mineral gets close. Sort of.

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Speaker: Brendan Sweeney, VP of Sales & Devyn Blume, Sr. Account Executive

Are you curious about how artificial intelligence is reshaping sales coaching, learning, and development? Join Brendan Sweeney and Devyn Blume of Allego for an engaging new webinar exploring AI's transformative role in sales coaching and performance improvement! Brendan and Devyn will share actionable insights and strategies for integrating AI into coaching and development - ensuring personalized, effective, and scalable training!

AI

Marktechpost

OCTOBER 11, 2024

While writing the code for any program or algorithm, developers can struggle to fill gaps in incomplete code and often make mistakes while trying to fit new pieces into existing code snippets or structures. These challenges arise from the difficulty of fitting the latest code with the prior and following parts, especially when the broader part of the context is not taken into consideration.

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Extreme Tech

OCTOBER 11, 2024

Microsoft acknowledges the issue and promises a fix in the upcoming update.

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Marktechpost

OCTOBER 11, 2024

Multimodal Situational Safety is a critical aspect that focuses on the model’s ability to interpret and respond safely to complex real-world scenarios involving visual and textual information. It ensures that Multimodal Large Language Models (MLLMs) can recognize and address potential risks inherent in their interactions. These models are designed to interact seamlessly with visual and textual inputs, making them highly capable of assisting humans by understanding real-world situations and provi

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Extreme Tech

OCTOBER 11, 2024

The boards are now available for pre-order, even though the CPUs have yet to be tested by independent sites.

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Marktechpost

OCTOBER 11, 2024

In the rapidly evolving landscape of artificial intelligence, the quality and quantity of data play a pivotal role in determining the success of machine learning models. While real-world data provides a rich foundation for training, it often faces limitations such as scarcity, bias, and privacy concerns. These challenges can hinder the development of accurate and reliable AI systems.

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Extreme Tech

OCTOBER 11, 2024

Don't book your ride yet—it'll be years before we see either of these vehicles on the road.

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Marktechpost

OCTOBER 11, 2024

The problem that this research seeks to address lies in the inherent limitations of existing large language models (LLMs) when applied to formal theorem proving. Current models are often trained or fine-tuned on specific datasets, such as those focused on undergraduate-level mathematics, but struggle to generalize to more advanced mathematical domains.

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Large Language Models ML AI AI 105

Extreme Tech

OCTOBER 11, 2024

A OnePlus executive confirms the upcoming release of the OnePlus 13 with the latest Snapdragon chip.

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Speaker: Michael Mansard and Katherine Shealy

Generative AI is no longer just an exciting technological advancement––it’s a seismic shift in the SaaS landscape. Companies today are grappling with how to not only integrate AI into their products but how to do so in a way that makes financial sense. With the cost of developing AI capabilities growing, finding a flexible monetization strategy has become mission critical.

AI

AWS Machine Learning Blog

OCTOBER 11, 2024

Customers across all industries are experimenting with generative AI to accelerate and improve business outcomes. Generative AI is used in various use cases, such as content creation, personalization, intelligent assistants, questions and answers, summarization, automation, cost-efficiencies, productivity improvement assistants, customization, innovation, and more.

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Metadata Generative AI LLM Data Ingestion 85

Marktechpost

OCTOBER 11, 2024

Graphical User Interface (GUI) agents are crucial in automating interactions within digital environments, similar to how humans operate software using keyboards, mice, or touchscreens. GUI agents can simplify complex processes such as software testing, web automation, and digital assistance by autonomously navigating and manipulating GUI elements. These agents are designed to perceive their surroundings through visual inputs, enabling them to interpret the structure and content of digital interf

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Large Language Models Artificial Intelligence Artificial Intelligence Automation 100

NVIDIA

OCTOBER 11, 2024

The autonomous driving industry is shaped by rapid technological advancements and the need for standardization of guidelines to ensure the safety of both autonomous vehicles (AVs) and their interaction with human-driven vehicles. At the NVIDIA AI Summit this week in Washington, D.C., industry experts shared viewpoints on this AV safety landscape from regulatory and technology perspectives.

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Marktechpost

OCTOBER 11, 2024

Text-to-Audio (TTA) and Text-to-Music (TTM) generation have seen significant advancements in recent years, driven by audio-domain diffusion models. These models have demonstrated superior audio modeling capabilities compared to generative adversarial networks (GANs) and variational autoencoders (VAEs). However, diffusion models face the challenge of long inference times due to their iterative denoising process.

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NYU Center for Data Science

OCTOBER 11, 2024

Diffusion models have transformed generative AI by enabling the creation of realistic images, videos and molecules, yet they’ve been limited by an inability to handle nonlinear diffusion processes common in the physical sciences. Addressing this gap, CDS Assistant Professor of Computer Science and Data Science Rajesh Ranganath and Courant PhD students Raghav Singhal and Mark Goldstein developed a method to extend diffusion models to nonlinear processes.

Automation 58

Automation Data Science Machine Learning AI 58

Marktechpost

OCTOBER 11, 2024

Multimodal Attributed Graphs (MMAGs) have received little attention despite their versatility in image generation. MMAGs represent relationships between entities with combinatorial complexity in a graph-structured manner. Nodes in the graph contain both image and text information. Compared to text or image conditioning models, graphs could be converted into better and more informative images.

ML 59

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ODSC - Open Data Science

OCTOBER 11, 2024

Technology is causing businesses to evolve quickly. However, companies must ensure their workforce has the right skills to use it. To tackle this challenge, organizations are turning to AI to help identify and address skill gaps. How AI Helps Identify Skill Gaps Technology adoption is driving business and workforce transformation, and skill gaps are becoming more apparent.

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