AI News

OCTOBER 14, 2024

When we talk about real-time data, what we refer to is information that becomes available as soon as it’s created and acquired. Rather than being stored, data is forwarded directly to an application as soon as it’s collected and is made immediately available – without any lag – to support live, in-the-moment decision-making. Real-time data is at work in virtually every aspect of our lives already, powering everything from bank transactions to GPS to emergency maps created when a disa

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Analytics Vidhya

OCTOBER 14, 2024

Introduction Today, we will discuss the first pattern in the series of agentic AI design patterns: The Reflection Pattern. The Reflection Pattern is a powerful approach in AI, particularly for large language models (LLMs), where an iterative process of generation and self-assessment improves the output quality. We can picture it as a course developer who […] The post What is Agentic AI Reflection Pattern?

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AI News

OCTOBER 14, 2024

Four major US firms have announced plans to invest a combined £6.3 billion in UK data infrastructure. The announcement, made during the International Investment Summit , was welcomed by Technology Secretary Peter Kyle as a “vote of confidence” in Britain’s approach to partnering with businesses to drive growth. CyrusOne, ServiceNow, CloudHQ, and CoreWeave have all committed to substantial investments, bringing the total investment in UK data centres to over £25 billion since t

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IBM Journey to AI blog

OCTOBER 14, 2024

Data’s the gas that makes the AI engines hum. And many companies aren’t taking full advantage of the treasure trove of unstructured data at their fingertips because they’re not sure how to fill the tank. That’s why businesses that have the tools to process unstructured data are catching investors’ attention. Just last month, Salesforce made a major acquisition to power its Agentforce platform—just one in a number of recent investments in unstructured data mana

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Business Intelligence AI AI Automation 219

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

Unite.AI

OCTOBER 14, 2024

Skip Levens is a product leader and AI strategist at Quantum, a leader in data management solutions for AI and unstructured data. He is currently responsible for driving engagement, awareness, and growth for Quantum's end-to-end solutions. Throughout his career – which has included stops at organizations like Apple, Backblaze, Symply, and Active Storage – he has successfully led marketing and business development, evangelism, launched new products, built relationships with key stakeholders, and

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Analytics Vidhya

OCTOBER 14, 2024

Introduction In today’s digital world, Large Language Models (LLMs) are revolutionizing how we interact with information and services. LLMs are advanced AI systems designed to understand and generate human-like text based on vast amounts of data. They use deep learning techniques, particularly transformers, to perform various language tasks such as translation, text generation, and summarization. […] The post 12 Free And Paid LLMs for Your Daily Tasks appeared first on Analytics Vidh

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Unite.AI

OCTOBER 14, 2024

We live in a world where personalized consumer experiences are increasingly the norm. To think, a couple of decades ago, the only options at the coffee shop were cream and sugar or black. Nowadays, you assume you’ll be able to order your half-caff, no-foam, almond milk cappuccino with two pumps of sugar-free vanilla—anything less would seem outdated.

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Analytics Vidhya

OCTOBER 14, 2024

Introduction While FastAPI is good for implementing RESTful APIs, it wasn’t specifically designed to handle the complex requirements of serving machine learning models. FastAPI’s support for asynchronous calls is primarily at the web level and doesn’t extend deeply into the model prediction layer. This limitation poses challenges because AI model predictions are resource-intensive operations that […] The post LitServe: The Future of Scalable AI Model Serving appeared firs

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Unite.AI

OCTOBER 14, 2024

OPINION Nobody in the fictional Star Wars universe takes AI seriously. In the historic human timeline of George Lucas's 47 year-old science-fantasy franchise, threats from singularities and machine learning consciousness are absent, and AI is confined to autonomous mobile robots ( ‘droids' ) – which are habitually dismissed by protagonists as mere ‘machines'.

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Analytics Vidhya

OCTOBER 14, 2024

Introduction Artificial intelligence (AI) is rapidly changing industries around the world, including healthcare, autonomous vehicles, banking, and customer service. While building AI models acquires a lot of attention, AI inference—the process of applying a trained model to fresh data to make predictions—is where the real-world impact occurs. As enterprises become more reliant on AI-powered applications, […] The post NVIDIA NIM: The Future of Scalable AI Inferencing appeared first on Analy

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Unite.AI

OCTOBER 14, 2024

Artificial Intelligence (AI) is transforming the way we create visuals. Text-to-image models make it incredibly easy to generate high-quality images from simple text descriptions. Industries like advertising, entertainment, art, and design already employ these models to explore new creative possibilities. As technology continues to evolve, the opportunities for content creation become even more vast, making the process faster and more imaginative.

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IBM Journey to AI blog

OCTOBER 14, 2024

OpenAI made history recently by securing a USD 6.6 billion investment to scale up its large language models—increasing their size, data volume and computational resources. Meanwhile, Anthropic’s CEO said his company already has USD 1 billion models in development, with USD 100 billion models coming soon. But as spending balloons, new research published in Nature suggests that LLMs may in fact become less reliable as they grow.

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Marktechpost

OCTOBER 14, 2024

Generative AI models, driven by Large Language Models (LLMs) or diffusion techniques, are revolutionizing creative domains like art and entertainment. These models can generate diverse content, including texts, images, videos, and audio. However, refining the quality of outputs requires additional inference methods during deployment, such as Classifier-Free Guidance (CFG).

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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

IBM Journey to AI blog

OCTOBER 14, 2024

OpenAI made history recently by securing a USD 6.6 billion investment to scale up its large language models—increasing their size, data volume and computational resources. Meanwhile, Anthropic’s CEO said his company already has USD 1 billion models in development, with USD 100 billion models coming soon. But as spending balloons, new research published in Nature suggests that LLMs may in fact become less reliable as they grow.

Large Language Models 113

Large Language Models LLM OpenAI ChatGPT 113

Marktechpost

OCTOBER 14, 2024

The problem with efficiently linearizing large language models (LLMs) is multifaceted. The quadratic attention mechanism in traditional Transformer-based LLMs, while powerful, is computationally expensive and memory-intensive. Existing methods that try to linearize these models by replacing quadratic attention with subquadratic analogs face significant challenges: they often lead to degraded performance, incur high computational costs, and lack scalability.

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LLM Large Language Models Inference Engine AI 122

AWS Machine Learning Blog

OCTOBER 14, 2024

With recent advances in large language models (LLMs), a wide array of businesses are building new chatbot applications, either to help their external customers or to support internal teams. For many of these use cases, businesses are building Retrieval Augmented Generation (RAG) style chat-based assistants, where a powerful LLM can reference company-specific documents to answer questions relevant to a particular business or use case.

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Marktechpost

OCTOBER 14, 2024

Current multimodal retrieval-augmented generation (RAG) benchmarks primarily focus on textual knowledge retrieval for question answering, which presents significant limitations. In many scenarios, retrieving visual information is more beneficial or easier than accessing textual data. Existing benchmarks fail to adequately account for these situations, hindering the development of large vision-language models (LVLMs) that need to utilize diverse types of information effectively.

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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.

PyImageSearch

OCTOBER 14, 2024

Home Table of Contents Photogrammetry Explained: From Multi-View Stereo to Structure from Motion Technique #1: Multi-View Stereo Technique #2: Structure from Motion Example: COLMAP Summary and Next Steps Next Steps Citation Information Photogrammetry Explained: From Multi-View Stereo to Structure from Motion In this blog post, you will learn about 3D Reconstruction.

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Marktechpost

OCTOBER 14, 2024

The challenge lies in automating computer tasks by replicating human-like interaction, which involves understanding varied user interfaces, adapting to new applications, and managing complex sequences of actions similar to how a human would perform them. Current solutions struggle with handling complex and varied interfaces, acquiring and updating domain-specific knowledge, and planning multi-step tasks that require precise sequences of actions.

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Artificial Lawyer

OCTOBER 14, 2024

It’s conference season and Artificial Lawyer and its founder, er…me…Richard Tromans, are on tour this October and November. Here are some of the upcoming speaking.

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Marktechpost

OCTOBER 14, 2024

Current text-to-image generation models face significant challenges with computational efficiency and refining image details, particularly at higher resolutions. Most diffusion models perform the generation process in a single stage, requiring each denoising step to be conducted on high-resolution images. This results in high computational costs and inefficiencies, making it difficult to produce fine details without excessive resource use.

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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

databricks

OCTOBER 14, 2024

Over the last few years, we've seen tremendous growth and adoption of Databricks SQL , our intelligent data warehouse purpose-built on the Data.

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Marktechpost

OCTOBER 14, 2024

Language models (LMs) are widely utilized across domains like mathematics, coding, and reasoning to handle complex tasks. These models rely on deep learning techniques to generate high-quality outputs, but their performance can vary significantly depending on the complexity of the input. While some queries are simple and require minimal computation, others are far more complex, requiring significant computational resources to achieve optimal results.

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SAS Software

OCTOBER 14, 2024

El futuro de la innovación empresarial no solo está llegando, está ocurriendo ahora. La reciente clausura del evento SAS Innovate On Tour 2024 en la Ciudad de México dejó claro que la inteligencia artificial generativa (GenAI) y la analítica avanzada están cambiando radicalmente la manera en que las organizaciones operan [.] The post IA generativa y analítica avanzada: el futuro de la innovación corporativa appeared first on SAS Blogs.

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Marktechpost

OCTOBER 14, 2024

LLMs leverage the transformer architecture, particularly the self-attention mechanism, for high performance in natural language processing tasks. However, as these models increase in depth, many deeper layers exhibit “attention degeneration,” where the attention matrices collapse into rank-1, focusing on a single column. These “lazy layers” become redundant as they fail to learn meaningful representations.

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Explore how enterprises can enhance developer productivity and onboarding by adopting self-hosted Cloud Development Environments (CDEs). This whitepaper highlights the simplicity and flexibility of cloud-based development over traditional setups, demonstrating how large teams can leverage economies of scale to boost efficiency and developer satisfaction.

Extreme Tech

OCTOBER 14, 2024

Vast Space hopes Haven-2, which includes everything from laboratories to wood-paneled entertainment rooms, will succeed the ISS after it retires in 2030.

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Marktechpost

OCTOBER 14, 2024

A Model Inversion (MI) attack is a type of privacy attack on machine learning and deep learning models, where an attacker tries to invert the model’s outputs to recreate privacy-sensitive training data that was used during training including the leakage of private images in face recognition models, sensitive health details in medical data, financial information such as transaction records and account balances, and personal preferences and social connections in social media data, etc. raisi

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Extreme Tech

OCTOBER 14, 2024

The company is expected to gain even more market share in 2025 thanks to blockbuster sales of its Blackwell architecture.

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