DataBloom

In today’s data-driven world, the ability to retrieve accurate information from even modest amounts of data is vital for developers seeking streamlined,…

In today’s data-driven world, the ability to retrieve accurate information from even modest amounts of data is vital for developers seeking streamlined, effective solutions for quick deployments, prototyping, or experimentation. One of the key challenges in information retrieval is managing the diverse modalities in unstructured datasets, including text, PDFs, images, tables, audio, video…

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A well-crafted systematic review is often the initial step for researchers exploring a scientific field. For scientists new to this field, it provides a…

A well-crafted systematic review is often the initial step for researchers exploring a scientific field. For scientists new to this field, it provides a structured overview of the domain. For experts, it refines their understanding and sparks new ideas. In 2024 alone, 218,650 review articles were indexed in the Web of Science database, highlighting the importance of these resources in research.

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Vision language models (VLMs) are evolving at a breakneck speed. In 2020, the first VLMs revolutionized the generative AI landscape by bringing visual…

Vision language models (VLMs) are evolving at a breakneck speed. In 2020, the first VLMs revolutionized the generative AI landscape by bringing visual understanding to large language models (LLMs) through the use of a vision encoder. These initial VLMs were limited in their abilities, only able to understand text and single image inputs. Fast-forward a few years and VLMs are now capable of…

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Generative AI is redefining computing, unlocking new ways to build, train and optimize AI models on PCs and workstations. From content creation and large and small language models to software development, AI-powered PCs and workstations are transforming workflows and  enhancing productivity. At GTC 2025, running March 17–21 in the San Jose Convention Center, experts from
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Explore the future of extended reality, and learn how spatial computing is changing the future of immersive development and industry workflows.

Explore the future of extended reality, and learn how spatial computing is changing the future of immersive development and industry workflows.

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Chip and hardware design presents numerous challenges stemming from its complexity and advancing technologies. These challenges result in longer turn-around…

Chip and hardware design presents numerous challenges stemming from its complexity and advancing technologies. These challenges result in longer turn-around time (TAT) for optimizing performance, power, area, and cost (PPAC) during synthesis, verification, physical design, and reliability loops. Large language models (LLMs) have shown a remarkable capacity to comprehend and generate natural…

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NVIDIA cuDSS is a first-generation sparse direct solver library designed to accelerate engineering and scientific computing. cuDSS is increasingly adopted in…

NVIDIA cuDSS is a first-generation sparse direct solver library designed to accelerate engineering and scientific computing. cuDSS is increasingly adopted in data centers and other environments and supports single-GPU, multi-GPU and multi-node (MGMN) configurations. cuDSS has become a key tool for accelerating computer-aided engineering (CAE) workflows and scientific computations across…

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Agentic workflows are the next evolution in AI-powered tools. They enable developers to chain multiple AI models together to perform complex activities, enable…

Agentic workflows are the next evolution in AI-powered tools. They enable developers to chain multiple AI models together to perform complex activities, enable AI models to use tools to access additional data or automate user actions, and enable AI models to operate autonomously, analyzing and performing complex tasks with a minimum of human involvement or interaction. Because of their power…

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There is an activity where people provide inputs to generative AI technologies, such as large language models (LLMs), to see if the outputs can be made to…

There is an activity where people provide inputs to generative AI technologies, such as large language models (LLMs), to see if the outputs can be made to deviate from acceptable standards. This use of LLMs began in 2023 and has rapidly evolved to become a common industry practice and a cornerstone of trustworthy AI. How can we standardize and define LLM red teaming?

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