AI and Machine Learning

New information on AI and Machine Learning

Four Practical Applications Of Artificial Intelligence And 5G

It is no secret that artificial intelligence (AI) is a technical marketing whitewash. Many companies claim that its algorithms and data scientists enable a differentiated approach in the networking infrastructure space. However, what are the practical applications of AI for connectivity and, in particular, 5G? From my perspective, it encapsulates four key areas. Here I …

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NVIDIA GTC: “DPU” Smart NIC And More

NVIDIA Co-founder and CEO Jensen Huang rarely disappoints his audience nor his investors. This week he once again delivered the goods at the GPU Technology Conference. Announcing a broad range of hardware and software innovations, Jensen made it clear that he intends to reshape computation, from GPUs to CPUs to NICs and switches. So, let’s …

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RESEARCH PAPER: Tenstorrent’s Holistic Stack Of AI Innovation

The explosive growth of AI processing in data center and edge environments has induced AI startups and established firms alike to develop silicon to handle the massive processing demands of neural networks. Inference processing, in particular, is an emerging opportunity, wherein a trained deep neural network is processed to predict characteristics of new data samples. …

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RESEARCH PAPER: Blaize: AI For The Edge

While NVIDIA dominates the market for AI-specific silicon accelerating the training of neural networks, many AI startups are developing silicon to accelerate inference processing, both for data center and edge applications. CPUs have typically been the choice for inference processing, but this is changing rapidly as the size of neural networks grows exponentially and applications …

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Qualcomm Launches Cloud AI Chip

Last year, Qualcomm teased its Cloud AI100, promising strong performance and power efficiency to enable Artificial Intelligence in cloud edge computing, autonomous vehicles and 5G infrastructure. Today, the company announced it is now sampling the platform, with volume shipments planned for the first half of 2021. This begs the question: why would a company known for …

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NVIDIA Needed A CPU, But Did It Need To Buy Arm To Get One?

I often opine that NVIDIA needs a data center-class CPU to compete with Intel and AMD, both of whom have used tightly-coupled CPU/GPU technology to win the first three U.S. exascale supercomputer deals. Connecting massive GPUs to fast CPUs over a painfully slow PCIe interface will not meet the needs of the future of supercomputing …

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