Shutterstock Expands into AI Services for Model Training
Shutterstock has launched a new suite of AI services aimed at enhancing model training and evaluation, announced in a press release. This move leverages Shutterstock's extensive content corpus and metadata licensing expertise to provide specialized training datasets and evaluation tools for AI model builders.
The new services include custom content production, creative-expert preference data, curation and annotation services, and evaluation and performance insights. These offerings are designed to support the entire model training lifecycle, providing high-quality, human-calibrated signals that align with AI models' specific needs.
Shutterstock aims to transition from being a data provider to an active partner in model construction, training, and assessment. This strategic evolution positions Shutterstock as a valuable partner to industry leaders like NVIDIA, Meta, and OpenAI, helping shape the next generation of generative AI tools and standards.
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Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
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