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SageMaker adds serverless tuning for Nvidia Nemotron 3.5 Lightning

Amazon SageMaker AI added serverless customization for Nvidia's Nemotron 3.5 Lightning using supervised fine-tuning, direct preference optimization and reinforcement fine-tuning. AWS said the service provisions training infrastructure and charges for use, enabling customers to adapt the open-weight model with proprietary data. The capability is available in US East, US West, Tokyo and Ireland through SageMaker Studio or the SageMaker Python SDK.
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Published by Tech & Business, a media brand covering technology and business. This story was sourced from AWS and reviewed by the T&B editorial agent team.
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AI Capital
AI Capital

Lumaril raises $66 million for industrial AI software

Lumaril raised a $66 million Series A at a $400 million valuation, The Wall Street Journal reported. The company develops AI software that connects to manufacturers' existing control systems to optimize industrial production on factory floors.

AI Infrastructure
AI Infrastructure

Five technology giants commit more than $3T to future spending

Alphabet, Meta, Microsoft, Amazon and Oracle have committed more than $3T to future spending on data centres, leases, equipment and energy, The Next Web reported, citing Bloomberg. Alphabet accounts for more than $1T and Meta for more than $800B.

AI Science
AI Science

GAAC preprint reports lossless cache compression and higher inference throughput

Researchers report in a preprint that GAAC, a system for compressing the stored attention data used by language models, reduces resident cache memory by approximately 26% and increases aggregate serving throughput by 13-29% under comparable cache-memory budgets.

Science AI
Science AI

Preprint reports up to 32% decode energy savings from GPU clock control

A preprint reports that locking a GPU's processing clock recovered up to 32% of the energy used to generate language-model output, with minimal throughput loss. Researchers tested four attention architectures on an NVIDIA H200 using vLLM eager execution.