Akamai adds Nvidia GPUs to cloud network, initially targeting media
Akamai has been steadily building out its distributed cloud infrastructure for multiple use cases including AI and machine learning workloads that require low latency near data.
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Akamai has been steadily building out its distributed cloud infrastructure for multiple use cases including AI and machine learning workloads that require low latency near data.
Foundational model debates--large language models, small language models, orchestration, enterprise data and choices--are surfacing in ongoing enterprise buyer discussions. The challenge: You may need a crystal ball and architecture savvy to avoid previous mistakes such as lock-in.
Anthropic CEO Dario Amodei said large language model personality is starting to matter, argued costs to train models will come down and agents that act autonomously will need more scale and reliability.
The price changes go into effect Oct. 1 and range from an additional $10 to $15 more a month per user for most apps, but $30 more for a select apps.
Amazon CEO Andy Jassy said AWS is underway building "primitive services," or discrete building blocks, for generative AI and that approach will ensure customers bring more workloads to the cloud service.
The second version of the Meta Training and Inference Accelerator (MTIA) highlights how cloud hyperscale players are creating their own processors for large language model (LLM) training and inferencing.
Google Cloud pitched an agent-oriented vision for generative AI at Google Cloud Next and highlighted a bevy of emerging use cases going from pilot to production.
The chipmaker's Gaudi 3 launch, announced at the Intel Vision conference, is the linchpin of Intel's plans to garner AI training and inference workloads and take share from Nvidia.
MongoDB expanded integrations with Google Cloud's Vertex AI, BigQuery, Google Distributed Cloud and Google Cloud Manufacturing Data Engine.
Google Cloud outlined a series of services and enhancements across its platform in a bid to make it easier for enterprises to bring their data to generative AI models, build applications and deploy them at scale.
JPMorgan Chase CEO Jamie Dimon issued his annual shareholder letter and provided an incremental update on the company's artificial intelligence efforts as well as private cloud buildout.