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Demand for end-to-end platforms, the convergence of data and AI, and the evolution of roles in the generative AI era are all driving the change, say analysts.
Their current success and growth are thanks to AI adoption, but unsustainable costs and viable alternatives may turn enterprises away in the longer term.
Usage API monitors token usage by minute, hour, or day and includes a costs endpoint that provides a breakdown of daily spend.
Family of tunable vision-language models based on Gemma 2 generate long captions for images that describe actions, emotions, and narratives of the scene.
Microsoft’s new generative AI-powered, multimodal, content analysis service is a next-generation version of its existing Cognitive Services platform.
From an all-new version of SageMaker to new large language models, AWS is going all out to boost its offerings for developers.
Even as Meta touts its Llama model, the company is incorporating OpenAI’s GPT-4 to enhance internal tools and philanthropic ventures.
Heroku also announced that its Next Generation platform, which supports building and deploying Kubernetes and AI applications, is available in a pilot.
Other database updates include the general availability of MemoryDB Multi-Region and new observability features for Amazon Aurora MySQL and PostgreSQL.
What’s the best way to store, search, and analyze content not based on their technical characteristics but on their meaning?