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Submission Deadline: Friday August 9, 2024 5:00PM ET
The new grounding features will help enterprises to reduce hallucinations across their generative AI-based apps and agents, the company says.
Cloud-based generative AI systems that use too many resources turn out to be too complex and expensive. Here’s how you can avoid this.
eBPF allows users to load and safely run custom programs within the Linux kernel, without requiring direct changes to the kernel itself. The possibilities are endless.
To create effective machine learning and deep learning models, you need copious amounts of data, a way to clean the data, and a way to train them, deploy them, and keep them updated. The cloud is usually the best platform for this, but not always.
In the ramp-up for AI, companies feel pressured to choose cloud or on-premises. Let’s learn from past mistakes and realize the solution is rarely one size fits all.
If you've wondered whether you should invest in cloud certification, or which certifications really make a difference, this article has answers.
Amazon Q Developer works well for completing lines of code, doc strings, and if/for/while/try code blocks, but can’t generate full functions for certain use cases.
At Build, Microsoft described how Azure is supporting large AI workloads today, with an inference accelerator, high-bandwidth connections, and tools for efficiency and reliability.
The Linux packager’s SUSE AI Early Access Program could interest companies wanting to run generative AI on premises.
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