Fireworks says you’re wasting money on AI unless you’re using all the models
The case for managed inference, or automatically routing queries to the right model for the right job
As we navigate the expanding universe of AI models, it's clear that a one-size-fits-all approach is inefficient and costly. Embracing managed inference, where queries are directed to the most suitable model for the task, promises smarter, more economical use of AI resources, aligning with our long-term goal of sustainable technological growth.
Panel script
A crowded tech conference booth with a demo laptop and a stack of brochures. A person types on a keyboard while a colleague adjusts a 'Fireworks' presentation on a nearby monitor.
Managed inference: routing queries to the right model.
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Script
Panel 1
INT. HOME OFFICE - DAY JACK, a scruffy but determined software engineer, is sitting in front of his computer, surrounded by empty energy drink cans and scattered papers. He's staring intently at a laptop screen displaying a complex AI model setup. JACK (muttering to himself) I need to pick the right AI model for this project... but there are so many options!
Panel 2
JACK sighs deeply, rubbing his temples as he looks up from his screen, glancing at a stack of books on AI models and a whiteboard filled with complex diagrams and equations.
Jack: Ugh, if only there was a way to automate this...
Panel 3
JACK’s computer screen suddenly changes, showing a simple interface with a button labeled He stares at it in disbelief, then bursts into laughter. JACK (laughing) Well, duh! I should have known there’s an AI for that!
JACK: Managed Inference.
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