Flush with new cash, AssemblyAI looks to grow its AI-as-a-service business

Large-scale machine learning models are at the heart of headline-grabbing technologies like OpenAI’s DALL-E 2 and Google’s LaMDA. They’re impressive, to be sure, capable of generating images and text convincing enough to pass for a human’s work. But developing the models took an enormous amount of time and compute power — not to mention cash. DALL-E 2 alone was trained on 256 GPUs for 2 weeks, which works out to a cost of around $130,000 if it were trained on Amazon Web Services instances, according to one estimate. 
Smaller companies struggle to keep up, which is why m

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