Massive models were too slow to scale. Moving to H100 inference cut latency by 50% and slashed costs by 4x.
Founded by the former engineering lead for PyTorch at Meta, this platform enables developers to run and fine-tune large language models efficiently.
Foundation models with billions of parameters require massive compute resources, making them too slow or expensive for production use. Developers...
“Achieving optimal cost-performance for scale and productionization is a primary challenge for customers developing on PyTorch. It’s particularly true with generative AI products and models because of their sheer size as well as how new and fast this field is. We wanted to use AWS to help to bridge this gap.”
Inference platform for deploying and fine-tuning open-source generative AI models.
Cloud computing platform and on-demand infrastructure services.
Fireworks AI's Generative AI infrastructure is part of this use case:
Related implementations across industries and use cases
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Similarity search mixed up Q3 and Q4 earnings. Hybrid AI now anchors retrieval with keywords and learns from human fixes instantly.
Voice integration demanded 400 lines of code. A pre-built framework cuts that to 40, enabling rapid agent deployment.
Engineers spent 90% of time on data prep. New pipelines flipped that to 90% modeling and cut tuning from 7 days to 1 hour.
Micro-delays broke 200-step automations. A custom inference engine now ensures 92% accuracy and handles 3x traffic spikes.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Massive models were too slow to scale. Moving to H100 inference cut latency by 50% and slashed costs by 4x.
Founded by the former engineering lead for PyTorch at Meta, this platform enables developers to run and fine-tune large language models efficiently.
Foundation models with billions of parameters require massive compute resources, making them too slow or expensive for production use. Developers...
“Achieving optimal cost-performance for scale and productionization is a primary challenge for customers developing on PyTorch. It’s particularly true with generative AI products and models because of their sheer size as well as how new and fast this field is. We wanted to use AWS to help to bridge this gap.”
Inference platform for deploying and fine-tuning open-source generative AI models.
Cloud computing platform and on-demand infrastructure services.
Fireworks AI's Generative AI infrastructure is part of this use case:
Related implementations across industries and use cases
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Similarity search mixed up Q3 and Q4 earnings. Hybrid AI now anchors retrieval with keywords and learns from human fixes instantly.
Voice integration demanded 400 lines of code. A pre-built framework cuts that to 40, enabling rapid agent deployment.
Engineers spent 90% of time on data prep. New pipelines flipped that to 90% modeling and cut tuning from 7 days to 1 hour.
Micro-delays broke 200-step automations. A custom inference engine now ensures 92% accuracy and handles 3x traffic spikes.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.