AI: Data, Algorithm and Compute
To successfully deploy state-of-the-art AI, three criteria must be met: a large and clean dataset with little bias, great algorithms and models, and an efficient compute infrastructure that can be scaled easily without staggering increases in cost.
With the growing popularity of AI and cumulative investments over the years, “Data” and “Algorithm,” have become much more accessible. Many open-source and commercial tools exist for data labeling and annotation. Libraries like FastAI, Hugging Face, and PyTorch Lightning are providing higher level abstractions to make model prototyping and research easier.
Most importantly, the introduction of the Transformer architecture enabled a new paradigm of deep learning development. Transformers allowed the use of open-source pre-trained models and their adoption to individual datasets, creating a new era of deep learning for natural language processing. The Transformer architecture provided remarkable performance on tasks such as text generation, classification, translation, and more. However, the models were much larger than the computer vision versions, making them easy to explore but harder to put into production.
The Need for AI Acceleration
With larger and more accurate ML models, average model latency has increased, resulting in less model inferences per dollar. Accordingly, larger ML models have become more expensive, time-consuming, and difficult to deploy than their smaller counterparts. The solution to this problem is AI acceleration: a process of making compute-intensive workloads run faster and more efficiently through hardware and software. However, only the largest tech companies have access to these technologies, leaving everyone else who wants to efficiently deploy the best ML models behind.
After years of research on making machine learning algorithms run as efficiently as possible, we have decided to tackle the challenges of AI acceleration to make the best AI accessible to everyone through our Accelerated AI Platform.
Stochastic X: Accelerated AI Platform
Stochastic X revolutionizes how companies use machine learning models by generating a production-grade AI pipeline, powered by automated AI acceleration technology. Through our proprietary AI-powered solution, we enable customers to optimize AI models based on their individual objectives.
State-of-the-Art AI Production Pipeline
With Stochastic X, companies can:
Compute more: access more dollars per inference when compressing larger models with higher accuracy and lower latency. On some of the most demanding deep learning models, our platform can achieve latency improvements exceeding 10x
Spend less: decrease total compute costs by more than 80% as the result of making AI compute more efficient
Save time: lower time-to-production from months to hours. Most optimization pipelines take weeks or months to implement, and they require engineers with expert knowledge (who fail in many cases)
Features
The Stochastic X platform has the following features:
AI acceleration: receive over 10x speedup by leveraging cutting-edge optimization of large deep learning models using software and hardware acceleration techniques
Comprehensive benchmarking: make informed decisions on model deployment options by comparing performance of datasets across models, and comparing models across different compute options
Pipeline monitoring and auto-tuning: monitor already-deployed models and use auto-tuning to automatically improve pipeline efficiency over time
Hosting Options
Stochastic supports deploying models on the cloud or on-premise. Stochastic works with all the popular tools and frameworks.
Fully-managed ML service: Host your models and data on our cloud. Great for companies who don’t want to set up their own machine learning infrastructure.
Enterprise self-hosted: Host your models and data on your servers. Our product easily integrates into existing CI/CD pipelines. Great for companies who have strict restrictions on data privacy.
The Next-generation Deep Learning Platform
Stochastic has built a platform that makes the best AI accessible to all companies. Through libraries, UI or APIs, large and complex models can be automatically optimized, and deployed to production in a line of code or a click of a button. Access Stochastic X here.
For more information, contact us at hello@stochastic.ai.