Leads and prospects generated from search or display ads can be very costly and challenging to obtain. That’s why Apposphere, an Austin, Texas based company, saw a huge opportunity in mining the huge amount of information and activity happening on social media for lead generation.
Aingine™, their powerful real-time data gathering and intelligence engine, troves massive amounts of data and uses deep learning to get extremely targeted and effective in discovering the best opportunities for a given company.
Underneath the hood of their intelligence engine, which is hosted on Amazon Web Services, are Bitfusion’s Deep Learning AMIs. By leveraging the cloud scalability of AWS, and the data science focus and GPU scalability of the Bitfusion solutions, Apposphere scales 50-60% every month — and keeps customer satisfaction high.
Normally, complex deep learning workflows require a lot of disjointed steps and slow-downs in productivity — Sridhar notes that disparate infrastructure components that have to be combined to create a holistic solution. The combination of AWS and Bitfusion allow a single, unified architecture that maximizes flexibility, cost-effectiveness, and data scientist and engineer productivity:
- Collect data from social media sources.
- Leverage a combination of data stores for polyglot data persistence.
- Seamlessly move through the phases of deep learning development… from prototyping, to large-scale training, to production inference.
- Scale up or down any aspect of the solution as data volumes fluctuate and as customer demands dictate.
Bitfusion Deep Learning AMIs make it much faster and easier to get started with deep learning and advanced data science projects. You can check them out in more detail on the AWS Marketplace using the links below. Each one comes with a 5 day free-trial, so spin them up and give them a try.
- Bitfusion Ubuntu 14 TensorFlow – Quick-start, deep learning AMI with Nvidia Drivers, Cuda 7.5 Toolkit, cuDNN 5.1, TensorFlow 0.10, TFLearn, TensorFlow Serving, TensorFlow TensorBoard, Jupyter and more
- Bitfusion Boost Ubuntu 14 Caffe – Quick-start, deep learning AMI with Nvidia Drivers, Cuda 7.5 Toolkit, cuDNN 5.1, Caffe, pyCaffe, and more — plus includes Bitfusion Boost™ for seamless horizontal GPU scalability
- Bitfusion Boost Ubuntu 14 Torch 7 – Quick-start, deep learning AMI with Nvidia Drivers, Cuda 7.5 Toolkit, cuDNN 5.1, Torch7, iTorch, Jupyter and more — plus includes Bitfusion Boost™ for seamless horizontal GPU scalability
- Bitfusion Ubuntu 14 Theano – Quick-start, deep learning AMI with Nvidia Drivers, Cuda 7.5 Toolkit, cuDNN 5.1, Theano 0.8.2, Keras 1.1.0, Lasagne 0.2, iPython 5, Jupyter and more
- Bitfusion Mobile Deep Learning Service – quick-start AMI with GPU Rest Engine and REST API Server for moving trained models and inference tasks to production — also includes Nvidia Drivers, Cuda 7.5 Toolkit, Caffe, and more
Interested in a more details on how Bitfusion, AWS, and Apposphere work together? Check out the deep-dive presentation on SlideShare.