Inventing
What’s Next.
An open source Python toolkit for exploring and using the capabilities of in-memory computing devices in the context of artificial intelligence.
A large-scale dataset with approximately 14 million code samples, each of which is an intended solution to one of 4000 coding problems. Rich annotation enables research in code search, code completion, code-code translation, and myriad other use cases.
The technologies underlying Project Debater available as cloud services. Includes core natural language understanding capabilities, argument mining, and narrative generation.
This toolkit is a Linux-based Docker container that demonstrates computing on encrypted data without decrypting it. The toolkit ships with two demos including a fully encrypted machine learning inference with a neural network and a privacy-preserving key-value search.
