AI-Powered Journalism: CrunchLetter is Here
The team behind CrunchLetter, a project developed at the TechCrunch Disrupt SF Hackathon, has created an AI system capable of automating the creation of venture capital news summaries. Utilizing Google’s Tensor Flow, CrunchLetter leverages unsupervised machine learning to analyze CrunchBase data and articles from prominent VC publications. This allows the system to generate rudimentary summaries of funding rounds, including the amount raised, participating VCs, and details about the funded company’s products or services.
The project’s potential lies in its ability to generalize, going beyond simple information parsing to generate analyses with vetted character and word models. The creators envision a future where AI can generate longer, more complex funding round summaries that incorporate market competitor analysis.
The team trained their framework using the TechCrunch and WordPress APIs, processing over 15,000 articles during the hackathon. While the current system is still in its early stages, the creators believe that with more time, data, and additional recurrent neural networks, CrunchLetter can evolve into a sophisticated tool for automating VC news reporting.
