In our research project, however, we were developing structured summaries of articles. While there have been quite a few improvements since 2.5 years ago when I was working on this project, this is still an unsolved problem. In addition, there is hardly any structure to the actual articles.
However, the problem space is enormous since you have limited structure to the summaries. In your favor you have data and the ability to train these models on over a million articles. In that task you're taking news articles and summarizing them into roughly a few sentences. The high-level overview: Take a task like the CNN news article summarization. What was your research on?īack at the Berkeley AI Research Lab, I was working on a gene ontology annotator project where we were summarizing PubMed articles with specific output parameters. You previously did some research using deep learning and NLP at UC Berkeley College of Engineering. AI that can dig through your day-to-day utterances, find useful information, and use that information to help you out. While we are solving the issue of documentation for physicians, we’re attempting a whole new wave of intelligence while doing it: ambient intelligence. This actually directly relates to one of my core motivations in founding DeepScribe. But when it comes to something like Jarvis, where it can actually learn and understand, filter, and pick up on important topics during another conversational exchange-that hadn't really been done before.
Particularly, what became apparent was, commands such as “Alexa do this,” “Alexa do that,” were pretty easy and accurate to do with the current state of technology. While they didn't work as seamlessly as Jarvis, I so badly wanted to make them work as Jarvis did. It was this concept of “AI by itself won't be as good as humans at most tasks but put a human and AI together and that combination will dominate.” Natural language processing is the most efficient way for this human/AI combination to happen.įrom then on, I was obsessed with Siri, Google Now, Alexa, and the others. Particularly, I found it fascinating how much faster a human was able to not only go through tasks but also go into an incredible level of depth into certain tasks and unveil certain information that they wouldn't have even known about if it weren't for this AI. If I remember correctly, Jarvis from “Iron Man” was the first thing that really attracted me to the world of natural language processing and AI. What was it that introduced and attracted you to AI and natural language processing? Akilesh Bapu is the Founder & CEO of DeepScribe, which uses natural language processing (NLP) and advanced deep learning to generate accurate, compliant, and secure notes of doctor-patient conversations.
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