Note Taking and a Walk Down Memory Lane
We’re taught from an early age to take notes. I believe the first time I recall starting to take notes was when I entered junior high. In fact, I can even recall being required to take a class on how to take notes – Roman numbers, indentation, etc. The act of taking notes is one of the few activities that has stood the test of time as I continued to do this not only in junior high, but throughout my education and it is something that I continue to do regularly today in my professional career. The reason why notes continue to be so prevalent in all of our lives is not because our teachers were so effective at influencing our young impressionable selves, but it’s because taking notes is an extremely useful practice. It allows us to capture the highlights of a class, meeting, or event and serves as a tool to help us recall information or re-enforce learning.
There are also downsides of notetaking. Often, the more focused a person is on capturing accurate notes, the more he or she misses out on being able to step back and really appreciate the big picture, and most importantly, misses out on being able to actively participate in the discussion. And then there’s the frustration of being able to efficiently locate the information when it comes time to reference your notes. What notepad or file did I use? Or recalling when a specific topic was discussed, but not being able to remember the event where that conversation took place to even begin searching for the notes.
Finally, technology is catching-up to what we have all longed for since our days of walking the halls of junior high school; our own personalized note taker. It’s with great pleasure that I’m excited to announce our investment into Voicera, whose virtual assistant, Eva, can attend, record and transcribe meetings in real-time, then uses a combination of AI and user generated highlights that can be shared with others.
Why Are We So Excited About This Investment?
We’ve all known how powerful data can be in enabling business outcomes. Several large tech companies have been built by tapping into data to provide better services or by enabling other companies to analyze and understand their own data – think Google, Facebook, Amazon, Splunk, among others. In many cases the more data a company has, the better its offering. The more this offering gets used, even more data is collected, and it becomes a seemingly virtuous cycle. Because data can be a powerful differentiator, businesses have aggressively sought to mine all accessible data sets to take advantage of this dynamic. However, I would argue that business conversations are one of the largest and highly business relevant data that remains virtually untapped.
This is where Voicera comes in. Eva takes these conversations and converts them to text where suddenly a new data set exists that can be indexed and searched. Not only is this useful to the individual user in being able to quickly search their own meeting database, but companies can start to glean new insights by aggregating these conversations across their organizations. Imagine an executive who wants to identify the engineers in his company who may also be machine learning experts because they regularly speak about this topic. Or another executive may want to understand what their customers are saying on sales calls about their closest competitor. These types of insights are just the tip of the iceberg of the rich data that is contained within business conversations.
The Holy Grail of Meeting Technology
Besides the transcription of meetings, one of the related pain points that we see in our own meeting ecosystem is the lack of effective methods for efficiently sharing these other past events. Today this is largely accomplished through the sharing of an audio recording; however, very few professionals have the time to listen to a recording and what they really desire is a concise meeting summary.
Summarization is a very technically challenging problem as most approaches contemplate enabling machines to performing Natural Language Generation (NLG), a technology which has yet to truly have been mastered. However, Voicera’s ability to allow users to identify the meeting highlights could be the basis for such a summary in which the actual language used in the meeting can serve as the summary itself eliminating the need for NLG. Over time, we believe Eva will be able to leverage machine learning to independently identify these important meeting moments and achieve the holy grail of meetings – the computer-generated meeting summary.
We look forward to working with Voicera as they continue on their journey to unlock the value of meetings, and would encourage anyone who is intrigued at the prospect of having Eva join their own conversations to sign-up for a free account here.
About the Author:
Donald Tucker leads Cisco’s acquisition and investment efforts related to the market for Collaboration products and services. Donald joined Cisco from Oracle via the acquisition of Responsys, and prior to that spent time at Jefferies & Co., Liberty Mutual Investments and Chevron in a variety of finance, investment and research roles.