YOUR EYE ON INNOVATIVE MACHINE LEARNING SOLVING REAL WORLD PROBLEMS
Azafran Capital Partners
INSIGHTS Data Evolution and Revolution Sound and imagery - our first means of communicating and recording history, from the oldest cave art dating back over 60K years to over 100K years when the instrument of modern speech, voice, acoustics and all that comes with it began to form. Fast forward to the past decade and the role of these two mechanisms had not advanced much beyond the simple dimensions we had been using them, as a call and response, communications, recording, art, music, etc. All wonderful and amazing, these primary elements of what makes and defines us as a species. Now, with the enormous advances in data, machine learning, and deep learning, we are beginning to unlock the next dimension of voice, acoustics and imagery. Over the past decades, we have been recording, scanning, storing, amassing huge troves of digital data which are now being put to use by innovative entrepreneurs and companies as they create applications, platforms and solutions to some of life’s most vexing and intractable problems.
issue six FOCUS At Azafran Capital Partners, we invest in companies using Deep Learning and Machine Learning, emphasizing voice, acoustics and imagery datasets in the health, wellness, robotics/sensory and enterprise spaces - a $1 Trillion market by 2025 (see Market Predictions on following page). In the following pages we visit trends and predictions focused on data and datasets through the lens of voice, acoustics and imagery as the inputs to solutions built on deep and machine learning solving real world problems.
Think of all the data Facebook and others have collected, hospital systems, insurance companies, governments, clinical trials but until the last 10 years we did not have the tools to “mine” this data. These data sources provide incredible volume of baseline information for startups to train their models and train their algorithms. Starting with unformatted data (See page 3 for piece on Data Lakes) - really a bunch of noise - and then you run models against the sounds, against the imagery and then you begin to see patterns emerge. It’s all about benchmarking the data and looking for patterns. When you look at the mountains of data that entities of every size have been saving, we are now using it to create algorithmic models to solve problems that we could not imagine solving before the marriage of data, deep learning and machine learning. Once solutions begin to appear, problems get solved via deep learning and machine learning engines are applied as the datastores are constructed and organized. We now can correlate patterns, trends and garner data from these mechanisms that was previously not possible. Now, that’s a revolution. Over the rest of this ISSUE of INSIGHTS, we will explore dynamics and use cases related to this huge new opportunity and reality. Companies already cracking the code, from healthcare to safety, security and enterprise applications - all with consequences and improvements for humanity that we could not imagine even ten years ago, and at the core, we focus on data + voice and acoustics + imagery + machine and deep learning, a $1 Trillion-plus opportunity (see Market Predictions on next Page) within the next 5-7 years, and the core of Azafran’s Investment Thesis.
One of the significant challenges that the current research community is trying to address is how to equip the machines to recognize, process, and infer decisions from sounds and visuals. A lot of technologies are powering the research works. However, machine learning (ML) is a promising technology that is expected to impart the highest value to a range of interactive real-world applications such as image and speech recognition. The repetitive style of ML is essential for interactive models as they can adapt independently when exposed to new data sets. ML can easily apply knowledge and experience from an extensive collection of data repositories to allow face recognition, speech recognition, and much more.” - Future of Image and Speech Recognition with Machine Learning | CIOReview | July 9, 2019
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Volume 1 Issue 6 - Page One