Machine Learning Use Cases That Were Impossible Before

Below is the continuation of the transcript of a Webinar hosted by InetSoft on the topic of Enabling the Intelligent Enterprise with Machine Learning. The presenter is Abhishek Gupta, Product Manager at InetSoft.

Let's go to the other side of the business to speak about machine learning use cases that were impossible before. What if you could not just put marketing dollars in putting your brand or logo somewhere, what if you couldn't just sponsor a team or a particular venue or event but you could measure the impact and the outcome of that in real time.

Thanks to computer vision and full HD video processing we are able to find your logos, your products, your offerings in real time in commercial broadcast quality and video path and to determine accurate impact metrics so that you can measure what you pay for in terms of scholarship for advertising and make that available in near real time.

These are capabilities that have never been available on the market before, and this aims to revolutionize the way we do advertising impact metrics and return on advertising investment calculations. We look forward to deriving many additional visual and video base use cases that bring concrete business value to the enterprise.

It's interesting to see that machine learning touches basically every aspect of a business, whether it's sales or marketing, whether it's technology, whether it's operation or whether it's finance. Machine learning is and will be everywhere. You will see.

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Innovative Machine Learning

This brings us basically to the next topic about some of the popular and innovative machine learning technology and applications that are being implemented today.

What we see is that devices that have natural language processing provide interactive responses to people and to other devices, and some examples are Amazon Echo, Google Home, Netflix and recommendation engines.

I see this myself as a very interesting development of machine learning particularly the natural language recognition parts. They give us an interactive customizable experience that we've never seen before. What we see is also machine learning has enabled the popular digital assistants.

We see all the applications that you have, whether it's Apple's Siri or some other speech recognition applications. They are responsive – yeah they provide responsive tools also via your mobile. It's predicted that machine learning could, let's say make text and maybe GUIs basically really obsolete in the future, which is interesting development to follow.

What we see as well is that machine learning applications are altering and revolutionizing various industries whether we are talking about medical research, and whether it's diagnostics and healthcare, improving consumer applications in all different kinds of industries. For example, machine learning can provide healthcare personnel with real time information about the patient's care or making diagnostics and treatments much more accurate, and they can use augmented intelligence to advise the doctors.

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In the customer service industry we see that machine learning can help them to offer relevant fast personalized experiences, and we see some substantial changes in this as well. What we also see is machine learning can classify and categorize social media posts, so everything in the marketing domain. It enables companies to deliver higher quality customer experiences through all the channels that you're connecting with people from a company perspective.

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