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AWS re:Invent 2019 – my experience and takeaways

It was a fantastic opportunity to not only present what we at Trinity Audio do and are striving to do but to also get the inside scoop on various emerging technologies that will soon take place in the respective tech stacks of businesses worldwide.

With all the accomplishments voice assistants and smart speakers made, the industry is still missing some sort of platform where you can buy ads or upload them programmatically, not to mention buy audio traffic.

On top of that, while creating audio content is considered easier than creating video content, it’s still more demanding than typing out a few coherent sentences.

Therefore, any kind of AI-powered TTS solution is highly appreciated and sought after on the content creation side, regardless if it’s a large publisher or a small individual blogger.

There are different formats that are relevant for specific needs, such as the Newscaster reading style tailored to news narration or the Conversational speaking style for a wide variety of use cases.

The artificial intelligence behind these services is getting an inch by inch closer to the real thing, which is super important because it drives up the human tolerance for synthesized/mechanical voices.

Moving away from all the robust and largely unnecessary legacy systems is a relief of sorts as it means moving away from skills that are no longer needed.

The message didn’t particularly resonate with me at that moment, not until after my second speaking session when someone actually drew a parallel between that modernization trend and the current status of digital audio advances, and in particular –

people were really digging our presentations but more importantly, what we are doing as our solution effectively addresses and answers demands of all sides of the ecosystem: publishers and content creators, advertisers, and users.

The vast majority of people present looked at me like I escaped from a mental institution when I mentioned my vision of voice technology and audio content.

The shift that started over a year ago has produced an increasing number of people from the “holy triangle” who want to engage in some sort of audio/voice solution.

AWS Industrial Software at ReInvent 2019

Las Vegas was packed December 2-6 due to the influx of more than 65,000 attendees for AWS ReInvent 2019, the marquee event for Amazon Web Services (AWS) at which AWS industrial software was displayed.

CEO Andy Jassy spent about 2 ½ hours in his Tuesday keynote, with some periodic support from others of course, highlighting a litany of releases that included new AWS industrial software services.

 These modern capabilities are at the heart of industrial transformation, which leverages software to support new and more agile business processes, services, and models that companies will use to reinvent how they operate and serve customers.

As the visual below suggests, it extends SiteWise’s IIoT capability beyond modeling and storage into fully-managed web application visualization and near real-time and historical data interaction.

 This bottom layer provides tools for those practitioners who want to experiment with algorithms and other building blocks for developing machine learning.  The next layer consists of machine learning services, which are designed for machine learning developers, and tilt toward various types of API shortcuts for building, training, and deploying machine learning.

 What it highlights is the need for those serious about AI to consider how they will align resources to use machine learning—in an industrial setting, those with the competitively differentiating knowledge and skills likely float more toward the top of the machine learning stack.

 If you consider the AI services available to them at that top layer—vision, chatbots, forecasting and the like—more will be necessary to deliver new means of competitive differentiation, the real goal of digital transformation, from the unique skills and knowledge inherent in these individuals.

 That’s not a knock on AWS by any stretch—it’s just that their stack points out that hybrid skills and multi-disciplinary work groups will be required to harness digital transformation as a competitive weapon.

An example is Amazon SageMaker CodeGuru, which uses machine learning to automate the review, correction, and improvement of code.  Already, business process system providers are integrating machine learning into supply chain, resource planning, work management, and a host of other areas.

 As hyperscalers, like AWS, continue to put their considerable resources to developing software, hardware, and ecosystems, it’s putting immense pressure on established industrial solution providers.

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