Home Ico Review Mykrosystem Ico Review: OPEN SOURCE VOICE INTEGRATION




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About Mykrosystem

The Mykrosystem is built of myriad loosely connected Mykrocosms, each of which is a self-encouraging system of software development, data aggregation, research and service delivery. The Myke trade token is exchanged for services and work performed, which benefits the Mykrocosm. Transactions involving this token are recorded on a central blockchain, providing the transparency and immutability required for trust.

Basic Information

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Know Your CustomerYes
Restricted countriesUnited States of America
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Mycroft AI

As with many open source projects, Mycroft began as a solution to a problem. In 2015, Joshua Montgomery wanted to install a voice assistant similar to Iron Man’s JARVIS at his makerspace, but no suitable platform could be found outside of the movies. When faced with a tough problem, Joshua did what he does best: assemble a team to solve it. Excitement grew as the team realized the potential of what they were building. A successful Kickstarter campaign proved the public’s interest in this new type of device and marked the launch of the open source Mycroft AI project to build an AI for Everyone. The project attracted collaborators from around the world, including Steve Penrod who had been building his own voice assistant since 2014, and Sean Fitzgerald who was on the original teams behind both Apple’s Siri and Amazon’s Alexa. Following their second successful Kickstarter campaign, Mycroft’s global team has grown to a staff of twenty, with hundreds of contributors and tens of thousands of users assembled across all seven continents.

The Paradox of Knowledge

Machine Learning has become the most active field in AI research. The deep learning variant, in particular, operates by analyzing large swaths of data to reveal hidden knowledge.6 The analysis is computationally expensive, however, so the limits of knowledge are bound by time and data. Obtaining hoards of varying data is not enough; it must be “tagged” with the appropriate metadata. This is the greatest challenge faced by AI researchers. Most machine learning systems create a feedback loop, collecting more data as they are used, which is then used to make the system perform better. Thus the first paradox: it takes data to build the system that collects more data. Mozilla faced this paradox when they began the DeepSpeech system. In order to train an effective voice transcription tool, they needed the kinds of voices it would ultimately be hearing.

The Paradox of Privacy

The Android voicemail recordings are an example of the depth of data aggregation occurring in the largest technology companies of today. Social networks collect intimate demographic details which are combined with ‘tracking pixels’, ad-viewing location and history, GPS coordinates and more, to produce massive stores of information about individuals. The never before the imaginable scale of this has recently dawned on the consumer, bringing concerns of personal privacy to the popular consciousness. Legislation like GDPR has emerged in an attempt to curb these fears. Now the very personalization which made the technology compelling is in peril; a paradox exists that threatens the core business of these aggregators. Legislative cures are well-intentioned but ultimately flawed. Rigid rules to stop abuse by a few overreaching companies threaten to disrupt the entire internet.

The Paradox of Trust

Privacy concerns manifest the fundamental issue of trust. Initially, an organization such as Facebook is trusted by its users who gladly concede their data because of the value added by the new service. Adding capabilities expands utility which leads to further success and users, acquiring more personal information in the process. With the aggregation of information, control escapes the individual and ultimately the organization loses the trust of their users. Thus the paradox: trust leads to success, which leads to power, which leads to distrust. The same treacherous paradox undermines the foundation anchoring a collaborative project to its participants. As progress demands more effort, it becomes ever more prone to centralization. Recourse is not afforded to invested developers who have no right of determination regarding operations in the presence of a single director. It is an eventuality either the man or machine will fail, breaking the trustful relationship between the developers and the project.

The Paradox of Value

Open source development has produced works of tremendous capability, utility, efficiency, and scalability. In other words, these works have incredible value. Yet by the very design of the open source system, there is no way to return any of the economic gains to those who created the open source software. This immense value is paradoxically created for free. Donating time and effort to a cause is certainly noble and should not to be dismissed. However, a system which relies exclusively on the charity of others is tenuous. It is not uncommon for projects to be abandoned – or rarely updated – because of the demands of the core contributor’s “day job”. Major 9 open source projects get around this by forming foundations, but smaller efforts have no easy method to allow users to share benefits or community appreciation and thereby encourage continued development.

A New Data Economy

The four paradoxes cannot be solved in today’s paradigm of data ownership, as these problems are inherent to the structure of our current data economy. And while these structures reflect techniques which were considered the state of the art when created, a radically new technology has since emerged. Blockchain technology fundamentally changes assumptions of record keeping and security. In other words, the paradigm of data protection by concealment within servers of private organizations is no longer the only option to secure privacy. In fact, it is no longer the best option.

The Mycroft Mykrocosm

The first Mykrocosm encompasses the Mycroft voice assistant. Developers build the core software and skills. The Mark II and other devices run the software, generating valuable voice data in the process. That voice data can be aggregated in the Mycroft Open Dataset Collective to share with the researchers at Mozilla. Mozilla can use this data to improve the DeepSpeech speech-to-text models, which can be run as a service for Mark II users. Myke cycles among developers sharing code, users consuming services, researchers utilizing datasets and service providers offering their APIs. Each piece supports the other, simultaneously producing technology, such as DeepSpeech, valuable outside the Mykrosystem.

Joshua Montgomery – CEO
Steve Penrod – CTO
Nate Tomasi – COO
Derick Schweppe – CDO

Also Read – Click Here for Read All ICO Review

Quote This article is writing on 28 June 2018 based on information available online & news portal. If you feel it’s outdated or incorrect, please write here to update it. Mail us: support@coinworldstory.com Or Whatsapp Us- +13098896258


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