More than 4.3 million videos are viewed every minute on YouTube and over 1.1 billion hours of video are watched per day on Facebook and Google. These are just some of the problems which have arisen due to the massive expansion of video use online. With the deluge of videos being uploaded and consumed, searching for and/or discovering content becomes harder and harder. YouTube is the closest thing to a search engine for video today, but it relies on the uploading user to properly catalog, tag and provide descriptions for each of the videos that they upload. Obviously, this will result in inconsistent cataloging. Yet, online video is everywhere and YouTube is no longer the only destination for online video.
Google, Bing and Yahoo search engines work by indexing the textual content of pages. These search engines have two major functions: crawling and building an index, and providing search users with a ranked list of the websites they've determined are the most relevant. Metadata must also be normalized and standardized if it is to be used for better search and discovery. Because humans are biased with their own perspectives, each human looking at the same video will come up with different metadata information and tags for that video. One of the most challenging problems in the video industry is to ensure video content are safe for our children to watch and for brands to advertise on through access to metadata. Another challenging problem within the video industry is that least 80% of content on the Internet is accessible in only one of 10 top languages. Most videos on the internet are only accessible in a single language, usually English.
ArtificialIntelligence (AI) is defined as “the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI also requires a computational infrastructure capable of processing large amounts of data on Computing Processing Units (CPUs) or Graphics Processing Units (GPUs). Because of the amount of data, no one CPU or GPU can typically process all the data so the data must be broken up and distributed to multiple CPUs or GPUs for processing.
Online video is growing exponentially as the ability to shoot and capture video becomes commoditized and democratized with the pervasive adoption of smartphones and 4G mobile access globally. everything we do online including online video as well as web traffic, users, user data, online advertising, search and social networking is dominated.
Our solution known as AIVON is a decentralized, open-source blockchain protocol and ecosystem being built on a consensus network of ArtificialIntelligence (AI) computing. AIVON believes that Internet and services on the Internet must be decentralized or else there is too much power in too few powerful hands. AIVON focuses on decentralizing and democratizing online video, giving power back to Internet users. Specialized AI algorithms will be deployed on AI nodes, of which the CPU and GPU resources can be used to scan media files, generate the enhanced metadata including time-coded tags, classification, categories, transcripts and translations, and an index of the video objects. AIVON nodes will record their metadata in JSON format anchored to the Ethereum blockchain. Most of the metadata will not be stored directly in the blockchain, but linked to it using the EIDR identifier.
ArtificialIntelligenceVideoOpenNetwork (AIVON) is a decentralized, open-source blockchain protocol and ecosystem built on a consensus network of Artificial Intelligence (AI) computing resources and a community of human experts, used to generate normalized and enhanced metadata for video content. Developers can build Decentralized Video Applications (DApps) on top of the AIVON protocol, the first of which will be the first decentralized Open Video Search Engine which AIVON will build. Platform participants can either run AI nodes or provide expertise and be rewarded with AVO Tokens.
Until recently, it was very difficult for a computer to tell apart a cat and a tiger or recognize a human's face, whereas a human can perform these tasks almost effortlessly. Fortunately, the field of Artificial Intelligence (AI) and Machine Learning (ML) has made tremendous progress in the last few years to become better at understanding images. AIVON will also leverage some of the state-of-art open source machine learning frameworks such as Tensorflow, Caffe, Torch and Darknet, combined with our existing data sets. This approach will ensure that AIVON AI software will be continuously upgraded with the latest technique and technologies especially given that the field is advancing by leap and bound.
Aside from assigning a content safety index, AI algorithms will be used to capture various types of metadata. The 3 most common types of metadata used for search optimization are: source, derived, and added metadata or tagging. Despite rapid advancement in the field, AI is not perfect; humans continue to play two important roles in the process. AIVON will reward these crowdsourced human experts with tokens based on their accuracy and productivity. This approach not only provides a larger pool of human experts to choose from, the diversity of decision making process and the use of a consensus network can eventually lead to better results in AI accuracy. AIVON will pose to its human expert questions that are similar to image recognition reCaptcha, meaning a human expert can be offered a random number of celebrity images and be asked to select the ones that belong to George Clooney.
AIVON will be part of a larger content ecosystem consisting of content producers, advertisers and streaming media service providers. In the illustration below, we can see how our AIVON platform enables collaboration and cooperation. The AIVON community will provide an open, distributed and crowd-sourced community for transcription and translation. As mentioned, iVideoSmart already has a complete video content platform that allows publishers to reach out to buyers and allows advertisers to purchase ad placements. So, this can be thought of as a ‘front-end’ for AIVON blockchain protocol and ecosystem. AIVON is built on a standard Ethereum blockchain as well as Plasma Network.
All the video metadata will be anchored to Ethereum blockchain and Decentralized Applications (DApps) can easily access the data and either spend or earn AVO token. AVO Token is implemented as an ERC20 token on Ethereum mainnet while AIVON is implemented on a Plasma Network. We chose the Ethereum chain because of its robustness, great ecosystem of DApps, security and strong immutability features. Smart contracts on Ethereum mainnet acts as a trustless medium to bring AVO Token into AIVON Plasma network from Ethereum mainnet and vice versa. Transactions involving AVO Token that take place in AIVON Plasma chain are signed by validators based on a consensus algorithm. There will be independent nodes and blockchain in AIVON Plasma network, independent of Ethereum.
Incentivizing individuals who make available their computing resources for AI processing, or who apply their expertise to tagging, verification, transcription and translation is the primary purpose of the token. AIVON is preparing to launch a token sale in November 2018 to fund the development, operations and marketing of the AIVON protocol and ecosystem. The adoption and use of the AVO Token will benefit from the existing user base of over 500 million addressable users globally that already use an IVS-powered online video platform. Upon launch, IVS platform users will all be able to offer their computing resources or human expertise and be able to use AVO Tokens on IVS-powered platforms.
The token shall not and cannot be considered as shares or securities in any jurisdiction as they do not give any rights to dividends, interests, profits or to participate in the general meeting of the company. The token shall not and cannot be considered as shares or securities in any jurisdiction as they do not give any rights to dividends, interests, profits or to participate in the general meeting of the company. Our token sale for AVO token is scheduled for November 2018. Following are some of the key features of the token sale, distribution and use of proceeds.
The AVO tokens allocated to the advisors, early backers, founders and other team members as aforesaid will be distributed to each of them in such instalment intervals and on such terms as is necessary to incentivize them to remain committed to the AVION platform. A total of 400 million AVO tokens will be released in our initial token generation event. Thereafter, we will issue block rewards to incentivize AI nodes and validators to dedicate resources to the platform.
Every transaction must pay transaction fee to validator as part of block reward. Demand for AIVON token will increase as AIVON transaction volume increases. Requester must have AIVON token to request job execution. Demand for AIVON token will increase as number and scale of job requests increase. All participants must put down deposit (Staking) in AIVON token to gain the right to participate and be selected. To level up and qualify HE nodes, we envisage DApps that provide systematic online course to train and test humans on the high skilled tasks. 400,000,000 AIVON tokens will be created at Token Generation Event.
Let’s Join Now
For Information detail visit link in below :
Website : https://aivon.io/?utm_source=bounty
Whitepaper : https://aivon.io/download-whitepaper/
Telegram : http://t.me/aivonio
Facebook : http://www.facebook.com/aivonio
Twitter : http://www.twitter.com/aivonio
Medium : https://medium.com/@aivonio
My link Bitcointalk : https://bitcointalk.org/index.php?action=profile;u=1305012
My ETH Adress : 0xCC028E8465c39c8B5D250431c82239dc7EE48a6d
My Telegram : https://t.me/robiawal
My Telegram : https://t.me/robiawal
Tag : #Aivon
#aivonico #tokensale #AI #Blockchain #aivonio
0 komentar: