MACHINE GENETICS: THE UNREALIZED POTENTIAL OF THE WORLD
Open Strategic White Paper by John Alda. April 2018.
THE PROBLEM: The Demand for Instantly Recognizable DataThe precise content of every image, video and website uploaded to the web should automatically be recognized by browsers, applications, devices, routers, robots and aircraft. Newly uploaded web media should also self-organize into content similar networks, globally. This automatic networking technology would save Bing, Google, Amazon, Netflix and eBay millions each year in programming and development and enable the World Wide Web to become a self-organizing search engine. As Machine Genetics is adopted globally, vast hidden and unrealized information networks will be revealed.
SYNOPSIS: Machine Genetics is Required for Machine Learning and Machine IntelligenceTraditionally, images, videos and documents [media] have been designed for cpu efficiency, network speed, compression and resolution. Given the diverse expansion of services on the web and commercial needs of users, media must now be designed for copyright, commerce and communication—networking. Media should be automatically pre-programmed for interaction with search and advertising engines at the source of creation. These specific advancements mark a new period of industrial design (for utility and mass consumer use) merging with design engineering (file format design for computer applications and cameras). This thesis introduces a new form of interactive genetic barcoding (Machine Genetics) that pre-programs media for search, advertising, commerce and networking. Genetically imprinting media with machine intelligence will enable phones, browsers, word processors and search engines to immediately recognize the exact nature of information. The technology allows the creation of automatic networks bringing true interactivity to the World Wide Web. This is a fundamental step toward redesigning file formats (jpg, png, mp4, docx) for automatic networking, instant commerce and global self-organization. Robust investments are now being made in Machine Learning to achieve Machine Intelligence: the missing component is Machine Genetics—a method of designing information for global networking. Machine Genetics is an automatic networking technology that powers GI VIBES: a breakthrough user and business platform.
INTRODUCTION: Machine Genetics ⊃ Machine Intelligence ⊃ Machine Learning.In the immediate future, the web will become a self-organizing search engine. Machine genetic sequences (interactive genetic barcodes) will replace vast amounts of computer code. People, products and information will automatically form frictionless social and commercial networks. Newly uploaded images, videos and websites will join similarity [genetic] networks faster than search engines—bypassing search altogether. Images, videos and documents will be pre-programmed with detailed instructions [genetic sequences] for networking, copyright licensing, advertising, commerce and automatic indexing. The web will become inherently organized and a single genetic sequence encoded within an image or video will hold an ontology of the entire web. Web users will have total control over their advertising, privacy and copyright. The World Wide Web will no longer be held together by hyperlinks, but transform into an interactive media network of similar and highly relevant content—easily controlled and navigated by web users. Impetus: Every image, video, document and website uploaded to the web is a missed opportunity to network with similar content. Media sits in isolation on websites waiting to be found by search engines. The World Wide Web is linked, not networked—relying on hyperlinks to connect content, but media should network independently. Developers write enormous amounts of code to customize websites for search and advertising engines. Media and websites are severely deficient of metadata that help search engines determine the nature of content. Even more code is written for search engines to locate and parse HTML on websites all over the world. How? It is a simple procedure to redesign a search engine to act as a barcode scanner, instead of parsing through websites (HTML) all over the world. This modified engine scans an interactive barcode embedded within each piece of media (or independent of the media itself), revealing detailed Internet instructions governing copyright, commerce and communication. The same technology can be used by phones, browsers, operating systems and word processors to precisely detect and interpret content. The result: Documents, media and websites uploaded to the web automatically join content (similarity) networks, bypassing search engines altogether. Developers benefit by writing less code since instructions embedded in the barcode. This sets the stage for new image and file formats with networking ability, thereby transforming the web into a global interactive media network. Use Cases: Machine Genetics will have wide ranging impacts on information systems, networks and Internet appliances. A biotech firm will be able to automatically network patent information, websites, publications and internal documents to reveal new intersections of information. Developers will be able to send robots precise human movement abilities and computational logic through genetic sequences embedded in images and other forms of data. Internet of Things appliances will become more efficient at making logic based decisions. Mobile phones, word processors, browsers and operating systems will be able to interpret photographs and prevent computer viruses. The World Wide Web will become a self-organizing search engine and true interactive network. From the product design standpoint, the web is boiling over with missed opportunities. The following sections highlight deficiencies within the web’s design and products within broader the technology sector.
Major Missed Opportunities: The Architecture of the Web, User PrivacyWe just passed the 29th birthday of the most successful information model ever created: The World Wide Web. Based on a simple premise of linked pages comprised of text and media, its applications and permutations appear to be endless. However, the web is not just a product, but a vital utility that must be advanced to meet the requirements of the current environment. Search engines are still executing processes from the machine age, having to manually find websites all around the world. The websites are copied to servers which then employ blunt mechanical algorithms to decipher raw text and static file formats. Artificial intelligence does not exist in any real sense: Ask your phone to read the news, share photos with a friend or navigate an email box and the limitations become abundantly clear. Our interaction with (all) software includes operating systems that crash, web browsers that stall, need for constant updates and systems that cannot anticipate our productivity needs. Tech companies are in an era of blatant copycat behavior by marketing small incremental technologies and gimmicks. Somehow, tech firms fail to realize what a user demands in product design: having a smartphone assistant read the news, automate commerce, share a photo, block spam, kill viruses before infection, make scheduling decisions, enforce automatic copyright protection and ensure industrial strength privacy. We continually dumb ourselves down to use search engines by translating complex questions into overly simplified keyword searches—searches that turn into messy, disorganized lists and postage stamp advertising with little compelling reasons to click. Some keyword ads are trojan horses encapsulating viruses and social engineering scams, for example: “Your computer is infected with a virus, please call Microsoft.” It’s a graphical trick within the browser that has nothing to do with Microsoft or your computer, but the user believes it is true. This is a problem that should not exist in 2019 given the state of engineering and wealth of technology firms. Keyword searches interact with the browser cookie to create a fractured user profile—based on clicks that do not represent a user’s authentic personal taste. Tech companies earn billions in keyword ad revenue from this user surveillance model completely missing the point of customer value and rapport. Users value trust. Trust generates enormous revenue. User surveillance is tolerated, but not appreciated. New companies (meaning new brands) are beholden to the utter limitation of keyword advertising and anyone can test this vulnerability. For example, try to search for bloomingdales.com, without typing the keyword “Bloomingdales.” Which keywords will you enter into the search engine? Sofa or furniture or something else? In turn, Bloomingdales is trying to figure out which keywords a user will type into a search engine; keywords that will lead you to their brand. It’s not the best way to connect brands with potential customers. But it’s not just brands, it's people's livelihood. Keyword search technology has metastasized into employment recruiting where specific keywords on a resume must be an exact match before reviewed by a human. We live inside a deeply fragmented web where messaging, email, social media, storage, productivity, copyright licensing and advertising all exist on separate platforms with crude links to one another, rather than inherent integration. Their separation of function and platform interoperability prohibit the user from enjoying a truly rich and efficient web experience. Platform specific features are further hindered by a range of browsers that support different coding standards causing some services to function improperly or inconsistently; and, developers are under constant pressure to learn new platform technologies (API’s). The power of the web seems limitless, but it’s an illusion. The web has brought so many people, technologies and ideas together; still however, the overwhelming majority of web users do not have the coding skills to build a website. Users don’t have a firm grasp of how their information is being captured and propagated in the background among firms, governments and criminal hackers. Network and computer security is not well understood even by software engineers, unless they specialize in the subfield. Why is creating and optimizing a search engine so difficult? The answer: Images, videos, documents and websites are not designed or pre-programmed for search, advertising, copyright, commerce and networking. Metadata is essentially fallacy. Website metadata is a simple line of keywords that barely describe the content of a webpage. Image formats such as JPEG and PNG are designed for image quality and compression, not networking. Image metadata relates to size, technical data and sometimes GPS location, but not instructions related to subject matter or copyright. Video formats are even worse in this regard. Furthermore, most images on websites don’t possess a filename (e.g. 110002.jpg) that is conducive to a search engine’s ability to categorize the image (a better naming convention e.g. george_clooney.png). Government agencies and hackers don’t really deal with metadata; they gain full access to hard drives, intercept emails en route and subsequently misuse the term metadata in media for a layperson audience. The Fulcrum: At the center of the web universe is a deeply unappreciated web user. She conducts web searches, clicks through sites, uploads photos, shares videos, completes surveys; and yet, her thoughts, images and copyright are not hers. Her digital life is owned, operated and purveyed by third party platforms. Without the web user, there is no web. Wikipedia contributors, Craigslist buyers, eBay transactions, social media posts, personal blogs and endless personal videos comprise nearly all of the web’s content and activity. The web user not only lacks privacy, but control over their own digital lives. Every user should have inherent copyright that can be implemented easily at the root level: meaning within the architecture of a photo, video, document, email or user account. Many of these problems can easily be solved through solid information design and by companies that value the real demands of web users. Commerce on the web remains less efficient than the pony express, and light years from precognition. If the web user wants to buy, sell or market a product it all comes back to a “search.” The buyer and seller are forced to meet at sites such as eBay or Craigslist, but not without the irritation of repeated searches using different keywords and navigating the spam of daily incessant reposts. What if the buyer or seller is in Japan and does not use Craigslist? The web should be able to bring these people together automatically using the innate connectivity of the web. In another application of commerce, the photographer markets her photos on social media, acquires thousands of “likes,” but can’t license or transact on the same platform. She stores her photos in the cloud drive, but can’t market, transact or protect copyright from the cloud. She places her photo on Getty.com, which is back to the search paradigm of Craigslist and eBay: Her potential buyers have to know that Getty.com exists and then use the right combination of keywords to find her work. What web users really want is for buyers and sellers with matching interests to be paired automatically with very little effort or repeated searches.
and Web Services Fragmentation
The Form Factor of InformationFar-and-away, the most profound opportunity cost of the World Wide Web is information design: It’s hyperlinked and/or inert—fundamentally non-networkable. Every website created, every photo and video uploaded is a profound missed opportunity to network information. Newly uploaded websites, documents, photos and videos relate to thousands, perhaps millions of other media and websites based on their content and subject matter; yet, they sit in isolation waiting to be found by search engines. Developers spend hours writing metadata, whether in HTML or XML or RDF, hoping to be recognized by search engines. Photographers spend hours configuring metadata in Adobe Lightroom and Photoshop for image licensing that can be easily removed or ignored. For all this effort, web content remains in isolation without the monopoly of search. Instead, newly uploaded content of interest should go directly to users globally, bypassing search engines altogether.
Networkable Media is Inherently Obvious and Thoughtful Product DesignIt is abundantly obvious that images, videos, documents and websites should be able to form automatic hereditary (similarity) networks. A cnn.com article, an imdb.com page, a Guardian article, a photo on Vanity Fair, all related to George Clooney should form a network automatically. New George Clooney media that is uploaded to the web should join the same network. The network becomes a set of search engine results automatically—without the background labor of a search engine—which is to locate websites, decipher text and code, index a group of sites and map them to the keywords George Clooney. Networks of products can easily be mapped to people based on similarity of taste. Videos and content can be networked to form a recommendation engine. Media can be networked for the purpose of controlling copyright. Network intersections create ontologies such as correlations between George Clooney, Brad Pitt and their films. As new media are uploaded worldwide, they join networks bypassing search altogether. Simple network interfaces, whether embedded in apps, browsers or operating systems, make it easy to navigate information and sell products globally. As media in a given network change, the other networks adapt to form new relationships, thereby updating all other networks around the world. An example is a new film where George Clooney acts with Keanu Reeves for the first time. Articles will be authored and posted to the web, images will be taken of them together and an imdb.com page will be created. As media are uploaded, George and Keanu form a new network intersection and their respective networks have adapted. A scan of the wiki page related to an avocado might result in dozens of network intersections (e.g. California, United Kingdom, Mexico, Mesolithic, Florentine Codex). The web has billions of unrealized networks just waiting to be discovered. Hereditary networks are held together by genetic sequences (scannable genetic barcodes) that contain detailed instructions for copyright, commerce and communication. The short, simple sequences eradicate vast amounts of code writing for advertising and metadata. The sequence itself is a powerful form of information compression and can be added to the header of a document, JPG, PNG or PDF. As these hereditary networks of people, products and information intersect and evolve, the web becomes an automatic, self-organizing search engine. People share information that will pair automatically with interested parties globally. Companies will share information directly with customers who are interested in those products or services. Copyright holders will be able to revoke content in networks far and a wide. Images, videos an documents will communicate independently. A series of streamlined genetic sequences will replace the present voluminous amount of computer code. Security and encryption will be implemented at the root level—within images, videos and documents. Hereditary browsers, apps and operating systems will offer users unparalleled encrypted communication and interaction with hereditary media. Information navigation and privacy will be seamless. The web will be decentralized from the search and social media monopolies. Similar and relevant information will constantly network and evolve into a self-organizing ontology. The web will transcend into a pure interactive global heredity network: Genetic Internet, a genetically networked Internet.
ConclusionThe World Wide Web is the greatest information model ever created. The World Wide Web is linked, not networked, representing unrealized network potential. The form factor of information is the root limitation of copyright, commerce, security and global communication. Information (document, photo, etc.) has historically been designed to accommodate the needs of the computer processor, memory and network speed. Information must now be designed as a product—with thoughtful consideration for the needs of human interactions and trade. Instruction-rich hereditary information transforms the web into an interactive network. Networkable media is essential for an efficient global network.
Appendix A and BThe attached appendices provide a linear representation of this text.
About the AuthorJohn Alda is the founder and inventor of Hereditary Internet (Genetic Internet) and Genetic Internet VIBES. Prior to Genetic Internet, John was a systems engineer at Netscape and Internet applications engineer at Powersoft/Sybase. He founded and led a technology company providing technical strategy for Hologic, Thomson Financial, Allmerica Financial, McCann Erickson and Oxygen Media. John studied finance at Northeastern University and graduated summa cum laude with a BS in Design. He pursued a Master of Design at Northeastern University’s School of Architecture. GI VIBES is a cross-functional Internet system that seamlessly combines copyright, commerce, networking messaging, licensing, user privacy and gaming on a single platform. GI VIBES has embedded game mechanics, cash rewards and positive behavior incentives built into every feature, from messaging to commerce. Automatic Networking: The underlying technology of GI VIBES is a networking engine, Machine Genetics, that automatically networks people, products and information. Users can easily create a personal search engine, sell products, manage copyright and network the World Wide Web through a simple GI VIBES app and browser platform.
Appendix Representing Problem and Solution Domains
Problem Domain: The World Wide Web1 The World Wide Web is linked, not networked.
1.1 The World Wide Web is text-based: comprised of HTML and hyperlinks.
1.2 HTML Hyperlinks link pages and media from one to another.
1.3 Search engines are primarily text-based.
1.4 The primary role of a search engine is to resolve keyword searches.
1.5 To provide search results, engines must locate, decipher and index millions of websites.
1.6 Search engine results are not networked.
1.7 Keyword advertising is based on keyword (text) searches.
2 The World Wide Web is comprised of media displayed on linked pages.
2.1 Media: Images, videos, documents and websites.
2.2 Media are not-preprogrammed to interact with search, advertising or social media.
2.3 Media can’t talk, communicate or automatically network.
2.4 Media usually contain very little information about the subject matter, even with metadata.
2.5 Media do not contain information about advertising, networking or communication.
2.6 Similar Media: Two images, videos or documents of the same subject matter (e.g. actress Diane Lane) cannot automatically network or communicate.
2.7 Similar Websites: Two websites of the same subject matter are not networked or communicating.
2.8 Image search engines are far less effective than text-based engines.
3. Conclusion3.1 The World Wide Web turned 29 in March of 2018.
3.2 Information (media) is not-preprogrammed to interact with search, advertising or social media.
3.3 Information can’t talk, communicate, automatically network or self-organize.
3.4 When information acquires these capabilities, it will transform the nature of the web, information design and web commerce.
Solution Domain: Genetic Internet1. Machine Genetics
1.1 Information is automatically sequenced (images, videos, documents, websites).
1.2 Sequenced information automatically acquires a unique genome.
1.3 Information is automatically networked by the virtual Genetic Processor.
1.4 The virtual Genetic Processor networks and mutates millions of genomes globally.
1.5 Global Genetic Network : Genetic Internet.
1.6 Genetic App is a web, mobile platform, browser or operating system.
1.7 Genetic App allows users to network people, products and information—as well as the web, and the ability to create their own search engines.
2. Automatic Sequencing and Networking: Use Cases.
2.1 Users create image, video or document in phone and media is automatic sequenced, joins a network and becomes a search engine.
2.2 Users upload a product or service listing and media is automatic sequenced, joins a network and goes directly to potential buyers.
2.3 A User uploads an image for licensing. The image is automatically sequenced and networked with potential buyers.
2.4 Users create public and/or private genetic networks based on their personal preferences using the web platform or mobile app: the network may be a product, image or information network.
3. The Virtual Genetic Processor 3.1 The Genetic Processor automatically networks people, products and information.
3.2 The Genetic Processor continually sequences the World Wide Web.
3.3 The Genetic Processor continually updates the user’s network as information comes online.
3.4 The Genetic Processor automatically conducts commerce when specified by the user.
3.5 The Genetic Processor automatically updates millions of genomes worldwide under a two-part gene drive model: optimizing search results and clustering data storage.
4. A Self-organizing, Genetically Networked World Wide Web