The Race Is On to Control Artificial Intelligence, and Tech’s Future

Amazon, Google, IBM and Microsoft are using high salaries and games pitting humans against computers to try to claim the standard on which all companies will build their A.I. technology.

In this fight — no doubt in its early stages — the big tech companies are engaged in tit-for-tat publicity stunts, circling the same start-ups that could provide the technology pieces they are missing and, perhaps most important, trying to hire the same brains.

For years, tech companies have used man-versus-machine competitions to show they are making progress on A.I. In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM went even further when its Watson system won a three-day match on the television trivia show “Jeopardy!” Today, Watson is the centerpiece of IBM’s A.I. efforts.

Today, only about 1 percent of all software apps have A.I. features, IDC estimates. By 2018, IDC predicts, at least 50 percent of developers will include A.I. features in what they create.

Source: The Race Is On to Control Artificial Intelligence, and Tech’s Future – The New York Times

The next “tit-for-tat” publicity stunt should most definitely be a battle with robots, exactly like BattleBots, except…

  1. Use A.I. to consume vast amounts of video footage from previous bot battles, while identifying key elements of bot design that gave a bot the ‘upper hand’.  From a human cognition perspective, this exercise may be subjective. The BattleBot scoring process can play a factor in 1) conceiving designs, and 2) defining ‘rules’ of engagement.
  2. Use A.I. to produce BattleBot designs for humans to assemble.
  3. Autonomous battles, bot on bot, based on Artificial Intelligence battle ‘rules’ acquired from the input and analysis of video footage.

So Much Streaming Music, Just Not in One Place

In the old days, you never knew which CDs the record store would have in stock.  That limitation of physical media was supposed to be solved by digital. Back in the 1990s, technology evangelists and music fans alike began to talk about a “celestial jukebox” — a utopian ideal in which every song ever recorded would be available at a click.  In reality, even a celestial jukebox has gaps. Or more precisely, numerous jukeboxes have come along – iTunes, Pandora, Spotify, SoundCloud, YouTube – and each service has had gaps in its repertoire. And those gaps have been growing bigger and more complicated as artists have wielded more power in withholding their music from one outlet or another.

Source: So Much Streaming Music, Just Not in One Place – The New York Times

Additional Editorial:

Published music libraries are numerous, and have scattered artist coverage for one reason or another.  Music repositories may overlap, or lack completeness of coverage.

As expressed in “As a Data Deluge Grows, Companies Rethink Storage“, creating a system similar to the Internet Domain Name System for “Information Asset Libraries” would help in numerous ways.  Front end UIs may query these “Information Asset (object) libraries” to understand the availability of content across the Internet.

The Domain Name System (DNS) is a hierarchical decentralized naming system for computers, services, or any resource connected to the Internet or a private network.

Another opportunity would be to leverage the existing DNS platform for managing these “Information Asset Repositories”

In a relatively cost restrained implementation, a DNS type effort can be taken up by the music industry.  From artists to distribution channels, existing music repositories can be leveraged, and within months, a music aficionado may go to any participating platform, and search for an artist, title, album, or any other indexed meta data, and results across ‘Information Asset Repositories’ would be displayed to the user with a jump link to the registered information asset in the library.

Small independent artists need just populate a spreadsheet with rows that contain a row for each asset, and all the ‘advertised’ meta data.  Their Information Asset library may be a single flat file, i.e. XML, that conforms to a basic record/row structure.  The independent artist places this file on their web site, e.g. in their root folder, and informs their ISP of the address record type, and it’s location.  A new DNS record specification may need to be created, e.g. MX record.

As a Data Deluge Grows, Companies Rethink Storage

At Pure Storage, a device introduced on Monday holds five times as much data as a conventional unit.

  • IBM estimates that by 2020 we will have 44 zettabytes — the thousandfold number next up from exabytes — generated by all those devices. It is so much information that Big Blue is staking its future on so-called machine learning and artificial intelligence, two kinds of pattern-finding software built to cope with all that information.
  • Pure Storage chief executive, Scott Dietzen, “No one can look at all their data anymore; they need algorithms just to decide what to look at,”

Source: As a Data Deluge Grows, Companies Rethink Storage – The New York Times

Additional Editorial:

Pure Storage is looking to “compress” the amount of data that can be stored in a Storage Array using Flash Memory, “Flashblade”.   They are also tuning the capabilities of the solution for higher I/O throughput, and optimized, addressable storage.

Several companies with large and growing storage footprints have already begin to customize their storage solutions to accommodate the void in this space.

Building more storage arrays is a temporary measure while the masses of people, or fleets of cars turn on their IoT enabled devices.

Data is flooding the Internet, and innumerable, duplicate ‘objects’  of information, requiring redundant storage, are prevalent conditions. A registry, or public ‘records’ may be maintained.   Based on security measures, and the public’s appetite determine what “information objects” may be centrally located.  As intermediaries, registrars may build open source repositories, as an example, using Google Drive, or Microsoft Azure based on the data types of ‘Information Objects”

  • Information object registrars may contain all different types of objects, which indicate where data resides on the Internet.
    • vaguely similar to Domain name registrar hierarchy
    • another example, Domain Name System (DNS) is the best example of the registration process I am suggesting to clone and leverage for all types of data ranging from entertainment to medical records.
  • Medical “Records”, or Medical “Information Objects”
    • X-ray images, everything from dental to medical, and correlating to other medical information object(s),
  • Official ‘Education’ records from K-12 and beyond, e.g. degrees and certifications achieved;
  • Secure, easy access to ‘public’ ‘information objects’ by the owner, and creator.  Central portal(s) driving user traffic.  Enables ‘owner’ of records to take ‘ownership’ of their health, for example

Note: there are already ‘open’ platforms being developed and used for several industries including medical; with limed access.  However, the changes I’m proposing imposes a ‘registrar’ process whereby portals of information are registered, and are interwoven, linking to one another.

It’s an issue of excess weight upon the “Internet”, and not just the ‘weight’ of unnecessary storage, the throughput within a weaved set of networks as well.

Think of it in terms of opportunity cost.  First quantify what an ‘information object’, or ‘block of data’ equates to in cost.  It seems there must already be a measurement in existence, a medium amount to charge / cost per “information object”.  Finally, for each information object type, e.g. song, movie, news story, technical specifications, etc. identify how many times this exact object is perpetuated in the Internet.

Steps on reducing  data waste:

  • Without exception, each ‘information object’ contains an (XML) meta data file.
  • Each of the attributes describing information objects are built out as these assets are being used; e.g. proactive autopopulate search, and using an AI Induction engine
  • X out of Y metadata type and values are equivalent
    • the more attributes correlate to one or more objects, the more likely these objects are
      • related on some level, e.g. sibling, cousin
      • or identical objects, and may need meta relationship update
    • the metadata encapsulates the ‘information object’

Another opportunity to organize “Information Asset Objects” would be to leverage the existing DNS platform for managing “Information Asset Repositories”.   This additional Internet DNS structure would enable queries across information asset repositories.   Please see “So Much Streaming Music, Just Not in One Place”  for more details.