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Artificial stupidity as a DBA limitation of artificial intelligence

In Data, Database tuning, Databases, DBA on December 6, 2017 at 07:47

“Artificial intelligence is no match for natural stupidity” ― Albert Einstein

What about introducing Artificial Intelligence into the database to an extent it tunes itself into all possible dimensions?

You have probably either seen the question above or have already asked yourself if that was at all possible. On Ask Tom, John from Guildford wrote the following:

As for Artificial Intelligence, well Artificial Stupidity is more likely to be true. Humanity is not privy to the algorithm for intelligence. Anyone who’s had the pleasure of dealing with machine generated code knows that software is no more capable of writing a cohesive system than it is of becoming self-aware.

Provided you’re not trying to be a cheap alternative to an automaton you just need to think. That one function alone differentiates us from computers, so do more of it. The most sublime software on the planet has an IQ of zero, so outdoing it shouldn’t be all that hard.

Stephen Hawking thinks computers may surpass human intelligence and take over the world. Fear artificial stupidity, not artificial intelligence!

Einstein is credited with saying (but it was probably Alexandre Dumas or Elbert Hubbard who deserve the recognition): “The difference between genius and stupidity is that genius has its limits.”

Explore artificial stupidity (AS) and/or read Charles Wheelan’s book Naked Statistics to understand this kind of AI danger. By the way, according to Woody Allen, 94.5% of all statistics are made up!

So what are the limitations of AI? Jay Liebowitz argues that “if intelligence and stupidity naturally exist, and if AI is said to exist, then is there something that might be called “artificial stupidity?” According to him three of these limitations are:

  • Ability to possess and use common sense
  • Development of deep reasoning systems
  • Ability to easily acquire and update knowledge
  • But does artificial intelligence use a database in order to be an artificial intelligence? Few very interesting answers to that question are give by Douglas Green, Jordan Miller and Ramon Morales, here is a summary:

    Although AI could be built without a database, it would probably be more powerful if a database were added. AI and databases are currently not very well integrated. The database is just a standard tool that the AI uses. However, as AI becomes more advanced, it may become more a part of the database itself.

    I don’t believe you can have an effective Artificial Intelligence without a database or memory structure of some kind.

    While it is theoretically possible to have an artificial intelligence without using a database, it makes things a LOT easier if you can store what the AI knows somewhere convenient.

    As Demystifying Artificial Intelligence explains, AI hass been embedded into some of the most fundamental aspects of data management, making those critical data-driven processes more celeritous and manageable.

    Amazon Mechanical Turk is worth looking into and Oracle are also ready for business with AI.

    Matt Johnson, a Navy pilot turned AI researcher, at a conference this simmer by saying that one of the places we are not making a lot of advances is in that teaming, in that interaction (of humans and AI) – Artificial Stupidity: When Artificial Intelligence + Human = Disaster

    Bottom line: if AI uses a database, then the intelligent database should be at least autonomous and have most tasks automated but not relying on artificial stupidity as a DBA limitation of artificial intelligence. Whatever it means… I do not want to curb your enthusiasm but we need to first fill in the skills gap: we need data engineers who understand databases and data warehouses, infrastructure and tools that span data cleaning, ingestion, security, predictions. And in this aspect Cloud is critical and a big differentiator.

    P.S. Is Artificial Intelligence Progress a Bubble? was published 4 days after this blog post.

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    Blockchain for DBAs

    In Data, Databases, DBA on October 30, 2017 at 09:25

    “Instead of putting the taxi driver out of a job, blockhchain puts Uber out of a job and lets the taxi driver work with the customer directly.” – Vitalik Buterin

    A blockchain database consists of two kinds of records: transactions and blocks. Blocks contain the lists of the transactions that are hashed and encoded into a hash (Merkle) tree. The linked blocks form a chain as every block holds the hash pointer to the previous block.

    The blockchain can be stored in a flat file or in a database. For example, the Bitcoin core client stores the blockchain metadata using LevelDB (based on Google’s Bigtable database system).

    The diagram above can be used to create the schema in PostgreSQL. “As far as what DBMS you should put it in”, says Ali Razeghi, “that’s up to your use case. If you want to analyze the transactions/wallet IDs to see some patterns or do BI work I would recommend a relational DB. If you want to setup a live ingest with multiple cryptocoins I would recommend something that doesn’t need the transaction log so a MongoDB solution would be good.”

    If you want to setup a MySQL database: here are 8 easy steps.

    But what is the structure of the block, what does it look like?

    The block has 4 fields:

    1. Block Size: The size of the block in bytes
    2. Block Header: Six fields in the block header
    3. Transaction Counter: How many transactions follow
    4. Transactions: The transactions recorded in this block

    The block header has 6 fields:

    1. Version: A version number to track software/protocol upgrades
    2. Previous Block Hash: A reference to the hash of the previous (parent) block in the chain
    3. Merkle Root: A hash of the root of the merkle tree of this block’s transactions
    4. Timestamp: The approximate creation time of this block (seconds from Unix Epoch)
    5. Difficulty Target: The proof-of-work algorithm difficulty target for this block
    6. Nonce: A counter used for the proof-of-work algorithm

    More details, like for example details on block header hash and block height, can be found here.

    But how about blockchain vs. relational database: Which is right for your application? As you can see, because the term “blockchain” is not clearly defined, you could argue that almost any IT project could be described as using a blockchain.

    It is worth reading Guy Harrison’s article Sealing MongoDB documents on the blockchain. Here is a nice quote: “As a database administrator in the early 1990s, I remember the shock I felt when I realized that the contents of the database files were plain text; I’d just assumed they were encrypted and could only be modified by the database engine acting on behalf of a validated user.”

    The Blockchain technology is a very special kind of a distributed database. Sebastien Meunier’s post cocludes that ironically, there is no consensus on the definition of what blockchain technology is.

    I particularly, like his last question: Is a private blockchain without token really more efficient than a centralized system? And I would add: private blockchain, really?

    But once more, what is blockchain? Rockford Lhotka gives a very good DBA-friendly definition/characteristics of blockchain:

    1. A linked list where each node contains data
    2. Immutable:
    – Each new node is cryptographically linked to the previous node
    – The list and the data in each node is therefore immutable, tampering breaks the cryptography
    3. Append-only
    – New nodes can be added to the list, though existing nodes can’t be altered
    4. Persistent
    – Hence it is a data store – the list and nodes of data are persisted
    5. Distributed
    – Copies of the list exist on many physical devices/servers
    – Failure of 1+ physical devices has no impact on the integrity of the data
    – The physical devices form a type of networked cluster and work together
    – New nodes are only appended to the list if some quorum of physical devices agree with the cryptography and validity of the node via consistent algorithms running on all devices.

    Kevin Ford’s reply is a good one to conclude with: “Based on this description (above) it really sounds like your (Rockford Lhotka’s) earlier comparison to the hype around XML is spot on. It sounds like in and of itself it isn’t particularly anything except a low level technology until you structure it to meet a particular problem.”

    The nature of blockchain technology makes it difficult to work with high transnational volumes.

    But DBAs can have a look at (1) BigchainDB, a database with several blockchain characteristics added: high-transaction, decentralized database, immutability & native support for assets and (2) at Chainfrog if interested in connecting legacy databases together. As far as I know, they support as of now at least MySQL and SQL Server.

    DBA 3.0 – Database Administration in the Cloud

    In Cloud, DBA, OOW, Oracle database on September 23, 2017 at 10:35

    “The interesting thing about cloud computing is that we’ve redefined cloud computing to include everything that we already do … The computer industry is the only industry that is more fashion-driven than women’s fashion.” – Larry Ellison, CTO, Oracle

    DBA 1.0 -> DBA 2.0 -> DBA 3.0: Definitely, the versioning of DBAs is falling behind the database versions of Oracle, Microsoft, IBM, etc. Mainframe, client-server, internet, grid computing, cloud computing…

    The topic on the DBA profession and how it changes, how it evolves and how it expands has been of interest among top experts in the industry:

    Penny Arvil, VP of Oracle Database Product Development, stated that DBAs are being asked to understand what businesses do with data rather than just the mechanics of keeping the database healthy and running.

    Kellyn Pot’Vin-Gorman claims that DBAs with advanced skills will have plenty of work to keep them busy and if Larry is successful with the bid to rid companies of their DBAs for a period of time, they’ll be very busy cleaning up the mess afterwards.

    Tim Hall said that for pragmatic DBAs the role has evolved so much over the years, and will continue to do so. Such DBAs have to continue to adapt or die.

    Megan Elphingstone concluded that DBA skills would be helpful, but not required in a DBaaS environment.

    Jim Donahoe hosted a discussion about the state of the DBA as the cloud continues to increase in popularity.

    First time I heard about DBA 2.0 was about 10 years ago. At Oracle OpenWorld 2017 (next week or so), I will be listening to what DBA 3.0 is: How the life of a Database Administrator has changed! If you google for DBA 3.0 most likely you will find information about how to play De Bellis Antiquitatis DBA 3.0. Different story…

    But if I can also donate something to the discussion is probably the fact that ever since a database vendor automated something in the database, it only generated more work for DBAs in the future. More DBAs are needed now as ever. Growing size and complexity of IT systems is definitely contributing to that need.

    These DBA sessions in San Francisco are quite relevant to the DBA profession (last one on the list will be delivered by me):

    – Advance from DBA to Cloud Administrator: Wednesday, Oct 04, 2:00 p.m. – 2:45 p.m. | Moscone West – Room 3022
    – Navigating Your DBA Career in the Oracle Cloud: Monday, Oct 02, 1:15 p.m. – 2:00 p.m. | Moscone West – Room 3005
    – Security in Oracle Database Cloud Service: Sunday, Oct 01, 3:45 p.m. – 4:30 p.m. | Moscone South – Room 159
    – How to Eliminate the Storm When Moving to the Cloud: Sunday, Oct 01, 1:45 p.m. – 2:30 p.m. | Moscone South – Room 160
    – War of the Worlds: DBAs Versus Developers: Wednesday, Oct 04, 1:00 p.m. – 1:45 p.m. | Moscone West – Room 3014
    – DBA Types: Sunday, Oct 01, 1:45 p.m. – 2:30 p.m. | Marriott Marquis (Yerba Buena Level) – Nob Hill A/B

    And finally, a couple of quotes about databases:

    – “Database Management System [Origin: Data + Latin basus “low, mean, vile, menial, degrading, ounterfeit.”] A complex set of interrelational data structures allowing data to be lost in many convenient sequences while retaining a complete record of the logical relations between the missing items. — From The Devil’s DP Dictionary” ― Stan Kelly Bootle
    – “I’m an oracle of the past. I can accurately predict up to 1 minute in the future, by thoroughly investigating the last 2 years of your life. Also, I look like an old database – flat and full of useless info.” ― Will Advise, Nothing is here…