MCubed 2019: Speaker lineup shows how to put ML and AI to work

We're pleased as punch to announce the first speakers for MCubed London 2019, our three-day dive into machine learning, AI and data science, and what they mean for real-world companies and organisations. So, if you haven't grabbed one of our blind bird tickets yet, we suggest you do now as they're poised to disappear for good …

[I.Geller]

ordinary texts become programs

Don't listen to charlatans! Machine Learning is the addition and removal of structured in synonymous clusters texts, where each their pattern is a direct analog of a programming language command.

For example there is a paragraph:

-- Alice and Bob exercise a lot. Their goal is to be strong. --

In paragraph 16 patterns: 3 nouns + 1 pronoun, 2 verbs and 2 adjectives.

- Alice exercises a lot

- Bob exercises a lot

- Their exercises a lot

- Alice exercises strong

- Bob exercises strong

- Their exercises strong

- Alice is to be a lot

- Bob is to be a lot

- Their is to be a lot

- Alice is to be strong

- Bob is to be strong

- Their is to be strong

- Goal is to be strong

- Goal is to be a lot

- Goal exercises strong

- Goal exercises a lot

These 16 patterns are combined into synchronous clusters. For example one of them has 4 patterns:

- Alice exercises a lot

- Alice exercises strong

- Alice is to be a lot

- Alice is to be strong

Then the pattern

-- Alice exercises a lot

litterally becomes a command. For example, to search for information on the Internet about food suppliments.

Now comes another paragraph:

-- Alice bought kettlebell. It helps her to stay thin.

This paragraph is also structured and some synonymous clusters added to the first. This is Machine Learning: ordinary texts become programs.

[amanfromMars 1]

Re: ordinary texts become programs

Yes, I.Geller. And? ......... Is it problematical and exploitable?

And of course, as there's bound to be the question asked .... Is it exportable and Lend-Lease ACTionable?

[I.Geller]

Yes

Yes, this is a ready to be used AI technology, all detail are ate the US PTO.

[amanfromMars 1]

Re: Yes

Yes, this is a ready to be used AI technology, all detail are ate the US PTO. .... I.Geller

Hmmm?

Is it in any practical or virtual use anywhere where it is making any great difference yet? Or who and/or what would be thinking to use it for the benefits of an unfair advantage/leading application, is at least next logical question, methinks? And who and or what would be thinking them able and willing to offer support and pick up the tab for running costs? If they wish to stay well clear and are content to just go with the current flow, such would allow them a sort of virtual remote control/invisible guiding hand.

Flash cash/deposited stash has that power to create all manner of energies that matter and thrive ..... although it has to be said, the present crop of exceedingly filthy rich entrepreneurs appear to have run right out of Outstanding and Upstanding Ideas for Realisation and Universal Presentation.

[I.Geller]

AI understanding: 4-5 layers is the requirement, 7-8 is the best.

Dictionary definitions for patterns' words are extremely important, without them AI is unthinkable. The quality of dictionary definitions determines how much AI understands what is wanted from it. AI needs to know all the possible details of the definitions because the details form tuples that allow it to understand.

For example, the definition of a word consists of words (each of which has its own definition) and AI should know them all. Extremely, for the same reason, it is important to know synonyms for all dictionary definitions: they help to chose only meaningful definitions and cut off random.

Each definition on the dictionary definition form a layer. The more layers are present the better AI understands. 4-5 layers is the requirement, 7-8 is the best.