Why is AI not Real Intelligence?

Artificial Intelligence Market worth 16.06 Billion USD by 2022 http://www.marketsandmarkets.com/PressReleases/artificial-intelligence.asp

Since around 1998 I was creating chatbots and building up libraries of AIML Artificial Intelligence Markup Language, XML dialect used in natural language software agents. Example sites: pandorabots.com and alicebot.org

More recently I've been testing out some of the newer solutions like api.ai, they make it very simple to build conversational interfaces using Natural Language.

One of the biggest problems with Machine leaning is the Training System Required to build a large enough data set to handle variations in Conversation. So most of my thoughts have focused on producing Input based learning from large data souces (e.g. books) Or Learning based on Conversation and Articles.

Recently my wife and I had a few friends staying with us and all have kids at differnent ages. It's fasinating to think about how we learn language. We learn based on Input and Experience (I'd love to see a dual language learning app based on aipoly.com). So mapping Input and Output to a Software model would need some kind of Experience Engine.

To produce Output / Results / Reply a system would need to understand the Input based on Experience.

I've also been thinking about a simple architecture / sitemap of those systems

 

Back to the real world I made a note of some applications from ai.api:

1. Small Talk - Make small talk
2. Booking - Make reservations at restaurants or hotel …
3. Weather - Get weather information
4. Wisdom - Ask general knowledge questions
5. Flight Schedules - Get flight schedules and statuses
6. News - Read news
7. Call - Call a number, contact, or venue
8. Messages - Compose and read messages
9. Email - Compose and read emails
10. Media - Control music/video players and radio
11. User Name & Agent Name - Change names of users or agents
12. Web Search - Perform web searches
13. Web Browsing - Open websites
14. Apps - Open, close, download, remove, search,  …
15. Time & Dates - Work with time and date
16. Calculator - Perform basic calculations and conversion …
17. Calendar - Work with calendar
18. Reminders and Notifications - Work with reminders and notifications
19. Manage App - Open, close, or update the app
20. Maps - Search in maps
21. Navigation - Navigate to places
22. Points of Interest - Search for venues
23. Device Control - Control device’s settings
24. Units and Formats - Change default formats for units
25. Translate - Translate text to various languages
26. Language Selection - Switch between different languages
27. Shopping - Search for things to buy
28. Notes - Work with notes
29. Tasks - Work with tasks
30. Social Networks - Work with Twitter and Facebook
31. Events - Search for events
32. Taxi Search - Request a taxi
33. TV Listings - Get TV listings
34. Smart Home - Control smart devices
35. Sports - Get sports scores, stats, schedules, etc …
36. Finance - Get stock prices and market reports
37. Authentication - Log in/out or sign up for online service …
38. Learning - Train the agent to understand new commands …
39. Nicknames - Work with nicknames
40. Contacts Search - Search for a contact
41. Images - Search for images
42. Traffic - Request a traffic information
43. Maps Shortcuts - Work with maps shortcuts

Currently my own two faves:

1 Automated conversations with people looking to buy Insurance.

Competition in this space:

• http://www.synergist.io/ negotiation layer
• https://artificiallawyer.com/2017/01/11/legal-tech-pioneer-synergist-reinvents-contract-creation/
• https://mty.ai/ Service to train artificial intelligence engines
• http://www.ibm.com/watson/how-to-build-a-chatbot/ AI Service provider
• https://cloud.google.com/products/machine-learning/ AI Service provider
• https://aws.amazon.com/amazon-ai AI Service provider

2 Semi-automated platform creates written article content. 

Competition in this space:

• https://automatedinsights.com/
• http://www.arria.com/ 
• https://www.narrativescience.com/
• http://www.articoolo.com/
• http://www.emmaai.com/

Building an Experience Engine is key

Experience could be built from Relationship of entities.

Relationship of entities could be done with Content Context. So we need to build up huge datasets of related entities which should be anything and everything e.g. Language, Time , Date, Grammar, Letter, Word, Word, Phrase, Sentence, Paragraph, Question, Answer, Intent, Symbols, Abbreviations, Database of Examples, Fruit, Company, Numbers, Stock market symbols, Currency codes, Currency symbols, ISO codes, Maths equations, Plant names, Animals, Birds, Piano notes, Guitar notes, Voltage, Frequency, Artists, Architects, Websites, Planets, Navigation, Coordinates, Molecules, Particles, Elements, Countries, People names, Boys names, Girls names, Music bands, Music artists, Clouds

For example: Take a short list of Currency symbols (£ GBP, $ USD) for any Real Intelligence there should be a huge number of related of entities to Build an Experience.

For example: USD relates to many entities e.g. Language=English, Time=1.02pm, Date=24 Feb 2017, Grammar=English grammar, Letter=U,S,D,USD, Word=USD, Abbreviations=USD, Currency codes, Currency symbols.

In summary. Talking with Software developers in a past they always had concerns about database storage and CPU processing limits but we're reaching a point now where those limitations will not be a concern. Yes Apple, Google, Amazon, Microsoft are all building conversational agents but I think there'll be room for more. (Note a side note I still don't like the term "AI" cause it's based on Real Intelligence).