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The real strength of Siri lies in its middleware infrastructure, that ties together more than 35 APIs. I've got a wealth of resources listed under my Meta-Guide.com project website. And, I've put together a comprehensive survey of "Artificial Intelligence Middleware" [1], as well as a webpage listing relevant "Application Programming Interfaces" [2].
In fact, Siri is based on a government sponsored (SRI) project called PAL (Personalized Assistant that Learns), and *some* of the PAL Framework [3] components are open source. (Actually, CALO, the Cognitive Agent that Learns and Organizes, was originally developed as part of the PAL project.)
Comment • Jan 14, 2012
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Firstly, I recommend checking my "Proceedings" page on Twylah [1].
Secondly, you might check the following:
Declarative Agent Languages and Technologies
Intelligent Virtual Agents
Interactive Digital Storytelling
International Conference on Virtual Storytelling
Web Reasoning and Rule Systems
Comment • Dec 20, 2011
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"Computational Dreaming" is directly related to "Metaphor Analytics", which necessarily involve "imaging" and pattern recognition.
Comment • Dec 16, 2011
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There are plenty of data visualization applications to see the spread of information on Twitter over time. I simply monitor Topsy [1] to see who says what, and when, about any given URL.
Your answer may need to be a more direct response. (more)
1 Comment • Dec 16, 2011
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My Pipes seem to be working correctly at the moment. Pipes was down for a few days, but came back up this morning. There are lots of modules in Pipes, and any one of them can develop issues. I lost some vital functionality in the "Fetch Data" module after the recent upgrade to V2.
1 Comment • Dec 15, 2011
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I suggest looking at OpenEphyra [1], a contender in the Text REtrieval Conference (TREC) [2] series, and precursor to IBM Watson.
Comment • Dec 12, 2011
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I suggest reading Twitter's own "Automation Rules and Best Practices" [1]. I am currently building travel and tourism Twitter bots for every country on Earth [2]. I've also got an inventory of non-travel Twitter bots I've made [3].
At this time, Twitter uses automation to "suspend" abusive Twitter bots. There is an appeal process, which works for me maybe 50% of the time. In particular, Twitter does not like "@" sign abuse; I've taken to replacing them with "#" tags (after removing existing "#" tags). Also, Twitter does not like people ripping off tweets without attribution of some kind (such as, at least a link to the original).
Since twitterfeed.com is rate limited, I now prefer dlvr.it. (BTW, Twitterfeed was acquired by bitly.com not long ago.) I have also used tweethopper.com in the past. Actually, feedburner.com now includes the native ability to pass feeds into Twitter. And of course, there are others.
Comment • Dec 11, 2011
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In addition to Alabot [1], Vimagino (vHelp.me) [2] and WEBees (Convogent) [3] work in the conversational agent (chatbot) space in India.
Comment • Dec 10, 2011
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Basically, rules based AI has given way to machine learning. Unstructured data is "understood" by checking it in parallel against structured data, and statistically analyzing the evidence.
Have a look at my January 2011 blog post, "How Many PlayStations Make A Watson?" [1]. I've also got a page of "Best IBM Watson Videos" [2].
Comment • Dec 4, 2011
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Wavii appears to be a combination of automated "web content curation" [1] and so-called "text synthesis" [2], which would make it related to both Summify [3] and Automated Insights' [4] (formerly StatSheet) [5] STAT.US [6].
Comment • Dec 4, 2011
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Comment • Dec 4, 2011
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What immediately comes to my mind are the Boston Museum of Science "responsive virtual human museum guides", Ada and Grace [1], made at the University of Southern California Institute for Creative Technologies [2]. Certainly, such virtual human museum guides might also be implemented in augmented reality.
There is a new book available in this field, titled "Language Technology for Cultural Heritage" [3]. The AMICUS network [4] for "automated motif discovery in cultural heritage and scientific communication texts" is another available resource. And, a registry of technology-related museum projects is maintained online by MuseTech Central [5].
Comment • Nov 24, 2011
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"Human-like" AI is commonly referred to as AGI, or "Artificial General Intelligence" [1]. I believe that "sentiment analysis" is in fact more closely related to conversational agent (aka chatbot) NLP or AI than people seem to realize.
Keep in mind, there are two layers to "human-like" AI. One is the speech layer, or dialog system (using essentially the same technology as sentiment analysis, but in a different way). The second layer is the "cognitive", perhaps more like IBM Watson in that it's actually "understanding" concepts and their relations. So, the fusion of Apple Siri and IBM Watson would give some idea of a more "human-like" AI. Once Apple releases a Siri SDK, and IBM releases its Watson API, then people may begin to hack around and realize this potential. (Of course, the availability of robust AI middleware platforms would also be helpful.)
However, Seth Grimes is probably right that the "easiest" way forward would be with machine learning based on crowd-sourcing. Perhaps one day soon machines will be digesting and learning from Quora.
Comment • Nov 24, 2011
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Gary, I have written extensively about the need for "Open Chatbot Standards" [1], and have frequently mentioned on Quora [2] the potential key role of XMPP for machine to machine natural language communication.
FYI, I have also recently aggregated links and videos about "Multi Bot Scenarios" [3], such as the viral "AI vs AI".
BTW, my personal feeling about the Turing test is that it is a "red herring".
Comment • Nov 24, 2011
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I would like to expand on Kitano and O'Brien's answers. I am seeing 2 sectors here. One I'm calling "robojournalism", and the other "curation". Robojournalism may be "newspaper" or "magazine" formats. Robojournalism also includes "summarization"[1] or "text synthesis"[2], and there are topics for these on Quora. Curation may be automated or manual.
Paper.li (@SmallRivers) and TweetedTimes.com (@TwtTimes) come under the newspaper format. And, Postano.com (@ilpostano), Twylah.com (@Twylah), and Scoop.it (@scoopit) qualify as magazine formats. There are differences here, some do your inside stream, some do outside stream, others follow hashtags or multiple streams, and Scoop.it is manual curation though magazine format.
So-called "summarizers" include Summify.com (@summify), Strawberryj.am (@strawberryapp), Knowabout.it (@knwbt), News.me (@newsdotme), and Topicmarks.com (@topicmarks).
Examples of more advanced "text synthesis" robojournalism include AutomatedInsights.com (@AInsights), formerly StatSheet, and NarrativeScience.com (@narrativesci).
Comment • Nov 21, 2011
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It does not yet remember links. I would prefer to never receive the same link twice.
Apparently, links are triggered by 2x posts; so, it doesn't even check links for rank until it sees them twice. I would prefer to have all links checked on popularity outside my stream.
And then there is the inverse. Do I really want the most popular links (think TV)? Maybe the gold is really in the least popular ones?
1 Comment • Nov 20, 2011
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I would say one is more "push", and the other more "pull". For example Apple Siri, if not a "recommender system" per se, certainly involves elements of recommendation systems; whereas, something like StumbleUpon.com would be more of a "discovery engine".
Comment • Nov 15, 2011
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I've got a listing of (82x) conversational agent companies on Twitter at
Comment • Oct 18, 2011
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I feel strongly that there will be a boom in XMPP for machine-to-machine natural language communication (AI vs. AI).
Extensible Messaging and Presence Protocol
Further, if there were any decent IM-Voice bridge (app) available, then not only would everyman have safer hands-free instant messaging, but would also be able to speak with their own AI using speech i/o.
1 Comment • Sep 12, 2011
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It seems that "constructed languages" would lend themselves more readily to machine intelligence, because they are equivalently artificial, as opposed to natural language. In fact, Cleverbot.com is able to speak the constructed language "Toki Pona".
List of constructed languages - Wikipedia
On a tangential note, I am a great proponent of XMPP for machine-to-machine natural language communication (AI vs. AI).
Extensible Messaging and Presence Protocol
Comment • Sep 12, 2011
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I just got back a few months ago from an extended trip, with my iPod Touch, to South America. The iTouch is great for travel because you don't need a plan for WiFi, and it does Skype just fine.
Though there were a few choices, I finally settled on paying $9.99 for Wiki Offline by Avocado Hills [1]. This was by far the best app for the trip. I loved reading background and history, even for a surprising number of medium-sized places.
In contrast, Word Lens by Quest Visual proved to be a complete waste of money.
I found another unlikely app to be most handy, the free MapsWithMe - Travel Guide by Yury Melnichek [2]. This is great for two reasons. It had all the free offline local maps I needed for the whole trip, and contained all the offline Wikitravel I needed.
I really love the Web Reader - Text to Speech $1.99 app by Chris Chauvin [3]; because, I filled my Mendeley - Reference Manager app [4] with 1,000 research PDFs and listened to them to my hearts content. ;^)
Finally, I ended up buying the Justin.tv app [5] for $4.99 en route, just to get some free English language TV. Despite containing atrocious advertising for a paid app, it really surprised me what all you can watch on Justin.tv. ;^)
I never did locate a really good *offline* podcast app.
Comment • Sep 8, 2011
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PersonalBrain Tour in 10 Minutes
Concept mapping versus topic maps and mind mapping
List of concept mapping and mind mapping software
Data visualization is a related field, which might give you some more ideas.
Data visualization software
1+ Comments • Sep 6, 2011
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I just ran across "Ping Identity Corporation" [1] the other day while researching the fate of the former Jabber.com (acquired by Cisco.com). It seems that Jabber, Inc founder Andre Durand moved on to found "The Cloud Identity Security Leader"(tm).
1+ Comments • Sep 6, 2011
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Chat means one thing to me, XMPP. I would encourage you to look into Voxeo IMified at
http://imified.com . I really don't think that people appreciate the significance of XMPP. XMPP is all about natural language communication. I feel strongly that in the future more machines will be using it than people. I believe that XMPP will be the primary means of machine to machine communication using natural language. I also believe that XMPP will be the way that people communicate with AIs; however, surprisingly, there is no consumer IM - Voice bridge currently available. That will be a revolutionary app, a simple bidirectional instant message to voice app, with universal XMPP plug and play on the backend - not only for hands-free IM, but also to actually speak with AIs.
Comment • Aug 29, 2011
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Just a quick google shows about 750,000 results for site:pipes.yahoo.com
I think there could reasonably be around three quarters of a million pipes created. I would hazard to guess that there may be half that number of all time registered users, so about 375,000. I can say that I have 50,000 users on 50 pipes on Twitter, so 1,000 users per pipe. That would make some 750 million Yahoo! Pipes users total. (I will be happy to be proven or disproven on any of these numbers.)
Comment • Aug 25, 2011
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Gary, as you probably know, there's been a lot of talk on Robitron and the Chatbots.org AIZone about Bruce Wilcox's ChatScript (versus AIML). There is also RiveScript by Noah Petherbridge, CML (Conversation Markup Language) by Chongguan Yang, and AIScript (PersonalityForge) by Benji Adams. The list goes on.
Current Loebner champion Wilcox has waxed eloquent about this in March 2011, "Beyond Façade: Pattern Matching for Natural Language Applications":
He revealed more details about his work in June 2011, "Suzette, the Most Human Computer":
As I've mentioned previously on Chatbots.org AIZone, its not so much the language as the interpreter that makes the most difference to the learning curve. (Though I do agree theoretically with the logic for the improvements of ChatScript over AIML.) Its in fact the (cloud) infrastructure of new services like Chatbot4u that make the most difference. It just feels like to me that the old days of hosting an interpreter on your own hardware are quickly passing away.
That said, I'm a great believer in MODULARITY, open plug and play frameworks. I believe, both Apple Siri and IBM Watson were made in this way. Currently, the biggest bottleneck is the voice-in/voice-out lipsync avatar. I am a big promoter of XMPP as the lingua franca for open, modular conversational agents. But, there is no good IM-Voice bridge available at this time (with or without avatar).
Comment • Aug 25, 2011
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This is a hot topic now, and a lot is being written about it.
I work with speech recognition in conversational agents, and can tell you it's still not perfect. While this is amusing in chatbots, it's not quite ready for mission critical applications.
But voice search does not mean simply speech to text; voice search also implies text to speech. For instance, all of the Twitter readers I've tried are still imperfect and have a hard time with hashtags, URLs, and SMS language, which doesn't make for fun listening.
The big component that's still missing in almost all applications is summarization. Any voice search will need to at least partially abbreviate and interpret, if not tailor, results.
I imagine in the medium-term future people will cease to surf the web as they do today, and a layer of (voice) agents will use the web as we know it for their backend.
1+ Comments • Aug 23, 2011
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I've just begun Alpha testing DataSift, and its not yet clear to me what I can do with DataSift that I'm not already doing with Yahoo! Pipes.
There is no clear feed-in / feed-out paradigm, since DataSift taps services internally:
To do anything in DataSift involves using its own Curated Stream Definition Language (CSDL):
For feed-out, DataSift more resembles Tarpipe in terms of pricing:
Comment • Aug 9, 2011
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The holy grail of travel technology... the artificially intelligent, robotic travel agent, as smart or smarter than the average professional travel agent today. Smartphone apps such as Apple Siri and others are a step in that direction, but no cigar yet. In fact, I've been working on this for the past 13 years at Meta-Guide.com .
Comment • Aug 2, 2011
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Siri - The Personal Assistant on your Phone
Monica iPhone Application Full Demo - Your Virtual Assistant
Meet Alfred, your personal robot!
Comment • Jul 31, 2011
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In these new videos, Philadelphia lawyer Frank Taney
http://twitter.com/scarylawyer of Buchanan Ingersoll & Rooney discusses legal and IP issues for botmasters at the recent Chatbots 3.1 Conference.
Chatbots 3.1 - Francis Taney - Legal and IP Issues for Botmasters (1/2)
Chatbots 3.1 - Francis Taney - Legal and IP Issues for Botmasters (2/2)
Comment • Jul 21, 2011
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I can add three clues to this thread.
Firstly, I recently came across the 2009 book, "Introduction to Chinese Natural Language Processing"
by
Secondly, it seems Ben Goertzel has been working extensively in China with Australian Professor Hugo de Garis; so, I suspect either would know who's who and what's what.
Third, there appears to be significant recent work being done in China on metaphor analytics, which might explain the current interest in Washington.
2010: "The Chinese Noun Metaphors Knowledge Base and its Use in the Recognition of Metaphors"
by
2010: "Research on the Cognitive Comprehension Logic and Its Application in Understanding of Metaphor"
by
Comment • Jul 20, 2011
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Stephen Wolfram wrote a great blog post in January 2011 comparing IBM Watson with Wolfram|Alpha side by side, entitled "Jeopardy, IBM, and Wolfram|Alpha".
Apparently Wolfram|Alpha uses Stephen Wolfram's own Mathematica software to supposedly compute symbolic representations.
I would welcome a more detailed explanation of just how this works myself! ;^)
I was able to find this Youku video of Stephen Wolfram's brother Conrad Wolfram explaining symbolic computation in Mathematica.
1 Comment • Jul 20, 2011
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There is a Quora topic for this at
Wikipedia is now referring to this as an "Automated online assistant"
The software may be referred to as a "Dialog system" (or Dialogue system)
See in particular "Toolkits and architectures"
Comment • Jul 18, 2011
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"Artificial intelligence has the same relation to intelligence as artificial flowers have to flowers." David L Parnas
These are very recent, very cool videos that tell it like it is, and we ain't there yet.
Henry Markram: Simulating the Brain -- The Next Decisive Years [1/3]
Henry Markram: Simulating the Brain -- The Next Decisive Years [2/3]
Henry Markram: Simulating the Brain -- The Next Decisive Years [3/3]
1 Comment • Jul 17, 2011
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I just ran across this 2010 book:
Automated Grammatical Error Detection for Language Learners
by
Comment • Jul 17, 2011
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This is an interesting concept; though, I've got a slightly different slant on it. There are two basic kinds of "artificial intelligence", one is conventional machine intelligence, and the other is "collective intelligence" along the "Mechanical Turk" model. (And of course, there is also the combination of the two.) It seems that you have identified a prime opportunity to implement this kind of solution, and not to forget the FUN (and learning)!
I will add to this that as things get worse in the world environmentally and socially, I expect people will retreat into virtual worlds, along the lines of games such as Second Life and World Of Warcraft. At the same time, these virtual worlds are predicted to become MUCH more realistic (probably hyper-realistic like HDTV). Therefore, the question may become how to employ people as "Mechanical Turks" in the virtual worlds.
Comment • Jul 15, 2011
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This may be a somewhat tangential or ancillary answer, but is inline with my area of expertise, social agents for question answering.
According to "Agent Virtuel - LE BLOG"
http://agent-virtuel.fr ... the main players in the "automated online assistant" industry in France are:
VirtuOz - Assistant Virtuel pour la Gestion du Service Client
Agent virtuel ASKOM: améliorer la relation client - guider, conseiller, humaniser
Do You Dream Up ? (aka createmyassistant.com)
Agent virtuel dialoguant, agent conversationnel - dialonics
Comment • Jul 13, 2011
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AdaptiveAI is behind SmartAction, and Peter Voss is behind both. You can find his 2007 paper, "Essentials of General Intelligence: The Direct Path to Artificial General Intelligence", below:
a2i2 : Adaptive AI, Inc
Peter Voss | LinkedIn
Essentials of General Intelligence: The Direct Path to Artificial General Intelligence (2007)
Comment • Jul 8, 2011
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Artingence - The Artificially Intelligent Call Center
SmartAction call center IVR, hosted speech IVR, IVR solutions
Comment • Jul 8, 2011
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>>
The term reverse Turing test has no single clear definition, but has been used to describe various situations based on the Turing test in which the objective and/or one or more of the roles have been reversed between computers and humans.
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(NLG) is the natural language processing task of generating natural language from a machine representation system such as a knowledge base or a logical form.
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Machine learning is getting pretty darn good, especially when coupled with brute force computing. I suspect that the time is not long off where machines will be able to identify humans more readily than humans will be able to identify machines.
Comment • Jul 5, 2011
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There is no Wikipedia entry for "text synthesis".
However, there are Wikipedia entries for "Natural language generation" and "Automatic summarization":
There are recently answered questions on Quora in these topics:
On Wikipedia StatSheet is referred to as "automated publishing":
The only thing I could find on Wikipedia directly related to automated publishing was "Dynamic publishing":
There was a Quora question on "dynamic semantic publishing" which I've added to your "text synthesis" topic:
Comment • Jun 30, 2011
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Cleverbot uses string metrics, a technique called "string similarity"..
http://www.youtube.com/playlist?list=PL5558B77F03AE612E
Comment • Jun 29, 2011
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Addendum:
This Ruby-1.8 "Natural Language Processing (NLP) Software" by Masao Utiyama (last updated 2007) turned up after my original answer above:
Comment • Jun 26, 2011
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Good question. I know of at least two companies working in this area:
and
Offhand, I am not aware of turnkey products to accomplish your goal. However, I recommend you look at the new Guile3D conversational agent (aka chatbot) Denise
http://www.guile3d.com , basically taking advantage of Windows7 speech tools.
I have asked Richard Wallace, inventor of AIML, a number of times for a list of known voice interactive applications, but so far without success. I have been told by Voxeo/Tropo that IVR Grammars are not up to this task, despite their announcement of partnering with
http://artingence.com to do just this.
What caught my attention while listening to the paper you cited (in iPhone Web Reader text to speech app) was the mention of confidence scoring, of the type used in IBM Watson, and the use of Ngrams, such as Microsoft Web N-gram Services or Google Ngram Viewer.
Comment • May 18, 2011
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This question does not make sense. Please clarify. Do you mean Visual Basic or visually impaired?? Otherwise, Pipes is as visual as it gets; but, to do anything really creative you still need to do some programming, essentially creating your own webhooks.
1+ Comments • May 15, 2011
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I certainly couldn't say who's the smartest NLP person in Poland; however, I can say that there are a number of chatbot specialists either based in Poland or originally from Poland. I hope you find the following five companies interesting.
Comment • Jan 30, 2011
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Yes, its trivial to send Quora feeds into a chatbot or question answering API; however, chatbot replies tend to be "chatty" rather than informative, and currently available question answering APIs tend to just do simple, factual questions and answers. IBM researcher Bill Murdock believes that IBM Watson could handle Quora questions with a little re-tuning; however, IBM Watson does not currently offer any API. Furthermore, since Quora has no API yet, it would be more challenging to post answers back to Quora.
1 Comment • Jan 23, 2011
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1 Comment • Jan 21, 2011
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That depends on what purpose you want it for, enterprise, small business, or personal. There are quite a few companies offering customer service solutions for substantial companies. There are also a good number of qualified consultants who can implement this kind of solution for small business. And, there are do it yourself hacks available online for the hobbyist. It would also depend on what country you are in, not to mention what language your customers speak, to determine the best solution. ;^)
Comment • Jan 20, 2011
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Certainly, people will be able to make a machine with self-awareness; however, that does not mean it will have human self-consciousness. I imagine self-awareness in a machine would be able to examine and modify its own coding, if not its own hardware.
Comment • Jan 20, 2011
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Its worth re-examining the IBM Deep Blue (chess computer) story to compare for potential effects .. You can read more about it here:
There is also a good 4 part documentary available on YouTube about Kasparov versus Deep Thought:
See also:
Comment • Jan 19, 2011
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1 Comment • Jan 19, 2011
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Ben Goertzel and Hugo de Garis are real characters ..
See their:
A world survey of artificial brain projects Part I: Large-scale brain simulations (2010)
and
World survey of artificial brains, Part II: Biologically inspired cognitive architectures (2010)
Comment • Jan 19, 2011
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Two related issues:
1) Better to start with dolphins:
Scientists say dolphins should be treated as 'non-human persons'
2) Issues of agent abuse must be addressed:
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See also Isaac Asimov's Three Laws of Robotics:
Comment • Jan 19, 2011
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Real world questions tend toward messy and rambling (like asking three questions in one, and more often than not ungrammatically, if not misspelled or even in SMS jargon), which makes it really difficult for question answering machines. Both WolframAlpha and TrueKnowledge have question answering APIs available today, but seem to only be able to answer brief factual questions. One of the problems with learning machines is that they tend to become degraded when released into the wild, because people will drag them down to the lowest common denominator. So in answer to your question, I would say Watson would be able to answer only a small percentage of questions on Quora.
Comment • Jan 19, 2011
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2 Comments • Jan 17, 2011
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Who can say what is really "normal" in AI? The UIMA natural language architecture could be said to be somewhat standard. The metalearner confidence scoring is an interesting twist. Without a doubt though, its the supercomputer hardware that gives it the edge, doing in seconds what it would take mere mortal machines to do in hours.
Comment • Jan 16, 2011