Weekly QUEST Discussion Topics and News, May 17
This week we will have to cut our meeting to a half hour – 12-12:30 due to a call we have at 1 with the Google Director of Engineering.
The topics are:
1.) The notes for the Ray Kurzweil call. The AF is seeking an Investment strategy that will lead to Game Changing (10-100x) improvements in mission capabilities – our specific interests are in the mission areas of command and control of our forces and in the Intelligence / Surveillance / Reconnaissance missions, so we’re seeking Mr. Kurzweil’s opinion on what breakthroughs will occur and when they will occur and what he would recommend our investment strategy should be (lead investor, fast adaptor of commercially developed solutions, watch for breakthroughs) – as an example -what would allow us to break out of our current ‘drowning in data’ problems
2.) The second topic is a series of documents associated with the Palantir’s Director of Forward Deployed Engineering, Shyam Sankar’s talk on intelligence augmentation – in it he notes – the stories behind two classic encounters between man and machine: the 1997 match in which IBM’s Deep Blue supercomputer defeated chess grandmaster Garry Kasparov, and a 2005 freestyle tournament in which two amateur players using three weak laptops defeated all comers, including grandmasters armed with supercomputers… he also notes – the relevance and impact of Human-Computer Symbiosis today with the emergence of Big Data and related technologies. Responding quickly to victims of the Haiti earthquake, making sense of complex documents found in an Al-Qaeda house, designing the 9/11 Memorial—these are all tasks that are best tackled by a nimble mind and powerful technology working in concert… – he suggest the focus should be – By building software in such a way that it reduces the friction experienced at the boundaries between the computing power, the analyst, and the source data… with the dramatic walk-away conclusion point : Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.
Weekly QUEST Discussion Topics and News, May 10th
A Framework / Theory for Artificial Consciousness:
A framework is not a detailed hypothesis or set of hypotheses; rather, it is a suggested point of view for an attack on a scientific problem, often suggesting testable hypotheses – we will discuss how defining characteristics of consciousness can provide the guidance to developing a mathematical framework for QUEST. We will focus on which of the tenets / fundamental laws we’ve discussed are critical to embody in QUEST solutions and thus the mathematical framework must support.
THE ULTIMATE GOAL of a theory of consciousness is a simple and elegant set of fundamental laws, analogous to the fundamental laws of physics.
• What might the underlying fundamental laws be?
• There is no reason they should not be strongly constrained to account accurately for our own first-person experiences, aswell as the evidence from subjects’ reports.
• If we find a theory that fits the data better than any other theory of equal simplicity, we will have good reason to accept it.
• If the theory leads to the engineering of systems that demonstrate an engineering advantage then that will be a success!
Weekly QUEST Discussion Topics, Apr 19
This week’s discussion will focus on Capt Amerika’s prep for his interaction with Ray Kurzweil of Google, particularly his views on the Singularity. Please see the attachment for a review of Kurzweil’s book by Paul Allen, as well as a response from Kurzweil to be used as a starting point for the discussion.
Weekly QUEST Discussion Topics and News, April 12th
This week, we are happy to have some colleagues from Rome NY lead the discussion. Please see below for a brief description of the subject matter.
Cogent Confabulation: From Statistical Inference to Neuromorphic
Architectures
Cogent confabulation originates from the maximum likelihood estimation
method, a branch of statistical inference. After simplification in
formulations, optimization in algorithmic implementation and adaptation
to real-world applications, the structure of the confabulation method
becomes analogous to the human brain in many operational aspects. The general term, “inference method”, has been used by many academic research groups and on-going government research programs. At AFRL, we have done in-depth research on confabulation models for natural languages and just started the research on special-temporal vehicle behavioral modeling.
Weekly QUEST Discussion Topics and News, April 6th
The meeting will start with an open discussion to allow people who attended the seminar Capt Amerika gave on Wednesday to ask any questions about the content. Any question from the broad overview down to the details is welcomed and far more time can be spent on the answers than the seminar forum provided. This review of the seminar presentation leads to a more detailed discussion on our recent compilation of tenets for artificial consciousness with an emphasis on those that capture what we know about the phenomenal aspects of the conscious representation (the hard problem).
Weekly QUEST Discussion Topics and News, Mar 29th
1.) Topic is the upcoming AFRL commander’s seminar series – below is my abstract –what I need from our AFRL colleagues is one slide and talking point notes on the implication of what we are doing to your day jobs within AFRL (Derriso – slide from the dissertation, Tsou – slide to capture the recent autonomy proposal, Young – slide if you are interested in aligning your recent proposal to a quest influence, Jared – a slide on maybe you work in category theory as a theory for ATR?, Ox – a slide associated with ongoing AFIT work, Trevor – maybe a sldie from you since we know AFRL/CC is interested in fostering improved AFIT/AFRL connections?- or we could make a single slide to capture the Birrer / Dube / Trevor work – Rome confabulation slide, anyway my idea is the last part of the seminar will be a discussion of these slides:
Qualia Exploitation of Sensing Technology (QUEST)
Presentation by Steve ‘Capt Amerika’ Rogers
AF Senior Scientist for Automatic Target Recognition and Sensor Fusion
Abstract:
Understanding intelligence is a classic problem that both engineers and philosophers have considered. Great advances have been made in generating non-trivial behavior by analyzing vast amounts of data (Data Driven Artificial Intelligence, DDAI), powered by Statistical Learning, Optimization and Pattern Analysis. Current solutions do not ‘understand’ the directions/advice they provide. What is the implication when they recommend your next movie or book on Amazon? Natural intelligent systems produce appropriate behavior as a result of interactions between simple systems not just declarative knowledge.
An AFRL group has been conducting weekly seminars in an attempt to define new innovative approaches in sensing based on solutions consisting of two interactive systems (a subconscious and a conscious system). No one knows what consciousness is, why we have it or how do biological processes create it. The question the QUEST seminars address: ‘Are there engineering characteristics of the interacting subconscious system and consciousness that can be defined providing a framework for achieving robustness in computer based sensor data processing?’
Intelligent agents can pursue their goals in complex environments by making informed decisions and adapting to situations not directly specified by the designer. We have termed this the ability to respond appropriately to the ‘unexpected query’ and consider it necessary for autonomy.
Google and Amazon are examples of the nexus between Data Driven AI and Interacting agents. Their power is the result of Data Driven AI AND their ability to exploit ‘closed loop’ interactions with their environment. Colonies of Ants or the systems of Google/Amazon consist of many modules (agents) to generate the desired result. Many of the agents are the traditional DDAI solutions (classifiers, clustering algorithms). It is the integration into a SYSTEM AND the coupling of the resulting system with the rich ENVIRONMENT that creates the intelligent behavior. Intelligent behavior is a property of a system in an environment.
2.) A revisit to the tenets at the core of our theory of consciousness –
Weekly QUEST Discussion Topics and News, Mar 22nd
Topics this week are:
1.) Last week I sent an email to our Math – Theory of consciousness subgroup encouraging them to look to the current approaches to the mathematics being used for natural language understanding – my thought was that since Qualia are communicated via language representations that try to capture the meaning of a phrase (not the semantics although that has to be subsumed) have to be attempting to capture a representation that aligns with meaning – that email prompted a response from kirk s along the lines of he was believing I was requesting a mathematical theory of abstraction – due to our need to generate plausible narratives – (possibly using induction, inference, …, with feedback to ensure coherence) – that email is extremely insightful and I think should be discussed – the words ‘ a theory of abstraction’ is exactly what I believe we need in the sense of abstraction is all about trying to ‘chunk’ stimuli into the simplest explanation = meaning.
2.) The second topic is the Searle review of the Koch book from the NY times book review – he raises several objections that are worth us understanding – after my conversation with him last week I’m hoping to provide you my read of many of his concerns. We will also discuss the Koch response to the review and then the Searle response to that response.
3.) The last topic is the upcoming AFRL commander’s seminar series – I was able to slightly delay my commitment to do a seminar but the opportunity is coming back up in about a week – below is my current abstract – happy to take comments back AND what I need from our AFRL colleagues is one slide and talking point notes on the implication of what we are doing to your day jobs within AFRL (Derriso – slide from the dissertation, Tsou – slide to capture the recent autonomy proposal, Young – slide if you are interested in aligning your recent proposal to a quest influence, Jared – a slide on maybe you work in category theory as a theory for ATR?, Igor – if you are willing to align any of your work to quest a slide on your stuff with speaker notes, I’ve requested a slide from the group in Rome doing neuromorphic confabulation also, Ox – a slide associated with ongoing AFIT work, Trevor – maybe a slide from you since we know AFRL/CC is interested in fostering improved AFIT/AFRL connections?- or we could make a single slide to capture the Birrer / Dube / Trevor work – anyway my idea is the last part of the seminar will be a discussion of these slides:
Qualia Exploitation of Sensing Technology (QUEST)
Presentation by Steve ‘Capt Amerika’ Rogers
AF Senior Scientist for Automatic Target Recognition and Sensor Fusion
Abstract:
Understanding intelligence is a classic problem that both engineers and philosophers have considered. Great advances have been made in generating non-trivial behavior by analyzing vast amounts of data (Data Driven Artificial Intelligence, DDAI), powered by Statistical Learning, Optimization and Pattern Analysis. Current solutions do not ‘understand’ the directions/advice they provide. What is the implication when they recommend your next movie or book on Amazon? Natural intelligent systems produce appropriate behavior as a result of interactions between simple systems not just declarative knowledge.
An AFRL group has been conducting weekly seminars in an attempt to define new innovative approaches in sensing based on solutions consisting of two interactive systems (a subconscious and a conscious system). No one knows what consciousness is, why we have it or how do biological processes create it. The question the QUEST seminars address: ‘Are there engineering characteristics of the interacting subconscious system and consciousness that can be defined providing a framework for achieving robustness in computer based sensor data processing?’
Intelligent agents can pursue their goals in complex environments by making informed decisions and adapting to situations not directly specified by the designer. We have termed this the ability to respond appropriately to the ‘unexpected query’ and consider it necessary for autonomy.
Google and Amazon are examples of the nexus between Data Driven AI and Interacting agents. Their power is the result of Data Driven AI AND their ability to exploit ‘closed loop’ interactions with their environment. Colonies of Ants or the systems of Google/Amazon consist of many modules (agents) to generate the desired result. Many of the agents are the traditional DDAI solutions (classifiers, clustering algorithms). It is the integration into a SYSTEM AND the coupling of the resulting system with the rich ENVIRONMENT that creates the intelligent behavior. Intelligent behavior is a property of a system in an environment.
