[Stolen from @sharkmime] To help make connections: name things that interest you but aren't in your profile, as tags so they are searchable. Then boost/repeat its instructions so others know to do the same.
#ClimateChange #Science #InfoSec #InfoSecButOnlyAsAPopcornEatingTourist #NewZealand #NZPol #Pol #BESS #Equality #SocialJustice #ParkRun #MTB #eMTB #Bafang #CYC #CYCPhoton #Cycling #NotJustBikes #SolarPV #LessIsMore #TheBugle #DanCarlin #DogsOfMastodon #Raglan
#TheBugle #Aoteara #JamesNokise
#cyc
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Питер Норвиг: автор лучшего в мире учебника по ИИ
Питер Норвиг (Peter Norvig) — выдающийся учёный, один из отцов современной ИИ-разработки. После сингулярности ИИ точно оставит его в живых в знак благодарности. Норвиг не только хороший программист, но и теоретик программирования, учёный и преподаватель, в длинном резюме перечислено 58 статей, а количество цитирований на сегодняшний день составляет 78 830 . Основное признание Норвиг получил как автор учебника «Искусственный интеллект: современный подход» , который в наше время считается самым популярным учебником по ИИ в вузах. Эта фундаментальная работа претерпела уже четыре переиздания.
https://habr.com/ru/companies/ruvds/articles/809241/
#ruvds_статьи #Питер_Норвиг #фильм_Сеть #учебник #ИИ #вузы #JScheme #Scheme #Java #Prolog #Lisp #Franz #LispWorks #парсер_натуральных_языков #Cyc #НАСА #Deep_Space 1 #Remote_Agent #самовосстановление
ХабрПитер Норвиг: автор лучшего в мире учебника по ИИПитер Норвиг (Peter Norvig) — выдающийся учёный, один из отцов современной ИИ-разработки. После сингулярности ИИ точно оставит его в живых в знак благодарности. Норвиг не только хороший программист,...
Cade Metz’s NYTimes article on Doug Lenat, featuring quotes from Ken Forbus and @garymarcus. The connection between the game Traveller and #Cyc is interesting and is new to me.
Douglas Lenat, Who Tried to Make Computers More Human, Dies at 72 https://www.nytimes.com/2023/09/04/technology/douglas-lenat-dead.html
The New York Times · Douglas Lenat, Who Tried to Make Computers More Human, Dies at 72
This was an EXTREMELY interesting paper on what modern LLMs can learn from older older symbolic AI / expert system approaches to improve the validity of what those statistical models generate on their own, using the Cyc system as the contrast to the modern systems.
arXiv.orgGetting from Generative AI to Trustworthy AI: What LLMs might learn from CycGenerative AI, the most popular current approach to AI, consists of large
language models (LLMs) that are trained to produce outputs that are plausible,
but not necessarily correct. Although their abilities are often uncanny, they
are lacking in aspects of reasoning, leading LLMs to be less than completely
trustworthy. Furthermore, their results tend to be both unpredictable and
uninterpretable.
We lay out 16 desiderata for future AI, and discuss an alternative approach
to AI which could theoretically address many of the limitations associated with
current approaches: AI educated with curated pieces of explicit knowledge and
rules of thumb, enabling an inference engine to automatically deduce the
logical entailments of all that knowledge. Even long arguments produced this
way can be both trustworthy and interpretable, since the full step-by-step line
of reasoning is always available, and for each step the provenance of the
knowledge used can be documented and audited. There is however a catch: if the
logical language is expressive enough to fully represent the meaning of
anything we can say in English, then the inference engine runs much too slowly.
That's why symbolic AI systems typically settle for some fast but much less
expressive logic, such as knowledge graphs. We describe how one AI system, Cyc,
has developed ways to overcome that tradeoff and is able to reason in higher
order logic in real time.
We suggest that any trustworthy general AI will need to hybridize the
approaches, the LLM approach and more formal approach, and lay out a path to
realizing that dream.
Doug Lenat died. RIP. #cyc #lispm #lispmachines #ai #commonlisp #cycorp
He started the Cyc project, using Lisp Machines as a development environment. The project is roughly since 40 years ongoing. Cyc was the dream of a large-scale knowledge base of common sense knowledge. One that has many ways of reasoning and making inferences. It used SubL a variant of Common Lisp.
Here is an old screen shot...
Getting from generative AI to trustworthy AI: What LLMs might learn from Cyc. ~ Doug Lenat, Gary Marcus. https://arxiv.org/abs/2308.04445 #GenerativeAI #AI #LLMs #Cyc
arXiv.orgGetting from Generative AI to Trustworthy AI: What LLMs might learn from CycGenerative AI, the most popular current approach to AI, consists of large
language models (LLMs) that are trained to produce outputs that are plausible,
but not necessarily correct. Although their abilities are often uncanny, they
are lacking in aspects of reasoning, leading LLMs to be less than completely
trustworthy. Furthermore, their results tend to be both unpredictable and
uninterpretable.
We lay out 16 desiderata for future AI, and discuss an alternative approach
to AI which could theoretically address many of the limitations associated with
current approaches: AI educated with curated pieces of explicit knowledge and
rules of thumb, enabling an inference engine to automatically deduce the
logical entailments of all that knowledge. Even long arguments produced this
way can be both trustworthy and interpretable, since the full step-by-step line
of reasoning is always available, and for each step the provenance of the
knowledge used can be documented and audited. There is however a catch: if the
logical language is expressive enough to fully represent the meaning of
anything we can say in English, then the inference engine runs much too slowly.
That's why symbolic AI systems typically settle for some fast but much less
expressive logic, such as knowledge graphs. We describe how one AI system, Cyc,
has developed ways to overcome that tradeoff and is able to reason in higher
order logic in real time.
We suggest that any trustworthy general AI will need to hybridize the
approaches, the LLM approach and more formal approach, and lay out a path to
realizing that dream.
With all this talk of #AI, I often wonder whatever happened to #Cyc.
OpenCyc seems to have been mothballed.
The full-blown Cyc project (assuming that's what this is, still) now seems to be selling itself as, like, AIaaS to giant corporations (and nobody else) -- with what degree of success, I know not.
sourceforge.netOpenCyc - Browse /OpenCyc 4.0 at SourceForge.netOpenCyc is the open source version of the Cyc(r) technology, the world's largest and most complete general knowledge base and reasoning engine. A…