[Dee]

Everybody knows that machine learning (ML) is a part of AI,


ML is about  learning new things, it's like the learning process of a new baby,


so what else should be listed in AI category? instincts? let's discuss 

[LOCKSUIT]

Oh I said this somewhere before :-)

You could literally say read all my 3773 posts I've made, skip the rest of he Forum, and there you have it, just 3773 posts and you've seen everything I've seen in 5 years of nonstop AGI research. And I have said all I know as well. The most recent posts of mine are the most interesting.

It's not so much the instincts at all, no. It is the thoughts, simulating the real world of what happens after x. The brain records frequency of 'words' and 'phrases' appearing after the last number of letters, so has a probability prediction. It does use rewards on nodes. See my big movie's hierarchy net to understand. >>>>>>> https://aidreams.co.uk/forum/index.php?topic=14490.15



AI runs on predictions to Generate the Future. AI is all about Generative Models.

Applications:
filling in holes in images
extending the image at the sides
frame rate increase
predicting next image frames
super-resolution
2D-to-3D translation
style modification
object segmentation
object importance
object frequency
recognition of what an object in a image/text/etc is or what entails it
and same for text, music, robotics; extending sentences/video length or res or sides, filling in words, translation, segmentation, summarization, importance of a text, etc
data compression
learning to walk etc, solve rubiks cubes, etc
self-repair its body or swarm
optimal utility utilization
research, development, repeat
image2text translation
seeing around corners in a video
map navigation
related-data generation
take on a voice for the text spoken
physics simulation/modelling using a video-model instead of any physics functions
text2code translation
playing games and improving as plays longer ones
doodles2images
3D printing cells etc, modyfing cells
categorical cluster translation meanings
depth prediction
noise filtering
adaption
playing against itself/its own data it regurgitates
evolutionary algorithms and monte carlo search variants
robustness against typos, time delays, alternative words, unknown words, missing words, added words, or ground (robust animal-walker by Boston Dynamics) or robust humanoid in a sim after learning to use physics methods in 3D space to imitate human sequence of motion captures
anything that involves time/memory and can use context to aid in short cuts
all problems in life can be described in text or video alone
an AGI Evaluation

[LOCKSUIT]

more:

White-Box artificial neural nets
Online Learning
One-Shot Learning
Scaleable
Manageable
Vizualizations
Simple+biologically-correct math/schema
Infinite SuperResolution & Summarization & Fillin
Unsupervised Learning everywhere with a new type of Cost, advanced RL, and teaching (Supervised Learning)
One Master Algorithm
Find deep patterns/relationships in data
Discovers Answers
Sequence Prediction
LSTM abilities
Parses
generalizes/inference
Conversational intelligence, Knowledge about the world with Goal-Directed Desires pending to be Seen Come True
A clear cut understanding of what/how/why/when/where AGI and ASI

What they mostly have lol:
Black-Box GOFAI
Offline Learning
Multi-Shot Learning
Unscaleable
Unmanageable
Univisualizable
Complex+artificially-made math/schema
Finite SuperResolution & Summarization & Fillin
Supervised Learning everywhere with a new type of Gain, narrow RL, and studying (unsupervised Learning)
Many Narrow Algorithms
Hide shallow anomalies/independencies in information
Forget Questions
Static Expectation
CNN disabilities
Construct
overfit/abduction
Introvert intelligence, info about the surroundings with undirected hangovers Coming True
An unclear understanding of what/how/why/when/where AGI and ASI

Refined:
White-Box artificial neural nets
Online Learning
One-Shot Learning
Scaleable
Manageable
Vizualizations
Simple+biologically-correct math/schema
Infinite SuperResolution & Summarization & Fillin
Unsupervised Learning everywhere with a new type of Cost, advanced RL, and studying/teaching (Supervised Learning/Transfer Learning)
One Master Algorithm
Find deep patterns&anomalies/relationships&independencies in data/etc
Discovers Answers
Sequence/Static Prediction/Expectation
LSTM abilities
Parses/construct
generalizes/inference&SomeAbduction
Conversational intelligence, Knowledge about the world with Goal-Directed Desires pending to be Seen Come True
A clear cut understanding of what/how/why/when/where AGI and ASI

[LOCKSUIT]

moreee:

attention types
recognition
thinking
node cost
flexibleness
generalness
compression
senses=actions
language=images
story telling
satisfaction
generative
predictor using past experience
reward transfer
links
big data
big model
dropout
revisement/update of nodes/friend connections
unsupervised learning
parallel sequences
hierarchy
heterarchy
feedback scientific method
Self-Attention in Transformers
self-regeneration
physics, self-organization
propagation of waves in hierarchies aligned nodes
clustering by k-means
entailment
translation
sumarization
segmentation
task CHANGE by energy
AGI=simple/efficient
re-use of hierarchies
adaption
adjustment
update
revising
repair
replication
emergence
candidates
probability of entailment/translation

[infurl]

Everybody knows that machine learning (ML) is a part of AI,
ML is about  learning new things, it's like the learning process of a new baby,
so what else should be listed in AI category? instincts? let's discuss 

natural language understanding

[HS]

I like to combine a succession of abilities into a self-perpetuating loop. A body with sensible needs, elicits and morphs emotions which give reasoning something to do, thereby changing the body/environment, which interacts with the body in novel ways, producing a new melange of emotions and so on. Awareness hovers, oversees, and can exert a little influence if the process is having trouble. Once a self-sustaining sequence of steps is discovered, I think each step should be broken apart on to series of constituents, until you have a list of thousands of little steps which are simple enough for us to make them individually. So, get your big concept that works, like an engine, then figure out the details.

[HS]

Also, I don’t think all these various skills make AGI. The essence of AGI is a process which can grow skills as needed. As long as there’s a good loop happening, which has a high potential expansion pack standing at the ready, then the thing should be firm enough to require self optimization, yet flexible enough to create the optimal intelligence for accomplishing the self optimizations.

[8pla.net]

My first thought was...

robotics

Yet someone...

said this somewhere before 

Then someone else mentioned...

potential

which provides for the...

expansion

of A.I.

[yotamarker]

hypergamy negation. other wise it wouldn't survive.
and death comprehention

[Zero]

From https://aidreams.co.uk/forum/index.php?topic=12723.msg49997#msg49997




state
   type of thoughts
      concept
         abstract
         concrete
         instance
      conjecture
      decision
      definition
         term
         meaning
         synonym
            nuance
            context
         antonym
            nuance
            context
      explanation
         fact
         cause
         consequence
         context
      hypothesis
      idea
      logical argument
      logical assertion
      mental image
      percept
         perceptual component
      premise
      proposition
      syllogism
      thought experiment
   content of thoughts
      argument
      belief
         certainty
         probability
         bayesian network
      data
      information
      knowledge
         theoretical
            cause consequence chain
         practical
            know how to
      schema
   memory
      implicit
         procedural
         perceptual
      explicit
         episodic
         semantic
   goal
      requirement
      subgoal
      goal-to-current path
         state event state
         path criteria
   association
   plan
      step
   language
      vocabulary
      grammar
   emotion
      attraction
      repulsion
   thought frames
      active frame
      suspended frame
process
   thought frame handling
   generalizing
      pattern recognition
      pattern label creation
   associating
   focusing
      unexpected event noticing
   reasoning
      abductive reasoning
      analogical reasoning
      deductive reasoning
      inductive reasoning
      moral reasoning
      probabilistic reasoning
   volition
      decision making
         goal-to-current pathfinding
         path comparing
      acting
      problem solving
   planning
   learning
   percepting
   interpreting
      context targeting
      choosing role set
      role dispatching
   imagining
      scene space creation
      scene element evocation
      scene evolution
   memorizing
   remembering
   comparing
eventact
   frame
      open thought frame
      switch thought frame
      close thought frame
   goal
      find goal-to-current path
   percept
      link new percept to set of percepts

[Dee]

Everybody knows that machine learning (ML) is a part of AI,
ML is about  learning new things, it's like the learning process of a new baby,
so what else should be listed in AI category? instincts? let's discuss 

natural language understanding

seems NLU is still kind of learning(?)


i mean stuff in AI category those are not about learning (ML), like instincts

[Dee]

From https://aidreams.co.uk/forum/index.php?topic=12723.msg49997#msg49997

state
   type of thoughts
      concept
         abstract
         concrete
         instance
      conjecture
      decision
      definition
         term
         meaning
         synonym
            nuance
            context
         antonym
            nuance
            context
      explanation
         fact
         cause
         consequence
         context
...

wow this category tree is detailed

[infurl]

seems NLU is still kind of learning(?)

That's debatable. 
https://en.wikipedia.org/wiki/Innateness_hypothesis

i mean stuff in AI category those are not about learning (ML), like instincts

Yes I know what you meant and I believe that the facility for natural language understanding is built-in. It's one of those instincts that you're referring to.

[infurl]

Here's an interesting article on this subject. It considers how much information could actually be built-in to a human brain, given the constraints of the capacity of the human genome. It's not such an easy question to answer.

http://www.wiringthebrain.com/2020/01/how-much-innate-knowledge-can-genome.html

[Art]

There are several videos here and the panel discussion from many of the great, innovative minds was quite interesting.

https://interestingengineering.com/neuralink-how-the-human-brain-will-download-directly-from-a-computer