I believe that Zoox, Cruise, Waymo, and Tesla all use these techniques.

Also my dog does not consider the Roomba to be alive.  She performed some 
experiments.

<https://arxiv.org/pdf/2106.08417v3.pdf>
arxiv.org<https://arxiv.org/pdf/2106.08417v3.pdf>
[X]<https://arxiv.org/pdf/2106.08417v3.pdf>

On May 29, 2023, at 11:01 AM, Russ Abbott <russ.abb...@gmail.com> wrote:


I saw that Rodney Brooks video. He claimed that transformer-based software has 
no semantic content. I think that's an exaggeration. The semantic content is 
defined by the token embeddings. So many of the explanations of token 
embeddings overcomplicate the basic idea. Look up 
wordToVec<https://www.google.com/search?q=word-to-vec+&tbm=isch&ved=2ahUKEwju7IP4i5v_AhUEK0QIHbXrDycQ2-cCegQIABAA&oq=word-to-vec+&gs_lcp=CgNpbWcQAzIECCMQJzIECAAQHjIECAAQHlD0EVj0EWDpGWgAcAB4AIABWogBrwGSAQEymAEAoAEBqgELZ3dzLXdpei1pbWfAAQE&sclient=img&ei=S-Z0ZK6bDITWkPIPtde_uAI&bih=956&biw=1781&cs=0&rlz=1C1RXQR_enUS1008US1008#imgrc=aSLVbcgBsmbHKM>
 and read some of the articles. Word-to-Vec was around before transformers. But 
transformers are based on that idea. (One of the keys to transformers is that 
the embedding space, including the features themselves, is generated as part of 
the training.) The embedding of all tokens in the GPT embedding space is the 
semantics. It's amazing the extent to which that idea can be pushed and the 
results LLMs produce!

-- Russ


On Mon, May 29, 2023 at 10:13 AM Jochen Fromm 
<j...@cas-group.net<mailto:j...@cas-group.net>> wrote:
Yes, Rodney Brooks said something similar. He said "GPTs have no understanding 
of the words they use, no way to connect those words, those symbols, to the 
real world. A robot needs to be connected to the real world and its commands 
need to be coherent with the real world. Classically it is known as the 'symbol 
grounding problem""
https://rodneybrooks.com/what-will-transformers-transform/

One could argue that this form of connectedness and embeddedness leads 
eventually to self-awareness. First physical embeddedness, then social 
embeddedness and finally self-awareness

1. Physical Embeddedness:
Agents who are embedded in a physical world are aware of the world and move in 
it. To be embedded they need to be embodied. Embeddedness leads to a grounding 
and a unique point of view
https://iep.utm.edu/husspemb/

2. Social Embeddedness:
Agents who are embedded in a world of social actors are aware of other agents 
in the world and interact with them
https://mitpress.mit.edu/9780262518581/the-new-science-of-the-mind/

3. Self-Awareness:
Agents who are embedded in two worlds, the physical world and the world of 
language become aware that they are actors in a world of social actors by 
creating a link between the embodiment in the physical world (the body) and the 
embodiment in the world of language (the name or I)

-J.


-------- Original message --------
From: Russ Abbott <russ.abb...@gmail.com<mailto:russ.abb...@gmail.com>>
Date: 5/29/23 7:08 AM (GMT+01:00)
To: The Friday Morning Applied Complexity Coffee Group 
<friam@redfish.com<mailto:friam@redfish.com>>
Subject: [FRIAM] A distinguishing feature of living entities

While watching my two little dogs run around our house, it struck me that a 
feature that distinguishes living from non-living entities is the apparent 
effortlessness with which living ones navigate the world. Imagine how difficult 
it would be to build a robot that could navigate the world so effortlessly. To 
make the comparison a bit simpler, imagine how difficult it would be to build a 
robotic cockroach.

When I asked ChatGPT whether anyone has built a robotic cockroach, it came up 
with these examples. (I haven't checked to see whether these are real projects.)

  *   DASH: The Dynamic Autonomous Sprawled Hexapod (DASH) robot, developed at 
the University of California, Berkeley, was inspired by the rapid locomotion of 
cockroaches. It has six legs and can move quickly on various terrains using a 
simple control mechanism.

  *   Harvard RoboBee: Although not specifically modeled after a cockroach, the 
Harvard RoboBee project aims to develop small, insect-like robots. These tiny 
flying robots are inspired by the mechanics and flight capabilities of insects 
and demonstrate similar agility and maneuverability.

  *   iSprawl: The iSprawl robot, developed at the University of California, 
Berkeley, was inspired by cockroaches' ability to squeeze through small spaces. 
It uses a compliant body design and six legs to navigate tight and cluttered 
environments.

  *   VelociRoACH: Developed at the University of California, Berkeley, the 
VelociRoACH is a fast-running robot designed to mimic the high-speed locomotion 
of cockroaches. It utilizes a legged design and has demonstrated impressive 
speed and agility.

These mainly explore locomotion. Besides locomotion, cockroaches notice when 
someone enters an area where they are exposed. They quickly scuttle off to some 
hiding place. How do they sense the presence of a new being? How do they know 
where the hiding places are? How do they know how to move in the right 
direction? How do they know how to avoid small obstacles and fires? Etc.

One can argue that these capabilities are hard-wired in. But that doesn't make 
it any easier. These are still capabilities they have, that would be a 
challenge to build.

I became amazed at how well-connected living entities are to their 
environments. They quickly and easily extract and use information from their 
environment that is important to their survival.

Man-made robots have nowhere near that level of embeddedness and environmental 
integration.

Was it Rodney Brooks who said that we should build that sort of connectedness 
before worrying about building intelligence into our robots? Today that struck 
me as an important insight.
-- Russ Abbott
Professor Emeritus, Computer Science
California State University, Los Angeles
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