More about Dr. Karl Firston, Chief Scientist at Verses AI

[John F Sowa]

After a bit of searching, I found more info about Verses AI and their new chief scientist.  I like the approach they're taking:  putting more emphasis on natural thinking process in neuroscience.  And their new chief scientist has publications that would lead them in that direction.  The ideas look good, and I would recommend them.  But I don't know how far he and his colleagues have gone in implementing them, or how long it will take for anything along those lines to be running in a practical system.

However, it's unlikely that any company would hire somebody as chief scientist without a considerable amount of prior work.  And I doubt that any company would make an announcement in a full-page ad in the New York Times unless they already had some kind of prototype.

Following is a list of theoretical publications by Karl Friston:  https://www.fil.ion.ucl.ac.uk/~karl/#_Computational_neuroscience

None of them describe an implementation.  But it's possible that he and his colleagues (and/or graduate students) have implemented something that Verses AI wanted.

And by the way, one reason why I like this approach is that it's related to methods that Peirce was suggesting.  He is famous for his innovations in logic, but he also had many ideas about biosemiotics and reasoning methods in living things down to the level of insects and plants.  He even mentioned possible aliens in outer space as agents that might continue research if humans didn't survive.

Although I don't know whether Verses AI will succeed with their plans, I believe that the direction they're taking is more promising than anything OpenAI or Google is doing.  I believe that any design that ignores neuroscience is a dead end for AGI.

John

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An excerpt from https://www.verses.ai/press-2/vers-karl-friston

“It is with great enthusiasm and excitement that we welcome Karl Friston to VERSES as our Chief Scientist,” said Gabriel René, Founder, and CEO of VERSES. “Dr. Friston’s breakthrough work in neuroscience and biologically-inspired AI, known as Active Inference, aligns beautifully with our vision and mission to enable a “smarter world” where AI powers the applications of the 21st century. As the originator of this principle, it is only fitting that Karl has a significant role in VERSES AI research and development all the way through their applied uses in product commercialization.”

Friston who was ranked #1 most influential neuroscientist in the world by Semantic Scholar in 2016 has had an illustrious and decorated scientific career. He became a Fellow of the Royal Society in 2006 and The Royal Society of Biology in 2012, received the Weldon Memorial Prize and Medal in 2013 for his remarkable contributions to mathematical biology and was elected as a member of EMBO in 2014 and the Academia Europaea in 2015. He was the 2016 recipient of the Charles Branch Award for unparalleled breakthroughs in Brain Research and the Glass Brain Award from the Organization for Human Brain Mapping. He holds Honorary doctorates from the universities of York, Zurich, Liège, and Radboud University. 

“I am delighted and honored to join VERSES. I have seldom met such a friendly, focused, committed, and right-minded group of colleagues. On a personal note, my appointment as Chief Scientist is exactly the kind of dénouement of my academic career I had hoped for – a dénouement that marks the beginning of a new and exciting journey of discovery and enabling.” said Karl Friston.

 

[Ricardo Sanz]

Hi John, 

I think I know enough about the "VERSES alternative" to make a comment on this.

 

Friston's work is ok. Neuroscience, statististics and optimal control. Good, ol' classic math.

VERSES' narrative is classic bullshit. Not "breakthrough" bullshit; just classic bullshit.

Two references:

[1] Frankfurt, H. G. (2005). On bullshit. Princeton University Press.

[2] Sokal, A. D., & Bricmont, J. (1998). Fashionable nonsense: postmodern intellectuals’ abuse of science. Picador.

In my opinion, anthropocentrism, the intelligence=brain fallacy, and biomesmerization are the biggest roadblocks in the way to AGI.

Best,

R.

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Ricardo Sanz

Head of Autonomous Systems Laboratory

Escuela Técnica Superior de Ingenieros Industriales

Center for Automation and Robotics

Jose Gutierrez Abascal 2.

28006, Madrid, SPAIN

ricard...@upm.es

http://www.aslab.upm.es/~sanz

+34 913 36 30 61 | +34 630 89 11 63

Aviso / Disclaimer

[Dan Brickley]

For an implementation-oriented survey see 

https://github.com/BerenMillidge/Predictive_Coding_Papers and in general work under “predictive processing” and “predictive coding” banners

Also this book has PDFs available;

https://direct.mit.edu/books/oa-monograph/5299/Active-InferenceThe-Free-Energy-Principle-in-Mind and also gets pretty specific eg ch8 on continuous time dynamical systems representation, see 

https://doi.org/10.7551/mitpress/12441.003.0012

Dan

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[John F Sowa]

I agree with Mihai Nadin "that AGI is yet another of those impossible to achieve tasks."   I have repeatedly said that it won't be achieved in the 21st C, but I won't make any predictions about the 22nd.   So far, nobody has produced the slightest shred of evidence for any kind of AGI any sooner.  Best summary of the issues:  "AGI is 30 years in the future, always was and always will be."    There are still some diehards who claim that the prediction from the year 2000 will come to pass in the next 6 years, but the hopes for generative AI are already dying.  --  But there are many useful applications for better natural language interfaces to all kinds of systems, not just AI.

Dan Brickley dug up some excellent references on predictive coding, and Karl Friston is one of the pioneers in the field (see below).  A recent book (2022) from MIT Press with a foreword by Friston covers the field:  "Active Inference: The Free Energy Principle in Mind, Brain, and Behavior."  Chapters of that book can be downloaded for free.   Appendix C has an annotated example of the Mathlab code.

I believe that this is the approach and the software techniques that Verses AI has adopted.  I don't know how well Friston and his colleagues can develop this approach, but I strongly suspect that some of the co-authors and/or their colleagues and students will be working with them.  However, practical applications always take more time and more investment than was predicted.  (I worked at IBM R & D for 30 years, and I know the issues from close observation and participation.)

Ricardo Sanz:  Friston's work is ok. Neuroscience, statististics and optimal control. Good, ol' classic math.  VERSES' narrative is classic bullshit. Not "breakthrough" bullshit; just classic bullshit. In my opinion, anthropocentrism, the intelligence=brain fallacy, and biomesmerization are the biggest roadblocks in the way to AGI.

Neuroscience is much broader than anthropomorphism.  Living things from bacteria on up are far more successful in complex behavior than any of the latest and greatest driverless cars.  Furthermore, very few of the people who have been working on generative AI know anything about neuroscience or the other branches of cognitive science.  Therefore, none of the work in those fields could deter (or inspire) them.  And it shows.

I won't defend the claims by Verses AI unless and until they come up with software that implements their promises.   But I love their criticisms of generative AI.  I can't see how anybody could claim that it's on a path toward AGI.

John

 

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From: "Dan Brickley" <dan...@danbri.org>

[Mike Peters]

Thanks, John, for starting this discussion and thanks, Dan, for the excellent reading references. 

The approach by Verses is broadly correct. 

This is a very interesting article from Verses

https://www.verses.ai/blogs/executive-summary-designing-ecosystems-of-intelligence-from-first-principles

It is the same approach I have also used to build Pipi 9. And it works.  The main difference is that Pipi is a piece of software running on a server containing hundreds of interacting agents. It also sets out to provide a Complex Adaptive System (CAS) as a SAAS platform to host SAAS CAS Applications.

https://www.blog.ajabbi.com/p/pipi.html

I hope to have Pipi up on a public-facing website later this year so people can play with the demo version and give me lots of feedback.

I wish the Verses team the best of luck.

Mike Peters

-----------------------------------

Ajabbi

 

PO Box 902

Invercargill 9840

New Zealand

 

Software Architecture www.blog.ajabbi.com

[John F Sowa]

Thanks, Mike.   

I'm glad to see that other subscribers agree.  These millipedes have many more shoes to drop.  The note I just sent shows that Google researchers are also discovering the limitations of LLMs.

Thanks for the references below.   In my previous note I sent a link to the Verses article.  I also like the idea of running "hundreds of interacting agents".  I have seen other systems that do that.  They can run on a laptop and scale up to a supercomputer with performance that scales almost linearly with the number of CPUs.

Your Pipi and Ajabbi systems sound like reliable software that would be more secure and practical than anything that depended on LLMs for anything other than a user interface.

John

 

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From: "Mike Peters" <mi...@redworks.co.nz>
Sent: 12/31/23 3:44 PM
To: ontolog-forum <ontolo...@googlegroups.com>
Subject: [ontolog-forum] Re: More about Dr. Karl Firston, Chief Scientist at Verses AI

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