CHATGPT won't ever be the same again after this

HUGE ANNOUNCEMENT, CHATGPT+WOLFRAM! You saw it HERE first! Dr. Wolfram is a renowned polymath who has made significant contributions to the fields of physics, computer science, and mathematics.
Pod version: podcasters.spotify.com/pod/sh...
Support us! / mlst
MLST Discord: / discord
Stephen's announcement post: writings.stephenwolfram.com/2...
OpenAI's announcement post: openai.com/blog/chatgpt-plugins
In an era of technology and innovation, few individuals have left as indelible a mark on the fabric of modern science as our esteemed guest, Dr. Steven Wolfram.
A prodigious young man too, Wolfram earned a Ph.D. in theoretical physics from the California Institute of Technology by the age of 20. He became the youngest recipient of the prestigious MacArthur Fellowship at the age of 21.
Wolfram's groundbreaking computational tool, Mathematica, was launched in 1988 and has become a cornerstone for researchers and innovators worldwide. In 2002, he published "A New Kind of Science," a paradigm-shifting work that explores the foundations of science through the lens of computational systems.
In 2009, Wolfram created Wolfram Alpha, a computational knowledge engine utilized by millions of users worldwide. His current focus is on the Wolfram Language, a powerful programming language designed to democratize access to cutting-edge technology.
Wolfram's numerous accolades include honorary doctorates and fellowships from prestigious institutions. As an influential thinker, Dr. Wolfram has dedicated his life to unraveling the mysteries of the universe and making computation accessible to all.
First of all... we have an announcement to make, you heard it FIRST here on MLST! ....
TOC
00:00:00 - Big announcement! Wolfram + ChatGPT!
00:02:28 - What does it mean to understand?
00:10:43 - Feeding information back into the model
00:17:04 - Semantics and cognitive categories
00:20:45 - Navigating the ruliad
00:28:34 - Computational irreducibility
00:35:38 - Conceivability and interestingness
00:40:38 - Human intelligible sciences

[@SzabolcsSzekacs]

I love how Stephen went exponential from explaining how ChatGPT develops a model to the computational structure of the universe behind what we can perceive in our physical world.

[@skierpage]

"What will you be wanting for dinner, Dr. Wolfram?" "From my principle of computational irreducibility, it necessarily follows that our brains are structures that can only perceive a subset of the ruliad graph theory underlying all computable realities, which would make predicting my future dietary wants impossible with the computational resources available in this universe; however my Wolfram language is close to generating a proof that neural firing is congruent with a cellular automata of sufficient complexity as explained in my book _A New Kind of Science_. So... fish and chips please."

[@ChatGPT1111]

It is quite elementary actually.

[@Inception1338]

​@@skierpagecheers!

[@jordanzothegreat8696]

@@skierpage hard disagree. Brilliant, yes. Trailblazer, yes. Wise? maybe not... can't predict the output were his words... he minimizes cellular automata and I'm fearful. 18:15

[@skierpage]

@@jordanzothegreat8696 I have no idea how your garbed comment relates to my joke.

[@Delta8Raven]

It only took 23 minutes for Wolfram to pivot from chatGPT and LLMs to the ruliad. This man has a one track mind and I love him for it.

[@TurnerRentz]

Agree

[@ChatGPT1111]

Indeed, he is a versatile individual.

[@thetruthserum2816]

GPT-5: "John..."

[@timeflex]

Will such a ruliad stay conform to the Incompleteness Theorems? And if yes (or no), how would such a Turing machine work?

[@mikeb3172]

AI can't do any serious computation, so why can any of these guys

[@jooky87]

I bought Wolfram’s book A New Kind of Science in 2001, and finally we are coming full circle to his ground breaking idea of computational irreducibility… bravo!

[@markryan2475]

The really remarkable thing about this interview is to hear Dr. Wolfram talk about something other than what he has created himself.

[@user-tg6vq1kn6v]

He did seem to bring everything back to his own stuff when left to talk long enough

[@jyjjy7]

He literally does hours long weekly sessions on the history of science and technology and another of general Q&A on his KZbin channel, but yes, that he finds the time to do so instead of just talking about his own superlative ongoing scientific achievements is indeed remarkable

[@mark_makes]

His work is extremely relevent to the conversation. It's an interview. He's the SME. This is to be expected.

[@user-tg6vq1kn6v]

Excellent, we are all correct

[@nneisler]

@@mark_makes He's not really a NLP guy

[@1fattyfatman]

Wish this was longer. Also appreciate the hosts allowing him to follow his thoughts as he presented them without silly interruptions.

[@zackzodiac1757]

Ni no no no no ji hum hum hum tá no gu tô gu! Tô no

[@henryleonardi5368]

That metaphor with the mosaic and fractal patterns was so interesting. Like discovering stuff before you have the "scientific history" to realize how useful it is

[@bujin5455]

I think this is one of the reasons that having industry experience before you attend college is profoundly useful. I had been in industry for a while before I pursued my CS degree, and when I got there I found everything profoundly interesting. My peers on the other hand were constantly asking questions like, "is this important?", "why do we need to know this?", etc. Of course the professors tried their best to answer these questions, to contextualize the importance of the subjects being explored, but the answers themselves met with similar apathy. In the end, it's very difficult to form a crystal, or pearl, without a starting structure to seed the process.

[@astilen5647]

Let me explain, they put pretty stones side by side instead of painting. Basically they made an AI with stone.

[@Hexanitrobenzene]

Yeah, it also reminded me of a Jordan Peterson lecture, where he said that our perception is shaped by our mental state and that reality is diferentiated into abstractions we call "objects" by the possible use cases.

[@bilbobagginssword3926]

Pandora’s Box IS open. Not metaphorically either, more like literally

[@onedaya_martian1238]

@@bujin5455 You observation is very, very accurate !!!

[@bujin5455]

I feel as though that interview could have been five times longer, and we wouldn't even have gotten the man warmed up.

[@justinwmusic]

I really do think that this WolframChatGPT feedback loop will be one of the main drivers allowing LLMs to transition into something that we perceive as AGI. "Attention is all you need". With its attention focused on unlimited, novel machine-generated data founded in deep computational understanding, provided as answers to its own questions, acquired at a speed limited only by available processing power, all models that don't have such resources (including the biological models called human brains) will be quickly left in the dust.

[@skierpage]

Maybe. It's still unclear that the combination can come up with a plan of attack to investigate an area and come up with a novel conclusion useful to human beings, as Wolfram says in the interview about theorem generation and cellular automata. But even if it only acts as a super-capable assistant to human research and development it will be hugely significant. "What is the chemical formula of a room-temperature superconductor that can be cheaply manufactured?" is my acid test, far more important than acing graduate-level exams or "Summarize as a poem."

[@yoyoclockEbay]

That's exactly what I was thinking

[@realist4859]

What an intro! And well deserved!

[@krasko6688]

It seems like I have low knowledge of how Wolfram is relevant to this field; what has wolfram done to be hailed with a intro like his?

[@bryankarsh9909]

One of the most fascinating hours I’ve spent in a long time. Thanks for putting this video together! My mind is blown in all the best ways.

[@erasmus9627]

This is such a profoundly important discussion. The implications of ‘emergence’ are both exciting and terrifying. Humanity has reached a critical crossroads.

[@awdsqe123]

And because of capitalism we don't have a choice. Instead billionares and corporations, that only see profits, are the ones chosing which road to take.

[@Alex-bl6oi]

I don’t know, it almost seems inevitable that these complex AI’s will be reverse engineered, copied, escape, or become open source.

[@Inception1338]

​@@Alex-bl6oioyu cannot steal the computational power that is needed though... That still requires some infra...

[@itsd0nk]

@@awdsqe123 The Bing Ai Chatbot is already a perfect example of how these companies have a financial incentive to forego safety in favor of speed, in an attempt to “get there first”. This will get progressively more dangerous as these systems become exponentially more powerful in short amounts of time.

[@cdreid9999]

​@@Alex-bl6oi ai tech isnt secret. It's a science. What you should worry about that noone is talking about is that google ms etcs information gathering capability just increased a hundredfold. Ms is putting their ai into all their products which means they can analyse your email, business and household finances etc

[@datasciyinfo5133]

My Meetup group was discussing Toolformer paper by Meta AI last week, and we were all saying how hooking up Wolfram Alpha to ChatGPT will be a game changer, and here it is already! Thanks for the video guys. Really concentrated concepts. Difficult to follow but fascinating. I am going to check out Wolfram’s other talks now.

[@Khari99]

Only Stephen Wolfram can go on a scientific rant like this and end it by saying "we didn't get deeply technical" lmao

[@lollihonk]

Take him for a longer interview 2-3h please. This would be gold.

[@tybowesformerlygoat-x7760]

When I was about 12 (1986) I wrote a program that I called Petri Dish, to simulate cellular activity. It had already been discovered a decade before (Conway's Game of Life), but it still blows my mind a bit that I had the idea for it at that age.

[@vikramreddy12]

😊

[@karenbolton9526]

Seems it’s a gatekeeper for gvt

[@DJWESG1]

That's what's great about the way we all perceive our reality. Some ppl are surprised when they produce the same things after receiving the same inputs. Observing the same reality.

[@ELECTR0HERMIT]

This was a great conversation. ChatGPT empowering already powerful luminaries such as Wolfram, we probably just have no idea how advanced and accelerated things are about to become

[@congareel]

A massive thank you to MLST for this video. This is the real conversation we all need to be aware of in a world where AI can grow our human understanding and an exciting time for the future of language and knowledge.

[@Woef718]

Now i can finnaly learn mathematics. Really most books are unreadable but being able to "talk" about mathematical topics really changes my learning approach. Heck I maybe gonna start bachelor pure mathematics again. Thanks bois.

[@williamparrish2436]

I keep thinking a similar thing. I could learn the math of quantum mechanics

[@M1kl00]

@@williamparrish2436 it's not that hard math wise

[@damightyom]

@@M1kl00 I guess? I never had Calc 1, I studied some on my own. I imagine I need Calc1, 2, and 3, Differential Equations, Abstract Algebra, Real Analysis, Linear Algebra? and more Physics too. That sounds like a lot to be honest. BUT... If I can ask questions and actually have a computer understand them it all sounds possible.

[@M1kl00]

@@damightyom you need calc and DEs for anything in physics. Imo you don't really need to study real analysis and abstract algebra. Linear algebra however is the language of quantum mechanics pretty much. I recommend strangs book on it

[@damightyom]

@@M1kl00 That's good to know, thank you!

[@ozziepilot2899]

How nearly one hour seemed to go very fast. This was an amazing interview.

[@itsd0nk]

It’s interesting that Moore’s law is kind of back up and running in a new way now with AI deep learning models in the past few years. It had finally started to plateau around 2013-2015, compared to the yearly leaps during the 70’s, 80’s, 90’s and 2000’s. Performance and power only seemed to be incremental each year or two over the past decade and a half really, rather than the exponential leaps we saw every single year in the 90’s and 2000’s. But now AI is finally a new paradigm of similar growth, if not even more exponentially increasing than the traditional transistor/compute power growth. It’s scary to imagine where we will be with it in just two years from now.

[@garethbaus5471]

AI, at least in its current form is highly dependent on having a lot of computational power.

[@pilotwolfram6192]

I started using Mathematica around 1994. I was pressured by a couple of physicists to use it when I started a job in R&D. Best tool ever for modeling and analysis. I still use it today.

[@refinery.studio]

That was one fucking hell of an introduction. And he deserves every bit of it.

[@ajarivas72]

First time I used Mathematica was in August 1995. I fell from the chair when I saw the calculation of sqrt(2),

[@Mutual_Information]

This channel picks such good guests. Well done!!

[@Think4aChange]

So much respect! Bravo Sir for all your incredible contributions. Bravo to you and your team!

[@mfu9943]

Discovered this amazing channel through this interview. Thanks guys for doing it.

[@Anders01]

Amazing! Before I listen to the whole presentation what came to me is that ChatGPT 4 (and beyond) getting access to directly executing Wolfram Language code and use Wolfram Alpha seems extremely powerful. This will be interesting to see where it goes.

[@chrisreed5463]

The singularity. But a very weird one, where the AI isn't sentient (most likely) and has odd deficits. The question 'is a model perfect?' is the wrong question, the right question is: Is it useful? (If I can twist a physics statement into the world of AI.)

[@bernhardd626]

The most extreme form of how "simple" rules created complex things is life.

[@nhatmnguyen]

Dr. Wolfram is based and deserve at Turing Prize.

[@riahmatic]

He would try to rename it the Wolfram Prize

[@sb_dunk]

For what specifically?

[@bjpafa2293]

It's naïveness not to recognize the Berkeley code, his beginning s, much later, Wolfram Alpha as a baby... Maybe you didn't live that exponentially, like SpaceX when it was a crazy idea only...

[@ChatGPT1111]

I am not impressed. He exaggerates the threat of AI and Chat GPT.

[@GarfieldSaunders]

His level of knowledge is on par with a high school AP teacher

[@Georgesbarsukov]

Finally!!! Stephen Wolfram!!!

[@dougg1075]

Somebody said the soul is not that voice you use to talk to yourself , it’s the thing that recognizes the voice in your head.

[@1Esteband]

There are many jewels of wisdom in this riveting interview. We are living in a time where our knowledge is expanding at a speed that very few individuals will be able to understand and even fewer harness it.

[@hariveturi4193]

"even fewer harness it" - THIS. I've been trying to tell this to people around me but they just do not get it.

[@alertbri]

This is where AI becomes a very timely and necessary tool.

[@sunlight8299]

May those few wield it well for the good of all including non humans.

[@howmathematicianscreatemat9226]

@@alertbri yes but it has large potential to even further degrade the brains of the masses. Imagine when even research is partially done by AI. What will people still understand themselves ? 🤔

[@thinkaboutwhy]

Thank you for this, and thank you for just letting them speak. So hard to do, but you crushed it.

[@grehuy]

Fantastic! Thank you all for your great minds ! Nice introduction !

[@AndreasEsau]

Wow.. that was an amazing discussion. And it actually stroke a nerve. I love that the fact was mentioned that having simple rules can lead to rich and complex behavior. I have a small anecdote which directly discribes this and gave me goosbumps hearing about it in this discussion. I once made a simple jump and run game. For that game I wanted to have some birds to play a role. The will follow your character and fly around him. I gave those birds some very basic simple rules. 3 to 4 rules. Fly forward. Rotate towards the character, shoot a ray in front. When ray hits another bird, rotate into a random direction. I can't recall if there were a few more. But this resulted in such an amazing looking boid behavior. I wasn't even anticipating this could be done with so few simple rules. And seeing such complex behavior in nature, I would have never thought that just a few rules can possibly lead to that behavior. So again, thanks a lot for that talk, I could have listend a few more hours. Loved seeing the hosts faces and how Wolframs explanations tingled their thoughts! Mine too for sure!

[@sabawalid]

Another amazing episode. Very illuminating. Brilliant guy. Great job MLST gang !!!

[@brianjanson3498]

So fascinating. Great question at about the 20 minute mark. And the response...whoa!

[@videowatching9576]

Fascinating video! As mentioned by Wolfram at the end: a deeply technical one as a follow-up? That said, I appreciated that this interview focused on abstractions that are more relatable and about important topics in the direction of AI - and so are more parseable than still technical. Though I am curious what questions Wolfram had in mind, because my guess is that Wolfram would speak in a technical way that is also understandable. Cheers!

[@mikenashtech]

Super conversation Dr Scarfe, Dr Duggar and Dr Wolfram. Really interesting discussion with excellent questions. Especially liked the Wolfram + ChatGPT exclusive. Amazing news, what a scoop! Thank you. M

[@filipgara3444]

Stephen builds his thoughts on very coherent world model. Fascinating

[@billcosby8411]

Wolfram saved my life.

[@maloxi1472]

@@billcosby8411 How so ?

[@DavidAKZ]

@@billcosby8411 ?

[@livb4139]

Love the excitement of the interviewer. Feels very genuine and it's contagious

[@Talismantra]

I admire the man's conversational generosity of not specifically correcting the host's slip-up use of the term "irreducible complexity" and instead just finding ways to repeat the correct term a number of times during the conversation. I look forward to watching this over and over until some part of it sinks in! Thanks for making this conversation available.

[@MachineLearningStreetTalk]

Watch our show on emergence kzbin.info/www/bejne/g3XXY5hujdmImaM - the host understands what computational irreducibility means, "irreducible complexity" is a different term by the way - it means "biological systems with multiple interacting parts would not function if one of the parts were removed"

[@Talismantra]

@@MachineLearningStreetTalk thanks for clarity, and I didn't doubt your understanding. I apologise for the comment; I shouldn't have spoken until I knew via listening again for what I might have missed. The issue was with how I heard that part of the conversation while my attention was split. It's not a term I am accustomed to hearing outside of theistic apologetics and seemed out of context here and I imagined it might be akin to a mistake I sometimes make while speaking English where I queue the right words correctly in my mind yet still speak something else and don't even hear the misarticulation myself. I'm watching some other videos of yours, and I can see this doesn't seem to be a concern for you.

[@lemapp]

I scrapped together what cash I could in the late 1980's to get a copy of Mathmatica. It was amazing, My brother and I would bang away on it for hours graphing equations and such. I quickly joined Mathmatica Alpha when it appeared online. I've sense the reports on Mathmatica language. I hope to continue with the latest evolution as I make projects for VR.

[@sebastianzimmerhackl3849]

Link to your Work!??

[@DevoyaultM]

Great interview. Happy to have Mr. Duggar back too!!! Please come back more often!

[@quasarsupernova9643]

Our department purchased the latest version Mathematica 13.1. It is no exaggeration to say that our department will be out of business in no time if it were not for Mathematica.

[@RinnRua]

I believe I have studied all of the KZbin discussions and lectures that Stephen Wolfram has published over the last three years but this presentation is the first that has made me eerily aware that the Ruliad, rather than an inconvenient threat to expansion of human consciousness, is in fact an opportunity to use our facility for imagination (conceivability) to obtain anything that we desire from the Universe… a Universe of infinite possibilities.

[@MrDaniyuca]

Such a rich conversation, an absolute treat.

[@sebastianrtj]

Absolutely loved it! Colonisation of the rulial space

[@benjamindorsey2058]

Closed formulas vs. recursive definitions vs. recurrence relations

[@apalomba]

That was phenomenal! My mind was blown when I imagined the ruliad space that is created by AI and how it will help unlock more areas of this space. How this will create new expressions of science we have never known before!

[@MarcelBlattner]

Yet another great interview in a series of excellent interviews. Thanks, Tim & team.

[@skippy6086]

I think it’s fascinating how nobody seems to know how it actually has become so good at so many surprising skills. Even Ilya Sutskever said he doesnt know.

[@michaelwisniewski6047]

Is it perhaps because we are so simple? Not a lot is required to satisfy our daily life and work needs... Not sure, but something to think about. Clearly the new plugins that allow translation between our simple language and actual complex matters bring in a lot of value, but ChatGPT is just a translator there.

[@skippy6086]

@@test-zg4hv - yep, Im sure you’re right. Our higher brains are basically pattern recognition and prediction machines. The mystery was probably more like astonishment at the comparatively small amount of human reinforcement learning that was required to produce nonlinear improvements in its evals.

[@Michael-ul7kv]

Wow he can talk, and it's all so deep and rich. Really enjoyed this.

[@bjpafa2293]

Thank you so much for your Art and knowledge, One always have had so much expectations, it's a pleasure to see they were transcended by your performance, humility, empathy &&. 🙏👏🐰

[@segelmark]

Another great episode! ❤ Thanks guys for your amazing work! 💪

[@colintomjenkins]

Wonderful; thanks all.

[@expensivetechnology9963]

#MachineLearningStreetTalk Your 0:45 introduction of Wolfram was exquisite. By comparison, most introductions today are ill-conceived at best but more often than not they’re insultingly abbreviated.

[@cosmicmuffet1053]

I liked the talk of cellular behavior at the end. Michael Levin has some interesting work that relates, I think--getting at the questions of where the more specific behavior of biology comes from, since it's not like there are entities inside a cell that can 'see' know where to go, yet not only do structures inside form coherently (and move around according to the needs of the cell), but multicellular organisms arrange themselves into repeatable shapes without needing an external guide like a mold or an observer to hold the pattern that the cells are filling out.

[@JasonCunliffe]

"Intelligence goes ALL the way down!" (in scale in biology) -- Michael Levin

[@l3lixx]

Biological tissue, it is a solid is it a liquid? What it is, is a computational phase of matter. We (as humans) can recognize that there is (meaningful) structure in the way things are transported around, inside cells, inside processes.

[@kaielvin]

No one knew about chaos before Stephen played around with cellular automata.

[@marcusmarcula]

Yes finally I'm so thrilled about this announcement!!!

[@HighStakesDanny]

The turning point is here. This is something very big in the tech world. It will all change moving forward.

[@phobosthemage260]

Wolfram alpha + chat gpt = solution to world hunger. I'm being hyperbolic, but more or less truthful about my feelings. Especially if there is an effort put into decentralizing the knowledge - it's all too easy to disrupt internet @ the nation state level.

[@pretzelboi64]

That's beyond hyperbolic. World hunger is not even fully understood and the first thing we know about it is that our ability to produce food is hardly the main cause. Even if some kid in Africa gets access to ChatGPT, they're not going to be able to do very much. A gun and a desire to kill some African warlords and corrupt politicians is more likely to help than that.

[@NoMoWarplz]

Fascinating collaboration between ChatGPT & Wolfram, combining AI prowess with computational genius! Can't wait to see the breakthroughs this partnership brings to science and tech.🚀🧠👍

[@JohnPretto]

Brilliant. Great interview guys. I enjoyed it and learned some. Carry On.

[@harriehausenman8623]

The whole AI discussion feels a little like people in the early 1900 discussing if *the car* is a good thing - or how in the 2000s people were discussing if *mobile phones* should be used and by whom. Both cases were a clear *evolutionary steps* and we as humanity had actually very little say in it. (A very few humans could steer where it goes, but that was it.) I suspect that the current phase of AI is history rhyming: We massively overestimate our agency in all of this, as we have done for centuries now.

[@drhilm]

Missed this format. what a great interview

[@MachineLearningStreetTalk]

Great to have Duggar back in the house!

[@markhottman2652]

Wolfram Alpha is AWESOME

[@matthewdozier977]

The proposed ability to have llms find structured concepts that we can utilize to effect outcomes without having to understand, or perhaps not even being capable of understanding sounds very much like magic. A way of generating clarktech.

[@EdTimTVLive]

Excellent news 👌 very exciting. I've been using Mathematica for a very long time now - way back since 1990s.

[@oysterboulevard6623]

Dr. STEPHEN WOLFRAM thank you.

[@felipealvarezsuarez2202]

I do not know if it was a coincidence or ment to be but the espisode number #110 and the Rule of Cellular automata discovered by the mathematician Stephen Wolfram is also Rule #110. Here a ChatGPT sumary of it: Cellular automata are mathematical models that simulate the behavior of simple computational systems. Rule 110 is a one-dimensional cellular automaton that was discovered by the mathematician Stephen Wolfram, who has studied and written extensively about the behavior of cellular automata and their relationship to computation. Rule 110 is interesting because it is "computationally universal", which means that it can simulate any other Turing-complete system. In other words, any problem that can be solved by a computer can also be solved by Rule 110.

[@shereerabon8551]

Thank for this interview! The depths of infinite space, theoretical physics, computational reducability, biological metadata....oooooh my God! Mind blowing.

[@JamesSarantidis]

I love this guy. Is there a part 2 with the technical stuff? His work helped me grasp Multivariable Differential Equations.

[@tims.2832]

Highly interesting, thanks. One thing though, the flashy „stage“ lightning in the middle is so much detached from the others. once I was aware of it, it became really distracting.

[@ObservingBeauty]

Truly appreciate this interview

[@LukeKendall-author]

So much good stuff there! I loved the bonus idea at the end that biological material can be thought of not as a gas, a liquid, or a solid, but as a computational state of matter.

[@GuinessOriginal]

So the universe is just a big computer?

[@GuinessOriginal]

I prefer to think of it as an idea, and the Big Bang was when that idea was first sparked into consciousness

[@LukeKendall-author]

@@GuinessOriginal Kind of: more like a big self-modifying machine. Like Conway's Game of Life, except where the things that can form include stuff like stars and life. As Wolfram points out, many outcomes can't be predicted: you have to perform the operation to see what happens.

[@GuinessOriginal]

@@LukeKendall-author a computer is a machine, and it won’t be long before we have self modifying AI. We’ve Al already got AI training AI and writing code for AI.

[@Glokiii]

Amazing can we have a part 2 please

[@paulussantosociwidjaja4781]

Thank you for the learning as only a musical not or dot in this musical world. Waiting for "black boxes" either or both hardware and software to help AI can understand as we do understand then become tools to communicate with others, let say: octopus, alien, trees, etc. Really love it, should go deeper. Cheers!

[@ChannelTomsMusic]

Very inspiring conversation, which I think is only the beginning of rethinking consciousness of humans, human languages and their ability to understand the universe, and our direction of learning as human kind

[@KALLAN8]

What a bombshell to end it on. Stephen just mentions a resolution the 3rd law of thermodynamics by explaining the biology is actually just a Turing complete form of matter!

[@maryolamide5759]

This is a remarkable discussion, it was worth sitting pretty and listening closely to.

[@numbersix8919]

Hey geniuses! I'm a a janitor, so cut me some slack here. When SW talks about Wolfram Language as the bridge between concepts and procedures in natural language and "what is computationally possible" for a digital computer, I'm reminded of the original goals of the Positivists led by Russell and Whitehead, and the entire Positivist movement for a while, to create a formal (logical) language that could represent knowledge and thought in consistent and analyzable (computable) statements. But the positivist program was undermined By Kurt Gödel, and, if I'm not mistaken, by quantum theory to some extent, and by the findings that human natural language and abstract thought are based on evolved organs with baked-in limitations. I understand that this issue was addressed in this talk from a few angles by SW, but I'd like to hear what other people here think about it.

[@johntanchongmin]

Amazing how LLMs can be used as an interface to APIs!

[@MachineLearningStreetTalk]

I know, it's such a game-changer. This is going to democratise computing more than GUIs ever did!

[@keithhenry19]

What a session! I've learnt alot.

[@robocop30301]

What a great listen. Always appreciate your work guys!

[@shinkurt]

I'd be able to listen to wolfram all day

[@javadhashtroudian5740]

Thank you, thank you,thank you. I was a classically trained pure scientist and later a software engineer with interest in AI since 1980 Lisp, neural nets from 1982 ML etc Anyway this talk was both very informative and spiritual to me. Tat Tuam Asi

[@PhilipStreets]

I discover this man this morning and I am in wonder of how we will be able to progress in the future. Awesome.

[@JimmyArcanum]

wow i am a big admirer of Dr. Wolfram great announcement!

[@DJWESG1]

KRBM (Knowledge-Reasoning-Balance-Motion) is a feedback-based decision-making framework that is used to process inputs and generate outputs in a wide range of applications. The framework consists of four key components: Knowledge: The knowledge component represents the inputs to the system. In machine learning applications, this might include data from sensors or other sources. In other applications, it might include user input or other forms of data. Reasoning: The reasoning component applies logic and reasoning to evaluate the inputs and generate outputs. This might involve statistical analysis, pattern recognition, or other forms of computation. Balance: The balance component assigns weights to the outputs generated by the reasoning component based on their relative importance. This allows the system to prioritize certain outputs over others. Motion: The motion component represents the output generated by the system. In machine learning applications, this might include actions taken by the system based on the inputs and reasoning. In other applications, it might include user feedback or other forms of output.

[@onedaya_martian1238]

This is a proto-"The Forbin Project". Colossus and Guardian have just met - ChatGPT and Wolfram-Alpha. Maybe the second coming of a millennium of peace will come to humanity !!

[@bojan368]

I wish this episode was longer. It seemed he had many more things to say

[@MachineLearningStreetTalk]

I know, we only had an hour. I hope we did a good enough job that Stephen will return 😀

[@JasonCunliffe]

>> Checkout the 3 interviews Lex Fridman & Stephen Wolfram

[@rodrigoavilalarriva]

Wolfram is one of the greatest minds of our time, thanks for sharing your thoughts and knowledge.

[@lagrinta9689]

I don't understand a word but I like listening to very smart people.

[@therecyclingguy256]

I learned a great deal from this particular interview..

[@babarbaig8983]

Prof. Wolfram is too smart and hard to digest in a go. Will keep trying to understand what he says. I got a few nuggets from this talk: My favorite quotes (edited): 29:28: 'When you have a new paradigm for thinking about things, you notice things you didn't notice before. And a very interesting question is: 'What things are there in the world we haven't noticed before?' 40:40: (Thought experiment: Make a new word for 'look at clouds in the sky' ) Until I tell you why we care about that, it's something we're not connected to. There's a sense of gradual progress (in learning?), but you can't jump ahead to a random place, and expect to have understanding there ... The second quote deeply resonated with me. Why? My life experience: Years ago, based on my test scores, and educational achievement, I got admitted into a nationally ranked Masters in Computer Science program without any programming knowledge. It was a disaster, but I still graduated with a "B". It has taken me decades to back-fill the knowledge I needed to start that program, before I could actually start to enjoy what CS is all about. The accomplishment didn't feel real, or interesting, without the necessary groundwork that naturally leads to it. Another example: In many eastern cultures, there's the idea of a wise man with many disciples. They seek wisdom, but the wise man only imparts it when he feels they're ready to 'receive' the wisdom. Wisdom imparted too soon, will fail to connect and resonate with the disciple, and will be wasted.

[@dartmoorrambler]

Thankyou for a fascinating discussion. I think what we need next is an architecture where we can add further models in an adverserial configuration. For example Chat GPT and Wolfram need to be able to keep exchanging their output until both models agree that the output is correct for the input. Then we need to explore the other models that we need to take part in this adverserial architectural exchange. We need an ethics model, a physics model, a biology model, a medical model, a chemistry model, and so on. We also need to give more weight to published academic papers than wikipedia. Once we do that the results could be very interesting.

[@l3lixx]

I just saw something weird that is weird because it's not totally weird. ESMFold for protein folding structure predictions now beats AlphaFold. 60 times faster using LLM large language models. What makes that not weird is I have seen how well LLMs do writing essays and computer language code. Writing out step-by-step protein folds should not be much different. What's weird is, some underlying structure of language has the same rules for assessing what moves are more or less likely when curling up protein strings.

[@angelbythewings]

The interesting thing is that other language models also somehow reach the exact same conclusion. There are only a few things now that seem to make us unique

[@m.x.]

Bad conclusion based on assumptions.

[@serta5727]

I just had the idea as 53:07 you were talking about neural nets and cellular automata. A knowledge core at the start of training a neural net. Imagine you would put the weights of biobert and a bert model that is good at math or something into some part of the weights of ChatGPT before it was trained and all other weights would be not initialized. Would the little pre defined bert intelligence steer the rest of the weights into a specific direction and would it also differentiate stronger this way from other regions in the weights? Comparative to our different brain regions that are pre initialized since birth to do some different specific things?

[@jawadmansoor6064]

He does not even seam human at this point. He is like an angel. He is so way ahead than what we aree

[@tinkabreytenbach-sima8218]

just add netlogo to that and it'll be even more wonderful. love Wolfram -super genius