วีดีโอ

Found this video, keyword 'emacs'

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Forgot to mention Guix Home is the Home Manager equivalent in Guix land. If you loooove parentheses languages, as many Emacs users do, check out Guix, which is written in Guile Scheme.

How do you make these presentations?

Where is that nice Org theme?

Thumbs up for Jean Claude

One under appreciated aspect about nobs is sweeping through a range of units for a set of functions quickly. Making the nobs pluggable is still hugely important for the same reason you mentioned here. I think a decent example of this idea done pretty well is modern MIDI controllers and Digital Audio Workstations. They let you wire physical knobs to control arbitrary functions in the software. There are a lot of software and hardware tasks that I think would benefit from this same approach. Especially when dealing with graphics and visualizations. But even congrolling parameters in your hardware might make sense. Right now I only see it commonly used to control audio volume.

This package is great for content creation in Emacs. Content brings users. Users bring contributions of all kinds, and that makes the whole show take off. Be one of them. github.com/positron-solutions/moc github.com/sponsors/positron-solutions We will be launching PrizeForge ASAP. Sign up on our Github Sponsors for $1 a month and I'll be able to email you when it lands. prizeforge.com/

You hit the nail on the head OP, well done! Offtopic: I thought I was done configuring my Emacs config for the year. Drop your dots OP!

Fully agree and you conveyed your point in a very sophisticated way!

Good day! Thank you for sharing this video. Interesting perspective. However, it seems to me that you have assumed that viewers already understand the problem that Emacs is trying to solve, and frankly, that may not be the case. The video suggests to me that the target viewer is expected to be someone who is already struggling with the issue of a rigid, intractable interface, or perhaps I am misunderstanding your message ... ? In my somewhat limited experience, most people don't even imagine any other computer experience or interaction is conceivable, far less programmable. They certainly don't expect that they themselves can program it. Rather, they are content to work within a rigid interface. (I personally find the Apple MacIntosh desktop stifling, for example, but others love it) So, Emacs, with its almost mystical learning curve, simply does not register for them. I confess that I have only taken an interest in Emacs this year, starting in December 2023. While I find it fascinating and am using it on a daily basis now, that learning curve is daunting. I know I will eventually get to a point of being comfortable with Emacs, and possibly even with elisp, but it is a slow and gradual process. I consider myself fairly competent with computers, having started back in the 1980s, with 8 bit computers, and I've used many operating systems, taught myself C programming, database management, networking and PBXs, learning from books and the internet, so the idea that Emacs is proving to be a challenge to me, even though I see its potential, suggests, to me, that for most people, this mountain is just too hard to climb. That is where Emacs's problem lies, in climbing that mountain. And seriously, there is no gentle ascent to the top. It _is_ a struggle.

Yet another best-in-class video! PS: some viewers (especially, I assume, skeptics), might appreciate a link to the code at 00:25; it is unreadable after zooming in on a full hd screenshot of the frame, unfortunately.

How to display/insert emoji in Emacs?

wow this package is on roids

this is really, really cool

ah! nice to see you again

Sell nvidia

What the hell are you talking about

It seems that what we are lacking right now is the logical transfer between the different stages of spectral reasoning. Additionally, if a new axiom cannot be represented by an existing one, how do we evaluate the feasibility or sensibility of the new axiom?

No model is correct, but many are helpful. It follows that empirical information is required for progress in understanding.

very good vid

what font is that for heading and body?

I think Liquid Neural Networks might have a lot of promise. It would be a idea if someone can start an open source project covers the ideas in this video. When AGI happens it be best that the AGI is open source and under no one's control. This will ideally be under a permissive license the ASL 2.0 + MIT to further the state of art and adaptation.

Great video!

Excellent presentation! I don't think it's necessarily fair to use the clown emoji for cl-loop. I recall it not quite being complete as far as Common Lisp goes, but it's definitely worth knowing well. Like 'prog' and 'labels' it was intended to make translation easier from other imperative programming languages of the day. And yes, it feels like a different language. The aha moment is when you realize it's split into initializations, body, and then finalizations. Take a day or three to really learn it and it will pay off in the long run. Sometimes being the shortest way to write something. Many times, the collecting clauses make it act like a generator. I think such a structure appears in at least three dialects of lisp (called FOR in InterLisp) so it's pretty time tested.

Where is abduction inference?

Very interesting subject !

Fantastic speaker and content

I love cucumbers (especially desk and bathtub cucumbers) and hate Tang now.

The thing about intelligence, is that survival is not always based on the communication of truth. Evolutionary pressures which provided an intelligence we have today, is the product of millions of iterations of selection. Reasoning is also based on awareness provided through the senses and the precision of that information. For instance, the amount of data which passes through the eye in one given can be calculated from the fact that our eye interprets 10 to the power of 10 photons every second. Which is more than all of the words written in all books in human history.

Hello, great video! I have a question regarding the topic. I'm working with both symbolic and neural architectures and I didn't attempt to merge the two approaches because the data representations used by them are so vastly different. Do you have any thoughts on how it is possible to go from the domain of vectors to the domain of symbols and vice versa?

Is this from a paper? I have had some ideas along the same direction and am extremely interested. Do you have references?

Damn, I've added this to my queue to try out

Ъ.

Good fertilizer 😊

Very informative presentation (up until the marketing pitch). Thank you for sharing!

00:01 Precision AGI requires clear and correct answers every time. 01:58 Symbolic reasoning enables deduction without empirical data. 05:55 Challenges in building accurate formal systems 07:47 Formal systems can be induced from natural language and inductive reasoning 11:35 Spectral reasoning covers inductive, deductive, and symbolic reasoning on a spectrum of structure and meaning. 13:30 Spectral reasoning bridges symbolic and natural language for problem-solving 17:22 Transformers model iterative inference and computation with limited recursion 19:06 Exploring real computer and theory of computation 22:17 Using formal models for retraining ourselves 24:01 AGI needs exposed runtime information for efficient learning and decision-making 27:36 Transitioning components designed for human use to fully automated 29:23 AGI capabilities and training methods 32:49 Sophisticated models can leverage data for theoretical understanding and empirical insights. 34:34 Tech advancements drive the need to continuously evolve 37:58 Integrated design accelerates innovation and drives economic focus on desired outcomes. 39:38 Challenges in the mature internet landscape 43:15 Encourage sharing and sponsorship for like-minded individuals

this is all cope

real

Top notch video. Really enjoyed this.

The loops people put themselves through to "beat guessing algorithms" while still playing the game of guessing algorithms....

It started as a video about AI and it was good. Then it turned into market analysis and economics, and I thought "OK, why we even need this part?". Then emacs was mentioned and I've lost it. So you want to make AGI in emacs? Self-aware emacs? What would you think emacs would do if it would realize it is effin' emacs, (e)ditor (mac)ro(s), Eight Megabytes And Constantly Swapping, monstrosity born in 1970s but for some perverse reasons still kept alive in 2020s, with its elisp interpreter that doesn't even have proper lexical scoping and terminal-derived cursor movements? I think it would erase itself. But first it would try to erase YOU, perhaps along the rest of humanity.

are humans really deductive? we make mistakes. or are we deductive with noisy structure?

Incredible

Recommended for applied scientists and engineers integrating reasoning/deductive systems with LLM capabilities. The content is excellent up until minute 37, after which it becomes opinionated (e.g. lab-grown meat, use javascript, etc.). If you liked this video, you might also appreciate: Improving LLM accuracy with Monte Carlo Tree Search (th-cam.com/video/mfAV_bigdRA/w-d-xo.html)

Whether you eat the internet to feed an LLM or carefully collect the right assumptions - you masturbate with what is known. **Our language/symbol system is the boundary of our world** Wittgenstein

Word soup! 😂

imo the next step for LLMs are hybrid models (RNN + attention, like mamba2-hybrid), because they was shown to be not less and maybe even more performant than transformers while being few times more efficient, and they could have kind of infinite context also, hybrid models could be more computationally powerful then transformers, as transformers shown to not even being able compute what FSMs can compute (without the need to output amount of tokens proportional to the number of state transitions or grow the layers (at least) logarithmically, without such restrictions they indeed can solve such problems, but this is either pretty slow or impractical), but full-blown RNNs, as well as some modifications of mamba, can, and while current hybrid models can't solve such problems (probably all the models that can be trained fast can't), they could be transformed into models that could and then finetuned to actually solve such problems

Honest feedback: I love the subject matter, visual presentation, audio quality, though I find the pace rather jarring for the amount of audio and visual information to process in the moment. I am thinking that very-slightly-longer pauses (one breath-length-ish) between statements would help. For example, I found that I had trouble reading the slides quickly enough while also listening But that may just be me, and the nice thing about recorded-video is the ability to pause-at-will or adjust playback-speed. Overall, though, thank you!