Stargate... Another few billons for Sammy's Toy Factory?

@lkedves1 day ago
25+ years in working with AI (NOT the current chatbot bubble) and the true pioneers of informatics say: it does not matter how far you go into a dead end street because you did not even know that there were maps showing where to go. The question is: when do you realise the mistake and turn back from it... (no problem if you delete this comment, just a minority report)


@rwlurk1 day ago
there is no insatiable demand for AI, but there is insatiable demand from investors for more growth in tech stocks, which are propping up the USA's security markets

@Abouttime-p8u4 hours ago
@lkedves it just might be too lste by then... AI makes work so much easier though, 10 hours of work turn into 1

@Abouttime-p8u4 hours ago
@rwlurk My reply: Have you seen how many billions of pare using AI? Just from the time ChatGPT started to a year later it tremendous growth. Sure, there is also a lot of demand from stock investors interested in companies related to AI.


@lkedves27 minutes ago (edited)
​ @Abouttime-p8u Ironically, you are right but maybe not for the reason you think. Social media is not a big fan of facts and real science, I try to be as lightweight as possible here. Let's quote Alan Turing, highlighting the keys that nobody seem to read. 

--- 

1. The Imitation Game 

I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think". The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. 

The new form of the problem can be described in terms of a game which we call the 'imitation game." 

--- 

Understand? 

Turing stated that both the goals and the means of this current "mainstream AI" are absurd. The "imitation game" does not answer the question if machines can think but replaces it. Turing wrote this article in the Mind (a Quarterly Review on Psychology and Philosophy !) to explain why people should stop calling the Universal Turing Machine a "thinking machine". I don't think he could imagine that a whole industry will be based on misinterpreting the first page (and completely ignoring the next 21) Or rather, just quoting Benedict Cumberbatch from the movie because he is so cute. Scientists... 

I have spent good 25 years on finding a definition of these terms on par with the UTM. I follow Douglas Engelbart, a mentioned pioneer when read AI as Augmenting Intellect, because his forgotten results hold the key. My daily job is to deliver solutions to "impossible missions" in real life with real deadlines and restricted budgets, not hype riding. 

The ratio is not 10 to 1 but 1 to 0. 

On the other hand, social media defines "thinking" as skimming over the popular news following the latest hypes (including videos like this), conduct some excited discussions with relatable buddies in your idea bubble and regurgitate some word salad as your well-founded opinion. And you are absolutely right. 

LLMs can do this much better than 10 to 1. 

But, there is a question. Is this second path really worth billions of dollars and terawatts of consumption? 

Back in the days before LinkedIn turned to a GeekBook, I picked up a quote that still holds today: 

I suppose one way for a machine to pass the Turing test is to wait until the quality of actual human conversation is so bad that a bot could be an improvement. This seems to be happening here. 

Peace... 

---- Interestingly, the first comment remained public and got a response to it ----

@rhettmelton

I've been thinking about this in addition to a "maximum wage" in the USA. Thinking of ceilings for progress. I'm becoming ever-more convinced that we should impose ceilings as a society, to slow the rate of progress for the sake of security and happiness. 

EACC folks (effective accelerationists) encourage us to barrel forward because AGI will solve all of our problems. I have extreme doubts. We will see how it okays out.

@lkedves

Quite the opposite. If you understand that our monetary system is based on exponential functions (the definition of the yearly interest on your bank deposit, or the GDP), combine it with enough elementary mathematics or informatics to know what it means, you realise that there is no ceiling. The repeated hype-rides and falls are simple consequences of the systemic ignorance, under various, sometimes bittersweet ideologies. 

I often watch The Big Short, you only have to replace the few words and get the AGI story - the two mortgage brokers are just like Sammy boy and the whoever that showed the site to Emily. I play a mix of Mark Baum and Michael Burry. Informatics offered a solution but the middle men took over, check Joseph Weizenbaum, the creator of the first chatbot, ELIZA, 1966. For contrast, Softbank invested in all hypes so far: Theranos, FTX, WeWork... I would rather consider that a red flag. Let alone, a praise from Trump.

I wonder if Bloomberg shadow bans this comment individually, or I am banned as a person. Testing, testing... 

😉

What Is The Future Of Programming Languages?

The questions are excellent, the answers are "state of the art", the latter is not a compliment in this case. Here is a different take on the graph part.

0. You have two fundamentally different ways to transfer and curate knowledge, A: storytelling (very human, imprecise) or B: knowledge graph building (hard for a human, as precise as can be). 👉 JCR Licklider, Libraries of the Future (1965, book).
1. STEM knowledge is always B: a graph. When you have a problem in physics, biology, math, medicine, ... it's NOT about how you sing it or what language you use, but to build a precise network of property pages filled with data and linked to each other. The very terms (labels of data and links) are also graphs (DSLs). Information systems are graphs, too. In the computer's memory, you have flowcharts of the algorithms and you use the memory to hold the content of those property sheets. 👉 Ivan Sutherland Sketchpad (YouTube)
2. EVERY program is a combination of a DSL set (the "meta" layer of classes, members, functions and their parameters) and a bunch of stories (the code of the functions and procedures), quoting Bob Martin: the software is assignment statements, if statements and while loops 👉 Future of Programming (YouTube).
3. The real problem is that the text-based tools make us focus on the storytelling, we only see the big list of features or use cases, instead of the DSLs that allow us to describe and solve the atomic problems (modularity, KISS, DRY, SRP. ...). We have already solved every possible atomic problems literally millions of times, but repeating them every time (copy-paste or in "modern cases", LLMs🤦‍♂) in the endless possible combinations, and that grows every day. 👉 Alan Kay's Power of Simplicity (YouTube)
4. Introducing new programming languages that do the same has one effect: it even erodes the "burden" of cumulated human experience and the codebase, start it all over again, not solving the fundamental issue.

Problem: Information systems are graphs. Storytelling is not the right way to interact with graphs. The blamed imprecision is manageable "human error" in the case of graphs but inevitable fatal block in text-based programming. Teaser 👉 Bret Victor, Future of Programming (YouTube); hard-core answer 👉 Douglas Engelbart: Augmenting Human Intellect (report)

Solution: STEM languages are graphs (DSLs). THE future programming language is the DSL of information systems. The same that we have in physics, mathematics, biology, ...

Question: has anyone read this far? 😉

---[ discussion under a comment ]---

CallousCoder
Your behaviour is like the old horse and cart people against the automobile. It's nonsensical, the technology is here to stay. So either adopt it or you'll go extinct. You know that good developers are terrible managers, right? ;) Also I don't get it, what the resistance is. Whether you ask a junior or medior to implement something or you ask an LLM. It's no different other than that the LLM just does it and doesn't nag especially after the 2nd or 3rd iteration ;)

CallousCoder
“bro” is 52 years old and didn’t take philosophy but EE and CS.

lkedves
Age is just a number (happens to be the same...) Check the Mother of All Demos, that was real technology behind the Apollo program, while this chatbot AI is just another stock market bubble. Side note: before the previous AI winter, we won Comdex '99 with a data mining / AI tool. Back then people could read the first paragraph of Turing's article, the definition of "the test" instead of trying to implement cartoon dreams... (including a Nobel prize winner psychologist) 

But you got the point with "Modern software is a disease!" LLMs learn from their sources, kids copy-paste them to real software, LLM learns from them again. Quantity goes up, quality goes down. LLM companies use human slaves to avoid stupid mistakes in everyday tasks after the first flops. Regardless of we accept this as a solution, who will censor generated codes? 

Dead end.

cyberfunk3793
AI is obviously going to fix data races and buffer overflows and every other type of bugs you can think of. You don't understand what is coming if you think it's just hype. I don't know if it will be 5 years or 50, but at some point humans will only be describing (in human language) what they want the program to do and reviewing the code that is produced. Currently AI is already extremely helpful but still makes a lot mistakes. These mistakes will get more and more rare and the ability of AI to program will far exceed humans just like computers beat us at chess.

TCMx3
Chess engines did not need AI to curbstomp us at chess. Non-ML based engines with simple table-bases for endings were already some 700 points stronger than the best humans. Sounds like you don't actually know very much about chess engines lmao.

CallousCoder
btw playing chess with an LLM is a hilarious experience. If it looses it brings back pieces from the dead or just “portals” them into safety.

lkedves
[retry, I promise I leave if disappears again]

You may have missed so I repeat. We won Comdex '99 with a data mining / AI tool (and there is nothing new on this field except the exponential growth of the hardware). Since then I have worked on refining knowledge graph management in information systems under every single project I touched, often delivering "impossible missions". I work together with the machine because I follow a different resolution of AI: Augmenting Intellect (Douglas Engelbart) on systems that are of course smarter than me (and generate part of their own codes for years from these graphs). Right now at the national AI lab in a university applied research project that I will not try to explain here.
You find some of my conclusions with references to sources in my comment added to this video (11th May). 

I know the pioneers who predicted and warned about what we have today (recommended reading: Tools For Thought by Howard Rheingold, you find the whole book online). One of them is Alan Turing, who asked people not to call the UTM a "thinking machine" and wrote an article in Mind: A Quarterly Review of Psychology and Philosophy about the dangers of making such claims without proper definitions. Poor man never thought that in a few decades "IT folks" would think this was an aim. Or Joseph Weizenbaum, the guy who wrote the first chatbot, ELIZA. 

I know why your dream will never happen because I know informatics (its original meaning, not the business model Gates invented) was against this fairy tale. LLMs are just try to prove that old story from quantum mechanics, that infinite monkeys in infinite time will surely type in the whole Hamlet. The problem is that we don't have infinite time and resources, and the goal is not repeating but write the next Hamlet. Those who initiated informatics, made this clear. Start with Vannevar Bush: As We May Think, 1945. 

@TCMx3 , @CallousCoder - thanks for your answers... 🙏 Another excellent example - in chess, you have absolute rules.

In life, we know that all the laws we can invent are wrong (Incompleteness theorem) and thinking means improving the rules while solving problems and taking the responsibility of all errors. The ultimate example is the Apollo program with Engelbart's NLS in the background, that's how THEY went to the moon. We go to the plaza to watch the next Marvel story in 4D, now with the help of genAI. If we go with the question of predicting the next 50 years, look up "Charly Gordon Algernon 1968" here on YouTube.

---[ This answer "disappeared" for the second time so I left the place ]---