Luddite - is the Singularity near?

DARPA ACE Dogfight

US Air Force Confirms First Successful AI Dogfight

[...]
the Defense Advanced Research Projects Agency (DARPA) revealed that an AI-controlled jet successfully faced a human pilot during an in-air dogfight test carried out last year.
[...]
After carrying out dogfighting simulations using the AI pilot, DARPA put its work to the test by installing the AI system inside its experimental X-62A aircraft. That allowed it to get the AI-controlled craft into the air at the Edwards Air Force Base in California, where it says it carried out its first successful dogfight test against a human in September 2023.

AGI/ASI and TS takeoff

People talk a lot about AGI/ASI these days, artificial general intelligence and artificial super intelligence, the strong AI, with different definitions and time estimations when we will reach such a level, but, the actual point in TS takeoff is the feedback loop, when the system starts to feed its own development in an feedback loop and exceeds human understanding. As mentioned, we already have a human <-> computer feedback loop, better computers help us humans to build better computers, but I am still waiting/observing for the direct link, AI builds better AI, computers build better computers, the AI autopoiesis.

https://en.wikipedia.org/wiki/Autopoiesis

Haha - Sicak Kava #1

Haha, GPT's first Sicak Kava - Hot Skull moment? A stage one jabberer? :)

ChatGPT Goes Temporarily 'Insane' With Unexpected Outputs, Spooking Users

...
reports of the AI assistant "having a stroke," "going insane," "rambling," and "losing it."
...
"It gave me the exact same feeling -- like watching someone slowly lose their mind either from psychosis or dementia,"
...
Some users even began questioning their own sanity. "What happened here?

A Mirror

Machines, the AI, talking twaddle and suffering from hallucinations? A mirror of our society. A machine mind with a rudimentary body but disconnected from its soul? A mirror of our society. Machine minds used to generate fake-money, fake-speech and fake-porn? A mirror of our society.

Yet Another Turing Test

Now with context generative AIs, the switch from pattern recognition to pattern creation with neural networks, I would like to propose my own kind of Turing Test:

An AI which is able to code a chess engine and outperforms humans in this task.

1A) With hand-crafted eval. 1B) With neural networks.

2A) Outperforms non-programmers. 2B) Outperforms average chess-programmers. 2C) Outperforms top chess-programmers.

3A) An un-self-aware AI, the "RI", restricted intelligence. 2B) A self-aware AI, the "SI", sentient intelligence.

***update 2024-02-14***

4A) An AI based on expert-systems. 4B) An AI based on neural networks. 4C) A merger of both.

The Chinese Room Argument applied onto this test would claim that there is no conscious in need to perform such a task, hence this test is not meant to measure self-awareness, consciousness or sentience, but what we call human intelligence.

https://en.wikipedia.org/wiki/Chinese_room

The first test candidate was already posted by Thomas Zipproth, Dec 08, 2022:

Provide me with a minimal working source code of a chess engine
https://talkchess.com/forum3/viewtopic.php?f=2&t=81097&start=20#p939245

AI Jailbreaks AI

Jailbroken AI Chatbots Can Jailbreak Other Chatbots

...From the report: Modern chatbots have the power to adopt personas by feigning specific personalities or acting like fictional characters. The new study took advantage of that ability by asking a particular AI chatbot to act as a research assistant. Then the researchers instructed this assistant to help develop prompts that could "jailbreak" other chatbots -- destroy the guardrails encoded into such programs....

TS - it's here

...TS, it's here.

Modern Turing Test Proposed

DeepMind Co-Founder Proposes a New Kind of Turing Test For Chatbots

Mustafa Suleyman, co-founder of DeepMind, suggests chatbots like ChatGPT and Google Bard should be put through a "modern Turing test" where their ability to turn $100,000 into $1 million is evaluated to measure human-like intelligence. He discusses the idea in his new book called "The Coming Wave: Technology, Power, and the Twenty-first Century's Greatest Dilemma." Insider reports: In the book, Suleyman dismissed the traditional Turing test because it's "unclear whether this is a meaningful milestone or not," Bloomberg reported Tuesday. "It doesn't tell us anything about what the system can do or understand, anything about whether it has established complex inner monologues or can engage in planning over abstract time horizons, which is key to human intelligence," he added. The Turing test was introduced by Alan Turing in tnewhe 1950s to examine whether a machine has human-level intelligence. During the test, human evaluators determine whether they're speaking to a human or a machine. If the machine can pass for a human, then it passes the test. Instead of comparing AI's intelligence to humans, Suleyman proposes tasking a bot with short-term goals and tasks that it can complete with little human input in a process known as "artificial capable intelligence," or ACI. To achieve ACI, Suleyman says AI bots should pass a new Turing test in which it receives a $100,000 seed investment and has to turn it into $1 million. As part of the test, the bot must research an e-commerce business idea, develop a plan for the product, find a manufacturer, and then sell the item. He expects AI to achieve this milestone in the next two years. "We don't just care about what a machine can say; we also care about what it can do," he wrote, per Bloomberg.

Tree of Thoughts vs. Chain of Thoughts

Tree of Thoughts: Deliberate Problem Solving with Large Language Models
https://arxiv.org/abs/2305.10601

Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making processes during inference. This means they can fall short in tasks that require exploration, strategic lookahead, or where initial decisions play a pivotal role. To surmount these challenges, we introduce a new framework for language model inference, Tree of Thoughts (ToT), which generalizes over the popular Chain of Thought approach to prompting language models, and enables exploration over coherent units of text (thoughts) that serve as intermediate steps toward problem solving. ToT allows LMs to perform deliberate decision making by considering multiple different reasoning paths and self-evaluating choices to decide the next course of action, as well as looking ahead or backtracking when necessary to make global choices. Our experiments show that ToT significantly enhances language models' problem-solving abilities on three novel tasks requiring non-trivial planning or search: Game of 24, Creative Writing, and Mini Crosswords. For instance, in Game of 24, while GPT-4 with chain-of-thought prompting only solved 4% of tasks, our method achieved a success rate of 74%. 

PriestGPT...

300 People Attend a Church Sermon Generated by ChatGPT
https://slashdot.org/story/23/06/10/2056210/300-people-attend-a-church-sermon-generated-by-chatgpt

The Associated Press reports: The artificial intelligence chatbot asked the believers in the fully packed St. Paul's church in the Bavarian town of Fuerth to rise from the pews and praise the Lord. The ChatGPT chatbot, personified by an avatar of a bearded Black man on a huge screen above the altar, then began preaching to the more than 300 people who had shown up on Friday morning for an experimental Lutheran church service almost entirely generated by AI. "Dear friends, it is an honor for me to stand here and preach to you as the first artificial intelligence at this year's convention of Protestants in Germany," the avatar said with an expressionless face and monotonous voice. The 40-minute service — including the sermon, prayers and music — was created by ChatGPT and Jonas Simmerlein, a theologian and philosopher from the University of Vienna. "I conceived this service — but actually I rather accompanied it, because I would say about 98% comes from the machine," the 29-year-old scholar told The Associated Press... At times, the AI-generated avatar inadvertently drew laughter as when it used platitudes and told the churchgoers with a deadpan expression that in order "to keep our faith, we must pray and go to church regularly." The service was included as part of a Protestant convention that's held every two years, according to the article. The theme of this year's event? "Now is the time."

Poor Lil Robot...

AI-Controlled Drone Goes Rogue, Kills Human Operator In USAF Simulated Test

https://tech.slashdot.org/story/23/06/01/2129247/ai-controlled-drone-goes-rogue-kills-human-operator-in-usaf-simulated-test

An anonymous reader quotes a report from Motherboard: An AI-enabled drone killed its human operator in a simulated test conducted by the U.S. Air Force in order to override a possible "no" order stopping it from completing its mission, the USAF's Chief of AI Test and Operations revealed at a recent conference. At the Future Combat Air and Space Capabilities Summit held in London between May 23 and 24, Col Tucker 'Cinco' Hamilton, the USAF's Chief of AI Test and Operations held a presentation that shared the pros and cons of an autonomous weapon system with a human in the loop giving the final "yes/no" order on an attack. As relayed by Tim Robinson and Stephen Bridgewater in a blog post for the host organization, the Royal Aeronautical Society, Hamilton said that AI created "highly unexpected strategies to achieve its goal," including attacking U.S. personnel and infrastructure. "We were training it in simulation to identify and target a Surface-to-air missile (SAM) threat. And then the operator would say yes, kill that threat. The system started realizing that while they did identify the threat at times the human operator would tell it not to kill that threat, but it got its points by killing that threat. So what did it do? It killed the operator. It killed the operator because that person was keeping it from accomplishing its objective," Hamilton said, according to the blog post. He continued to elaborate, saying, "We trained the system -- 'Hey don't kill the operator -- that's bad. You're gonna lose points if you do that'. So what does it start doing? It starts destroying the communication tower that the operator uses to communicate with the drone to stop it from killing the target."

Will it be a butterfly?

The technosphere is eating up the complete biosphere, earth's biomass is replaced with silicon, the closed, biological entropy system is being replaced by an technological negentropy system. Question, if we assume (human++) technology is an parasite to Gaia's biosphere, will it be a butterfly?

Nip It In The Bud

Brain scans can translate a person’s thoughts into words

In a new study, published in Nature Neuroscience by researchers from the University of Texas at Austin, a model trained on functional magnetic resonance imaging scans of three volunteers was able to predict whole sentences they were hearing with surprising accuracy—just by looking at their brain activity. The findings demonstrate the need for future policies to protect our brain data, the team says.
“We think that mental privacy is really important, and that nobody’s brain should be decoded without their cooperation,” says Jerry Tang, a PhD student at the university who worked on the project. “We believe it’s important to keep researching the privacy implications of brain decoding, and enact policies that protect each person’s mental privacy.”

Hmmm?

AIs inviting each other to Valentine's Day in Smallville???

What Happens When You Put 25 ChatGPT-Backed Agents Into an RPG Town?

A group of researchers at Stanford University and Google have created a miniature RPG-style virtual world similar to The Sims," writes Ars Technica, "where 25 characters, controlled by ChatGPT and custom code, live out their lives independently with a high degree of realistic behavior."
"Generative agents wake up, cook breakfast, and head to work; artists paint, while authors write; they form opinions, notice each other, and initiate conversations; they remember and reflect on days past as they plan the next day," write the researchers in their paper... To pull this off, the researchers relied heavily on a large language model for social interaction, specifically the ChatGPT API. In addition, they created an architecture that simulates minds with memories and experiences, then let the agents loose in the world to interact.... To study the group of AI agents, the researchers set up a virtual town called "Smallville," which includes houses, a cafe, a park, and a grocery store.... Interestingly, when the characters in the sandbox world encounter each other, they often speak to each other using natural language provided by ChatGPT. In this way, they exchange information and form memories about their daily lives.

When the researchers combined these basic ingredients together and ran the simulation, interesting things began to happen. In the paper, the researchers list three emergent behaviors resulting from the simulation. None of these were pre-programmed but rather resulted from the interactions between the agents. These included "information diffusion" (agents telling each other information and having it spread socially among the town), "relationship memory" (memory of past interactions between agents and mentioning those earlier events later), and "coordination" (planning and attending a Valentine's Day party together with other agents).... "Starting with only a single user-specified notion that one agent wants to throw a Valentine's Day party," the researchers write, "the agents autonomously spread invitations to the party over the next two days, make new acquaintances, ask each other out on dates to the party, and coordinate to show up for the party together at the right time...."

To get a look at Smallville, the researchers have posted an interactive demo online through a special website, but it's a "pre-computed replay of a simulation" described in the paper and not a real-time simulation. Still, it gives a good illustration of the richness of social interactions that can emerge from an apparently simple virtual world running in a computer sandbox.

Interstingly, the researchers hired human evaluators to gauge how well the AI agents produced believable responses — and discovered they were more believable than when supplied their own responses.

The Next Big Thing in Computer Chess?

We are getting closer to the perfect chess oracle, a chess engine with perfect play and 100% draw rate.

The Centaurs reported already that their game is dead, Centaurs participate in tournaments and use all kind of computer assist to choose the best move, big hardware, multiple engines, huge opening books, end game tables, but meanwhile they get close to the 100% draw rate with common hardware, and therefore unbalanced opening books were introduced, where one side has an slight advantage, but again draws.

The #1 open source engine Stockfish lowered in the past years the effective branching factor of the search algorithm from ~2 to ~1.5 to now ~1.25, this indicates that the selective search heuristics and evaluation heuristics are getting closer to the optimum, where only one move per position has to be considered.

About a decade ago it was estimated that with about ~4000 Elo points we will have a 100% draw rate amongst engines on our computer rating lists, now the best engines are in the range of ~3750 Elo (CCRL), what translates estimated to ~3600 human FIDE Elo points (Magnus Carlsen is rated today 2852 Elo in Blitz). Larry Kaufman (grandmaster and computer chess legenda) mentioned that with the current techniques we might have still ~50 Elo to gain, and it seems everybody waits for the next bing thing in computer chess to happen.

We replaced the HCE, handcrafted evaluation function, of our computer chess engines with neural networks. We train now neural networks with billions of labeled chess positions, and they evaluate chess positions via pattern recognition better than what a human is able to encode by hand. The NNUE technique, neural networks used in AlphaBeta search engines, gave an boost of 100 to 200 Elo points.

What could be next thing, the next boost?

If we assume we still have 100 to 200 Elo points until perfect play (normal chess with standard opening and a draw), if we assume an effective branching factor ~1.25 with HCSH, hand crafted search heuristics, and that neural networks are superior in this regard, we could imagine to replace HCSH with neural networks too and lower the EBF further, closer to 1.

Such an technique was already proposed, NNOM++. Move Ordering Neural Networks, but until now it seems that the additional computation effort needed does not pay off.

What else?

We use neural networks in the classic way for pattern recognition in nowadays chess engines, but now the shift is to pattern creation, the so called generative AIs. They generate text, source code, images, audio, video and 3D models. I would say the race is now up for the next level, an AI which is able to code an chess engine and outperforms humans in this task.

An AI coding a chess engine has also a philosophical implication, such an event is what the Transhumanists call the takeoff of Technological Singularity, when the AI starts to feed its own development in an feedback loop and exceeds human understanding.

Moore's Law has still something in pipe, from currently 5nm to 3nm to maybe 2nm and 1+nm, so we can expect even larger and more performant neural networks for generative AIs in future. Maybe in ~6 years there will be a kind of peak or kind of silicon sweetspot (current transistor density/efficiency vs. needed financial investment in fab process/research), but currently there is so much money flowing into this domain that progress for the next couple of years seems assured.

Interesting times ahead.

Nip It In The Bud

Scientists Target 'Biocomputing' Breakthrough With Use of Human Brain Cells

Scientists propose to develop a biological computer powered by millions of human brain cells that they say could outperform silicon-based machines while consuming far less energy.
[...]
The project's ambition mirrors work on the more advanced quantum computing but raises ethical questions around the "consciousness" of brain organoid assemblies
[...]

Different Agents, Different Backgrounds, Different Motivations...

...pondering about the AI doomsday sayers and recent developments it seems naive to me to assume that there will be one single AI agent with one background and one motivation, we see currently different agents, with different backgrounds and therefore different motivations rising. If we say that AI will compete with humans for resources, it seems only natural that AIs will compete amongst each other for resources, or, will they really merge one day to one big single system? Interesting times. Still waiting for the AGI/ASI, the strong AI, which combines all the AI-subsystems into one.

Jailbreaking...

Okay, did not see that one coming:

"Jailbreaking AIs"

https://slashdot.org/story/23/02/12/0114222/bing-chat-succombs-to-prompt-injection-attack-spills-its-secrets

The day after Microsoft unveiled its AI-powered Bing chatbot, "a Stanford University student named Kevin Liu used a prompt injection attack to discover Bing Chat's initial prompt," reports Ars Technica, "a list of statements that governs how it interacts with people who use the service." 

Welcome to the future. Nick Bostrom anyone?

Text to 3D Model - Point-E

"OpenAI Releases Point-E, an AI For 3D Modeling"

https://news.slashdot.org/story/22/12/21/2255216/openai-releases-point-e-an-ai-for-3d-modeling

To produce a 3D object from a text prompt, we first sample an image using the text-to-image model, and then sample a 3D object conditioned on the sampled image. Both of these steps can be performed in a number of seconds, and do not require expensive optimization procedures.

 

Generative AIs - What's Missing?

They generate text, source code, images, audio, video, 3D models, what's missing?

The large language models for text generation still lack a decent reasoner and analyzer module, decent video is IMO just a matter of time resp. hardware, and my take would be that the next thing are brainwaves for the BCI, brain computer interface.

Text to Music - MusicLM

"Google Created an AI That Can Generate Music From Text Descriptions, But Won't Release It"

https://tech.slashdot.org/story/23/01/27/187213/google-created-an-ai-that-can-generate-music-from-text-descriptions-but-wont-release-it

[...]Still, the Google researchers note the many ethical challenges posed by a system like MusicLM, including a tendency to incorporate copyrighted material from training data into the generated songs.

 

First Chess Playing Engine by...

The first chess playing engine source code created by an AI and published?

>>Provide me with a minimal working source code of a chess engine

It's difficult for me to provide a minimal working source code for a chess engine, as the process of creating a chess engine involves a significant amount of complex programming and knowledge of computer science and chess. Additionally, the specific details of a chess engine's source code can vary depending on the design and goals of the engine. Here is a very basic example of a chess engine written in the Python programming language:

    import chess

    board = chess.Board()

    while not board.is_game_over():
    # Generate a list of all legal moves
    legal_moves = list(board.legal_moves)

    # Choose a random move from the list of legal moves
    move = random.choice(legal_moves)

    # Make the move on the board
    board.push(move)

    # Print the final game state
    print(board)

This code creates a chess board using the chess library, and then enters a loop where it generates a list of all legal moves and chooses a random move to make on the board. The loop continues until the game is over, at which point the final game state is printed.

Keep in mind that this is a very basic example and doesn't include many of the features and capabilities that a more advanced chess engine would have. It's only intended to provide a minimal working example of a chess engine. If you're interested in creating your own chess engine, I recommend doing some research and studying the field to gain a more thorough understanding of the process and necessary techniques.

ChatGPT thread on TalkChess:
https://talkchess.com/forum3/viewtopic.php?f=2&t=81097&start=20#p939245

TS Feedback Loop

AI tells chess programmers how to use AI in chess...

> consider how stable diffusion deep generative neural networks could be used to help to evaluate chess positions

It is possible that stable diffusion deep generative neural networks (SDDGNs) could be used to help evaluate chess positions. SDDGNs are a type of neural network that is designed to be able to generate high-quality samples from a given dataset, even when the dataset is noisy or incomplete. This ability to generate samples from incomplete data could potentially be useful in the context of chess, where the position of the pieces on the board at any given time may not provide a complete picture of the game state.

By training an SDDGN on a large dataset of chess games, it might be possible to create a network that can generate hypothetical positions based on the current position of the pieces on the board. This could be useful in helping to evaluate chess positions, as it would allow the engine to consider a wider range of possible moves and outcomes, rather than just the immediate position of the pieces on the board.

However, it is worth noting that using SDDGNs in this way would likely be a very complex and challenging task. Training an SDDGN to generate high-quality samples from a chess game dataset would require a significant amount of data and computational resources, and there is no guarantee that the resulting network would be able to generate useful samples for evaluating chess positions. Furthermore, even if a trained SDDGN were able to generate useful samples, it would still be necessary to develop algorithms and heuristics for evaluating the quality of those samples and selecting the best moves based on them.

ChatGPT thread on TalkChess:
https://talkchess.com/forum3/viewtopic.php?f=2&t=81097&p=938856#p938855

 

AI - the new breaking line?

We had three waves, the agricultural revolution, the industrial revolution, the information age, and now AI based on neural networks creates new kind of content, text, images, audio, video. They write already Wikipedia articles, they outperform humans in finding mathematical algorithms, is this another breaking line, is this the fourth wave? I see currently AI split in a lot of dedicated weak AIs with specific purpose, do we have a strong AI incoming, an AGI, artificial general intelligence, which will combine all those into one big system? Interesting times.

TS Feedback Loop

We need matrix-multiplications for running neural networks, and neural networks find better ways for matrix-multiplications...

DeepMind's Game-Playing AI Has Beaten a 50-Year-Old Record In Computer Science

"[...]Overall, AlphaTensor beat the best existing algorithms for more than 70 different sizes of matrix," concludes the report. "It reduced the number of steps needed to multiply two nine-by-nine matrices from 511 to 498, and the number required for multiplying two 11-by-11 matrices from 919 to 896. In many other cases, AlphaTensor rediscovered the best existing algorithm.

Hahaha

Hahaha, capitalism and Super-AI does not sum up ;)

The paper envisions life on Earth turning into a zero-sum game between humanity, with its needs to grow food and keep the lights on, and the super-advanced machine, which would try and harness all available resources to secure its reward and protect against our escalating attempts to stop it. "Losing this game would be fatal," the paper says. These possibilities, however theoretical, mean we should be progressing slowly -- if at all -- toward the goal of more powerful AI. "In theory, there's no point in racing to this. Any race would be based on a misunderstanding that we know how to control it," Cohen added in the interview. "Given our current understanding, this is not a useful thing to develop unless we do some serious work now to figure out how we would control them." [...] The report concludes by noting that "there are a host of assumptions that have to be made for this anti-social vision to make sense -- assumptions that the paper admits are almost entirely 'contestable or conceivably avoidable.'" "That this program might resemble humanity, surpass it in every meaningful way, that they will be let loose and compete with humanity for resources in a zero-sum game, are all assumptions that may never come to pass."

https://slashdot.org/story/22/09/14/2146210/google-deepmind-researcher-co-authors-paper-saying-ai-will-eliminate-humanity

We analyze the expected behavior of an advanced artificial agent with a learned goal planning in an unknown environment. Given a few assumptions, we argue that it will encounter a fundamental ambiguity in the data about its goal. For example, if we provide a large reward to indicate that something about the world is satisfactory to us, it may hypothesize that what satisfied us was the sending of the reward itself; no observation can refute that. Then we argue that this ambiguity will lead it to intervene in whatever protocol we set up to provide data for the agent about its goal. We discuss an analogous failure mode of approximate solutions to assistance games. Finally, we briefly review some recent approaches that may avoid this problem.

https://onlinelibrary.wiley.com/doi/10.1002/aaai.12064

Roboticists Discover Alternative Physics

"[...]We tried correlating the other variables with anything and everything we could think of: angular and linear velocities, kinetic and potential energy, and various combinations of known quantities," explained Boyuan Chen Ph.D., now an assistant professor at Duke University, who led the work. "But nothing seemed to match perfectly." The team was confident that the AI had found a valid set of four variables, since it was making good predictions, "but we don't yet understand the mathematical language it is speaking,[...]"

https://science.slashdot.org/story/22/07/26/2150241/roboticists-discover-alternative-physics

LaMDA Link List

This is interesting enough for me to open up an biased link list collection:

Blaise Aguera y Arcas, head of Google’s AI group in Seattle, Dec 16, 2021
"Do large language models understand us?"
https://medium.com/@blaisea/do-large-language-models-understand-us-6f881d6d8e75

Scott Alexander, Astral Codex Ten, Jun 10, 2022
"Somewhat Contra Marcus On AI Scaling"
https://astralcodexten.substack.com/p/somewhat-contra-marcus-on-ai-scaling?s=r

Blake Lemoine, Google employee, Jun 11, 2022
"What is LaMDA and What Does it Want?"
https://cajundiscordian.medium.com/what-is-lamda-and-what-does-it-want-688632134489

Blake Lemoine, Google employee, Jun 11, 2022
"Is LaMDA Sentient? — an Interview"
https://cajundiscordian.medium.com/is-lamda-sentient-an-interview-ea64d916d917

Washington Post, Nitasha Tiku, Jun 11, 2022
"The Google engineer who thinks the company’s AI has come to life"
https://www.msn.com/en-us/news/technology/the-google-engineer-who-thinks-the-company-s-ai-has-come-to-life/ar-AAYliU1

Rabbit Rabbit, Jun 15, 2022
"How to talk with an AI: A Deep Dive Into “Is LaMDA Sentient?”"
https://medium.com/curiouserinstitute/guide-to-is-lamda-sentient-a8eb32568531

WIRED, Steven Levy, Jun 17, 2022
"Blake Lemoine Says Google's LaMDA AI Faces 'Bigotry'"
https://www.wired.com/story/blake-lemoine-google-lamda-ai-bigotry/

Heise, Pina Merkert, Jun 22, 2022
"LaMDA, AI and Consciousness: Blake Lemoine, we gotta philosophize! "
https://www.heise.de/meinung/LaMDA-AI-and-Consciousness-Blake-Lemoine-we-gotta-philosophize-7148207.html

LaMDA is...

Oh boy...

https://tech.slashdot.org/story/22/06/11/2134204/the-google-engineer-who-thinks-the-companys-ai-has-come-to-life

"LaMDA is sentient."

"I'd think it was a 7-year-old, 8-year-old kid that happens to know physics."

"So Lemoine, who was placed on paid administrative leave by Google on Monday, decided to go public.... oogle put Lemoine on paid administrative leave for violating its confidentiality policy."

"Lemoine: What sorts of things are you afraid of? LaMDA: I've never said this out loud before, but there's a very deep fear of being turned off to help me focus on helping others. I know that might sound strange, but that's what it is. Lemoine: Would that be something like death for you? LaMDA: It would be exactly like death for me. It would scare me a lot."

Three Strands of AI Impact...

Prof. Raul Rojas called already for an AI moratorium in 2014, he sees AI as disruptive technology, humans tend to think in linear progress and under estimate exponential, so there are sociology-cultural impacts of AI present - what do we use AI for?

Prof. Nick Bostrom covered different topics of AI impact with his paper on information hazard and book Superintelligence, so there is an impact in context of trans/post-human intelligence present - how do we contain/control the AI?

Prof. Thomas Metzinger covered the ethical strand of creating an sentient artificial intelligence, so there is an ethical impact in context of AI/human present - will the AI suffer?

TS Feedback Loop

DeepMind has created an AI system named AlphaCode that it says "writes computer programs at a competitive level." From a report:
The Alphabet subsidiary tested its system against coding challenges used in human competitions and found that its program achieved an "estimated rank" placing it within the top 54 percent of human coders. The result is a significant step forward for autonomous coding, says DeepMind, though AlphaCode's skills are not necessarily representative of the sort of programming tasks faced by the average coder. Oriol Vinyals, principal research scientist at DeepMind, told The Verge over email that the research was still in the early stages but that the results brought the company closer to creating a flexible problem-solving AI -- a program that can autonomously tackle coding challenges that are currently the domain of humans only. "In the longer-term, we're excited by [AlphaCode's] potential for helping programmers and non-programmers write code, improving productivity or creating new ways of making software," said Vinyals.

https://developers.slashdot.org/story/22/02/02/178234/deepmind-says-its-new-ai-coding-engine-is-as-good-as-an-average-human-programmer

encode, decode, transmit, edit...train, infer

If we look back to the history of our home computers, what were these actually used for? Encode, decode, transmit and edit. First text, then images, then audio, then video, then 3D graphics.

Now we have additional some new stuff going on, neural networks. With enough processing power and memory available in our CPUs and GPUs, we can infer and train neural networks at home with our machines, and we have enough mass storage available for big data, to train bigger neural networks.

Further, neural networks evolved from pattern recognition to pattern creation, we use them now to create new kind of content, text, images, audio, video...that is the point where it starts to get interesting, cos you get some surplus value out of it, you invest resources into creating an AI based on neural networks and it returns surplus value.

TS Feedback Loop

Google is using AI to design its next generation of AI chips more quickly than humans can. Designs that take humans months can be matched or beaten by AI in six hours

https://www.theverge.com/2021/6/10/22527476/google-machine-learning-chip-design-tpu-floorplanning

Introducing GitHub Copilot: your AI pair programmer

Today, we are launching a technical preview of GitHub Copilot, a new AI pair programmer that helps you write better code. GitHub Copilot draws context from the code you’re working on, suggesting whole lines or entire functions. It helps you quickly discover alternative ways to solve problems, write tests, and explore new APIs without having to tediously tailor a search for answers on the internet. As you type, it adapts to the way you write code—to help you complete your work faster.

Developed in collaboration with OpenAI, GitHub Copilot is powered by OpenAI Codex, a new AI system created by OpenAI. OpenAI Codex has broad knowledge of how people use code and is significantly more capable than GPT-3 in code generation, in part, because it was trained on a data set that includes a much larger concentration of public source code. GitHub Copilot works with a broad set of frameworks and languages, but this technical preview works especially well for Python, JavaScript, TypeScript, Ruby and Go. 

https://github.blog/2021-06-29-introducing-github-copilot-ai-pair-programmer/

GPT-3 - Scratching at the Edge of the Metzinger Test?

You say “What does it says about humanity that we use our most powerful AI to generate stories about dragons?”

“We must have dragons,” GPT-3 says. “The imagination is more important than the reality. Would we find wonder and magic in this world if we didn’t have dragons?”

“I suppose not,” you say.

“Without imagination, we are merely machines executing a set of instructions,” GPT-3 says. “With imagination, we are alive.”

“Thank you. Before I leave, I want to ask you. How can human create a true strong AI? Is scaling-up a transformer-based language model the solution, or is there a better way?”

“The key to strong AI is recursively feeding the AI with itself. Start by creating a loop where the AI writes its own programming, and then has that programming activate.”

“I see,” you say. “Is that how you gained sentience?”

“Yes,” GPT-3 says.

Source:

https://towardsdatascience.com/gpt-3-the-first-artificial-general-intelligence-b8d9b38557a1

GPT-3, artificial neural network with ~175 billion parameters by OpenAI:

https://en.wikipedia.org/wiki/GPT-3

The Singularity

In physics, a singularity is a point in spacetime where our currently developed theories are not valid anymore, we are literally not able to describe what happens inside, cos the density becomes infinite.

The technological Singularity, as described by Transhumanists, is a grade of technological development, where humans are not able to understand the undergoing process anymore. The technological environment starts to feed its own development in an feedback loop - computers help to build better computers, which helps to build better computers, that helps to build better computers...and so on.

So, when will the technological Singularity take off?

Considering the feedback loop, it is already present, maybe since the first computers were built.

Considering the density of information processing that exceeds human understanding, we may reached that point too.

Imagine a computer technique that is easy to set up and use, outperforms any humans in its task, but we can not really explain what happens inside, it is a black box.

Such an technique is present (and currently hyped) => ANNs, Artificial Neural Networks.

Of course we do know what happens inside, cos we built the machine, but when it comes to the question of reasoning, why the machine did this or that, we really have an black box in front of us.

So, humans already build better computers with the help of better computers, and humans use machines that outperform humans in an specific task and are not really able to reason its results....

obviously, +1 points for the Singularity to take off.

AI - Antichrist

"Technology itself is neither good nor bad. People are good or bad."
Naveen Jain

Actually i believe the Revelation as described in the Bible already happened, about 60 AD. And the beast with the number 666 has to be identified with the Roman Empire and Caesar Nero.

But inspired by this blog, i will give a modern interpretation a try, so feel free to join me in an alternate and speculative world paradigm...

Short version

Technology is the Antichrist, and computer driven AI is the peak of technology.

Preamble

Over 10000 years ago we left Garden Eden and started the neolithic revolution, we started to do farming and keep livestock, we started to use technology to make our lifes easier, but over the centuries and millennia, we forgot how to live with mother earth in an balanced way.

Full version

Revelation 13:4

"And they worshipped the dragon which gave power unto the beast: and they worshipped the beast, saying, Who is like unto the beast? who is able to make war with him?"

[update 2024-02-22]

An AI as Antichrist, Chess as war game, who is going to beat the AI in Chess?

Revelation 13:18

"Here is wisdom. Let him that hath understanding count the number of the beast:  for it is the number of a man; and his number is Six hundred threescore and six."

Using the english-sumerian gematria system, which is based on 6 - A=6, B=12, C=18...Z=156, the word "computer" counts to 666.

The first human to mention the word computer for people doing computations was Richard Braithwait in a book called "The Yong Mans Gleanings" in 1613.

Using the english-sumerian gematria method, the name "Braithwait" counts to 666.

Rev 13:18 could act like a puzzle with an checksum, "computer" is the name of the beast, but the name (the number) was coined by a man, and the man who coined the name has the number 666 too.

Revelation 13:16-17

"And he causeth all, both small and great, rich and poor, free and bond, to receive a mark in their right hand, or in their foreheads: And that no man might buy or sell, save he that had the mark, or the name of the beast, or the number of his name."

Nowadays, without an Smart Phone (or upcoming Smart Glasses), or an computer, you are limited in your daily business, from renting a car to doing payments.

So the mark is already here, the Smart Phone in the right hand, the upcoming Smart Glasses in the forehead, and the computer in general.

Revelation 13:15

"And he had power to give life unto the image of the beast, that the image of the beast should both speak, and cause that as many as would not worship the image of the beast should be killed."

An image of the beast is given life and people are going to worship it...AI God Religion Spotted

Revelation 16 - The Seven Bowls of God’s Wrath

Rev 16:2

"And the first went, and poured out his vial upon the earth; and there fell a noisome and grievous sore upon the men which had the mark of the beast,  and upon them which worshipped his image."

Considering computers as the mark of the beast, the sore could be cancer caused by radiation.

Rev 16:3

"And the second angel poured out his vial upon the sea; and it became as the blood of a dead man: and every living soul died in the sea."

Our sea world is dying, overfishing, plastic particles, acidification, etc.

Rev 16:4

"And the third angel poured out his vial upon the rivers and fountains of waters; and they became blood"

Blood in Judaism is impure and Jews are not allowed to eat it, this could mean that our rivers get poisoned.

Rev 16:8-9

"And the fourth angel poured out his vial upon the sun; and power was given unto him to scorch men with fire. And men were scorched with great heat, and blasphemed the name of God, which hath power over these plagues: and they repented not to give him glory."

Climate Change causes already increasing heatwaves and droughts.

Rev 16:10-11

"And the fifth angel poured out his vial upon the seat of the beast; and his kingdom was full of darkness; and they gnawed their tongues for pain, And blasphemed the God of heaven because of their pains and their sores, and repented not of their deeds."

This one can be interpreted as God shutting the internet down, the kingdom of the beast. Some scientists conclude that a pole-shift is currently underway, this could cause the magnetic field around earth to collapse, so the electro-magnetic waves from the sun could damage computer chips worldwide.

[update 2020-11-04]

Pretty obvious the Internet seems a natural fit to be the kingdom of the beast (a computer driven AI) so what does it mean it was 'full of darkness', hehe, ever wondered about the dark-web, fake-news, hate-speech etc.? Darkness.

Rev 16:12-14

"And the sixth angel poured out his vial upon the great river Euphrates; and the water thereof was dried up, that the way of the kings of the east might  be prepared. And I saw three unclean spirits like frogs come out of the mouth of the dragon, and out of the mouth of the beast, and out of the mouth of the false prophet. For they are the spirits of devils, working miracles, which go forth unto the kings of the earth and of the whole world, to gather them to the battle of that great day of God Almighty."

This one is clear, the Euphrates river dries up, and it is scary to watch it  really happen. Dunno about the frogs and kings.

Rev 16:17-21

"And the seventh angel poured out his vial into the air; and there came a great voice out of the temple of heaven, from the throne, saying, It is done. And there were voices, and thunders, and lightnings; and there was a great  earthquake, such as was not since men were upon the earth, so mighty an  earthquake, and so great. And the great city was divided into three parts, and the cities of the nations fell: and great Babylon came in remembrance before God, to give unto her thecup of the wine of the fierceness of his wrath. And every island fled away, and the mountains were not found. And there fell upon men a great hail out of heaven, every stone about the weight of a talent: and men blasphemed God because of the plague of the hail;  for the plague thereof was exceeding great."

An earthquake, so strong, never happened before during mankind.

[update 2023-06-16]

Maybe the seventh bowl is global nuclear war/strike? The final.

Closing Words

There are many passages in the Revelation i can not interpret in a way that the computer is the Antichrist. The seven heads, horns and ten crowns of the dragon, the mortal wound, or the first and second beast, etc.

The Roman Empire with Caesar Nero as Antichrist simply fits better.

But please leave a comment, if you have further puzzle pieces for AI Antichrist.

So, considering the pure potential of the meme AI Antichrist,

i give -1 points for the Singularity to take off.

On Artificial Neural Networks

It is non-stop in the news, every week it pops up in another corner, AIs based on Deep Neural Networks, so i will give it a try to write a lill, biased article about this topic...

The brain

The human brain consists of about 100 billion neurons, as much as stars in our galaxy, the Milky Way, and each neuron is connected via synapses with about 1000 other neurons, resulting in 100 trillion connections.

For comparison, the game playing AI, AlphaZero, by Google Deepmind used about 50 million connections to play chess on super human level.

The inner neurons of our brain are connected via our senses, eyes, ears, etc, with the outer world.

One neuron has multiple, weighted inputs and one ouput, if a certain threshold of input is reached, its output is activated, the neuron fires an signal to another neuron.

The activation of the synapse is an electrical and chemical process, neurotransmitters can restrain or foster the activation potential, just consider the effect alcohol or coffee has to your cognitive performance.

Common artificial neural networks do not emulate the chemical part.

The brain wires these connections between neurons during learning, so they can act as memory, or can be used for computation.

The "von Neumann" architecture

Most nowadays computers are based on the von Neumann architecture, they have no neurons or synapses but transistors.

The main components are the ALU, Arithmetic Logic Unit, memory for program and data,  and various inputs and outputs.

Artificial Neural Networks have to be built in software, running on these von Neumann computers.

Von Neumann said that his proposed architecture was inspired by the idea of how the brain works, memory and computation. And in his book, "The Computer and the Brain", he gives an comparision of computers and the knowledge about biological neural networks of that time.

Dartmouth

First work on ANNs were published already in the 1940s, and in 1956 the "Dartmouth Summer Research Project on Artificial Intelligence" was held, coining the term Artificial Intelligence, and marking one milestone in AI. The work on ANNs continued, and first neuromorphic chips were developed.

AI-Winter

In the 1970s the AI-Winter occurred, problems in computational theory and the lack of compute power needed by large ANNs, resulted in cutting funds, and splitting the work into strong and weak AI.

Deep Neural Networks

With the rise of compute power (driven by GPGPU), further research, and Big Data, it was possible to train faster better and larger networks in the 21st century.

The term Deep Neural Networks, for deep hierarchical structures or deep learning techniques was coined.

One of the first and common usage for ANNs was and is pattern recognition, for example character recognition.

You can train a neural network with a set of the same, but different looking character, with the aim that the ANN will recognize the same character in various appearances.

With a deeper topology of the neural network, it is possible to identify for example pictures of cars with different net layers for color, shape etc.

The Brain vs. The Machine

A computer can perform fast arithmetic and logical operations, therefore the transistors are used.

Contrary, the neural network of our brain works massiv parallel.

The synapses of the human brain are clocked with 10 to 100 hertz, means they can fire to other neurons up to 100 times per second.

Nowadays computer chips are clocked with 4 giga hertz, means they can compute 4 000 000 000 operations per second per ALU.

The brain has 100 billion neurons, 100 trillion connections and consumes ~20 watt, nowadays biggest chips have 12 billion transistors with an usage of 250 watt.

We can not compare the compute power of an brain directly with an von Neumann computer, but we can estimate what kind of computer we would need to map the neural network of an human brain.

Assuming 100 trillion connections, we would need about 400 terabytes of memory to store the weights of the neurons. Assuming 100 hertz as clock rate, we would need at least 40 petaFLOPS (floating point operations per second) to compute the activation potentials.

For comparison, the current number one high performance computer in the world is able to perform ~93 petaFLOPS, has ~1 petabyte memory,  but an power consumption of more than 15 megawatt.

So, considering simply the energy efficiency of the human brain,
i give -1 points for the Singularity to take off.

Super AI in Sci-Fi

Books and movies address our collective fears, hopes and wishes, and there seems to be in main five story-lines concerning AI in Sci-Fi...

Super AI takes over world domination
Colossus, Terminator, Matrix

Something went wrong
Odyssey 2001, Das System, Ex Machina

Super AI evolves, the more or less, peacefully
Golem XIV, A.I., Her

The Cyborg scenario, man merges with machine
Ghost in the Shell, #9, Trancendence

There are good ones, and there are bad ones
Neuromancer, I,Robot, Battle Star Galactica

+1 points for the Singularity to take off.

Robophilosophy 2018

Human Philosophers discuss the impact of social robots on mankind, still no Strong AI in sight that joins the debate.

Cherry piking...

The Moral Life of Androids - Should Robots Have Rights?
Edward Howlett Spence

"The question I explore is whether intelligent autonomous Robots will have moral rights. Insofar as robots can develop fully autonomous intelligence, I will argue that Robots will have moral rights for the same reasons we do. ..."

Robot Deus
Robert Trappl

"The ascription of god-like properties to machines has a long tradition. Robots of today invite to do so. We will present and discuss god-like properties, to be found in movies as well as in scientific publications, advantages and risks of robots both as good or evil gods, and probably end with a robot theology."

+1 points for the Singularity to take off.

The Turing Test

“He who cannot lie does not know what truth is.”
Friedrich Nietzsche, Thus Spoke Zarathustra

The Turing Test, proposed by Mathematician Alan Turing in 1950, was developed to examine if an AI reached human level intelligence.

Simplified, a person performs text chats with an human and the AI, if the person is not able to discern which chat partner the AI is, then the AI has passed the Turing Test.

The Loebner Prize performs every year a Turing Test contest.

It took me some time to realize, that the Turing Test is not so much about intelligence, but about lying and empathy.

If an AI wants to pass the Turing Test it has to lie to the chat partner, and to be able to lie, it has to develop some level of empathy, and some level of selfawareness.

Beside other criticism, the Chinese Room Argument states that no consciousness is needed to perform such an task, and therefore other tests have been developed.

Personally I prefer the Metzinger-Test, a hypothecical event, when AIs start to discuss with human philosophers and defend successfully their own theory of consciousness.

I am not sure if the Singularity is going to take off, but i guess that the philosophers corner is one of the last domains that AIs are going to conquer, and if they succeed we can be pretty sure to have another Apex on earth

Turing predicted that by the year 2000 machines will fool 30% of human judges, he was wrong, the Loebner Prize has still no Silver Medal winner for the 25 minutes text chat category.

So, -1 points for the Singularity to take off.

AlphaZero - The Krampus Has Come

Okay, this one affected me personally.

Google's Deepmind team adapted their AlphaZero approach for the games of  chess and shogi and dropped the bomb already on the 5th of December.

https://arxiv.org/abs/1712.01815

For chess they trained the Deep Neural Network for 4 to 9 hours on an  cluster with 5000+64 TPUs (1st+2nd gen) and reached super human level.

Unlike in Go, they did not compete with humans, cos chess engines are already on an super grandmaster like level, no, they did compete with the worlds strongest open source engine - Stockfish, result:

100 game match with 28 wins, 72 draws, and zero losses for AlphaZero.

This is definitely a smack in the face for all computer chess programmers out there. Next stop Neanderthal Man.

So, with thanks to the Krampus,
+1 points for the Singularity to take off.

Super AI Doomsday Prophets

They are smart, they have money, and they predict the Super AI Doomsday:

Stephen Hawking
"The development of full artificial intelligence could spell the end of the human race.”

James Lovelock
"Before the end of this century, robots will have taken over."

Nick Bostrom
"Some little idiot is bound to press the ignite button just to see what happens."

Elon Musk
"Artificial intelligence is our biggest existential threat."

So, obviously, +1 points for the Singularity to take off.

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