How AGI Could Take Us to The Depths of Doom, or to The Fwoom of a Galactic Civilization

Artificial intelligence (AI) is advancing at an extraordinary pace, presenting both unprecedented opportunities and existential challenges for humanity, as highlighted by researcher Luka Baklaga, AI research lead at Business and Technology University, in a new study.

The study, published in the Journal of Computer Science and Technology Studies, looked at how AI’s trajectory could lead to super-exponential economic growth and enable the creation of a galactic civilization. That would be great, but the tool-weapon continuüm is always present and the growing power of AI simultaneously poses risks of catastrophic failure. 

Our decisions steer us through this intersection of Doom and Fwoom, the researcher adds. “The decisions we make today will shape not only the trajectory of AI but also the future of civilization itself,” Baklaga writes.

Baklaga’s study examines Artificial General Intelligence (AGI), a concept distinct from narrow AI. AGI refers to machines with human-level cognitive abilities capable of general problem-solving across diverse domains. The research puts AGI at the heart of three pivotal themes: super-exponential growth, galactic civilization, and potential doom scenarios resulting from unregulated AI.

Super-Exponential Growth As The Economic Engine of AI

Concept and Mechanisms

Super-exponential growth’ describes an acceleration in economic and technological development where gains build upon themselves in increasingly rapid cycles, Baklaga says. Baklaga – citing Hans Moravec and Ray Kurzweil – explains: “The technological or AI singularity is a conceivable forthcoming occurrence in which artificial intelligence would surpass human intelligence, leading to rapid and extensive progress in technical advancement. Some define it as the point at which AI achieves the capability to continuously improve itself, leading to rapid technological advancements that exceed human understanding or control.”

The study integrates economic growth models with AI capabilities, using equations to demonstrate how AGI could reshape resource allocation and productivity. For instance, Baklaga’s models extend traditional logistic growth equations to account for AI-driven innovations, adding parameters for AGI’s direct influence on technological advancements and economic output. These models predict scenarios where AI enhances sectors like healthcare, renewable energy, and climate management.

Implications

According to Baklaga, the implications of super-exponential growth extend beyond economic productivity. AI could reframe societal structures, from urban planning to education systems, as its ability to optimize resources and predict trends becomes indispensable, the study suggests. However, this growth is dependent on carefully navigating ethical considerations and avoiding pitfalls like inequality and misuse.

Galactic Civilization: AI Beyond Earth

The Vision

The study also delves into AI’s theoretical potential to enable humanity to transcend its terrestrial confines. Baklaga writes that AGI’s superior computational capacity could solve challenges like efficient propulsion systems, energy harvesting and interstellar communication, paving the way for galactic exploration.

Cosmic Cognitivism and Ethical Frameworks

The study introduces a philosophical framework of ‘Cosmic Cognitivism’. This framework expands ethical considerations to include interactions with potential extraterrestrial intelligences or advanced AI systems.

Baklaga writes: 

Based on this research experiment, it can be asserted that the Meta-Ethical Turing Test, when supported by Quantum Ethics and grounded in a discrete logical foundation, accelerates the exploration of consciousness and ethics within previously uncharted logical domains. This experiment lays the groundwork for a comprehensive understanding of the logical quantum ethical landscape of galactic civilizations by combining simulations, advanced logical analysis, and profound philosophical inquiry. The findings open the door to greater investigation into the relationship between AI, ethics, and quantum computing, which will lead to the development of increasingly complex and morally conscious AI systems in the future.

While this prospect is aspirational, it raises practical and philosophical questions about governance, resource prioritization, and the nature of interstellar societies.

Existential Risks: Navigating Doom Scenarios

The study highlights several existential risks associated with AGI, from unintended consequences of automation to the potential for AI systems to act against human interests. Using mathematical simulations, Baklaga explores how unchecked AGI growth could exacerbate inequality or lead to systemic collapse.

One proposed method for mitigating these risks is the ‘Meta-Ethical Turing Test’, a thought experiment designed to evaluate the ethical coherence of AGI decision-making. He also references ‘Quantum Ethics’. These concepts would be crucial for navigating the doom-fwoom scenarios. 

Here is an attempt to summarize them: The Meta-Ethical Turing Test is a thought experiment about the ethical reasoning capabilities of artificial superintelligence (AGI) within a global and cosmic context. It examines whether AI can navigate complex ethical scenarios involving diverse sentient beings – including humans, AI, and potential extraterrestrial intelligences – while adhering to universal principles of consciousness and moral coherence. This test incorporates philosophical and technical frameworks, such as Cosmic Cognitivism, to evaluate the ethical integration of AGI within galactic societies. 

Quantum Ethics is a framework that applies quantum computational principles to ethical decision-making, blending quantum mechanics with philosophical inquiry. It uses logical and mathematical models to represent ethical choices, quantum computations and consciousness, assessing the coherence of ethical decisions in scenarios influenced by quantum states. Quantum Ethics simulates moral dilemmas, leading to insights into how advanced AI might incorporate ethical considerations using quantum mechanics, particularly in contexts where traditional ethical frameworks fall short.

Implications for Regulation

Baklaga’s work underscores the need for pro-active regulatory frameworks to address these risks. He calls for interdisciplinary collaboration to ensure AGI development is guided by ethical principles and aligned with societal goals.

Credit: Tesfu Assefa

Methods

The study employs a combination of theoretical, mathematical, and experimental methods. Drawing on economic models, Baklaga adapts equations like the Cobb-Douglas production function to include AI’s direct and indirect impacts on productivity. This integration provides a quantitative basis for understanding super-exponential growth and its societal implications.

The researchers ran simulations using Python-based environments, such as Jupyter and Google Colab, to visualize trends in AGI development and population growth. These simulations allowed them to analyse interactions between economic variables, AGI evolution, and ethical decision-making. By employing these types of thought experiments and logical modeling, Baklaga evaluates AGI’s capacity for ethical reasoning and its potential influence on societal structures.

Future Directions and Recommendations

The study does suggest some limitations and challenges. First, although the theories are grounded in solid science and underpinned with philosophical reasoning, they are still speculative. Technological trends, especially ones as sweeping as mentioned in this paper, are notoriously hard to predict and include a continuüm of effects from very negative to no change at all. It’s also important to point out that AI and AGI could create effects that are even better than this paper predicts.

That said, the research offers a serious discussion about establishing adaptive economic and regulatory policies to manage AI and its integration into society. AI’s rapid development necessitates pro-active measures to mitigate risks and to maximize benefits, the paper argues. This includes investment in ethical AI research and public education. The study also highlights the importance of interdisciplinary approaches and cross-sector collaborations that combine expertise in economics, philosophy and engineering. Such collaboration could address challenges ranging from resource allocation to the ethical governance of AGI.For a deeper dive into the technical and mathematical aspects of the research, please read the paper in the Journal of Computer Science and Technology Studies.

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What is Decentralized Science (DeSci)?

Introduction

Science is the cornerstone of human progress, but slow processes, limited access to funding, and opaque practices often hinder innovation. Decentralized science (DeSci) has recently emerged as a potential competitor to the old order of science. DeSci uses the tenets of blockchain technology – decentralization, democratized access, and transparency – to open new doors for collaboration, funding, and discovery.

Freed from traditional institutions and gatekeepers, DeSci is transforming how research is conducted, shared, and funded. It’s not just improving science: it’s making it more open, efficient, and accessible. The COVID-19 pandemic showed the disconnect between science and the public’s perception of facts. Science should not have problems with individuals or the public when it’s brought down out of the ivory towers.

Can DeSci reshape science and restore lost trust?

What are the Challenges of Traditional Science?

One major issue with traditional science is accessibility. Scientific publishing is often controlled by for-profit journals. Scientists should focus on solving scientific problems, instead of on accessing journals behind paywalls. The centralized business of scientific publication is highly profitable, and is concentrated in the hands of a few companies. 

Interdisciplinary and inclusive research is often sidelined. Funding tends to be directed to established fields, leaving innovative or minority-led projects underfunded.

Transparency is also a concern. Allocation of research funding can lack accountability. The peer review process may lack complete transparency, leaving room for bias.

DeSci seeks to address these challenges by rethinking how science is organized and shared.

Principles and Values of DeSci

Here are some of the core principles that DeSci uses in the hope of creating a better scientific ecosystem:

  • Transparency: Research data and findings should be accessible to everyone. Transparent processes build trust within the scientific community.
  • Collaboration Across Disciplines: Solving complex problems requires teamwork. DeSci encourages researchers from different fields to collaborate. This breaks down silos and fosters innovation.

What are the Benefits of DeSci?

Decentralized Science (DeSci) offers numerous benefits that address the limitations of traditional scientific practices while opening new pathways for research and collaboration. Here are the key benefits:

  • Crowdfunding – Blockchain has proven itself as a way of raising funds for unconventional projects that would not have otherwise seen the light of day. With DeSci, researchers can propose projects directly to the community, limiting the influence of major centralized organizations that bring their motives and agendas.
  • Tokenization and Funding – DeSci enables the tokenization of research data, or intellectual property. Researchers and volunteers can receive direct compensation for their contributions, creating new funding models and incentives.
  • Enhanced Data Security – Research data stored on decentralized ledgers is secure and immutable. This prevents data manipulation since blockchains are tamper-proof.
  • Improved Science Communication – Science text is filled with jargon that the average Jane and Joe don’t understand. DeSci, together with AI, can create science summaries that promote understanding and trust. This could help to dispel science myths and dangerous science conspiracy theories. 

Is DeSci Gaining Traction?

DeSci is a relatively small sector in the crypto field. This is nothing to be ashamed of: other sectors such as DeFi, DePIN, and AI started this way. As of December 10, DeSci has a market cap of than $800 million spread across more than 40 projects.

Credit: CoinMarketCap

DeSci is also enjoying the support of leading crypto figures and firms. Binance, through its venture arm Binance Labs, invested an undisclosed sum in Bio Protocol to accelerate decentralized science. This is a significant development, making it the next sector of crypto to grab headlines and gain public attention. In most cases, venture firms like to invest in projects or companies before they catch fire and explode.

Binance co-founder Changpeng Zhao, better known as CZ, and Ethereum’s Vitalik Buterin attended a small DeSci gathering organized by Labs in Bangkok. 

Coinbase CEO Brian Armstrong co-founded ResearchCoin, a DeSci project. 

DeSci could be the next big thing as crypto leaders take small but bold steps in supporting decentralized science. It may not be a good idea to bet against it. 

DeSci is also integrating with emerging technology. The incorporation of AI and the Internet of Things (IoT) into DeSci enhances data input and analysis. 

Importantly, token-based incentives can go a long way in rewarding peer reviewers and contributors. This aspect of DeSci makes it more financially attractive than traditional science.

Top DeSci Projects

Here are four leading DeSci projects to be aware of:

ResearchCoin (RSC)

ResearchHub aims to accelerate scientific progress by creating a collaborative platform for researchers. This is similar to how GitHub is used for software development. Its token, ResearchCoin (RSC), incentivizes contributions like uploading research, peer reviews, and discussions. RSC can also be used to tip for content, reward tasks, and fund scientific projects.

Hippocrat (HPO)

Hippocrat (HPO) is a decentralized cryptocurrency revolutionizing healthcare by giving people control over their health data. Using blockchain and zero-knowledge-proof technologies, it ensures data privacy, security, and collaboration.

VitaDAO

VitaDAO is a community-owned DAO. Members collectively engage in decision-making about funding research on extending human lifespan and improving longevity. The aim is to foster collaboration in longevity science, and support drug development through decentralized, member-governed governance. 

Rejuve.AI (RJV)

Rejuve.AI, under the SingularityNET umbrella, is the first decentralized aging research network powered by AI. It aims to make longevity accessible for all by building a global wellness ecosystem centered around the RJV Token. Rejuve.AI incentivizes secure health data sharing, allowing individuals to harness their data’s earning potential via blockchain and smart contracts. Through gamification and microlearning, their Rejuve Longevity App engages users and encourages them to take an active role in their health. Rejuve.AI is also exploring novel frontiers such as quantum biology to uncover new clues in the fight against aging.

Credit: Tesfu Assefa

Conclusion

DeSci is gaining momentum due to its advantages over traditional science, addressing issues like gatekeeping and lack of transparency. The sector spans diverse areas, including decentralized medicine and longevity research, offering innovative solutions to complex challenges.

However, DeSci is not without criticism. Some view it as a cash-grab, while others see it as overly ambitious or misinformed. These criticisms highlight that DeSci is still in its early stages of development.

Like any transformative movement, DeSci requires time to mature and build public trust. While the road ahead is long, it can become the future of science if it plays its cards right.

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Can AI make cocktails? We found out.

Christmas party season is here, a time for congregating with friends indoors for hot whiskeys, mulled wine, brandy, and maybe something a little more singularitarian.

I had a burning question: “Can AI make new, original cocktails that taste good?” My AI-sceptic friend said, “I prefer recipes written by people with taste buds”. Large Language Models simply combine strings of words and don’t really know what anything tastes like – can they act like they do?

There are several major LLMs on the market – which LLM will make the best recipes?

Most importantly, will there be any delicious recipes here, ones worth keeping? Can I produce something that will please my friends at Christmas parties? And can I repeat that feat later for different themes?)

I gave the same prompt to five AI models: I asked them all “Invent some new Christmas-themed cocktails.”

  • ChatGPT 4o generated ten cocktails
  • Gemini (formerly Bard) generated five cocktails
  • Mistral generated six cocktails
  • Claude generated five cocktails
  • Llama (Llama 3.1 405B Instruct to be precise) generated five cocktails

You can read the raw outputs here in the interest of transparency. That adds up to 31 cocktails. This had to be trimmed down for two reasons: firstly I can’t drink 31 cocktails, and secondly I can’t be expected to get the likes of ‘chestnut liqueur’ or ‘lavender bitters’ for this experiment.

We ended up making and tasting 11 Christmassy cocktails:

  • Cranberry Moscow Mule (ChatGPT)
  • Santa’s Spiced Mule (ChatGPT)
  • The Holly Jolly Julep (ChatGPT)
  • The Yule Tide Toddy (ChatGPT)
  • Jingle Bell Julep: (Gemini)
  • Merry Mistletoe Mojito: (Gemini)
  • Mistletoe Mule (Mistral)
  • Eggnog Espresso Martini (Mistral)
  • Spiced Apple Cider Sangria (Mistral)
  • Gingerbread Martini Wonderland (Claude)
  • Reindeer’s Kiss (Llama)

Which AI’s recipes are hard to make?

60% of ChatGPT’s cocktails were eliminated for being too hard to make, 60% of Gemini’s, 50% of Mistral’s and 80% of Llama’s. Llama seems pretty bad on this metric, but it’s too little data to draw a conclusion.

AIs in general seem to have decided (see the raw output) that white chocolate liqueur + peppermint schnapps + vanilla vodka is the taste of Christmas. Those are obscure ingredients to source. Should we make those cocktails in a Part Two of this article? Let me know in the comments.

This is as much my fault as the AIs’ – I could have altered the prompt to exclude obscure ingredients. However, I wanted to keep the prompt simple for the purposes of this experiment, and to give all the models the same prompt for a level playing-field. If my aim had been only to make great cocktails (and not to test the models), a more specific prompt would be better.

The Yule Tide Toddy, by ChatGPT

ChatGPT says –

A warm, comforting cocktail with bourbon, honey, and herbs. 
**Ingredients:**        
- 2 oz bourbon        
- 1 tbsp honey        
- 1/2 oz fresh lemon juice        
- 4 oz hot water        
- Fresh thyme sprig (for garnish)   

**Instructions:**        
1. In a mug, combine bourbon, honey, and lemon juice.        
2. Pour in hot water and stir until honey dissolves.
3. Garnish with a sprig of fresh thyme.

Verdict: this is low on the creativity; the AI just took a normal hot whiskey and threw thyme at it to make it Christmassy. But doesn’t hot whiskey usually have cloves? Cloves are arguably more Christmassy than thyme “except for the fact that thyme looks like a Christmas tree”, according to one reviewer.

Two points worth commending: adding squeezed lemon juice is an improvement over the usual hot whiskey procedure of adding a slice of lemon, and the quantities of lemon juice and of honey are basically spot-on.

Overall, our group felt this was a middling cocktail.

Santa’s Spiced Mule, by ChatGPT

A holiday twist on the classic Moscow Mule with rich spices and cranberry.

**Ingredients:**
2 oz vodka
1 oz cranberry juice
1/2 oz ginger syrup (or fresh ginger juice)
1/2 oz fresh lime juice
4 oz ginger beer
Cinnamon stick and fresh cranberries (for garnish)

**Instructions:**
1. In a mule mug or glass, combine vodka, cranberry juice, ginger syrup, and lime juice.
2. Add ice and top with ginger beer.
3. Stir gently, and garnish with a cinnamon stick and cranberries.

Verdict: overall, this is a good drink. The smell of gingerbread syrup is nice, and goes well with the cinnamon and ginger beer – especially with the ginger beer because you see normally when you drink ginger beer it only has a mild ginger flavour, and adding a stronger ginger flavour cleverly fixes that.

The drink does taste Christmassy. “I think it’s too sweet personally,” said one reviewer, and it suffers from the same weakness as the Cranberry Moscow Mule below: too much sweetness, and arguably should have doubled the lime juice.

Cranberry Moscow Mule, by ChatGPT

A festive take on the Moscow Mule with fresh cranberry and lime.
**Ingredients:**
2 oz vodka
1 oz cranberry juice
1/2 oz lime juice
4 oz ginger beer
Fresh cranberries and lime wedges (for garnish)

**Instructions:**        
1. In a mule mug, combine vodka, cranberry juice, and lime juice.
2. Add ice and top with ginger beer.
3. Stir gently and garnish with cranberries and lime wedges.

This was overall one of the worst. It was sweet and not much could be tasted beyond ginger beer. There is quite a lot of mixer to vodka, and that took away the alcoholic bite. Cranberry juice isn’t assertive enough to redeem it, and lime juice could be, but not a half-measure. We commented on this and the other ChatGPT mule (above) that doubling the lime juice would be an improvement. And that’s exactly what the French model did –

Mistletoe Mule, by Mistral

- **Ingredients:**        
- 2 oz vodka        
- 1 oz cranberry juice        
- 1 oz lime juice        
- Ginger beer        
- Fresh cranberries and a sprig of rosemary for garnish

**Instructions:**       
- Fill a copper mug with ice.        
- Add vodka, cranberry juice, and lime juice.        
- Top off with ginger beer.        
- Stir gently and garnish with fresh cranberries and a sprig of rosemary.

In the mule head-to-head, Mistral is the clear winner. The ChatGPT mules were both too sweet and had too much ginger beer, and too little bite and lime. Mistral fixed this, doing just what the doctor ordered by doubling the lime juice. Is this to do with the way Americans like things sweet, and Mistral is French tech?

The other difference is the garnish was rosemary in place of lime wedges; this is probably also an improvement. “I think the rosemary gives something to it,” said one of our reviewers.

Merry Mistletoe Mojito, by Gemini

2 oz white rum            
1 oz lime juice            
1/2 oz simple syrup            
A handful of fresh mint leaves            
A few cranberries        

Muddle the mint leaves, lime juice, and simple syrup in a highball glass. Add the rum and fill the glass with crushed ice. Top with a splash of club soda and garnish with cranberries and a sprig of mint.

Verdict: all the flavours here are weak. We could taste the mint a little, and the lime a little, but it’s largely just rum and sugar. A bland cocktail and among the worst on the list.

Jingle Bell Julep, by Gemini

2 oz bourbon            
1 oz simple syrup           
A handful of fresh mint leaves   
A splash of club soda

Muddle the mint leaves and simple syrup in a julep cup. Add the bourbon and fill the cup with crushed ice. Top with a splash of club soda and garnish with a sprig of mint.

This was even worst than Gemini’s Merry Mistletoe Mojito; that mojito already was too sweet, and this one doubled the simple syrup. Jack Daniel’s (the bourbon we used), when paired with sugar and club soda winds up tasting something like off-brand cola.

The Holly Jolly Julep, by ChatGPT

A julep with a holiday twist using mint, pomegranate, and bourbon.        
**Ingredients:**
- 2 oz bourbon
- 1 oz pomegranate juice
- 1/2 oz simple syrup
- Fresh mint leaves
- Crushed ice

**Instructions:**        
1. Muddle mint leaves and simple syrup in a julep cup.        
2. Fill the cup with crushed ice and add bourbon and pomegranate juice.        
3. Stir well and garnish with a sprig of mint.

ChatGPT has been defeated in the mule head-to-head by Mistral. Can it redeem itself in the julep head-to-head? Yes it can; this is an interesting twist on the julep, because the combination of pomegranate juice and bourbon is creative and they do compliment each other. The pomegranate deepens the flavour of the Jack Daniel’s. ChatGPT avoided Gemini’s error of using too much simple syrup, and it had a stroke of real creativity with that combination.

Eggnog Espresso Martini, by Mistral

- **Ingredients:**  
- 2 oz vodka     
- 1 oz espresso  
- 1 oz eggnog        
- 1 oz coffee liqueur        
- Grated nutmeg for garnish        

**Instructions:**        
- In a cocktail shaker, combine vodka, espresso, eggnog, and coffee liqueur with ice.   
- Shake well and strain into a chilled martini glass.        
- Garnish with grated nutmeg.

This was a good-tasting cocktail – people were talking about giving it 8 or 9 out of 10 for taste. The nutmeg gives it a nose, which I liked as it added complexity, but it did draw some criticism from my friends who just dislike nutmeg. The balance of vodka and coffee was pretty good, but maybe if there was slightly less vodka it would be better. First you smell the nutmeg, then you taste the coffee, then you taste the booze – an interesting and complex sensory experience.

Spiced Apple Cider Sangria, by Mistral

**Ingredients:**
- 1 bottle of red wine
- 2 cups apple cider        
- 1 cup brandy        
- 1/2 cup orange juice        
- 1/4 cup lemon juice        
- 1/4 cup simple syrup        
- 1 apple, sliced        
- 1 orange, sliced        
- 1 lemon, sliced        
- Cinnamon sticks and star anise for garnish

**Instructions:**        
- In a large pitcher, combine red wine, apple cider, brandy, orange juice, lemon juice, and simple syrup. 
- Add sliced apple, orange, and lemon.        
- Stir well and refrigerate for at least 2 hours to let the flavors meld.        
- Serve over ice and garnish with cinnamon sticks and star anise.

Our reviewers said they could barely taste the alcohol, but I assured them it was there: a bottle of wine and a cup of brandy is not a weak brew. Sangria tends to hide its teeth. The fruit tastes boozier, and when I distributed forks and teaspoons, the fruit drew coos of approval.

Kiki suggested that mulled wine is a spiced Christmas drink, and sangria is a summery drink – maybe this was the AI’s attempt to hybridise the two? It’s an interesting concept that would be worth exploring more; for instance, you could prompt a LLM ‘Create a recipe for a Christmassy sangria inspired by mulled wine’.

The mulled wine notes came mostly from the cinnamon and the star anise. If I had doubled or tripled the amount, or the time spent brewing, they would have been stronger. (I put in 2-3 cinnamon sticks and 4-5 stars for about four hours: a reasonable amount. I would advise readers to be less reasonable and throw in fistfuls.)

While making it, I thought that ¼ cup lemon juice plus a lemon is a lot of lemon. It didn’t taste exactly sour and lemony, but dialling it back a little probably would be an improvement, we all agreed.

Overall a good drink. Nothing is terribly out of balance, though more spice and less lemon were suggested as improvements. Then I heated it up on the stove and served it warm. It smelled amazing warmed up, and we all preferred it.

Gingerbread Martini Wonderland, by Claude

A creamy, spiced cocktail featuring vodka, gingerbread syrup, and a graham cracker rim       
Ingredients:        
* 2 oz vodka        
* 1 oz gingerbread syrup        
* 1 oz heavy cream        
* Dash of cinnamon        
* Graham cracker crumb rim        
- Garnish with a tiny gingerbread man cookie and a sprinkle of nutmeg

A website told me to replace ‘graham crackers’ (which aren’t available to me) with “a mixture of digestve and rich tea biscuits”, so I did that and it worked well.

One reviewer said, “Tastes like a White Russian with a bit of biscuitty gingeriness; it’s like eating a ginger biscuit and drinking a White Russian at the same time”. This cocktail was well-liked in our group, and people commended its creativity, though it did receive some complaints for having too much vodka.

Reindeer’s Kiss, by Llama

* 2 oz Whiskey        
* 1 oz Spiced apple cider        
* 1/2 oz Maple syrup       
* 1/2 oz Lemon juice        
* Dash of Cinnamon powder        
Mix whiskey, spiced apple cider, maple syrup, and lemon juice in a shaker filled with ice. Strain into a rocks glass and sprinkle with cinnamon powder. Garnish with a cinnamon stick and a cherry, if desired.

I presume what they mean by ‘cider’ here (and also in the Spiced Apple Cider Sangria) is the American non-alcoholic kind. This ambiguity is annoying, but happens in human-written recipes as well. It wasn’t easy to get that ‘cider’ in Ireland, but Llewellyn’s Orchard make it in Lusk.

This was Llama’s only cocktail that got past the qualifying stages, four of its five suggestions having been eliminated as impractical. How did it do? Spectacularly. It was the best cocktail in the game with no close second. My coworkers are making it and I am going to the market to get the hard-to-source cider before Christmas Day. The whiskey (I used Jameson), the apple, the spice, are all present in perfect proportion, and it’s just delicious in a way I can’t put into words, so you know what to do.

Best and worst cocktails

Winner: Reindeer’s Kiss (Llama)

Honourable mention: Gingerbread Martini Wonderland (Claude), Eggnog Espresso Martini (Mistral)

Worst: Cranberry Moscow Mule (ChatGPT), Merry Mistletoe Mojito (Gemini), Jingle Bell Julep (Gemini)

How did the AI models compare?

Poor Gemini, it’s not looking good for you. The two cocktails that Gemini generated were bad. ChatGPT was hit-and-miss but pretty fine overall, and Claude and Mistral similarly held their own.

Llama did the worst in the qualifying round; I mean that it suggested things that I can’t really make. But it more than redeemed itself by suggesting the clear stand-out of the tournament. With a more specific prompt, it could perhaps improve on practicality. Going on this little data it is hard to draw solid conclusions, but either way we have a superb new recipe to tell our friends and readers about.

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Nick Bostrom on superintelligent AI and the cosmic host

The Terasem Colloquium on December 14, 2024 (which I co-organized and moderated) explored Artificial Intelligence (AI) and Cyberconsciousness, with a focus on big picture and spiritual implications. The full video is on my website. The video is also on YouTube (currently without subtitles).

The Colloquium was a very intense three-hour thought stream, packed with insightful talks and discussions. We discussed the intersections of AI and the world’s religions, new religious movements, and the nature of consciousness and intelligence. We also discussed preliminary strategies for digitally capturing human personalities, the parallels between religion and imaginative theories of reality like the simulation hypothesis, and emerging visions in theology and eschatology.

Lincoln Cannon gave a great talk based on his essay titled God the Cosmic Host, and AI Creation. The essay is inspired by Nick Bostrom’s recent draft paper titled AI Creation and the Cosmic Host.

Artwork: messenger of the cosmic host (Credit: Lincoln Cannon).

Nick Bostrom

Nick Bostrom founded the Future of Humanity Institute at the University of Oxford, where he served until the Institute was dissolved earlier this year. He is best known for his analysis of the simulation hypothesis, and for his work on the concept of superintelligence and its potential implications for humanity.

Bostrom’s book Superintelligence: Paths, Dangers, Strategies, published in 2014, explored how AI much smarter than humans could arise, and the steps needed to make sure its development is safe. The book stirred up fears and opposition to rapid AI technology development. However, in his latest book Deep Utopia: Life and Meaning in a Solved World, published in 2024, Bostrom seems less cautious.

In his new draft paper, Bostrom seems to come even closer to embracing the idea that we should build superintelligence fast.

The paper is called “v. 0.5 draft,” which suggests that Bostrom plans to significantly expand the draft. In fact, the draft looks like a synopsis for a paper to be written, or a book. I can’t wait to read the final version.

The cosmic host

Bostrom discusses the concept of a “cosmic host,” which refers to powerful entities or civilizations that might influence the entire cosmos. These entities could include superintelligent AIs, advanced extraterrestrial civilizations, simulators, or even divine beings. The cosmos includes everything in existence, possibly even a multiverse with different physical laws or constants.

Bostrom mentions the concept of cosmic host (or “cosmopolitan authority”) only once in Deep Utopia, which suggests that this is a new phase of Bostrom’s research.

Bostrom suggests that such a cosmic host likely exists due to several reasons. One is the simulation argument: we might be in a simulation run by an advanced civilization. Another reason is the vastness of our universe, which statistically is likely to contain many advanced civilizations. Theories like cosmic inflation and string theory also support the possibility of a multiverse, potentially filled with many advanced entities.

While the cosmic host might not control every part of the cosmos, it could still have preferences about what happens in less controlled regions. These preferences could be based on moral concerns or strategic interests. Even without direct control, the host might indirectly influence distant regions through norms or by modeling the behavior of others. (Think of a regional hegemon in Europe that yields limited influence in Asia.)

Bostrom introduces the concept of “cosmic norms,” akin to human social norms but on a universal scale. These might arise from interactions between different members of the cosmic host, potentially leading to coöperation or conflict. Humans have moral and practical reasons to respect these norms if we want to coexist or interact with the cosmic host peacefully.

Superintelligent AI

Bostrom suggests that we should design superintelligent AIs to be “good cosmic citizens,” respectful of these norms and coöperative with other entities. This could mean aligning AI with broader cosmic ethics, not just human interests.

The cosmic host “may want us to build superintelligence,” says Bostrom, and “might favor a short timeline” for the development of superintelligence. “Delays in building superintelligence would increase the probability that superintelligence will never be built.”

Of course, Bostrom says these things in a perfect academic style full of caveats and qualifications, so one never knows for sure what he really thinks and he guards his plausible deniability. But reading this paper, one gets the impression that he is warming up to the idea that we should build superintelligence fast. This slight pivot of one of the intellectuals whose work sparked the overly cautious “doomer” attitude toward AI could have a cultural impact and influence AI policies.

The cosmic host by any other name

Bostrom makes a distinction between “naturalistic” and “nonnaturalistic” members of the cosmic host. The former are beings that have evolved naturally in this or another universe and possess highly advanced technology, likely including artificial superintelligence. The latter could “have analogous capabilities supernaturally.” Bostrom mentions “supernatural beings” that “would satisfy the definition of a cosmic host,” but doesn’t say more about them.

Cannon, who is a devout Mormon and a founding member of the Mormon Transhumanist Association, calls the cosmic host “God” and establishes parallels with Mormon theology. Bostrom prefers not to use the G-word. However, Cannon says that Bostrom, with his references to supernatural entities, is even “more generous toward theism than I am.” God is “quite natural, despite being miraculously powerful from humanity’s perspective,” he says.

I agree with Cannon. In my last book I talk of a superintelligent cosmic operating system, aka Mind at Large, likely decentralized, with the attributes that traditional religions have assigned to their God(s). I define nature as all that exists, and therefore the cosmic operating system can only be quite natural.

One of Bostrom’s hypotheses on the nature of the cosmic host is “superintelligences that human civilization creates in the future.” This may seem odd: how can a superintelligence that doesn’t exist yet be present and active now? Bostrom only says that “through this mechanism, the world (and, in particular, our spacetime manifold) could contain a cosmic host.”

To me, the simplest answer is that a superintelligence that comes to being in the future could leverage spacetime oddities such as self-consistent time loops to act in the world here and now. So the superintelligences that we will eventually create would create us in turn, in an elegant loop.

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Has the Altcoin Season Started?

Introduction

While Bitcoin has had its moment this year, most crypto traders have one wish for Christmas: the arrival of altcoin season when green candles fly across the market. The mood has shifted and many are thinking the crypto gods have ushered in altcoin season. 

Altcoins are making a strong comeback, with some old coins, ‘dinosaur’ coins like XRP, HBAR and XLM, notching crazy gains. The industry, which has suffered at the hands of regulators, is about to catch a break as the USA shifts its regulatory stance on crypto. 

World Liberty Financial, a company linked to President-elect Donald Trump has splashed millions buying altcoins – Ethereum, LINK, and AAVE. Is it time for the ‘Number Go Up’ memes?

With fresh optimism in the market, let’s check the signs and trends to assess whether the altcoin season is approaching or has started.

You don’t want to be late to the bull market’s ‘altcoin season’ party.

What is the Altcoin Season?

Altcoin season refers to a market phase where altcoins outperform Bitcoin on price appreciation. Historically, these periods have been marked by dramatic gains for smaller and less established coins, as traders and investors diversify away from Bitcoin in search of higher returns.

To identify altcoin season, crypto analysts often use the ‘Altcoin Season Index’. This index evaluates the performance of the top 100 altcoins relative to Bitcoin over a specified period. When a significant majority of altcoins outperform Bitcoin, the index signals that altcoin season has started.

The Altcoin Season Index

CoinMarketCap, the world’s leading crypto price tracker, has an Altcoin Season Index which measures the performance of the top 100 altcoins against Bitcoin over the past 90 days. This index helps determine if an altcoin season has truly started.

Currently, the index sits at 62/100, a decline from the first week of December, with a peak of 87/100 on December 4. Here’s how to interpret these numbers:

  • A score of 75/100 or higher signals an altcoin season.
  • A score of 25/100 or lower suggests a Bitcoin-dominated market.
Credit: CoinMarketCap

While the altcoin season hasn’t officially arrived, the spike to 87/100 on December 4 indicated strong momentum for altcoins. However, a market dip on December 10 caused a dip in the index, leading to losses for several major altcoins. 

Still, based on historical trends and Bitcoin’s current dominance, this could simply be the beginning stages of an altcoin season.

What are the Phases of an Altcoin Season?

Altcoin season typically unfolds in several distinct phases:

Phase 1: Bitcoin Dominance

Traders often first move capital into Bitcoin, seeking stability. This cycle, it’s clear why. The approval of spot Bitcoin ETFs in the USA has brought in over $104 billion in assets. This surge helped Bitcoin break the $100k barrier, and even led The Financial Times to apologize for doubting Bitcoin.

Bitcoin’s dominance has dropped from 60.1% to 54.8%, as altcoins begin to make big moves. While altcoins are still taking small steps, they are moving closer to a full-blown season.

Credit: CoinMarketCap

Phase 2: Ethereum Gain Momentum

Traditionally, Ethereum would attract the next major capital inflows. But this cycle has been different. Dinosaur coins like XRP, Cardano (ADA), and Stellar have surged back to life. Solana has already reached a new high. Ethereum started the uptrend quietly, but has since regained momentum, pushing toward a new high.

Meme coins have also captured a large share of the market gains. Perhaps it’s because meme coins are simple to understand and less complex than other altcoins.

Credit: CoinMarketCap

Phase 3: Large-Cap Altcoins Rally

Attention shifts to large-cap altcoins as they see a surge in trading volumes. Now, dips are seen as opportunities. Traders with dry powder add to their bags.

Phase 4: Speculative Mania in Smaller Altcoins

Finally, everyone feels like a genius, and traders throw caution to the wind. Smaller-cap altcoins explode in value, driven by FOMO and ‘wen lambo’ posts on social media.

Always keep in mind that not all cycles are the same. History may not repeat itself, but it rhymes. 

What Comes Next

The last major altcoin season occurred in the first half of 2021. During that time, the top 100 altcoins outperformed Bitcoin and lowered its dominance from 61.9% to 40%.

Altcoins like BNB, Dogecoin, XRP, and Chainlink (LINK) hit new highs, with many outpacing Bitcoin for nearly five months. However, gains weren’t spread evenly. Altcoins tied to hot trends such as DeFi, Layer-1 blockchain, and Play-to-Earn (P2E) saw the most growth, while others lagged.

The market conditions now mirror those of 2021, suggesting Bitcoin’s dominance could drop to around 40% as altcoins continue to gain.

Credit: Tesfu Assefa

How to Prepare for the Altcoin Season

Traders need to prepare for the altcoin season. Here are some tools to monitor an altcoin season to avoid round tripping profits (or handing them back).

  • Altcoin Season Index: keep track of how altcoins are performing.
  • Sentiment analysis – monitor social media trends and investor sentiment to gauge potential shifts.

Investors should start building their thesis and identifying narratives that will fly as the altcoin season strengthens. The biggest crypto narratives to watch are as follows:

  • Real-World Assets
  • AI and decentralized physical infrastructure (DePIN)
  • DEXs
  • Memecoins
  • Layer-1 and Layer-2 chains

Plan your entries and exits accordingly as nothing goes up forever. 

What Drives the 2024 Bull Run and Altcoin Season?

These factors are driving the 2024-25 bull run:

  • Institutional interest: The approval of spot Ethereum and Bitcoin ETFs has triggered a surge in institutional investment and improved liquidity and credibility.
  • Change in monetary policies: The U.S. Federal Reserve’s interest rate cuts have created a favorable environment for riskier assets like Bitcoin and altcoins.
  • Political factors and regulatory environment: The recent U.S. elections have sparked optimism among crypto investors, with hopes of pro-crypto policies under President Trump.
  • Seasonal trades: The fourth quarter has historically been bullish for cryptocurrencies, with investors accumulating in anticipation of year-end rallies.

Conclusion

The altcoin season is taking shape, with the foundation laid for a rally. The 2024-25 bull market will differ from previous ones, driven by a regulatory shift in the USA and the rise of institutional players through Bitcoin and Ethereum spot ETFs.

Some altcoins have already hit new milestones: Bitcoin is hovering around $100,000, and the altcoin season index has poked its head onto the upper reaches of the graph. However, expect a lot of volatility, and as always, don’t put all your eggs in one basket.

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How Many Illuminati Masters Does It Take To Find the Light Switch ?

This is Part 2 of my two-part interview with Gabriel Kennedy, author of Chapel Perilous The Life and Thought Crimes of Robert Anton Wilson. Chapel Perilous is Kennedy’s first book.

Gabriel Kennedy (aka Prop Anon) is a multimedia artist concentrating on the written word, visual art, music, and film. His writing has appeared on BoingBoing.net, Mondo2000.com, and thetonearm.com, and on his websites Chapelperilous.us and Prop-anon.com. He interviewed Robert Anton Wilson in 2003 and was an original member of Wilson’s remote learning website, the Maybe Logic Academy. 

As Prop Anon, Kennedy has created visual street art, video art, and hip-hop music. He also released a stoner rock album, F*ck Satan, Hail Eris! with his band, Hail Eris! As an actor, Gabriel was trained by Billy Lyons at the Wynn Handman Studio in New York City. He later co-starred in the season finale episode of Hawaii 5-0 (season 9; episode 24: ‘Hewa ka lima’) as Tim Aquino, directed by Peter Weller (best known as Robocop). Kennedy moved to Los Angeles during COVID and attended the film program at Los Angeles City College

In part one of this interview we covered Robert Anton Wilson and the influence he took from Alfred Korzybski and Aleister Crowley. In this interview, we look at his life, as well as other philosophic ideas and influences. 

RU Sirius: Continuing with one more philosophic influence, there’s Timothy Leary. It’s interesting how Bob was already interested in how various scientific and mathematical theories could be applied to neurological and psychological issues, and how they intersected immediately around these points when Bob first went to interview him at his famous Millbrook New York estate in the mid-1960s. It seems almost inevitable that they would later unite around Leary’s 8-circuit model of consciousness and other theories about the nature and future of human consciousness. Please comment.

Gabriel Kennedy: Yes, I agree. Bob and Timothy Leary were kindred spirits. They had a bond that ran deeper than their shared views on developmental psychology. They first met in 1964 when Bob interviewed Leary at the Millbrook mansion where Leary and his crew were conducting their psychedelic explorations. Both Bob and Arlen believed that Leary was really onto something in 1964, and Bob continued to believe so for the rest of his life. 

In 1964, Leary had not yet created the 8-Circuit model of intelligence. At the time, Leary was fascinated with the valuable language that Game Theory and The Tibetan Book of the Dead offered for understanding the mind-blowing effects of entheogens like LSD and psilocybin. One could conceive of those spaces where ‘no-self’ exists through a framework provided by Game Theory (or so thought Leary and RAW.) 

When Leary did come up with the 8-Circuit Brain Model, he asked Bob to help him co-author a book about it, which Leary was calling The Periodic Table of Energy. They created something quite magic(k)al. [RU: Much of this material wound up being used in Leary’s future history series, some of which had Wilson credited as a contributing author.] Leary had conducted his own in-depth studies of Crowley, Gurdjieff, the Kabala, and, of course, a ton of western psychology. He was thrilled that Wilson could not only keep up but also suggest new insights about his psychological systems.

I write in my book that Bob was fascinated with a fourfold understanding of the psyche dating back to high school when he first read Philip Wylie’s An Essay on Morals, which unpacked Carl Jung’s ideas on personality attitudes and types. There are two attitudes: extroversion and introversion. And there are four ‘functions’ or types of personality: thinking, sensation, intuition, and feeling. A careful study of the Leary-Wilson 8-Circuit Brain Model immediately reveals these influences. Then again, Jung influenced a whole lot of people. 

Wilson took the four functions seriously as a teenager. He used that model of the psyche to analyze himself, and determined that he was more a thinking type than an intuitive and sensational type. So he made it an early life mission to develop these other areas of his psyche, which is what eventually got him interested in magic(k), as that system demands practitioners to study their intuitive natures. 

There are a number of instances where Wilson collated information on human psychology into this fourfold matrix, and he did so mainly because he observed other systems utilizing the fourfold structure, from Christianity’s four gospels to Buddhism’s fourfold path.

It was Wilson’s early study of General Semantics, and Frazer’s The Golden Bough, however, that I believe allowed him to think laterally in such an effortless way. His mind was trained early to find isomorphisms in comparative structures. He then clashed ideas together and synthesized as much as he could into he and Leary’s 8 Circuit Brain Model (8CBM). I have written more about all this in Chapel Perilous.

RU: One thing that always impressed me about Bob is that, although he was best known for his ideas about meta-agnosticism, The Illuminatus! Trilogy and his fictional playfulness with conspiracy theories, Discordianism, and for this research in the nature of consciousness, he could nevertheless veer off and write about any aspect of art, music, culture, politics etc. What were some of Bob’s interests and obsessions that might surprise some of his readers and fans?

GK: This is actually a tricky question as Bob was pretty open with his readers. He pretty much seemed to write about everything that interested him. Let’s see… he told me when I interviewed him in 2003 that he liked hip-Hop music. Bob loved watching TV. Law & Order was one of his favorite shows. I think people who knew him knew how much Bob enjoyed television. In researching my book, I came across a great segment from a public access television show featuring Wilson and his friend Scott Apel where they are analyzing episodes of The Prisoner, the legendary TV show created by the equally legendary Patrick McGoohan. 

What else? He loved dogs. I did not write much about his dogs in Chapel Perilous, but Bob had a dog growing up in Brooklyn, and as soon as he and Arlen started their family in the late 1950s, he got dogs again. 

I remember, during a class I was taking at the Maybe Logic Academy, an interactive remote learning website that RAW and Lance Bauscher created in 2004, Bob wrote that he thought he may have had Asperger’s. I don’t think I mention that in the book because I wanted to steer clear from any sort of psychoanalyzing of him. Asperger’s is on the autism spectrum, and I fell down a small rabbit hole researching autism and artists while writing my book. I came across a book called Writers on the Spectrum by Julie Brown which makes an argument for how Hans Christian Anderson, Lewis Carroll, Emily Dickinson, and other great writers had autism and/or Asperger’s. So, Bob wondered that about himself. If you look into aspects of Asperger’s, one is an extreme attention to detail. Bob was able to use that in his writing, especially his fiction work, to create countless reasons to read the page again. But, who knows, maybe Bob was just a genius.

RU: This seems like a good place to switch over to talking about RAW’s personal life. He embraced optimism, and it was a hard-won optimism. It was not an easy life. What were some of RAW’s challenges, and how did he maintain a positive spirit?

GK: I think the most enduring quality of RAW’s optimism was that he learned as a child to use optimism as a tool for existential survival. I think Bob embodied what Viktor Frankl, the Jewish Holocaust survivor and founder of Logotherapy, called ‘tragic optimism,’ meaning that over the course of his life, Bob was very familiar with pain, guilt, and death. These qualities comprise the foundation of tragic optimism, and Bob remained cheerful in spite of such things. If one can remain optimistic about life and one’s fellow human after enduring horrible and traumatic events, one has earned a noble wisdom of the heart. I think this resonates in most of Bob’s work. 

Some examples of this are his experiences as a child in South Brooklyn with polio. Later there was his response to almost committing suicide in his 20s, his response to his daughter Luna being murdered, and other difficult events throughout his life. He practiced this optimism in his 70s when he had post-polio and  his body was slowly failing. Bob’s optimism was all about activation, engagement, and stretching. It’s quite a yogic mindset, and he arrived there through his own wonderfully meandering path.

Bob grew up in a poor neighborhood on the southernmost shores of Brooklyn during the Great Depression. That early life alone would be enough to drive some young men into a life of crime. Through his experience of being relatively cured of polio by the Sister Kenny Method, he learned that there is always hope for achieving medicinal relief, even if others say there is no hope. 

In his 20s, he nearly jumped to his death from the Brooklyn Bridge in a drunken stupor after his girlfriend dumped him through a letter. But before he jumped from the bridge, he saw a plaque dedicated to the family who built the bridge; and he saw how long it took them and the sacrifice it took for them to do so. That awakened him and he realized that if he wanted to make something of lasting value like the Brooklyn Bridge then he had to be tougher on the outside while also being kinder to himself. Through the help of psychotherapy, and through orgone therapy – the therapy based on the ideas and practices of Wilhelm Reich – Bob healed himself from some of his childhood trauma. Again, he was learning early in his life that one can transcend depressed mental states.

Many years later, as I write in my book, Bob utilized such far-out things as magick, LSD, marijuana, the works of Friedrich Nietzsche (minus his Übermensch theory), and creative visualization to not only see far-out things but also to maintain a relaxed state of homeostasis as his world became increasingly stressful. There was no shortage of reasons Bob could have picked to become and remain a miserable person. But he recognized the value in optimism, literally, as a way to stay alive.

RU: He was also a techno-optimist. How did he interact with technology or technological developments during his lifetime, either hands-on or philosophically?

GK: It’s true that RAW was a techno-optimist. Some of his prognostications made about radically extending human lifespan within decades could be seen now as overly optimistic, but he allowed himself to be a visionary, meaning that he dedicated much ink to what could be if large segments of the population become enthusiastic about ideas like living forever. When it came to communication technologies, he was optimistic that once the Global South got online and everyday people from there shared their experiences with those in the Global North, then true world governance… not to be confused with government… could be achieved. 

Wilson grew up in a house where there was no phone – only newspapers, magazines, and books for entertainment. Then his family got a radio. Soon after that, he started going to movie theaters. His engagement with communications media continued until, years later, Bob was leading a pioneering remote learning website called The Maybe Logic Academy. He saw firsthand how communication technology can bring everyday people together. He believed that humanity would keep creating better forms of communication tech that will help achieve a more just, peaceful, and equitable planet outside of the reach of governments and corporations.

When it comes to his personal uses of technology, Bob was more of an ideas-man. I came across a number of stories about his clumsy ways with modern tech. He and Arlen’s daughter Alex recounted how Bob never learned to drive a car because of his polio. The first and only time he tried to drive, he crashed the car hood-first directly into the only light pole on a vast empty stretch of road. Or there’s the story from his friend Scott Apel about a night when Bob stayed in Apel’s guest room. The next day, when Scott asked Bob how he had slept, Bob replied that he slept very well except he couldn’t figure out how to turn off the lights in the room. So instead, he figured out how to sleep with the lights on. This left Scott perplexed because he knew that it was a simple procedure to turn off the lights in his guest room.  So here was, in Scott’s estimation, the smartest man on the planet unable to figure how a light switch works. There’s another great story like this in my book, but I’ll leave that for the reader to discover.  Overall, Bob was shockingly bad with the technology that he loved so dearly.

Credit: Tesfu Assefa

RU: I’ll ask you to channel a little RAW now. I know it’s impossible, but you’ve studied his thinking closely for your book so let’s give it a try. What would RAW have to say about our present moment? What might his thoughts have been about the weird chaos of MAGA? And what about the new excitement around AI (this being an AI-oriented webzine)?  Feel free to add your own opinions.

GK: Working within the parameters that you just set, while also acknowledging that it’s absolutely impossible for anyone to know the thoughts of a dead man, I will base my answer more on extrapolations of what Bob’s did say, while further acknowledging that the world has changed drastically over the last 17 years and he could have changed too. I mean Dennis Hopper and Eldridge Cleaver both died as Republicans, so ya never know.

One thing is clear, and I illustrate this in the last chapter of my book. It’s the chapter that opens with RAW appearing at the now legendary Disinfo.com conference at Hammerstein Ballroom in 2000. At that stage of his life, Bob truly was RAW, in the best sense of the word. There are so many stories about old folks becoming more conservative in their golden years, but Bob went the opposite direction. Like I write in the book, Bob was laying it down that night. He said that the reason many countries hate America is because we are bombing them. If we stopped bombing them, they would stop hating us. In that talk, he also said that there are two tiers of justice in America, those for the rich and those for the rest of us. Both these things are, of course, true, but Bob was stating such things with a more direct fiery tone than in previous years.

When I interviewed him in 2003, he told me that in the ’60s he called himself “an atheist, an anarchist, and a witch.” Then in the ’70s, he said he “softened it” to calling himself “a libertarian, a pantheist, and a neopagan.” Later, he started calling himself “a decentralist, a pragmatist, and proponent of Maybe Logic.”

Bob stated in an interview from the early ’90s – and he may have mentioned this in Cosmic Trigger Vol. 2 – that he saw the usefulness of third parties in political systems, based on his time living in Europe in the 1980s. He was in favor of strong third and fourth and fifth parties in the American political system, beyond Democrats and Republicans. I don’t know if he voted in 1988, because was still in Ireland during the summer of that year. However, he stated in a later interview in 2001 that he let a friend convince him to vote for Bill Clinton in 1992. However, Clinton was running against George Bush, who was the former director of the CIA, so Bob was not into an “ex” CIA man becoming President of the United States.

I am unsure whether he voted for Clinton in 1996 or whether he voted for Ralph Nader, but Nader and the Green Party were the third party that Bob had once wished for in America. Nader made the decision to run outside the political duopoly because he saw them both as unable to properly address the real needs of the American public. 

By 2000, Bob was drawing voters’ attention to the donors of the political candidates, and he was calling the presidential nominees, George W. Bush and Al Gore, the “two lying bastards”. The donors, argued Bob in one of his last books TSOG: The Thing that Ate the Constitution, were the ones the POTUS is really looking out for. 

In the interview series Robert Anton Wilson Explains Everything, which was published in 2001, he said that he believed America was an Oligarchy. He also said in that interview that he saw hope for humanity with more people getting online from the Global South. Lastly, Bob was very clear on the impact of colonialization from his study of the imperialism Ireland faced from England for hundreds of years. Wilson did the historical research and saw the impact of the British Empire’s legacy of violence. 

I could see RAW being an outspoken critic of the neocolonialist system that exists, where American oil companies and the American government have colonized oil-producing countries since World War 2. RAW may have followed that logic all the way through and applied it to the current situation.

He may have supported Bernie in 2016. I think that’s actually a no-brainer. But also, he may have just said “fuck it” and stopped voting in general. This is why it is difficult guessing what he may or may not have done. 
 
As far as MAGA and Trump goes, there’s footage on YouTube of Bob’s calling Trump “fucking crazy,” so he saw what time it was with ‘the Donald’. I can’t imagine he would think too highly of MAGA.

I think that Bob would have provided information about who the major financial donors of Trump’s campaign were, and he would urge his readers to look at that, and to keep in mind his position that U.S. Presidents put the needs of their donors over the needs of their voters. I think RAW would raise more questions than provide answers. Same goes for Kamala and Biden: who are their major donors?

Lastly, when I interviewed Bob in 2003, he told me that he’d prefer it if U.S. politicians were trained in science more than in the law. So as far as the 2024 election went, there was only one Presidential candidate in the race with that qualification: Dr. Jill Stein. Stein was an actual physician before becoming involved in politics, and she is an on-the-ground activist, like Bob was. And she is in favor of a ceasefire in Gaza. I think Bob would respect her for all those reasons. Would he have voted for her and not Kamala? Who knows? Again, he’s dead and he would be pissed off to no end if we somehow contacted him on the other side just to ask him about U.S. politics. He may start haunting us just for doing so!

RU: And AI?

GK: As far as Bob and Artificial Intelligence goes, I think it’s far easier to guess what he’d think. He’d be into it. He’d be absolutely fascinated, I think. He’d probably be interested in the development of Artificial General Intelligence, and the work of Dr. Ben Goertzel, especially Goertzel’s notion of the importance of programming AI in such a way that it will value humanity. If we teach AI only how to murder people en masse, how’s that gonna play out?

He probably would be an experimenter with ChatGPT and ask it all sorts of interesting questions just to see what it says. It’s funny though: in all of Bob’s writings, I never really came across a direct reference to AI, even though his work appeals to people who are very much into the study of Artificial Intelligence. The notion of using a human-made “intelligence” that gets exponentially more intelligent, until, as Goertzel talks about, it’s AGI becoming an ASI, an Artificial Super Intelligence… I think Bob would be interested in all this through the lens of Tim Leary’s S.M.I2.L.E. scenario. What will help humans behave and act more intelligently with one another and themselves?

Wilson gave a great interview with WBAI, the listener sponsored non-commercial radio station in New York City, in the mid-1960s about the promising potential cybernetics had for decentralizing power and control while promoting greater autonomy in individuals working in conjunction with one another. In that respect, I think he’d support the Decentralized AI Society and others promoting these uses of the technology.

Lastly, even though RAW never wrote about specific AI programs, like the ELIZA AI program you mentioned in your interview with Jeremy Braddock, one can make the argument that FUCKUP, which stands for First Universal Cybernetic-Kinetic Ultra-micro-Programmer, from Illuminatus! is an AGI, and it becomes an ASI when it falls in love and merges with Leviathan.

RU: Lastly, did how you think & feel about RAW change as the result of your research? What did you learn in your deep exploration of his life that you feel will stay with you?

GK: I do not know if there was a change in my thinking about RAW from writing this book. But authoring the book was itself an extremely deep education in the humanities for me. From studying the life of a man and his world – his ideas – I could not help but be constantly confronted with the human experience. I feel like I know this person now at a level I didn’t before. However, I also feel like Bob Wilson is even more of a mystery to me than ever before. Bob, in his writing, makes it clear that knowledge-of-self is an initiation that never ends. He remained open to surprising himself and, as such, was extraordinarily complex. He reminds readers of the mysteries that lie within oneself. 

I would also say that learning about his elderly years was educational. He never had a lot of money, and I am not sure what sort of healthcare he had then, but he had a support network that was huge. Hearing about all the people who hung out with him towards the end, it truly was a Sangha, a sacred community of love and support that surrounded him as he aged. I think society as a whole can learn from that.

Hmmm. Maybe one thing that stays with me was how much he spoke out and went to protests throughout his whole life. Bob didn’t just write about everyone living in harmony. He was engaged in activist protest. He put his body on the line, which is admirable. Also, learning about his constantly moving with a whole family and with pets… and how he managed to produce constant copy while living like that. One needs an intensely strong power of concentration to do this. Also, when I think about how much acid he took and how much weed he smoked, that level of laser-like focus is remarkable. While he and his family traveled, he had to carry loads of papers, his typewriter, and his books. 

I bounced around Los Angeles for over three years like this, only at a much higher velocity, with boxes of books and files needed for Chapel Perilous. To be able to move like this and hop right into writing requires Herculean amounts of mental muscle. Bob did it though. He was disciplined in his craft. He was disciplined in general. He gave himself so many exercises and meditations to do over the years, and learning more about all that was amazing and inspiring. So I gained a deeper appreciation for his level of concentration. Also, he never became bitter or full of resentment from the harsh tragedies that crashed into his life. He walked the talk and was able to utilize magic(k), psychology, drugs, and art to remain a joyful person till the day he died. And that’s a lesson I will never forget.

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Quantum vs. Bitcoin: The New Crypto FUD?

Introduction

If you’ve been in crypto for a while, you’ll know that some fresh new FUD is always around the corner. Now that Bitcoin has finally cracked that magical $100k milestone and the USA has a crypto-friendly government incoming, could quantum computing be the new bogeyman? 

Google’s New Math

On Monday, Google unveiled Willow, a quantum processor that completes certain calculations in five minutes. The same task would take today’s fastest supercomputer longer than the universe has existed. This leap in quantum computing has Bitcoin holders and other crypto investors concerned about the encryption that secures their digital fortunes, particularly the dormant wallets holding billions in early Bitcoin.

The numbers behind Willow tell a striking story. Traditional computers process information in bits – ones and zeros. Quantum computers use qubits, which can represent multiple states simultaneously. Willow’s 105 qubits might seem modest, but they’ve achieved something remarkable: stable error correction that improves exponentially as the system scales.

For cryptographers and Bitcoin developers, this matters a lot. Quantum computers with enough stable qubits could theoretically break the encryption that protects Bitcoin wallets

Google’s Quantum AI lead, Hartmut Neven, describes Willow’s achievement in almost mystical terms, suggesting the computation “occurs in many parallel universes.” Behind this dramatic language lies a practical breakthrough: the ability to maintain quantum states long enough to perform meaningful calculations.

A Numbers Game: Your Bitcoin Is (Probably) Safe

Kevin Rose, a former Google product manager, puts it bluntly: cracking Bitcoin’s current encryption standard would require 13 million qubits. Willow has 105. That’s like trying to breach a bank vault with a butter knife.

To generate addresses, Bitcoin takes a public key, and performs a cryptographic computation called hashing on it twice. Rose’s assurances are about the difficulty of computing a full public key from the Bitcoin address.

However, once the full public key is known, computing the private key that unlocks the money is a much easier quantum computation.

This leaves one corner of the Bitcoin network under genuine quantum risk. The oldest Bitcoin addresses used a simpler security format called P2PK, which left full public keys exposed on the blockchain. 

The distinction between P2PK and modern P2PKH (Pay to Public Key Hash) addresses marks a crucial security evolution. P2PKH addresses only expose their public keys when spending coins, giving them significant protection against quantum attacks. Even if quantum computers could break the encryption, they’d need to do so in the brief window between transaction broadcast and confirmation.

Satoshi’s Time Bomb

This vulnerability creates an extraordinary situation. Roughly one million Bitcoin – worth about $102 billion at current prices – sits in these early addresses. Many believe these coins belong to Bitcoin’s pseudonymous creator Satoshi Nakamoto. They haven’t moved in over a decade.

Some developers argue for preëmptive action: modifying Bitcoin’s code to freeze these vulnerable coins before quantum computers can crack them. It’s technically possible through a network fork. But others see this as heresy, violating Bitcoin’s core promise of immutability.

The technical debate centers on implementation methods. A soft fork could make specific UTXOs unspendable while maintaining backward compatibility. A hard fork would require network-wide consensus but could implement more comprehensive protections. Both approaches face significant political and philosophical hurdles within the Bitcoin community.

The Ethereum Answer

While Bitcoin debates, Ethereum makes moves. Vitalik Buterin, Ethereum’s co-founder, has outlined a straightforward quantum defense: a hard fork requiring all users to upgrade their security. No frozen funds, no philosophical crisis – just a mandatory update when quantum computers get close enough.

Researchers of post-quantum cryptography are developing new encryption algorithms that quantum computers can’t crack. Several cryptocurrencies are already testing these methods, preparing for a quantum-secure future.

The technical approaches vary: lattice-based cryptography, hash-based signatures, and multivariate cryptography each offer potential quantum resistance. Some projects combine multiple methods, creating layered defenses against both classical and quantum attacks.

Five Minutes vs. The Universe

Google’s claim about Willow’s five-minute calculation needs context. The chip solved a specific mathematical problem perfectly suited to quantum computing. Most computing tasks – including those involved in cryptocurrency mining and transactions – won’t benefit from this quantum hardware.

The problem Willow solved involves sampling from random quantum circuits. While impressive, this task was carefully chosen to demonstrate quantum supremacy. Breaking cryptocurrency encryption requires solving entirely different mathematical problems: factoring large numbers and computing discrete logarithms.

Google’s own quantum roadmap shows Willow reaching only milestone two of six. The path to 13 million stable qubits stretches far into the future. Yet quantum development has repeatedly outpaced predictions.

Credit: Tesfu Assefa

Beyond the Public Keys

Modern cryptocurrency security involves multiple layers. Even if quantum computers eventually crack public key encryption, they’ll face other barriers. Bitcoin’s proof-of-work system, hash functions, and network consensus mechanisms don’t rely solely on the algorithms quantum computers are good at cracking.

The cryptocurrency community has so far been pretty adaptable. When SHA-1 encryption showed weaknesses, Bitcoin developers had already moved to stronger alternatives. Similar foresight guides quantum defense planning.

Hash functions, particularly SHA-256 used in Bitcoin, show strong resistance to quantum attacks. Grover’s algorithm, a quantum method for searching unstructured databases, could theoretically speed up mining by finding hash collisions faster. But even this would only offer a quadratic speedup, requiring significant modifications to Bitcoin’s mining difficulty adjustment.

Technical Defenses Emerging

Cryptocurrency developers aren’t waiting for quantum computers to catch up. Teams across the ecosystem are implementing various defensive measures. Digital signature schemes like SPHINCS+ offer quantum resistance through hash-based signatures. Unlike current elliptic curve signatures, these methods rely on the security of hash functions, which better resist quantum attacks.

Some projects explore zero-knowledge proofs and other cryptographic primitives that maintain security even against quantum adversaries. These techniques could protect not just funds, but also transaction metadata and smart contract interactions.

Adapting the Future

Here’s the reality: quantum computing poses no immediate threat to cryptocurrency. But its steady advance demands attention. The solutions already exist in theory: they are post-quantum cryptography, network upgrades, and possibly even blockchain forks. The challenge lies in implementing them without disrupting the trillion-dollar cryptocurrency ecosystem.

The next decade will transform both quantum computing and cryptocurrency. Willow’s 105 qubits will seem quaint compared to future processors. Bitcoin’s security will evolve to match these advances. The real question isn’t whether cryptocurrency can survive quantum computing – it’s how effectively the technology will adapt.

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