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? The Dinarian on Locals brings you the latest in news, interviews, in-depth conversations, and stories from across the blockchain and global communities—within and beyond cryptocurrency ?. Experts delve into how blockchain technology is reshaping industries, enhancing business networks ?, transforming transaction workflows, and advancing distributed ledger systems ??. We also explore intriguing topics that may venture into the realm of conspiracies—and so much more!
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September 20, 2024
Distributed Rebellion: A thesis on crypto x AI from Delphi Labs 📝

AI represents arguably the biggest technological revolution in history, and has kickstarted a technological arms race the likes of which the world has never seen before. Current AI models are already scoring in the top decile on most standardized college tests and outperforming humans at many tasks including AI research itself. Even at its current level, this is already transformative to many industries such as search, customer service, content creation, programming, education, and more.

We expect AI capabilities, funding, and its effect on society to only accelerate from here. All the big tech giants understand AI is existential to their businesses and are investing accordingly. NVIDIA revenue, arguably the best proxy for AI CapEx, is on track for over $100b in 2024, more than double that of 2023, >4x that of the year prior.
Google CEO Sundar Pichai on AI investments:
“The risk of underinvesting is dramatically greater than the risk of overinvesting for us here."

At the same time, startups sense AI is a disruptive force with which they can unseat multi-decade incumbents and an estimated $83b has been invested into AI startups over the last 18 months.

Given that AI capabilities have tended to scale exponentially with the compute applied to them, it’s very likely we will reach something like AGI within the decade.

In this piece, we argue that competitive dynamics will result in a world of millions of models, and crypto is the ideal substrate for this many-model world. We’ll start by discussing why we think a many-models world is the logical end-game for AI. We then go over the unique differentiators crypto provides to AI. Finally, we cover the crypto x AI stack as we see it, and provide specific examples of the kinds of projects we’re excited about.
There are strong philosophical and moral reasons why open-source AI and crypto x AI is a better state of affairs for humanity, and these are excellently covered elsewhere. While we agree with them entirely and this is part of what motivates us to build in this space, for the purposes of this piece will focus purely on the practical reasons why crypto x AI will win, rather than the moral arguments for why it should win.

○ God-model vs many-models

Right now, we’re tracking towards a world where a few, large vertically-integrated tech companies produce “God-models” that dominate everything else.

However, we don’t think think this is the end-game for a few reasons:

Rug risk: Organisations, entrepreneurs and developers building experiences on top of AI don’t want to be dependent on a single closed-source company which can change the model, alter the terms of use, or even stop serving them entirely.

Cost-performance-tradeoff: The extremely large, generalised models favoured by the big tech companies are necessarily much more expensive, both to train and to run. As a result, this renders them overpriced and overpowered for many use cases. While this isn’t as big a consideration right now as people aren’t thinking about profitability, as AI reaches scale people will optimise to get the lowest cost possible for the level of performance they’re looking for. For many tasks, large models will not be competitive here. There is extensive research to support this, showing much smaller, specialised models can outperform the generalised models at everything from medical imaging diagnoses, fraud detection, speech recognition and much more.

Vertical integration: As Apple has repeatedly demonstrated, the best products often result from vertical integration across the entire stack. Ambitious entrepreneurs building AI-enabled products will seek to gain a competitive advantage by building on top of their own specialised models.

These products will also be able to capture more value, attracting more investment, etc.
Privacy concerns: AI will be at the core of organisational workflows in a way that arguably no other technology has been. Many organisations are reluctant to entrust their sensitive data to these models.

For these reasons, we believe we’re much more likely to end up in a world with many smaller, specalised models that are tailored and cost-effective for particular use cases. Application developers and users will leverage open source models such as LLaMA or those from @MistralAI as a base from which to fine-tune their own dedicated models, often using proprietary data. Many models will continue to run on servers, but smaller, more privacy-sensitive applications will run locally on client devices, while others who require censorship-resistance might use decentralised compute networks.

This is a world of modular AI legos, where devs and entrepreneurs compete to provide value to users, and users are able to pick, choose and combine different services to suit their particular needs. Routing, orchestration, synthesis, payments, and all sorts of other infrastructure will need to be built to unbundle the “God-model” stack and serve this emergent AI economy.

This also happens to be the world where crypto thrives.

○ Crypto x AI

Crypto intuitively feels like an area which can find utility in this many-models world. However this hype has led to significant capital allocation in the space from often under-informed investors. Much like the infra bubble before it, many projects are being funded and built which perhaps should not be. As such it’s not easy to determine which subsectors in the crypto x AI space genuinely have merit, leading many to dismiss the whole space as a meme without fundamental value.

We don’t think it’s a meme, but it’s true that this many-models world could theoretically ex$ist without crypto. Therefore, it was important for us to focus on the unique ƞ of crypto that allow us to create radically better products or, ideally, ones that couldn’t be built without it. In order to do this, we start by identifying the unique properties of crypto and how they could apply to AI in a way that results in better products. We’ll then go over the crypto x AI stack and provide examples of use cases that we think fit this.

Trustlessness: Crypto rails tend to be trustless, which means you can have cryptographic assurances that they don’t change, access cannot be unexpectedly withdrawn and you can verify that execution is as expected. This is important for the modular AI stack because, unlike with an integrated approach, builders will need to compose with a bunch of primitives they don’t control and users will need to inherently trust a number of services, many of which they don’t even know about.

Censorship-resistance: If deployed as immutable contracts, applications running on crypto rails are unstoppable. Even if upgradeable, it’s often by a DAO which requires a quorum of tokenholders to reach consensus. Assuming AI becomes as powerful as we expect, it’s highly likely governments will seek to control and influence it. In fact, we’re already seeing this happen. Just as Bitcoin and crypto provide money/financial rails that sit outside the system, crypto x AI provides unstoppable intelligence.

○ The crypto x AI stack

Given these benefits, what applications do we think are particularly interesting at the intersection of crypto x AI?

Data Centers and Compute

The utility of compute for models broadly falls into two categories: training and inference. We see merit in using decentralised compute for both of these and we’ll expand on each below.

Training on Decentralised Compute

Distributed compute is currently difficult due to the heavy communication and latency requirements between nodes during training. There are many teams trying to solve this problem and, given the size of the prize and the quality of talent working on it, we’re confident it will probably be solved. A few promising approaches here include @NousResearch’s DisTrO and @PrimeIntellect’s OpenDiLoCo.

In addition to solving the hard technical problems of distributed training and building a product that abstracts away this complexity, winners will also have to figure out:

1. How to ensure quality and accountability on a permissionless network

2. How to bootstrap a supply-side, ideally of data centers and clusters rather than consumer hardware

Token incentives will probably be table stakes for incentivising a supply-side, and more creative approaches may include giving compute providers ownership in the resulting model.

Fundamentally, the advantages of a distributed compute marketplace are that you can tap into the lowest marginal cost of compute around the world. This becomes increasingly important as rising costs from incumbent service providers causes more companies/orgs to push back and seek out cheaper alternatives. The disadvantages are latency, heterogeneous hardware as well as lack of all the optimisations and economies of scale that come from building and operating your own data centers. It remains to be seen how this plays out.

○ Verifiable Inference

Broadly, we see the use case for verifiable inference as extending trust-minimised systems with AI capabilities. It’s not practical to embed a model into a smart contract, but it is possible to run the model off-chain and post some attestation or proof that it ran as expected on-chain. For instance, projects could trustlessly offload governance decisions (e.g. decisions regarding risk parameters in a money-market) to an off-chain model.

This concept could also be used for open or closed-source models more generally, giving users assurances that the output came from the model they expected. This may become important as applications and users leverage AI for increasingly mission-critical tasks. There are many projects tackling this in various ways such as Delphi Ventures portco Inference Labs (@inference_labs).

○ Data

Training LLMs today is a multi-step process requiring various kinds of data and human intervention. It starts with pre-training, where LLMs train on cleaned, curated versions of the common crawl and other freely available data sets. During post-training, the models are trained on smaller, more specific, labeled datasets to make them proficient in specific areas (e.g. Chemistry), often with the help of experts.

In order to ensure fresh and/or proprietary data, AI labs often secure deals with owners of large data sources. For example OpenAI and Reddit signed a deal worth a rumoured $60m. Similarly, the Wall Street Journal reported that News Corp's deal with OpenAI was valued at more than $250 million over five years. It’s clear that data is more valuable than ever.

We believe that crypto networks are well placed to help teams source the data and resources required by every stage of this process. Perhaps the most interesting sector is data collection, where we believe crypto incentives are well placed to bootstrap the supply side of data collection and unlock much of the significant long tail of data sources.

For example, Grass AI (@getgrass_io) incentivises users to share their idle internet bandwidth to help scrape the web for data which is then structured, cleaned and made accessible for AI training. If Grass can bootstrap enough of a supply-side, it can effectively act as an API key providing fresh internet data for use in models.

@Hivemapper is another good example - the network was launched in November 2022 and collects millions of kilometers of road-level imagery every week, having already mapped 25% of the world. It’s easy to see how similar models could be applied to other forms of multi-modal data and monetised by selling to AI labs.

As the NewsCorp/Reddit deals show, there are many companies who own valuable data but many are either too small or lack the connections to AI labs to monetise it. Similarly, AI labs making deals with individual small providers may not be worth the effort. A well-designed data marketplace could mitigate this by connecting providers to AI labs in a somewhat uniform manner. There are a few challenges here, the primary ones being solving for quality of data, as well as fungibility of both APIs and data.

Finally, data preparation is a significant set of tasks involving labeling, cleaning, enrichment, transformations and so on. A small team may not have all these skills in-house and look to outsource. Scale AI (@scale_AI) is a centralised company offering these services - currently estimated to have revenue of around $700m and growing fast. We believe a well designed marketplace and workflow system based on crypto rails can do well here. Lightworks is one that Delphi Ventures invested in and there are a few others - all at quite an early stage.

○ Model

To paraphrase Delphi Digital’s report, The Tower & The Square, the production and control of AI models are tracking to be almost entirely controlled by “the tower” - big tech and governments.

This is arguably an even more dystopian state of affairs than government-controlled money. As it allows them to not only control the most important economic resource, but also control the narrative by censoring and manipulating information, cutting certain “undesirable” people off from the system entirely, using people’s private AI interactions against them, or simply using AI to maximize ad revenue.

There are many smart people working to create “the square” - a decentralised network with the goal of producing a fully neutral, censorship-resistant model accessible to all. So just as Bitcoin and crypto provide money/financial rails that sit outside the system, crypto x AI would provide intelligence that sits outside the system.

Such projects aim to create a god model that rivals GPT and LLaMA by decentralising every part of the model creation process - the network sources and prepares data, trains on its own decentralised compute, runs inference on that same compute, and coordinates the whole process through decentralised governance. No part of the process is centralised and thus the model is truly community-owned and uncontrollable by the “Tower”.

Obviously creating a decentralised model that comes anywhere close to rivaling frontier models is going to be extremely difficult. We can’t expect that a large percentage of users will tolerate a worse product for moral reasons. We consider this class of projects to be "moonshots", unlikely to succeed by definition but if they do, would be incredibly valuable - and we sincerely hope they do.
It’s also worth mentioning centralised AI labs, which embrace crypto ideals and are likely to have a token or leverage crypto rails in some other way. @NousResearch, @PondGNN and @PondGNN are some examples that Delphi Ventures has invested in.

Lastly model creation infrastructure such as Bittensor by @opentensor falls under this model part of the stack. Bittensor has been discussed thoroughly elsewhere however so we won’t get into the pros and cons of it here.

Continued:

https://x.com/delphi_labs/status/1834247706103160939?s=09

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đŸ€”ON FOX NEWS? One Has To Wonder... WHY NOW?đŸ€”

ARE WE ALONE? Tonight on @SpecialReport a look at a new documentary on UAP's and what government officials may know about top secret programs.

00:07:02
🚹 The convergence of crypto and traditional finance is accelerating the Internet of Value 🚹

Institutional payments. Secure asset custody. Regulated stablecoins. Everything onchain.

It's happening: the convergence of crypto and traditional finance is accelerating the Internet of Value.

That’s a wrap for Ripple Swell 2025. We’ll see you next year, NYC! đŸ—œ

00:01:41
đŸ‡ș🇾 Jerome Powell said banks are free to provide Bitcoin and crypto services

TRILLIONS incoming 🚀

00:00:24
👉 Coinbase just launched an AI agent for Crypto Trading

Custom AI assistants that print money in your sleep? 🔜

The future of Crypto x AI is about to go crazy.

👉 Here’s what you need to know:

💠 'Based Agent' enables creation of custom AI agents
💠 Users set up personalized agents in < 3 minutes
💠 Equipped w/ crypto wallet and on-chain functions
💠 Capable of completing trades, swaps, and staking
💠 Integrates with Coinbase’s SDK, OpenAI, & Replit

👉 What this means for the future of Crypto:

1. Open Access: Democratized access to advanced trading
2. Automated Txns: Complex trades + streamlined on-chain activity
3. AI Dominance: Est ~80% of crypto 👉txns done by AI agents by 2025

🚹 I personally wouldn't bet against Brian Armstrong and Jesse Pollak.

👉 Coinbase just launched an AI agent for Crypto Trading

🚹 CANARY LIKELY TO PAUSE ETF FILINGS, EYES SEC SHIFT FOR WHAT'S NEXT 🚹

Canary Capital CEO Steven McClurg has indicated that the firm may pause its ETF filings for other altcoins like Litecoin and Hedera following the successful launch of its spot XRP ETF (XRPC). The decision comes as the company assesses market conditions and awaits potential regulatory shifts under the Trump administration.

🔑 Key Points

  • Pause on Altcoin ETFs: Canary Capital is likely to pause further ETF filings for altcoins like Litecoin (LTC) and Hedera (HBAR) after launching its XRP ETF. CEO Steven McClurg stated the firm wants to see how XRP performs before proceeding with other filings.

  • Market Strategy: The company prefers to focus on quality over quantity, taking a measured approach to ensure each ETF launch has sufficient liquidity and market demand. This strategy reflects lessons learned from the rapid proliferation of Bitcoin and Ethereum ETFs.

  • Regulatory Outlook: Canary is also watching ...

🚹 BNY MELLON LAUNCHES MONEY MARKET FUND DESIGNED FOR STABLECOIN RESERVES 🚹

BNY Mellon has launched a new money market fund specifically designed to serve as reserves for stablecoins. This move represents a significant step toward integrating traditional financial infrastructure with the rapidly growing cryptocurrency ecosystem, particularly within the stablecoin sector.

🔑 Key Points

  • Institutional-Grade Solution: BNY Mellon, the world's largest custody bank with $50 trillion in assets under custody, has created a money market fund tailored specifically for stablecoin issuers seeking to back their tokens with high-quality, liquid assets.

  • Regulatory Compliance: The fund is structured to meet the stringent regulatory requirements that stablecoin issuers face, particularly around reserve transparency and asset quality.

  • Market Infrastructure: This offering provides stablecoin issuers with access to traditional financial markets while maintaining the liquidity and ...

🚹 SBI & DIGIFT CREATE JOINT VENTURE TO LINK JAPANESE RWA TOKENIZED ASSETS GLOBALLY 🚹

SBI Digital Asset Holdings has partnered with DIGIFT to create a joint venture called "SBI/DIGIFT Joint Venture" that aims to connect Japanese tokenized real-world assets (RWAs) with global markets. This partnership leverages SBI's extensive network in Japan and DIGIFT's expertise in tokenization to facilitate cross-border investment opportunities.

🔑 Key Points

  • Joint Venture Details: SBI Digital Asset Holdings and DIGIFT have formed a joint venture to link Japanese tokenized RWAs with global investors. The partnership will focus on tokenizing Japanese assets such as real estate, infrastructure, and corporate debt.

  • Global Connectivity: The joint venture aims to create a bridge between Japanese RWAs and international markets, enabling foreign investors to access Japanese assets through tokenization. This will enhance liquidity and broaden the investor base for Japanese assets.

  • ...

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3I/ATLAS — Secret Laws Of Gravity
Unlocking the future of space travel through the precise calculation of time and orbital trajectories.

"My preliminary analysis suggests two principal hypotheses regarding the reported phenomenon known as '3I/Atlas':

  1. A Coordinated Psychological Operation (PsyOp): The phenomenon may constitute a calculated effort to manipulate public sentiment or induce fear, potentially preceding a planned, large-scale deception (referred to informally as 'Project Bluebeam').

  2. A Highly Anomalous Object: Alternatively, the phenomenon represents an authentic, significant anomaly warranting serious scientific or intelligence scrutiny.

Regardless of its origin, '3I/Atlas' represents an historically noteworthy development that necessitates close, informed observation."

 

~Crypto Michael | The Dinarian 🙏

Abstract Introduction:

New data is now showing something that arrived early and its changing colors as we previously predicted.

In orbital mechanics where trajectories are calculated centuries in advance with accurate precision measured in seconds.

A 11-minute deviation is not a rounding error.

It’s not a typo in the database.

It’s not close enough.

"It’s Physically impossible.”

Now The longest government shutdown in U.S. history still blocking NASA releases while the object executed its closest Fly-by approaches to Mars, The Sun and Venus at the moment of maximum observational blackout.

But orbital mechanics don’t care about “government shutdowns.”

Our observations Don’t Stop.

And the math doesn’t wait for “Press releases.”

The math says this:

“If 3I/ATLAS is natural, it should have lost about 5.5 billion tons of mass.”

It didn't.

1. The 5.5 Billion Ton Problem:

Let’s start with what everyone agrees on: 3I/ATLAS “now” arrived earlier than pure gravitational predictions would allow. Even though we have been mentioning this trajectory change over 2 Weeks ago (October 21st Article HERE) TRACKING 3I/ATLAS .

The scientific consensus explanation? “Natural outgassing” the "rocket effect." As water ice sublimates near the Sun, it creates thrust, like a slow-motion rocket engine powered by evaporating ice. Comets do this all the time. It’s normal. It’s natural. It’s explainable.

Except for ONE problem.

“The Physics Don’t Add Up!”

To generate enough thrust to arrive approximately “11 minutes early” would require shedding a staggering amount of mass.

Our calculations show “over 5.5 billion tons” of gas ejected over the perihelion passage.

Think about that for a moment.

That’s not a little puff of vapor.

That’s not some gas leaking from surface cracks.

That’s 15% of the object’s total estimated mass.

If 3I/ATLAS lost that much material naturally, it would create a debris cloud larger than Jupiter’s magnetosphere—visible to amateur telescopes from Earth. Absolutely impossible to miss in professional observations, and bright enough to be catalogued by every sky survey on the planet.

1.1 ~ The Plume Paradox:

Here’s where it gets interesting:

No such cloud has yet to be observed.

Not by Hubble. Not by JWST. Not by ground-based observatories. Not by the Mars orbiters that watched it pass at 30 million kilometers.

The brightness remained within “expected limits.” The coma showed stable & geometric shifting features. The tail structure now disappeared (but that’s another story). The main one is that: “The debris cloud that should exist — simply doesn’t.”

This isn't a minor discrepancy.

This is complete, mathematical failure of the natural comet hypothesis.

Part 2: The Industrial Signature:

So if natural sublimation didn't create the thrust, what did?

The answer is hidden in the chemistry—specifically, in what shouldn’t be there. “The Nickel Anomaly.” When multiple astronomers analyzed 3I/ATLAS’s spectral signature, they found something extraordinary: “nickel vapor” (Ni) at extreme distances from the Sun, where temperatures should be far too cold for metals to vaporize naturally.

Nickel doesn't just evaporate on its own at those temperatures.

It needs HELP.

And there’s only one known process—natural or industrial—that produces a volatile nickel-carbon compound at cold temperatures which we have said several times previously;

Nickel Tetracarbonyl: Ni(CO)₄

This is not a natural cosmic process.

This is an “industrial chemical pathway” used on EARTH for metal refinement!!!

It forms at 120°C and decomposes at 180°C allowing nickel to vaporize at temperatures where water ice would remain frozen solid.

It is LITERALLY, an industrial refrigerant for metal processing.

The presence of Ni(CO)₄ in the plume tells us two things:

  • The core is not ice — It’s a nickel-rich, engineered structure.
  • The process is not passive sublimation — it’s an active, controlled system.

The nickel vapor isn’t contamination.

It’s not a coincidence.

It’s Exhaust.

3. Secret Gravity (SOEG) Model:

This is where our research team proposes something NEW.

We call it The “Self-Optimizing Ejection Guidance (SOEG) Model”

A Brand New Scientifically defensible framework that explains the acceleration not as chaotic outgassing, but as “controlled propulsion.”

The SOEG Model (Project EE / 3IE)

The System:
‱ Volatile Reservoir — CO₂ ice + Nickel-rich metallic core.
‱ Solar Heating — Perihelion triggers sublimation at optimal moment.
‱ Magnetic Ionization — Internal magnetic field ionizes nickel vapor into plasma.
‱ Anisotropic Jets — Plasma channeled through focused nozzles. (not random cracks)
‱ Thrust Optimization — Maximum momentum transfer with minimal mass loss.

Unlike natural cometary outgassing—which is chaotic, omnidirectional, and wildly inefficient. The SOEG Model Fully Represents: (CONTROLLED, DIRECTIONAL, OPTIMIZED PROPULSION.)

It’s the engineering solution to interstellar navigation: Using a “magnetofluidic drive” that uses the Sun’s + Nearby Planets & Star energy to activate a propulsion system that was BUILT.

The secret is in the magnetic field. By ionizing the nickel-carbon vapor into a high-velocity plasma jet, the system achieves thrust efficiencies that natural sublimation could never match.

This isn’t science fiction. This is “magnetohydrodynamics” the same physics that powers experimental plasma thrusters being developed by NASA and ESA for deep-space missions.

The difference?

We’re building prototypes


Someone else already perfected it.

4. The Scientific Statistical Test:

Here’s what makes it undeniable.

Natural comets exhibit HIGH temporal variance in their acceleration parameters.

Technical terms like (A₁) and (A₂) that describe how thrust changes over time. Natural outgassing is messy, chaotic & unpredictable.

Our Prediction:

We formally predict that when sufficient post-perihelion data is published — expected from JUICE observations (data release February 2026) and ground-based telescopes through December 2025— 3I/ATLAS WILL show:

  • (A₂ parameter near zero) — phase-locked rotational coherence.
  • Temporal drift < 0.5σ — stability far beyond natural variance.
  • “Thrust vector alignment” with rotational axis — body-fixed engine signature.

If ALL 3 conditions are met.

The probability that 3I/ATLAS is a natural comet drops below 0.01% (a >4σ statistical rejection).

This is not speculation. This is a time-stamped, falsifiable prediction.

By February — March 2026, we will either be proven right or wrong.

The data doesn’t care about our theories. It only cares about what actually happens.

5. The Blue Hue đŸ””:

Now there’s one more piece of evidence—and it’s visible to the naked eye (well, through a telescope). “The Color Anomaly.”

Natural comets scatter sunlight off dust particles, producing a yellowish-red glow. At 1.36 AU from the Sun, 3I/ATLAS should have appeared reddish-orange from thermal emission.

Instead, observers noted something strange: “A distinct blue fluorescence” in the coma.

What Blue Light Means?

Blue emission in a comet’s coma comes from highly ionized species—primarily “CO” (carbon monoxide ions) and certain excited metallic vapors. This requires enormous, “FOCUSED” energy to achieve.

You don’t get this level of ionization from passive solar heating. You get it from ~ Active Plasma Generation. The blue hue is the visible proof of the SOEG engine operating at perihelion. It’s the "engine glow" of a magnetofluidic drive generating high-energy plasma to achieve maximum thrust efficiency.

Compare:
- Natural comets (Hale-Bopp, NEOWISE, 67P, Etc.): Usual Yellowish-red dust scattering.
- Expected for 3I/ATLAS at 1.36 AU: Reddish-orange thermal glow.
- Observed in 3I/ATLAS: Distinct “Blue” plasma fluorescence.

This isn't subtle.

This is the difference between reflected sunlight and an active thruster firing.

5.5 ~ Convergence of Evidence:

Let's put it all together.

The Self-Optimizing Ejection Guidance (SOEG) Model is not speculation. It’s not wild theorizing. It’s one of the only frameworks that coherently explains:

✅ The early arrival— non-gravitational acceleration without natural explanation.

✅ The missing 5.5-billion-ton debris cloud — controlled thrust with minimal mass loss.

✅ The Ni(CO)₄ industrial signature — engineered propulsion chemistry.

✅ The blue plasma glow — active ionization system visible during perihelion.

✅ The statistical impossibility — phase-locked stability beyond natural variance. (pending verification)

However each piece of evidence, standing alone, is anomalous but potentially explainable.

Together, they form an interlocking pattern that demands a technological origin.

But then there’s the Silence.

Venus conjunction: Still offline.

This is not incompetence.

This is recognition.

THEY know something we’re still calculating.

December 19, 2025: 3I/ATLAS reaches closest approach to Earth at 167 million miles.

“If the calculations are correct, the 5.5-billion-ton debris cloud should be impossible to miss. Every telescope on the planet will be watching.”

All of this new information scheduled to be released should definitely include the following: High-resolution spectroscopy, morphological analysis, particle environment data and MOST CRITICALLY the astrometric parameters that will confirm or refute our SOEG model’s predictions.

“If the A₂ parameter shows phase-locked stability, the SOEG model is confirmed.”

Conclusion:

The Numbers Don’t Lie. The orbital path was not set by gravity alone. The acceleration was not powered by ice. The chemistry was not natural. And the timing is not “coincidental.”

3I/ATLAS is a message written in orbital mechanics, plasma physics, and industrial chemistry—a message we have “74 days” left to fully decode.

The mathematics are clear.

The predictions are calculated.

We don't have to speculate about what it is.

“We just have to (wait) for the complete data packet to arrive.”

And when it does, one of two things will happen:

Either the natural hypothesis survives (unlikely, given the evidence). Or we confirm what the numbers have been screaming to us since October are TRUE.

“Something pushed it. Something controlled it. Something arrived exactly when it needed to.”

Or The A-parameters will lock.

The plasma signature will confirm.

The debris cloud will be absent.

And the institutional silence will make perfect sense.

Because you don’t announce a discovery like this through a press release.

You announce it through a “Calculated Strategy.”

Analogy Conclusion:

The orbital path was set by laws that were not known,
For where the starlight failed, a force was subtly sown.

No dust and ice, but Nickel in the plume’s blue gleam,
A pulse of hidden power, of controlled, forgotten dreams.

The A-Parameter locks, The true secret of the sphere,
The Simultaneous Truth arrives, When all the numbers are near.

— Earth Exists

Additional Reference & Data Source Links đŸ–‡ïž:

EARTH EXISTS Documentation:
- [Previous article. 35 Days of Silence — 3I/ATLAS]

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BlackRock Is Manipulating The Price Of Bitcoin👀

Blackrock possess a strategic depth that goes far beyond initial appearances. When the general market perceives selling and traders respond with emotion, these major players are often operating on a much more profound level. They adeptly identify and leverage every available mechanism to influence market dynamics. Their power isn't in direct control of the asset, but in understanding how to move the market without ever taking direct ownership.

What entity has become the most prominent corporate champion of Bitcoin ($BTC)?

It's the one with the massive treasury holdings, known as Microstrategy.

 

However, the major strategic challenge lies here: the size of their Bitcoin position is fundamentally linked to their external financing, typically in the form of debt.

This reliance on significant debt creates an inherent vulnerability—a dependence on creditors and shareholders. When an entity's position is highly leveraged, that dependence makes them susceptible to market manipulation or strategic pressure from external financial forces.

When a highly leveraged corporate holder of a significant asset (like $BTC) faces external financial stress, that pressure inevitably transfers to the asset itself.

Blackrock's goal isn't to induce a market crash, but rather to establish a dominant position and control.

Any substantial sale of major cryptocurrencies like $BTC or $ETH initiated by Blackrock, can be interpreted not as routine trading, but as a deliberate effort to manipulate market sentiment and pricing.

Blackrock is deploying a sophisticated combination of tactics: they simultaneously generate market volatility through strategic sales of the asset ($BTC) while accumulating shares in key corporate holders (the stock symbolized by $MSTR).

The deeper intent is to leverage this equity stake to direct the corporate strategy of the highly leveraged Bitcoin champion.

With a sufficiently large ownership percentage, this influence becomes highly effective. The resulting market power is therefore a function of both manipulating price movement and controlling corporate policy.

Is Microstrategy (the company represented by the $MSTR stock) vulnerable to this kind of pressure? The evidence suggests yes.

A substantial stake held by Blackrock grants them effective leverage to influence and manipulate the company itself.

When the company's shares experience a significant decline, the leadership is often compelled to take action, potentially buying back their own stock. This action is driven by the fact that falling share prices directly intensify financial and market pressure on the entire organization.

If the stock of Microstrategy continues a sustained decline, lenders will inevitably begin to re-evaluate and revise the terms of existing loans. This is a critical point of failure for the entire strategy.

The fundamental operational model of this corporate champion works like a closed loop:

  • It secures debt financing (taking loans) to acquire $BTC.

  • Alternatively, it issues new equity (selling shares) to acquire $BTC.

Crucially, the ongoing interest payments on this substantial debt are often managed by the mechanism of issuing even more shares, creating a continuous cycle of dilution and reliance on a high stock price.

A major consequence of rising leverage is the escalating cost of borrowing, requiring Microstrategy to source even larger amounts of capital.

The most straightforward solution—to issue and sell more stock—proved to be insufficient.

In fact, the situation worsened: the company’s recent attempt to raise funds through a stock offering did not fully sell out. This failure directly resulted in a significant liquidity shortfall, hamstringing Microstrategy’s ability to meet its financial obligations and continue its asset acquisition strategy.

And the ultimate shock came when Microstrategy—the very entity that vowed it would never liquidate its holdings—began to sell.

These weren't insignificant trades; the sales were valued at billions of dollars.

The key question now becomes: Does this sudden, massive reversal signal the imminent collapse of Microstrategy, or is it simply a necessary, albeit drastic, maneuver of 'business as usual' under extreme duress?

There appear to be two primary strategic objectives behind Blackrock's calculated moves:

  • Scenario A (Direct Dominance): Blackrock aims to neutralize its most prominent competitor (the corporate Bitcoin accumulator) in order to seize the title as the largest holder of $BTC.

  • Scenario B (Indirect Control): The institution’s goal is to establish absolute market control and influence, preferring to leverage Microstrategy to execute the most aggressive or politically difficult actions.

The outright financial destruction of Microstrategy is highly improbable. Such an action would trigger a severe market crash that could take years to fully repair.

The far more intelligent strategy is integration and control.

Under this model, Microstrategy remains operational, while Blackrock secretly dictates strategy. This allows Microstrategy to absorb the market blame for any necessary but controversial manipulation, a classic and often dirty tactic used by high-powered financial entities.

In the immediate future, the market will continue to exhibit strong reactions to the strategic maneuvers of Blackrock.

When they execute sales, it instantly captures headlines, is aggressively amplified by the media, and causes fearful retail traders ('weak hands') to panic and exit their positions.

Every decrease in price that results from this panic directly translates into a superior entry point for Blackrock. This clearly illustrates that the current market environment is driven purely by emotion, making it a survival game reserved only for those with the strongest resolve.

In the long run, the nature of $BTC will likely shift, moving away from its original ideals of being completely free and decentralized.

The vast majority of the available supply is projected to become highly concentrated within a small number of major corporations and investment funds.

Consequently, the price cycles will no longer be reliably tied to events like halvings or popular narratives. Instead, they will be driven primarily by government and central bank policy decisions, overarching macroeconomic conditions, and the internal political maneuverings of the world's most dominant funds and corporations.

Blackrock's goal is not to eliminate $BTC; instead, they are focused on constructing an elaborate system of control around the asset.

Microstrategy (the stock symbolized by $MSTR) remains a powerful tool, but it now operates under terms and directives that the company's leadership no longer fully dictates.

Since direct command over the decentralized asset is impossible, control is established through strategic influence over the largest corporate and fund custodians. Moving forward, Blackrock will be the primary entity determining the market's trajectory.

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A Request for NASA to Release Scientific Data on 3I/ATLAS

During my recent podcast interview with Joe Rogan (accessible here), I had mentioned the unfortunate circumstances, under which NASA had not released for four weeks the images collected by the HiRISE camera onboard the Mars Reconnaissance Orbiter. These images were taken on October 2–3, 2025, when the interstellar object 3I/ATLAS passed within 30 million kilometers from Mars. The images are extremely valuable scientifically because they possess a spatial resolution of 30 kilometers per pixel, about 3 times better than the spatial resolution achieved in the best publicly available image from the Hubble Space Telescope, taken on July 21, 2025 (accessible here and analyzed here). Whereas the Hubble image was taken from an edge-on perspective since Earth and the Sun were separated by only ~10 degrees relative to distant 3I/ATLAS, the HiRISE image offers a sideways perspective, valuable in decoding the mass loss geometry and glow around as it approached the Sun.

The delay in the data release was argued to be the result of the government shutdown on October 1, 2025. Nevertheless, conspiracy theorists suggested that it may have to do with evidence for extraterrestrial intelligence in the HiRISE images. When asked about it, I suggested that the delay is probably not a sign of extraterrestrial intelligence but rather of terrestrial stupidity. We should not hold science hostage to the shutdown politics of the day. The scientific community would have greatly benefited from the dissemination of this time-sensitive data as astronomers plan follow-up observations in the coming months.

Joe Rogan suggested that I contact the interim NASA administrator, Sean Duffy. The following day, I corresponded with congresswoman Anna Paulina Luna regarding a related formal request from NASA. Following our exchange, Representative Luna wrote a brilliant letter to NASA’s acting administrator Duffy.

We all owe a debt of deep gratitude for the visionary support displayed by Representative Luna to frontier science through her letter, attached below.

Avi Loeb is the head of the Galileo Project, founding director of Harvard University’s — Black Hole Initiative, director of the Institute for Theory and Computation at the Harvard-Smithsonian Center for Astrophysics, and the former chair of the astronomy department at Harvard University (2011–2020). He is a former member of the President’s Council of Advisors on Science and Technology and a former chair of the Board on Physics and Astronomy of the National Academies. He is the bestselling author of “Extraterrestrial: The First Sign of Intelligent Life Beyond Earth” and a co-author of the textbook “Life in the Cosmos”, both published in 2021. The paperback edition of his new book, titled “Interstellar”, was published in August 2024.

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