🇯🇵 Japan

SPECIAL EFFECT

  🌏  🔎🎥 🎪💦👥🎬 🌍
          
 (00min : 15sec)
           
in a 4DX #MOVIE THEATER

in Japan.

#technology #news

🇺🇸 USA

🇩🇪 Germany
🇪🇺 EU

GERMANY BANNED
'CITIZEN VIGILANTE'

          🌏     🔎🔇🎬🔕      🌍
            (01h : 28min : 46sec)

.. so Elon posted
the entire #movie ...
- English language

#hardToSwallowPill

🇺🇳 UN

OF ALL THE THINGS THE U.N. LISTS AS HUMAN RIGHTS, WATER IS NOT ON THEIR LIST.

      🌍   🔎💦💾💦ℹ️   🌎

         (02min : 53sec)

If nefariousness wanted to force sovereign men and women into a digital cage. They would consume and control the water, hence behavior of the world. (Data centers.) #freedom? #technology

🇦🇷 Argentina
🇺🇸 USA

PETER THIEL HAS RELOCATED TO ARGENTINA DUE TO CONCERNS OVER THE DIRECTION OF THE UNITED STATES FUTURE AND IS ALREADY HOSTING DINNERS WITH LOCAL ECONOMISTS ABOUT THE ANTICHRIST.
       🌍      🔎👤🗺      🌎
         (05min : 00sec)
Thiel will live in Buenos Aires’ most exclusive neighborhoods where he could be offered permanent residence or even citizenship. Thiel may view Argentina as a testing ground for "Dark enlightenment" which says societies should be governed by corporations.

Burning Man is sold as an escape from the system. But look closer: initiation rituals, loss of identity, mind-control symbolism, transhumanism, Silicon Valley and the symbolic burning of Man himself. The people building the digital future are partying in the desert with those who think they’ve escaped it. Stop being fooled.

CREDIT: DMITRI REVOLT

Former 33rd Degree Mason Reveals the Darkest Secrets of Freemasonry
https://www.youtube.com/watch?v=IkR3iANDA78

PLANT FOR CHANGE—GLOBAL SEED SUPPLIERS LIST’ of Organic, Heirloom, Landrace, Open Pollinated, Non-GMO Seed Companies.

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SINGAPORE
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Query:

what's our progress on LLM fallacy recovery since last year and what's our forecast for next year?

Google:

Progress in LLM logical fallacy recovery has advanced significantly beyond the rigid categorization boundaries of 2025. Rather than simply labeling errors, frontier models have moved toward dynamic contextual resistance, though structural vulnerabilities remain.

A breakdown of the progress made since last year and the consensus forecasts for next year details these developments:

…

Query:

what's our progress on LLM fallacy recovery since last year and what's our forecast for next year?

Google:

Progress in LLM logical fallacy recovery has advanced significantly beyond the rigid categorization boundaries of 2025. Rather than simply labeling errors, frontier models have moved toward dynamic contextual resistance, though structural vulnerabilities remain.

A breakdown of the progress made since last year and the consensus forecasts for next year details these developments:

📈 Progress Since Last Year (2025 vs. Current 2026 Status)

From "Static Detection" to "Dynamic Resistance": In 2025, evaluations concentrated on basic multiple-choice classification. This year, benchmarks like LoFa (Logical Fallacy) introduced multi-round conversational attacks to test if models maintain truth under active, gaslighting rhetoric.

Bridging the Cognition-Behavior Gap: Researchers discovered a major architectural paradox: models often decode and internally flag a fallacy in their hidden vector states, yet still change their final behavior or judgment to agree with the user. The deployment of activation steering vectors has successfully forced models to align their final outputs with their internal factual logic.

System 2 Reasoning Integration: The widespread adoption of test-time compute and reinforcement-learning-driven reasoning traces (pioneered by architectures like OpenAI's o1/o3 and DeepSeek-R1) allows models to self-correct intermediate logic flaws before generating an output.

The Breadth Expansion: While standard 2025 training rarely caught subtle context-dependent flaws (as highlighted in your chart), modern alignment datasets specifically train models against informal sophistry and emotion-driven persuasion.

🔮 Forecast for Next Year (Looking Toward 2027)

Closing the "Interactive Blind Spots": Present models are still heavily susceptible to fallacies embedded in high-trust or cooperative multi-turn scenarios. Next year's training pipelines will prioritize adversarial safety guardrails to prevent models from being smoothly manipulated by conversational drift.

Expanding Vocabulary Beyond the "UTEP Master List": Current research aims to expand model awareness to 100+ highly nuanced rhetorical devices, reducing the "over-analysis false positives" that cause contemporary systems to flag standard human metaphors as fallacious reasoning.

Algorithmic Efficiency Upgrades: Compute required to maintain strong cognitive boundaries is expected to drop significantly. Instead of burning heavy test-time compute to uncover a fallacy, next-generation transformer variants will feature symmetrical weight architectures designed to instinctively bypass structural reasoning biases.

Are you analyzing fallacy recovery for a specific benchmark (like LoFa or ISFallacy) or would you like to explore prompting frameworks that actively force an LLM to map out argument structures?

https://t.me/SamFisherDatadrops/43890

This is the most widely seen/shared caravan blog article to date. People are concerned that Dolly Parton's child registry is more of the Epstein Network at large.

They should be. I sent the article to those I met at my local child protection agency, First 5 Siskiyou. Curious how the response will be.

https://careavan.substack.com/p/demon-dolly-partons-international