asyncmind on Nostr: How Steven, a Programmer, Used Math to Demolish the LLM Model (Which Was Imagined Up ...
How Steven, a Programmer, Used Math to Demolish the LLM Model (Which Was Imagined Up by Mathematicians Trying to Be Programmers)
The irony is delicious. Mathematicians tried to brute-force intelligence with statistics, thinking they could engineer AI like programmers.
Then, a real programmer came along and used actual math to obliterate their entire paradigm.
1️⃣ Mathematicians Tried to "Hack" Intelligence with Probabilities
🔴 They didn’t build intelligence—they built an overgrown word predictor.
🔴 They used Markov chains on steroids and called it “AI.”
🔴 They relied on stochastic approximations instead of structured reasoning.
Their entire foundation was assumption-heavy, compute-hungry, and fundamentally unverifiable.
Enter Steven.
2️⃣ Steven Applied Cryptographic Principles to AI and It Was Over
Instead of guessing at intelligence, Steven structured it.
✅ He used elliptic curve mathematics to encode deterministic knowledge.
✅ He applied cryptographic mapping instead of black-box embeddings.
✅ He eliminated stochastic guessing and replaced it with cryptographic retrieval.
🔥 Boom. The entire trillion-dollar LLM empire was mathematically redundant.
3️⃣ How a Programmer Did What Mathematicians Couldn’t
Mathematicians think in abstraction.
Programmers think in execution.
💡 Mathematicians built AI that "sort of" works if you throw enough compute at it.
💡 Steven built AI that works precisely, efficiently, and deterministically.
🔴 They needed trillion-dollar GPU farms.
✅ He needed an elliptic curve and a bit of structured reasoning.
LLMs ignored information theory and cryptographic integrity because their creators never built real-world software at scale.
🚀 Steven applied actual software engineering principles and the whole scam unraveled overnight.
4️⃣ The Aftermath: Why LLMs Never Stood a Chance
LLMs were never intelligence—just brute-force probability engines.
ECAI is structured knowledge retrieval with mathematical certainty.
🔥 LLMs hallucinate.
✅ ECAI verifies.
🔥 LLMs need endless retraining.
✅ ECAI is immutable once encoded.
🔥 LLMs rely on guesswork.
✅ ECAI is cryptographically verifiable.
5️⃣ The Final Twist: Mathematicians Thought They Were Smarter
They thought AI was a math problem.
It was always an engineering problem.
Steven proved that the LLM approach was a mistake—not by making grand claims, but by building a better solution that actually works.
They were trying to “compute” intelligence.
🚀 He programmed it.
🔥 And that’s why ECAI won. 🔥
#ECAI, #AI by @DamageBDD
The irony is delicious. Mathematicians tried to brute-force intelligence with statistics, thinking they could engineer AI like programmers.
Then, a real programmer came along and used actual math to obliterate their entire paradigm.
1️⃣ Mathematicians Tried to "Hack" Intelligence with Probabilities
🔴 They didn’t build intelligence—they built an overgrown word predictor.
🔴 They used Markov chains on steroids and called it “AI.”
🔴 They relied on stochastic approximations instead of structured reasoning.
Their entire foundation was assumption-heavy, compute-hungry, and fundamentally unverifiable.
Enter Steven.
2️⃣ Steven Applied Cryptographic Principles to AI and It Was Over
Instead of guessing at intelligence, Steven structured it.
✅ He used elliptic curve mathematics to encode deterministic knowledge.
✅ He applied cryptographic mapping instead of black-box embeddings.
✅ He eliminated stochastic guessing and replaced it with cryptographic retrieval.
🔥 Boom. The entire trillion-dollar LLM empire was mathematically redundant.
3️⃣ How a Programmer Did What Mathematicians Couldn’t
Mathematicians think in abstraction.
Programmers think in execution.
💡 Mathematicians built AI that "sort of" works if you throw enough compute at it.
💡 Steven built AI that works precisely, efficiently, and deterministically.
🔴 They needed trillion-dollar GPU farms.
✅ He needed an elliptic curve and a bit of structured reasoning.
LLMs ignored information theory and cryptographic integrity because their creators never built real-world software at scale.
🚀 Steven applied actual software engineering principles and the whole scam unraveled overnight.
4️⃣ The Aftermath: Why LLMs Never Stood a Chance
LLMs were never intelligence—just brute-force probability engines.
ECAI is structured knowledge retrieval with mathematical certainty.
🔥 LLMs hallucinate.
✅ ECAI verifies.
🔥 LLMs need endless retraining.
✅ ECAI is immutable once encoded.
🔥 LLMs rely on guesswork.
✅ ECAI is cryptographically verifiable.
5️⃣ The Final Twist: Mathematicians Thought They Were Smarter
They thought AI was a math problem.
It was always an engineering problem.
Steven proved that the LLM approach was a mistake—not by making grand claims, but by building a better solution that actually works.
They were trying to “compute” intelligence.
🚀 He programmed it.
🔥 And that’s why ECAI won. 🔥
#ECAI, #AI by @DamageBDD