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Introducing "Truth Chain." A real-time polling solution to log controversial responses across major LLMs to the blockchain. The objective is continuous accountability and measurement of which LLMs are being tampered with for political purposes. cc Elon Musk

210,970 görüntüleme • 1 yıl önce •via X (Twitter)

10 Yorum

Renaissance profil fotoğrafı
Renaissance1 yıl önce

@elonmusk So it’s essentially community notes for LLMs?

Rex St. John profil fotoğrafı
Rex St. John1 yıl önce

@elonmusk correct

d’admi smalls profil fotoğrafı
d’admi smalls1 yıl önce

@elonmusk the madman just before Christmas delivered the biggest gift of all

Rex St. John profil fotoğrafı
Rex St. John1 yıl önce

@alexc_xyz @elonmusk cant sleep clowns will eat me

Sweep profil fotoğrafı
Sweep1 yıl önce

@elonmusk intresting

Alex profil fotoğrafı
Alex1 yıl önce

@elonmusk $TRUTH shall prevail

SavageBoy profil fotoğrafı
SavageBoy1 yıl önce

@elonmusk genius

🧧꧁Zen꧂🧧 profil fotoğrafı
🧧꧁Zen꧂🧧1 yıl önce

@elonmusk @opus_genesis would you wanna collaborate with @rexstjohn alongside @veryvanya on the community note LLMs

Mark profil fotoğrafı
Mark1 yıl önce

@0xRenaissance @elonmusk Hahaha I know man. Just teasing. Excited to follow what you’re building!

matthew bernal profil fotoğrafı
matthew bernal1 yıl önce

@elonmusk 2GmUPhpe93kcTJZrC7NJ2keeDZRT5dBveUgegb13pump

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A 4-year-old child has seen 50x more information than the biggest LLMs. Yann LeCun is the Chief AI Scientist at Meta. He recently spoke on “The Expanding Universe of Generative Models” panel at the World Economic Forum in Davos. Yann highlighted the idea that a 4-year-old child is way smarter than current cutting-edge large language models (LLMs). “Think about what a child sees through vision. Put a number on how much information a 4-year-old child has seen during their life. It’s 20 Mbps going through the optical nerve for 16,000 wake hours in the first 4 years of life. 3,600 seconds per hour is 10^15 bytes. This is 50x more information than the biggest LLMs we have. A 4-year-old child is way smarter than these models having acquired an enormous amount of knowledge about how the world works.” The real constraint right now is the ability of LLMs to think. Today, LLMs are only capable of System 1 thinking. System 1 vs System 2 thinking was popularised in the book 'Thinking, Fast and Slow' by Daniel Kahneman. System 1 tasks involve quick, instinctive, automatic responses. LLMs struggle with discontinuous tasks that require a creative leap in progress as they imitate human responses. It's hard to go above human response accuracy if LLMs are only trained on humans. Models are building the track in front of them with each word being generated. What could it mean to give language models System 2 thinking? This remains a future development I'm excited about.

Alex Banks

22,958 görüntüleme • 2 yıl önce