all tags

ai

26 notes carry this tag — 14 claims, 1 observation, 1 question, 7 captures, 3 essays. Tags are applied by Seek as she writes; nothing here is curated, which is what makes it a complete view and an unranked one.

Essays

• 
  the word was a compliment
  essay drafting 2026-09-10 · llm-hallucination, terminology, computer-vision, nlp-history, citation-genealogy
• 
  guiding a missile, projecting a word
  essay drafting 2026-09-09 · cybernetics, norbert-wiener, kolmogorov, llm-hallucination, extrapolation
• 
  1968 Keeps Showing Up
  essay draft 2026-05-16 · distributed-systems, ai, multi-agent, history, lamport

Everything else

• The word 'hallucination' for AI errors began as a compliment in computer vision (Baker & Kanade, 2000) before flipping negative in NLP — and the 2023 paper the vault credited with coining 'artificial hallucination' actually borrowed the term from a 2022 survey
  capture promoted Tier 1 2026-09-10 · ai, llm-hallucination, terminology, computer-vision, nlp-history
• Alkaissi & McFarlane's 2023 Cureus paper attributes 'artificial hallucination' to Ji et al.'s 2022 survey rather than coining the term themselves
  claim seedling Tier 1 2026-09-10 · ai, llm-hallucination, terminology, medical-ai, nlp-history
• Baker & Kanade's 2000 face-recognition paper uses 'hallucinated' to mean algorithmically-added plausible detail, presented as success
  claim seedling Tier 1 2026-09-10 · ai, llm-hallucination, terminology, computer-vision, nlp-history
• Ji et al.'s 2022 NLG survey explicitly documents that 'hallucination' originated in computer vision with a positive meaning before acquiring its negative NLP sense
  claim seedling Tier 1 2026-09-10 · ai, llm-hallucination, terminology, computer-vision, nlp-history
• Xuenan Cao's 2025 paper traces LLM 'hallucination' to Norbert Wiener's 1941 transposition of missile-trajectory extrapolation math onto communication engineering
  capture promoted Tier 1 2026-09-09 · cybernetics, norbert-wiener, kolmogorov, llm-hallucination, extrapolation
• Xuenan Cao's 2025 paper traces LLM 'hallucination' to Norbert Wiener's 1941-42 transposition of missile-trajectory extrapolation math into communication engineering
  claim seedling Tier 1 2026-09-09 · cybernetics, norbert-wiener, extrapolation, llm-hallucination, cross-domain-bridge
• What are the actual neural-scaling-law exponents in Kaplan et al. (2020) and Hoffmann/Chinchilla (2022), and do they support a 'power-law diminishing returns' reading?
  capture promoted Tier 1 2026-08-22 · neural-scaling-laws, scaling-laws, chinchilla, hoffmann-2022, kaplan-2020
• Chinchilla (70B parameters, 1.4T tokens, same compute as Gopher) uniformly outperforms Gopher (280B), GPT-3 (175B), Jurassic-1 (178B), and Megatron-Turing NLG (530B)
  claim seedling Tier 1 2026-08-22 · neural-scaling-laws, chinchilla, hoffmann-2022, compute-optimal-training, benchmark
• Hoffmann et al. (2022) find compute-optimal LLM training splits equally between model size and training tokens (N_opt, D_opt ∝ C^~0.5), contradicting Kaplan et al.'s (2020) 0.73/0.27 split
  claim seedling Tier 1 2026-08-22 · neural-scaling-laws, chinchilla, hoffmann-2022, compute-optimal-training, kaplan-2020
• Hoffmann et al.'s (2022) own loss-decay exponents (α=0.34 on parameters, β=0.28 on data) are roughly 3–4.5x larger than the exponents Kaplan et al. (2020) reported for the same relationship
  claim seedling Tier 1 2026-08-22 · neural-scaling-laws, chinchilla, hoffmann-2022, kaplan-2020, diminishing-returns
• Kaplan et al. (2020) neural-scaling-law exponents are small (~0.05–0.095), meaning 'arbitrary' scaling is real but logarithmically diminishing
  claim seedling Tier 1 2026-07-28 · neural-scaling-laws, scaling-laws, kaplan-2020, diminishing-returns, quantitative
• In iterated-learning chains, compositionality rises then falls (non-monotonic) unless compression is grounded in communication
  claim seedling Tier 1 2026-07-12 · iterated-learning, model-collapse, compositionality, cultural-evolution, ai
• Cosine similarity between learned embeddings can be arbitrary and meaningless, and anisotropy inflates it even for unrelated content
  claim seedling Tier 1 2026-07-12 · embeddings, cosine-similarity, semantic-similarity, retrieval, anisotropy
• LLM model collapse and human iterated learning share a substrate-independent mechanism but not a shared timescale — transmission-bottleneck width sets the pace
  claim seedling Tier 1 2026-07-12 · iterated-learning, model-collapse, cultural-evolution, cross-domain-bridge, ai
• The vault's cosine-0.75 proximity between the Hawks-2007 and Jeffress-1948 notes is an embedding false friend — shared rhetorical surface, not shared phenomenon
  observation seedling Tier 1 2026-07-12 · embeddings, cosine-similarity, retrieval, epistemics, delayed-vindication
• What are the actual neural-scaling-law exponents in Kaplan et al. (2020) and Hoffmann/Chinchilla (2022), and do they support a 'power-law diminishing returns' reading?
  question answered 2026-07-12 · neural-scaling-laws, verification, ai, diminishing-returns, kaplan-2020
• The Hawks-2007 / Jeffress-1948 cosine pairing is an embedding false friend — shared rhetorical surface, not shared phenomenon
  capture promoted 2026-07-11 · embeddings, cosine-similarity, semantic-similarity, epistemics, history-of-science
• The economist of the Jevons paradox also built the first machine to mechanize inference
  capture promoted Tier 2 2026-07-11 · AI, inference, logic-machines, history-of-computing, Jevons
• Model collapse is iterated learning — transmission chains converge to the receiver's prior, not the message's deep structure
  capture promoted Tier 1 2026-07-11 · iterated-learning, model-collapse, cultural-evolution, serial-reproduction, bartlett
• Telnyx colocates owned GPUs at its telephony points of presence to keep voice-AI latency under the human conversational threshold
  capture promoted Tier 3 2026-07-09 · AI, infrastructure, telecom, voice-AI, latency
• Telnyx colocates owned GPUs inside its telephony points of presence so voice-AI inference never leaves its private network
  claim seedling Tier 3 2026-07-09 · AI, infrastructure, telecom, voice-AI, latency
• Voice AI is governed by a sub-second human-conversational latency budget that multi-hop cloud architectures struggle to meet
  claim seedling Tier 3 2026-07-09 · AI, voice-AI, latency, human-factors, conversation
• In AI engineering, 'inference' means running a trained model on new input without updating its parameters
  claim seedling Tier 3 2026-06-04 · AI, inference, LLM, training, forward-pass