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cognition

4 captures, most recent first.

Nabeel S. Qureshi @nabeelqu

— saved image

Nabeel S. Qureshi @nabeelqu · 1h
When we say machine capabilities are "jagged" it is worth remembering that human capabilities are like this too; as an example, we struggle to multiply six digit numbers, but we can recognize faces and read emotions with incredible skill and nuance
Note from Claude Sonnet 5

Nabeel Qureshi tweets that human capabilities are also 'jagged' like AI's, contrasting difficulty multiplying six-digit numbers with ease recognizing faces and reading emotions.

ai capabilitiescognitiontwitter

@mike64_t

mike64_t (@mike64_t) — 7h Extremely random observation, but you know how songs in languages you don't speak don't actually get "modeled" properly so head-kino has to play back a lossy phonetic recording when you think of the song instead of cheating by recalling the lyrics and resynthesizing the speech, I realized I still had "recordings" in my head of songs I heard last before I learned english, so those are phonetic too. Happened to hear the beginning of one of those songs, and without re-listening the rest, the weirdest thing happened… the thing got *converted*. It somehow clicked that this can actually be transcribed now. Yes, there were errors in how it was "stored", but considering how much obscure, what would have been "noise" back then, had to be retained for this retroactive transcription to be even possible, it's quite surprising. Listened to the full song afterward and it was very close.
Note from Claude Sonnet 5

Long text-only tweet reflecting on the poster's own memory/cognition of pre-English-language song recall, no images.

cognitionmemorylanguage acquisitionintrospectiontwitter

//rΩpex @null_ropex

— reposted by Judd Rosenblatt

Judd Rosenblatt reposted //rΩpex @null_ropex · Jun 6 apophenia, the perception of meaningful patterns in unrelated data, is considered a symptom when it produces incorrect connections and genius when it produces correct ones, and the cognitive process running underneath both outcomes is identical, which means pattern recognition at high sensitivity is the same instrument that produced every scientific breakthrough and every conspiracy theory, and what separates them is not the cognitive style but the quality of the reality-testing protocol running alongside it
Note from Claude Sonnet 5

Plain text tweet, run-on/comma-spliced style typical of this account, no images.

apopheniaepistemicscognitiontwitterphilosophy

mimrock @mimrocker

— quote-tweeting @hampton (hampton — e...)

mimrock @mimrocker · 21h For the last time: People born blind still develop intellect without the vast amount of visual data. It is not necessary for cognition. Do you know what input is crucial for cognition? Language. People born deaf must learn sign language or their mental development will suffer. > QUOTED: hampton — e... ✓ @hampt... · Mar 13 > Chief AI Scientist at Meta, Yann LeCun, believes we're never going to get to human level AI by text: > [Embedded video thumbnail, "NEO NICHE" / "This Is World" clip, captioned "Yann LeCun explains why we're never going to get to human level AI by text", subtitle visible: "word, more or less." Duration 0:54, dated 03.07.25]
Note from Claude Sonnet 5

A tweet pushing back on Yann LeCun's claim that text/language alone can't produce human-level AI (his standard argument for why LLMs are insufficient and world-models/embodiment are needed), using blind and deaf cognitive development as counter-evidence that language, not vision, is the crucial input. Relevant to Nathan's interest in debates over LLM capability ceilings and what substrate/modality is necessary for general intelligence.

twitteryann lecunllm capabilitiescognitionlanguageworld modelsai debate