Key Arguments

• Dreyfus notes that Quillian’s results raise a question about the adequacy of the model itself, not merely about implementation: 'These difficulties suggest that the model itselfthe idea that our understanding of a natural language involves building up a structured whole out of an enormous number of explicit partsmay well be mistaken.'
• He emphasizes that Quillian’s approach assumes 'an analysis which has no place for perceptual gestalts', thereby excluding holistic, non‑part‑based forms of understanding that Dreyfus has argued are central elsewhere.
• He points out that Quillian’s program must store 'the gigantic number of facts resulting from' such analysis, and that the key issue is how the size of this fact base scales: 'If this data structure grows too rapidly with the addition of new definitions, then Quillian's work, far from being encouraging, would be a reductio ad absurdum of the whole computer-oriented approach.'
• He insists that, before treating Quillian’s work as grounds for optimism, 'one would expect an answer to the basic question: Does Quillian's data base grow linearly or exponentially with additional entries?'—a question that remains unanswered.
• Dreyfus notes the empirical limitation that Quillian’s program 'contains definitions of only from 50 to 60 words,' far from the hundreds or thousands that would test scaling behavior.
• He underscores that even Minsky, three years after Quillian’s work was completed, concedes ignorance about scalability: in 1968 Minsky has to admit that '"we simply do not know enough about how powerful Quillian's methods would be when provided with a more substantial knowledge bank."' and Dreyfus adds, 'Again, no further progress has been reported.'

Source Quotes

The processing that goes on in a person's head when he ''understands" a sentence and incorporates its meaning into his memory is very large indeed, practically all of it being done without his conscious knowledge. 46 The magnitude of the problem confronting Quillian becomes clear when we note that the definition of eight hundred and fifty words comprise far more information than can be modeled in the core of today's computers. . . .47 These difficulties suggest that the model itselfthe idea that our understanding of a natural language involves building up a structured whole out of an enormous number of explicit partsmay well be mistaken. Quillian's work raises rather than resolves the question of storing the gigantic number of facts resulting from an analysis which has no place for perceptual gestalts.

46 The magnitude of the problem confronting Quillian becomes clear when we note that the definition of eight hundred and fifty words comprise far more information than can be modeled in the core of today's computers. . . .47 These difficulties suggest that the model itselfthe idea that our understanding of a natural language involves building up a structured whole out of an enormous number of explicit partsmay well be mistaken. Quillian's work raises rather than resolves the question of storing the gigantic number of facts resulting from an analysis which has no place for perceptual gestalts. If this data structure grows too rapidly with the addition of new definitions, then Quillian's work, far from being encouraging, would be a reductio ad absurdum of the whole computer-oriented approach.

Quillian's work raises rather than resolves the question of storing the gigantic number of facts resulting from an analysis which has no place for perceptual gestalts. If this data structure grows too rapidly with the addition of new definitions, then Quillian's work, far from being encouraging, would be a reductio ad absurdum of the whole computer-oriented approach. Before taking a stand on whether Quillian's work is grounds for optimism, one would expect an answer to the basic question: Does Quillian's data base grow linearly or exponentially with additional entries?

If this data structure grows too rapidly with the addition of new definitions, then Quillian's work, far from being encouraging, would be a reductio ad absurdum of the whole computer-oriented approach. Before taking a stand on whether Quillian's work is grounds for optimism, one would expect an answer to the basic question: Does Quillian's data base grow linearly or exponentially with additional entries? On this crucial point it is surprising to find much hope but little information.

On this crucial point it is surprising to find much hope but little information. Quillian's program contains definitions of only from 50 to 60 words, and, in describing Quillian's work, in his book written in 1968, three years after the work was completed, Minsky has to admit that "we simply do not know enough about how powerful Quillian's methods would be when provided with a more substantial knowledge bank."48Again, no further progress has been reported. II Significance of Current Difficulties What would be reasonable to expect?

Key Concepts

• These difficulties suggest that the model itselfthe idea that our understanding of a natural language involves building up a structured whole out of an enormous number of explicit partsmay well be mistaken.
• Quillian's work raises rather than resolves the question of storing the gigantic number of facts resulting from an analysis which has no place for perceptual gestalts.
• If this data structure grows too rapidly with the addition of new definitions, then Quillian's work, far from being encouraging, would be a reductio ad absurdum of the whole computer-oriented approach.
• Before taking a stand on whether Quillian's work is grounds for optimism, one would expect an answer to the basic question: Does Quillian's data base grow linearly or exponentially with additional entries?
• Quillian's program contains definitions of only from 50 to 60 words, and, in describing Quillian's work, in his book written in 1968, three years after the work was completed, Minsky has to admit that "we simply do not know enough about how powerful Quillian's methods would be when provided with a more substantial knowledge bank."48Again, no further progress has been reported.

Context

Having presented Quillian’s ambitions and subsequent disappointments, Dreyfus steps back to question the underlying explicit‑parts model of understanding and to frame Quillian’s program as a potential reductio of the symbolic, fact‑accumulation strategy, especially given the lack of data on how the system scales and the absence of reported advances.