# Quiz with answers — DeltaNet: correcting memory ### Question 1 Solve the worked-case variant: Replace the first target coordinate in [1,0] with 1.2 while keeping readout [0.6,0.2]. Recompute correction error. - A. If S reads [0.6,0.2] for target [1,0], error [0.4,−0.2] drives only the missing correction, unlike fully adding the target again. - B. Target-minus-read error moves from [0.4,−0.2] to [0.6,−0.2]. The first correction rises by 50% while the second is unchanged; the rule corrects observed error rather than rewriting all memory indiscriminately. - C. The delta rule reduces some interference; it does not create unlimited capacity, and stability depends on keys, gates, and normalization. - D. Memory predicts first: v̂ = Sᵀk. On S = [[2,3],[5,1]] with k=[1,0], v̂ = [2,3] — exactly what an aligned query would read. The write becomes conditional on the state, no longer only on the input. **Answer: B.** Target-minus-read error moves from [0.4,−0.2] to [0.6,−0.2]. The first correction rises by 50% while the second is unchanged; the rule corrects observed error rather than rewriting all memory indiscriminately. The correct answer executes the requested change and gives a checkable result; the other texts do not close this calculation or trace. --- ### Question 2 Which causal order correctly connects the first three stages of “DeltaNet: correcting memory”? - A. Local error → Read before writing → Limit of addition - B. Read before writing → Limit of addition → Local error - C. Limit of addition → Local error → Read before writing - D. Limit of addition → Read before writing → Local error **Answer: D.** Limit of addition → Read before writing → Local error The chain follows the taught progression; reversing stages consumes a representation or state before it is produced. --- ### Question 3 If “Local error” is removed, which diagnostic method is defensible? - A. Keep the same input, predict the first output that depends on “Local error,” then compare the before/after trace. - B. Also change the data to amplify the difference. - C. Observe only the final output and invent the cause. - D. Conclude that the whole system fails before measuring. **Answer: A.** Keep the same input, predict the first output that depends on “Local error,” then compare the before/after trace. One intervention and a prior prediction make the delta attributable to the removed mechanism. --- ### Question 4 Which verdict respects this session’s validity boundary? - A. The mechanism guarantees accuracy, speed, and stability for every workload. - B. One successful example proves the whole architecture is superior. - C. The delta rule reduces some interference; it does not create unlimited capacity, and stability depends on keys, gates, and normalization. - D. The mechanism name alone is enough for a production choice. **Answer: C.** The delta rule reduces some interference; it does not create unlimited capacity, and stability depends on keys, gates, and normalization. The correct answer bounds the conclusion; the others turn a local relation into a global guarantee. --- ### Question 5 Which evidence best matches the stated status of “DeltaNet: correcting memory”? - A. The route loads without an error. - B. Established mechanisms; numerical simplifications are pedagogical. - C. Every learner opened the file. - D. The same result is assumed on every hardware target. **Answer: B.** Established mechanisms; numerical simplifications are pedagogical. Product or mechanism evidence must remain attributed and measured; availability and completion do not prove value. --- ### Question 6 When should a simpler baseline be preferred to “Fast weights”? - A. Never: the newest mechanism wins by default. - B. As soon as one memory metric falls, regardless of quality. - C. As soon as the diagram contains fewer components. - D. When a controlled test shows equivalent quality with lower memory, latency, or complexity. **Answer: D.** When a controlled test shows equivalent quality with lower memory, latency, or complexity. The choice depends on a measured trade-off on the real workload, not novelty or one isolated metric. --- ### Question 7 A learner gets the right result but cannot explain “Read before writing.” Which remediation is most useful? - A. Rebuild the first missing transformation, label its inputs and outputs, then test a neighboring case. - B. Accept the answer because the final number is correct. - C. Provide the final result a second time. - D. Change several variables and ask for an intuition. **Answer: A.** Rebuild the first missing transformation, label its inputs and outputs, then test a neighboring case. The remediation targets the first causal break and then requires transfer instead of rewarding a guessed result. --- ### Question 8 Which submission actually demonstrates the outcome “Separate fast weights and trained parameters.”? - A. A list of terms without causal relations. - B. A screenshot without values or interpretation. - C. A trace with starting data, transformations, observed result, boundary, and next experiment. - D. A confident claim without a baseline or threshold. **Answer: C.** A trace with starting data, transformations, observed result, boundary, and next experiment. The correct submission makes the reasoning reproducible and the verdict revisable by future measurement.