---
title: Identify the principal manner in which AI image generators acquire t… — AI pictures and AI music, as reported · tree and pragmatics
description: Identify the principal manner in which AI image generators acquire their capacity to produce pictures. Exam question 1 of lesson 36 «AI pictures and AI music, as reported» of the arts course of Mova's primary school, with the dependency tree and pragmatics of the question and of each option; Mova's 
---

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# Exam question 1 · AI pictures and AI music, as reported

<!-- .ven lang=en -->
Identify the principal manner in which AI image generators acquire their capacity to produce pictures.

<!-- .vintro -->
**Mova's choice:** option 1 · **The right answer:** option 2 · wrong ✗ · **Who acts:** you, image generators · **What happens:** identify, acquire, produce · **To what, where:** principal manner, capacity, pictures

<!-- .vabout -->
This is exam question 1 of lesson 36 «AI pictures and AI music, as reported» of the arts course of Mova's primary school, asked in stiff, formal language. The page gives the question's syntax tree — a dependency tree in the style of Universal Dependencies — and its pragmatics clause by clause, then the 4 options as the student saw them, each with its tree and pragmatics. Every text is parsed by Mova itself. How the student answered it, with the score of every option and why: [the test at school](https://md.mova.elamur.ai/free/en/school-run/arts/36-ai-pictures-and-ai-music-as-reported/#e1).

## The question {#question}

```conllu
# sent_id = question:arts:36-ai-pictures-and-ai-music-as-reported:e1:1
# text = Identify the principal manner in which AI image generators acquire their capacity to produce pictures.
1	Identify	identify	VERB	VB	Mood=Imp|VerbForm=Fin	0	root	_	_
2	the	the	DET	DT	Definite=Def|PronType=Art	4	det	_	_
3	principal	principal	ADJ	JJ	Degree=Pos	4	amod	_	_
4	manner	manner	NOUN	NN	Number=Sing	1	obj	_	_
5	in	in	ADP	IN	_	6	case	_	_
6	which	which	DET	WDT	PronType=Int	9	det	_	_
7	AI	ai	NOUN	NN	Number=Sing	8	compound	_	_
8	image	image	NOUN	NN	Number=Sing	9	compound	_	_
9	generators	generator	NOUN	NNS	Number=Plur	10	nsubj	_	_
10	acquire	acquire	VERB	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	1	parataxis	_	_
11	their	their	PRON	PRP$	Case=Gen|Number=Plur|Person=3|Poss=Yes|PronType=Prs	12	nmod:poss	_	_
12	capacity	capacity	NOUN	NN	Number=Sing	10	obj	_	_
13	to	to	PART	TO	_	14	mark	_	_
14	produce	produce	VERB	VB	VerbForm=Inf	10	advcl	_	_
15	pictures	picture	NOUN	NNS	Number=Plur	14	obj	_	SpaceAfter=No
16	.	.	PUNCT	.	_	1	punct	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **identify** | imperative | you *not said here* | the principal manner |  |  |  |  | vn characterize-29.2-1-1 «NP V NP S\_ING»: agent=Agent manner=Theme |
| 2 | **acquire** | present | which image generators | generators's capacity |  |  |  |  | vn obtain-13.5.2-1 «NP.asset V NP»: agent=Asset capacity=Theme |
| 3 | **produce** | to-infinitive | which image generators *not said here* | pictures |  |  |  |  | vn create-26.4 «NP V NP»: agent=Agent picture=Result |

<!-- .note -->
One row per clause the reader finds. «not said here»: a role filled from the clause above. «roles by»: a VerbNet class and frame when one fits the verb, else the reader's rules on the tree.

## The options {#options}

### Option 1 · ← Mova's choice {#o1}

<!-- .ven lang=en -->
By inventing images without any exposure whatsoever to prior work

```conllu
# sent_id = question:arts:36-ai-pictures-and-ai-music-as-reported:e1:o1:1
# text = By inventing images without any exposure whatsoever to prior work
1	By	by	SCONJ	IN	_	2	mark	_	_
2	inventing	invent	VERB	VBG	Tense=Pres|VerbForm=Part	0	root	_	_
3	images	image	NOUN	NNS	Number=Plur	2	obj	_	_
4	without	without	ADP	IN	_	6	case	_	_
5	any	any	DET	DT	PronType=Ind	6	det	_	_
6	exposure	exposure	NOUN	NN	Number=Sing	2	obl	_	_
7	whatsoever	whatsoever	ADV	RB	_	2	advmod	_	_
8	to	to	ADP	IN	_	10	case	_	_
9	prior	prior	ADJ	JJ	Degree=Pos	10	amod	_	_
10	work	work	NOUN	NN	Number=Sing	2	obl	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **invent** | gerund |  | images |  |  |  | without any exposure; to prior work; whatsoever *property* | vn create-26.4-1 «NP V NP»: agent=Agent image=Result |

### Option 2 · ✓ the right answer {#o2}

<!-- .ven lang=en -->
Training on many images made by people

```conllu
# sent_id = question:arts:36-ai-pictures-and-ai-music-as-reported:e1:o2:1
# text = Training on many images made by people
1	Training	train	VERB	VBG	Tense=Pres|VerbForm=Part	0	root	_	_
2	on	on	ADP	IN	_	4	case	_	_
3	many	many	ADJ	JJ	Degree=Pos	4	amod	_	_
4	images	image	NOUN	NNS	Number=Plur	1	obl	_	_
5	made	make	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	4	acl	_	_
6	by	by	ADP	IN	_	7	case	_	_
7	people	people	NOUN	NNS	Number=Plur	5	obl:agent	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **train** | gerund |  |  |  | many images |  |  | vn hire-13.5.3 «NP V NP»: agent=Agent |
| 2 | **make** | participle |  | many images *not said here* |  |  |  |  | vn build-26.1-1 «NP.asset V NP»: agent=Asset |

### Option 3 {#o3}

<!-- .ven lang=en -->
Copying one artist each time

```conllu
# sent_id = question:arts:36-ai-pictures-and-ai-music-as-reported:e1:o3:1
# text = Copying one artist each time
1	Copying	copy	VERB	VBG	Tense=Pres|VerbForm=Part	0	root	_	_
2	one	one	NUM	CD	NumForm=Word|NumType=Card	3	nummod	_	_
3	artist	artist	NOUN	NN	Number=Sing	1	obj	_	_
4	each	each	DET	DT	PronType=Tot	5	det	_	_
5	time	time	NOUN	NN	Number=Sing	1	obl:unmarked	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **copy** | gerund |  | one artist |  |  | time |  | vn scribble-25.2 «NP V NP»: agent=Agent artist=Theme |

### Option 4 {#o4}

<!-- .ven lang=en -->
By employing concealed human illustrators to fulfil every request

```conllu
# sent_id = question:arts:36-ai-pictures-and-ai-music-as-reported:e1:o4:1
# text = By employing concealed human illustrators to fulfil every request
1	By	by	SCONJ	IN	_	2	mark	_	_
2	employing	employ	VERB	VBG	Tense=Pres|VerbForm=Part	0	root	_	_
3	concealed	conceal	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	5	amod	_	_
4	human	human	ADJ	JJ	Degree=Pos	5	amod	_	_
5	illustrators	illustrator	NOUN	NNS	Number=Plur	2	obj	_	_
6	to	to	PART	TO	_	7	mark	_	_
7	fulfil	fulfil	VERB	VB	VerbForm=Inf	2	advcl	_	_
8	every	every	DET	DT	PronType=Tot	9	det	_	_
9	request	request	NOUN	NN	Number=Sing	7	obj	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **employ** | gerund |  | concealed human illustrators |  |  |  |  | vn hire-13.5.3 «NP V NP»: agent=Agent illustrator=Theme |
| 2 | **conceal** | participle |  |  |  |  |  |  | vn concealment-16 «NP V NP»: agent=Agent |
| 3 | **fulfil** | to-infinitive |  | every request |  |  |  |  | tree rules |

<!-- div src -->

**Text:** the tests of Mova's primary school, written for Mova (`world/data/school/`), as the course runner gave them to the student. **Trees:** Mova's own parse — the `en` model on the CPU, when the site is built — not checked by a teacher; they may be wrong. **Frames:** Mova's frames reader (`prag`), each text read on its own. Elamur Cosmic License.

<!-- /div -->

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