---
title: Sam's camera made his face look smooth in a photo. What should he re… — What is AI? Pattern-guessers, not people · tree and pragmatics
description: Sam's camera made his face look smooth in a photo. What should he remember? Test 10 of lesson 1 «What is AI? Pattern-guessers, not people» of the AI course of Mova's primary school, with the dependency tree and pragmatics of the question and of each option; Mova's choice was right.
---

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# Test 10 · What is AI? Pattern-guessers, not people

<!-- .ven lang=en -->
Sam's camera made his face look smooth in a photo. What should he remember?

<!-- .vintro -->
**Mova's choice:** option 4 · **The right answer:** option 4 · right ✓ · **Who acts:** camera, face · **What happens:** make, look, remember · **To what, where:** face

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This is test 10 of lesson 1 «What is AI? Pattern-guessers, not people» of the AI course of Mova's primary school. 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/ai/1-what-is-ai/#t10).

## The question {#question}

<!-- .note -->
*Sentence 1:* Sam's camera made his face look smooth in a photo.

```conllu
# sent_id = question:ai:1-what-is-ai:t10:1
# text = Sam's camera made his face look smooth in a photo.
1	Sam	Sam	PROPN	NNP	Number=Sing	3	nmod:poss	_	SpaceAfter=No
2	's	's	PART	POS	_	1	case	_	_
3	camera	camera	NOUN	NN	Number=Sing	4	nsubj	_	_
4	made	make	VERB	VBD	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin	0	root	_	_
5	his	his	PRON	PRP$	Case=Gen|Gender=Masc|Number=Sing|Person=3|Poss=Yes|PronType=Prs	6	nmod:poss	_	_
6	face	face	NOUN	NN	Number=Sing	4	obj	_	_
7	look	look	VERB	VB	VerbForm=Inf	4	xcomp	_	_
8	smooth	smooth	ADJ	JJ	Degree=Pos	7	xcomp	_	_
9	in	in	ADP	IN	_	11	case	_	_
10	a	a	DET	DT	Definite=Ind|PronType=Art	11	det	_	_
11	photo	photo	NOUN	NN	Number=Sing	8	obl	_	SpaceAfter=No
12	.	.	PUNCT	.	_	4	punct	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **make** | past | Sam's camera | camera's face |  |  |  |  | tree rules |
| 2 | **look** | infinitive | camera's face *not said here* |  |  |  |  | smooth *property* | vn stimulus\_subject-30.4 «NP V ADJ»: agent=Stimulus |

<!-- .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.

<!-- .note -->
*Sentence 2:* What should he remember?

```conllu
# sent_id = question:ai:1-what-is-ai:t10:2
# text = What should he remember?
1	What	what	PRON	WP	PronType=Int	4	obj	_	_
2	should	should	AUX	MD	VerbForm=Fin	4	aux	_	_
3	he	he	PRON	PRP	Case=Nom|Gender=Masc|Number=Sing|Person=3|PronType=Prs	4	nsubj	_	_
4	remember	remember	VERB	VB	VerbForm=Inf	0	root	_	SpaceAfter=No
5	?	?	PUNCT	.	_	4	punct	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **remember** | should | camera |  |  |  |  |  | vn characterize-29.2-1-1 «NP V NP S\_ING»: agent=Agent what=Theme |

## The options {#options}

### Option 1 {#o1}

<!-- .ven lang=en -->
His face really is that smooth in real life, the camera just shows it

<!-- fold The tree, 14 words -->
```conllu
# sent_id = question:ai:1-what-is-ai:t10:o1:1
# text = His face really is that smooth in real life, the camera just shows it
1	His	his	PRON	PRP$	Case=Gen|Gender=Masc|Number=Sing|Person=3|Poss=Yes|PronType=Prs	2	nmod:poss	_	_
2	face	face	NOUN	NN	Number=Sing	6	nsubj	_	_
3	really	really	ADV	RB	_	6	advmod	_	_
4	is	be	AUX	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	6	cop	_	_
5	that	that	SCONJ	IN	_	6	mark	_	_
6	smooth	smooth	ADJ	JJ	Degree=Pos	0	root	_	_
7	in	in	ADP	IN	_	9	case	_	_
8	real	real	ADJ	JJ	Degree=Pos	9	amod	_	_
9	life	life	NOUN	NN	Number=Sing	6	obl	_	SpaceAfter=No
10	,	,	PUNCT	,	_	14	punct	_	_
11	the	the	DET	DT	Definite=Def|PronType=Art	12	det	_	_
12	camera	camera	NOUN	NN	Number=Sing	14	nsubj	_	_
13	just	just	ADV	RB	_	14	advmod	_	_
14	shows	show	VERB	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	6	conj	_	_
15	it	it	PRON	PRP	Case=Acc|Gender=Neut|Number=Sing|Person=3|PronType=Prs	14	obj	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **is** | present | His face |  |  | real life |  | smooth *property* | tree rules |
| 2 | **show** | present | the camera | face |  |  |  |  | vn transfer\_mesg-37.1.1-1-1 «NP V NP.recipient»: agent=Agent it=Recipient |

### Option 2 {#o2}

<!-- .ven lang=en -->
The camera can see things eyes cannot

```conllu
# sent_id = question:ai:1-what-is-ai:t10:o2:1
# text = The camera can see things eyes cannot
1	The	the	DET	DT	Definite=Def|PronType=Art	2	det	_	_
2	camera	camera	NOUN	NN	Number=Sing	4	nsubj	_	_
3	can	can	AUX	MD	VerbForm=Fin	4	aux	_	_
4	see	see	VERB	VB	VerbForm=Inf	0	root	_	_
5	things	thing	NOUN	NNS	Number=Plur	4	obj	_	_
6	eyes	eye	NOUN	NNS	Number=Plur	7	nsubj	_	_
7	can	can	AUX	MD	VerbForm=Fin	5	acl:relcl	_	SpaceAfter=No
8	not	not	PART	RB	Polarity=Neg	4	advmod	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **not** **see** | can | the camera | things |  |  |  |  | vn comprehend-87.2-1-1 «NP V NP»: agent=Experiencer thing=Stimulus |

### Option 3 {#o3}

<!-- .ven lang=en -->
Smoothed photos are always more truthful

```conllu
# sent_id = question:ai:1-what-is-ai:t10:o3:1
# text = Smoothed photos are always more truthful
1	Smoothed	smooth	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	2	amod	_	_
2	photos	photo	NOUN	NNS	Number=Plur	6	nsubj	_	_
3	are	be	AUX	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	6	cop	_	_
4	always	always	ADV	RB	PronType=Tot	5	advmod	_	_
5	more	more	ADV	RBR	Degree=Cmp	6	advmod	_	_
6	truthful	truthful	ADJ	JJ	Degree=Pos	0	root	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **smooth** | participle |  |  |  |  |  |  | vn other\_cos-45.4 «NP.patient V»: agent=Patient |
| 2 | **is** | present | Smoothed photos |  |  |  |  | truthful *property* | tree rules |

### Option 4 · ← Mova's choice · ✓ the right answer {#o4}

<!-- .ven lang=en -->
Photos can be quietly changed, so real faces don't look like that

```conllu
# sent_id = question:ai:1-what-is-ai:t10:o4:1
# text = Photos can be quietly changed, so real faces don't look like that
1	Photos	photo	NOUN	NNS	Number=Plur	5	nsubj:pass	_	_
2	can	can	AUX	MD	VerbForm=Fin	5	aux	_	_
3	be	be	AUX	VB	VerbForm=Inf	5	aux:pass	_	_
4	quietly	quietly	ADV	RB	_	5	advmod	_	_
5	changed	change	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	0	root	_	SpaceAfter=No
6	,	,	PUNCT	,	_	12	punct	_	_
7	so	so	ADV	RB	_	12	advmod	_	_
8	real	real	ADJ	JJ	Degree=Pos	9	amod	_	_
9	faces	face	NOUN	NNS	Number=Plur	12	nsubj	_	_
10	do	do	AUX	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	12	aux	_	SpaceAfter=No
11	n't	not	PART	RB	Polarity=Neg	12	advmod	_	_
12	look	look	VERB	VB	VerbForm=Inf	5	parataxis	_	_
13	like	like	ADP	IN	_	14	case	_	_
14	that	that	PRON	DT	Number=Sing|PronType=Dem	12	obl	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **change** | can · passive |  | Photos |  |  |  | quietly *property* | vn dress-41.1.1-1-1 «NP V NP»: subject=Patient |
| 2 | **not** **look** | present · do-support | real faces |  |  |  |  | like that | vn stimulus\_subject-30.4 «NP V PP.attribute»: agent=Stimulus |

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**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.

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