Trends Final Flashcards

1
Q

What is AI and what are the 3 types

A

Artificial Intelligence

Generative
Predictive
Stochastic Parrot

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1
Q

Disruptive Technology

A

is an innovation that significantly alters how consumers, industries, or businesses operate. It supersedes an older established process, product, or habit with recognizably superior attributes.

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2
Q

ML

A

Machine Learning

uses data and algorithms to mimic
human learning

statistical methods to train
algorithms to classify or predict and
even provide insights into data
mining projects

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3
Q

Generative AI

A

Generative AI focuses on understanding patterns and structure in data and using that to create new data that looks like it. This includes writing blocks of text, lines of code or creating photorealistic images

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4
Q

Predictive AI

A

Is mainly on classification, learning the difference between “things”
This is what’s used in recommendation engines like those used by Netflix or Amazon to distinguish between things you might want to watch or buy and things you’re unlikely to be interested in

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5
Q

3 major features of AI

A

Extremely high computing speed
Large volume dataset processing
ability to self learn

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6
Q

3 levels of AI

A

ANI
AGI
ASI

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7
Q

ANI

A

Narrow intelligence

is specialized
to the function for which it has been developed

Specific

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8
Q

AGI

A

General intelligence

Is generally referred to as
‘human-level AI’, because it describes the capacity of a computer that is as smart as
a human, a point often referred to as ‘Singularity’

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9
Q

ASI

A

Super intelligence

ASI is the point at which computers
possess an intellectual capacity far greater than that of human beings with the capacity for social skills and general knowledge that would increase exponentially over time.

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10
Q

3 examples of AI

A

Chat gpt
Luna
soudstorm

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11
Q

LLM

A

Large language models

artificial intelligence program designed to understand, generate, and work with human language on a large scale

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12
Q

NLP

A

Natural language processing

involves enabling computers to
understand, interpret, and respond to
human language in a way that is both
meaningful and useful.

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13
Q

Application programming interface

A

protocols that allow different software programs to communicate with each other/AI

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14
Q

Deep Learning

A

subset of ML

uses neural networks to analyze and
learn from data.

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15
Q

Randomness vs learning and data volume

A

“Monkey in the theorem”
based on generating text randomly, without any understanding

output mostly random gibberish with the occasional coherent sentence

no training

Ai
learning from the previous inputs.

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16
Q

Understanding vs mimicking

A

“Monkey in the theorem”
do not understand the meaning of the text it is generating

AI
AI and NLP models do not truly understand the text they generate

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17
Q

3 strategies for facial recognition

A

feature based
appearance based
knowledge based

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18
Q

Feature based facial recognition

A

identify fiducial points: specific facial landmarks

measures relationships and distances between facial features

generally more robust to variations in lighting and facial expressions since it relies on stable and distinctive facial landmarks

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19
Q

Appearance based facial recognition

A

Appearance-based methods use holistic information from the face.

Instead of focusing on individual features, these techniques analyze the entire facial image as a whole

can be more effective in capturing more detailed and subtle facial characteristics

generally easier to implement since they don’t require the detection of specific facial landmarks

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20
Q

knowledge based facial recognition

A

designed to identify suspicious or abnormal behaviors based on predefined rules or knowledge about facial expressions and behaviors.

relies on a database of facial expressions/ behaviors corresponding with specific intentions/emotions

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21
Q

3 benefits of facial recognition

A

Enhanced security and safety

Efficiency in policing

finding missing persons

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22
Q

3 disadvantages to facial recognition

A

Privacy concerns

Potential for abuse

Bias and inaccuracy

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23
Q

AFIS

A

Automated fingerprint identification system

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24
Q

how many records does the AFIS database contain

A

4 million

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25
Q

What does AFIS do

A

It attempts to locate and measure the reliable and persistent features within fingerprint and palm print images

It then notes their location X-Y coordinates
And their theta (θ) vectors – showing the orientation of those features.

i.e. ridge endings, bifurcating ridges, large ridge dots

Can also use minutiae, sweat pores and edge features

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26
Q

Can fingerprints be the same

A

No two complete fingerprints have been found to be the same – Not
even from the same person.

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27
Q

4 problems AI overcomes in the AFIS database

A

growth
injury
deviation
quality of record

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28
Q

CPAP

A

Capture, process, analyze, present

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29
Q

M4

A

Multimodal mobility morphobot

29
Q

How does laser scanning work

A

A laser beam is shone onto a
rotating mirror that reflects the
beam out

Simultaneous to this vertical
rotation, the system rotates
horizontally to cover a range of
360 degrees

The laser beam is reflected back to the scanner by objects and/or surfaces in its path

The beam is recorded as a series of pulses or points as the distances as well as their relative vertical and
horizontal angles are determined, recorded and converted into X-Y-Z values.

30
Q

SLAM

A

Simultaneous Location and mapping

31
Q

Nerf

A

Neural radiance fields

computer generated 3-models that mimic the dynamics of lighting on an object or scene to create a near photo-realistic representation that can in turn be viewed from any viewpoint as either a static image or simulated video

32
Q

Attention span

A

the average attention span of a gold fish is 9 seconds

average attention span of a human is 8 seconds

33
Q

hierarchy of attention

A

actions
objects
picture
diagrams
written word
spoken word

34
Q

transhumanism

A

the belief or theory that the human race can evolve beyond its current physical and mental limitations

35
Q

First fully AI generated movie

A

Salt 2023

36
Q

Two main DNA databases

A

National DNA databank
Local DNA database at CFS

37
Q

Positive outcomes of DNA evidence

A

Increased sensitivity of DNA
analysis (smaller samples
required).

Faster results.

Better interpretation of mixed
profiles.

Better results from difficult
surfaces.

38
Q

Challenges in DNA evidence

A

Issues regarding
secondary and tertiary
transfer of DNA.

Increased issues with
collection (cross
contamination).

39
Q

2 ways bias in fingerprinting can be avoided

A

Blind verification of comparison process.

Controls on exposure to contextual information by fingerprint examiners.

40
Q

Fingerprint development techniques

A

Chosen for surface: porous vs non-porous

Chosen for fingerprint matrix: blood, sweat, dust

Chosen for contrast / photography

41
Q

What is VMD

A

Depositing very thin layers of metal on to an exhibit surface, in a
vacuum chamber, to visualize latent fingerprints or touch marks.

42
Q

One advantage of footwear evidence

A

Uniqueness of the
footwear impression
caused by wear &
damage.

43
Q

Common methods of preserving impressions

A

Photography
3D Casting
Electrostatic or Gel Lift
Chemical Enhancement

44
Q

What do people generally remember in learning activities

A

90% of what they do
70% of what they write and say
50% of what they see and hear

45
Q

VR

A

Virtual Reality

A computer-generated artificial Immersive Environment experienced through sensory stimuli (primarily sights and sounds), in which one’s actions may affect what happens in the environment

46
Q

In training, the effectiveness of VR is a direct function
of the

A

Fidelity of its immersive environment

47
Q

Fidelity

A

To the visuals of the actual situation (how realistic are the representations),

To the task (how accurately is the task
modelled and presented), and

To the cognitive path (how closely do the mental processes experienced and retained reflect the real-world process)

48
Q

3 fidelity types

A

Perceptual
Feedback
Emotional

49
Q

Perceptual fidelity

A

Virtual interactions that closely mimic the physical world activate the same neural pathways in the brain. I.e.
“muscle memory”

50
Q

Feedback Fidelity

A

In VR, learners make decisions just as they would in the real world, and depending on the level of engagement,
these decisions can have a direct and immediate positive or negative
impact

51
Q

Emotional fidelity

A

VR can invoke a sense of presence that creates real emotional and empathic responses. These sensory stimulations
trigger the brain in much the same way it reacts to actual situations
(whether joy, fear or surprise) to release endorphins, serotonin,
and/or dopamine.

52
Q

What generates presence in VR

A

Agency along with the immersive environment generates presence

53
Q

What determines the success of the training process of VR

A

Engagement when combined with Fidelity, determines the Success of the
training process.

54
Q

3DoF VR

A

3 degrees of freedom

VR headsets with 3DoF only have rotational control (yaw, pitch, roll).

An analogy is a subject on a tour bus who can look around but can not interact with the environment or dictate where to go.

55
Q

6DoF VR

A

VR headsets with 6DoF have both rotational and translation control (vertical, lateral, forward/back).

Subjects using a 6DoF system have control over interacting with the scenario to enhance the experience

56
Q

The 5 W’s of VR training

A

Who
What
Where
When
Why

57
Q

DICE Scenarios

A

Dangerous
Impossible
Counter productive
Expensive

58
Q

7 rules of the metaverse

A

Rule #1. There is only one Metaverse.
Rule #2: The Metaverse is for everyone.
Rule #3: Nobody controls the Metaverse.
Rule #4: The Metaverse is open.
Rule #5: The Metaverse is hardware-independent.
Rule #6: The Metaverse is a Network. Rule #7: The Metaverse is the Internet.

58
Q

What was the brand Meta before it was the metaverse

A

Facebook

59
Q

What is the metaverse

A

A massively scaled and interoperable network of real-time 3d virtual worlds which can be experienced synchronously by a near unlimited number of users each with a sense of presence and persistent data (identity, history, entitlements, obligations, possessions and access to funds)

60
Q

What is the metaverse made up of

A

XR
AI
Blockchain

61
Q

What is source exclusion

A

Source exclusion is reached when the examiner’s opinion, considering the observed data, the probability that the two impressions came from the same source is considered negligible.

62
Q

What does LiDAR stand for

A

Light Detection and ranging

63
Q

What is the primary focus of UAV and anthropological collaborations

A

skeletal analysis and field recovery

64
Q

Surface enhanced raman spectroscopy (SERS) utilizes which type of nanoparticles for enhancing raman signal of fingerprint residues?

A

Silver nanoparticles

65
Q

What are the primary challenges associated with the widespread adoption of nanotechnology based techniques in fingerprint analysis?

A

Standardization, scalability, and cost-effectiveness

66
Q

What aspect of NeRF technology often outperforms other imaging technologies like photogrammetry?

A

Accuracy of reconstructions

67
Q

What is the primary focus of NeRF technology during the training phase?

A

Analyzing input images captured from different viewpoints

68
Q

What potential ethical concern arises from the use of NeRF technology in crime scene reconstruction, specifically in the context of manipulating facial features in videos?

A

Deep fakes

69
Q

One of the best predictors of general recidivism and antisocial behaviour is

A

Age

70
Q

How do we conduct tests to determine toxicity of nanoparticles?

A

Using model organisms

71
Q

The blank of AI within digital forensics is what some may call “smart forensics”

A

Automatism