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Study Notes 3rd Year > Trends Final > Flashcards

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
how many records does the AFIS database contain
4 million
25
What does AFIS do
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
26
Can fingerprints be the same
No two complete fingerprints have been found to be the same – Not even from the same person.
27
4 problems AI overcomes in the AFIS database
growth injury deviation quality of record
28
CPAP
Capture, process, analyze, present
29
M4
Multimodal mobility morphobot
29
How does laser scanning work
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
SLAM
Simultaneous Location and mapping
31
Nerf
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
Attention span
the average attention span of a gold fish is 9 seconds average attention span of a human is 8 seconds
33
hierarchy of attention
actions objects picture diagrams written word spoken word
34
transhumanism
the belief or theory that the human race can evolve beyond its current physical and mental limitations
35
First fully AI generated movie
Salt 2023
36
Two main DNA databases
National DNA databank Local DNA database at CFS
37
Positive outcomes of DNA evidence
Increased sensitivity of DNA analysis (smaller samples required). Faster results. Better interpretation of mixed profiles. Better results from difficult surfaces.
38
Challenges in DNA evidence
Issues regarding secondary and tertiary transfer of DNA. Increased issues with collection (cross contamination).
39
2 ways bias in fingerprinting can be avoided
Blind verification of comparison process. Controls on exposure to contextual information by fingerprint examiners.
40
Fingerprint development techniques
Chosen for surface: porous vs non-porous Chosen for fingerprint matrix: blood, sweat, dust Chosen for contrast / photography
41
What is VMD
Depositing very thin layers of metal on to an exhibit surface, in a vacuum chamber, to visualize latent fingerprints or touch marks.
42
One advantage of footwear evidence
Uniqueness of the footwear impression caused by wear & damage.
43
Common methods of preserving impressions
Photography 3D Casting Electrostatic or Gel Lift Chemical Enhancement
44
What do people generally remember in learning activities
90% of what they do 70% of what they write and say 50% of what they see and hear
45
VR
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
In training, the effectiveness of VR is a direct function of the
Fidelity of its immersive environment
47
Fidelity
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
3 fidelity types
Perceptual Feedback Emotional
49
Perceptual fidelity
Virtual interactions that closely mimic the physical world activate the same neural pathways in the brain. I.e. "muscle memory"
50
Feedback Fidelity
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
Emotional fidelity
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
What generates presence in VR
Agency along with the immersive environment generates presence
53
What determines the success of the training process of VR
Engagement when combined with Fidelity, determines the Success of the training process.
54
3DoF VR
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
6DoF VR
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
The 5 W's of VR training
Who What Where When Why
57
DICE Scenarios
Dangerous Impossible Counter productive Expensive
58
7 rules of the metaverse
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
What was the brand Meta before it was the metaverse
Facebook
59
What is the metaverse
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
What is the metaverse made up of
XR AI Blockchain
61
What is source exclusion
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
What does LiDAR stand for
Light Detection and ranging
63
What is the primary focus of UAV and anthropological collaborations
skeletal analysis and field recovery
64
Surface enhanced raman spectroscopy (SERS) utilizes which type of nanoparticles for enhancing raman signal of fingerprint residues?
Silver nanoparticles
65
What are the primary challenges associated with the widespread adoption of nanotechnology based techniques in fingerprint analysis?
Standardization, scalability, and cost-effectiveness
66
What aspect of NeRF technology often outperforms other imaging technologies like photogrammetry?
Accuracy of reconstructions
67
What is the primary focus of NeRF technology during the training phase?
Analyzing input images captured from different viewpoints
68
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?
Deep fakes
69
One of the best predictors of general recidivism and antisocial behaviour is
Age
70
How do we conduct tests to determine toxicity of nanoparticles?
Using model organisms
71
The *blank* of AI within digital forensics is what some may call “smart forensics”
Automatism

Study Notes 3rd Year (11 decks)

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