DeepMind | Product Presentation Deck | 55 slides

DeepMind · 2019-03
arc beats above · slides in the middle · loops below · scroll → 3 LOOPS
SETUP TENSION ANALYSIS EVIDENCE RESOLUTION APPENDIX
HOVER FOR DETAILS · CLICK A SLIDE FOR FULLSCREEN · STEP 2
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Deck intelligence map

1
coverage by narrative range · generated from this deck JSON
Narrative range 55 total
Metadata
Components
Metrics
Tools
Frameworks
Beats
Loops
Whole deck 55 slides 100% 55/55 slides 100% 55/55 slides · 226 hits
0/55 slides
47.3% 26/55 slides 29.1% 16/55 slides
0/55 slides
50.9% 28/55 slides

Slide inventory

55
every slide · same image gating as the playbook
01
Slide 1
front_matter
02
compare_peers
Open slide detailLoop · Pattern Hunter
03
The slide uses a high-contrast black background with white text and imagery, typical of a film promotional deck.front_matter
Open slide detailLoop · Pattern Hunter
04
The slide uses a high-contrast, metaphorical image of a chess piece to represent the subject matter.front_matter
Open slide detailLoop · Pattern Hunter
05
The slide uses a process flow to illustrate the progression from human-dependent learning to self-learning and generalized game playing.present_framework
Open slide detailLoop · Pattern Hunter
06
The background contains faint, semi-transparent text related to chess rules.establish_context
Open slide detailLoop · Pattern Hunter
07
The slide uses a famous historical image as a visual anchor for a presentation about AI or technological advancement.establish_context
Open slide detailLoop · Pattern Hunter
08
The slide lists specific technical implementations for board representation, search, transposition tables, move ordering, selectivity, evaluation, and endgame tpresent_framework
Open slide detailLoop · Pattern Hunter
09
The slide uses a central callout to highlight the core learning and search paradigm, surrounded by technical sub-components.present_framework
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10
The slide depicts a continuous improvement cycle (flywheel) where self-play generates synthetic training data to update the neural networks.present_framework
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11
The slide uses donut charts to show game outcomes and a line chart to show performance convergence over training steps.analyze_data
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12
The slide uses line charts to demonstrate learning curves and time-to-performance milestones.summarize
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13
The slide uses a horizontal axis to represent search intensity, with AlphaZero positioned between human intuition and brute-force engines.compare_peers
Open slide detailLoop · Pattern Hunter
14
The slide uses a famous chess position to contrast traditional engine evaluation (material) with AlphaZero's positional understanding (mobility).illustrate_case
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15
The slide highlights the authors' credentials and the scope of the book's research (2,000 games, 7 themes).illustrate_case
Open slide detailLoop · Pattern Hunter
16
The slide features a high-quality portrait of Garry Kasparov holding a chess piece, reinforcing the authority of the quote.establish_context
17
front_matter
18
The slide uses a high-contrast blue background with text on the left and a space-themed illustration on the right.frame_situation
19
The slide uses a split-screen comparison format to contrast the benefits of the platform with the technical difficulties it poses for AI development.frame_problem
20
The slide uses a visual process flow with imagery from StarCraft II to represent each step.plan_implementation
21
The diagram uses a standard flow-chart style to represent machine learning model components.present_framework
22
The slide depicts a complex machine learning pipeline involving agent iterations, neural network training, and matchmaking.present_framework
23
This is a visualization of AI training progress in StarCraft II, specifically showing the evolution of unit composition strategies.analyze_data
24
The slide uses a split-screen layout to introduce two individuals.introduce_nominees
25
The chart uses a dual-axis approach where the left side represents pre-training and the right side represents the training league. Skill tiers are mapped to MMRanalyze_data
26
summarize
27
The slide uses a non-linear, connected path to show the evolution of AI capabilities.present_framework
28
transition
29
diagnose_problem
30
The image of origami birds emerging from a geometric sphere serves as a metaphor for AI evolving beyond its initial 'gaming' container.transition
31
The slide uses a 2x2 grid layout to categorize applications.present_framework
32
The slide uses a simple vertical process flow to describe the problem, the intervention, and the outcome.present_solution
33
The chart uses a waterfall-bridge structure to show the incremental value added by three specific ML-driven improvements.quantify_opportunity
Open slide detailLoop · Before After
34
front_matter
Open slide detailLoop · Before After
35
The slide uses a numbered list format to define necessary conditions.present_framework
36
establish_context
37
The slide uses a 2x2 grid layout to showcase diverse applications of AI in scientific research.establish_context
38
front_matter
Open slide detailLoop · The Reveal
39
The slide uses a simple process flow to define a biological concept.establish_context
Open slide detailLoop · The Reveal
40
The slide uses a side-by-side comparison layout to illustrate biological mechanisms.establish_context
Open slide detailLoop · The Reveal
41
The slide uses a triptych layout to categorize the company's core capabilities or focus areas.present_framework
Open slide detailLoop · The Reveal
42
The slide depicts a machine learning architecture pipeline, specifically referencing protein structure prediction (likely AlphaFold-related).present_framework
Open slide detailLoop · The Reveal
43
The diagram shows a feedback loop where angle scores are optimized via gradient descent to minimize a total score, resulting in a predicted structure.present_framework
Open slide detailLoop · The Reveal
44
This is a standard AlphaFold or PDB-style protein structure visualization.other
Open slide detailLoop · The Reveal
45
The slide uses a metaphor ('Olympics') to frame the competition's significance.establish_context
Open slide detailLoop · The Reveal
46
The slide uses color-coding (green for ground truth, blue for predicted) to visually demonstrate the accuracy of the model.illustrate_case
Open slide detailLoop · The Reveal
47
The chart uses a purple arrow to highlight the top-performing team (G043).analyze_data
Open slide detailLoop · The Reveal
48
The chart shows a clear performance gap between AlphaFold (purple line) and other competitors (orange lines).compare_peers
Open slide detailLoop · The Reveal
49
The image is a 3D protein structure model.frame_problem
Open slide detailLoop · The Reveal
50
transition
51
The background is a library, reinforcing the theme of information management.frame_problem
52
Includes logos for DeepMind Ethics & Society and Partnership on AI.summarize
53
The slide uses a famous Feynman quote to bridge the gap between AI development and human cognition.establish_context
54
This is an acknowledgments slide listing team members for specific projects.other
55
closing_ask