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ARK Invest Big Ideas 2026 PPT

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ARK Invest Big Ideas 2026 - Disruptive Innovation Platforms and Investment Opportunities

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Disruptive innovation
Artificial intelligence
AI infrastructure
Blockchain technology
Bitcoin

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描述

主要主题

ARK Invest Big Ideas 2026 - Disruptive Innovation Platforms and Investment Opportunities

主要优势

  • •Comprehensive analysis of 13 major innovation platforms reshaping the global economy
  • •Data-driven forecasts for technological convergence and market opportunities through 2030
  • •Detailed market sizing across AI, blockchain, robotics, energy storage, and multiomics sectors
  • •Investment framework identifying $28+ trillion in potential digital asset and innovation markets
  • •Provocative thesis predicting acceleration of global GDP growth from 3.1% to 7.3% annually

目标受众

  • •Institutional investors and asset managers
  • •Technology entrepreneurs and startup founders
  • •Corporate strategists and innovation leaders
  • •Policy makers and government officials
  • •Venture capital and private equity investors
  • •Business decision-makers across industries
  • •Academic researchers in technology and economics

使用场景

  • •Investment portfolio strategy and allocation decisions
  • •Technology trend analysis and market research
  • •Corporate innovation planning and R&D prioritization
  • •Startup pitch decks and business plan development
  • •Academic research on disruptive technologies
  • •Executive presentations on industry transformation
  • •Policy development for emerging technologies

独特价值主张

  • •10th annual edition establishing decade-long track record of innovation forecasting
  • •Convergence Network Strength metric quantifying technology interdependence (35% increase in 2025)
  • •Wright's Law-based cost decline projections across multiple sectors
  • •Provocative space-based AI compute infrastructure thesis
  • •Integration of five major platforms: AI, Public Blockchains, Robotics, Energy Storage, Multiomics
  • •Forecast of innovation platforms reaching 35% of global equity market cap by 2030

幻灯片页面 (110)

每张幻灯片页面的详细视图,包括布局、关键内容和视觉元素。

页面 1
Title Slide

Cover - BIG IDEAS 2026

内容

Title page for ARK Investment Management's 10th annual Big Ideas research report, emphasizing disruptive innovation themes

布局结构

Bold typography with 'BIG IDEAS 2026' as main title, disclaimer text at top, ARK branding

关键视觉元素

  • •Large typography for '2026'
  • •White background with clean design
  • •Legal disclaimer at top
  • •ARK Investment Management LLC branding
页面 2
Risk Framework

Risk Disclosure - Investing in Innovation

内容

Overview of key risks associated with disruptive innovation investments including rapid pace of change, uncertainty, regulatory hurdles, competitive landscape, and political/legal pressure

布局结构

Centered circular diagram with 'DISRUPTIVE INNOVATION' at center, risk factors radiating outward, source citation at bottom

关键视觉元素

  • •Circular diagram with interconnected risk factors
  • •Key risk categories highlighted
  • •Guidance bullets for risk mitigation
  • •Clean infographic design
页面 3
Table of Contents

Table of Contents

内容

Lists 13 Big Ideas with page numbers: The Great Acceleration (4), AI Infrastructure (19), AI Consumer OS (25), AI Productivity (32), Bitcoin (38), Tokenized Assets (45), DeFi Applications (52), Multiomics (58), Reusable Rockets (78), Robotics (83), Distributed Energy (90), Autonomous Vehicles (95), Autonomous Logistics (101)

布局结构

Two-column layout with Big Ideas titles on left and page numbers on right, introduction paragraph at top

关键视觉元素

  • •Clean numbered list
  • •Page number alignment
  • •Introduction text block
  • •Simple, navigable structure
页面 4
Chapter Divider

The Great Acceleration - Introduction

内容

Chapter opener explaining how AI is the central dynamo accelerating five major innovation platforms and igniting macroeconomic growth inflection. Author: Brett Winton, Chief Futurist

布局结构

Large title with subtitle, author credit, minimal text on clean background

关键视觉元素

  • •Bold chapter title
  • •Descriptive subtitle
  • •Author name and title
  • •Clean white space
页面 5
Framework Visualization

Technological Convergence Is Accelerating

内容

Complex diagram showing five major innovation platforms (AI, Public Blockchains, Robotics, Energy Storage, Multiomics) with their component technologies and interdependencies. Examples of convergence include reusable rockets enabling AI infrastructure and multiomics data powering precision therapies

布局结构

Five-column framework with technology stacks, interconnection lines showing relationships, explanatory text boxes

关键视觉元素

  • •Five vertical technology stacks
  • •Interconnecting arrows showing relationships
  • •Color coding by platform
  • •Example callout boxes
页面 6
Data Visualization

Technology Platform Growth Rates Are Accelerating

内容

Two charts showing: 1) AI's dominant role as technological catalyst with increasing importance of robotics, 2) Convergence Network Strength increased 35% in 2025, growing from ~24 to ~32 on 100-point scale. Details major developments in cross-platform catalysis

布局结构

Two side-by-side bar charts with explanatory bullet points, horizontal layout

关键视觉元素

  • •Grouped bar charts comparing 2023-2025
  • •Color-coded platforms
  • •Percentage increase indicators (+20%, +35%)
  • •Detailed source notes
页面 7
Market Opportunity Analysis

Convergence Should Lead To Major Increases In Demand

内容

Analysis of reusable rocket demand driven by AI compute needs. Shows potential 60x increase in demand for space-based AI infrastructure. Compares terrestrial vs space compute costs at different launch price points

布局结构

Two charts: logarithmic scale bar chart for upmass demand, horizontal bar chart comparing cost ratios

关键视觉元素

  • •Logarithmic scale visualization
  • •Cost comparison bars
  • •~60x and ~11x multiplier callouts
  • •Detailed technical notes
页面 8
Historical Context + Forecast

Unprecedented Technology Investment Cycle

内容

Historical chart of US fixed asset investment as percent of GDP from 1852-2030, showing major technology waves (railroad, telephony, electrification, cars, computers) and forecasting AI-driven investment surge through 2030

布局结构

Line chart spanning 178 years with technology wave annotations and forward projections

关键视觉元素

  • •Multi-generational timeline
  • •Technology wave annotations
  • •Forecast extensions
  • •Color-coded investment categories
页面 9
Conceptual Framework

Disruptive Technologies Catalyze Growth Multiple Ways

内容

Framework showing four ways disruptive tech drives growth: accelerates capital formation, increases returns on deployed capital, transforms non-market activity into GDP, frees human potential. Uses robotaxis as example

布局结构

Four-column framework with robotaxis case study at bottom showing specific mechanisms

关键视觉元素

  • •Four-pillar structure
  • •Detailed robotaxi example
  • •Flow diagram showing causation
  • •Clean iconography
页面 10
Economic Impact Analysis

Humanoid Robots GDP Impact Case Study

内容

Detailed analysis of how household humanoid robots could impact GDP. Currently only $2,600 of ~$68,000 home upkeep value flows to GDP. Single humanoid could add $62,000 per household, potentially boosting US GDP by 20% ($6 trillion)

布局结构

Two side-by-side bar charts comparing current vs robot-enabled GDP impact

关键视觉元素

  • •Stacked bar charts
  • •GDP inclusion indicators
  • •Dollar value callouts
  • •Consumer surplus visualization
页面 11
Macro Forecast

Step Change In Real GDP Growth

内容

Logarithmic chart showing global real GDP growth from 100,000 BC to 2030. ARK forecasts 7.3% annual growth vs IMF's 3.1%, driven by five innovation platforms and capital investment adding 1.9 percentage points

布局结构

Logarithmic timeline chart with historical data points and diverging forecasts

关键视觉元素

  • •Logarithmic scale
  • •Historical growth rate markers
  • •Diverging forecast lines
  • •Percentage growth annotations
页面 12
Technology Assessment

Quantum Computing Timeline

内容

Analysis explaining why quantum computing won't be disruptive for 20-40 years. Shows distance from cracking RSA 2048 under different progress scenarios. Even with Moore's Law pace, useful quantum computing not until 2040s-2060s

布局结构

Area chart showing progress scenarios with explanatory text box

关键视觉元素

  • •Multi-scenario progress curves
  • •Timeline markers (2044, 2054, 2063)
  • •Percentage scale (0-100%)
  • •Scenario definitions sidebar
页面 13
Market Forecast

Disruptive Technologies To Dominate Global Markets

内容

Chart showing innovation share of global equity market cap growing from ~20% today to 35% by 2030. Compares nominal GDP growth vs innovation and non-innovation market cap growth rates. Historical context from 1870 railroad market dominance

布局结构

Area chart with historical data and forward projections, growth rate comparison table

关键视觉元素

  • •Stacked area chart
  • •Growth rate comparison table
  • •Historical railroad analogy
  • •Dollar value projections to $300T
页面 14
Platform Introduction

Artificial Intelligence Platform Overview

内容

Summary of AI innovation platform describing computational systems evolving with data, neural networks, next-gen cloud infrastructure, and intelligent devices. Emphasizes AI's transformative impact across all sectors

布局结构

Text-focused slide with centered content, white space, minimal graphics

关键视觉元素

  • •Centered text block
  • •Key terminology highlighted
  • •Clean typography
  • •Source citation
页面 15
Platform Introduction

Energy Storage Platform Overview

内容

Description of battery technology enabling autonomous mobility, electric drivetrains, flying taxis, and distributed energy generation. Emphasizes cost decline impacts and integration with AI data center power demands

布局结构

Text-focused slide with centered content describing platform components

关键视觉元素

  • •Centered text block
  • •Technology category mentions
  • •Clean layout
  • •Platform relationships described
页面 16
Platform Introduction

Multiomics Platform Overview

内容

Explains multiomics technologies (DNA, RNA, protein data), programmable biology, precision therapies, and AI-powered autonomous labs collapsing drug discovery costs. Mentions pan-cancer blood tests and novel biological constructs

布局结构

Text-focused slide describing multiomics ecosystem

关键视觉元素

  • •Centered content
  • •Technology terminology
  • •Application examples
  • •Future vision described
页面 17
Platform Introduction

Public Blockchains Platform Overview

内容

Describes migration of money and contracts onto public blockchains, cryptocurrencies, stablecoins, smart contracts, and digital wallets. Emphasizes transparency, reduced capital controls, and AI-driven purchasing agents

布局结构

Text-focused platform description

关键视觉元素

  • •Centered text
  • •Key technology terms
  • •Use case implications
  • •Corporate structure questions raised
页面 18
Platform Introduction

Robotics Platform Overview

内容

Overview of humanoid robots, specialized robots, and reusable rockets. Describes AI-enabled automation across manufacturing, logistics, healthcare, and space-based compute infrastructure unconstrained by terrestrial limitations

布局结构

Text-focused robotics platform summary

关键视觉元素

  • •Centered content block
  • •Robot categories defined
  • •Application areas listed
  • •Cost reduction themes
页面 19
Chapter Divider

AI Infrastructure - Chapter Opener

内容

Chapter introduction defining next generation of cloud infrastructure. Authors: Frank Downing (Director of Research, AI & Cloud) and Jozef Soja (Research Analyst, AI & Cloud)

布局结构

Chapter title with subtitle and author credits

关键视觉元素

  • •Large chapter title
  • •Author names and titles
  • •Clean white space
  • •Simple design
页面 20
Market Dynamics

AI Demand Growing As Inference Costs Collapse

内容

Two charts showing: 1) Inference costs dropped 99%+ in past year (from $28.90 to $0.10 per million tokens), 2) OpenRouter demand increased 25-fold since December 2024 from ~250B to ~7,000B tokens

布局结构

Two charts side-by-side: logarithmic cost decline and exponential demand growth

关键视觉元素

  • •Logarithmic price chart
  • •Exponential growth curve
  • •Model name annotations
  • •Billion-scale y-axis
页面 21
Investment Analysis

Data Center Systems Growth Acceleration

内容

Chart showing data center systems investment accelerated from 5% CAGR (2012-2023) to 29% CAGR (ChatGPT moment onward). Annual investment reached ~$500B in 2025, up 2.5x from 2012-2023 average

布局结构

Bar chart with CAGR annotations and trend line

关键视觉元素

  • •Annual bar chart
  • •CAGR annotations
  • •Trend line showing inflection
  • •2026E forecast bar
页面 22
Valuation Context

Tech Capex vs Valuations Comparison

内容

Two charts comparing current tech boom to dot-com era: 1) Capex as % of GDP matches 1998 levels, 2) P/E ratios for Mag 6 (~45x) well below dot-com peak (~115x for Cisco/Oracle/Nokia/Intel/Microsoft)

布局结构

Two side-by-side charts with historical comparisons

关键视觉元素

  • •Time series line charts
  • •Dot-com bubble comparison
  • •P/E ratio scale
  • •Company groupings
页面 23
Competitive Analysis

Nvidia Facing More Competition

内容

Performance comparison showing AMD catching up to Nvidia in small model inference (MI355X: 38 vs Nvidia B200: 32 tokens per TCO dollar). Large model performance still Nvidia-dominated. Detailed GPU specifications table included

布局结构

Two bar charts comparing performance, specifications table below

关键视觉元素

  • •Side-by-side bar comparisons
  • •GPU specifications table
  • •Nvidia vs AMD color coding
  • •Performance metrics
页面 24
Market Forecast

Sustainable Infrastructure Growth Forecast

内容

Forecast showing data center systems investment reaching $1.4T by 2030 (30% CAGR). Market share shift from traditional to accelerated servers (GPUs and ASICs). ASICs expected to gain significant share

布局结构

Stacked bar chart and market share area chart

关键视觉元素

  • •Stacked investment bars
  • •Market share area chart
  • •30% CAGR annotation
  • •Three compute categories
页面 25
Chapter Divider

AI Consumer Operating System - Chapter Opener

内容

Chapter introduction on transforming search, discovery, transactions, and e-commerce economics. Authors: Nicholas Grous (Director) and Varshika Prasanna (Research Associate)

布局结构

Chapter title with authors

关键视觉元素

  • •Chapter title typography
  • •Author credits
  • •White space design
页面 26
Historical Framework

Four Eras of Digital Interactivity

内容

Framework showing evolution: Command Era (1980-1994), Web Era (1995-2006), Mobile Era (2007-2022), Agentic Era (2022+). Chart shows AI adoption outpacing internet adoption (~27% penetration in 3 years vs ~7% for internet)

布局结构

Timeline framework with adoption comparison chart

关键视觉元素

  • •Four-era timeline
  • •Adoption curve comparison
  • •Interface type descriptions
  • •Percentage penetration chart
页面 27
Process Evolution

AI Compressing Purchase Journey Time

内容

Timeline showing transaction time compression: Pre-internet (60 min) → Web (10 min) → Mobile (5 min) → Agentic AI (1.5 min). Notes 95% of consumer journey occurs before purchase

布局结构

Line graph showing time compression across eras with purchase funnel stages

关键视觉元素

  • •Declining time curve
  • •Era markers
  • •Purchase funnel stages
  • •Time annotations
页面 28
Technical Architecture

Agent Protocols Transforming Commerce

内容

Diagram showing agentic enablers (MCP, ACP, A2A, AP2, UCP) connecting AI platforms (ChatGPT, Gemini, Claude) to retailers through standardized protocols, contrasting with internet era's complex disconnected integrations

布局结构

Side-by-side comparison: internet era complexity vs agentic era simplicity

关键视觉元素

  • •Protocol flow diagram
  • •Platform logos
  • •Before/after comparison
  • •Protocol abbreviations explained
页面 29
Market Forecast

AI-Facilitated Spend Forecast

内容

Projection of AI-facilitated online spend growing from $0.1T (2%) in 2025 to $8T (25%) in 2030. Includes table comparing traditional marketplaces vs AI agents across discovery, engagement, decision-making, and purchasing

布局结构

Area chart with percentage overlay and comparison table

关键视觉元素

  • •Stacked area chart
  • •Percentage line overlay
  • •Comparison table
  • •Trillions scale
页面 30
Market Transition

AI Search Taking Share

内容

Two charts showing: 1) AI search traffic share growing from 10% (2025) to 65% (2030), 2) AI search ad spend reaching ~$300B by 2030 with ~50% CAGR while traditional search stagnates

布局结构

Two area charts showing market share shift and revenue growth

关键视觉元素

  • •Stacked area charts
  • •Percentage scale
  • •Dollar value projections
  • •Traditional vs AI coloring
页面 31
Revenue Forecast

AI Consumer Revenue Forecast

内容

Forecast showing AI consumer revenue growing from ~$20B (2024) to ~$900B (2030) at ~105% CAGR. Lead generation and advertising drive growth, overwhelming subscription revenue contributions

布局结构

Stacked area chart showing three revenue streams

关键视觉元素

  • •Stacked area chart
  • •Three revenue categories
  • •~105% CAGR noted
  • •Billions scale to $1T
页面 32
Chapter Divider

AI Productivity - Chapter Opener

内容

Chapter on scaling digital intelligence. Authors: Frank Downing and Jozef Soja

布局结构

Simple chapter divider

关键视觉元素

  • •Chapter title
  • •Author names
页面 33
Performance Metrics

AI Agent Performance Improving

内容

Chart showing AI agent task duration capability increased 5x from 6 minutes to 31 minutes at 80% success rate during 2025. ChatGPT Plus subscriber payback period analysis showing break-even in ~0.5 day

布局结构

Line chart with exponential growth and payback calculation box

关键视觉元素

  • •Exponential curve
  • •Time duration scale
  • •ROI calculation box
  • •Break-even callout
页面 34
Cost Analysis

Cost of Intelligence Collapsing

内容

Two charts showing: 1) Software development costs fell 91% (April to December 2025) from $3.50 to $0.32 per million tokens, 2) Annualized cost declines of 93-99.7% across different benchmarks

布局结构

Logarithmic cost chart and horizontal bar chart of decline rates

关键视觉元素

  • •Logarithmic scale
  • •Cost decline curve
  • •Percentage bars
  • •Benchmark categories
页面 35
Competitive Landscape

US-China AI Competition

内容

Chart showing Chinese models trailing US by only 6 months in performance. Production capacity comparison: TSMC produces 38x more compute than SMIC (~135B vs ~3.5B transistors daily)

布局结构

Scatter plot of model performance over time and production capacity comparison

关键视觉元素

  • •Time series scatter plot
  • •US vs China color coding
  • •Production capacity callout (38x)
  • •Model name annotations
页面 36
Market Sizing

AI-Native Revenue Growing

内容

Charts showing general purpose AI revenue (OpenAI: $20B, Anthropic: $9B in 2025) and specialized startups (Cursor: $1B ARR, Harvey, OpenEvidence, Sierra: $100M ARR each) growing rapidly at 250-850% CAGR

布局结构

Two charts: bar chart for general purpose and callout boxes for specialized startups

关键视觉元素

  • •Grouped bar charts
  • •CAGR annotations
  • •Startup callout boxes
  • •Vertical categorization
页面 37
Opportunity Sizing

Multi-Trillion Dollar Productivity Opportunity

内容

Forecast showing global software spend could grow 19-56% annually (vs 14% historical) depending on AI adoption scenario. Three scenarios ranging from $3.4T to $13T by 2030, unlocking $22T-$117T in value

布局结构

Stacked bar chart showing development phases and three scenario comparisons

关键视觉元素

  • •Development phase bars
  • •Three scenario columns
  • •CAGR annotations (19-56%)
  • •Value unlocked metrics
页面 38
Chapter Divider

Bitcoin - Chapter Opener

内容

Chapter on leading movement into new asset class. Author: David Puell (Research Trading Analyst & Associate PM)

布局结构

Chapter divider

关键视觉元素

  • •Chapter title
  • •Author credit
页面 39
Market Timeline

Bitcoin Maturing as Institutional Asset

内容

Timeline of 2025 bitcoin institutional developments including Trump's strategic reserve, Metaplanet's $5.4B treasury, SEC's generic listing standards, Fidelity Crypto IRA, Texas strategic reserve, Wisconsin pension fund allocation

布局结构

Line chart of bitcoin price with timeline annotations of major events

关键视觉元素

  • •Price line chart
  • •Event annotations
  • •Timeline markers
  • •Price range $50K-$150K
页面 40
Ownership Analysis

ETFs and Public Companies Hold 12% of Bitcoin

内容

Chart showing US ETF and public company bitcoin holdings grew from 8.7% to 12% of total supply in 2025. ETF balances increased 19.7%, public company holdings grew 73%

布局结构

Dual-axis chart with absolute numbers and percentage

关键视觉元素

  • •Stacked area chart
  • •Percentage overlay line
  • •Monthly timeline
  • •Two y-axes
页面 41
Performance Analysis

Bitcoin's Risk-Adjusted Returns Lead Crypto

内容

Charts showing bitcoin's Sharpe ratio surpassed ETH, SOL, and CoinDesk 10 average for most of 2025. Average yearly Sharpe ratio comparisons across different timeframes (since Nov 2022, 2024-2025, 2025)

布局结构

Line chart and grouped bar chart comparing Sharpe ratios

关键视觉元素

  • •Rolling Sharpe ratio line chart
  • •Grouped bar comparison
  • •Multiple timeframe analysis
  • •Four asset comparison
页面 42
Volatility Analysis

Bitcoin Drawdowns Were Muted in 2025

内容

Chart showing 2025 had shallowest average drawdowns in bitcoin history across 5-year, 3-year, 1-year, and 3-month horizons, demonstrating reduced volatility as safe-haven asset

布局结构

Multiple time series showing drawdown patterns

关键视觉元素

  • •Multiple time series
  • •Drawdown visualization
  • •Historical comparison
  • •Dot markers for 2025 records
页面 43
Methodology Update

Bitcoin Forecast Assumptions Changed

内容

Side-by-side comparison of 2024 vs 2025 assumptions for bitcoin 2030 forecast. Major changes: Digital Gold TAM increased 37% (gold up 64.5%), Emerging Market penetration decreased 80% (due to stablecoin adoption)

布局结构

Two side-by-side tables comparing TAM and penetration assumptions

关键视觉元素

  • •Comparison tables
  • •Bear/Base/Bull scenarios
  • •Six forecast components
  • •Penetration rate changes
页面 44
Market Forecast

Digital Assets Could Reach $28T by 2030

内容

Forecast showing digital asset market cap growing at ~61% CAGR to $28T by 2030. Bitcoin expected to dominate at 70% (~$16T at 63% CAGR), smart contracts reaching ~$6T (54% CAGR)

布局结构

Stacked bar chart with detailed breakdown bullet points

关键视觉元素

  • •Stacked bar comparison (2025 vs 2030)
  • •Two asset categories
  • •~61% CAGR callout
  • •Trillions scale
页面 45
Chapter Divider

Tokenized Assets - Chapter Opener

内容

Chapter on moving trillions onto blockchains. Authors: Lorenzo Valente (Director) and Raye Hadi (Research Associate)

布局结构

Chapter divider

关键视觉元素

  • •Chapter title
  • •Author credits
页面 46
Regulatory Impact Analysis

GENIUS Act Impact on Stablecoins

内容

Timeline of 2025 stablecoin developments following GENIUS Act: Circle IPO/Layer 1, Wyoming's FRNT, Stripe's Tempo, Tether's Plasma, major bank stablecoin launches. Weekly transaction volume chart showing surge to $1.2T

布局结构

Line chart with timeline annotations of major events

关键视觉元素

  • •Transaction volume line chart
  • •Event timeline markers
  • •Key announcements annotated
  • •Billions scale
页面 47
Market Comparison

Stablecoin Volumes Dwarf Legacy Payments

内容

Chart showing stablecoin adjusted transaction volume reached $3.5T (30-day average) in December 2025, 2.3x larger than Visa + PayPal + Remittances combined. USDC dominates at ~60% share, USDT ~35%

布局结构

Logarithmic line chart comparing payment systems over time

关键视觉元素

  • •Logarithmic scale
  • •Multiple payment system lines
  • •Stablecoin market share callout
  • •Trillions scale
页面 48
Asset Growth Analysis

RWA Tokenization Tripled to $19B

内容

Chart showing tokenized real-world assets grew 208% to $18.9B in 2025. Led by US Treasuries ($9B including BlackRock's $1.7B BUIDL), commodities ($4.1B with Tether/Paxos gold dominating), and institutional funds

布局结构

Stacked area chart showing RWA categories over time

关键视觉元素

  • •Stacked area chart
  • •Multiple asset categories
  • •Monthly timeline
  • •Billions scale
页面 49
Blockchain Comparison

Ethereum Leads Blockchain Asset Storage

内容

Bar chart showing assets on major blockchains. Ethereum dominates with $400B+. Stablecoins and top 50 tokens account for ~90% on most chains. Solana unique with ~21% in memecoins

布局结构

Horizontal bar chart showing asset composition by blockchain

关键视觉元素

  • •Horizontal stacked bars
  • •Eight blockchains compared
  • •Asset category breakdown
  • •Billions scale
页面 50
Market Forecast

Tokenized Assets Could Exceed $11T by 2030

内容

Forecast showing tokenized assets growing from $19B to $11T (~1.38% of financial assets) by 2030. Bank deposits and public equities expected to see greater on-chain migration than sovereign debt

布局结构

Stacked area chart with category projections

关键视觉元素

  • •Stacked area forecast
  • •Multiple asset categories
  • •2023-2030 projection
  • •Trillions scale
页面 51
Infrastructure Development

Companies Launching Blockchain Infrastructure

内容

Analysis of traditional companies launching on-chain infrastructure: Circle (Arc), Coinbase (Base, cbBTC), Kraken (Ink), etc. Charts showing cbBTC bitcoin-backed loans growth and Robinhood tokenized equities reaching $15M market cap

布局结构

Two charts showing cbBTC growth and tokenized equity breakdown

关键视觉元素

  • •Dual-axis chart for cbBTC
  • •Stacked area for tokenized stocks
  • •Company examples listed
  • •Market cap scales
页面 52
Chapter Divider

DeFi Applications - Chapter Opener

内容

Chapter on designing engines of digital asset growth. Authors: Lorenzo Valente and Raye Hadi

布局结构

Chapter divider

关键视觉元素

  • •Chapter title
  • •Author credits
页面 53
Market Dynamics

Value Capture Shifted to Applications

内容

Charts showing application revenue hit $3.8B in 2025 (January alone: $800M+ record). App/network revenue ratio increased. 70 applications generate $1M+ MRR. Led by Hyperliquid, Pump.fun, Pancakeswap

布局结构

Combined bar and line chart showing revenue and ratio

关键视觉元素

  • •Revenue bars
  • •App/network ratio line
  • •Dual y-axes
  • •Monthly timeline
页面 54
Asset Comparison

DeFi Catching Up to Fintechs in Assets

内容

Bar chart comparing assets on platform: Traditional fintechs (Coinbase $500B, Robinhood $157B) vs DeFi protocols (Tether $160B, Aave $67B). Top 50 DeFi platforms have $1B+ TVL, top 12 have $5B+

布局结构

Horizontal bar chart comparing platforms

关键视觉元素

  • •Horizontal bars
  • •Fintech vs DeFi color coding
  • •Billions scale
  • •Platform categorization
页面 55
Efficiency Analysis

Most Revenue Efficient Companies

内容

Bar chart showing revenue per employee: Hyperliquid leads at ~$60M+, followed by Tether (~$55M). Crypto companies dominate top rankings ahead of OnlyFans, Valve, Nvidia. Highlights double-digit headcount powering world-class revenues

布局结构

Horizontal bar chart ranking companies by efficiency

关键视觉元素

  • •Revenue per employee bars
  • •Crypto vs other company distinction
  • •Millions scale
  • •Top companies highlighted
页面 56
Market Share Analysis

DeFi Derivatives Taking Share from Binance

内容

Charts showing Hyperliquid revenue growing to $100M+ monthly. Market share analysis shows on-chain exchanges (led by Hyperliquid) taking significant share from Binance in perpetual futures market

布局结构

Stacked area chart and area share chart

关键视觉元素

  • •Revenue growth bars
  • •Market share area chart
  • •Binance vs on-chain comparison
  • •Multiple time series
页面 57
Valuation Framework

Layer 1s as Monetary Assets

内容

Analysis showing 90%+ of Ethereum and Solana market value attributed to monetary premium rather than network revenue (using 50x revenue multiple). Only few digital assets will retain monetary properties

布局结构

Stacked bar chart showing value decomposition

关键视觉元素

  • •Stacked percentage bars
  • •Three assets compared
  • •Implied value vs monetary premium
  • •Percentage scale
页面 58
Chapter Divider

Multiomics - Chapter Opener

内容

Chapter on AI-native biology catalyzing healthcare shifts. Authors: Shea Wihlborg PhD and Brett Winton. Notes five educational subsections ahead

布局结构

Chapter divider with structural note

关键视觉元素

  • •Chapter title
  • •Author credits
  • •Subsection note
页面 59
Section Divider

Multiomics Section 1 - Defining Multiomics

内容

Section divider

布局结构

Simple section header

关键视觉元素

  • •Section title
  • •Minimal design
页面 60
Conceptual Framework

Five Biological Layers Shape Phenotypes

内容

Framework showing multiomics layers: Genomics (DNA blueprint), Epigenomics (gene expression regulation), Transcriptomics (RNA transcripts), Proteomics (proteins), Metabolomics (metabolites). Together shape observable phenotypes

布局结构

Linear flow diagram showing biological information flow

关键视觉元素

  • •Five-layer flow diagram
  • •DNA to metabolites progression
  • •Phenotype outcome arrow
  • •Layer descriptions
页面 61
Market Landscape

Sample Companies Across Biological Layers

内容

Table mapping companies to biological layers: DNA (Illumina, CRISPR Therapeutics), Epigenome (10X Genomics, Ipsen), RNA (Tempus, Ionis), Protein (Quantum Si, Nurix), Metabolites (908 Devices, Ultragenyx)

布局结构

Five-column table with company examples

关键视觉元素

  • •Five-column layout
  • •Company logos/names
  • •Layer categorization
  • •Brief descriptions
页面 62
System Dynamics

Multiomics-AI Flywheel

内容

Circular flywheel diagram showing how multiomics generates data → AI creates insights → better tools/tests/cures → more data. Includes company examples: Multiomics tools (Illumina, PacBio), Diagnostics (Guardant, Natera), AI drugs (Absci, Generate Bio), Cures (Beam, CRISPR Tx)

布局结构

Circular flywheel with four segments and company callouts

关键视觉元素

  • •Circular flywheel diagram
  • •Four key stages
  • •Company examples
  • •Performance metrics
页面 63
Section Divider

Multiomics Section 2 - Data Growth & Cost Decline

内容

Section divider

布局结构

Section header

关键视觉元素

  • •Section title
页面 64
Cost Analysis

Multiomics Testing Costs Falling

内容

Two charts: 1) Historical genome sequencing cost decline from $100M+ (2001) to ~$100 (2024) following Wright's Law, 2) Forecast of 10-fold cost declines by 2030 across genome, epigenome, and structural variant testing

布局结构

Logarithmic historical chart and forecast bar comparison

关键视觉元素

  • •Logarithmic scale
  • •Cost decline curve
  • •2015/2020/2025 comparison bars
  • •10x reduction forecast
页面 65
Data Growth Forecast

Explosion in Molecular Test Data

内容

Charts showing molecular test volumes growing from ~2M (2020) to ~7M (2025E) to ~30M (2030E), generating data tokens increasing from ~20T to ~200T by 2030 - exceeding frontier LLM training data (15T tokens)

布局结构

Two growth charts: test volumes and data tokens generated

关键视觉元素

  • •Exponential growth curves
  • •Test volume bars
  • •Token generation projection
  • •LLM comparison marker
页面 66
Regulatory Trend

AI-Enabled Diagnostics Inflecting

内容

Chart showing AI-enabled diagnostics as percent of FDA approvals inflected post-ChatGPT from single-digit % to forecast ~30% by 2030, approaching ~100% over time. Example: Tempus ECG-AF for atrial fibrillation detection

布局结构

Time series with pre/post ChatGPT distinction and forecast

关键视觉元素

  • •Percentage growth curve
  • •ChatGPT inflection marker
  • •Forecast projection
  • •Clinical example callout
页面 67
Section Divider

Multiomics Section 3 - AI Drug Development

内容

Section divider

布局结构

Section header

关键视觉元素

  • •Section title
页面 68
Economic Impact

AI Transforming Drug Economics

内容

Comparison showing AI reducing drug development costs from $2.4B (industry average) to $1.7B (initial AI efforts) to $0.7B (future AI design). Time-to-market reduced from 13 to 11 to 8 years. Failure rates drop significantly

布局结构

Stacked bar chart showing development phase costs and timeline

关键视觉元素

  • •Phase-by-phase cost bars
  • •Three scenario comparison
  • •Timeline reduction indicators
  • •Success vs failure visualization
页面 69
Financial Analysis

Drug Cashflow Efficiency Boost

内容

Charts showing: 1) AI drug generating $4B cumulative cashflow over 30 years vs traditional drug's $1B, 2) Patent life value increasing 30-80% depending on time-to-market acceleration (2-5 years faster)

布局结构

Cashflow curve and patent value analysis chart

关键视觉元素

  • •Cumulative cashflow curves
  • •Break-even comparison
  • •Patent value multipliers
  • •30-year timeline
页面 70
Section Divider

Multiomics Section 4 - Cures Transform Healthcare

内容

Section divider

布局结构

Section header

关键视觉元素

  • •Section title
页面 71
Valuation Analysis

Rare Disease Cures Highly Valuable

内容

Analysis showing cure price of ~$1.1M represents 15x lifetime prescription costs ($75K). Cure enterprise value averages $3.5B - 20x typical drug value. Frontloaded cash and lack of competition drive value

布局结构

Waterfall chart building to cure price and value comparison bars

关键视觉元素

  • •Waterfall price buildup
  • •Enterprise value comparison
  • •Multiple scenarios
  • •10X/13X/19X EBIT multiples
页面 72
Case Study

HAE Gene Editing Economic Case

内容

Hereditary angioedema case study: Gene-editing treatment at $3M (vs $11M value-based price) could save $52B for US HAE patients. Lifetime costs reduced from $12-22M to $4M per patient

布局结构

Bar charts comparing lifetime costs and total savings

关键视觉元素

  • •Treatment regimen comparison bars
  • •Lifetime cost analysis
  • •Total savings calculation
  • •Value-based vs real-world pricing
页面 73
Market Sizing

Cardiovascular Disease Cure Market

内容

ASCVD gene-editing TAM analysis: Value-based price of $165K per patient × 17M US patients with uncontrolled lipids = $2.8T market, 12x Lipitor's 20-year cumulative sales ($225B)

布局结构

Value buildup waterfall and market size comparison

关键视觉元素

  • •Value component waterfall
  • •Population funnel
  • •TAM vs Lipitor comparison
  • •12x multiplier callout
页面 74
Investment Returns

AI + Cures Transform R&D Returns

内容

Return analysis showing AI-accelerated cures achieving 40-50% ROIC vs traditional drug development's <10%. Phase 1 pipeline value increases from negative for traditional to $2B+ for AI-enabled cures

布局结构

ROIC comparison bars and pipeline value progression chart

关键视觉元素

  • •ROIC horizontal bars
  • •Pipeline stage value progression
  • •Representative company examples
  • •Millions scale
页面 75
Section Divider

Multiomics Section 5 - Longevity Science

内容

Section divider

布局结构

Section header

关键视觉元素

  • •Section title
页面 76
Scientific Framework

Biology of Aging Extends Lifespans

内容

Framework showing shift from preventing early deaths (1950-2023: life expectancy 46.5→73 years) to targeting biological aging processes. Evolution of aging measures from clinical markers to DNA methylation clocks to proteomic/digital measures

布局结构

Death distribution chart and aging measurement timeline

关键视觉元素

  • •Age distribution comparison
  • •Measurement evolution timeline
  • •1950s to 2020s progression
  • •Technology categories
页面 77
Market Opportunity

Longevity Market Worth $1.2 Quadrillion

内容

Analysis showing US healthy life potential could double from 11.7B to 23.6B quality-adjusted life years (QALYs). At $100K per QALY, longevity gain of 11.9B QALYs = $1.2 quadrillion opportunity. Current biotech represents only ~0.1% of TAM

布局结构

Waterfall chart building to total longevity potential

关键视觉元素

  • •QALY waterfall buildup
  • •Gain vs loss visualization
  • •Quadrillion scale
  • •Biotech market comparison
页面 78
Chapter Divider

Reusable Rockets - Chapter Opener

内容

Chapter on unlocking space economy. Authors: Daniel Maguire and Sam Korus

布局结构

Chapter divider

关键视觉元素

  • •Chapter title
  • •Author credits
页面 79
Market Transformation

Reusable Rockets Catapult Into Space Age

内容

Charts showing: 1) Annual upmass to orbit reached 3,500+ metric tons in 2025 vs ~500 in 2022, 2) Active satellites surged to 14,000+ (SpaceX Starlink accounts for ~66%). Major inflection post-Starlink launch in 2019

布局结构

Two time series charts showing dramatic post-2019 growth

关键视觉元素

  • •Upmass bar chart
  • •Active satellite line chart
  • •Pre/post-Starlink distinction
  • •SpaceX dominance visualization
页面 80
Cost Decline Analysis

Launch Costs Continue Falling

内容

Wright's Law analysis showing SpaceX reduced costs 95% from ~$15,600/kg (2008) to <$1,000/kg (2025). Starship forecast to reach <$100/kg at scale. 17% cost decline per cumulative doubling of upmass

布局结构

Logarithmic scatter plot with historical data and forecast

关键视觉元素

  • •Log-log scatter plot
  • •Falcon historical trajectory
  • •Starship forecast line
  • •Wright's Law curve fit
页面 81
Technology Evolution

Satellite Bandwidth Costs Falling

内容

Wright's Law showing 44% bandwidth cost decline per doubling. Evolution from ViaSat-1 (2011) to Starship V4 forecast (2035). Table shows mobile connectivity evolution: 2001 GPRS (~1% coverage) to 2030E (100% coverage, unlimited data)

布局结构

Logarithmic cost curve and mobile evolution comparison table

关键视觉元素

  • •Log-log bandwidth cost curve
  • •Satellite generation markers
  • •Mobile connectivity comparison table
  • •Coverage evolution metrics
页面 82
Market Forecast

Satellite Connectivity $160B Opportunity

内容

Chart showing satellite connectivity revenue could reach $160B+ (~15% of global communications revenue forecast). Revenue scales with constellation bandwidth (Tbps). Two percentage charts show satellite growing from ~0.01% to ~1.2% of GDP

布局结构

Scatter plot and percentage comparison charts

关键视觉元素

  • •Revenue vs bandwidth scatter
  • •GDP percentage comparison
  • •2025E vs 2035E bars
  • •Billions scale
页面 83
Chapter Divider

Robotics - Chapter Opener

内容

Chapter on leveraging human labor. Authors: Sam Korus and Akaash TK

布局结构

Chapter divider

关键视觉元素

  • •Chapter title
  • •Author credits
页面 84
Labor Market Analysis

Technology Frees Workers From Low Productivity Tasks

内容

Charts showing: 1) Labor productivity and participation coexisted (1948-2000), then diverged due to aging/globalization not automation, 2) Average US labor hours declined from ~2,000 (1950) to ~1,750 (2024)

布局结构

Two time series: productivity/participation and hours worked

关键视觉元素

  • •Dual-axis productivity chart
  • •Hours worked decline
  • •1948-2025 timeline
  • •Divergence point marked
页面 85
Market Penetration

Industrial Automation In Its Infancy

内容

Robot density comparison: Amazon (6,427 robots per 10K employees) far exceeds automotive manufacturing (1,500 in US) and general manufacturing (1,129 in US). Global automotive leaders: Korea (2,867), China (1,422)

布局结构

Grouped bar chart comparing robot density across countries and sectors

关键视觉元素

  • •Grouped bars by country/sector
  • •2014/2021/2023/2025 comparison
  • •Amazon standout bar
  • •Robots per 10K employee metric
页面 86
Opportunity Sizing

$26 Trillion Automation Opportunity

内容

Breakdown showing ~$13T household robotics opportunity (2.8B workforce × 2.3 hrs/day × $12/hr × 50% time value) + ~$13T manufacturing opportunity ($32T global manufacturing GDP × 100% productivity uplift × 35% take rate)

布局结构

Two calculation frameworks and cumulative unit sales comparison

关键视觉元素

  • •Calculation waterfalls
  • •Two market segments
  • •Unit sales comparison (~27K industrial vs 2M humanoids cumulative)
  • •Trillions scale
页面 87
Technical Complexity

Humanoid vs Robotaxi Complexity Ratio

内容

Logarithmic analysis showing humanoids ~200,000x more complex than robotaxis across: kinetic demand (13x-16x), mobility (10x-30x), perception (4x-5x), adaptability (4x), error tolerance (100x less tolerant)

布局结构

Waterfall chart building complexity multipliers on log scale

关键视觉元素

  • •Logarithmic waterfall
  • •Complexity multipliers
  • •10^0 to 10^8 scale
  • •Five complexity categories
页面 88
Technology Roadmap

Path To Human-Level Optimus By 2028

内容

Chart mapping compute capacity to performance: Tesla FSD scaling laws project Optimus reaching human-level proficiency around 2028 with 1,080MW AI compute (vs 91MW in Dec 2025)

布局结构

Log-log scatter plot with performance milestones

关键视觉元素

  • •Log-log scatter plot
  • •Compute capacity timeline
  • •Performance milestones
  • •2028 human-level projection
页面 89
Market Landscape

Robotics Market Landscape

内容

Company categorization: Specialized robots (ABB, FANUC, KUKA, Intuitive Surgical, etc.) vs Generalizable robotics (Tesla Optimus, Figure F.03, Boston Dynamics Atlas, 1X NEO, etc.). Market shifting to generalizable platforms

布局结构

Two-column company listing with categorization

关键视觉元素

  • •Two-category framework
  • •Company/product names
  • •Robot model images
  • •Incumbent vs pioneer distinction
页面 90
Chapter Divider

Distributed Energy - Chapter Opener

内容

Chapter on powering AI revolution. Authors: Daniel Maguire, Sam Korus, Akaash TK

布局结构

Chapter divider

关键视觉元素

  • •Chapter title
  • •Author credits
页面 91
Energy Transition

Energy Powering Economic Growth Efficiently

内容

Charts showing: 1) Energy intensity (kWh per GDP dollar) declining globally especially in China, 2) Global power capacity additions surged post-ChatGPT (2022), led by solar PV, wind, and battery storage reaching 1,000GW in 2024

布局结构

Energy intensity line chart and capacity additions bar chart

关键视觉元素

  • •Multi-country intensity trends
  • •Capacity additions stacked bars
  • •ChatGPT launch marker
  • •Technology category breakdown
页面 92
Cost Decline Analysis

Solar, Battery, Nuclear Cost Declines

内容

Wright's Law analysis showing: 1) Solar and nuclear following steep cost curves (nuclear disrupted by 1975 regulation), 2) Battery costs (LFP and Nickel cells) declining steeply with cumulative MWh

布局结构

Two log-log scatter plots showing cost trajectories

关键视觉元素

  • •Log-log cost curves
  • •Nuclear regulatory change marked
  • •Battery chemistry comparison
  • •Wright's Law fit lines
页面 93
Price Forecast

Electricity Prices Resuming Decline

内容

Analysis showing US electricity prices fell 1893-1974, then stagnated. If nuclear costs hadn't been disrupted, electricity would be ~40% cheaper. New build LCOE comparison shows nuclear SMR, solar+storage, wind+storage all below retail prices

布局结构

Historical log scale chart and LCOE comparison bars

关键视觉元素

  • •Century-long price curve
  • •Regulatory disruption marker (1974)
  • •LCOE comparison bars
  • •US vs China cost comparison
页面 94
Investment Forecast

Global Power Investment To $10T by 2030

内容

Charts showing cumulative global power capital investment must scale ~2x to ~$10T by 2030 (data centers: 5% of total). Stationary energy storage deployments must scale 19x from ~100GWh to ~19,000GWh

布局结构

Two bar charts: capital investment and energy storage deployment

关键视觉元素

  • •Stacked investment bars
  • •Log scale storage chart
  • •~2x and ~19x multipliers
  • •2016-2030 timeline
页面 95
Chapter Divider

Autonomous Vehicles - Chapter Opener

内容

Chapter on cars driving themselves and lowering costs. Authors: Tasha Keeney and Daniel Maguire

布局结构

Chapter divider

关键视觉元素

  • •Chapter title
  • •Author credits
页面 96
Market Penetration

Robotaxis Taking Share From Ride-Hail

内容

Charts showing Waymo reached ~400K daily driverless miles, 6B cumulative autonomous miles. Waymo market share in San Francisco operating zone reached ~60% by August 2025 vs Uber ~25% and Lyft ~15%

布局结构

Three charts: daily miles, cumulative miles, market share area chart

关键视觉元素

  • •Daily miles bars by company
  • •Cumulative miles comparison
  • •Market share area chart
  • •Waymo dominance visualization
页面 97
Economics Analysis

Falling Robotaxi Costs Drive Demand

内容

Cost analysis showing robotaxi incremental cost per mile declining from ~$1.20 (Waymo 5th Gen early) to ~$0.25 (Cybercab at scale). Price per mile forecast: Human ride-hail $2.80 → Robotaxis $0.25 (2035E)

布局结构

Stacked cost breakdown bars and price evolution comparison

关键视觉元素

  • •Cost component stacks
  • •Four scenarios compared
  • •Price decline visualization
  • •2025E to 2035E timeline
页面 98
Market Sizing

Robotaxis Could Dominate Urban Transit

内容

Analysis showing ~140K robotaxis could serve current US urban ride-hail demand. ~24M robotaxis (<10% of US vehicle fleet) could accommodate majority of urban miles. Tesla has production capacity for top ride-hail cities

布局结构

Time-of-day demand chart with production capacity comparison

关键视觉元素

  • •Hourly demand curves by city
  • •Production capacity bars
  • •12 major US cities shown
  • •Millions scale
页面 99
Valuation Forecast

Robotaxis $34T Enterprise Value by 2030

内容

Forecast showing robotaxi ecosystem generating $200B revenue, $20B EBIT, $34.1T enterprise value by 2030. Breakdown: Autonomous technology providers ($1.9T EV at 19x EBIT), fleet owners ($200B), manufacturers ($400B)

布局结构

Three-column comparison: revenue, EBIT, enterprise value with multiples

关键视觉元素

  • •Revenue/EBIT/EV bars
  • •Multiple callouts (10X, 13X, 19X)
  • •Three category breakdown
  • •Trillions scale
页面 100
Value Chain Analysis

Technology Platforms Win Majority of Economics

内容

Partnership matrix showing autonomous technology platforms (Tesla, Waymo, Baidu, etc.) partnering with automakers and fleet operators. Value capture: Technology platforms get 98% of EV, 97% of EBIT, 76% of revenue

布局结构

Partnership matrix table and value capture breakdown

关键视觉元素

  • •Partnership matrix
  • •Three-column value breakdown
  • •Percentage allocations
  • •Company relationships mapped
页面 101
Chapter Divider

Autonomous Logistics - Chapter Opener

内容

Chapter on slashing costs and delivery times. Authors: Tasha Keeney and Daniel Maguire

布局结构

Chapter divider

关键视觉元素

  • •Chapter title
  • •Author credits
页面 102
Market Status

Fully Autonomous Delivery Is Here

内容

Cumulative delivery data: Drones (Zipline 2M+, Meituan 780K, Wing 750K), Robot deliveries (Starship 9M, Meituan 4.9M), Autonomous trucking miles (Inceptio 250M, Pony.ai 4.2M, Aurora 3.8M, Kodiak 3M, Gatik 2.1M)

布局结构

Three bar charts showing delivery volumes by company

关键视觉元素

  • •Three delivery category comparisons
  • •Company-level bars
  • •Millions scale
  • •Leading companies highlighted
页面 103
Cost Reduction

Autonomous Machines Reduce Delivery Costs

内容

Cost comparisons: Last mile delivery falls ~90% from $15 (app delivery fees) to <$1 (drone/robot). Truckload delivery falls ~60% from $0.07 to $0.03 per ton-mile (human diesel truck to autonomous electric)

布局结构

Two side-by-side cost comparison charts

关键视觉元素

  • •Cost decline bars
  • •Percentage reduction callouts (~60%, ~90%)
  • •Traditional vs autonomous comparison
  • •Dollar values
页面 104
Revenue Forecast

Autonomous Delivery Revenue Forecast

内容

Forecast showing autonomous delivery revenue reaching $480B globally by 2030, split between last mile drone/robot ($160B) and over-the-road trucking ($320B). Regulation and back-end automation are gating factors

布局结构

Stacked bar chart with 2030E projection

关键视觉元素

  • •Stacked 2030E bar
  • •Two delivery categories
  • •Billions scale
  • •Gating factors noted
页面 105
References Section

Works Cited - Introduction

内容

Introduction page to works cited section

布局结构

Simple section header

关键视觉元素

  • •Section title
  • •Page number
页面 106
Bibliography

Works Cited - Page 1

内容

Alphabetical bibliography starting with '36Kr European Central Station 2025' through 'Artificial Analysis 2025b', covering sources on robotics, AI, costs, energy, and finance

布局结构

Two-column bibliography with standard citation format

关键视觉元素

  • •Two-column layout
  • •Alphabetical ordering
  • •Standard citations
  • •Source dates included
页面 107
Bibliography

Works Cited - Page 2

内容

Bibliography continuing from 'Arute, F. et al. 2019' through 'Bryce. 2025', covering quantum computing, retail, blockchain, and space industry sources

布局结构

Two-column bibliography continuation

关键视觉元素

  • •Continued citations
  • •Multiple source types
  • •Academic and industry sources
页面 108
Bibliography

Works Cited - Page 3

内容

Bibliography continuing from 'Bureau of Labor Statistics 2026' through 'Guardant Health 2025', covering government data, blockchain analytics, and healthcare sources

布局结构

Two-column bibliography continuation

关键视觉元素

  • •Government sources
  • •Company reports
  • •Academic citations
页面 109
Bibliography

Works Cited - Page 4

内容

Bibliography continuing from 'Hedges & Company 2025' through 'Roland, A. et al. 2024', covering automotive, longevity, AI performance, and pharmaceutical R&D sources

布局结构

Two-column bibliography continuation

关键视觉元素

  • •Diverse source types
  • •Industry reports
  • •Research papers
页面 110
Bibliography & Legal

Works Cited - Page 5 & Disclaimer

内容

Final bibliography entries from 'rwa.xyz 2025' through 'Winton, B. 2024', followed by comprehensive legal disclaimer covering cryptocurrency risks, forward-looking statements, and copyright notice

布局结构

Citations at top, multi-paragraph disclaimer below

关键视觉元素

  • •Final citations
  • •Extensive legal disclaimer
  • •Copyright notice
  • •Risk disclosures

常见问题

关于此幻灯片和基础演示文稿内容的常见问题。

What is ARK's main thesis for GDP growth by 2030?

ARK forecasts global real GDP growth will accelerate from the IMF's consensus 3.1% to 7.3% annually through 2030, driven by five major innovation platforms (AI, Public Blockchains, Robotics, Energy Storage, and Multiomics). Capital investment alone could add 1.9 percentage points to annual growth, with additional gains from increased returns on invested capital, transformation of non-market activity into GDP, and freed human potential for productive use.

How much could AI infrastructure investment reach by 2030?

ARK projects data center systems investment will reach approximately $1.4 trillion annually by 2030, growing at a 30% compound annual rate. This represents a dramatic acceleration from the 5% CAGR seen from 2012-2023 to 29% CAGR post-ChatGPT. The forecast includes a shift toward accelerated compute (GPUs and ASICs) taking increasing market share from traditional servers.

What is the potential market size for robotaxis by 2030?

ARK forecasts the robotaxi ecosystem could generate $34 trillion in enterprise value by 2030, with $200 billion in revenue and $20 billion in EBIT. Autonomous technology platforms are expected to capture 98% of enterprise value, 97% of EBIT, and 76% of revenue. The analysis suggests autonomous ride-hail could drop prices from $2.80 per mile (human-driven) to $0.25 per mile by 2035.

How does ARK value bitcoin and digital assets in 2030?

ARK projects the digital asset market could reach $28 trillion by 2030, growing at ~61% CAGR. Bitcoin is expected to dominate with 70% share (~$16 trillion at 63% CAGR), while smart contract networks could reach ~$6 trillion (54% CAGR). The forecast is based on penetration rates across six use cases: institutional investment, digital gold, emerging market safe haven, nation-state treasury, corporate treasury, and on-chain financial services.

What is the $26 trillion robotics opportunity?

ARK identifies a $26 trillion revenue opportunity split between household robotics ($13T) and manufacturing automation ($13T). The household opportunity is calculated from 2.8 billion global workforce × 2.3 hours unpaid work per day × $12/hour average × 50% time value. Manufacturing opportunity comes from $32T global manufacturing GDP × 100% productivity uplift × 35% provider take rate. Humanoid robots reaching human-level proficiency around 2028 is key to unlocking this market.

How significantly could AI reduce drug development costs?

ARK's analysis shows AI could reduce drug development costs from $2.4 billion (industry average) to $0.7 billion for future AI-designed drugs—a 4x reduction. Time-to-market could decrease from 13 years to 8 years, and human trial failures could drop from 7.6 to 1.9. AI-developed drugs could generate $4 billion in cumulative cashflow over 30 years versus $1 billion for traditional drugs. Gene-editing cures are valued at 20x typical drugs.

What is the forecast for stablecoin and tokenization markets?

Stablecoin adjusted transaction volumes reached $3.5 trillion monthly (30-day average) in December 2025, already 2.3x larger than Visa + PayPal + Remittances combined. The tokenized assets market tripled to $19 billion in 2025 and could reach $11 trillion by 2030, representing ~1.38% of all financial assets. DeFi applications are achieving extraordinary revenue efficiency, with companies like Hyperliquid generating $60M+ revenue per employee.

How does ARK's multiomics forecast connect to longevity?

ARK identifies a $1.2 quadrillion US longevity market opportunity based on doubling healthy life potential from 11.7 billion to 23.6 billion quality-adjusted life years (QALYs). At $100,000 per QALY, this 11.9 billion QALY gain represents massive value. The multiomics-AI flywheel is accelerating this: molecular test data volumes will increase 10x by 2030 (exceeding frontier LLM training data), AI-enabled diagnostics will reach ~30% of FDA approvals, and gene-editing cures for rare diseases could be worth $3.5 billion each—20x typical drugs.

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