Moore's Law and Impact on Technology Management

Chapter 6: Moore's Law And More: Fast/Cheap Computing, and What This Means for the Manager

Section 6.1: Learning Objectives

  • Define Moore’s Law: Chip performance per dollar doubles every eighteen months.

    • Technological Advancements: Includes predictions for the advancement of technologies (e.g., magnetic storage and telecommunications).

  • Price Elasticity: Understand how faster and cheaper technologies create new markets and opportunities, driving industry disruption.

  • Data Capacity Measurement: Recognize various terms for measuring data capacity.

  • Managerial Implications: Consider the effects of faster computing on strategic planning, inventory, and accounting.

Moore’s Law and How Managers Interpret It

  • Moore’s Law Explained: It is an observation and prediction about the growth rate of chip performance related to cost.

    • Doubling Rate: Performance doubles approximately every 18 months, though Intel proposes it may now slow to 2.5 years.

  • Chip Types: Applies to:

    • Processors

    • Chip-based storage

    • Microprocessor: Executes instructions of a computer program.

  • Implications for Managers: Awareness of accelerating power and dropping costs is essential for strategic planning.

AI and Machine Learning—Faster than Moore’s Law

  • Comparative Progress: Key computing areas show faster advancement than Moore’s Law.

  • Cost Reduction Examples:

    • Training an image recognition model cost $1,000 in 2017 but only $7.43 in 2020.

    • Training time for the model reduced from 6.2 minutes in 2018 to 47 seconds in 2020.

  • AI System Performance: Doubling every six months, significantly exceeding Moore’s Law.

    • Importance of user growth in maintaining low costs.

The End of Moore’s Law, but Not Really an End to Fast/Cheap Computing

  • Transistor Density Limitations: Slowing progress in transistor density does not imply a halt in computing advancement.

    • Focus on improved chip design and cloud computing as growth vectors.

  • Apple’s Transition: Switching from Intel chips to custom silicon yielded faster performance while consuming less power.

  • Compatibility Issues: Transition challenges due to older software and instruction sets, mitigated by Apple's emulators.

    • Compiler Definition: Translates developer code into processor-understandable instructions.

Some Definitions

  • Random-access memory (RAM): Fast, volatile storage in computing devices.

  • Volatile vs. Nonvolatile Memory:

    • Volatile: Data lost when power is cut.

    • Nonvolatile: Retains data without power.

    • Flash Memory: A form of nonvolatile, chip-based storage.

  • Solid State Electronics: Semiconductor-based devices.

Bits and Bytes

  • Binary Basics: Data expressed in bits (0s and 1s).

    • Byte Definition: 8 bits.

  • Measured in increasing orders of magnitude:

    • Kilobyte (KB): 1,000 bytes

    • Megabyte (MB): 1 million bytes

    • Gigabyte (GB): 1 billion bytes

    • Terabyte (TB): 1 trillion bytes

    • Petabyte (PB): 1 quadrillion bytes

    • Exabyte (EB): 1 quintillion bytes

  • Telecommunication Capacity: Often reported in bits per second (bps).

Price Elasticity and Computing Waves

  • Price Elasticity Definition: Demand fluctuation rate with price change.

  • Evolving Waves of Computing:

    • First wave (1960s): Mainframe computers

    • Second wave (1970s): Minicomputers

    • Third wave (1980s): PCs

    • Fourth wave (1990s): Internet computing

    • Fifth wave (2000s): Smartphone revolution

    • Sixth wave (2010s): Pervasive computing

    • Seventh wave (present): AI through cloud computing.

Application of Technology in Poverty Alleviation

  • Global Mobile Phone Accessibility: 93% of the global population connected to mobile broadband.

  • Impact on Farming:

    • Example: Esoko company helps farmers in Ghana with market prices and information via text.

Technology Application Cases (Amazon Kindle and Apple Music Storage)

  • Performance and Capacity Trends: Tracking the trends in technological performance over generations.

  • Comparison of Storage Solutions:

    • First-generation iPod to fourth-generation comparison highlighting transitions in storage capacity and cost (e.g., 250MB to 5GB).

The Internet of Things (IoT) Implementations

  • Spread of Smart Technologies: Adoption of digital thermostats, smart advertisements, and advanced vehicle safety measures.

  • IoT Vision: Integration of sensors and processors to improve data collection and automation in product functionalities.

  • Smart Solutions: Examples include smart pill bottles for medication adherence and healthcare improvements through technology.

Managerial Responsibilities

  • E-Waste and Its Challenges:

    • Definition and impact of electronic waste on the environment.

    • Importance of recycling and the toxic implications of improper disposal.

    • U.S. recycling challenges and international standards.

  • Ethical Management Considerations:

    • Need for proactive planning in technology disposal and lifecycle management.

Disney Case Study: Mickey’s Wearable

  • MagicBand Functionality: Technology that streamlines visitor experience in Disney World parks.

    • Data Analytics Application: Leveraging analytics for improving customer service, resource allocation, and operational efficiency.

    • Cost and Integrative Challenges: The capital investment and complex integration processes involved in execution.