Cyborg

• Merging of human and machine components
• Can repair, replace or augment organic components
• Many cultural implications
• Rapidly-accelerating science

Examples:

• RoboCop
• Prosthetics
• Camera + visual cortex in human brain
• Extensive use of smartphones
• Pacemakers/heart monitor implants

Brands: Push to Pull

• Push-based brands are focused on telling customers about themselves and trying to cause a sale before value is created
• Pull-based brands are about creating inherent value for customers first, generating gravitational pull—and then allowing purchases to be a natural result of that value

Examples:

• Nike+/Nike Fuel
• iOS and Android ecosystems

BMW ConnectedDrive

• In-car infotainment system
• Allows third-party app development (closed system, not an open API)

Examples:

• In-car infotainment system
• Allows third-party app development (closed system, not an open API)

Big Data

• Collection and aggregation of large pools of data for analysis
• Many companies pool large quantities of data without knowing use cases yet
• Storage, privacy, security, speed and reliability are major concerns
• Big data + analytics needed for business insights; multi-sided platforms needed for advanced data-driven products

Examples:

• Collection and aggregation of large pools of data for analysis
• Many companies pool large quantities of data without knowing use cases yet
• Storage, privacy, security, speed and reliability are major concerns
• Big data + analytics needed for business insights; multi-sided platforms needed for advanced data-driven products

Autonomous Driving

• Varying degrees of machine augmentation or automation of human driving capacity
• Five levels of autonomous driving by US NHTSA (National Highway Traffic Safety Administration)
• (Level 0): No assistance or automation
• Function-specific Automation (Level 1): i.e. ABS, ESC
• Combined Function Automation (Level 2): i.e. Adaptive Cruise Control with Lane Centering
• Limited Self-Driving Automation (Level 3): i.e. Tesla Autopilot or early Google Car test vehicles
• Full Self-Driving Automation (Level 4): i.e. Google Car

Examples:

• Google Car
• Tesla Autopilot
• Traditional Automaker Prototypes (Mercedes, Audi, Etc)

Automatic

• In-car connector bridging internet and built-in systems (CAN-BUS)
• Provides basic trip and mechanical information to phone; some models provide 3G connectivity to function even when smartphone not present
• Provides ability for in-car measurements to feed into its own app or third-party applications in its marketplace

 Examples:

• unMooch (share costs for rides with friends)
• Expensify (automatically log reimbursable miles driven for work)

As a Service

• Pricing model of charging a fee (usually subscription-based) for the value provided to a customer, rather than delivery of a tangible good
• Common in software world with web-based tools hosted in the cloud
• Increasing application to the physical world (mobility as a service via Uber and Didi, for example)
• Requires constant innovation by company, but stabilizes cashflow and upkeep costs
• Lowers cost of entry to expensive or complex systems

Examples:

• Salesforce
• Spotify
• Netflix
• Google Apps for Work
• FreshBooks
• Office 365

Artificial Ingelligence

• Augmentation or emulation of human intelligence in machine systems
• Creation of new, non-human forms of intelligence
• Includes expert systems (modeling human knowledge) as well as systems with decision-making skills

Examples:

• IBM Watson
• Assistant.ai
• Autonomous driving systems

Apple CarPlay

• Apple in-dash infotainment functionality
• Vehicle or 3rd-party manufacturer creates head unit in dash of vehicle
• Connects to iPhone and mirrors functionality through high-speed USB (and potentially future wireless connection) running specifically-designed apps in a manner safer and easier than using handset
• Relies on voice for primary input device
• Relies on mobile data connection for most functions 

APIs

• Application Program Interfaces to create conduits between various systems and datasets 
• Enables internal or third-party developers
• Requires robust and secure architecture, including authentication, data integrity efforts and use logging
• Necessary for platform-based value

Examples:

• HomeKit
• Facebook Connect and other Single-Sign-On (SSO) options
• Ripple
• Fidor
• Apple CarPlay
• Software Development and Hardware Development Kits (SDK and HDKs)

Analytics

• Discovery, interpretation and communication of meaningful information in data
• Multidisciplinary—covers entire methodology and data value chain
• Many subfields, such as text analytics
• Temporal (time) element: batch (past) analytics, real-time analytics, predictive/prescriptive analytics

Examples:

• Google Analytics (web properties)
• Sales analytics
• Inventory analytics
• Mixpanel