BLOCK∙CHAIN The Audacity To Break Into A New Economic Period [RE] @richieetwaru
scope of today’s conversation Bitcoin Blockchain v.s. Just an instance of the blockchain Where is commerce globally Requires miners, and personal Understanding blockchain computing power Relies on “proof of work” Where does commerce go next [RE] @richieetwaru
@richieetwaru
Experience & Engagement Economic Period 2000 - 2020 [RE] @richieetwaru
@richieetwaru
The valley of Competitive greenfield death 2000 2020 [RE] @richieetwaru
@richieetwaru
How did we compete before the year 2000? [RE] @richieetwaru
Price & Quality Economic Period 1960 - 2000 [RE] @richieetwaru
@richieetwaru
The valley of Competitive greenfield death 1940 2000 [RE] @richieetwaru
1960 2000 2020 40 Years 20 Years [RE] @richieetwaru
What will we compete with after the year 2020? [RE] @richieetwaru
1960 2000 2020 2040 [RE] @richieetwaru
What triggers one economic period to another? [RE] @richieetwaru
[RE] @richieetwaru
1960 2000 2020 2040 Democratizing Compressing Industrializing Credit Distance Trust [RE] @richieetwaru
Trust & Transparency Economic Period 2020 - 2040 [RE] @richieetwaru
BLOCKCHAIN
What is the problem that blockchain solves? [RE] @richieetwaru
@richieetwaru
@richieetwaru
We manufacture trust with intermediaries, contracts and familiarity [RE] @richieetwaru
@richieetwaru
(1) Blockchain reduces the time and cost of verifying data [RE] @richieetwaru
tamper-able data that requires significant effort to decipher if it was tampered with 008 Second speeding ticket 2013 007 007 License reinstated 2004 2004 006 006 License suspended (6 months) 2003 2003 005 005 Driving while intoxicated 2003 2003 004 Stop light violation 2003 003 License renewed 2001 002 First speeding ticket 1997 001 Drivers license issued 1996 [RE] @richieetwaru
immutable data that requires little effort to decipher if it was tampered with NJ State Police 008 Second speeding ticket 2013 DMV 007 License reinstated 2004 NYS Court 006 License suspended (6 months) 2003 NYC Police Dept. 005 Driving while intoxicated 2003 NYC Police Dept. 004 Stop light violation 2003 DMV - Online 003 License renewed 2001 NYC Police Dept. 002 First speeding ticket 1997 DMV 001 Drivers license issued 1996 [RE] @richieetwaru
this is one of the fundamental mental cornerstones of blockchain “Trust me, you can “Easily test if I am vs trust me.” trustable.” [RE] @richieetwaru
trust new data which were once not worth the investment to manufacture trust around Financial Identity Reputation Inventory Market Agreement Corporate Data Data Data Data Data Data Data Data that can be exchanged 1:1 without intermediary [RE] @richieetwaru
(2) Blockchain increases the reach of market consensus and partner familiarity [RE] @richieetwaru
NYC Police Dept. NJ State Police DMV Richie’s Personal Copy [RE] @richieetwaru
Proof of Proof of VS Work Stake [RE] @richieetwaru
this is one of the fundamental mental cornerstones of blockchain “I need to know you to “Your trustworthiness vs transact with you” is publically available [RE] @richieetwaru
consensus and familiarity with unfamiliar trading partners in intimate ways Inter-organization & Inter-industry and Intra-organization Inter-geographies intra-industry intra-geographies Those that I don ’ t Those that I don ’ t Those that I already Those I already know but don ’ t really trust know that I don ’ t know and already know and as a result don ’ t trust trust as yet know as yet New trading partners at low cost and high confidence [RE] @richieetwaru
New business networks Unfamiliar partners transacting in Blockchain is emerging as the New market exponential structures agent for IoT and AI intimately New information ecosystems New data sets that can be trusted at low cost [RE] @richieetwaru
Blockchain IoT
Internet of Things
IoT Connects things other than computers to the Internet [RE] @richieetwaru
what are some commercial opportunities from the Internet of Things Invisible Smart Connected Computing Consumer Electronics Government Digital Wearable Connected Smart Cities Supply Industrial Health Clothing Homes & Transportation Constellations Internet Things Things Things Things Things Things Things Things Things Things In My On My I Carry Around In My That House That That Help At That Body Body Around My Body House Me Transport Commerce Work Build [RE] @richieetwaru
where and how is IoT likely to evolve over time Internet of Internet of Internet of Internet of Internet of dumb things chatty things obedient things useful things smart things Things that are Things that can Things that can WHAT CAN Things that can report Things that can engage connected have execute THEY DO or trigger events and add value digitally conversations instructions Sensor in trunk of car Light sensor can Controller that Sensor on mattress or Camera learns from calendar WHAT DOES IT only report back can change the bedroom to know that a connected to a that you are driving to FEEL LIKE absence or temperature in a person did not have tall building golf game, notices the presence of light house enough rest at night golf clubs not in trunk Network of sensors Sensor communicates Thermostat that Lens that can verifies that golf clubs with admin & calendar, Sensor to see if can be told to WHAT IS AN report back are still in the garage, moves an 7AM meeting a light is on or change the EXAMPLE remotely what it and orders a pickup to 8AM, and informs off temperature in a sees service to bring your alarm clock to allow house golf clubs to the course human one more hour [RE] @richieetwaru
New-er New business business networks networks Blockchain is Unfamiliar partners transacting emerging as the New market Trusted exponential structures Commerce agent for IoT and AI intimately New-er New information information ecosystems ecosystems New data sets that can be trusted at low cost [RE] @richieetwaru
@richieetwaru
where does the roadmap potentially lead Figure 1: Blockchain Institutional Revolution Maturity Model Finance Identity Reputation Inventory Market Agreement Cooperate Data Data Data Data Data Data Data TRUST 1A 2A 3A 4A 5A 6A 7A CONSENSUS 2A 3B 3B 4B 5B 6B 7B AUTONOMY 3A 4C 3C 4C 5C 6C 7C [RE] @richieetwaru
1960 2000 2020 2040 Democratizing Compressing Spotlighting Credit Distance Fraud [RE] @richieetwaru
opportunity for new businesses Basis of Price & Experience & Trust & Differentiation Quality Engagement Transparency Survival of 80% 50% 25% Incumbents State of Loyal to Incumbent Schizophrenic Low Loyalty Customer Loyalty Brands Loyalty To Untrusted Brands
01 To Blockchain or Not to Blockchain There is need for multiple types of companies to be interested in the state of a dataset Some datasets are only important to one party, or a small fixed number of parties who have worked with each other a long time, hence very clear and trusted processes are in place to enable multiple well-known parties to access the same dataset Unlikely Likely 1 2 3 4 5 6 7 8 9 10 Types of companies greater than 25? Normal distribution of company sizes? Data equally important to all company types? TOTAL 3-10 [RE] @richieetwaru
02 To Blockchain or Not to Blockchain Multiple parties can write new records to the dataset While some datasets are viewed by many parties, it may only be written by one party. In some cases, one party writes a part of a complete transaction, and other parties will write the other parts. Unlikely Likely 1 2 3 4 5 6 7 8 9 10 Types of companies greater than 10? Amount of times per day is greater than 12? Some parties have permissions that others don’t? TOTAL 3-10 [RE] @richieetwaru
03 To Blockchain or Not to Blockchain Each new record is additive, and changes derivatives from the entire dataset The aggregates derived from the dataset is of primary importance, and said derived aggregates changes with every new record. For example, the price of a stock, each new record is important as it tells the most recent price. While a derived aggregate such as average price over a period of time can be useful, its secondary. Unlikely Likely 1 2 3 4 5 6 7 8 9 10 New records can be added daily? New records create important derived data? 50+% of participants must know derived data? TOTAL 3-10 [RE] @richieetwaru
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