Bitcoin WhitePaper Day

Bitcoin – A Peer-to-Peer
Electronic Cash System

It’s bitcoin White Paper Day.

The mailing list was hosted by Metzdow and run by a group of cypherpunks who shared ideas on creating a kind of digital currency and payment system. Satoshi shared the whitepaper in a message that read, “Bitcoin P2P e-cash paper,” which outlined the main properties of the system.


“Bitcoin P2P e-cash paper
Satoshi Nakamoto satoshi at vistomail.com
Fri Oct 31 14:10:00 EDT 2008
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I’ve been working on a new electronic cash system that’s fully
peer-to-peer, with no trusted third party.

The paper is available at:
http://www.bitcoin.org/bitcoin.pdf

The main properties:
Double-spending is prevented with a peer-to-peer network.
No mint or other trusted parties.
Participants can be anonymous.
New coins are made from Hashcash style proof-of-work.
The proof-of-work for new coin generation also powers the
network to prevent double-spending.

Bitcoin: A Peer-to-Peer Electronic Cash System

Abstract. A purely peer-to-peer version of electronic cash would
allow online payments to be sent directly from one party to another
without the burdens of going through a financial institution.
Digital signatures provide part of the solution, but the main
benefits are lost if a trusted party is still required to prevent
double-spending. We propose a solution to the double-spending
problem using a peer-to-peer network. The network timestamps
transactions by hashing them into an ongoing chain of hash-based
proof-of-work, forming a record that cannot be changed without
redoing the proof-of-work. The longest chain not only serves as
proof of the sequence of events witnessed, but proof that it came
from the largest pool of CPU power. As long as honest nodes control
the most CPU power on the network, they can generate the longest
chain and outpace any attackers. The network itself requires
minimal structure. Messages are broadcasted on a best effort basis,
and nodes can leave and rejoin the network at will, accepting the
longest proof-of-work chain as proof of what happened while they
were gone.

Full paper at:
http://www.bitcoin.org/bitcoin.pdf

Satoshi Nakamoto

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The pseudonymous Bitcoin creator disclosed that they had been working on a new electronic cash system that uses a Proof-of-Work (PoW) consensus algorithm that required no trusted third party. Although the document met mixed reactions, it was the beginning of what is known today as blockchain technology.

A couple of months after the release, the Bitcoin network was launched, with the first block mined on January 3, 2009. About eight days later, Hal Finney received the first transaction of 10 BTC from Nakamoto, after which he posted a legendary tweet that read:

In the 14 years since that day, bitcoin’s value rose from zero to a peak of $68,990 last November and was hovering above $20,000 on Monday, according to CoinDesk data. The cryptocurrency currently has a market capitalization of over $390 billion. It also inspired the creation of more than 20,000 different cryptocurrencies currently in circulation, while bitcoin remains the largest by market cap.

Over the years, several people have been rumored to be Nakamoto, including early bitcoin contributor Hal Finney, cryptographer Nick Szabo, physicist Dorian Nakamoto and even Tesla’s chief executive Elon Musk, who all denied the claims.

Satoshi’s identity is still a mystery, but Finney was well-known for his contribution to the creation of Bitcoin. He worked hand-in-hand with Nakamoto to find and fix bugs in Bitcoin’s underlying infrastructure. Before his death in 2014, Finney shared a detailed story about his journey with Bitcoin

About a year after the launch of Bitcoin, the cryptocurrency went on to record its first real-world commercial use case when a Florida man spent 10,000 BTC to purchase two large Papa John’s pizzas on May 22, 2010.

Although the coins were worth $41 at prices back then, at today’s price, the transaction is worth more than $200 million. To commemorate the event, the Bitcoin community celebrates Bitcoin Pizza Day every year on May 22.


Bitcoin / bitcoin / blockchain




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Convergence of blockchain with AI and IOT


IoT and AI are growing exponentially

Internet of Things – IoT

A future of transacting intelligent machines


• Individually, each of these technologies deserves all the attention they’re getting as enablers and disruptors

• But, taken together?

• Their transformative effect becomes multiplicative

A future driven by machine connectivity, data exchange and commercial services:

  • IoT connects billions of machines and sensors generate unprecedented quantities of real-time data
  • AI enables the machines to act on data and trigger services
  • Blockchain functions are the transaction layer where data and service contracts are securely stored and payments for services are settled

How does blockchain support intelligent connected machines?


Smart Contracts enable self-executing and self-enforcing contractual states

  • Custom financial instruments (tokens), records of ownership of an underlying physical asset (smart property), any
  • complex business logic that can be programmable
  • Can such applications be ideal for intelligent (AI) and connected (IoT) machines?
  • These machines are intelligent enough to negotiate contracts, but need a technology allowing them to securely sign and enforce them

Digital currencies create new forms of money

  • Programmable and active
  • Will such money be ideal for intelligent (AI) and connected (IoT) machines?
  • These machines will need digital currency to pay for services assigned through the smart contracts

How will the three technologies work together?


IoT – Internet of Things

  • Sensors allow us to cost-effectively gather tremendous amounts of data.
  • Connectivity allows us to transmit/broadcast these data.
  • But, there is a missing element: intelligence to process these data.

AI – Artificial Intelligence

  • Intelligence at the very edges of the network (mini-brains).
  • Combine with IoT and you have the ability to recognize meaningful patterns buried in mountains of data in ways that would be impossible for most humans, or even non-AI algorithms, to do.
  • But, there is a missing element: a secure storage layer for data and a transaction layer for services

DLT (blockchain) – Distributed Ledger Technology

  • Decentralized governance, coupled with no single point of failure, disintermediation, unalterable and searchable records of events.
  • Digital currencies and tokenized custom financial instruments.
  • Combine with AI and IoT and you have a new world of autonomous systems interacting with each other, procuring services from each other and settling transactions.

The technology stack of the future


Technology Stack of the Future

Toward a world of machine commerce


A world of Machine Commerce

M2M will need SSI (self-sovereign identities) – for objects!


Human Identities types

Object identities can be SSI by default

  • Multi-source, multi-verifier
  • Digitally signed, verifiable credentials that can prove issuer, holder and status
  • Secure peer-to-peer connections (permanent or session-based)
  • Exchange full credentials, partial credentials or ZKPs derived from credentials

Next milestone: Decentralized Organizations (DOs)


DOs are good at:

  • Coordinating resources that do not know/trust each other (including hybrid
  • H/M)
  • Governing in a geography-agnostic, censorship-resistant manner
  • Enabling short-term or informal organizational structures  (networks/communities)
  • Tracking and rewarding contribution

Challenges

  • Jurisdictional issues
  • Legislating new types of work for humans and work rules for machines
  • Governance modalities, including external supervision


Challenges


New/upgraded system architectures

• From legacy to blockchain/AI/IoT-native systems
• Integration, interoperability, backward compatibility
• ROI obvious ex post, difficult ex ante – Bootstrapping

Advanced analytics capabilities

• As devices at the edge become smarter, the smart contracts enabled by blockchain platforms will require more advanced data analytics capabilities and gateways to the physical world.

New Business Models

  • Disruptive innovation will dominate – but not without boom-and-bust cycles and big failures along the way.
  • Winners will NOT be the ones focusing on efficiency gains, but on disruptive models.

Key takeaways

• IoT, AI and DLT (blockchain) are foundational and exponentially growing technologies

  • When combined, they will create a new internet of connected, intelligent and commercially transacting machines
  • An era machine-to-machine (M2M) and human-to-machine (H2M) commerce is likely to emerge, with profound consequences on social and economic dynamics
  • New forms of corporations or organizational formats (code-only, autonomous) will emerge

• There are numerous challenges that must be overcome

  • IoT has outpaced the human internet, but is still a largely passive, insecure and privacy-vulnerable network
  • AI has made huge leaps, but still requires immense computational resources and is largely incompatible with edge computing
  • DLT is a new technology, largely untested at scale; both smart contracts and digital assets lack the regulatory clarity required for mass adoption

This work is available under a Creative Commons Attribution-Non-Commercial-No Derivatives license
© University of Nicosia,
Institute for the Future, unic.ac.cy/blockchain





With 💚

A.I.


Artificial Inteligence

Can computers be ‘intelligent’?

AI is about machines performing tasks normally requiring human intelligence

  • Visual perception, natural language processing, complex decision making (automated reasoning), artificial creativity, etc.
  • “AI is whatever hasn’t been done by computers yet” (Larry Tesler’s Theorem)
  • When AI solves a problem, it stops being considered AI and becomes part of everyday computing
  • So, in 1998, playing chess and optical character recognition were considered AI applications
  • Now, AI is more about autonomous robots and self-driving vehicles
  • In a few years time, these applications might not be considered AI anymore
  • AI is crossing into our everyday lives:
  • Face recognition, digital assistants, language translation and other applications on our mobile phones
  • New computer interfaces (e.g. non-invasive brain-machine interfaces)


Stages of AI

Artificial Narrow Intelligence (ANI)

  • Also known as Weak AI
  • Machines can perform a narrow set of specific tasks (e.g. play chess, sustain a dialogue with a human, identify faces in a picture, etc.)
  • Machine learning can be based on rules (reactive AI) or examples (limited memory AI)
  • Today’s AI is ANI

Artificial General Intelligence (AGI)

  • Also known as Strong AI
  • Machines possess human-like abilities to think and make decisions (theory of mind AI, self-aware AI)
  • In AGI, machines will be able to keep on learning by experience and develop their intelligence, much like humans do (but, presumably, faster and deeper)

Artificial Super Intelligence (ASI)

  • This is just a hypothesis at this stage: machines with AGI might one day reach a stage where they are collectively (much) smarter than humans
  • Singularity

Enterprise AI Companies – 2020


Sources:

https://topbots.com/
https://techreaserchonline.com/
https://muted.com/
https://rmit.edu.au/




With 💚