Contenu connexe
Similaire à AI and Blockchain 2017 (20)
Plus de Peter Morgan (11)
AI and Blockchain 2017
- 17. Blockchain – A Definition
At its most basic, blockchain is a vast, global distributed
ledger or database running on millions of devices and open to
anyone, where not just information but anything of value –
money, titles, deeds, music, art, scientific discoveries,
intellectual property, and even votes – can be moved and
stored securely and privately. On the blockchain, trust is
established, not by powerful intermediaries like banks,
governments and technology companies, but through mass
collaboration and clever code. Blockchains ensure integrity
and trust between strangers. They make it difficult to cheat –
HBR, May 2016
17© Ivy Data Science
- 18. Blockchain
• Distributed digital ledger - an entirely decentralized system
• Invented by Satoshi Nakamoto in 2008 (inventor of bitcoin)
• A technology that is revolutionizing the financial services industry by
empowering millions across the globe to authenticate and transact
immediately without costly intermediaries
• Design goal is to speed up and simplify how transactions are recorded
• Any type of asset can be transacted using the blockchain
• Makes possible a currency without a central bank
18© Ivy Data Science
- 19. Blockchain
• Can be public or private
• Bitcoin is an interesting application for blockchain but there are
thousands of applications and wider use cases beyond that - every kind
of digital record and transaction
• Settlement and clearing time is reduced to seconds
• The distributed ledger is replicated on thousands of computers around
the world
• Kept secure by encryption algorithms
• May in time spur new changes in how companies and governments work
19© Ivy Data Science
- 24. Opportunities
• Disruptive new technology providing opportunities to innovate
• Introduce new products and services
• Reduce costs of existing services by
• Introducing process efficiencies
• Automating existing services
• Significantly reduce transaction costs
• According to White & Case, Blockchain could reduce banks’ infrastructure
costs worldwide by $20 Billion a year by year 2022*
• Significantly reduce transaction times (days to seconds)
• The next Google or Facebook?
*http://news.crowdvalley.com/news/state-of-blockchain-and-artificial-intelligence-ai-in-fintech
24© Ivy Data Science
- 25. Risks & Challenges
• Security
• Bitcoin & Ethereum cryptocurrencies have both been hacked
• New safeguards put in place each time to close vulnerabilities
• Environmental
• Impact on environment due to energy required to run network
• Expensive equipment
• Cryptocurrency mining (data centers)
• Interoperability
• There will likely be many blockchains
• The ability to work with other banks’ and partners’ blockchain technology
• The idea of making trust a matter of coding, rather than of democratic
politics, legitimacy and accountability, is not necessarily an appealing or
empowering one
25© Ivy Data Science
- 26. Blockchain Applications
• Legal agreements (contracts)
• Finance
• Cryptocurrency - peer-to-peer version of electronic cash
• Other asset classes (bonds, commodities, etc.)
• Credit Suisse has conducted 10 proofs of concept with blockchain startups to achieve cost reductions
• Autonomous vehicles
• Transportation infrastructure
• Accommodation
• Hotels, apartments, smart locks
• Energy grid
• Internet of Things
• ”The Internet of Everything needs a Ledger of Everything”
• Supply chain management
• Things that haven’t been thought of yet
• Blockchain as a Service
26© Ivy Data Science
- 28. Examples - Bitcoin
• First decentralized digital currency
• Invented by an unidentified programmer, or group of programmers, under the
name of Satoshi Nakamoto, bitcoin was introduced on 31 October 2008
• Like paper money and gold before it, bitcoin is a currency that allows parties to
exchange value
• Platform for innovation with open source code
• Bitcoin is mathematically limited to 21million bitcoins and that can never be
changed
• People store Bitcoin in software called a wallet, available for most devices
• More and more businesses are accepting Bitcoin payments (>100,000)
• Can be mined, or bought from one of the trusted exchanges – asset class
• https://www.youtube.com/watch?v=Gc2en3nHxA4
28© Ivy Data Science
- 30. Examples - Ethereum
• Ethereum is a decentralized platform that runs smart contracts
• Applications that run exactly as programmed without any possibility of
downtime, censorship, fraud or third party interference
• Runs on a custom built blockchain shared global infrastructure - moves
value around and represents the ownership of property
• Enables developers to create markets and many other things that have
not been invented yet, without a middle man or counterparty risk
• Offers a range of services that are not possible using bitcoin
• Initially proposed in late 2013 by Vitalik Buterin
• Github site https://github.com/ethereum/
30© Ivy Data Science
- 33. Blockchain Organizations
Hyperledger Project https://www.hyperledger.org
• Open-source blockchain project that will allow businesses to build a
cross-industry distributed ledger solution
• Lead by IBM and the Linux Foundation, members include Cisco, Intel,
Accenture, ANZ Bank, Digital Asset, Fujitsu, State Street, LSE, SWIFT,
Vmware, JPMorgan and Wells Fargo
• IBM is contributing tens of thousands of lines of existing code to the
project, as well as dedicated developers and intellectual property
• Github repo: https://github.com/hyperledger
Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 33© Ivy Data Science
- 34. Blockchain Organizations
R3 http://www.r3cev.com
• Studying how trading of securities, derivatives and loans can be overhauled by
using distributed ledger and blockchain technology
• Includes more than 70 banks including Bank of America, Citigroup, Deutsche
Bank, Morgan Stanley, SocGen, Barclays, Goldman Sachs and JPMorgan
EEA http://entethalliance.org
• Thirty member companies including JPMorgan, BP, Microsoft and Intel
• Will work to enhance the privacy, security and scalability of Ethereum
blockchain
• Make it better suited to business applications
Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 34© Ivy Data Science
- 35. IBM & Blockchain
• IBM offers Blockchain as a Service (announced this Monday)
https://www.ibm.com/blockchain/getting-started.html
• Create private and secure digital assets in test applications that can be traded quickly
and securely over a permissioned network
• Uses hyperledger fabric
https://hyperledger-fabric.readthedocs.io/en/latest/
• This is also on github
https://github.com/hyperledger/fabric/blob/master/docs/source/index.rst
• In June 2016, IBM opened an incubator in Singapore where 5,000 computer scientists
work to build rapid prototypes using the company’s blockchain and Watson AI tools for
businesses in the APAC region
• "Watson and blockchain are two technologies that will rapidly change the way we live
and work” – Randy Walker, IBM CEO APAC
Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 35© Ivy Data Science
- 36. Microsoft & Blockchain
• Blockchain as a Service
https://azure.microsoft.com/en-us/solutions/blockchain/
• Ethereum Blockchain as a Service on Azure
https://www.oreilly.com/topics/data-fintech
• Project Bletchley is Microsoft’s Blockchain Architectural approach
https://github.com/Azure/azure-blockchain-
projects/blob/master/bletchley/bletchley-whitepaper.md
• Open source code is on github
https://github.com/Azure/azure-blockchain-projects/tree/master/bletchley
• They learned that Consortium blockchains, which are members-only,
permissioned networks for consortium members to execute contracts, are ideal
Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 36© Ivy Data Science
- 40. State Street
• Blockchain-based indices
• 64% of wealth and asset managers polled expected their firms to adopt
blockchain in the next five years – State Street Report
• Further, 50% of firms said they expect to employ artificial intelligence
• Data is stored and made secure using Blockchain - AI can analyze the
data while it remains secure
• "You, in theory, can now put all that data on a blockchain," Maiuri said.
"I can never take possession of it, but I can ask questions of the data.”
• Turn unstructured data turned into a structured instrument
Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 40© Ivy Data Science
- 43. Blockchain & Watson
• Integrate Watson with the IoT
• Watson IoT Group – “Intelligent IoT”
• Let devices perform tasks like running self-diagnoses at set times
• Risk management – how blockchains might be used to make devices safer
for their users, in part by reducing human involvement in their operation
• Using blockchain tech, artificially intelligent software solutions could be
implemented autonomously
• An artificially intelligent blockchain will let joint parties collectively agree
on the state of the device and make decisions on what to do based on
language coded into a smart contract
Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 43© Ivy Data Science
- 47. References
• Ethereum Blockchain as a Service now on Azure https://azure.microsoft.com/en-
us/blog/ethereum-blockchain-as-a-service-now-on-azure/
• Blockchain A to Z http://www.pcmag.com/article/344969/blockchain-a-z-
everything-you-need-to-know-about-the-game-c
• Banks are sold on blockchain
https://www.americanbanker.com/news/banks-are-sold-on-blockchain-concerned-
about-collaboration
• Banking on Blockchain – Accenture Report
https://www.accenture.com/us-en/insight-banking-on-blockchain
Books
• Tapscott, Dan - Blockchain Revolution, Portfolio, 2016
• Tale, Steve – Blockchain Technology, CreateSpace, 2017
© Ivy Data Science 4747© Ivy Data Science
- 50. AI In Industry
• “Just as 100 years ago electricity transformed industry after industry, AI will
now do the same.” - Andrew Ng, Chief Scientist at Baidu
• Deep learning produces real results and is at the root of a real industry that
makes money today. The promises of it in the near future are very exciting...
in areas like self-driving cars, medical imaging, personalized medicine,
content filtering/ranking, etc-- Yann LeCun, Facebook AI Research
• Some of the ways these techniques have now started to be deployed in
industry include healthcare, transportation, robotics, AI Assistants, chatbots,
education, satellite imaging, speech recognition and language generation
• In addition to these various applications, deep learning and other techniques
in AI will soon impact additional areas ripe with new challenges, including
video understanding, security, public safety, and the Internet of Things
© Ivy Data Science 50© Ivy Data Science 50
- 52. Mentorship
• Company Mentors - AI teams at leading companies from diverse sectors and sizes
who will share the problems they are currently solving
• Industry and Open Source Leaders - Pioneers at the forefront of Artificial
Intelligence that help you learn best practices & disruptive trends in the industry
• Your Fellows – Experienced, ambitious scientists, researchers, and engineers with
common goals and a diverse set of skills that complement yours. Learn the way you
do in the industry, by collaborating and working through challenges with your peers
• Ivy Data Science Alumni – Fellowship Alumni from our Artificial Intelligence
program have transitioned into AI roles at top companies. They provide
individualized guidance and practice with interviews
• Ivy Data Science Team - Ivy Data Science offers continued guidance throughout the
entire process. We point you to the right resources to help troubleshoot tough
issues
© Ivy Data Science 52© Ivy Data Science 52
- 57. Applied AI
• Finance
• Healthcare
• Transportation
• Robotics
• Personalized AI Assistants
• Video Understanding
• Security
• Public Safety
• Education
• Etc.
© Ivy Data Science 57© Ivy Data Science 57