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iDate: AI and blockchain


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Will the highly hyped technologies change telco and media industries? - Presented by Bertrand Copigneaux, IDATE at London Breakfast Club on 11 Sep 2018


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iDate: AI and blockchain

  1. 1. AI and blockchain Will the highly hyped technologies change telco and media industries? Bertrand Copigneaux - IDATE Bertrand COPIGNEAUX +33 (0)4 67 14 44 05
  2. 2. AI and Blockchain Seeing beyond the buzz words
  3. 3. © IDATE DigiWorld 2017 – p. 3 The Buzz words of our time There’s a need to see beyond the buzz to understand the strategic implications of these technologies, in the short and long term.
  4. 4. © IDATE DigiWorld 2017 – p. 4 AI – Blockchain a comparative analysis The technology foundations Defining what we’re talking about exactly Looking at the origins of the technologies Understanding the basic technological principles and the recent innovations Short term applications What’s happening today ? What is commercially available ? Long term vision What are the current limitations ? What remains to be solved ? What these technologies might become ? What are the potential impacts ? Which actors to benefit ?
  5. 5. AI – Blockchain : Technology Foundations What’s really in there ?
  6. 6. © IDATE DigiWorld 2017 – p. 6 AI Technology Foundation Artificial Intelligence can be defined in several ways:  Autonomy: The ability for a machine to act on its own, perceiving its environment, and taking actions to maximize its chances of success in a defined task  Problem solving: The ability for a machine, given defined inputs to produce outputs that maximize predefined criteria of success.  Machine Learning: The ability to get better over time at a defined task. Or said differently, the ability for a machine to progress autonomously at problem solving.  Automation  Robotics  IoT  Algorithmic  Machine Learning  Deep Learning
  7. 7. © IDATE DigiWorld 2017 – p. 7 AI Training and Predictions Machine Learning, is the ability of a computer to perform tasks that go beyond the initial static programming instructions it received. The core principle of Machine Learning is to be able to “train” a computer program on a data set so that, once trained, it can make use the defined model to make prediction on its own given similar data. “Predictions” include: detection of patterns, categorization of inputs, sorting, predicting future trends, etc. “Predictions” retains a strong dependency on the data fed to the algorithm
  8. 8. © IDATE DigiWorld 2017 – p. 8 A.I. Technology Foundation - Summary  A data analysis technology  A large range of applications Key Benefit: - Software that Evolve, Learn, Predicts
  9. 9. © IDATE DigiWorld 2017 – p. 9 Blockchain : Technology Foundations Blockchain (or DLT) is a data storage technology Various implementations co-exists and compete Not limited to a specific application type or domain Blockchain is an information storage technology: Decentralized There is no need of a central authority « Trusted Third Party » to validate and store information. Duplicated Numerous synchronized are kept, ensuring the resilience of information. Immutable Everything that is written in a blockchain is written there forever, with no possibility of modification or suppression. Authenticated Everything written in a blockchain is linked in a unique and verifiable way to a unique user (pseudonymous). Public Some of the most notorious blockchain are publicly open both for reading and writing, others require permissions.
  10. 10. © IDATE DigiWorld 2017 – p. 10 Evolutions of Blockchains Ledger for all manner of information Registry for any type of data Today the Bitcoin blockchain is still the most heavily used, but a host of alternative initiatives have emerged for storing all types of information in blockchains. Use case: Transaction Ledger • A common history easily verifiable (audit) • Guarantee against « double spend » transactions • Without necessity of a third party authority acting as regulator and control of transactions. Use case: Archive and timestamping • Clear authentication of owners • Precise datation of when a data has been inserted in the blockchain • Data is stored in a secure, decentralized, and immutable database.
  11. 11. © IDATE DigiWorld 2017 – p. 11 Evolutions of the blockchain Automated conditional transactions The parties define the contract The contract is a set of rules The programme is stored in a blockchain It is stored in a computer programme that codes these rules The nodes of the blockchain network execute the programme Smart contracts Financial transactions are executed when the contract’s conditions are met. The contract is automatically executed by the network nodes: no intermediaries Source: IDATE DigiWorld, Blockchain, October 2016
  12. 12. © IDATE DigiWorld 2017 – p. 12 Blockchain Technology Foundation - Summary  A data storing technology  Many variations around a few common principles (Decentralization, Duplication, Authentication, Immutability)  Many Evolutions and Application:  Ledger of Transactions  Archive  Timestamping  Automated Transactions (i.e. Smart Contracts)  Decentralized Applications Blockchain is a technological disruption in secured infrastructure. • Secure and immutable data storage • With no need for a trusted third party Key Benefit: - An infrastructure to share data between people with varying, potentially competing, interests. - without anyone having a full control of the storage infrastructure.
  13. 13. © IDATE DigiWorld 2017 – p. 13 AI and Blockchain compared
  14. 14. AI – Blockchain : Short Term Applications What’s really happening ?
  15. 15. © IDATE DigiWorld 2017 – p. 15 AI – Image Recognition The initial application case for Deep Learning is the field of computer vision, and more specifically image recognition. Applying Deep Learning to Image Recognition has enabled dramatic progresses with computer being able to reach success rates around 95%, close and sometime better than human results. The potential field of application include: • Factory: identifying defective products in assembly lines • Medical: imagery analysis • Security: face recognition and identification • Social network / advertising: better identify user habits and preferences
  16. 16. © IDATE DigiWorld 2017 – p. 16 AI – Natural Language Processing Natural Language Processing is another field in which Deep Learning has enabled important progresses. Error rates in speech recognition has dropped to level comparable to human performances. AI also enables progresses in semantic processing and text generation with application in user interfaces and translation.
  17. 17. © IDATE DigiWorld 2017 – p. 17 Virtual Assistants Amazon Echo Alexa 31 millions unit (US – 12/17) Google Home Google Assistant 14 millions unit (US) Apple HomePod Siri 600 000 in Q1 2018 (world) The progresses in Natural Language Processing led to the development of a new UI : Virtual Personal Assistants (VPAs) They are marketed as intelligent assistants able not just of understanding but of taking decisions, supporting and potentially replacing human in several tasks Yet for now usage concentrate on mundane tasks
  18. 18. © IDATE DigiWorld 2017 – p. 18 Data Analytics Applying deep learning to a field where algorithms are already ahead of most humans, such as data analytics, promises potential tremendous breakthroughs. Using deep learning approach can help in health record data analysis to improve diagnostics, risk analysis and preventive medication. The Mount Sinai hospital recently showed the potential of using unstructured deep learning on the secondary use of electronic health records to predict health status, as well as to help prevent disease or disability.
  19. 19. © IDATE DigiWorld 2017 – p. 19 Blockchains : Cryptocurrencies and FinTech Far from being a threat, the blockchain opens up major opportunities for the financial industry. Cryptocurrency economy Optimise traditional processes •Exchange platform •Wallet app •Price speculation •Loans & investments •Blockchain audit •Private blockchain & back-office •International interbank payments •Capital market •Smart contracts for payments when due, or on delivery •Insurance •Shareholder agreements Thanks to massive financial backing, the blockchain's financial applications still account for the majority:  A banking system rebuilt around cryptocurrencies  Using the blockchain to streamline traditional services’ costs
  20. 20. © IDATE DigiWorld 2017 – p. 20 Blockchains : The ICO Model Implementing decentralized apps relies on a financing model that takes advantage of the possibilities opened up by the blockchain and cryptocurrencies. Source: IDATE DigiWorld, Blockchain, October 2016 Key Benefit: - Getting Funds without diluting shares - A “Trendy” way to attract funds
  21. 21. © IDATE DigiWorld 2017 – p. 21 Blockchain and ownership records The blockchain can be used as a register for all types of property. A unique and reliable record of ownership, shared by an entire ecosystem. Register diamonds and artwork to: •Facilitate police inquiries •Detect insurance fraud •Facilitate loans and swaps •Provide traceability and past history Food supply chain traceability: • Food associated with a digital tag • The tag refers to a blockchain entry • Information added at each step of food processing along the supply chain • End customer get access to life cycle Music royalties payment •Free streaming and download to own services (5% commission) •Use the cryptocurrency principle for crowdfunding for artists. Experimenting with blockchain for national land registries •Rapid audit •Faster procedures •Tamper-proof National land registries
  22. 22. © IDATE DigiWorld 2017 – p. 22 Blockchain and Insurance: Smart Contract Smart Contract maturity is still limited but first large scale commercial use start to appear Based on smart contracts using the Ethereum Blockchain Automatic compensation in case of flight delay (bet on your flight delay) Live but still in test phase, need to attract partners for the blockchain approach to make sense.
  23. 23. © IDATE DigiWorld 2017 – p. 23 AI and Blockchain compared Cryptocurrencies AI Blockchain Quite Mature Mostly Proof of Concepts Image Recognition NLP VPAs ICOs Ownership records Smart Contracts Financial Back Office tool Advanced Data Analytics
  24. 24. AI – Blockchain : Long Term vision What they might become
  25. 25. © IDATE DigiWorld 2017 – p. 25 AI Long Term Vision Extending the use of Deep Learning to a large range of use case to extract knowledge out of data
  26. 26. © IDATE DigiWorld 2017 – p. 26 AI Long Term Vision Dreaming of beyond human capabilities… > Artificial Narrow Intelligence (ANI)  Specialized in a single task > Artificial General Intelligence (AGI)  Equivalent to a human intelligence > Artificial Super Intelligence (ASI)  Beyond human capabilities 2000 2100 Today Median Expert Prediction For AGI (2040) Median Expert Prediction For ASI (2060)
  27. 27. © IDATE DigiWorld 2017 – p. 27 AI Current Limitations VPA use and capabilities are still limited. • Mostly use as a “hand free” user interface / gadget • User acceptance is still limited • Still largely unable to : follow a conversation, take context into account, learn over time and be personalized and proactive. Deep learning is strongly dependent upon data. • Requires availability of large data sets (not the case for every use case) • Data access can be an issue (data ownership, data monetization, privacy…) • Training algorithms and validating the quality of the result on more complex tasks than basic image recognition / NLP can be an issue. AGI and ASI are still hypothetical. • There is no certainty that these level of AI are reachable and that the current solutions (deep learning) will lead there.
  28. 28. © IDATE DigiWorld 2017 – p. 28 AI Main Benefitors The key is in the control of the data B2C : A new way to lock-in customers for internet giants B2B : Opportunities for data platforms
  29. 29. © IDATE DigiWorld 2017 – p. 29 Blockchain Long Term Vision Traditional economy Provide a product or service Decentralized economy Eliminate the middlement Internet economy Put parties in contact A disruptive vision: Bold claims: • Cryptocurrencies replacing fiat currencies • Decentralized applications competing with Internet Giants • …
  30. 30. © IDATE DigiWorld 2017 – p. 30 Blockchain Current Limitations Performances: limits of « Proof of Work »: Number of transactions per seconds (TPS) Resources consumption. Today, no clear alternative to proof of work with the same level of maturity and security (consensus algorithm is a research topic). Smart Contract: a technology lacking maturity Smart contracts cannot be considered today as a stable and mature technology except for minimal use cases. Research topics: limitations of programming languages (non turing complete) formal proof and code validation… Security at the system margins Several important stake appear in the end-to-end security of blockchain solutions: Identity validation, interoperability with legacy systems and data, validation of data entered in a blockchain (oracle role). These developments are necessary to go from PoC to production. Acceptance and legal issues The world of cryptocurrencies remains mostly separated from the rest of the economy and very unstable An area of speculation and uncertainties unfit for acceptance
  31. 31. © IDATE DigiWorld 2017 – p. 31 Blockchain Main Benefitors The blockchain enables organizations to reduce their operating costs, particularly in the area of inter-organization exchanges (shorter timeframes, increased reliability). It can also help reduce the number of intermediaries involved in certain types of application. By and large, however, it is no expected to upset existing value chains. The blockchain, B2B infrastructure: The blockchain as back-office infrastructure for transactions between established players: banks, businesses, platforms, government agencies. Exchanges between consumers and producers still go through trusted third parties. Main Benefitors: - IT suppliers have a new set of solutions to sell
  32. 32. © IDATE DigiWorld 2017 – p. 32 AI and Blockchain compared extending existing successes to other fields : big data processing and predictions, general intelligence, beyond human capabilities… Good for financial back office, ownership records, supply chain data exchange, automated financial transactions A.I. A secure infrastructure for sharing information with parties with differing, potentially conflicting interests Solving complex problems by learning from very large data sets Blockchain Good in Computer Vision, Natural Language Processing, and more generally data analytics Going out of the sandbox and proof of concepts and establishing a new kind of infrastructure What it is? What it is good for? The challenge ahead?
  33. 33. © IDATE DigiWorld 2017 – p. 33 IDATE DigiWorld is one of the foremost European ICT expert houses specializing in telecom, media & internet markets and digital territories. Since 1977, our team has delivered consultancy services, market intelligence solutions & networking opportunities to provide an in-depth understanding of the digital world and enhance our clients’ strategic decision-making. We are proud that every year more than 400 public bodies & multinational companies all over the world renew their trust in our services. Learn more about our three activities: Yearly programme • Executive Clubs • DigiWorld Summit • DigiWorld Future • DigiWorld Economic Journal • DigiWorld Yearbook • DigiWorld Watch • Collaborative Research Reports & Datasets • FTTx & Gigabit • Wireless 4G & 5G • Digital Telcos • Internet of Things • Future TV & Video Consulting Services • Market & usage analysis • Feasibility studies • Strategic coaching • Public policies • Training & Communication
  34. 34. © IDATE DigiWorld 2017 – p. 34 AI Neural Networks Deep Learning, is a form of Machine Learning building on the “Neural Network” approach (that dates to the 80s) They function by defining small and simple individual programs, artificial neurons (called Perceptron) The Artificial Neurons are then connected together and arranged in a network Through repeating a long training process, the weights of the connections, transfer and activation functions of each Neuron can then be optimized to take values that enable the overall network to provide the requested answer.
  35. 35. © IDATE DigiWorld 2017 – p. 35 AI Neural Networks The Deep Learning trend started at the end of the 2000s, as both very large data sets and computing power became largely available. In Deep Learning, layers of large numbers of Artificial Neurons are stacked together. Low level layers are able to find basic patterns that are refined into more and more abstract concepts by each layer.
  36. 36. © IDATE DigiWorld 2017 – p. 36 Blockchain : Technology Foundations Transaction … Transaction … … Blocks aggregate transactionsA chain of « blocks » What is a blockchain ? Blocks are added at the end of the chain The network verifies collectively that the new block is valid Once added blocks cannot be deleted Adding information in a blockchain requires validation by a peer-to-peer network         
  37. 37. © IDATE DigiWorld 2017 – p. 37 Evolutions of Blockchains Transaction ledger Ledger for all manner of information Automated conditional transactions Decentralized applications Smart contractsCryptocurrencies 2008 – The idea of Bitcoin emerges in response to the financial crisis: an alternative, decentralized currency that is independent of both political powers and financial institutions, governed solely by mathematical and cryptographic principles. 2009 – The first blockchain originated with Bitcoin. It is a ledger that logs all of transactions made, and stored securely in a distributed network.Financial Registry Initially designed as a ledger for cryptocurrencies, the principles that underpin the blockchain have evolved over time. Source: IDATE DigiWorld, Blockchain, October 2016
  38. 38. © IDATE DigiWorld 2017 – p. 38 New decentralized applications If we can store and execute computer programmes on a blockchain network… Decentralized applications … We can create fully decentralized applications, and even organisations. The blockchain network is used as the infrastructure for decentralized apps. Fully peer-to-peer applications with no centralized platform. Decentralized organisations and businesses entirely managed by smart contracts, with no administrators or employees. Source: IDATE DigiWorld, Blockchain, October 2016 Evolution of Blockchains