Euskal Encounter inspiration

Every year late July I attend the Euskal encounter. A meeting of over 8,000 computer enthusiasts who gather to share their passion. For me this is an opportunity to catch up with old friends and discuss our vision of the state of the industry and the future to come. I have seen it evolve over 25 years from the early days when it was a meeting of amiga demoscene fans to today where we have gigabit access to the internet, drone races and training of 10 year old future engineers who are helped to work together to build electric karts and race them.

Every year I obtain a few wisdom pearls that I take back with me and fuel my inspiration. These are the highlights I take with me this time as exciting material for investigation:

  1. Bime is a competitor to Tableau, Qlik, microsoft powerBI, and gooddata in the Business Intelligence space. Setting up a demo is easy and free, and it looks like a powerful front end for end user data analysis.
  2. Tmux is a program which allows you to, just opening one ssh connection to a linux server, split this terminal in as many windows as you like, allowing to split your workspace very flexibly and move fast thanks to keyboard shortcuts. It has similarities with screen.
  3. Terraform allows you to automatically provision your architecture in the cloud. My good friend @ibannieto gave a demo on this for beginners and showed us how easy it is to provision from scratch several machines in the Amazon, Microsoft or Google clouds and how to deploy software on these machines automagically with just a few lines of code.
  4. Awesome is a super lightweight linux window manager that allows to organise your desktop with very powerful keyboard shortcuts and taking up very litte resources. This is ideal when you are running linux on a 10 year old laptop with no resources to spare, as is my case in this occasion.
  5. Google Data Flows is a google ETL service which can manage your data integration needs for real time and batch integration capable of managing massive amounts of data.
  6. Data lakes are a way of storing massive amounts of data without the need for too much structure, allowing for future querying of this data. Hadoop is a data lake which allows for these massive amounts of data distributed amongst thousands of machines to be queried using simple programming models.
  7. Fusion4energy is an exciting european project aiming to bring sustainable energy to the world by using nuclear fusion. Different to nuclear fision, fusion would cause no nuclear residue and would be a revolutionary source of clean energy. Fusion has already been achieved producing Megawatts of energy, the only problem being that it produced less energy than it consumed.
  8. Reveal is a very cool software to create impacting presentations using html. It allows to integrate gifs, video, dynamic content, in a way that microsoft powerpoint can’t.
  9. Drone racing was one of the new surprises of this year’s euskal encounter. The drivers wear headsets with which they see what their flying drone sees and they race at vertiginous speeds through an obstacle race aiming to be the fastest without crashing.
  10. was for me the most inspiring of all. Maybe it’s due to my parenthood, but I was moved seeing the different teams of 10 year olds building their electric karts together. I find it crucial to inspire the future generations to take up the challenges of engineering. This way allows them to start easy and small in a fun and collaborative way.


How to mine Ethereum

Mining ethereum is an easy 5 step process:

  1. Get a computer with a powerful GPU or two
  2. Get an ethereum wallet here
  3. Download geth from here and run it like this in a cmd window (because if you have a powerful GPU or two you use it for gaming, hence you have a windows machine)
    1. geth.exe -rpc
  4. Download ethminer from here and run it like this in different cmd window
    1. ethminer.exe -G
    2. The -G parameter instructs ethminer to use your GPU instead of your CPU, which will be orders of magnitude faster at mining.
  5. You are set, you should see something like thisethminer

Now for the bad part. I have two GTX 1080 TI and I am getting around 62 MH/s. This means my computer is capable of taking the Ethereum block we are trying to solve, add it a random string and calculate the hash of it to see if the first ten characters are zeroes and therefore win this block. 62 million times every second. 

62 million times per second sounds like a lot! I should have good chances of winning a block once in a while. Taking into account a new block is generated every 15 seconds, I should have good chances..

The problem is that the Ethereum network has a hash rate capacity of around 60TH/s, this means that the number of hashes the network produces every second are one million times bigger than the hashes my computer produces. This gives me a chance of winning of one in one million every 15 seconds. Taking into account that the reward for winning is 5 ETH (approx 1,150 EUR), I have 1/1,000,000 chance of winning 1,150 EUR every 15 seconds if I leave my computer mining.. this does not sound too promising.

Business Intelligence state of the art

Usually when we need to understand our business’ numbers, we open Microsoft Excel and start applying filters, pivot tables and charts to try to gain insight on what story our data are telling us.

It’s 2017, Isn’t there a better way to do this?

I think it must have been around 2014 when I first heard about Tableau. I immediately liked the tool’s proposal: Easy tool to analyse data in real time without needing to be an expert in SQL, Olap cubes, or any technology. It could take as input for data any number of excel sheets, csv files, or database sources and would immediately allow the user to move the data around, establish relationships between sets of data and start visualising. I’m a visual person, I need to see things in graphical form to understand them, so I really like this concept. In the Gartner Magic Quadrant for Feb 2017, the 3 top players in the BI space by completeness of vision and capacity of execution are Tableau, Microsoft, and Qlik who offer similar solutions for front end analytics.

One of the weak points that I see in Tableau’s proposal is that it only addresses the front end, the data analysis, but leaves the back end, the data model, the origin of data, for you to deal with. In the past I’ve worked on a few data warehousing projects where the immense complexity was in creating a data model which made sense from a business perspective and which could grow with the business’ future needs. Designing the data model wrong was similar to shooting yourself in the foot, as future needs could not be adapted, changes would require refactoring of the whole data model and of the downstream systems which read from this data model and maintenance of this data model would be expensive and complex. In all cases I experienced in the past, creating a data model was similar to creating a monster which would grow in unforeseen and inelegant ways getting more rigid and patchy as time went by.

A good example of a world class level attempt at creating a data model for the capital markets world is  ISDA’s (International Swaps and Derivatives Association) FPML (Financial Products Markup Language). The data model they have birthed is immensely complex, as could not be different when the goal is to be able to map any financial instrument. Any attempt at using FPML as inspiration for your data model promises a long and complex project.

Three weeks ago, I attended Moneyconf. There I saw a company called gooddata which offers an interesting model: They take care of your Business Intelligence needs as a service. You send them your data, they organise it and offer you a Tableau style front end tool to visualise it. This would take care of all data warehousing troubles.. however I have some concerns:

  1. How do they know all the ways you need to structure your data model?
  2. Does this scale well with big volumes of data?
  3. How do they manage confidential data? Imagine I have medical records to manage…
  4. Is the front end tool as complete as Tableau?


The BI world is very cool looking. It brings promise of granting better insights and fancy looking charts, but, is the price tag worth it when we can always just grab an excel and start applying filters, pivot tables and charts to understand the story our data are telling us?


Hyperledger, IBM’s vision for a corporate DLT

In 2008, the first Distributed Ledger Technology (DLT) was created with Bitcoin. Immediately it became visible across industries that DLT technology could be very useful to transfer assets. As time passed, different implementations have come to light using the concept of the DLT which attempt to address different problems with different implementations of a similar idea.

One of these implementations is IBM’s Hyperledger. In late 2015, IBM partnered with 17 other companies:

  • Blockchain software vendors such as Digital Asset, or R3
  • Technology platform companies such as Intel, RedHat or VMWare
  • Financial services firms such as CME, DTCC, Deutsche Borse, Swift or JP Morgan
  • System integrators such as Accenture.

The Hyperledger project’s governance is chaired by Blythe Masters (Ex-JP Morgan Executive, CEO of Digital Asset) under the Linux Software foundation. This open governance allows the open source community to contribute to the project, read the source code, download it for free and use it to create new software.

The vision for Hyperledger is a tool for confidential asset transfers in an enterprise environment. These assets can be of any nature: Securities, gold, legal contracts, wills, patents, medical information… Key differences with other DLT solutions such as Ethereum, are that there is no cryptocurrency involved and that access to transaction information is restricted with access rights. Whereas in Ethereum every miner node has a copy of the whole blockchain and can access all the information of any transaction, in Hyperledger all information is encrypted, and only thanks to having the right access rights can you decrypt and access certain information. In a corporate environment this would be a mandatory requirement as you may want to give one client a 10% discount without all your clients knowing about this.

Some interesting projects going on in the corporate world using Hyperledger:

  • CLS is working on a payment netting service
  • DTCC is building a DLT based derivatives processing platform
  • Japanese Stock Exchange is testing DLT for trading environments
  • Walmart is building a platform with Hyperledger to track where a Pork chop came from in 7 minutes instead of the current 7 days
  • Digital Asset are building a tool that will leverage hyperledger to offer DLT to the financial services community.
  • Northern Trust has built a DLT for private equity

Currently there are hundreds of players in the DLT world, in my view the top 4 are R3 Corda, Ethereum, Bitcoin, and Hyperledger. It is hard to tell who will come out ahead in the end, but Hyperledger is certainly worth keeping an eye on.



Bentham, Kant, and AI-driven cars

Imagine you are driving your car at 90kmh, and you realize the brakes are not working. 20 meters ahead of you, crossing the street, are five people who will inexorably die if you run them over. Looking to your right you see one person which is sitting in a terrace eating an ice cream. Your steering wheel is working well, so you could steer your car towards the terrace killing one person, but sparing the five.

What would you do? Most people would choose to kill the one person to spare the five. Sacrificing one life in order to save five seems the right thing to do.

Now imagine you are standing on a bridge overlooking the road. Down the road comes the brakeless car, and at the end of the road are five people who are about to die run over by this car.

You feel helpless to avert this disaster, until you notice, standing next to you on the bridge, a very heavy man. You could push him off the bridge, on to the track, into the path of the car. He would die, but the five people crossing the road would be saved. To make your job even more similar to the previous example, this man is standing on top of a trapdoor which you could open by turning a car-sized steering wheel to the right.

Would you push the unsuspecting fat man? Most people would find it terribly wrong to push the man onto the track. But this raises a moral puzzle: Why does the principle that seems right in the first case – sacrifice one live to save many – seem wrong in the second?

This example, taken from a beautifully taught Harvard online free course goes to explain how the consequentialist moral reasoning of Jeremy Bentham’s utilitarianism (it is the greatest happiness of the greatest number that is the measure of right and wrong) does not hold under the scrutiny of Immanuel Kant’s Categorical moral reasoning (Act only according to that maxim whereby you can, at the same time, will that it should become a universal law).

After 11th May 1997,when IBM’s Deep Blue beat human champion Garry Kasparov, no human will ever again, beat AI at chess.

After 27th May 2017, when Google’s Alphago beat human champion Ke Jie, no human will ever again beat AI at Go.

Once AI driven cars are mainstream, no human will ever again be allowed to drive.

While a human driver has visibility of 120 degrees, an AI has 360 vision from the car, through connectivity could simultaneously have 360 vision from other neighbouring cars, from traffic cameras, or from satellites. Other AI senses could come into play which the human counterpart does not have, for example an AI car could have sonar, similar to bats echoing a signal to detect proximity. An AI could have real time knowledge of where every other car in a radius of 10 kilometres is, in what direction it’s headed, and if it has any technical issue.

Human drivers get road rage, get impatient when sitting in a traffic jam, try to stick their car’s nose in front to gain one inch if possible… all these human behaviours cause traffic jams, accidents and inefficiencies. A perfect AI driver will have none of these traits, and thanks to this, traffic jams will be greatly, if not totally, reduced.

Having a human drive in the future will be as rare as having a human clean the clothes today. I could do it, but why woud I? I have a washing machine for that.

One human problem, is what to tell the AI to do when faced with the example at the beginning of this story. Should an AI follow Jeremy Bentham’s utilitarian principles? Should it choose to kill one to save five? This is particularly dangerous if we will also want the AI to perform surgery, as in order to save 5 patients who needed a heart, a lung, a kidney, a liver, and a stomach, it could choose to kill and butcher a perfectly healthy patient which had just gone to have a regular check-up in order to get the needed organs.

In the brink of a new era, these classic, unresolved questions are more important than ever.



#Moneyconf – 65 insights from C-level fintech executives

This week I attended moneyconf, a very interesting conference where startups and incumbents meet to discuss the future of fintech. Here are some wisdom-pearls I took away from c-level executives of multimillion incumbent companies and startups:

  1. “We spend 2.5 billion euro per year on innovation, to run the bank and to change the bank” Francisco González. President of Bbva
  2. “You have to change from inside the bank” Francisco González. President of Bbva
  3. “The core has to be built by ourselves. If it’s available outside we buy it and we bring it into our systems” Francisco González. President of Bbva
  4. “We had a Ferrari, the big mistake was not to pay attention to the rest of things, drivers, roads…” Francisco González. President of Bbva
  5. “The most important thing to change for incumbents is having the right management. We had to mix digitals and bankers.” Francisco González. President of Bbva
  6. “We alone could not go, we needed the help of the fintech companies” Francisco González. President of Bbva
  7. “The disruption of AI has nothing to do with fintech, because the world is going to fundamentally change.” – Neal Cross Chief Innovation officer DBS Bank
  8. “85% of all customer service requests are handled by chatbots.” – Neal Cross Chief Innovation officer DBS Bank
  9. “At Mastercard we enable people to move from one department/country to another they want to learn, to grow” – Anne Cairns President of Mastercard.
  10. “Financial inclusion starts with giving people a digital identity” – Anne Cairns President of Mastercard.
  11. banks will realise they need to be on a public or at least semi public network. Peter Smith. Founder and CEO
  12. “the Bitcoin core vs bicoin unlimited issue can be worked around by the industry by moving to other tokens ” Peter Smith. Founder and CEO
  13. “disruption is helping companies raise capital, that’s the innovation I’m interested in, not doing step 9 in the banking settlement process” Peter Smith. Founder and CEO
  14. “ ECB, EIB, can stimulate the real economy by lending to small businesses through LendingCircle” Samir Desai, Founder and CEO of Lending Circle
  15. “We return about 6.5-7% a year on our loans. Investors have made £120 million in net interest.” – Samir Desai, Founder and CEO of Lending Circle
  16. “The big thing now in Europe is PSD2. Banks will have to provide open API access to current accounts.” – Samir Desai, Founder and CEO of Lending Circle
  17. “P2P lending has proven to be resilient. Growth remains 60% even with Brexit” Samir Desai, Founder and CEO of Lending Circle
  18. “What banking will be in three years from now is not yet invented” Bernardo Sanchez Incera. Deputy CEO at Societe Generale.
  19. “Identity algorithms 20x safer than human.” Brett King, Founder and CEO of Moven
  20. “By 2025 the biggest bank will be a technology company, not a bank” Brett King, Founder and CEO of Moven
  21. “No human will be able to drive safer than a self-driving car. Decide on investments, build a car faster..” Brett King, Founder and CEO of Moven
  22. “The problem with banks is they think always in terms of iterating the branch model.” –Brett King, Founder and CEO of Moven
  23. “We’re seeing banking embedded into other services now. That’s when it is most useful, solving real problems.” –Brett King, Founder and CEO of Moven
  24. “A futurist is never being wrong today” Brett King, Founder and CEO of Moven
  25. “With etoro you can create an account in 60 seconds, fund it with your credit card and buy bitcoin.” Yoni Assia. Founder and CEO of EToro
  26. EToro launches Crypto-currency CopyFund to provide a straightforward way to invest in both Bitcoin and Ethereum online” Yoni Assia. Founder and CEO of EToro
  27. “Many financial services still run on fortran and cobol since the 70’s. Blockchain gives an opportunity to rethink all” David Rutter. Founder and managing partner at R3
  28. “11.000 computer scientists at goldman sachs. The challenge is to build fast and secure applications” Joanne Hannaford. Partner at Goldman Sachs.
  29. “Bitcoin or Ethereum blockchain will be used in the background, the user will not know. E.g @abra @epifyJon Matonis. Founding Director at Bitcoin Foundation
  30. “Any idiot can lend a dollar, it’s getting paid back that’s tricky” Douglas Merrill. Zest Finance.
  31. “The car will pay for gas, the phone for calls and data thanks to IoT” Ivan Glazachev. Yandex Money.
  32. “There is a huge fight to be the fintech capital of the world” Taavet Hinrikus. CEO of TransferWise.
  33. “Innovating to please ourselves vs innovating to please the customers” Yashish Dahiya. Founder and CEO at Policybazaar
  34. “People with +10y in the same company try to avoid the erosion. Younger folks see the disruption coming and want to ride it” Scott Walchek Founder and CEO of Trov
  35. “Innovation has to come from the top. Don’t do pilots. Anticipate your champions will move on. Appoint full time account mgmnt on both sides. Results will take time. Empower a steering committee with all stakeholders” Scott Walchek Founder and CEO of Trov
  36. “We are seeing and pushing a trend towards a cashless society” Rita Liu. Head of Alipay Europe, Middle East and Africa.
  37. “Payment technology has to be transparent, seamless” June Yee Felix. President of Verifone Europe.
  38. “In the past payment has been very complicated. People want to pay simply. Like Uber.” June Yee Felix. President of Verifone Europe.
  39. “San Francisco Venture Capital investment in fintech is double New York, which is double of all of Europe. 2 deals in China are bigger than San Francisco.” Sheel Mohnot Partner at 500Startups
  40. “EU regulatory sandox is a great idea we are pushing to get adopted in the US”  Sheel Mohnot Partner at 500Startups
  41. “Sharing of KYC information thanks to the blockchain can enable cross border payments in a regulated environment” David Thompson CTO at Western Union
  42. Western Union Reveals Pilot Coinbase Integration. David Thompson CTO at Western Union
  43. “Banks will do the back end, the Apples and Googles will do front end. As banks, we can’t prevent that happening.” – Anne Boden. CEO at Starling Bank
  44. “Trust comes from utility. I trust the bank because I can go to an ATM and get my money out. It works.” Brett King, Founder and CEO of Moven
  45. “70% of mobile payments in China are done by wechat and alipay, not by banks” Brett King, Founder and CEO of Moven
  46. “Banks will reduce their workforce 40% by 2025, but there are not enough AI people …yet” Roman Stanek, CEO of GoodData
  47. “Machine intelligence is the last invention that humans will ever need to make” Roman Stanek, CEO of GoodData
  48. “If banks figure out transparency and user experience they might reinvent themselves. But many won’t make it.” – Taavet Hinrikus. CEO of TransferWise.
  49. “The only bank branch that matters is the one we carry in our pockets.” – Taavet Hinrikus. CEO of TransferWise.
  50. “There is still no alternative to a bank to store your money. This will change” Taavet Hinrikus. CEO of TransferWise.
  51. “Currencies are like loyalty points with a standing army” David Birch, Director of Innovation at Consult Hyperion
  52. “Sending money to your mother in the philipines will be free” Mike Laven CEO at Currency Cloud
  53. “Central banks, commercial banks, companies, criptography, communities will be 5 creators of currency in the future.” David Birch, Director of Innovation at Consult Hyperion
  54. “The world is going to have a better way to send money between countries. This can be Bitcoin, Ethereum..” Mike Laven CEO at Currency Cloud
  55. “Our customers are spending 15-50hrs / year with their bank account online and only 1-2hrs in branch.” Derek White. Global head of customer solutions at Bbva
  56. “At Bbva we take selfie videos, share them across our google social network and teach each other” Derek White. Global head of customer solutions at Bbva
  57. If the developer understands how the problem is solved by the machine it’s not AI. That’s just rule based. AI is not taught the solution
  58. “Insurance underwriters, claims representatives, bank representatives, and financial analysts jobs will be replaced by robots” Roman Stanek, CEO of GoodData
  59. “80% of work in Financial advisory, fraud detection, legal work, AML, customer services, Backoffice, will be done AI-first.” Roman Stanek, CEO of GoodData
  60. “Mobile first is outdated. We are going to AI first” Roman Stanek, CEO of GoodData
  61. “India is leading the way in the path to financial inclusion. Universal ID. Removing cash..” Michael Schlein. CEO at Accion
  62. “Historically credit is only given to people who you have data on. Big data will bank the unbanked” Michael Schlein. CEO at Accion
  63. “The UK post brexit will be so busy negotiating banana import rules that they will have no time for fintech” David Birch, Director of Innovation at Consult Hyperion
  64. “The EU passport is quite cool, in USA you need to deal with different regulation per state” Taavet Hinrikus. CEO of TransferWise.


How can Bitcoin serve 7bn people?

Visa transfers 2,000 transactions per second, whereas Bitcoin transfers 7 transactions per second. If bitcoin wants to establish itself as a currency that can be used daily by 7bn people worldwide it needs to scale up. What can to be done for Bitcoin to scale up its transaction processing volume?

  1. Do nothing. Since the popularity of Bitcoin is growing, the demand for transactions is growing. Since there is more demand than capacity, and the miners are processing first the transactions which offer a higher transaction fee, the cost of sending money with Bitcoin is going up. Currently an average bitcoin processing fee is 101,700 Satoshis, which is worth 2.5 USD. This means that paying for a cup of coffee with Bitcoin would cost another cup of coffee in payment fees. This also means that the backlog of unprocessed transactions is growing. At the time of writing this there are 507 unconfirmed transactions. At a rate of 7 transactions per second, if no more transactions are received, it will take 2.20 hours to confirm the backlog. Imagine having to wait 2.20 hours for your coffee payment to go through.. doing nothing does not seem like a viable option.
  2. Increase the block size. By design, Bitcoin generates one block every 10 minutes. This block can fit in as many transactions as possible as long as it’s size is below 1MB. One simple solution would be to increase this 1MB limit to 20MB for example. This would fit many more transactions per block, and the speed at which transactions are processed would increase. Bitcoin Improvement Proposal BIP100 describes this. The problem with this increase is that larger blocks would make full nodes more expensive to operate, which would decrease decentralisation as some nodes would no longer be able to bear the cost. A hard fork would be needed, risking splitting bitcoin in two cryptocurrencies, and all of this would not give a final solution, as the block size would need to increase periodically to support all the world’s future transactions. Off-chain transactions would be the only long-term solution.
  3. Use each block more efficiently. In December 2015, at the Hong Kong Bitcoin Scaling event, Pieter Wuille introduced the idea of Segregated Witness, a modification to bitcoin which would reduce the amount of information needed for each block. This freed-up space could be used to introduce more transactions per block. The advantage of this approach is that it can be done with a soft fork minimising the risk of splitting bitcoin into two cryptocurrencies.
  4. Minimise the number of on-chain transactions. Joseph Poon & Thaddeus Dryja wrote in January 2016 the Lightning network whitepaper. This would enable minimising the number of transactions that need to go into the blockchain by adding a layer on top which would create one to one payment channels. These payment channels which would be fully collateralised IOUs between counterparties would form a network with which a payment could be routed. This is similar to the concept that Ripple is using, which in turn is similar to the concept of correspondent banking.

A heated debate has split the Bitcoin community for the last year. Developers, miners, markets and users could not agree on how to solve the problem, as every option had risks.

At the Consensus 2017 Conference an agreement seems to have been found. The option agreed is to implement Segwit with a 2MB block. Although even after this middle ground has been found, heated debate goes on.


Hopefully the bitcoin community will be able to find a way to find consensus, not only in the blockchain, but also in the way to evolve in order to meet the challenges that will be found.