Within the last year, several logistics and retail companies, researchers, and startups announced their interest in using blockchain technology for last-mile delivery solutions:

• Walmart implements blockchain-based delivery system
• Blockchain Technology: Possibilities for the U.S. Postal Service
• Carrefour implements blockchain as part of supply chain transformation

This article gives a summary of current challenges, initiatives and the possible future of the industry that will be opened by using blockchain technology.

Industry perspective: IoT penetration driven by eCommerce growth

Industrial globalization and ecommerce growth is leading to new challenges for retail and logistics companies. According to recent Accenture research, customer expectations are based on three main issues right now:

1. Delivery control: consumers are demanding a better last mile service that keeps them in control of how, when and where their parcels are delivered.
2. Delivery locations: as choices broaden, consumers want new delivery options such as lockers or pickup locations that enable a secure, 24×7 and sometimes anonymous delivery option.
3. Delivery timing: there is significant investment in speed; logistics companies should focus on giving consumers a range of delivery times (often at different price points) to provide flexibility.

All these challenges will lead to the automatization of last-mile delivery. According to McKinsey research, the level of automated last-mile solution penetration will reach 90% within ten years by drones, automated parcel lockers or, eventually, by automated guided vehicles (AVGs) with parcel lockers. If we think about all these devices as IoT devices, we should consider current limitations of this market as serious constraints for further market growth.

First of all, the pervasiveness of such devices in our society will require more confidence in security across the entire ecosystem. For example, in 2014 the first cyber IoT attack was carried out and confirmed when 750,000 consumer devices were compromised via phishing and spam emails. So, in the potentially huge market of last-mile IoT devices that interact with consumers on a regular basis, ensuring the security of the data, systems and devices, as well as the privacy of the data and data computations, is crucial as the impact of possible cyber attack on centralized IoT systems will be more powerful.  

The second challenge is scalability of these devices. To manage these systems we need an ever growing capacity and bandwidth in the cloud. It is not realistic to expect the IT team to be familiar with every individual connected device, although they have the system administrator capability to install patches, access the device and their data remotely, and so on. So in addition to less confidence in security across the entire ecosystem, with centralized device management, we will receive very high cost of installation and maintenance.

The third limitation is the increasingly complex interoperability between companies. This helps to create the monopolization of industry verticals by big players that want to meet customers’ expectations, such as Amazon who this year started launching end customer delivery that essentially makes them the owner of the whole ecosystem chain. Larger market players create standardization in the technology stack to integrate across technology vendors, standard protocols for sharing between systems, standard access to external data sources etc. So it is almost impossible for small and medium players to compete against these players without cooperation with them.

That leads us to the last but not least problem of development for this industry; security, privacy, and confidentiality of customers’ data that are gathered by all these devices.

That’s a limited list of reasons why the IoT industry needs to be rebooted to give the push for last-mile devices delivery.

Blockchain as the solution for revolutionize last-mile delivery challenges

Although there are a lot of different approaches for the scaling of IoT solutions, especially on a security level, blockchain technology is a very elegant way to revolutionize the industry and make the internet of things of the last-mile delivery industry a truly scalable and autonomous solution.

To understand how exactly. here is a brief explanation of Blockchain and IoT infrastructure elements.   

1. IoT hardware interacts with the physical world, perceives the physical information, converts it to digital information and stores it on the ledger as a causal chain.
2. Blockchain represents the physical world and maintains one or many causal chains in the form of blockchain. Sidechain can be used to speed up transactions, reduce costs, and diminish computational load.
3. Smart contracts provide a character to the “things”, for example an independent agenda for each station (goal, plans, policy and context) and update the ledger state through consensus. In other words, agent causation in the physical world is preceded by causation on the ledger, which in turn is preceded by consensus-based deliberation.

So, blockchain technology provides a very elegant and relatively easy solution to solve challenges of increasing number of devices in last-mile delivery industry. Picture 1 describes one possible configuration of blockchain interaction.

Picture 1. Example of Last-mile IOT Sidechain on Ethereum.  

Security. Decentralization of the system will allow mitigation of the risk of network failure because the integrity of the system is no longer reliant on penetrating single nodes. Instead it will rely on consensus between the nodes.

Scaling. By distributing computational and storage needs across devices in the network, instead of relying on central servers, the decentralized system will allow scaling and managing last-mile devices more easily.

Interoperability. Open protocols will allow establishment of trust with consumers for sharing data. Additionally, retail and logistics companies can eventually establish collaboration across companies and industry verticals to achieve horizontal data aggregation without putting in jeopardy security, privacy, and confidentiality issues.

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The Blockchain Lab at the Sutardja Center for Entrepreneurship & Technology (SCET) is pleased to announce support for students and faculty who are contributing to Blockchain’s future with cutting-edge projects.

 

Blockchain is an emerging capability where Berkeley has great promise to contribute. The lab began in the Fall of 2015 with generous support from Echolink, an emerging blockchain firm and NEO, a non-profit community developing the smart economy on blockchain.

 

We received many great applications, which our selection committee thoroughly enjoyed reviewing, although it did make their task of choosing the top four very challenging! However, a decision was made, and the first awards from the blockchain lab are going to the following projects:

 

1. Framework for Cryptoeconomic Incentives in Proof of Stake (PoS) Systems: Aparna Krishnan, Zubin Koticha, Alexis Gauba, Maaz Uddin, Philip Hayes, Vishesh Mehta
2. Decentralized Nondeterministically Verifiable Security: Jeremiah (Yiqi) Hou, Eric (Yiqi) Hou, Sid Masih, Alberto Todeschini, Jeremiah Andrews, Parth Singhal, Leon Ming, Nick Zoghb
3. Efficient and secure consensus for Blockchain: Gireeja Ranade
4. VoDChain: A Blockchain-based Crowdsourced Video-on-Demand System: Kannan Ramchandran 

We are awarding each of these teams to help to support applied and fundamental research that will reduce barriers in the adoption of blockchain and its inclusion in an increasingly digital world with new possibilities for fairness, transparency, and efficiency in both financial transactions and information sharing.

 

Please join us in celebrating the great work of these students and faculty as they continue to develop their work in the ever growing and interesting in Blockchain and its implications for the future of the digital world.

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Marissa Louie with her Animoodles before speaking at the SCET’s challenge lab class on disaster recovery in Puerto Rico.

Last week, there was an unusual sight in UC Berkeley’s Industrial Engineering 185 course: stuffed animals.

The toys, called Animoodles, put an innovative twist on the traditional plushie. As students passed them around the class, they found that hidden magnets allowed them to pop off each toy’s head or limbs and mix and match parts with other types of animals. Some put the head of a unicorn on a sloth or switched a lion’s limbs with those of a frog.

But the students soon learned that these toys are more than just an new take on what a stuffed animal can be –– they also have a distinct humanitarian mission. On Thursday, CEO and Chief Designer of Animoodles, Marissa Louie, joined the Sutardja Center for Entrepreneurship & Technology Challenge Lab class on disaster recovery in Puerto Rico, to give advice to students on how they can design products to have a social impact.

“A lot of people don’t know the whole reason behind Animoodles because we want the product to speak for itself,” Louie said. “Today is the first time I’m going to tell a room full of people what that really is.”

Louie is a UC Berkeley alumna who earned degrees in industrial engineering, business and economics. But beyond the practical knowledge that she gained at the UC Berkeley, she said that her time at the university laid the foundation for her critical thinking, morals and ethics as an entrepreneur.

It’s because of a desire for social change that she developed while at UC Berkeley, Louie said, that she felt she wasn’t fulfilling her true purpose when she started working as a designer for large tech organizations like Yahoo and Apple after college.

So after about a decade working in the tech industry, Louie switched gears to follow her dream of creating a toy that would promote diversity, inspire creativity and build the next generation of “little makers.” Louie explained that the mix-and-match design of Animoodles is key not only to the unique draw of the toy, but also to the company’s social mission.

“With Animoodles, you can literally have an animal walk a day in another animal’s shoes,” Louie said. “We want to instill these values in kids, and we can use Animoodles as a model to do so.”

Louie added that Animoodles are a way to get children away from screens and back to a type of playing that inspires them to use their imaginations. She noted that kids’ ability to switch around animals’ heads and limbs around builds an early interest in creating new things.

But building a stuffed animal that competes with the many digital toys on the market wasn’t easy  –– Louie started the project completely on her own and had to teach herself how to market products, how to design a package and how to illustrate, among many other skills.

After a year working on Animoodles by herself, she brought a rough prototype –– a teddy bear that she sewed herself –– to a former Pixar character designer, Dan Holland. He agreed to join the project and helped develop specific characters for the toys, like Randy the Orangutan, Hazel the Sloth, Miguel the Frog and Iris the Unicorn.

Since then, the project raised $100,000 on Kickstarter and launched in October 2017. A month later, Animoodles were named the number one trending toy in the world during Black Friday and Cyber Monday.

Beyond the social mission that emerges within the toy’s design, a major tenant of the Louie’s business model is giving back. When the U.S. government threatened to lift a ban on the import of elephant tusks, Animoodles introduced a new character on their website, Sophie the Elephant, and gave 100 percent of profits from the toy to the African Wildlife Foundation.

During the class, Louie stressed the importance of using for-profit companies as a way to make money to donate back to philanthropic causes. She encouraged students to use their own personal strengths to build products that promote humanitarian causes, just as she did with her design expertise.

“Working at a job to just get a paycheck is not enough anymore,” Louie said. “You can use your skills to make a happier world.”

The Sutardja Center for Entrepreneurship & Technology’s Challenge Lab Course on disaster and recovery in Puerto Rico encourages students to find innovative ways to solve the problems facing Puerto Rico in the wake of Hurricane Maria.

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On Jan. 31 two UC Berkeley alumni held a pre-sale for SPN tokens, a type of blockchain token that’s required to access a new social media platform they created. In two hours, people had bought $12 million dollars worth of it.

So why did their new social network, Sapien, create such a buzz? One of the biggest reasons, according to Sapien CEO and co-founder Ankit Bhatia, is that its basis in blockchain technology has created a new, more democratized infrastructure for social media networks. He says that this new infrastructure could help protect people’s privacy, give users a cut of ad revenue and put an end to fake news.

Bhatia was invited to the Sutardja Center for Entrepreneurship and Technology’s Challenge Lab class on Blockchain last week to talk about his journey with Sapien and explain how this new kind of social media works. He told UC Berkeley students about how the project grew out of his friendship with co-founder Robert Giometti and their mutual frustration with the current state of social media platforms.  

“We would be coming back from parties, talking about how we were upset about Facebook exploiting data,” Bhatia said.  

In 2016, they decided that rather than continue debating the future of social media, they’d make a new future themselves. So they started coding a new platform to fix the problems that frustrated them about existing social networks.

With other social media networks like Facebook, Reddit, Twitter and LinkedIn, all user data, including every time you “like” a post, “upvote” a comment or send a direct message, is stored on the platform’s central servers. This system allows companies to collect information about you that can help them to provide you with targeted ads, but it also means that if a hacker finds a way to compromise one of those servers, thousands of people’s sensitive personal information can be leaked.

Sapien’s promised blockchain-based infrastructure, however, allows users to bypass interacting with a central server. The network is built on Ethereum, a blockchain-based computing platform, which uses a peer-to-peer network. In this type of network, information is stored across a number of computers rather than in just a few central servers.

“Instead of going to one point for data, the data is distributed among everyone,” Bhatia said. “You can send a message to someone else without interacting with a central authority.”  

As a result, there’s no central targets for hackers and “no one point of failure,” because information is stored across several different devices.

Users can also rest easy, knowing that personal information about them isn’t automatically being collected by Sapien and stored. If they so choose, however, users can turn on ads and allow data collection from their account –– with an incentive. At least 50 percent of the revenue that Sapien earns from the advertisers will be directed back to the user in the form of SPN tokens.

“We’re distributing the wealth back to the people for opting in and giving their personal data,” Bhatia said.

Bhatia also explained to students at the class why he thinks the token format of Sapien will help to prevent internet trolls and the spread of fake news.

Users need to initially pay the equivalent of $20 in SPN tokens in order to use the platform. It’s a one-time fee, but it helps to put something at stake if a user posts illegal content, for example.

Bhatia said that he thinks this format will also prevent Sapien from having the “bot” accounts that are common on platforms like Twitter, because there will be a financial consequence to keep remaking accounts after being deleted for posting spam.

On the other hand, people on Sapien can also use the tokens to reward or “tip” people who post good content, incentivizing thoughtful articles and blog posts on the platform.

To Bhatia, the possibilities for this new type of social media network are endless and could completely change the way that people interact with each other online. In a final word of advice while speaking at the Blockchain Challenge Lab class, he encouraged UC Berkeley students to start their own projects that they think could make the world a better place.

“Go for the ambitious stuff,” Bhatia said. “Try doing things that are more meaningful… Projects that can be a win-win for everyone.”  

The Blockchain Lab at the Sutardja Center for Entrepreneurship & Technology is currently investigating unresolved technical and policy challenges preventing the technology from being widely adopted. We will be awarding funding for projects (see announcement on 3/10/18 on our Blockchain Lab site) and are seeking a research director.

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Illustration by Jiani Hou

“Well, in our country,” said Alice, still panting a little, “you’d generally get to somewhere else—if you run very fast for a long time, as we’ve been doing.”

“A slow sort of country!” said the Queen. “Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!”

 Lewis Carroll, Through the Looking-Glass

The Biology of Business

In business as in biology, primary producers occupy the lowest level in the food chain.  In biology, as organisms rise up the food chain they rise in trophic level: for example, from plants to herbivores.  Similarly, in business, as products rise up the value chain they also rise in trophic level: for example, from raw materials to manufactured goods.  In biology, carnivores are the apex predators sitting atop the food chain.  What defines the analogue apex predator in business?

Arguably, the most successful companies in any industry today are Silicon Valley titans Amazon, Google and Facebook (and their fellow Chinese titans, Baidu, Alibaba and Tencent).  Though each of the Silicon Valley giants is nominally in a different business – e-commerce, search, social networking – all three are unified by a common business model.  All three are in the business of collecting as much data as possible, by every means possible, and making money off that data.  Period.  This is all they do.  This is what might be known as the “Amazoogle” business model.

Although the mechanics (front-end) of how Amazon, Google and Facebook collect their data may differ, all three derive strategic and business value from the semantics (back-end) of their growing-by-the-split-second troves of data.  The competitive power of the Amazoogle business model lies in the simple fact that the more data you accrete, the keener the insights you can drive, essentially allowing Amazoogle companies to both predict future behavior and even drive future behavior.  Brands happily pay for both results.

And since Amazoogle decrees that data is good, then certainly more data must be even better.  Hence the additional data streams enabled by Facebook’s Like button, Google’s self-driving cars, and Amazon’s purchase of Whole Foods.  Crucially, because Amazoogle data grows continuously, both its efficacy and its competitive barrier grow apace.

Data-driven Amazoogle business models are now deconstructing every legacy business, whether in finance, transportation, retail, or now even in healthcare.  Consequently, the apex predator that legacy companies in each of these industries faces is not from their traditional legacy competitors but from business model disruptions fueled by Amazoogle.

 Data: The Anti-Commodity

The problem with any manufactured product (even software) is that it’s commoditized.  For example, the only real way to differentiate autos in the minds of the buying public is through vast advertising expenditure.  The only real way to differentiate relational database platforms to an enterprise buyer is through pricing.

But just today, we have finally passed out of the Industrial Age and truly into the Information Age.  It’s now the information itself — not the manufactured good, even if that manufactured good happens to be a really sophisticated electronic device, software platform or chemical compound — that fuels the predominant business model.  Business models will no longer be predicated on the manufacturing of a thing — mobile phone, automobile, pharmaceutical — but on the value and understanding of the data that each of these things creates.  This represents the most fundamental change in business model since the rise of manufacturing and the Industrial Age.

The mobile phone industry provides a ready example of the impact of the Amazoogle business model today.  Mobile phones are the result of incredibly expensive R&D and manufacturing processes.  Vendors must also incur the marketing, distribution and support costs in getting their product into the hands of consumers in a cut-throat industry, at hardware-product margins.  These devices then freely spill vast volumes of data 24×7 into Amazoogle’s business model.  In which part of this business model equation would you rather be?  Even heretofore invincible Apple is starting to feel Amazoogle’s effects.

Embracing Amazoogle, however, doesn’t mean that if you’re a vendor of a “device” that you should abandon what you’re doing.  You (we!) still need that device.  It’s just that you need to emulate Amazoogle (indeed, anticipate Amazoogle’s competitive entry into your market) and realize that your device is part of a holistic product with data at its foundation.

In the business environment of the future everything is commoditized already or will soon become so.  The sole competitive differentiator in a commoditized world lies in being able to predict the future.  The more data you have the more accurately you can predict the future.  Whoever controls the data wins.

The Red Queen

The Red Queen Hypothesis was put forward by University of Chicago biologist Leigh Van Valen in his seminal 1973 paper on “A New Evolutionary Law”.  In this hypothesis, Van Valen posited that organisms must constantly adapt and evolve because they live in an ever-evolving ecosystem, competing for survival against other ever-evolving organisms.  Everything is competitive, and nothing is constant; it’s explicitly a zero-sum game, and stasis means extinction.  Just as in the Red Queen’s quote to Alice in Through the Looking-Glass.

In business, the Red Queen says that it’s not enough that your company is running as fast as possible, you need to run fast relative to your competition.  With data-driven Amazoogle business models moving at breakneck speeds, how fast is your company running?  If you’re not positioning yourself to out-Amazoogle your Amazoogle competition, then you’re positioned for irrelevance at best and extinction at worst.

It’s a truism that for any type of company, whether two-person start-up or Fortune 500 behemoth, it’s the business model that drives success, not technology.  The world is awash in technology, but only those technologies that can exploit an inefficiency in — and change — a business model hold promise for creating new industries and companies.

You can certainly go ahead and invent <insert name of electro-mechanical device, enterprise software, or chemical compound here>.  Designing the next great commodity product — no matter how technologically cutting-edge — will not immunize you to the depredations of Amazoogle.  Eventually, patents expire and/or someone (perhaps even your company!) manufactures the product ever more cheaply, resulting in the steady compressing of your profit margins.  In the end, anything that’s a manufactured product, no matter how sophisticated, is fated to become a commodity.

For legacy industries, using data and machine learning to improve productivity is a nice starting point, but is far short of being enough.  Doing so only helps fuel race-to-the-bottom pricing: the more efficient you become at making something, the more commoditized it becomes, eventually leading to a lowering of the margins in your business.  So using machine learning for reservoir simulation or drug discovery might only be a short-term salve.  You may have addressed innovating your technology, but not have addressed the more fundamental innovation of your business model.

If business models win, not technology, then it’s not sufficient to use data to innovate your technology alone.  You need to use data to innovate your business model.  Tactical battles are won or lost on technology.  Strategic battles are won or lost on business model.

If history has taught us one thing it’s that the future will not look like the past.  Consequently, it’s suicidal to merely focus on making yourself competitive against your past competition, even if you’re comforting yourself that you’re now using the latest (machine learning and Big Data) technology to improve how you do so.  It will still be yesterday’s battle you’ll be fighting.  You’ll just become more efficient at fighting it.  Rather, if the Red Queen is right, your efforts must be expended in using data to re-envision your business and preparing yourself for combat with tomorrow’s fast-moving Amazoogle competitors.

Put another way, given the strategic imperatives above, whose stock would you rather own?  Commoditized 20^th Century business models such as Big Ag?  Big Auto?  Big Pharma?  Big Box retail?  Or 21^st Century business models built on Big Data?

 “Yabut”

 “The railroads are in trouble today not because the need was filled by others (cars, trucks, airplanes, even telephones), but because it was not filled by the railroads themselves. They let others take customers away from them because they assumed themselves to be in the railroad business rather than in the transportation business. The reason they defined their industry wrong was because they were railroad-oriented instead of transportation-oriented; they were product oriented instead of customer-oriented.”

 Theodore Levitt, “Marketing Myopia”, Harvard Business Review, July-August 1960

The most dangerous word in business today is “yabut”, as in “Yeah, but do we really…?”  Unfortunately, uttering “yeah, but” in any business conversation might only be a convenient way of justifying conservatism, dodging responsibility for looking ahead (painful as that may be), and affirming the need to continue to pursue the comfortable and familiar course of business as usual.

But start-ups seeking long-term investment as well as established companies seeking long-term relevance need to pay heed to Levitt and Van Valen.  Who’s moving the business model the fastest today, the fintech start-up or the nationwide bank?  The connected car company or the global auto manufacturer?  The Big Pharma behemoth or Google’s Verily?  With this in mind, realize that “yabut” generally presages an existential threat.

The insurance industry, for example, has to date had a business model of insuring physical assets.  In the data-driven world of Amazoogle, with virtualized transportation being provided by fleets of self-driving cars or via ride-hailing services, how does an insurance company abandon “yabut” concerns about existing revenue streams and monetize data assets instead?  Companies who do not heed the clarion call to re-examine their business models in this way risk falling victim to the “fatuous contentment” in Levitt’s polemic, and thereby “guarantee premature senescence”.  This applies to all industries, even information technology.  Silicon Valley is replete with its own examples of companies that were felled by the “marketing myopia” warned by Levitt.

The technology industry has by now seen the passing of “peak hardware” and “peak software”.  Is Amazoogle also fated to pass its moment of apotheosis?  The answer is no.  Human technology has replicated physical labor through the invention of machines, and replicated the process of thinking through the invention of software.  Machine learning driven by Big Data now finally replicates — and, for good or bad, will soon surpass — the final piece: the human capacity to learn, create, and anticipate the future.  There’s now nothing left to replicate.  If you want the ultimate business model — the apex predator — it must by definition be a data-driven Amazoogle business model.

Nokia once thought they were in the cell phone business.  Yahoo thought they were in the search engine business.  Toys “R” Us thought they were in the toy store business.  Amazoogle showed each of these companies otherwise.  Business leaders wanting to avoid a similar fate should read Levitt and Van Valen.  Consider the implications of business model stasis on your long-term viability.  And then ask yourself what business you’re in.  The Red Queen warns: Amazoogle is coming.

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On February 20th, Michael Seibel came to speak to the A. Richard Newton Series course about his journey with Y Combinator (YC), a leading startup accelerator, and what entrepreneurs can do to be successful at YC today.

Seibel was the co-founder and CEO of Justin.tv for four years and later became the CEO of Socialcam. Socialcam was in a YC batch and raised funding by investors Yuri Milner, Tim Draper, Laurene Powell Jobs and more, which was later sold to Autodesk, Inc. Justin.tv transformed into Twitch Interactive and later sold to Amazon for over $900 million.

Seibel attended Yale University where he studied Political Science on track to becoming a lawyer. Later, Seibel met his co-founder, Justin Kan at Yale and decided to pursue Justin.tv full time. “I’m not too fond of talking about my background,” Seibel said. “When you explain your company to someone, never talk about the background of how you got there. Just talk about your product, what it does and how you plan to grow it.”

Throughout the lecture, Seibel spoke about the advice he gives to startups every day. He requires that each startup team consists of 2-4 individuals with at least half of the team holding technical positions. He stated that in order for startups to be successful, you must be focused and be ready to quit your current job to be more dedicated to the development of the product.

Every week, the YC startups attend workshops and mentor office hours to further their companies

In order to ideate, Seibel mentioned that it is important to have personal experience and focus on solving daily problems. It is important to realize that many people might be working on solving the same problem, but the one that becomes successful is the one that solves it the best. Seibel continued stating that the minimum viable product should be something the user should be able to have as soon as possible. He mentioned that from the beginning, it is important to find a co-founder that you know and trust and to start building your product instead of talking about it to others.

In order to convince the class to pursue an idea they believe in, no matter how good or bad, he assured, “Something you know that you think is right and other people think is wrong is normally an idea that works.” Seibel proved that in some cases, some lacking ideas, even in previous YC batches, can lead to successes if executed properly.

Seibel working on one of his earlier companies, Socialcam

Students later had the opportunity to ask their own questions to Seibel regarding what YC looks for in a startup to get an interview, what the first steps are to begin a company, and how to find the best co-founder.

Seibel ended the lecture by stating, “It can be hard to seek a mentor or ask someone a question, but I read every single one of my emails, so there should be no excuse for you on who to contact.”

To learn more about YC visit the website here.

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Future of Blockchain – A Berkeley Perspective

Ikhlaq Sidhu, Alexander Fred-Ojala
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
Feb 11, 2018

Current Situation: Blockchain is an Emerging Technology With a Significant Promise

In 2009, a previously unknown cryptographer by the name of Satoshi Nakamoto introduced a mysterious new digital currency to the world.  Ignored by the traditional finance industry, Bitcoin gained popularity quietly on the Internet and now is considered the first mainstream cryptocurrency that has been heralded as the biggest innovation in finance since the invention of the double-sided ledger.  The comparison is no mistake, cryptocurrencies can be considered the re-invention of the ledger, a public ledger, once the exclusive playground of banks and governments.  The power behind cryptocurrencies is Blockchain technology, an equally mysterious concept that can only exist in a world of cheap high speed computing power and ubiquitous Internet.

Since Blockchain’s introduction in 2009 as the base technology enabling the Bitcoin network, Blockchain has offered significant promise to revolutionize the IT and financial landscape, disrupting the traditional roles of governments, banks and other institutions.  Marc Andreessen, the co-creator of the first commercial Web browser, Netscape, and a big investor in the technology, claims it is one the greatest breakthroughs in Computer Science in the 21^st century.  At the core of Blockchain is the ability to create a global database (extended from a ledger/list) which is immutable (not changeable by anyone after the fact), transparent, trusted, even when the parties who write to it are not trusted by each other.

The result and promise of Blockchain technology and its related view of the world includes:

• Global electronic transaction commerce including secure financial payment/transfers with reasonably short settlement times
• Increased financial transparency leading to lower corruption, less illicit activity, and/or fewer black market options
• The possibility of a true, user controlled, and tamper-resistant digital identity and digital records
• Distributed networks of smart contracts that automatically execute transactions-based policy and on real life events.
• A decentralized internet where information and data are owned by the user, rather than the service provider
• Automatic grid infrastructure with minimal maintenance, e.g. electric grid where producers and consumers could connect without going through a central instance.

In its current state, many leading companies and governments explore demonstrations of the Blockchain integrated into finance, supply chain, identity management, credential validation, property exchange recording, and other verticals.  In most of these cases, the proof of concept demonstrations are indicative of the possibility and promise, but have yet to be deployed in meaningful or scalable manner.

One of the main reasons why true adoptability of Blockchain technology has been slow is because of the uncertainty in policy.  Firms and organizations are waiting for political decision makers to clearly state how rules and laws related to tax and financial exchange will affect the technology. So far, we have witnessed the earliest forms of actual Blockchain implementations in applications that involve compliance.  In these cases, the value of immutability, decentralization, and transparency are the most significant. We expect security applications to be the next area where significant adoption will take place.  There is also a general trend in all industries and governments, where slow but steady acceptance of Blockchain technology is taking place.
We expect the gradual development of a globally transparent ledger which will become the backbone of many new applications.  Blockchain technology today is in its infancy, but for institutions, states, and companies alike to ignore this technological revolution would be equivalent to ignoring Internet technology when it emerged 25 years ago. We expect many researchers and firms to compete and work on algorithms, technological improvements and infrastructure that can offer the Blockchain promise in a scalable, yet secure manner. We believe that it is crucial for institutions, organizations, and governments to be part of this groundbreaking development and research.

What are the Next Technological Breakthroughs in Blockchain

For Blockchain technology to transform industries and everyday lives of people there is a lot of technological development still to be made. We would like to compare this to the development of the original Internet that allowed a certain number of applications (i.e. web browsing, email, information sharing, etc.). This first iteration of the Internet (Web 1.0) was made possible by open protocols developed by researchers. The true Internet economy that we are witnessing today emerged from the second layer of the Internet, namely interactive and social applications (Web 2.0).  This second wave of Internet companies included Facebook, LinkedIn, Instagram, etc. that thrive on human exchange and interaction.

In a similar way, we expect a wave of Blockchain solutions that will solve a new set of social issues to disrupt the current world order.  Thus, it may not be enough for people to simply have direct access to the primitives of a global Blockchain ledger.  We believe that as the current set of issues with Blockchain protocols, scalability technologies, and standards are resolved, Blockchain will deliver impact on societies and people all over the world, creating new winners and losers. This is the horizon we would like to explore and that is what we consider as the next stage of Blockchain.
There exists a number of challenges and new values that could be created via Blockchain if these problems were pursued:

1. Consensus mechanisms need to be developed and game theoretical models for decision making need to be thoroughly studied, especially to keep the systems decentralized and prevent / lower the incentive of a majority take over.
2. Given the number of transactions that will be possible on Blockchain, a person will require their own Personal policy / User Interface to manage a personal control layer for their transaction flow.
3. There will be so many transactions, that sophisticated AI technologies will be required to detect anomalies the get recorded.
4. A policy language to control your acceptances of transactions will likely be needed. Today, this layer does not exist.
5. Keeping the infrastructure alive and optimally distribute workload will be a major issue:
   1. First the scalability issues will be significant as the number of transactions per user grow on an exponential scale with time. And then the number of nodes that keep copies grow on an exponential scale. The product of the two defines the complexity of the emerging system.
   2. Security standards and hacking prevention measures becomes a significantly larger issue particularly since humans will trust the systems instead of centralized authorities.
   3. We must consider how the emerging Blockchain infrastructure will map to and/or interface with emerging new failure points.
6. Perhaps the largest barrier for the Blockchain today and the most evident point of failure for smart contracts will be how this technology interacts with the real-world. These are called edge cases or edge devices, points in the network that have to register something that has happened in the real-world and then utilize that information in the smart contract system. The problem is evident as any smart contract is only as reliable as the information that it reads to execute its transactions. g. If a cargo company tracks the source of all delivered goods, how can we make certain that the entity registering the source does not provide false information?

7. In parallel, we expect a Smart city and Internet of Things management systems will also have to be developed that will integrate and monitor all the nodes and participants of this global network.
8. While some of these issues can be solved with technology, many can only be solved by policy and conventions that live outside of the Blockchain technology itself. A framework for this policy is necessary and yet does not exist.
9. Finally, there is a significant issue that when the systems based on Blockchain do breakdown there is no way to debug them due to their tamper-proof immutable nature. How do we trace back the results that are largely unreadable to humans to obtain layers of information and intent?  This capability and framework must also be developed.

Illustration of a Long-Term Concern: Blockchain intention is not easily human readable

A Note on Blockchain’s Future:

If we compare the state of the Internet in 2000 to the state of the Internet in 2010, we will see that the firms that led the first round of technological breakthroughs largely did not survive and further the key players by 2010 were not all even developed in the first round. For example, Netscape who developed the first Browser and Sun who created Java both lost their lead.  Some firms like Amazon and Netflix increased in power.  And many firms from Facebook and Google became leaders only after the second iteration of Internet technology had been developed and adopted. It stands to the same reason that the leading players in Blockchain today, who are building infrastructure and developing fundamental protocols, are not necessarily the players that will dominate the next Blockchain landscape—there is plenty of room for new companies to emerge.

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In January of 2018, professors and students from all over the world gathered at Hong Kong Baptist University (HKBU) for its annual Principal’s Day in order to tackle the theme of “A.I. in X: The Future of Education.” HKBU is a global partner with the Sutardja Center for Entrepreneurship and Technology (SCET) and has previously participated in SCET’s Global Venture Lab, which is a summit of academics, innovators, and entrepreneurs from all over the world who gather in order to share insights on research and educational programs.

Professor Ikhlaq Sidhu, founding director and chief scientist of SCET, was the keynote speaker for this event and shared both Berkeley’s current research efforts into this theme as well as his own insight into how students can prepare themselves for a future where humans and machines collaborate on projects. Professor Sidhu concluded that while it is important for educators and students alike to understand how artificial intelligence will affect academia, in the end, humans will be an indispensable part of any new technology.

In the days following this keynote address, Professor Sidhu and Alex Ojala (a lecturer of the Data-X course at Berkeley) taught a two-day version of the Data-X class that is offered at Berkeley in order to instruct skilled managers at HKBU how to “master the technologies and concepts that are changing the business landscape.” This masterclass included sessions on a variety of topics, including big data, machine learning, and the future of data science and should be seen as a step towards equipping students with the knowledge to tackle both data science and A.I.

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