November 2022 - AI Superpowers by Kai Fu Lee

This month we dive into head of Sinovation Ventures, Kai Fu Lee’s book on the future of AI. I disagree with a lot of this book, and overall found it underwhelming. However, there are some interesting ideas that people can take with them into the future.

Tech Themes

1. Competitive Intensity in China. China's tech industry is fiercely competitive due to the sheer size of its market and the government's support for innovation. Local players like Baidu, Alibaba, and Tencent (BAT) have dominated the industry for years, but new players are emerging every day. This intense competition has created a dynamic tech ecosystem where companies constantly innovate and disrupt traditional industries. The race to dominate emerging technologies like AI, cloud computing, and 5G is particularly intense as these technologies have the potential to reshape entire industries. The markets are so competitive that entrepreneurs use almost absurd tactics to beat out rivals. In one instance, a new social network named Kaixin001 was gaining in popularity. The company was new and didn’t have enough cash to buy the Kaixin.com domain name, so its number one competitor Renren built an exact copy of Kaixin001’s website and bought the Kaixin.com domain name to launch the product. Within months their traffic plummeted and although they eventually won a lawsuit for unfair competition, the $60,000 reward was nothing compared to the loss of customers. Renren itself was a clone of Twitter, started by Wang Xing, the eventual founder of Meituan. In another instance, Tencent and Qihoo 360 got in a repeated blame-game fight, that eventually led to Qihoo Anti-Virus blocking the use of Tencent’s QQ and Tencent suing Qihoo in the first-ever Anti-Monopoly court case. The Groupon Clone Wars were a series of intense price wars between Chinese group buying sites like Meituan and Dianping. At one point, China had 6,000 group-buying sites. These sites copied Groupon's business model of offering discounts on local goods and services but adapted it for the Chinese market. The result was a hyper-competitive market where companies would aggressively discount their services to attract customers. This competition was good for consumers but ultimately unsustainable for the companies involved. Meituan and Dianping have merged to form a dominant force in China's online-to-offline (O2O) market. This merger directly opposed Alibaba’s wishes, and it massively funded competitor Ele.Me to compete. Today, Bytedance and Alibaba are suing Tencent and Meituan over monopolizing the food delivery industry. The competition in China is absolutely brutal - copying isn’t just allowed, it’s encouraged.

2. AI in Practice. Meituan Dianping and Bytedance are two of China's most successful tech companies. Meituan Dianping started as a group buying site for food and beverage deals but has since expanded into other verticals like travel and entertainment. Bytedance, on the other hand, is the company behind TikTok. Both companies have experienced explosive growth in recent years and are now among the most valuable startups in the world. Their success is a testament to China's ability to create homegrown tech giants that can compete on a global stage. Tiktok has built one of the best and most successful content recommendation algorithms ever. Alibaba's customer service chatbot, AliMe, uses natural language processing to understand and respond to customer queries. It can handle over 90% of customer inquiries without human intervention, allowing for quick and efficient responses. Another example is China Merchants Bank, which uses facial recognition technology to identify customers and provide personalized services. AI-powered recommendation systems are also being used by companies such as JD.com to suggest products based on customers' browsing and purchasing history. Furthermore, AI-powered voice assistants, like those developed by iFlytek and Baidu, are being used to help customers with tasks such as ordering food, booking hotels, and making payments. By leveraging AI technology, Chinese companies can provide customers with faster, more personalized, and more efficient service, ultimately leading to greater customer satisfaction and loyalty.

3. Chinese Government Investment in AI. China has become a hotbed for entrepreneurship in recent years, with startups popping up in every industry, from e-commerce to healthcare. The government has made it a priority to encourage innovation and entrepreneurship through initiatives like the "Made in China 2025" plan. The rise of angel investors and venture capitalists has also made it easier for entrepreneurs to raise funding. However, the market is still highly competitive, and success is far from guaranteed. The government has set ambitious targets for the industry, including the goal of making China the world's primary AI innovation center by 2030. China is expected to double its investment in AI to $27B by 2026, a simply astounding figure.

Business Themes

1. Mobile Payments and AI. Mobile payments have exploded in China, with platforms like Alipay and WeChat Pay becoming ubiquitous. China's large population and relatively low adoption of credit cards have made it an ideal market for mobile payments. Today, mobile payments are used for everything from paying for groceries to renting bikes. The convenience of mobile payments has also fueled e-commerce growth, as consumers can easily make purchases on their phones. The future of mobile payments in China looks bright, with experts predicting continued growth and innovation.

2. Four Types of AI. Lee categorizes AI into four types: internet AI, business AI, perception AI, and autonomous AI. Internet AI refers to algorithms that are used to power online services like search engines and recommendation systems. Business AI is used to optimize business processes and improve efficiency. Perception AI is used to analyze and understand visual and auditory data. Autonomous AI is used to power self-driving cars and other autonomous systems. Each type of AI has its own unique challenges and opportunities, and companies are investing heavily in each area to gain a competitive advantage.

3. The future of the Chip Industry. In December China announced an absolutely massive stimulus to the chip industry: “China is working on a more than 1 trillion yuan ($143 billion) support package for its semiconductor industry, three sources said, in a major step towards self sufficiency in chips and to counter U.S. moves aimed at slowing its technological advances.“ One of the big geopolitical challenges of today’s age is the role of TSMC in the chip industry. “‘TSMC is just absolutely critical,” says Peter Hanbury, a semiconductor specialist at the Bain & Co. consulting firm. “They basically control the most complicated part of the semiconductor ecosystem, and they’re a near monopoly at the bleeding edge.’” With TSMC located in Taiwan, the proximity to China can be concerning for the US, especially with China repeatedly ratcheting up the tensions. China’s domestic chip industry has not been able to reach the pinnacle of chip development, which is no easy feat. TSMC believes that excellence only comes from rigorous kaizen process and is not the result of larger investment dollars. Only time will tell who will win the chip wars.

   Dig Deeper

• China's massive investment in artificial intelligence has an insidious downside

• Mckinsey: The Future of Digital Innovation in China

• Qihoo 360 CEO Zhou Hongyi Speaks at the 8th CHINICT in Beijing

• ‘Four Battlegrounds’ shaping the U.S. and China’s AI race

• The next frontier for AI in China could add $600 billion to its economy

January 2021 - Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages by Carlota Perez

This month we read Carlota Perez’s understudied book covering the history of technology breakthroughs and revolutions. This book marries the role of financing and technology breakthrough so seamlessly in an easy to digest narrative style.

Tech Themes

1. The 5 Technology Revolutions. Perez identifies the five major technological revolutions: The Industrial Revolution (1771-1829), The Age of Steam and Railways (1829-1873), The Age of Steel, Electricity and Heavy Engineering (1875-1918), The Age of Oil, the Automobile and Mass Production (1908-1974), and The Age of Information and Telecommunications (1971-Today). When looking back at these individual revolutions, one can recognize how powerful it is to view the world and technology in these incredibly long waves. Many of these periods lasted for over fifty years while their geographic dispersion and economic effects fully came to fruition. These new technologies fundamentally alter society - when it becomes clear that the revolution is happening, many people jump on the bandwagon. As Perez puts it, “The great clusters of talent come forth after the evolution is visible and because it is visible.” Each revolution produces a myriad of change in society. The industrial revolution popularized factory production, railways created national markets, electricity created the power to build steel buildings, oil and cars created mass markets and assembly lines, and the microprocessor and internet created amazing companies like Amazon and Airbnb.

2. The Phases of Technology Revolution. After a decently long gestation period during which the old revolution has permeated across the world, the new revolution normally starts with a big bang, some discovery or breakthrough (like the transistor or steam engine) that fundamentally pushed society into a new wave of innovation. Coupled with these big bangs, is re-defined infrastructure from the prior eras - as an example, the Telegraph and phone wires were created along the initial railways, as they allowed significant distance of uninterrupted space to build on. Another example is electricity - initially, homes were wired to serve lightbulbs, it was only many years later that great home appliances came into use. This initial period of application discovery is called the Irruption phase. The increasing interest in forming businesses causes a Frenzy period like the Railway Mania or the Dot-com Boom, where everyone thinks they can get rich quick by starting a business around the new revolution. As the first 20-30 years of a revolution play themselves out, there grows a strong divide between those who were part of the revolution and those who were not; there is an economic, social, and regulatory mismatch between the old guard and the new revolution. After an uprising (like the populism we have seen recently) and bubble collapse (Check your crystal ball), regulatory changes typically foster a harmonious future for the technology. Following these changes, we enter the Synergy phase, where technology can fully flourish due to accommodating and clear regulation. This Synergy phase propagates outward across all countries until even the lagging adopters have started the adoption process. At this point the cycle enters into Maturity, waiting for the next big advance to start the whole process over again.

3. Where are we in the cycle today? We tweeted at Carlota Perez to answer this question AND SHE RESPONDED! My question to Perez was: With the recent wave of massive, transformational innovation like the public cloud providers, and the iPhone, are we still in the Age of Information? These technological waves are often 50-60 years and yet we’ve arguably been in the same age for quite a while. This wave started in 1971, exactly 50 years ago, with Intel and the creation of the microprocessor. Are we in the Frenzy phase with record amounts of investment capital, an enormous demand for early stage companies, and new financial innovations like Affirm’s debt securitizations? Or have we not gotten to the Frenzy phase yet? Is the public cloud or the iPhone the start of a new big bang and we have overlapping revolutions for the first time ever? Obviously identifying the truly breakthrough moments in technology history is way easier after the fact, so maybe we are too new to know what really is a seminal moment. Perez’s answer, though only a few words, fully provides scope to the question. Perez suggests we are still in the installation phase (Irruption and Frenzy) of the new technology and that makes a lot of sense. Sure, internet usage is incredibly high in the US (96%) but not in other large countries. China (the world’s largest country by population) has only 63% using the internet and India (the world’s second-largest country) has only 55% of its population using the internet. Ethiopia, with a population of over 100M people only has 18% using the internet. There is still a lot of runway left for the internet to bloom! In addition, only recently have people been equipped with a powerful computing device that fits in their pocket - and low-priced phones are now making their way to all parts of the world led by firms like Chinese giant Transsion. Added to the fact that we are not fully installed with this revolution, is the rise of populism, a political movement that seeks to mobilize ordinary people who feel disregarded by the elite group. Populism has reared its ugly head across many nations like the US (Donald Trump), UK (Brexit), Brazil (Bolsonaro) and many other countries. The rise of populism is fueled by the growing dichotomy between the elites who have benefitted socially and monetarily from the revolution and those who have not. In the 1890’s, anti-railroad sentiment drove the creation of the populist party. More recently, people have become angry at tech giants (Facebook, Google, Amazon, Apple, Twitter) for unfair labor practices, psychological manipulation, and monopolistic tendencies. The recent movie, the Social Dilemma, which suggests a more humane and regulatory focused approach to social media, speaks to the need for regulation of these massive companies. It is also incredibly ironic to watch a movie about how social media is manipulating its users while streaming a movie that was recommended to me on Netflix, a company that has popularized incessant binge-watching through UX manipulation, not dissimilar to Facebook and Google’s tactics. I expect these companies to get regulated soon -and I hope that once that happens, we enter into the Synergy phase of growth and value accruing to all people.

Yes, I do. I will find the time to reply to you properly. But just quickly, I think installation was prolonged by QE &casino finance; we are at the turning point (the successful rise of populism is a sign) and maybe post-Covid we'll go into synergy.

— Carlota Perez (@CarlotaPrzPerez) January 17, 2021

Business Themes

1. The role of Financial Capital in Revolutions. As the new technology revolutions play themselves out, financial capital appears right alongside technology developments, ready to mold the revolution into the phases suggested by Perez. In the irruption phase, as new technology is taking hold, financial capital that had been on the sidelines waiting out the Maturity phase of the previous revolution plows into new company formation and ideas. The financial sector tries to adopt the new technology as soon as possible (we are already seeing this with Quantum computing), so it can then espouse the benefits to everyone it talks to, setting the stage for increasing financing opportunities. Eventually, demand for financing company creation goes crazy, and you enter into a Frenzy phase. During this phase, there is a discrepancy between the value of financial capital and production capital, or money used by companies to create actual products and services. Financial capital believes in unrealistic returns on investment, funding projects that don’t make any sense. Perez notes: “In relation to the canal Mania of the 1790s, disorder and lack of coordination prevailed in investment decisions. Canals were built ‘with different widths and depths and much inefficient routing.’ According to Dan Roberts at the Financial Times, in 2001 it was estimated that only 1 to 2 percent of the fiber optic cable buried under Europe and the United States had so far been turned on.” These Frenzy phases create bubbles and further ingrain regulatory mismatch and political divide. Could we be in one now with deals getting priced at 125x revenue for tiny companies? After the institutional reckoning, the Technology revolution enters the Synergy phase where production capital has really strong returns on investment - the path of technology is somewhat known and real gains are to be made by continuing investment (especially at more reasonable asset prices). Production capital continues to go to good use until the technology revolution fully plays itself out, entering into the Maturity phase.

2. Casino Finance and Prolonging Bubbles. One point that Perez makes in her tweet, is that this current bubble has been prolonged by QE and casino finance. Quantitative easing is a monetary policy where the federal reserve (US’s central bank) buys government bonds issued by the treasury department to inject money into the financial ecosystem. This money at the federal reserve can purchase bank loans and assets, offering more liquidity to the financial system. This process is used to create low-interest rates, which push individuals and corporations to invest their money because the rate of interest on savings accounts is really really low. Following the financial crisis and more recently COVID-19, the Federal Reserve lowered interest rates and started quantitative easing to help the hurting economy. In Perez’s view, these actions have prolonged the Irruption and Frenzy phases because it forces more money into investment opportunities. On top of quantitative easing, governments have allowed so-called Casino Capitalism - allowing free-market ideals to shape governmental policies (like Reagan’s economic plan). Uninterrupted free markets are in theory economically efficient but can give rise to bad actors - like Enron’s manipulation of California’s energy markets after deregulation. By engaging in continual quantitative easing and deregulation, speculative markets, like collateralized loan obligations during the financial crisis, are allowed to grow. This creates a risk-taking environment that can only end in a frenzy and bubble.

3. Synergy Phase and Productive Capital Allocation. Capital allocation has been called the most important part of being a great investor and business leader. Think about being the CEO of Coca Cola for a second - you have thousands of competing projects, vying for budget - how do you determine which ones get the most money? In the investing world, capital allocation is measured by conviction. As George Soros’s famous quote goes: “It's not whether you're right or wrong, but how much money you make when you're right and how much you lose when you're wrong.” Clayton Christensen took the ideas of capital allocation and compared them to life investments, coming to the conclusion: “Investments in relationships with friends and family need to be made long, long before you’ll see any sign that they are paying off. If you defer investing your time and energy until you see that you need to, chances are it will already be too late.” Capital and time allocation are underappreciated concepts because they often seem abstract to the everyday humdrum of life. It is interesting to think about capital allocation within Perez’s long-term framework. The obvious approach would be to identify the stage (Irruption, Frenzy, Synergy, Maturity) and make the appropriate time/money decisions - deploy capital into the Irruption phase, pull money out at the height of the Frenzy, buy as many companies as possible at the crash/turning point, hold through most of the Synergy, and sell at Maturity to identify the next Irruption phase. Although that would be fruitful, identifying market bottoms and tops is a fool’s errand. However, according to Perez, the best returns on capital investment typically happen during the Synergy phase, where production capital (money employed by firms through investment in R&D) reigns supreme. During this time, the revolutionary applications of recently frenzied technology finally start to bear fruit. They are typically poised to succeed by an accommodating regulatory and social environment. Unsurprisingly, after the diabolic grifting financiers of the frenzy phase are exposed (see Worldcom, Great Financial Crisis, and Theranos), social pressures on regulators typically force an agreement to fix the loopholes that allowed these manipulators to take advantage of the system. After Enron, the Sarbanes-Oxley act increased disclosure requirements and oversight of auditors. After the GFC, the Dodd-Frank act mandated bank stress tests and introduced financial stability oversight. With the problems of the frenzy phase "fixed” for the time being, the social attitude toward innovation turns positive once again and the returns to production capital start to outweigh financial capital which is now reigned in under the new rules. Suffice to say, we are probably in the Frenzy phase in the technology world, with a dearth of venture opportunities, creating a massive valuation increase for early-stage companies. This will change eventually and as Warren Buffett says: “It’s only when the tide goes out that you learn who’s been swimming naked.” When the bubble does burst, regulation of big technology companies will usher in the best returns period for investors and companies alike.

Dig Deeper

• The Financial Instability Hypothesis: Capitalist Processes and the Behavior of the Economy

• Bubbles, Golden Ages, and Tech Revolutions - a Podcast with Carlota Perez

• Jeff Bezos: The electricity metaphor (2007)

• Where Does Growth Come From? Clayton Christensen | Talks at Google

• A Spectral Analysis of World GDP Dynamics: Kondratieff Waves, Kuznets Swings, Juglar and Kitchin Cycles in Global Economic Development, and the 2008–2009 Economic Crisis

December 2019 - The Moon is a Harsh Mistress by Robert A. Heinlein

This futuristic, anti-establishment thriller is one of Elon Musk’s favorite books. While Heinlein’s novel can drag on with little action, The Moon is a Harsh Mistress presents an interesting war story and predicts several technological revolutions.

Tech Themes

1. Mike, the self-aware computer and IBM. Mycroft Holmes, Heinlein’s self-aware, artificially intelligent computer is a friendly, funny and focused companion to Manny, Wyoh and Prof throughout the novel. Mike’s massive hardware construction is analogous to the way companies are viewing Artificial Intelligence today. Mike’s AI is more closely related to Artificial General Intelligence, which imagines a machine that can go beyond the standard Turing Test, with further abilities to plan, learn, communicate in natural language and act on objects. The 1960s were filled with predictions of futuristic robots and machines. Ideas were popularized not only in books like The Moon is a Harsh Mistress but also in films like 2001: A Space Odyssey, where the intelligent computer, HAL 9000, attempts to overthrow the crew. In 1965, Herbert Simon, a noble prize winner, exclaimed: “machines will be capable, within twenty years, of doing any work a man can do.” As surprising as it may seem today, the dominant technology company of the 1960’s was IBM, known for its System/360 model. Heinlein even mentions Thomas Watson and IBM at Mike’s introduction: “Mike was not official name; I had nicknamed him for Mycroft Holmes, in a story written by Dr. Watson before he founded IBM. This story character would just sit and think--and that's what Mike did. Mike was a fair dinkum thinkum, sharpest computer you'll ever meet.” Mike’s construction is similar to that of present day IBM Watson, who’s computer was able to win Jeopardy, but has struggled to gain traction in the market. IBM and Heinlein approached the computer development in a similar way, Heinlein foresaw a massive computer with tons of hardware linked into it: “They kept hooking hardware into him--decision-action boxes to let him boss other computers, bank on bank of additional memories, more banks of associational neural nets, another tubful of twelve-digit random numbers, a greatly augmented temporary memory. Human brain has around ten-to-the tenth neurons. By third year Mike had better than one and a half times that number of neuristors.” This is the classic IBM approach – leverage all of the hardware possible and create a massive database of query-able information. This actually does work well for information retrieval like Jeopardy, but stumbles precariously on new information and lack of data, which is why IBM has struggled with Watson applications to date.

2. Artificial General Intelligence. Mike is clearly equipped with artificial general intelligence (AGI); he has the ability to securely communicate in plain language, retrieve any of the world’s information, see via cameras and hear via microphones. As discussed above, Heinlein’s construction of Mike is clearly hardware focused, which makes sense considering the book was published in the sixties, before software was considered important. In contrast to the 1960s, today, AGI is primarily addressed from an algorithmic, software angle. One of the leading research institutions (excluding the massive tech companies) is OpenAI, an organization who’s mission is: “To ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity.” OpenAI was started by several people including Elon Musk and Sam Altman, founder of Y Combinator, a famous startup incubator based in Silicon Valley. OpenAI just raised $1 billion from Microsoft to pursue its artificial algorithms and is likely making the most progress when it comes to AGI. The organization has released numerous modules that allow developers to explore the wide-ranging capabilities of AI, from music creation, to color modulation. But software alone is not going to be enough to achieve full AGI. OpenAI has acknowledged that the largest machine learning training runs have been run on increasingly more hardware: “Of course, the use of massive compute sometimes just exposes the shortcomings of our current algorithms.” As we discussed before (companies are building their own hardware for this purpose, link to building their own hardware), and the degradation of Moore’s Law imposes a serious threat to achieving full Artificial General Intelligence.

3. Deep Learning, Adam Selene, and Deep Fakes. Heinlein successfully predicted machine’s ability to create novel images. As the group plans to take the rebellion public, Mike is able to create a depiction of Adam Selene that can appear on television and be the face of the revolution: “We waited in silence. Then screen showed neutral gray with a hint of scan lines. Went black again, then a faint light filled middle and congealed into cloudy areas light and dark, ellipsoid. Not a face, but suggestion of face that one sees in cloud patterns covering Terra. It cleared a little and reminded me of pictures alleged to be ectoplasm. A ghost of a face. Suddenly firmed and we saw "Adam Selene." Was a still picture of a mature man. No background, just a face as if trimmed out of a print. Yet was, to me, "Adam Selene." Could not he anybody else.” Image generation and manipulation has long been a hot topic among AI researchers. The research frequently leverages a technique called Deep Learning, which is a play on classically used Artificial Neural Networks. A 2012 landmark paper from the University of Toronto student Ilya Sutskever, who went on to be a founder at OpenAI, applied deep learning to the problem of image classification with incredible success. Deep learning and computer vision have been inseparable ever since. One part of research focuses on a video focused image superimposition technique called Deep Fakes, which became popular earlier this year. As shown here, these videos are essentially merging existing images and footage with a changing facial structure, which is remarkable and scary at the same time. Deep fakes are gaining so much attention that even the government is focused on learning more about them. Heinlein was early to the game, imaging a computer could create a novel image. I can only imagine how he’d feel about Deep Fakes.

Business Themes

1. Video Conferencing. Manny and the rest of the members of the revolution communicate through encrypted phone conversations and video conferences. While this was certainly ahead of its time, video conferencing was first imagined in the late 1800s. Despite a clear demand for the technology, it took until the late 2000s arguably, to reach appoint where mass video communication was easily accessible for businesses (Zoom Video) and individuals (FaceTime, Skype, etc.) This industry has constantly evolved and there are platforms today that offer both secure chat and video such as Microsoft Teams and Cisco Webex. The entire industry is a lesson in execution. The idea was dreamed up so long ago, but it took hundreds of years and multiple product iterations to get to a de-facto standard in the market. Microsoft purchased Skype in 2011 for $8.5B, the same year that Eric Yuan founded Zoom. This wasn’t Microsoft’s first inroads into video either, in 2003, Microsoft bought Placeware and was supposed to overtake the market. But they didn’t and Webex continued to be a major industry player before getting acquired by Cisco. Over time Skype popularity has waned, and now, Microsoft Teams has a fully functioning video platform separate from Skype – something that Webex did years ago. Markets are constantly in a state of evolution, and its important to see what has worked well. Skype and Zoom both succeeded by appealing to free users, Skype initially focused on free consumers, and Zoom focused on free users within businesses. WebEx has always been enterprise focused but they had to be, because bandwidth costs were too high to support a video platform. Teams will go to market as a next-generation alternate/augmentation of Outlook; it will be interesting to see what happens going forward.

2. Privacy and Secure Communication. As part of the revolution’s communication, a secure, isolated message system is created whereby not only are conversations fully encrypted and undetected by authorities but also individuals are unable to speak with more than two others in their revolution tree. Today, there are significant concerns about secure communication – people want it, but they also do not. Facebook has declared that they will implement end to end encryption despite warnings from the government not to do so. Other mobile applications like Telegram and Signal promote secure messaging and are frequently used by reporters for anonymous tips. While encryption is beneficial for those messaging, it does raise concerns about who has access to what information. Should a company have access to secure messages? Should the government have access to secure messages? Apple has always stayed strong in its privacy declaration, but has had its own missteps. This is a difficult question and the solution must be well thought out, taking into account unintended consequences of sweeping regulation in any direction.

3. Conglomerates. LuNoHo Co is the conglomerate that the revolution utilized to build a massive catapult and embezzle funds. While Mike’s microtransaction financial fraud is interesting (“But bear in mind that an auditor must assume that machines are honest.”), the design of LuNoHo Co. which is described as part bank, part engineering firm, and part oil and gas exploitation firm, interestingly addresses the conventional business wisdom of the times. In the 1960s, coming out of World War II, conglomerates began to really take hold across many developing nations. The 1960s were a period of low interest rates, which allowed firms to perform leveraged buyouts of other companies (using low interest loans), sometimes in a completely unrelated set of industries. Activision was once part of Vivendi, a former waste management, energy, construction, water and property conglomerate. The rationale for these moves was often that a much bigger organization could centralize general costs like accounting, finance, legal and other costs that touched every aspect of the business. However, when interest rates rose in the late 70s and early 80s, several conglomerate profits fell, and the synergies promised at the outset of the deal turned out to be more difficult to realize than initially assumed. Conglomerates are incredibly popular in Asia, often times supported by the government. In 2013, McKinsey estimated: “Over the past decade, conglomerates in South Korea accounted for about 80 percent of the largest 50 companies by revenues. In India, the figure is a whopping 90 percent. Meanwhile, China’s conglomerates (excluding state-owned enterprises) represented about 40 percent of its largest 50 companies in 2010, up from less than 20 percent a decade before.” Softbank, the famous Japanese conglomerate and creator of the vision fund, was originally a shrink-wrap software distributor but now is part VC and part Telecommunications provider. We’ve discussed the current state of Chinese internet conglomerates, Alibaba and Tencent who each own several different business lines. Over the coming years, as internet access in Asia grows more pervasive and the potential for economic downturn increases, it will be interesting to see if these conglomerates break apart and focus on their core businesses.

Dig Deeper

• The rise and fall of Toshiba

• Using Artificial Intelligence to Create Talking Images

• MIT Lecture on Image Classification via Deep Learning

• 2019 Trends in the Video Conferencing Industry

• The Moon is a Harsh Mistress may be a movie

August 2019 - How Google Works by Eric Schmidt and Jonathan Rosenberg

While at times it reads as a piece of Google propaganda, this book offers insight into the management techniques that Larry, Sergey and Eric employed to grow the Company to massive scale. Its hard to read this book and expect that all of these practices were actually implemented – it reads like a “How to build a utopia work culture” - but some of the principles are interesting, and more importantly it gives us insight into what Google values in their products and operations.

Tech Themes

1. Smart Creatives. Perhaps the most important emphasis in the book is placed on the recruiting and hiring of what Eric Schmidt and Jonathan Rosenberg have termed: Smart Creatives – “people who combine technical & business knowledge, creativity and always-learning attitude.” While these seem like the desired platitudes of every silicon valley employee, it gives a window into what Google finds important in its employees. For example, unlike Amazon, which has both business product managers and technical product managers, Google prefers its PMs to be both business focused and highly technical. Smart Creatives are mentioned hundreds of times in the book and continually underpin the success of new product launches. The book almost harps on it too much, to the point where it feels like Eric Schmidt was trying to convince all Googlers that they were truly unique.

2. Meetings, Q&A, Data and Information Management. Google is one of the many Silicon Valley companies that hosts company wide all-hands Q&A sessions on Friday where anyone can ask a question of Google’s leadership. Information transparency is critically important to Google, and they try to allow data to be accessible throughout the organization at all times. This trickles into other aspects of Google’s management philosophy including meetings and information management. At Google, meetings have a single owner, and while laptops largely remain closed, it’s the owner’s job to present the relevant data and derive the correct insights for the team. To that end, Google makes its information transparently available for all to access – this process is designed to avoid information asymmetry at management levels. One key issue faced by poor management teams is only receiving the best information at the top – this is countered by Amazon through incredibly blunt and aggressive communication; Google, on the other hand, maintains its intense focus on data and results to direct product strategy, so much so that it even studies its own teams productivity using internal data. Google’s laser focus on data makes sense given its main advertising products harvest the world’s internet user data for their benefit, so understanding how to leverage data is always a priority at Google.

3. 80/20 Time. As part of Google’s product innovation strategy, employees can spend 20% of their work time on creative projects separate from their current role. While the idea sounds like an awesome to keep employees interested and motivated, in practice, its much more structured. Ideas have to be approved by managers and they are only allowed if they can directly impact Google’s business. Some great innovations were spawned out of this policy including Gmail and Google Maps but Google employees have joked that it should be called “120%” time rather than 80%.

Business Themes

1. Google’s Cloud Strategy. “You should spend 80% of your time on 80% of your revenue.” This quote speaks volumes when it comes to Google’s business strategy. Google clearly is the leader in Search and search advertising. Not only is it the default search engine preferred by most users, it also owns the browser market that directs searches to Google, and the most used operating system. It has certainly created a dominant position in the market and even done illegal things to maintain that advantage. Google also maintains and mines your data, and as Stratechery has pointed out, they are not hiding it anywhere. But what happens when the next wave of computing comes, and you are so focused on your core business that you end up light years behind competition from Amazon (Web Services) and Microsoft (Azure)? That’s where Google finds itself today, and recent outages and issues haven’t helped. So what is Google’s “Cloud Strategy?” The answer is lower priced, open source alternatives. Google famously developed and open sourced, Kubernetes, the container orchestration platform, which has become an increasingly important technology as developers opt for light weight alternatives to traditional virtual machines. They have followed this open sourcing with a, “We are going to open source everything” mentality that is also being employed, a bit more defensively at Microsoft. Google seeks to be an open source layer, either through Kubernetes (which runs in Azure and AWS) or through other open source platforms (Anthos) and just touch some of your company’s low churn cloud spend. Their issue is scale and support. With their knowledge of data centers and parallel computing, cloud capabilities seemed like an obvious place where Google could win, but they fumbled on building a great product because they were so focused on protecting their core business. They are in a catch up position and new CEO of Google Cloud, Thomas Kurian (formerly at Oracle), isn’t afraid to make acquisitions to build out missing product capabilities, which is why it bought Looker earlier this year. It makes sense why a company as focused as Google is on data, would want a cloud focused data analysis tool. Now they are betting on M&A and a highly open-sourced multi-public cloud future as the only way they can win.

2. “Objective” Key Results. As mentioned previously, the way Google combats potential information asymmetries by empowering individuals throughout the organization with data. This extends to famous venture capitalist (who invested in both Google and Amazon) John Doerr’s favorite data to examine – OKRs – Objective key results. Each Googler has a specific set of OKRs that they are responsible for maintaining on a quarterly basis. Every person’s OKRs are readily available for anyone to see throughout the Company i.e. full transparency. OKRs are public, measurable, and ambitious. This keeps engineers focused and accountable, as long as the OKRs are set correctly and actually measure outcomes. These fit so perfectly with Google’s focus on mining and monitoring data at all times: their products and their employees need to be data driven at all times.

Dig Deeper

• Recent reports highlight numerous cultural issues at Google, that are not addressed in the book

• Google Cloud was plagued by internal clashes and missed acquisitions

• PayPal mafia veteran, Keith Rabois, won’t fund Google PM’s as founders

• List of Google’s biggest product failures over time

• Stadia: Google’s game streaming service

July 2019 - Alibaba: The House That Jack Ma Built by Duncan Clark

This is an excellent book to understand Jack Ma, Alibaba and the Chinese tech ecosystem.

Tech Themes

1. Start with a Team: Alibaba’s 18 founders. At a young age, Jack Ma taught himself English by offering tours of his hometown Hangzhou to locals coming from English speaking countries. Jack went on to study English at Hangzhou Teachers Institute where he graduated in 1988. Following graduation, he taught English for a few years and because of his English skills, he was selected to go on a trip to America, on behalf of the Hangzhou government. While there, he tried using the internet to look up “beer” and noticed there were very few Chinese web pages. When he got back to China, he started China Pages, a custom website development shop for Chinese businesses. The business received funding from the Ministry of Foreign Trade and Economic Cooperation but was losing out to rival telecom company Hangzhou Communications that had recently started a competitor. China Pages was struggling to help customers realize return on their investments because there was so little business happening online at that time in China. Frustrated by competition and worried about the long-term effects of being funded by the government, Jack rounded up a group of 17 people - some were former students, some colleagues in the government, some employees at China Pages - and started Alibaba. Jack also met and recruited Joe Tsai, the first Taiwanese graduate of Yale Law School, who was then working at Investor AB on private equity investments, to join as CFO and founding board member. The team focused on the business to business market which they felt should gain more traction before business to consumer focused companies like Amazon.

2. Open Door Policies: How China became an economic powerhouse. In 2009, China became the World’s biggest exporter, a trend that until recently, seemed all the more likely to continue. But how did we get to this point in China? In 1979, Deng Xiaoping began a series of economic reforms in China that set the stage for enormous growth. The first major act was allowing Chinese individuals to start businesses, a practice that had been strictly forbidden during the previous political era. Next, Deng announced an Open Door Policy, to allow foreign business and investment to flow into specific, Special Economic Zones. This investment spawned incredible growth in now-famous Chinese regions including Shenzhen, which grew GDP on average of 40% per year from 1981 to 1993 and by 2005 became the world’s 3rd busiest port. This incredible growth has created massive companies and seen incredible innovation but has also created global pollution. How sustainable is this great economic expansion?

3. Right Place at the Right Time: The Importance of Timing in Innovation at Alibaba. When trying to build a business, timing can often be more important than the product itself. This can work in a number of ways - during the internet bubble, several entrepreneurs became millionaires on the backs of grandiose ideas without business models. Alibaba is the perfect example of excellent timing. Alibaba was founded in 1999, right as the internet bubble started to heat up. As valuations rose, institutional investors saw returns skyrocketing; this led Goldman Sachs to open up a dedicated Asia Tech fund, focused on investing small amounts into growing Chinese tech companies. Goldman led Alibaba’s first round in 1999 (a $3.3M fundraise), which allowed Alibaba to grow to significant scale with their tight founding team. The internet bubble also attracted a now re-famous Masayoshi Son, and his software distributor turned VC firm, Softbank, to start investing heavily in the internet. Aliababa was by no means the only fast growing Asian Tech company: Sohu (Founded in 1996 by Charles Zhang), Sina (founded in 1998 by Charles Chao who pioneered the Variable Interest Entity designation in China), and NetEase (Founded in 1997 by Ding Lei) were the famed Asian tech darlings of the day. In March 2001, right before the bubble burst, Softbank led a $20M round into Alibaba (which we discuss more below) that allowed Jack the flexibility to weather the internet bubble storm and keep Alibaba private despite growing losses. Sohu, Sina, and NetEase all needed to IPO and limped out into the public markets at poor valuations (Sohu dropped below $1 per share at one point), which caused a long-term drag on their stock prices and business performance. While Alibaba clearly had reached product-market fit by that time, their fortuitous timing (much like that of Amazon’s bond offering) allowed the Company to stay in business during a tough financial time.

Business Themes

1. Different Approaches to Similar Problems: Amazon vs. Alibaba. Alibaba is often hailed as the Amazon of China, but it’s actually, quite different in many major aspects. As discussed recently in this Stratechery article, Amazon’s core e-commerce business is about controlling inventory and logistics. Amazon buys at whole sale prices from brands, keeps the inventory in their 400+ warehouses and ships them out to customers. Retailers pay Amazon a fee on the sale as commission. While this revenue model is similar to Alibaba’s Tmall, a major brand e-commerce site that charges commissions on sale, Alibaba does not retain any inventory in the process. Furthermore, on Alibaba’s Taobao, independent small merchants can list any item for sale and pay no commissions, instead they pay for higher ranking on the site’s internal search engine, similar to Google’s revenue model. While Amazon boxes are delivered nationwide, primarily by Amazon, in China, Alibaba leverages a slew of 3rd party logistics providers to deliver packages any way possible: via bike, motorcycle, car, or on foot. This impacts profit margins as Amazon has to employ its entire logistics operation (350,000+ people) whereas Alibaba is comparatively smaller at 50,000 employees. Beyond their core e-commerce businesses, both Alibaba and Amazon have cloud computing offerings – as discussed before, AWS is the biggest platform in North America, and Alibaba is the biggest in China. While cloud in China is now growing more quickly than North America, it remains a much smaller piece of the overall global cloud landscape.

2. A Lesson in Investing: Analyzing Goldman, Softbank, and Yahoo’s Returns. Alibaba’s funding history is long and complex but illustrates a common dilemma faced by investors and shareholders in startups. Alibaba’s first funding round was led by Goldman Sachs at a $5M pre-money valuation. The next round was a $20M investment in Alibaba, led by Softbank to acquire 1/3 of the Company. At the next funding round in 2004, Softbank invested in an $82M round and Goldman sold its shares, thereby inking a 6.7x return in about 5 years, which by all means is a great investment. However, if Goldman had held on to that share, as Softbank did with its share, at IPO it would have been worth $12.5B, a 3,600x+ return. This is the dilemma faced by several VCs – do I sell now, ink a great return, and make my limited partners happy? Or do I risk it, let my winners ride and realize a potentially career changing win? Yahoo is another example of this complex dilemma. Yahoo invested $1B in Alibaba in 2005 for a 40% stake in the Company (a funding round that was allegedly hashed out over golf at Pebble Beach). After rebuffing Microsoft’s $44.6B offer to buy the Company, Yahoo’s stock price plummeted. A difficult fight with activist investors ensued, and Jerry Yang was eventually fired. This all set up nicely for new CFO, Scott Thompson to come in and promptly offload half of its Alibaba stake for $7.1B, two years later that would be worth $51B. Yahoo, now owned by Verizon, sold its remaining stake earlier this year, and its expected to net shareholders roughly $40B in value.

3. The Everything Companies: The Holdings of Chinese Internet Giants. The number and variety of companies owned by the major tech giants in China is simply staggering. Alibaba has bet big on a wide variety of companies including delivery giant Meituan-Dianping, Lyft, Snap, bike sharing startup Ofo, Chinese ride-hailing company Didi (which recently merged with Uber’s China business), fintech spinoff Ali-Pay and several others. Tencent, creator of the famous all-in-one application, WeChat, has invested in JD.com, League of Legends creator Riot Games, Fortnite creator Epic Games, and many more. Alibaba and Tencent are so competitive with one another that in recent years, the Companies have made thousands of investments trying to fund the next phase of growth in Chinese Tech. As the economist writes, “Tencent has a portfolio of 600 stakeholdings acquired over the past six years (see chart), many unannounced. There is barely a trace of bombast when Jack Ma, Alibaba’s founder, says that he eventually hopes to see former Alibaba employees running 200 of the top 500 Chinese firms.” It will be interesting to see how these investments mature – in 2018 rival delivery firms Meituan and Dianping had to merge to avoid going bankrupt despite billions in funding from Alibaba and Tencent.

Dig Deeper

• The Rise of China's Innovation Machine by WSJ

• Detail on the Uber-Didi ride-sharing merger in China from Business Insider

• 9:00am - 9:00pm, 6 days a week (9-9-6) is what Jack Ma wants out of his employees

• Jack Ma hated eBay

• Tencent’s Investment in Epic Games / Fortnite