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August 2023 - Capital Returns by Edward Chancellor

We dive into an investing book that covers the capital cycle. In summary, the best time to invest in a sector is actually when capital is leaving or has left.

Tech Themes

  1. Amazon. Marathon understands that the world moves in cycles. During the internet bubble of the late 1990s the company refused to invest in a lot of speculative internet companies. “At the time, we were unable to justify the valuations of any of these companies, nor identify any which could safely say would still be going strong in years to come.” In August of 2007, however, several years after the internet bubble burst, they noticed Amazon again. Amazon’s stock had rebounded well from the lows of 2001 and was roughly flat from its May 1999 valuation. Sales had grown 10x since 1999 and while they recognized it had a tarnished reputation from the internet bubble, it was actually a very good business with a negative working capital cycle. On top of this, the reason the stock hadn’t performed well in the past few years was because they were investing in two new long-term growth levers, Amazon Web Services and Fulfillment by Amazon. I’m sure Marathon underestimated the potential for these businesses but we can look back now and know how exceptional and genius these margin lowering investments were at the time.

  2. Semis. Nothing paints a more clear picture of cyclicality than semiconductors. Now we can debate whether AI and Nvidia have moved us permanently out of a cycle but up until 2023, Semiconductors was considered cyclical. As Marathon notes: “Driven by Moore’s law, the semiconductor sector has achieved sustained and dramatic performance increases over the last 30years, greatly benefiting productivity and the overall economy. Unfortunately, investors have not done so well. Since inception in 1994, the Philadelphia Semiconductor Index has underperformed the Nasdaq by around 200 percentage point, and exhibited greater volatility…In good times, prices pick up, companies increase capacity, and new entrants appear, generally from different parts of Asia (Japan in the 1970s, Korea in 1980s, Taiwan in the mid1990s, and China more recently). Excess capital entering at cyclical peaks has led to relatively poor aggregate industry returns.” As Fabricated Knowledge points out the 1980s had two brutal Semiconductor cycles. First, in 1981, the industry experienced severe overcapacity, leading to declining prices while inflation ravaged through many businesses. Then in 1985, the US semiconductor business declined significantly. “1985 was a traumatic moment for Intel and the semiconductor industry. Intel had one of the largest layoffs in its history. National Semi had a 17% decrease in revenue but moved from an operating profit of $59 million to an operating loss of -$117 million. Even Texas Instruments had a brutal period of layoffs, as revenue shrank 14% and profits went negative”. The culprit was Japanese imports. Low-end chips had declined significantly in price, as Japan flexed its labor cost advantage. All of the domestic US chip manufacturers complained (National Semiconductor, Texas Instruments, Micron, and Intel), leading to the 1986 US-Japan Semiconductor Agreement, effectively capping Japanese market share at 20%. Now, this was a time when semiconductor manufacturing wasn’t easy, but easier than today, because it focused mainly on more commoditized memories. 1985 is an interesting example of the capital cycle compounding when geographic expansion overlaps with product overcapacity (as we had in the US). Marathon actually preferred Analog Devices, when it published its thesis in February 2013, highlighting the complex production process of analog chips (physical) vs. digital, the complex engineering required to build analog chips, and the low-cost nature of the product. “These factors - a differentiated product and company specific “sticky” intellectual capital - reduce market contestability….Pricing power is further aided by the fact that an analog semiconductor chip typically plays a very important role in a product for example, the air-bag crash sensor) but represents a very small proportion of the cost of materials. The average selling price for Linear Technology’s products is under $2.” Analog Devices would acquire Linear in 2017 for $14.8B, a nice coda to Marathon’s Analog/Linear dual pitch.

  3. Why do we have cycles? If everyone is playing the same business game and aware that markets come and go, why do we have cycles at all. Wouldn’t efficient markets pull us away from getting too hyped when the market is up and too sour when the market is down? Wrong. Chancellor gives a number of reasons why we have a capital cycle: Overconfidence, Competition Neglect, Inside View, Extrapolation, Skewed Incentives, Prisoner’s Dilemma, and Limits to Arbitrage. Overconfidence is somewhat straightforward - managers and investors look at companies and believe they are infallible. When times are booming, managers will want to participate in the boom, increasing investment to match “demand.” In these decisions, they often don’t consider what their competitors are doing, but rather focus on themselves. Competition neglect takes hold as managers enjoy watching their stock tick up and their face be splattered across “Best CEO in America” lists. Inside View is a bit more nuanced, but Michael Mauboussin and Daniel Kahneman have written extensively on it. As Kahneman laid out in Thinking, Fast & Slow: “A remarkable aspect of your mental life is that you are rarely stumped … The normal state of your mind is that you have intuitive feelings and opinions about almost everything that comes your way. You like or dislike people long before you know much about them; you trust or distrust strangers without knowing why; you feel that an enterprise is bound to succeed without analyzing it.” When you take the inside view, you rely exclusively on your own experience, rather than other similar situations. Instead, you should take the outside view and assume your problem/opportunity/case is not unique. Extrapolation is an extremely common driver of cycles, and can be seen all across the investing world after the recent COVID peak. Peloton, for example, massively over-ordered inventory extrapolating out pandemic related demand trends. Skewed incentives can include near-term EPS targets (encourages buybacks, M&A), market share preservation (encourages overinvestment), low cost of capital (buy something with cheap debt), analyst expectations, and champion bias (you’ve decided to do something and its no longer attractive, but you do it anyway because you got people excited about it). The Prisoner’s Dilemma is also a form of market share preservation/expansion, when your competitor may be acting much more aggressively and you have to decide whether its worth the fight. Limits to Arbitrage is almost an extension of career risk, in that, when everyone owns an overvalued market, you may actually hurt your firm by actively withholding even if it makes investment sense. That’s why many firms need to maintain a low tracking error against indexes, which can naturally result in concentrations in the same stocks.

Business Themes

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  1. Capital Cycle. The capital cycle has four stages: 1. New entrants attracted by prospect of high returns: investor optimistic 2. Rising competition causes returns to fall below cost of capital: share price underperforms 3. Business investment declines, industry consolidation, firms exit: investors pessimistic 4. Improving supply side causes returns to rise above the cost of capital: share price outperforms. The capital cycle reveals how competitive forces and investment behavior create predictable patterns in industries over time. Picture it as a self-reinforcing loop where success breeds excess, and pain eventually leads to gain. Stage 1: The Siren Song - High returns in an industry attract capital like moths to a flame. Investors, seeing strong profits and growth, eagerly fund expansions and new entrants. Optimism reigns and valuations soar as everyone wants a piece of the apparent opportunity. Stage 2: Reality Bites - As new capacity comes online, competition intensifies. Prices fall as supply outpaces demand. Returns dip below the cost of capital, but capacity keeps coming – many projects started in good times are hard to stop. Share prices begin to reflect the deteriorating reality. Stage 3: The Great Cleansing - Pain finally drives action. Capital expenditure is slashed. Weaker players exit or get acquired. The industry consolidates as survivors battle for market share. Investors, now scarred, want nothing to do with the sector. Capacity starts to rationalize. Stage 4: Phoenix Rising - The supply-side healing during the downturn slowly improves industry economics. With fewer competitors and more disciplined capacity, returns rise above the cost of capital. Share prices recover as improved profitability becomes evident. But this very success plants the seeds for the next cycle. The genius of understanding this pattern is that it's perpetual - human nature and institutional incentives ensure it repeats. The key is recognizing which stage an industry is in, and having the courage to be contrarian when others are either too optimistic or too pessimistic.

  2. 7 signs of a bubble. Nothing gets people going more than Swedish Banking in the 2008-09 financial crisis. Marathon called out its Seven Deadly Sins of banking in November 2009, utilizing Handelsbanken as a positive reference, highlighting how they avoided the many pitfalls that laid waste to their peers. 1. Imprudent Asset-Liability mismatches on the balance sheet. If this sounds familiar, its because its the exact sin that took down Silicon Valley Bank earlier this year. As Greg Brown lays out here: “Like many banks, SVB’s liabilities were largely in the form of demand deposits; as such, these liabilities tend to be short term and far less sensitive to interest rate movement. By contrast, SVB’s assets took the form of more long-term bonds, such as U.S. Treasury securities and mortgage-backed securities. These assets tend to have a much longer maturity – the majority of SVB’s assets matured in 10 years or more – and as a result their prices are much more sensitive to interest rate changes. The mismatch, then, should be obvious: SVB was taking in cash via short-term demand deposits and investing these funds in longer-term financial instruments.” 2. Supporting asset-liability mismatches by clients. Here, Chancellor calls out foreign currency lending, whereby certain European banks would offer mortgages to Hungarians in swiss francs, to buy houses in Hungary. Not only were these banks taking on currency risk, they were exposing their customers to it and many didn’t hedge the risk out appropriately. 3. Lending to “Can’t Pay, Won’t Pay” types. The financial crisis was filled with banks lending to subprime borrowers. 4. Reaching for growth in unfamiliar areas. As Marathon calls out, “A number of European banks have lost billions investing in US subprime CDOs, having foolishly relied on “experts” who told them these were riskless AAA rated credits.” 5. Engaging in off-balance sheet lending. Many European banks maintained "Structured Investment Vehicles” that were off-balance sheet funds holding CDOs and MBSs. At one point, it got so bad that Citigroup tried the friendship approach: “The news comes as a group of banks in the U.S. led by Citigroup Inc. are working to set up a $100 billion fund aimed at preventing SIVs from dumping assets in a fire sale that could trigger a wider fallout.” These SIVs held substantial risk but were relatively unknown to many investors. 6. Getting sucked into virtuous/vicious cycle dynamics. As many European banks looked for expansion, they turned to lending into the Baltic states. As more lenders got comfortable lending, GDP began to grow meaningfully, which attracted more aggressive lending. More banks got suckered into lending in the area to not miss out on the growth, not realizing that the growth was almost entirely debt fueled. 7. Relying on the rearview mirror. Marathon points out how risk models tend to fail when the recent past has been glamorous. “In its 2007 annual report, Merrill Lunch reported a total risk exposure - based on ‘a 95 percent confidence interval and a one day holding period’ - of $157m. A year later, the Thundering Herd stumbled into a $30B loss!”

  3. Investing Countercyclically. Björn Wahlroos exemplified exceptional capital allocation skills as CEO of Sampo, a Finnish financial services group. His most notable moves included perfectly timing the sale of Nokia shares before their collapse, transforming Sampo's property & casualty insurance business into the highly profitable "If" venture, selling the company's Finnish retail banking business to Danske Bank at peak valuations just before the 2008 financial crisis, and then using that capital to build a significant stake in Nordea at deeply discounted prices. He also showed remarkable foresight by reducing equity exposure before the 2008 crisis and deploying capital into distressed commercial credit, generating €1.5 billion in gains. Several other CEOs have demonstrated similar capital allocation prowess. Henry Singleton at Teledyne was legendary for his counter-cyclical approach to capital allocation. He issued shares when valuations were high in the 1960s to fund acquisitions, then spent the 1970s and early 1980s buying back over 90% of Teledyne's shares at much lower prices, generating exceptional returns for shareholders. As we saw in Cable Cowboy, John Malone at TCI (later Liberty Media) was masterful at using financial engineering and tax-efficient structures to build value. He pioneered the use of spin-offs, tracking stocks, and complex deal structures to maximize shareholder returns while minimizing tax impacts. Tom Murphy at Capital Cities demonstrated exceptional discipline in acquiring media assets only when prices were attractive. His most famous move was purchasing ABC in 1985, then selling the combined company to Disney a decade later for a massive profit. Warren Buffett at Berkshire Hathaway has shown remarkable skill in capital allocation across multiple decades, particularly in knowing when to hold cash and when to deploy it aggressively during times of market stress, such as during the 2008 financial crisis when he made highly profitable investments in companies like Goldman Sachs and Bank of America. Jamie Dimon at JPMorgan Chase has also proven to be an astute capital allocator, particularly during crises. He guided JPMorgan through the 2008 financial crisis while acquiring Bear Stearns and Washington Mutual at fire-sale prices, significantly strengthening the bank's competitive position. D. Scott Patterson has shown excellent capital allocation skills at FirstService. He began leading FirstService following the spin-off of Colliers in 2015, and has compounded EBITDA in the high teens via strategic property management acquistions coupled with large platforms like First OnSite and recently Roofing Corp of America. Another great capital allocator is Brad Jacobs. He has a storied career building rollups like United Waste Systems (acquired by Waste Services for $2.5B), United Rentals (now a $56B public company), XPO logistics which he separated into three public companies (XPO, GXO, RXO), and now QXO, his latest endeavor into the building products space. These leaders share common traits with Wahlroos: patience during bull markets, aggression during downturns, and the discipline to ignore market sentiment in favor of fundamental value. They demonstrate that superior capital allocation, while rare, can create enormous shareholder value over time.

    Dig Deeper

  • Handelsbanken: A Budgetless Banking Pioneer

  • ECB has created 'toxic environment' for banking, says Sampo & UPM chairman Bjorn Wahlroos

  • Edward Chancellor part 1: ‘intelligent contrarians’ should follow the capital cycle

  • Charlie Munger: Investing in Semiconductor Industry 2023

  • Amazon founder and CEO Jeff Bezos delivers graduation speech at Princeton University

tags: Amazon, Jeff Bezos, National Semiconductor, Intel, Moore's Law, Texas Instruments, Micron, Analog Devices, Michael Mauboussin, Daniel Kahneman, Peloton, Handelsbanken, Bjorn Wahlroos, Sampo, Henry Singleton, Teledyne, John Malone, D. Scott Patterson, Jamie Dimon, Tom Murphy, Warren Buffett, Brad Jacobs
categories: Non-Fiction
 

June 2021 - Letters to the Nomad Partnership 2001-2013 (Nick Sleep's and Qais Zakaria's Investor Letters)

This month we review a unique source of information - mysterious fund manager Nick Sleep’s investment letters. Sleep had an extremely successful run and identified several very interesting companies and characteristics of those companies which made for great investments. He was early to uncover Amazon, Costco, and others - riding their stocks into the stratosphere over the last 20 years. These letters cover the internet bubble, the 08/09 crisis, and all types of interesting businesses across the world.

The full letters can be found here

The full letters can be found here

Tech Themes

  1. Scale Benefits Shared. Nick Sleep’s favored business model is what he calls Scale Benefits Shared. The idea is straight forward and appears across industries. Geico, Amazon, and Costco all have this business model. Its simple - companies start with low prices and spend only on the most important things. Over time as the company scales (more insured drivers, more online orders, more stores) they pass on the benefits of scale to the customer with even further lower prices. The consumer then buys more with the low-cost provider. This has a devastating effect on competition - it forces companies to exit the industry because the one sharing the scale benefits has to become hyper-efficient to continue to make the business model work. “In the case of Costco scale efficiency gains are passed back to the consumer in order to drive further revenue growth. That way customers at one of the first Costco stores (outside Seattle) benefit from the firm’s expansion (into say Ohio) as they also gain from the decline in supplier prices. This keeps the old stores growing too. The point is that having shared the cost savings, the customer reciprocates, with the result that revenues per foot of retailing space at Costco exceed that at the next highest rival (WalMart’s Sam’s Club) by about fifty percent.” Jeff Bezos was also very focused on this, his 2006 annual letter highlighted as much: “Our judgment is that relentlessly returning efficiency improvements and scale economies to customers in the form of lower prices creates a virtuous cycle that leads over the long-term to a much larger dollar amount of free cash flow, and thereby to a much more valuable Amazon.com. We have made similar judgments around Free Super Saver Shipping and Amazon Prime, both of which are expensive in the short term and – we believe – important and valuable in the long term.” So what companies today are returning scale efficiencies with customers? One recent example is Snowflake - which is a super expensive solution but is at least posturing correctly in favor of this model - the recent earnings call highlighted that they had figured out a better way to store data, resulting in a storage price decrease for customers. Fivetran’s recent cloud data warehouse comparison showed Snowflake was both cheaper and faster than competitors Redshift and Bigquery - a good spot to be in! Another example of this might be Cloudflare - they are lower cost than any other CDN in the market and have millions of free customers. Improvements made to the core security+CDN engine, threat graph, and POP locations result in better performance for all of their free users, which leads to more free users, more threats, vulnerabilities, and location/network demands - a very virtuous cycle!

  2. The Miracle of Compound Growth & Its Obviousness. While appreciated in some circles, compounding is revered by Warren Buffett and Nick Sleep - it’s a miracle worth celebrating every day. Sleep takes this idea one step further, after discussing how the average hold period of stocks has fallen significantly over the past few decades: “The fund management industry has it that owning shares for a long time is futile as the future is unknowable and what is known is discounted. We respectfully disagree. Indeed, the evidence may suggest that investors rarely appropriately value truly great companies.” This is quite a natural phenomenon as well - when Google IPO’d in 2004 for a whopping $23bn, were investors really valuing the company appropriately? Were Visa ($18Bn valuation, largest US IPO in history) and Mastercard ($5.3Bn valuation) being valued appropriately? Even big companies like Apple in 2016 valued at $600Bn were arguably not valued appropriately. Hindsight is obvious, but the durability of compounding in great businesses is truly a myth to behold. That’s why Sleep and Zakaria wound down the partnership in 2014, opting to return LP money and only own Berkshire, Costco, and Amazon for the next decade (so far that’s been a great decision!). While frequently cited as a key investing principle, compounding in technology, experiences, art, and life are rarely discussed, maybe because they are too obvious. Examples of compounding (re-investing interest/dividends and waiting) abound: Moore’s Law, Picasso’s art training, Satya Nadella’s experience running Bing and Azure before becoming CEO, and Beatles playing clubs for years before breaking on the scene. Compounding is a universal law that applies to so much!

  3. Information Overload. Sleep makes a very important but subtle point toward the end of his letters about the importance of reflective thinking:

    BBC Interviewer: “David Attenborough, you visited the North and South Poles, you witnessed all of life in-between from the canopies of the tropical rainforest to giant earthworms in Australia, it must be true, must it not, and it is a quite staggering thought, that you have seen more of the world than anybody else who has ever lived?”

    David Attenborough: “Well…I suppose so…but then on the other hand it is fairly salutary to remember that perhaps the greatest naturalist that ever lived and had more effect on our thinking than anybody, Charles Darwin, only spent four years travelling and the rest of the time thinking.”

    Sleep: “Oh! David Attenborough’s modesty is delightful but notice also, if you will, the model of behaviour he observed in Charles Darwin: study intensely, go away, and really think.”

    There is no doubt that the information age has ushered in a new normal for daily data flow and news. New information is constant and people have the ability to be up to date on everything, all the time. While there are benefits to an always-on world, the pace of information flow can be overwhelming and cause companies and individuals to lose sight of important strategic decisions. Bill Gates famously took a “think week” each year where he would lock himself in a cabin with no internet connection and scan over hundreds of investment proposals from Microsoft employees. A Harvard study showed that reflection can even improve job performance. Sometimes the constant data flow can be a distraction from what might be a very obvious decision given a set of circumstances. Remember to take some time to think!

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Business Themes

  1. Psychological Mistakes. Sleep touches on several different psychological problems and challenges within investing and business, including the role of Social Proof in decision making. Social proof occurs when individuals look to others to determine how to behave in a given situation. A classic example of Social Proof comes from an experiment done by Psychologist, Stanley Milgram, in which he had groups of people stare up at the sky on a crowded street corner in New York City. When five people were standing and looking up (as opposed to a single person), many more people also stopped to look up, driven by the group behavior. This principle shows up all the time in business and is a major proponent in financial bubbles. People see others making successful investments at high valuations and that drives them to do the same. It can also drive product and strategic decisions - companies launching dot-com names in the 90’s to drive their stock price up, companies launching corporate venture arms in rising markets, companies today deciding they need a down-market “product-led growth” engine. As famed investor Stan Druckenmiller notes, its hard to sit idly by while others (who may be less informed) crush certain types of investments: “I bought $6 billion worth of tech stocks, and in six weeks I had lost $3 billion in that one play. You asked me what I learned. I didn’t learn anything. I already knew that I wasn’t supposed to do that. I was just an emotional basketcase and I couldn’t help myself. So maybe I learned not to do it again, but I already knew that.”

  2. Incentives, Psychology, and Ownership Mindset. Incentives are incredibly powerful in business and its surprisingly difficult to get people to do the right thing. Sleep spends a lot of time on incentives and the so-called Principal-Agent Conflict. Often times the Principal (Owner, Boss, Purchaser, etc.) may employ an Agent (Employee, Contractor, Service) to accomplish something. However the goals and priorities of the principal may not align with that agent. As an example, when your car breaks down and you need to go to a local mechanic to fix it, you (the principal) want to find someone to fix the car as well and as cheaply as possible. However, the agent (the mechanic) may be incentivized to create the biggest bill possible to drive business for their garage. Here we see the potential for misaligned incentives. After 5 years of really strong investment results, Sleep and Zakaria noticed a misaligned incentive of their own: “Which brings me to the subject of the existing performance fee. Eagle-eyed investors will not have failed but notice the near 200 basis point difference between gross and net performance this year, reflecting the performance fee earned. We are in this position because performance for all investors is in excess of 6% per annum compounded. But given historic performance, that may be the case for a very long time. Indeed, we are so far ahead of the hurdle that if the Partnership now earned pass-book rates of return, say 5% per annum, we would continue to “earn” 20% performance fees (1% of assets) for thirty years, that is, until the hurdle caught up with actual results. During those thirty years, which would see me through to retirement, we would have added no value over the money market rates you can earn yourself, but we would still have been paid a “performance fee”. We are only in this position because we have done so well, and one could argue that contractually we have earned the right by dint of performance, but just look at the conflicts!” They could have invested in treasury bonds and collected a performance fee for years to come but they knew that was unfair to limited partners. So the duo created a resetting fee structure, that allowed LPs to claw back performance fees if Nomad did not exceed the 6% hurdle rate for a given year. This kept the pair focused on driving continued strong results through the life of the partnership.

  3. Discovery & Pace. Nick Sleep and Qais Zakaria looked for interesting companies in interesting situations. Their pace is simply astounding: “When Zak and I trawled through the detritus of the stock market these last eighteen months (around a thousand annual reports read and three hundred companies interviewed)…” Sleep and Zakaria put up numbers: 55 annual reports per month (~2 per day), 17 companies interviewed per month (meeting every other day)! That is so much reading. Its partially unsurprising that after a while they started to be able to find things in the annual reports that piqued their interest. Not only did they find retrospectively obvious gems like Amazon and Costco, they also looked all around the world for mispricings and interesting opportunities. One of their successful international investments took place in Zimbabwe, where they noticed significant mispricing involving the Harare Stock Exchange, which opened in 1896 but only started allowing foreign investment in 1993. While Nomad certainly made its name on the Scaled efficiencies shared investment model, Zimbabwe offered Sleep and Zakaria to prioritize their second model: “We have little more than a handful of distinct investment models, which overlap to some extent, and Zimcem is a good example of a second model namely, ‘deep discount to replacement cost with latent pricing power.’” Zimcem was the country’s second-largest cement producer, which traded at a massive discount to replacement cost due to terrible business conditions (inflation growing faster than the price of cement). Not only did Sleep find a weird, mispriced asset, he also employed a unique way of acquiring shares to further increase his margin of safety. “The official exchange rate at the time of writing is Z$9,100 to the U$1. The unofficial, street rate is around Z$17,000 to the U$1. In other words, the Central Bank values its own currency at over twice the price set by the public with the effect that money entering the country via the Central Bank buys approximately half as much as at the street rate. Fortunately, there is an alternative to the Central Bank for foreign investors, which is to purchase Old Mutual shares in Johannesburg, re-register the same shares in Harare and then sell the shares in Harare. This we have done.“ By doing this, Nomad was able to purchase shares at a discounted exchange rate (they would also face the exchange rate on sale, so not entirely increasing the margin of safety). The weird and off the beaten path investments and companies can offer rich rewards to those who are patient. This was the approach Warren Buffett employed early on in his career, until he started focusing on “wonderful businesses” at Charlie Munger’s recommendation.

Dig Deeper

  • Overview of Several Scale Economies Shared Businesses

  • Investor Masterclass Learnings from Nick Sleep

  • Warren Buffett & Berkshire’s Compounding

  • Jim Sinegal (Costco Founder / CEO) - Provost Lecture Series Spring 2017

  • Robert Cialdini - Mastering the Seven Principles of Influence and Persuasion

tags: Costco, Warren Buffett, Berkshire Hathaway, Geico, Jim Sinegal, Cloudflare, Snowflake, Visa, Mastercard, Google, Fivetran, Walmart, Apple, Azure, Bing, Satya Nadella, Beatles, Picasso, Moore's Law, David Attenborough, Nick Sleep, Qais Zakaria, Charles Darwin, Bill Gates, Microsoft, Stanley Druckenmiller, Charlie Munger, Zimbabwe, Harare
categories: Non-Fiction
 

May 2020 - Hitchhiker's Guide to the Galaxy by Douglas Adams

We want to recognize the craziness of the world today and the saddening police brutality and systemic racism that continues to occur in the US. This month we opted for a fiction book that may provide a minor break from that current, depressing reality. We want to acknowledge that our reality is messed up, and as a book club we are committed to reading more books about diversity in tech and more books written by a diverse set of authors.

Tech Themes

  1. The Computer knows the answer. There is an overwhelming feeling in society today, that the computer should be able to tell us the answer. Predictive models are everywhere, from personalized AI workflows to sports gambling. Society has become accustomed to the idea that computers will solve problems for us. Interestingly, the novel portrays technology in the opposite light. Marvin, the robot on Zaphod Beeblebrox’s ship is so knowledgeable that even the most complex task seems meaninglessly easy. As a result, Marvin is constantly depressed. Deep Thought, the most powerful computer in history, takes seven million years to come up with an answer to the question of what life is all about. The simplistic forty-two answer, prompts the crowd to ask what the question was to which the answer is forty-two. The computer suggests that earth will provide that question. These examples somewhat reverse the expectations of technology to the reader. We normally think of technology as providing the answer, simplifying our lives and dehumanizing us. At the end of the story it is not Marvin’s heroism that saves the crew from being killed by the Blagulon Kappa cops who are after the Heart of Gold, it is his depression. When Marvin seizes control of the cops computer and explains his life-view, they commit suicide. In these instances, the role of technology is reversed - it is emotion and human nature that can help save the world and provide the answers to the universe.

  2. Not so obvious, Space Travel and Towels. “A towel, it says, is about the most massively useful thing an interstellar hitchhiker can have.” Something so simple as a towel - which seems relatively unimportant in everyday life - is an absolute necessity for space travel and hitchhiking through the galaxy. Frequently throughout technological history, the simple and unimportant things are overlooked in favor of tackling more complex problems and solutions. The largest data breach in history occurred when Equifax overlooked an expired certificate. During early development of the ENIAC, one of the first computing machines, software was looked at as unimportant and was relegated to early female programmers. Little did these sexist hardware programmers realize that software would become the most important aspect of computing. When the first iPhone released, Microsoft CEO Steve Ballmer laughed at the the device, saying it was too expensive and unable to cater to business customers because it didn’t have a keyboard. The incredibly sad, failed launch of space shuttle Challenger was due to cold temperatures causing rubber joint rings to become too stiff for appropriate sealing. Sometimes the value of a technology or a towel is not inherently obvious.

  3. The Guide, the Whole Earth Catalog and the Internet. “The reason why it was published in the form of a micro sub meson electronic component is that if it were printed in normal book form, an interstellar hitchhiker would require several inconveniently large buildings to carry it around in.” The Hitchhiker’s Guide to The Galaxy is a massive electronic guide to help hitchhikers move throughout space. This interestingly mirrors the current state of the internet, which didn’t exist when Douglas Adams wrote Hitchhiker’s Guide to the Galaxy in the early 70s. Prior to the internet, this type of alternative information could be found in the Whole Earth Catalog, a famous magazine that Steve Jobs once called “Google in paperback form, thirty-five years before Google came along.” The Whole Earth Catalog was created by Stewart Brand, a famous writer and technologist, who actually participated with Douglas Englebart in the Mother of All Demos, which featured the introduction of the mouse and video conferencing. Brand wanted a way to publish material that wouldn’t be found in traditional textbooks, including product reviews of the latest technology. When the internet was starting to launch, Brand created The WELL (Whole Earth ‘Lectronic Link) to continue to provide interesting alternative articles and essays. The WELL is credited with being one of the first internet forums, which was originally accessed via dial-up bulletin board system. The internet today very much mirrors the Hitchhiker’s guide to the galaxy: its content is enormous, it isn’t necessarily factual (the Guide is not completely factual either, but based on experience), and its content spans all possible information needed to survive. On top of that, the packaging is described as suspiciously similar to modern smartphones: “He also had a device which looked rather like a largish electronic calculator. This had about a hundred tiny flat press buttons and a screen about four inches square on which any one of a million ‘pages’ could be summoned at a moment's notice.” The internet and mobile computing have come a long way in 50 years; it will be great to watch what happens in the next 50!

Business Themes

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  1. The Business of Space: SpaceX / Virgin Galactic. Elon Musk and Chamath Palihapitiya are outspoken, visionary billionaires. Elon has an incredible track record of under-delivering but still exceeding most people’s wildest expectations. Chamath was an early employee at Facebook and is now a part owner of the Golden State Warriors. He is CEO of a VC-firm turned “technological holding company” and the creator of three public SPACs, one of which now represents Virgin Galactic. A SPAC or Specialty Purpose Acquisition Company is a blank-check company with no commercial operations. A SPAC is normally led by experts in a specific space like software or real estate and these executives raise money to acquire a company. The money raised in an IPO sits in an interest bearing account until the blank-check company has found a company to acquire. If no deal is completed after two years, the SPAC will give money back to their investors. Chamath purchased 49% of Richard Branson's Virgin Galactic space company in 2019. Space is impossibly big and its natural to think that someone who can develop the technology to unlock that vastness to humans would also unlock a fortune. As the Guide puts it: “‘Space,’ it says, ‘is big. Really big. You just won’t believe how vastly, hugely, mindbogglingly big it is. I mean, you may think it’s a long way down the road to the chemist’s, but that’s just peanuts to space.’” But the business of space is in its earliest days. SpaceX relies almost completely on government contracted work which means the company needs an incredible amount of funding to survive because of the capital investment and the uncertain, non-recurring nature of these space contracts. Interestingly, the development of early commercial air travel, in the 1920’s, also had a similar funding issue, and it was up to the Guggenheim family, rich from mining profits, to set up a fund to exclusively contribute to the development of Western Air Express, the world’s first commercial airliner. Virgin Galactic is taking a piece out of Tesla’s playbook by selling future space rides ahead of any commercial launch. Public markets investors including reddit’s wallstreetbets community is piling into Virgin Galactic at the literal moonshot risk of it becoming the space company (Income statement above). Space has always been a billionaire passion, the question remains - can it be a business?

  2. Moore’s Law and Murphy’s Law. Murphy’s law states: “Anything that can go wrong, will go wrong.” Hitchhiker’s Guide to the Galaxy explores this notion repeatedly as Arthur continually finds himself in unbelievably bad circumstances; his house is demolished, his planet is destroyed, he is captured by Vogons, and sure-death missles approach the ship as the crew descends on Magarathea. Arthur continues to survive these dangers with the help of the improbability drive, which the book states is a “a wonderful new method of crossing interstellar distances in a few seconds; without all that tedious mucking about in hyperspace. As the Improbability Drive reaches infinite improbability, it passes through every conceivable point in every conceivable universe almost simultaneously. In other words, you're never sure where you'll end up or even what species you'll be when you get there. It's therefore important to dress accordingly.” In comparison to Murphy’s law, Moore’s Law is the idea that computing power doubles every 18 months. A 2006 Economist article explained Moore’s Law as the opposite of Murphy’s Law: “But his law seems safe for at least another decade—or two to three chip generations—which is as far as he has ever dared to look into the future. As things are made at scales approaching individual atoms, he says, there will surely be limitations. Then again, the law has often met obstacles that appeared insurmountable, before soon surmounting them. In that sense, Mr Moore says, he now sees his law as more beautiful than he had realised. “Moore's Law is a violation of Murphy's Law. Everything gets better and better.” While Moore’s Law has surely reached its current limitations, the question remains where do chips go from here? Some have posited that chips will push towards function specific hardware or purpose built for specific computing tasks like NVIDIA’s graphics cards. The space is large and complex - with companies like Apple licensing ARM technology to build their famous A13 chip while other companies have focused on specific parts of the value chain like TSMC. A big question that still remains is how cloud companies will scale hardware to meet continuing demand from customers. Arthur Dent, like Elon Musk, continues to benefit from infinite improbability - maybe quantum computing is the only way to know if Elon will succeed and what happens next in chip design.

  3. Mentorship. Slartibarfast is a wise, old, planet creator who is plopped into the story to provide Arthur with answers to so many incredible questions. Slartibartfast explains the creation of earth and the interaction with Deep Thought. The interactions between Arthur and Slartibartfast are somewhat akin to traditional business mentorship - when you have none of the answers or you have preconceived ideas of how everything came to be, a mentor can quickly dispel your ideas and provide deep answers. Mentorship has been popular in Silicon Valley, with Bill Campbell mentoring Steve Jobs and several others. Bill was also instrumental in several decisions Ben Horowitz contemplated as he took Opsware through its spinout and sale of its managed services division. Mentors help change perspective and provide guidance.

Dig Deeper

  • Discussion of how the Whole Earth Catalog pushed 1960s CounterCulture

  • List of the Latest OpenAI models for predictive image generation and interaction prediction

  • Chamath says “Let Them Get Wiped Out!” when talking about hedge funds during the coronarvirus downturn

  • The resurgence of a business model formerly considered fraud - SPACs

  • Apple releases A13 bionic chip and it works incredibly fast

tags: Equifax, Microsoft, Steve Ballmer, Elon Musk, Steve Jobs, WELL, Stewart Brand, Chamath Palihapitiya, Facebook, Virgin Galactic, SPAC, Moore's Law, TSMC, ARM, NVIDIA, Ben Horowitz, Bill Campbell, batch2
categories: Fiction
 

January 2020 - The Innovators by Walter Isaacson

Isaacson presents a comprehensive history of modern day technology, from Ada Lovelace to Larry Page. He weaves in intricate detail around the development of the computer, which provides the landscape on which all the major players of technological history wander.

Tech Themes

  1. Computing Before the Computer. In the Summer of 1843, Ada Lovelace, daughter of the poet Lord Byron, wrote the first computer program, detailing a way of repeatedly computing Bernoulli numbers. Lovelace had been working with Charles Babbage, an English mathematician who had conceived of an Analytical Engine, which could be used as a general purpose arithmetic logic unit. Originally, Babbage thought his machine would only be used for computing complex mathematical problems, but Ada had a bigger vision. Ada was well educated and artistic like her father. She knew that the general purpose focus of the Analytical Engine could be an incredible new technology, even hypothesizing, “Supposing, for instance, that the fundamental relations, of pitched sounds in the science of harmony and musical composition were susceptible to such expression and adaptations, the engine might compose elaborate and scientific pieces of music of any degree of complexity.” 176 years later, in 2019, OpenAI released a deep neural network that produces 4 minute musical compositions, with ten different instruments.

    2. The Government, Education and Technology. Babbage had suggested using punch cards for computers, but Herman Hollerith, an employee of the U.S. Census Bureau, was the first to successfully implement them. Hollerith was angered that the decennial census took eight years to successfully complete. With his new punch cards, designed to analyze combinations of traits, it took only eight. In 1924, after a series of mergers, the company Hollerith founded became IBM. This was the first involvement of the US government with computers. Next came educational institutions, namely MIT, where by 1931 Vanneaver Bush had built a Differential Analyzer (pictured below), the world’s first analog electric computing machine. This machine would be copied by the U.S. Army, University of Pennsylvania, Manchester University and Cambridge University and iterated on until the creation of the Electronic Numerical Integrator and Computer (ENIAC), which firmly established a digital future for computing machines. With World War as a motivator, the invention of the computer was driven forward by academic institutions and the government.

Business Themes

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  1. Massive Technological Change is Slow. Large technological change almost always feels sudden, but it rarely ever is. Often, new technological developments are relegated to small communities, like Homebrew computing club, where Steve Wozniak handed out mock-ups for the Apple Computer, which was the first to map a keyboard to a screen for input. The development of the transistor (1947) preceded the creation of the microchip (1958) by eleven years. The general purpose chip, a.k.a. the microprocessor popped up thirteen years after that (1971), when Intel introduced the 4004 into the business world. This phenomenon was also true with the internet. Packet switching was first discovered in the early 1960s by Paul Baran, while he was at the RAND Corporation. The Transmission Control Protocol and Internet Protocol were created fifteen years after that (1974) by Vint Cerf and Bob Kahn. The HyperText Transfer Protocol (HTTP) and the HyperText Markup Language (HTML) were created sixteen years after that in 1990 by Tim Berners-Lee. The internet wasn’t in widespread use until after 2000. Introductions of new technologies often seem sudden, but they frequently call on technologies of the past and often involve a corresponding change that address the prior limiting factor of a previous technology. What does that mean for cloud computing, containers, and blockchain? We are probably earlier in the innovation cycle than we can imagine today. Business does not always lag the innovation cycle, but is normally the ending point in a series of innovations.

  2. Teams are Everything. Revolution and change happens through the iteration of ideas through collaborative processes. History provides a lot of interesting lessons when it comes to technology transformation. Teams with diverse backgrounds, complementary styles and a mix of visionary and operating capabilities executed the best. As Isaacson notes: “Bell Labs was a classic example. In its long corridors in suburban New Jersey, there were theoretical physicists, experimentalists, material scientists, engineers, a few businessmen, and even some telephone pole climbers with grease under their fingernails.” Bell Labs created the first transistor, a semiconductor that would be the foundation of Intel’s chips, where Bob Noyce and Gordon Moore (yes – Moore’s Law) would provide the vision, and Andy Grove would provide the focus.

Dig Deeper

  • Alan Turing and the Turing Machine

  • The Deal that Ruined IBM and Catapulted Microsoft

  • Grace Hopper and the First Compiler

  • ARPANET and the Birth of the Internet

tags: IBM, Microsoft, Moore's Law, Apple, Alan Turing, OpenAI, Cloud Computing, Bell Labs, Intel, MIT, Ada Lovelace, batch2
categories: Non-Fiction
 

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

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  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

tags: Facebook, IBM, Zoom, Artificial Intelligence, AI, AGI, Watson, OpenAI, Y Combinator, Microsoft, Moore's Law, Deep Fakes, Deep Learning, Elon Musk, Skype, WebEx, Cisco, Apple, Activision, Conglomerate, Softbank, Alibaba, Tencent, Vision Fund, China, Asia, batch2
categories: Fiction
 

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