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December 2020 - Do Androids Dream of Electric Sheep? (Blade Runner) by Phillip K. Dick

This month we read the classic sci-fi novel, Do Androids Dream of Electric Sheep? The book follows Rick Deckard, a bounty hunter searching out android robots who are pretending to be human beings. Along the journey, the reader is asked to consider: what does it mean to be alive? Philip K. Dick was a crazy sci-fi writer, producing many books and stories that became famous like The Man in the High Castle, Minority Report, and Total Recall. Although his writing career was prolific, Dick was a troubled individual. He was a heavy drug user, he married five times, he experienced drug-induced “paranormal activities” and he was physically abusive to at least two of his wives. While

Tech Themes

The common, modern depiction of a Turing Test

The common, modern depiction of a Turing Test

  1. Are you an android? In 1950, British computer scientist Alan Turing conceived of the Turing Test, a hypothetical test to determine whether a machine can display intelligent behavior. Turing asked the question, “Can machines think?” and attempted to define a test whereby a human might be tricked into believing a machine was human. The test design is fairly complex but involves a human asking written questions to a machine in another room. If the machine can convince the interrogator that it’s human, then machines can “think.” This Turing test is mirrored in the Voigt-Kampff test used throughout the book. It’s unclear if the test works, and Rick Deckard almost misdiagnoses Rachel in the book's early parts. At the end of the book, the test is turned on its head, with Rick impersonating John Isidore (another human), trying to convince machines (in another room) to let him in. This role-reversal and the questioning of who is an android happens throughout the novel - at times, Rick, Phil Resh, and Harry Bryant might all be androids. These questions are the centerpiece of sci-fi lore. They are also explored in a similar style in the famous movie Ghost in The Shell, where people have now have some organs and limbs replaced by electric parts. When a cyber-attacker named the Puppet Master takes over the machine network of technological parts, it’s unclear who is human, who is an android, and who is possessed by the Puppet Master. In the video game world, this idea has also recently been explored in Detroit: Become Human. In the game, which is set up in choose-your-own-adventure style, players can play as humans or androids and choose whether they stay in character or break out of their controlled, android state. The idea of an interrogator or bounty hunter snooping out rogue machines has been explored across books, film, and video games. As technology has become more prevalent in our lives, the cultural mediums may have changed, but the classic philosophical question - what does it mean to be alive? - remains.

  2. Predicting the future. The Blade Runner movie is famously set in Los Angeles, 2019, while the book is set in 1992 in San Francisco. The book itself was written in 1968, and the movie Blade Runner debuted 14 years later in 1982. In 2019, Blade Runner experienced a comic resurgence as its dark, bleak futuristic society of flying cars, fully intelligent artificial beings, and international space travel never happened. Today, predictions of computing and artificial intelligence abound. In his original Imitation Game paper, Alan Turing made one of the most famous AI predictions: “I believe that in about fifty years’ time it will be possible to programme computers, with a storage capacity of about 10^9, to make them play the imitation game so well that an average interrogator will not have more than 70 percent, chance of making the right identification after five minutes of questioning.” It’s tough to know if this prediction came true (other than the 10^9 part because that is only 1 GB), with some places claiming to have built algorithms that beat the Turing Test. Interestingly, one common theme emerges about these computing predictions - both experts and non-experts typically predict about 15-25 years out. In the Innovators, Walter Issacson posited that this was enough time to allow people to engage in imaginative thinking. Roy Amara, co-founder of the Institute for the Future, probably put it best: “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” How long run is the long run, though? As John Maynard Keynes proclaimed: “In the long run we are all dead. Economists set themselves too easy, too useless a task if, in tempestuous seasons, they can only tell us that when the storm is long past the ocean is flat again.” It is seriously hard to estimate the combination of changing technologies and infrastructures, which unlock completely new and cost-effective ways of building things. Will we have self-driving cars in 20 years? Will we have Artificial General Intelligence? Will we have quantum computing? I have no idea.

  3. Technology and nature. One theme repeatedly explored throughout the novel is this balance or tension between technology and nature. World War Terminus has caused a layer of radioactive dust to fall over the world, killing animal life and changing the environment. Mechanical animals are the norm, and Rick dreams about procuring a real horse, ostrich, or goat one day. He regularly checks his Sidney’s Animal & Fowl Catalogue like a stockbroker checking the latest price change. A real animal is significantly more expensive than a mechanical version, despite it being nearly impossible to figure out whether an animal is real or fake. This mirror’s the book's whole premise - a real human is more important and valuable than an Android despite increasingly small differences between Androids and humans. Rick realizes this at the end of the book: “The spider Mercer gave the chickenhead, Isidore; it probably was artificial, too. But it doesn't matter. The electric things have their lives, too. Paltry as those lives are." Technology and nature have a tradeoff in today’s world as well. Cloud computing is certainly energy-intensive, but according to the companies that run those clouds (like Google Cloud or Microsoft Azure), it is significantly less intensive than having companies run their own data centers. Beyond the environmental impact, the behavior of nature is something to consider when operating a data center. A few years ago, Facebook data centers went down when a Snake chewed through a switchboard and took down all services. In 2014, a shark bit through an underwater Google fiber cable, and in 2012 a squirrel took down a Yahoo data center. Animals, technology, and nature are constantly interacting, sometimes in unexpected ways.

Business Themes

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  1. Status seeking and the growth of e-commerce. In the battle to achieve status, real animals are a highly sought after status symbol. Early on in the book, Rick engages in a jealous conversation over his neighbor’s real horse: “‘Ever thought of selling your horse?’ Rick asked. He wished to god he had a horse, in fact any animal.” After revealing that his sheep was electric, Rick’s neighbor kindly remarks that he won’t tell the other people in the apartment complex, suggesting that if people knew Rick had an electric sheep (rather than a real one), they would look down on him. While this interaction seems weird, it parallels so many interactions people have today. Vance Packard offered a description of “status seekers” in 1959: “People who are continually straining to surround themselves with visible evidence of the superior rank they are claiming.” As general consumption and wealth rose after World-War II in the US, luxury goods became more attainable for more classes. Globalization of supply chains also increased this trend. When commerce moved online, new shopping styles and behaviors emerged. E-commerce purchases can frequently replace feelings and there is even a psychological disorder caused by excessive purchasing: Buying-shopping disorder (BSD) is characterized by extreme preoccupations with and craving for buying/shopping and by irresistible and identity-seeking urges to possess consumer goods. Patients with BSD buy more consumer goods than they can afford, and those are neither needed nor frequently used. The excessive purchasing is primarily used to regulate emotions, e.g. to get pleasure, relief from negative feelings, or coping with self-discrepancy.” Dick may be signaling that humans seek status and importance compared to their reference groups, regardless of setting or what indicates that status to others, whether it be an expensive handbag or a goat.

  2. Buy goat now, pay-later. 2020 saw the emergence of buy-now, pay-later (BNPL) vendors like Affirm, Klarna, and Afterpay. These companies typically offer zero-interest loans to consumers and get paid a 5% merchant fee for increasing purchases at e-commerce stores. The stores (like Peloton for example) increase sales and the consumers benefit from not having to pay a significant upfront payment. The other way these companies make money is by charging interest payments on specific types of purchases (likely where the merchant doesn’t want to give away a fee). These interest rates can be really, really high - averaging around 10-30% depending on the purchase. This is not a new concept and the idea of payday loans at predatorily high-interest rates has been around for over 30 years. Luckily, the purchases that these BNPL providers are financing tend to not be really high-value products, but it’s still concerning that some people are buying things without understanding the true value they will have to pay in interest. When Rick purchases a real goat, after killing three androids, he finances it, paying $3,000 upfront and entering into a three-year payment contract. Rick’s wife Iran is outraged at the cost of the goat: "‘What are the monthly payments on the goat?’ She held out her hand; reflexively he got out the contract which he had signed, passed it to her. ‘That much,’ she said in a thin voice. ‘The interest; good god — the interest alone. And you did this because you were depressed. Not as a surprise for me, as you originally said.” With BNPL providers now securitizing these consumer loans and selling them off to banks, I wonder if we will see any new regulation come to bear for the benefit of consumers. If people are not careful, they could be locked into long contracts with significant interest over time.

  3. Two case studies in electric animals. Electric animals have actually been invented and while they may not be the equivalent of Goddard from Jimmy Neutron yet, they are pretty funny and interesting case studies. Sony released the AIBO dog in 1999 after many years of research. The original robot dog cost $2,100 (~$3,500 in today’s dollars) and sold about 65,000 units. The programmable software allowed the dogs to be used in a variety of situations including an AI soccer world cup. The initial popularity of the dogs waned, and price wars with new rivals caused sales to decline. In 2006, the AIBO dog was discontinued. In 2018, it made a resurgence and is now a barking flexible model that you can pet, play games with, and feed. Another tale of odd mechanic animals is Boston Dynamics. The company that spun out of MIT in 1992 produced massive quadruped animals including one called BigDog, that was capable of balancing, walking up-hill, and carrying significant amounts of equipment. The Company had trouble selling products though and was acquired by Google in 2013 for an undisclosed sum. This came at a time when Google was pushing heavily into robotics with Google Glass and what would become Waymo - they literally titled this Project Replicant (the name used for Android in the Blade Runner film). After some more years of underperformance, Google sold Boston Dynamics to Softbank in 2017. After years of development, the company finally released a product to consumers for a whopping $75,000. The dog is still pretty creepy and comes without a real face, unlike the Aibo. In 2020, it was announced that Hyundai had acquired an 80% stake in the business at a $1.1B valuation. We are still years away from having electric animals that mimic real-life animals and that may be a good thing.

Dig Deeper

  • Blade Runner: How Its Problems Made It a Better Movie

  • Does Buy Now, Pay Later Threaten Credit Card Issuers?

  • Predicting a Future Where the Future Is Routinely Predicted

  • An Overview of the latest Affirm Consumer Loan Securitization

  • Snakes in a Facebook Data Center

tags: Alan Turing, Ghost in the Shell, Blade Runner, Philip K. Dick, Sony, AI, AGI, Google, Microsoft, Yahoo, BNPL, Affirm, Klarna, Afterpay, e-Commerce, Securitization, Jimmy Neutron, AIBO, Boston Dynamics, Softbank, Hyundai, Facebook, Waymo, Rick Deckard, Detroit: Become Human, Los Angeles, San Francisco
categories: Fiction
 

August 2020 - Venture Deals by Brad Feld and Jason Mendelson

This month we checked out an excellent book for founders, investors, and those interested in private company financings. The book hits on a lot of the key business and legal terms that aren’t discussed in typical startup books, making it useful no matter what stage of the entrepreneurial journey you are on.

Tech Themes

  1. The Rise of Founder Friendly VC. Writing on his blog, Feld Thoughts, which was the original genesis for Venture Deals, Brad Feld mentioned that: “From 2010 forward, the entire VC market shifted into a mode that many describe as ‘founder friendly.’ Investor reputation mattered at both the angel and VC level.” In the 80’s and 90’s, because there was so little competition among venture capital firms, it was common for firms to dictate terms to company founders. The VC firms were the ones with the cash, and the founders didn’t have many options to choose from. If you wanted to build a big, profitable, public company, the only way to get there was by taking venture capital money. This trend started to unwind during the internet bubble, when founders started to maintain more and more of their businesses before the IPO. In fact, as this Harvard Business Review article points out, it was actually common to fire the founder/CEO prior to a public offering in favor of more seasoned leaders. This trend was bucked by Netscape, which eschewed traditional wisdom, going public less than a year from founding, with an unprofitable business. The Netscape IPO was clearly a royal coming-together of technology history. Tracing it all the way back - George Winthrop Fairchild started IBM in 1911; in the late 50’s, Arthur Rock convinced Fairchild’s son, Sherman to fund the traitorous eight (eight employees who left competitor Shockley Semiconductor) to start Fairchild Semiconductor; Eugene Kleiner (one of the traitorous eight) starts Kleiner Perkins, a venture capital firm that eventually invested in Netscape. Kleiner Perkins would also invest in Google (frequently regarded as one of the best and riskiest startup investments ever). Google was the first internet company to go public with a dual-class share structure where the founders would own a disproportionate amount of the voting rights of the company. Marc Andreessen, the founder of Netscape, loved this idea and eventually launched his own venture capital firm called Andreessen Horowitz, which ushered in a new generation of founder-friendly investing. At one point Andreessen was even quoted saying: “It is unsafe to go public today without a dual-class share structure.” Some notable companies with dual class shares include several Andreessen companies such as Facebook, Zynga, Box, and Lyft. Recently some have questioned whether founder friendly terms have pushed too far with some major flameouts from companies with the structure including Theranos, WeWork, and Uber.

  2. How to Raise Money. Feld has several recommendations for fundraising that are important including having a target round size, demo, financial projections, and VC syndicate. Feld contends that CEOs who offer a range of varying round sizes to VC’s don’t really understand their business goals and use of proceeds. By having a concrete round size it shows that the CEO understands roughly how much money it will take to get to the next milestone or said another way, it shows the CEO understands the runway (in months) needed to build that new product or feature. It shows command of the financing and vision of the business. Feld encourages founders to provide a demo, because: “while never required, many investors respond to things we can play with, so even if you are an early stage company, a prototype or demo is desirable.” Beyond the explicit point here, the demo shows confidence in the product and at least some ability to sell, which is obviously a key aspect in eventually scaling the business. Another aspect of scaling the business is the financial model, but as Feld states, “the only thing that can be known about a pre-revenue company’s financial projections is that they are wrong.” While the numbers are meaningless for really early stage companies, for those that have a few customers it can be helpful to get a sense of long-term gross margins and aspects of the company you hope to invest in and / or change over time. Lastly, Feld gives advice for building a VC syndicate, or group of VC investors. Frequently lead investors will commit a certain dollar amount of the round, and it will be up to the founder/CEO to go find a way to build out the round. This can be incredibly challenging as detailed by Moz founder, Rand Fishkin, who thought he had a deal in hand only to see it be taken away. There are multiple bids in the VC fundraising process, one called an indication of interest, which is non-binding and normally provides a range on valuation, one called a letter of intent, which is slightly more detailed and may include legal terms of the deal such as board representation, liquidation preference, and governance terms, and then final legal documentation. A lot of time, the early bids can be withdrawn based off of poor market feedback or when a company misses its financial projections (like Moz did in its process). Understanding the process and the materials needed to complete the deal is helpful at setting expectations for founders.

  3. Warrants, SPACs, and IPOs. With SPACMania in full-swing, we wanted to dive into SPACs and see how they work. We’ve discussed SPACs before, with regards to Chamath’s Social Capital merger with Virgin Galactic. But how do traditional SPAC financings work and why is there a rush of famous people, such as LinkedIn founder Reid Hoffman, to raise them? A SPAC or Specialty Purpose Acquisition Company is a blank-check company which goes public with the goal of acquiring a business, thereby taking it public. SPACs can be focused on industry or size of company and they are most frequently led by operational leaders and / or private equity firms. The reason SPACs have been gaining in popularity is that public markets investors are seeking more risk and a few high profile SPAC deals, namely DraftKings and Nikola, have traded better than expected. Most companies that are going public today are older, more mature businesses, and the public markets have been generally favorable to somewhat suspect ventures (Nikola is an electric truck company that has never produced a single truck, but is worth $14B on hype alone). VC firms and companies see the ability to get outsized returns on their investments because so many people are clamoring to find returns above the basically 0% offered by treasury bonds. The S&P 500 P/E ratio is now at around 26x compared to a historical average around 16x, meaning the market seems to be overvalued compared to prior times. SPACs typically come with an odd structure. A unit in a SPAC normally consists of one common share of stock and one warrant, which is the ability to purchase shares for $0.01 after a SPAC merges with its target company. The founders of the SPAC also receive founder shares, normally 20% of the business. Once the target is found, SPACs will often coordinate a PIPE (Private Investment in Public Equity), where a large private investor will invest mainly primary (cash to the balance sheet) capital into the business. This has emerged as a hip, new alternative to traditional IPOs, keeping with the theme of innovation in public offerings like direct listings, however, its unclear that this really benefits the company going public. Often the merged companies are the subject of substantial dilution by the SPAC sponsors and PIPE investors, lowering the overall equity piece management maintains. However, given the somewhat high valuations companies are receiving in the public markets (Zoom at 80x+ LTM Revenue, Shopify at 59x LTM Revenue), it may be worth the dilution.

Business Themes

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  1. How VC’s Make Money. In VC, the typical fund structure includes a general partnership (GP) and limited partners (LPs). The GP is the investors at the VC firm and the limited partners are the institutional investors that provide the money for the VC firm to invest. A typical structure involves the GP investing 1% of their own money (99% comes from LPs) and then getting paid an annual 2% management fee as well as 20% carried interest, or the profit made from investments. Using the example from the book: “Start with the $100 million fund. Assume that it's a successful fund and returns 3× the capital, or $300 million. In this case, the first $100 million goes back to the LPs, and the remaining profit, or $200 million, is split 80 percent to the LPs and 20 percent to the GPs. The VC firm gets $40 million in carried interest and the LPs get the remaining $160 million. And yes, in this case everyone is very happy.” Understanding how investors make money can help the entrepreneur better understand why VC’s pressure companies. As Feld points out, sometimes VC’s are trying to raise a new fund or have invested the majority of the fund already and thus do not care as much about some investments.

  2. Growth at all costs. There has been a concerted focus in VC on the get big quick motto. Nobody better exemplifies this than Masayoshi Son and the $100B VC his firm Softbank raised a few years ago. With notable big bets on current losers like WeWork and Oyo, which are struggling during this pandemic, its unclear whether this motto remains true. Eric Paley, a Managing Partner at Founder Collective, expertly quantifies the potential downsides of a risk-it-all strategy: “Investors today have overstuffed venture funds, and lots of capital is sloshing around the startup ecosystem. As a result, young startups with strong teams, compelling products and limited traction can find themselves with tens of millions of dollars, but without much real validation of their businesses. We see venture investors eagerly investing $20 million into a promising company, valuing it at $100 million, even if the startup only has a few million in net revenue. Now the investors and the founders have to make a decision — what should determine the speed at which this hypothetical company, let’s call it “Fuego,” invests its treasure chest of money in the amazing opportunity that motivated the investors? The investors’ goal over the next roughly 24 months is for the company to become worth at least three times the post-money valuation — so $300 million would be the new target pre-money valuation for Fuego’s next financing. Imagine being a company with only a few million in sales, with a success hurdle for your next round of $300 million pre-money. Whether the startup’s model is working or not, the mantra becomes ‘go big or go home.’” This issue is key when negotiating term sheets with investors and understanding board dynamics. As Feld calls out: “The voting control issues in the early stage deals are only amplified as you wrestle with how to keep control of your board when each lead investor per round wants a board seat. Either you can increase your board size to seven, nine, or more people (which usually effectively kills a well-functioning board), or more likely the board will be dominated by investors.” As an entrepreneur, you need to be cognizant of the pressure VC firms will put on founders to grow at high rates, and this pressure is frequently applied by a board. Often late stage startups have 10 people+ on their board. UiPath, a private venture-backed startup that has raised over $1B and is valued at $10B, has 12 people on its board. With all of the different firms having their own goals, boards can become ineffective. Whenever startups are considering fundraising, it’s important to realize the person you are raising from will be an ongoing member of the company and voice on the board and will most likely push for growth.

  3. Liquidation Preference. One of the least talked about terms in venture capital among startup circles is liquidation preference. Feld describes liquidation preference as: “a certain multiple of the original investment per share is returned to the investor before the common stock receives any consideration.” Startup culture has tended to view fundraises as stamps of approval and success, but thats not always the case. As the book discusses, preference can lead to very negative outcomes for founders and employes. For example, let’s say a company at $10M in revenue raises $100 million with a 1x liquidation preference at a $400 million pre-money valuation ($500M post money). The company is pressured by its VCs to grow quickly but it has issues with product market fit and go to market; five years go by and the company is at $15M in revenue. At this point the VCs are not interested in funding any more, and the board decides to try to sell the company. A buyer offers $80 million and the board accepts it. At this point, all $80M has to go back to the original investors who had the 1x liquidation preference. All of the common stockholders and the founders, get nothing. Its not the desired outcome by any means, but its important to know. Some companies have not heeded this advice and continued to raise at massive valuations including Notion which has raised $10M at a $800 million valuation, despite being rumored to be around $15M in revenue. The company raised at a $1.6B valuation (an obvious 2x) after being rumored to be at $30M in revenue. While not taking dilution is nice as a founder, it also sets up a massive hurdle for the company and seriously cramps returns. A 3x return (which is low for VC investors) means selling the company for $4.8B, which is no small feat.

Dig Deeper

  • Feld Thoughts: Brad Feld’s Blog

  • The Ultimate Guide to Liquidation Preferences

  • Startup Boards: A deep dive by Mark Suster, VC at Upfront Ventures

  • The meeting that showed me the truth about VCs on TechCrunch

  • SPOTAK: The Six Traits Marc Lore Looks for When Hiring

tags: Uber, WeWork, Theranos, Fairchild Semiconductor, Netscape, Marc Andreessen, SPAC, Chamath Palihapitiya, Zynga, Box, Facebook, Brad Feld, Nikola, Draftkings, Zoom, Shopify', Warrants, Liquidation Preference, VC, Founder Collective, Oyo, UiPath, Notion, Softbank, 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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