Dwarkesh did a fantastic job with this interview. He read the scientific papers on genomic prediction and his questions are very insightful. Consequently we covered the important material that people are most confused about.
Don't let the sensationalistic image above deter you -- I highly recommend this podcast!
Sebastian Mallaby is a writer and journalist whose work covers financial markets, international relations, innovation, and technology. He is the author of "The Power Law: Venture Capital and the Making of the New Future."
Steve and Sebastian discuss venture capital, tech startups, business model and technology innovation, global adoption of the Silicon Valley model, and the future of innovation.
Note: the part of the conversation I found most interesting -- venture and capital markets aspects of drug discovery, complexity and scale of biotech ecosystems, role of IP and US healthcare spending to incentivize discovery -- begins at ~35m.
Steve and Corey speak with Dr. Michael Kauffman, co-founder and CEO of Karyopharm Therapeutics, about cancer and biotech innovation. Michael explains how he and Dr. Sharon Schacham tested her idea regarding cellular nuclear-transport using simulation software on a home laptop, and went on to beat 1000:1 odds to create a billion dollar company. They discuss the relationship between high proprietary drug costs and economic incentives for drug discovery. They also discuss the unique US biotech ecosystem, and why innovation is easier in small (vs. large) companies. Michael explains how Karyopharm is targeting its drug at COVID-induced inflammation to treat people with severe forms of the disease.
In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.
Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.
Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.
Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.
Steve and Corey talk to Kieren James-Lubin and Victor Wong of the blockchain technology startup, BlockApps. They begin with a discussion of the COVID-19 epidemic (~25m): lockdown, predictions of ICU overload, and helicopter money. Will personal contact tracking become the new normal? Transitioning to blockchain, a technology many view as viable even in times of widespread societal disruption, they give a basic explanation of the underlying cryptographic and consensus algorithms. Kieren and Victor explain how BlockApps was founded, its business model, and history as a startup. They conclude with a comparison of startup ecosystems in China, Silicon Valley, and NYC.
Recorded on March 18, 2020. Now (March 26) I feel we can make much stronger predictions about CV-19 in the US. We will definitely see overloaded health systems (ICUs) across a broad part of the country. It is already starting to happen in NYC. I will be surprised if the US can avoid tens of thousands of fatalities by early April (say, 14 days from today).
1:08 - Lockdown and ICU Overload COVID-19 5:22 - Singapore and Taiwan Response 17:28 - Government Intervention and Helicopter Money 22:13 - End of the Lockdown?
25:58 - How BlockApps got started 28:56 - Private & Public Key Cryptography and Digital Signatures 34:40 - Blockchain 46:05 - Enterprise Blockchains 1:03:37 - Elevator Pitch 1:24:58 - Global Startup Scene
In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.
Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.
Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.
Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.
James Cham is a partner at Bloomberg Beta, a venture capital firm focused on the future of work. James invests in companies applying machine intelligence to businesses and society. Prior to Bloomberg Beta, James was a Principal at Trinity Ventures and a VP at Bessemer Venture Partners. He was educated in computer science at Harvard and at the MIT Sloan School of Business.
In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.
Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.
Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.
Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.
MIT Technology Review reports on our startup Genomic Prediction. Some basic points worth clarifying:
1. GP's first product, announced at the annual ASRM (American Society of Reproductive Medicine) meeting this week, tests chromosomal abnormality. It is a less expensive but more accurate version of existing tests.
2. The polygenic product, to be launched in 2018, checks for hundreds of known single-gene ("Mendelian") disease risks, and will likely have some true polygenic predictive capabilities. This last part is the main emphasis of the story, but it is just one component of the overall product offering. The article elides a lot of challenging laboratory work on DNA amplification, etc.
3. GP will only deliver results requested by an IVF physician. It is not a DTC (Direct to Consumer) company.
4. All medical risk analysis proceeds from statistical data (analyzing groups of people) to produce recommendations concerning a specific individual.
5. I am on the Board of Directors of GP but am not an employee of the company.
Will you be among the first to pick your kids’ IQ? As machine learning unlocks predictions from DNA databases, scientists say parents could have choices never before possible.
Nathan Treff was diagnosed with type 1 diabetes at 24. It’s a disease that runs in families, but it has complex causes. More than one gene is involved. And the environment plays a role too.
So you don’t know who will get it. Treff’s grandfather had it, and lost a leg. But Treff’s three young kids are fine, so far. He’s crossing his fingers they won’t develop it later.
Now Treff, an in vitro fertilization specialist, is working on a radical way to change the odds. Using a combination of computer models and DNA tests, the startup company he’s working with, Genomic Prediction, thinks it has a way of predicting which IVF embryos in a laboratory dish would be most likely to develop type 1 diabetes or other complex diseases. Armed with such statistical scorecards, doctors and parents could huddle and choose to avoid embryos with failing grades.
IVF clinics already test the DNA of embryos to spot rare diseases, like cystic fibrosis, caused by defects in a single gene. But these “preimplantation” tests are poised for a dramatic leap forward as it becomes possible to peer more deeply at an embryo’s genome and create broad statistical forecasts about the person it would become.
The advance is occurring, say scientists, thanks to a growing flood of genetic data collected from large population studies. ...
Spotting outliers
The company’s plans rely on a tidal wave of new knowledge showing how small genetic differences can add up to put one person, but not another, at high odds for diabetes, a neurotic personality, or a taller or shorter height. Already, such “polygenic risk scores” are used in direct-to-consumer gene tests, such as reports from 23andMe that tell customers their genetic chance of being overweight.
For adults, risk scores are little more than a novelty or a source of health advice they can ignore. But if the same information is generated about an embryo, it could lead to existential consequences: who will be born, and who stays in a laboratory freezer.
“I remind my partners, ‘You know, if my parents had this test, I wouldn’t be here,’” says Treff, a prize-winning expert on diagnostic technology who is the author of more than 90 scientific papers.
Genomic Prediction was founded this year and has raised funds from venture capitalists in Silicon Valley, though it declines to say who they are. Tellier, whose inspiration is the science fiction film Gattaca, says the company plans to offer reports to IVF doctors and parents identifying “outliers”—those embryos whose genetic scores put them at the wrong end of a statistical curve for disorders such as diabetes, late-life osteoporosis, schizophrenia, and dwarfism, depending on whether models for those problems prove accurate. ...
This week, Genomic Prediction manned a booth at the annual meeting of the American Society for Reproductive Medicine. That organization, which represents fertility doctors and scientists, has previously said it thinks testing embryos for late-life conditions, like Alzheimer’s, would be “ethically justified.” It cited, among other reasons, the “reproductive liberty” of parents.
... Hsu’s prediction is that “billionaires and Silicon Valley types” will be the early adopters of embryo selection technology, becoming among the first “to do IVF even though they don’t need IVF.” As they start producing fewer unhealthy children, and more exceptional ones, the rest of society could follow suit.
“I fully predict it will be possible,” says Hsu of selecting embryos with higher IQ scores. “But we’ve said that we as a company are not going to do it. It’s a difficult issue, like nuclear weapons or gene editing. There will be some future debate over whether this should be legal, or made illegal. Countries will have referendums on it.”
Highly recommended! I blogged about this guy 5 years ago here: From physics to Goldman to Y Combinator. The book is hilarious and pretty accurate, AFAICT. I don't know much about Facebook corporate culture or that particular era of ad monetization, but the finance and startup stuff all rings true.
The reality is, Silicon Valley capitalism is very simple:
Investors are people with more money than time.
Employees are people with more time than money.
Entrepreneurs are the seductive go-between.
Startups are business experiments performed with other people's money.
I was a Berkeley PhD student in physics when the first dot-com bubble grew to bursting and popped around 2001. Between the month-long backpacking trips and the telenovela-esque romances, I switched thesis topic three times, and felt my twenty-something vitality slipping away in academic wankery. Inspired by Michael Lewis’ Liar’s Poker and the prior example of many a failed physicist, I looked for a Wall Street gig as a way out. Very improbably, I landed a job on the trading desk of Goldman Sachs, earning twice what my tenured professor made, pricing and modeling credit derivatives at ground-zero of the credit bubble. I may have owned one pair of lace-up shoes at the time, but I got used to speaking in quantities of hundreds of millions of dollars, and thinking a million was a ‘buck’, i.e., a rounding error for most purposes. I was very far away indeed from Berkeley.
Right around 2008, when Lehman Brothers and Bear Stearns blew up, I knew the financial jig would be up for a while (and possibly forever), unlike most of my colleagues, who seemed to think orgies of rapacious greed lasted forever. The only piece of the US economy that would be spared the apocalypse was clear in my mind: the Bay Area tech of my languid grad school days, and all that VC money that (hopefully) hadn’t touched the mortgage bubble..
Two weeks later, I started as employee number seventy-something at a venture-backed advertising startup so incompetent and vile I’ll save the historical distaste for later. Bookended as it was by experiences at Facebook and Goldman, my time there was instructive in its awfulness and how not to run a company. But there was one piece of upside: I learned how online advertising worked, specifically its ad exchange variants. As a ‘research scientist’ I tortured every piece of data until it confessed, and used it to predict user behavior, value of media purchased, and optimal bids in the largest ad auctions in the world. Dull stuff you might say, but it’s what pays for the Internet, and it would set me light-years ahead of anyone inside Facebook Ads, when the time came.
But we’re jumping ahead.
Along with the two best engineers at Shitty Unnamed Company, I applied and was accepted to Y Combinator, the Valley’s leading startup incubator. We pitched some wild, ridiculous idea around local businesses that was doomed from the start, which eventually morphed into a novel tool for managing Google search campaigns for small businesses. The tool was beautiful, innovative, and didn’t make us a dime. More bad news: We got vindictively and frivolously sued by Shitty Company and fought an existential legal battle we narrowly won by being lying, ruthless little shits. We couldn’t raise money. We had co- founder and morale issues. Every ill that plagues early-stage startups visited us in turn, like some admonitory biblical tale about what happens if you fuck with the Israelites. ...
... Every startup entrepreneur faces the immense disadvantage of playing a crooked, complex game for the first time, against a world composed mostly of masters. Arrayed against you is an army of wily, self-interested venture capitalists who know term sheets better than their wife’s ass. Or seductive sales execs who could make pedophilia and genocide enforceable via a legal contract. Or petulant co-founders with hidden agendas and momentarily suppressed grievances. Or ungrateful employees who are exploiting your startup until they can start their own. Or thick-headed journalists with urgent deadlines who just want you for a misleading quote. You get trounced again and again, and the only hope is that you learn something of the game before expiring. This is your principal challenge as a first-time entrepreneur: to learn the game faster than you burn cash and relationships.
A Silicon Valley entrepreneur and angel investor (originally from Germany) on the Beijing startup ecosystem. See also Canyons of Zhongguancun.
recode: ... Beijing will be the only true competitor to Silicon Valley in the next 10 years.
Beijing is not just a nice startup playground which might become truly interesting in a few years. This is the big leagues now. Startups can achieve massive scale quickly, because the domestic market is 1.3 billion people, which is four times the U.S. or European population.
An increasing share of these 1.3 billion people is actually targetable. In the U.S., 190 million people carry a smartphone; in China, it is more than 530 million today, and it will be 700 million or more in three years.
But a large market alone does not mean that a place will become a startup hub. It is the combination of market size and the extreme consumer-adoption speed of new services, combined with the entrepreneurial spirit and hunger for scale of Chinese entrepreneurs.
Beijing is the main hub where it happens. Here, entrepreneurs, engineering talent from the two top Chinese universities — Tsinghua and Peking — and VC money come together. Seeing the scale, speed, aspirations, money supply and talent here, I walked away thinking this will be the only true competitor to Silicon Valley in the next 10 years.
... Big startups are built in three to five years versus five to eight in the U.S. Accordingly, entrepreneurs who try to jump on the bandwagon of a successful idea scramble to outcompete each other as fast as they can.
Work-life balance is nonexistent in Chinese startups.
Meetings are anytime — really. My meeting in Beijing with Hugo Barra, who runs all international expansion for Xiaomi — the cool smartphone maker and highest-valued startup in China, at around $45 billion or so — was scheduled for 11 pm, but got delayed because of other meetings, so it started at midnight. (Hugo had a flight to catch at 6:30 am after that.)
In China, there is a company work culture at startups that's called 9/9/6. It means that regular work hours for most employees are from 9 am to 9 pm, six days a week. If you thought Silicon Valley has intense work hours, think again.
For founders and top executives, it's often 9/11/6.5. That's probably not very efficient and useful (who's good as a leader when they're always tired and don't know their kids?) but totally common.
Teams get locked up in hotels for weeks before a product launch, where they only work, sleep and work out, to drive 100 percent focus without distractions and make the launch date. And while I don't think long hours are any measure of productivity, I was amazed by the enormous hunger and drive. ...
The fence we walked between the years
Did balance us serene
It was a place half in the sky where
In the green of leaf and promising of peach
We'd reach our hands to touch and almost touch the sky
If we could reach and touch, we said,
'Twould teach us, not to, never to, be dead
We ached and almost touched that stuff;
Our reach was never quite enough.
If only we had taller been
And touched God's cuff, His hem,
We would not have to go with them
Who've gone before,
Who, short as us, stood as they could stand
And hoped by stretching tall that they might keep their land
Their home, their hearth, their flesh and soul.
But they, like us, were standing in a hole
O, Thomas, will a Race one day stand really tall
Across the Void, across the Universe and all?
And, measured out with rocket fire,
At last put Adam's finger forth
As on the Sistine Ceiling,
And God's hand come down the other way
To measure man and find him Good
And Gift him with Forever's Day?
I work for that
Short man, Large dream
I send my rockets forth between my ears
Hoping an inch of Good is worth a pound of years
Aching to hear a voice cry back along the universal mall:
We've reached Alpha Centauri!
We're tall, O God, we're tall!
Fortune: Venture capital firms invested $1.8 billion in commercial space startups in 2015, nearly doubling the amount of venture cash invested in the industry in all of the previous 15 years combined. ...
This is a good discussion of VR technology, on the Andreesen Horowitz podcast. I recently bumped into a tech founder who swears the transition to full immersion is real and right around the corner technologically.
Virtual reality is coming fast, and everyone seems to assume that it will be gamers who get to have all the fun first. But there are other applications for VR that could also bring it into the mainstream. “It could very well be business users,” says 16z’s Chris Dixon. “It’s anything where you would want time travel or teleportation.”
Dixon is joined on this segment of the podcast by Saku Panditharatne and Kyle Russell, both on the firm’s deal team, to offer their perspective on how virtual reality is likely to enter all of our lives. This year promises to be the moment when more than a very small number of people will get their first taste of VR. What that looks and feels like, and what that shared experience sets in motion on this segment of the a16z podcast.
Via Dominic Cummings (@odysseanproject), this long discussion of the history of venture capital, which emphasizes the now largely forgotten 1980s. VC in most parts of the developed world, even large parts of the US, resembles the distant past of the above chart. There is a big gap between Silicon Valley and the rest.
... Risk is uncertainty about the future. High technical risk means not knowing if a technology will work. High market risk means not knowing if there will be a market for your product. These are the primary risks that the VC industry as a whole contemplates. (There are other risks extrinsic to individual companies, like regulatory risk, but these are less frequent.)
Each type of risk has a different effect on VC returns. Technical risk is horrible for returns, so VCs do not take technical risk. There are a handful of examples of high technical risk companies that had great returns–Genentech43, for example–but they are few44. Today, VCs wait until there is a working prototype before they fund, but successful VCs have always waited until the technical risk was mitigated. Apple Computer, for example, did not have technical risk: the technology worked before the company was funded.
Market risk, on the other hand, is directly correlated to VC returns. When Apple was funded no one had any way of knowing how many people would buy a personal computer; the ultimate size of the market was analytically unknowable. DEC, Intel, Google, etc. all went into markets that they helped create. High market risk is associated with the best VC investments of all time. In the late ’70s/early ’80s and again in the mid to late ’90s VCs were comfortable funding companies with mind-boggling market risk, and they got amazing returns in exchange. In the mid to late ’80s they were scared and funded companies with low market risk instead, and returns were horrible.
Today is like the 1980s. There are a plethora of me-too companies, companies with a new angle on a well-understood market, and companies founded with the hopes of being acquired before they need to bring on many customers. VCs are insisting on market validation before investing, and are putting money into sectors that have already seen big exits (a sign of a market that has already emerged.)
Saying VCs used to take high technical risk and now take high market risk is both an overly optimistic view of the past–the mythical golden age of heroic VCs championing the development of new technologies–and an overly optimistic view of the present–gutsy VCs funding radical innovations that create entirely new markets. Neither of these things is true. VCs have never funded technical risk and they are not now funding market risk45. The VC community is purposely avoiding risk because we think we can make good returns without taking it. The lesson of the 1980s is that no matter how appealing this fantasy is, it’s still a fantasy.
I'm catching up on podcasts a bit now that I'm back in Michigan. I had an iTunes problem and was waiting for the next version release while on the road.
Econtalk did a nice interview with Y Combinator President Sam Altman. Y Combinator has always been entrepreneur-centric, to the point that the quality of the founders is one of the main factors they consider (i.e., more important than startup idea or business plan). At around 19 minutes, Altman reveals that they often "fund for the pivot" -- meaning that sometimes they want to place a bet on the entrepreneur even if they think the original idea is doomed. Altman also reveals that Y Combinator never looks at business plans or revenue projections. I can't count the number of times an idiot MBA demanded a detailed revenue projection from one of my startups, at a stage where the numbers and projections were completely meaningless.
Another good observation is about the importance of communication skills in a founder. The leadership team are a central nexus that has to informationally equilibrate the rest of the company + investors + partners + board members + journalists + customers ... This is benefited tremendously by having someone who is articulate, succinct, and can "code switch" so as to speak the native language of an engineer or sales rep or VC.
@30 min or so:
Russ: ... one of the things that happens to me when I come out here in the summer--I live outside of Washington, D.C. and I come out every 6 or 7 weeks in the summer, and come to Stanford--I feel like I'm at the center of the universe. You know, Washington is--everyone in Washington, except for me--
Guest: Thinks they are--
Russ: Thinks they are in the center. And there are things they are in the center in. Obviously. But it's so placid there. And when I come to Stanford, the intellectual, the excitement about products and transforming concepts into reality, is palpable. And then I run into start-up people and venture capitalists. And they are so alive, compared to, say, a lobbyist in Washington, say, just to pick a random example. And there are certain things that just--again, it's almost palpable. You can almost feel them. So the thing is that I notice being here--which are already the next big thing, which at least they feel like they are. [ Visiting Washington DC gives me hives! ]
I recall a Foo Camp (the O'Reilly one, not SCI FOO at Google; perhaps 2007-2010 or so) session led by Paul Graham and some of the other Y Combinator founders/funders. At the time they weren't sure at all that their model would work. It was quite an honest discussion and I think even they must be surprised at how successful they've been since then.
The gritty life of a startup founder in 2014 Silicon Valley.
WIRED: ... you’re getting a lot of people starting companies who shouldn’t be starting companies. Another investor I talked to called this “buying a cheap call option on a guy who doesn’t know that’s what you’re doing”—on a guy, that is, who thinks you’re investing in his success, not betting on the high-risk, high-yield chances of it. You know the odds on any given company’s success are long, but that’s why you make a lot of bets. In the first dotcom boom, the risk was largely carried by the investors, but now the risk has been returned to the youth.
Without mentioning the name of the company, I told him about Boomtrain, about what the past few weeks and months had been like for them. About how quickly they’d aged, how much weight they’d lost, the Airbnb-ing, the heavy mask of confidence, the number of mornings they’d woken up at 5 am grinding their teeth. Martino was sympathetic but unmoved. He didn’t expect them to make it. “They ran an experiment. None of their lives have been ruined.” He knew they’d get good jobs, even if it meant the life of a project manager at Yahoo. “And none of their investors’ lives have been ruined either. When they close up shop, their investors will say, ‘That’s one more off the books. I don’t need to help them anymore. I get my time back.’”
Martino watched the game for a minute, then turned back to me and held my gaze. He could tell I’d come to like and admire and root for the Boomtrain guys. I could understand the risk they thought they were taking. I was glad it looked like they’d finally found the momentum they so badly needed. “Let me tell you what the worst thing would be. The worst thing is that these guys get their funding tomorrow and are stuck doing this for another year. So far, they only lost one.” ...
All the while, Martino’s ultimate warning—that they might someday regret actually getting the money they wanted—would still hang over these two young men, inherent to a system designed to turn strivers into subcontractors. Instead of what you want to build—the consumer-facing, world-remaking thing—almost invariably you are pushed to build a small piece of technology that somebody with a lot of money wants built cheaply. As the engineer and writer Alex Payne put it, these startups represent “the field offices of a large distributed workforce assembled by venture capitalists and their associate institutions,” doing low-overhead, low-risk R&D for five corporate giants. In such a system, the real disillusionment isn’t the discovery that you’re unlikely to become a billionaire; it’s the realization that your feeling of autonomy is a fantasy, and that the vast majority of you have been set up to fail by design.
The biotech industry is, collectively (despite the occasional wins), a huge net destroyer of investor capital. That Complete Genomics was able to go public in 2010 (NAS: GNOM) is crazy: both their business model and technology were unproven -- but that's biotech investing! BGI paid a startup price for a NASDAQ company ... Word on the street: over $100M invested by VCs pre-IPO, with a > $100M raise in the IPO float.
NYTimes: Complete Genomics, a struggling DNA sequencing company in Silicon Valley, said on Monday that it had agreed to be acquired for $117.6 million by BGI-Shenzhen, a Chinese company that operates the world’s largest sequencing operation.
The price of $3.15 a share represents an 18 percent premium to Complete Genomics’ closing price on Friday and a 54 percent premium to the closing price on June 4, the day before the company announced that it would fire 55 employees to save cash and that it had hired an adviser to explore strategic alternatives.
The deal, which will be carried out by a tender offer, is the latest sign of consolidation in the rapidly changing and fiercely competitive market for DNA sequencing. The price of determining the DNA blueprint of a person is tumbling and sequencing is starting to be used for medical diagnosis, not just for basic research. ...
See earlier post Physicists can do stuff. Despite the poor outcome for investors, Complete Genomics did develop good technology that will further the science of genomics. This is a very competitive space, and most companies that make sequencing breakthroughs will have a tough time putting it all together: bioinformatic services, sample handling, etc. (on these factors no one can beat BGI's cost advantages). They'll either have to make it in the hardware business or sell themselves to someone like BGI.
Today's WSJ has an article on success rates for venture backed startups. The claim is that 3/4 fail to return investor capital. I suspect the actual success rate is even lower (IIRC from earlier studies).
The excerpt below is from the Kauffman Foundation's report on venture investing. I'd like to see a similar report for hedge and private equity funds.
If you believe in efficient markets and rational sophisticated investors (i.e., pension funds, endowments, the super wealthy), you have to explain why they continue to invest in underperforming asset classes and pay exorbitant fees. My explanation is that apes are not smart. Alpha is hard to detect and it's easier to believe a story (narrative sales pitch) than the numbers (esp. if the numbers are hard to obtain or require a bit of brainpower to interpret). Financial services are incorrectly priced, both by sophisticated investors, and by society. Via Ben Lorica.
EXECUTIVE SUMMARY
Venture capital (VC) has delivered poor returns for more than a decade. VC returns haven’t significantly outperformed the public market since the late 1990s, and, since 1997, less cash has been returned to investors than has been invested in VC. Speculation among industry insiders is that the VC model is broken, despite occasional high-profile successes like Groupon, Zynga, LinkedIn, and Facebook in recent years.
The Kauffman Foundation investment team analyzed our twenty-year history of venture investing experience in nearly 100 VC funds with some of the most notable and exclusive partnership “brands” and concluded that the Limited Partner (LP) investment model is broken. Limited Partners—foundations, endowments, and state pension fund—invest too much capital in underperforming venture capital funds on frequently mis-aligned terms.
Our research suggests that investors like us succumb time and again to narrative fallacies, a well-studied behavioral finance bias. We found in our own portfolio that:
Only twenty of 100 venture funds generated returns that beat a public-market equivalent by more than 3 percent annually, and half of those began investing prior to 1995.
The majority of funds—sixty-two out of 100—failed to exceed returns available from the public markets, after fees and carry were paid.
There is not consistent evidence of a J-curve in venture investing since 1997; the typical Kauffman Foundation venture fund reported peak internal rates of return (IRRs) and investment multiples early in a fund’s life (while still in the typical sixty-month investment period), followed by serial fundraising in month twenty-seven.
Only four of thirty venture capital funds with committed capital of more than $400 million delivered returns better than those available from a publicly traded small cap common stock index.
Of eighty-eight venture funds in our sample, sixty-six failed to deliver expected venture rates of return in the first twenty-seven months (prior to serial fundraises). The cumulative effect of fees, carry, and the uneven nature of venture investing ultimately left us with sixty-nine funds (78 percent) that did not achieve returns sufficient to reward us for patient, expensive, longterm investing.
Investment committees and trustees should shoulder blame for the broken LP investment model, as they have created the conditions for the chronic misallocation of capital. ...
I was shocked at the $1B Instagram acquisition, but then again I'm not exactly up to speed on the latest in iPhone apps or social networking. This Times article gives some background. Although the article stresses founder Kevin Systrom's Stanford connections, it seems like the go to guy was really a Caltecher ;-)
NYTimes: Past midnight, in a dimly lighted warehouse jutting into the San Francisco Bay, Kevin Systrom and Mike Krieger introduced something they had been working on for weeks: a photo-sharing iPhone application called Instagram. What happened next was crazier than they could have imagined.
In a matter of hours, thousands downloaded it. The computer systems handling the photos kept crashing. Neither of them knew what to do.
“Who’s, like, the smartest person I know who I can call up?” Mr. Systrom remembered thinking. He scrolled through his phone and found his man: Adam D’Angelo, a former chief technology officer at Facebook. They had met at a party seven years earlier, over beers in red plastic cups, at the Sigma Nu fraternity at Stanford University. That night in October 2010, Mr. D’Angelo became Instagram’s lifeline.
... For Mr. Systrom, the connections forged at Stanford were crucial.
Mr. D’Angelo, a 2006 graduate of the California Institute of Technology, helped him find engineers, set up databases and flesh out features. Soon after Instagram came out of the box, he put his money into it.
This is an interview with Paul Graham of Y Combinator by Charlie Rose. Founders need to be smart, determined and willing to break the rules -- slightly devious :-)
techcrunch: ... Graham says that when people come to him and say they’ve got a great idea, his first response is, “Tell me about your cofounders”. In general the idea is less important, though he says that if it’s a really terrible idea that might reflect poorly on the founders, and a really great idea might lift them up.
“There are some people who just get what they want in the world. If you want to start a startup you have to be one of those people. You can’t be passive and wishy-washy,” Graham says.
Rose followed up with a key question: how can you tell which people have that kind of determination in ten minutes (which is how long YC interviews are)?
Graham says that it’s hard to tell. “We can be fooled about determination — you can usually tell how smart people are in ten minutes. But people can put on an act for determination for ten minutes.” The YC partners also look for mental flexibility — they’ll ask a company to rotate their idea 90 degrees to see how they respond. “Some people will say yeah, that would work. Others will say, ‘Oh no, actually we wanted to do the other thing.’”
Another key factor: Naughtiness. “Startups often have to do slightly devious things,” Graham says. “You can tell if people have a gleam in their eye. You don’t want people who would be obedient employees… we’re not looking for people who did what they were told in life.”
Graham recounted his initial interactions with Loopt founder Sam Altman, who he first spoke to when he was only 19. (“19 going on 40″, Rose added). Altman was actually initially rejected, but he “pushed back like a 40-year old” and told Graham that he would be joining the program.
Asked about the recurring arguments that we’re in a bubble, Graham said, “I worry prices are high, but I’m reluctant to use the word bubble. Things are not crazy. I warn people that prices are high and that they should raise money now, because things could change tomorrow.”
Overall, Graham says that YC partners are “looking for people like us”, explaining that many VCs are MBAs, whereas YC partners are mostly entrepreneurs. This, Rose later added, appears to be the lowest common denominator uniting the people that YC invests in.
... Asked to list ten of YC’s best successes, Graham listed off: Dropbox, Airbnb, Loopt, Heroku, Scribd, Grepplin, Xobni, Justin.tv (it sounded like he could keep going)
Y Combinator keeps track of the successful companies that they initially rejected. One anecdote: Graham says that MIT Professor and YC Partner Robert Morris is a notoriously low grader for the applications. He had given one app a ‘C’, which sunk it in the ratings, and it went on to be successful. Now YC double-checks every app Morris gives a low grade to.
The total value of YC companies is now around $3 billion — YC has invested a total of around $5 million. !!
I did this interview on entrepreneurship a while ago, and just noticed they now have a transcript up. I'm describing events between 2000-2003, when I was CEO of a startup called SafeWeb.
Me: ... It was the usual lose-a-dollar-on-every-transaction-but-make-it-up-in-volume kind of thing that a lot of people experienced this back in the day. So we succeeded wildly in terms of getting users and…but that was just eating up our cash reserves in terms of the bandwidth costs and stuff like that. ... it was apparent to us we couldn’t continue this way; we weren’t going to become profitable on the consumer side. And there were some efforts at that time to see if there was interest in say Yahoo or by Yahoo or other portals to acquire us so that they could have a kind of Yahoo branded privacy experience for their users. Stuff like that. We had some pretty high level meetings. I shook Jerry Yang’s hand and had a meeting with him at Yahoo and we thought, ‘Oh, hey there’s a chance we’re going to get acquired here.’ But those things didn’t play out and so we had to make a very tough decision just to drop that business and head in the enterprise direction. And that was a very tough decision and we had to cut our team quite a bit after that decision. I’ll never forget …
Me: ... Emeryville’s where Pixar is and a bunch of biotech companies just south of Berkeley; it’s right near the Bay Bridge. And it’s a beautiful little place and we were right on the water, we had a beautiful office and one day I had to … well, how do you fire people? You don’t want to fire people in the middle of a work day with other people around so you know, you kind of wait till the end of the day. This is all, if you look up in management books, there’s a whole algorithm for how you fire people. But one of the problems we had was we had to fire a lot of people, we had to do it all at once and there wasn’t space in the office. So what we did, because we didn’t want to call people in sequentially, so we basically ... just told ... guys to meet us outside. The group that we were going to let go and we had a conversation out there. And I’ll never forget ... it was a beautiful, sunny, idyllic day. We were standing next to the Bay but I was firing five or ten guys. And some of these guys were people I had known for years ... one of the guys actually started crying. And it just… I tell you, every time you hire somebody you should picture that you might have to fire them. That forces you to be careful in the hiring because the most painful thing for me at least, as a CEO, that I ever had to do was fire somebody. And you can’t … you’re not a man if you delegate that. You hired him, you brought him in, you've got to face him and tell him what’s going on. And it’s the toughest thing, I think, for me. Anyway, so anybody who’s ever done it knows what I’m talking about.
...
Me: OK, so, at this point, we were competing well in the SSL VPN space [enterprise security]. We have the potential of closing a pretty big round … like 5, 10 million dollar round, with one of the big Sand Hill shops. And at this time, I’m still the CEO. But what’s happening now is my Department Chair is telling me I have to come back. You’ve been out a year and a half, and you’re going to have to resign or come back. And that’s a typical story, actually. Universities are pretty rigid about this stuff. My wife is also a professor at the same university. So unless she wanted to give up her career, too, I had to go back to the university. I couldn’t stay down in the Valley anymore... very tough decision ... at one point, the senior partner, the managing partner of this fund that wanted to put the money in, we had had a very nice dinner in, you know, one of these. Can’t remember the name of the restaurant. It’s one of the standard restaurants where you eat with VC’s down there. [Laughs] Anyway, so he calls me on the phone ... for some reason I think I’m back in Eugene. He calls me. I’m in my office. I’m actually sitting right where I’m sitting right now. And he says, “Hey, we really like you. We love the company. We think it’s a great opportunity. We want to put the money in. But we’re not putting it in unless you’re CEO. And we don’t like the guy that you have slotted in to take your place.” That was a very tough decision. The future of the company basically bifurcated on that point. So had we taken the money, we would have muscled up. And we probably would not have gone for an acquisition until much later. And it would have been like a 100 million, 200 million dollar acquisition. Instead, because we didn’t get that money, we had to look more immediately for an acquisition. And it turned out to be a smaller acquisition. So my whole life, basically, in that other parallel universe, I would be very different, living in a very different life right now.
Interviewer: And so why did you make that decision? Here you’ve got someone who’s offering you money, who thinks so highly of you as an entrepreneur, that he won’t have anybody else in your place. You still have the possibility for incredible riches. Why give that up?
Me: Well, you know, part of it is, it’s a life choice. And I’m still, to this day, I’m still a professor. So, I’m obviously intellectually interested in the kind of work that I do as a theoretical physicist. And I ultimately chose that, and the family situation, over staying in the company. And, I mean, I became Chairman of the Board of Directors, but I wasn’t the CEO anymore. So, it was a tough decision. I second guess it. I mean maybe I should have stayed, you know.
