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7 Lessons On Startup Funding From a Research Scientist

The following is a guest post by Ty Danco. Ty is an angel investor and startup mentor. Read more of his thoughts at tydanco.com.

My wife isn't in business, but she is wise in the way of funding. Just as I have experience on both sides of the funding table (as an entrepreneur and as an angel), so does she. As a research scientist, she gets her own grants and also reviews grants from others. While she doesn't talk in startup lingo (pivots, minimum viable product, etc.), she has taught me that many of the issues we face as entrepreneurs have a corollary in science. Here's what I've learned from her.science lab

1. Always seek funding from the best people, even when you have easier alternatives.

Before the bootstrappers hang me, I didn't say that you have to raise a lot of money or that you should be working fat. But consider this story: my wife was slaving away writing one particular National Institutes of Health (NIH) grant knowing that the funding rate was ~5%. Why not look for a less competitive foundation to underwrite it instead, I asked. I figured that this could save her time and trouble, and that she could proceed with her experiments that much faster.

That's not how it works, she replied. That's like self-publishing a paper instead of getting it peer-reviewed. If she couldn't convince sophisticated research centers to part with their dwindling cash, she continued, obviously the project wasn't good enough. If it's not good enough to get other people to write a check, it's not good enough to be spending time on. Startup corollaryjust as a paper published in an inferior journal has less impact than the same paper in a good one, when you go for funding, get it from great people. If you have to take dumb money, you're doing it wrong.

Personal application: I'm temporarily self-funding my new startup, FX Aligned, but I'm pitching it to the best East Coast VCs who understand the space. The same logic appliesif I can't convince people who see 1,000 deals that my idea is worth funding, it isn't worth doing.

2. Proposals are always stronger once edited.

Nothing beats peer review, especially from people with deep expertise.

My chat with one VC surprised me. He thought our initial target market was too small. And upon reflection, he was right. At the same time, I was talking to another VC, and I explained to him that we intended to go after that smaller market first, get established, and then work closely with our alpha clients to find solutions to their real pain points. He quoted his senior partner, whose rule was if a new startup is counting on a two-part process to make money, don't fund it. This is exactly the tough love I needed to hear, and it saved me months to time I would have lost if I had self-funded and drunk my own Kool-Aid. We didn't need to do a two-step dance to discover the real market opportunity.

3. If the specific aims of your experiment (company) undergo too many major changes, that's a sign that you haven't thought through the issues yet, and it's too early.

No scientific grant ever makes it from start to finish without changes. Similarly, no VC or angel should be so nave to think that business models turn out perfectly on the first try. However, when a fundamental concept keeps shifting as the idea evolves, there is a problem.

My new company has gone through one major change as we search for product-market fit. However, our edit did not change the core concepts. Our pivot came as we realized that our solution for our original market would, with some minor systems tweaks, serve not only our target market of public pension funds, but now solve an industry-wide problem faced by all institutional managers buying and selling foreign securities. The aim — giving our clients a means to quickly, cheaply, and more efficiently transact foreign exchange without getting ripped-off remains the same, but now the same basic company has a far bigger potential market.

If your concept is not robust at its core, no iteration will help. Before you pivot, ask if the underlying ideas are still valid. If they are, take your time and get the change right.

4. Don't keep it secret.

Scientific grants and paper submissions are kept confidential during the review process to allow for brutally honest feedback, but generally that's the only time of secrecy. The point of science is to advance knowledge, which is done through sharing. Even before a paper is published, preliminary results typically are presented publicly at conferences and ideas are exchanged before the lengthy process of publication. These public discussions can bring in new collaborators, just as startup events can introduce co-founders to each other. Don't hide, network!

Initially I was reticent to talk to angels too much. While my angel friends were good at giving me feedback on presentation matters, none I knew had expertise in fintech, which is where my new company fits in. So I initially wasn't getting a lot of strong commentary. Thanks goes out to James Geshwiler of CommonAngels, however. While he didn't have expertise in my field, he sent me to two angels who did. One of those two angels is now on my Advisory Board, and the other is giving me solid advice on a technical matter that is critical to the company, but outside of my own expertise. What's the result? A lot less risk in our prospects. And besides, as Dharmesh says, stealth mode is for fighter jets — not startups. Read “The Real Reasons Startups Don't Talk”

The more you discuss your idea, the luckier you'll get. Never miss a chance to pitch your idea, but then keep your ears open, especially for the chance contacts that can turn out to be key.

5. It's easy to get funding in trendy areas, but focus more on impact.

I've tagged along to dinners with my wife's scientific colleagues, and once heard a story about zebras grazing. Those zebras that want to play it safe in the middle of the pack can get by, but the juiciest grass — and the greatest danger of being eaten is out on the edges. While it's tempting to go where the funding is, science is about more than just getting another grant.

Find a problem worth solving, not just something convenient for funding. And hopefully, that will be something different. The world doesn't need yet another daily deals aggregator.

By the way, no one should go through the rollercoaster that is startup life unless they are a) certifiably crazy, or b) intending to go big. (See Don Dodge on Google Dreaming BIG.) If you're pitching something, make sure it has potential to change the world.

6. Don't even think about pitching a project without preliminary data.

Scientific grants rarely get funded without substantial preliminary data. It's not just about feasibility, i.e., showing that the method can work; in addition, enough data needs to be submitted to statistically demonstrate the likelihood of the project's success.

This one is a little harder in my case, because it will take a few months to crank out a minimum viable product. However, that doesn't mean we can't test out the markets. We're talking with as many institutional investor customers as we can to get their input on what they need.

This is just customer development 101, a la Steve Blank. For startups, customer data is the best data.

7. The first funding is the hardest.

In science, like in startups, the experienced team always has it much easier rounding up backers. That's just the way it is.

That's one reason why I suggest that people who want to start their own companies begin by working for some rocketship company first. Your own startup becomes more bankable because you'll slowly be absorbing experience that will stand you in good stead in your own future startup. Whoever writes a check wants to see a return on that money, be it in science or in startups. You increase your chances of funding success when you de-risk your venture, especially when a team (or lab) has had time to gel previously.

Thankfully, the team at our new company has had success together before. And that, probably more than anything else, makes it easier this time around. Not that this stuff is ever easy

And a bonus, once you have that funding:

Always be running little experiments on the side. Especially those that can surprise you. For more on this, read Eric Ries' book, The Lean Startup. And while you're doing those experiments, make sure that they are sufficiently well-designed to give you answers.

Any other funding lessons from the lab I missed? Please leave a comment.

Looking for other startup fanatics?  Request access to the OnStartups LinkedIn Group.  130,000+ members and growing daily.

Oh, and by the way, you should follow me on twitter: @dharmesh.


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By Dharmesh Shah – January 16, 2012

Online Courses

There have been video-taped lectures on the web for the past decade since the arrival of video-sharing sites. Early on, I watched a number of them. Some were computer science lectures from the University of Washington Professional Master Program, sponsored by Microsoft, like Data Mining.

However, for the most part, I avoided these video-based lectures or simply played them in the background (learning via osmosis). My issues with video lectures were manifold:

  1. Time. Video lectures consume a considerable amount of time, one to three hours.
  2. Not designed for online consumption. The video is a taping of an in-person lecture. Often times, relevant material in the blackboard or notes slide are not even visible.
  3. Not self-contained. Additional readings are required.

Instead, I would read through lecture presentation and notes for a course from MIT’s OpenCourseWare and other university programs. However, the retention of terminology and information from reading slides is weak. Slides typically have little content and explanation—just bullet points and diagrams, and the amount of time spent reviewing the presentation is a small fraction of the time watching a lecture—not enough to think deeply about a topic. Lecture notes can help, but they are often dry and usually not available.

Led by Andrew Ng, Professors at Stanford in fall 2011 launched three unofficial non-credit courses over the fall directed at the worldwide online audience. These also included regular homework and exams. About a hundred thousand students signed up for each course with over ten thousand fully completing all the requirements .

I took part in all three and found them to be high quality and as effective as regular courses. The Stanford online course lectures have become my sole hobby.

  1. Streamlined videos. Videos are delivered in small chunks with dead time edited out and an option for accelerated viewing.
  2. Optimized for online. Professors speak directly to the camera. Lecture notes are clearly viewable on top a white background instead of a distant blackboard.
  3. Course progress. Viewed videos and completed homeworks are marked.
  4. Community forums. Students communicate with each other and with the course staff.

The courses are taught by prominent professors in their field. Peter Norvig, Google director of R&D and author of AI: A Modern Approach used by 95% of students, teaches AI alongside Sebastien Thrun, an expert in robotics. The courses are somewhat less rigorous than the official Stanford classes and come complete with a certificate of accomplishment. In the AI class, I received congratulatory mail for perfect homework scores and towards the end an invitation to job placement program for the top 1000 students out of about an estimated 36,000 students. I easily obtained a perfect score on ML and DB class assignments.

Stanford initiated other less optimized offerings in previous years such as Stanford Education Everywhere (SEE) and Stanford’s Class X, where are videotaped lectures of courses targeted to Stanford’s professional program: The courses are still available for viewing. In addition to the three Stanford courses earlier, I watched through Introduction to Robotics, Program Analysis and Optimization, iPhone Application Development.

There are currently sixteen Stanford course planned for the winter quarter using the same interactive system in computer science, entrepreneurship, engineering and medicine, of which I plan to take as many as possible.

MITX is an upcoming online course program by MIT along the same vein, extending beyond the OpenCourseWare program.

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By Wes – January 16, 2012

Testing Math Rendering with MathJax

The Lorenz Equations

\[\begin{aligned} \dot{x} & = \sigma(y-x) \\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{aligned} \]

The Cauchy-Schwarz Inequality

\[ \left( \sum_{k=1}^n a_k b_k \right)^2 \leq \left( \sum_{k=1}^n a_k^2 \right) \left( \sum_{k=1}^n b_k^2 \right) \]

A Cross Product Formula

\[\mathbf{V}_1 \times \mathbf{V}_2 = \begin{vmatrix} \mathbf{i} & \mathbf{j} & \mathbf{k} \\ \frac{\partial X}{\partial u} & \frac{\partial Y}{\partial u} & 0 \\ \frac{\partial X}{\partial v} & \frac{\partial Y}{\partial v} & 0 \end{vmatrix} \]

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By Wes – January 15, 2012

The Computers and Internet of Yesteryear

The underlying experiences that we obtain from using computers and the Internet may not be as alien to prior generations as we may think. Things are faster and smaller, but not fundamentally different.

Many complex systems have been with us around for millennia albeit in somewhat different forms: the rule of law, sophisticated government systems, commerce and engineering. A complex system of check processing was possible from distances of 500 miles during the Middle Ages. Our forebears were just as smart as us. For instance, the ancient Latin language is more advanced and refined than modern English in its grammar and sophistication.

We know Charles Babbage at the “father of the computer” for having attempted to build a mechanical computer called the difference engine during the Victorian Era in England, but, some time ago, another ancient mechanical computer was discovered from a Roman shipwreck off of the Greek island of Antikythera dating around 100-150 BC. Scientists who studied using x-ray tomography and other techniques were amazed of its flawless manufacturing and high level of miniaturization and sophistication. One of the scientists speculated that these kinds of devices may have been quite common, because a whole chain of inventions would have been needed to precede them.

Early archaeologists were probably did not recognize such past technological advances earlier because the knowledge was lost through time and of high sophistication requiring the eyes and tools of a trained scientists in other disciplines. In the same way, future generations may not understand, much less reconstruct, modern-day computer chips due to the expertise and billion dollar expenses involved, were the technology lost due to world war or natural disaster.

In another working instance, the book Group Theory in the Bedroom describes the 160-year old astronomical clock of Strasbourg Cathedral, which is essence a mechanical computer and one that has not succumbed to the Y2K problems of modern computers at the turn of the century. The clock includes an vast eclectic set of features, among them,  for instance….

Wait! There’s even more! The clock is inhabited by enough animated figures to open a small theme park. The day of the week is marked by a slow progression of seven Greco-Roman gods in chariots. At noon each day, the twelve apostles appear saluting a figure of Christ, who blesses each in turn and at the end offers benedictions to all present. Every half hour a putto overturns a sandglass, and on the quarter hours another strikes a chime. Still more chimes are sounded by figures representing the four ages of mankind, followed by a skeletal Death, who rings the hours. And a mechanical cock crows on cue, flapping its metal winds….

With regard to the Internet, there were many analogous social practices in prior times. Card catalogs in libraries served the same function as search engines. Penny universities in 18th-century London mirrored the online communities of the day. Long before the era of email, the U.S. Postal Service delivered mail seven days a week multiple times a day. The high frequency of the postal deliveries compensated for the general slowness of technology. The book Victorian Internet: The Remarkable Story of the Telegraph and the Nineteenth Century’s On-line Pioneers details the revolutionary impact of the electric telegraph in nullifying distance and shrinking the world during the nineteenth century much as the Internet has done today.

In his argument against Internet Software Patents, Philip Greenspun invoked the argument that the important technologies of today were envisioned by the early thinkers well before it was even practical to develop. I think that this hints at the commonalities of our experiences across time.

The old timers wrote that we would have tens of millions of computers connected to the Internet, that we would be using those computers to support collaborative work, that we would be able to search for information that would have been digitized on a vast scale, that we would be exchanging digital multimedia information such as pictures or video streams, that there would be a glut of information and that advertisers would pay to get users' attention. The old timers predicted that hardware engineers would figure out how to make silicon-based integrated circuits ever more dense with transistors and powerful, that we would have vast memories, and that there would be computers in every home. The old timers wrote that most business would be conducted via computer network, that electronic mail would surpass hardcopy letters for person-to-person correspondence, that unwanted email would be annoying.

A commenter cites specific examples.

Regarding UI: In As We May Think (1945), Vannevar Bush described an interface that is stunningly recognizable as web browsing. Doug Engelbart's work in the '60s (from which sprang the GUI, as Phil mentioned) was single-mindedly focused on providing the best user interface for what he called "knowledge workers". Some of his UI features, such as those for condensing text passages for quick skimming, are still unmatched. Direct manipulation showed up in Ivan Sutherland's Sketchpad (1963), whose constrained drawing features are also still unmatched. Windowed UI and WYSIWYG editing came with the Xerox Alto (1973). Even today, Photoshop and its clones still use the UI invented by Bill Atkinson for MacPaint (1983). And many believe that Atkinson's HyperCard (1987) is what the web should have been.

The two decades between Englebart's 1962 opus and the release of the Macintosh in 1984 were far and away the most fertile period of UI innovation. Most progress since then has been simply the wide-scale adoption of those ideas.

Regarding Moore's law: Look at the section "A Simple Vision of the Future" in Alan Kay's Early History Of Smalltalk. You will see a man who intimately understood Moore's Law, even in the late '70s.

Old-timers were able to conceive much of the digital experiences of today. Modern digital experiences are another reflection through more advanced technologies of fundamental human interactions that have always existed in some form.

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By Wes – January 15, 2012

News for Poker Copilot Translators

I've made the spreadsheets for translating the Poker Copilot strings a little better. You can now see the English text that you are translating all the time. I've added a column in which you can write "Yes" once you are done downloading. This makes it possible to filter out the strings already translated:

Screen Shot 2012 01 14 at 5 44 00 PM

 

You can also now see the total number of keys, and the number already translated. I figure seeing an updated counter makes it easy to see if much has happened since you last checked the spreadsheet.

 

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By Steve McLeod – January 14, 2012

New York City gets a Software Engineering High School

This fall New York City will open The Academy for Software Engineering, the city’s first public high school that will actually train kids to develop software. The project has been a long time dream of Mike Zamansky, the highly-regarded CS teacher at New York’s elite Stuyvesant public high school. It was jump started when Fred Wilson, a VC at Union Square Ventures, promised to get the tech community to help with knowledge, advice, and money.

I’m on the board of advisors of the new school, which plans to accept ninth graders for fall of 2012. Here’s why I’m excited about this new school:

1. It’s a “limited, unscreened” school.  That’s Board of Ed jargon. It means that any student who is interested can apply—their grades and attendence record are not taken into account in deciding whether or not to admit them, only their interest. I think this is the best thing about the school. A lot of kids are just not interested enough in other academic subjects to get good grades, but they would make great software engineers. A lot of immigrants (especially in New York) are not yet proficient enough in English to get good grades in all their subjects, but they’re going to make great software engineers, too. And in my humble opinion, a school that accepts a cross-section of students is bound to be more enriching than a school that only accepts academic superstars.

2. OMG do we ever need more software engineers. The US post-secondary education system is massively failing us: it’s not producing even remotely enough programmers to meet the hiring needs of the technology industry. Not even remotely enough. Starting salaries for smart programmers from top schools are flirting with the $100,000 mark. Supply isn’t even close to meeting demand. This school is going to be pretty small (in the 400-500 student range) but the Board of Ed has promised that if it’s successful it’ll be used as a template for more schools or for special programs inside larger schools. I predict that they will be overwhelmed with applicants and this will be the most popular new school in New York City in years.

3. And we need more diversity, too. One of the reasons the elite US colleges seem to turn out so few computer science majors every year is that they are only drawing from a narrow pool of mostly white and asian males. Minorities and women are embarrassingly under-represented. Hopefully an unscreened school in New York City can pump a lot more diversity into the pool.

4. It’s not a vocational school. Unlike traditional vocational schools, this new school will have a rigorous academic component and will prepare students for college. But college is not for everyone—many of the best programmers I know were just not interested enough in a general four year degree and went straight into jobs programming.

I’m pleased to be involved in this project, but it needs more help: they’re still looking for qualified computer science teachers and a principal. If you’re interested drop me an email and I’ll make sure it gets through to the right people.

Need to hire a really great programmer? Want a job that doesn't drive you crazy? Visit the Joel on Software Job Board: Great software jobs, great people.

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By Joel Spolsky – January 13, 2012

Updated Poker Copilot Translations

Thanks to the volunteer translators who have already started on the updates I made two days ago to the list of strings to be translated. I've put up a unreleased build that you can use to see how the strings you've translated look in place. Download it here.

 

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By Steve McLeod – January 13, 2012

New Poker Copilot Screenshots Reveal How Version 2 Changed

Updating the website screenshots has been on my to-do list for a year or so. Today I did it. The screenshots show just how much Poker Copilot 2.101 differs from Poker Copilot 2.0.

The HUD as it was:

Hud

The HUD now:

Hud

There are now player icons, colour-coded statistics, and table stats.

 

The hand replayer as it was:

Replayer

 

The hand replayer now:

 

Replayer

It is now sexier, it shows odds of winning, it shows the HUD stats, you can record the hand as a video, you can jump straight to the flop, turn, or river, there are keyboard shortcuts, and you can get the hand history text formatted.

Here is the bankroll chart as it is:

Bankroll

 

And now:

Bankroll

The bankroll chart has barely changed, but the screenshot lets you see how the whole interface has developed.

 

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By Steve McLeod – January 12, 2012

Poker Copilot Translation Project: Update

Hi Poker Copilot translators (current and future…),

The following Poker Copilot translations have 60 or so new text fragments that need to be translated:

  • Hungarian
  • Spanish (Latin American)
  • Italian
  • Dutch
  • French
  • German

The new strings are at the bottom of each translation spreadsheet.

If you've helped out in the past or want to volunteer to help now, I'd be grateful.

More information is here.

 

 

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By Steve McLeod – January 11, 2012

PokerStars now has built-in Auto-Hotkeys

I didn't notice that addition to PokerStars last October: Hotkeys built-in. Although we've had the free BlazingStars to help with on Mac OS X, it is even better when Hotkeys are part of PokerStars itself.

You'll find Hotkeys in PokerStars' Options menu:

Screen Shot 2012 01 11 at 3 55 34 PM

 

I think they've done a nice job in the user interface for defining Hotkeys:

Screen Shot 2012 01 11 at 3 55 07 PM

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By Steve McLeod – January 11, 2012