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Preview: Don Dodge on The Next Big Thing

Don Dodge on The Next Big Thing



Thoughts on business and technology



Updated: 2016-12-06T05:58:58-05:00

 



Google machine Learning news December 2016

2016-12-06T05:58:58-05:00

“Google’s Hand-Fed AI Now Gives Answers, Not Just Search Results” (Wired, Nov 29): “These ‘sentence compression algorithms’ just went live on the desktop incarnation of the search engine. They handle a task that’s pretty simple for humans but has traditionally been quite difficult for machines. They show how deep learning...“Google’s Hand-Fed AI Now Gives Answers, Not Just Search Results” (Wired, Nov 29): “These ‘sentence compression algorithms’ just went live on the desktop incarnation of the search engine. They handle a task that’s pretty simple for humans but has traditionally been quite difficult for machines. They show how deep learning is advancing the art of natural language understanding, the ability to understand and respond to natural human speech. ‘You need to use neural networks—or at least that is the only way we have found to do it,’ Google research product manager David Orr says of the company’s sentence compression work. ‘We have to use all of the most advanced technology we have.’”  https://www.wired.com/2016/11/googles-search-engine-can-now-answer-questions-human-help/ "Deep Learning for Detection of Diabetic Eye Disease" (Google Research Blog November 29) "Diabetic retinopathy (DR) is the fastest growing cause of blindness, with nearly 415 million diabetic patients at risk worldwide. If caught early, the disease can be treated; if not, it can lead to irreversible blindness. Unfortunately, medical specialists capable of detecting the disease are not available in many parts of the world where diabetes is prevalent. Working closely with doctors both in India and the US, we created a development dataset of 128,000 images which were each evaluated by 3-7 ophthalmologists from a panel of 54 ophthalmologists. This dataset was used to train a deep neural network to detect referable diabetic retinopathy. We then tested the algorithm’s performance on two separate clinical validation sets totalling ~12,000 images, with the majority decision of a panel 7 or 8 U.S. board-certified ophthalmologists serving as the reference standard. The results show that our algorithm’s performance is on-par with that of ophthalmologists. For example, on the validation set described in Figure 2, the algorithm has a F-score (combined sensitivity and specificity metric, with max=1) of 0.95, which is slightly better than the median F-score of the 8 ophthalmologists we consulted (measured at 0.91)." https://research.googleblog.com/2016/11/deep-learning-for-detection-of-diabetic.html?m=1 "9 Ways that Google Cloud Machine Learning can help businesses" (Google Blog, November 22) "Maximize job recruitment with Google Cloud Jobs API, Analyze images faster with Vision API and for 80% less cost, Analyze long form docs with Cloud Translation API, Explore, Natural Language Processing translates questions into useful formulas and offers up instant answers in Google Sheets, Graphical Processing Units (GPUs) are great for medical analysis, financial calculations, seismic/subsurface exploration, machine learning, video rendering, transcoding, scientific simulations and more., Quick Access to Google Drive on Android devices to easily and instantly access files, Smart Scheduling in G Suite can now schedule a time and book rooms with machine assistance that includes room suggestions based on previous bookings and time suggestions that account for conflicts easiest to resolve, such as recurring 1:1 meetings., Explore in Google Docs taps into Google’s search engine and machine intelligence to add suggestions based on content within documents. It recommends related topics, images and more for web and mobile docs creation., Format presentations faster: Explore in Google Slides adds ease and speed to creating the most presentable presentations, with design suggestions based on slide content." https://blog.google/topics/google-cloud/9-new-ways-google-cloud-machine-learning-can-help-businesses/ Machine learning | “This Algorithm May Well Save Your Eyesight” (Fortune, Nov 29):  “How transfo[...]



How Google is using Machine Learning and AI

2016-11-28T18:39:45-05:00

Machine Learning will impact everything we do at Google. You can already see the results in Google products you use today. Artificial Intelligence, Machine Learning, Deep Learning, and Big Data are buzzwords we hear every day. What do these words mean? How will Machine Learning make my life better? Let’s...Machine Learning will impact everything we do at Google. You can already see the results in Google products you use today. Artificial Intelligence, Machine Learning, Deep Learning, and Big Data are buzzwords we hear every day. What do these words mean? How will Machine Learning make my life better? Let’s take a look. What is Machine Learning?Isn’t that Artificial Intelligence? Not exactly. Let’s spend a minute defining the terms. AI is a high level term used to describe any approach to make a computer smart. AI started out as a programmed set of rules that could quickly sort through mountains of data to find the desired answer. But, AI rules couldn’t learn or adapt to new data. You could add more “rules” to handle new data, but there was no “learning”. Machine Learning (ML) is a new type of Artificial Intelligence (AI) that lets computers learn without being explicitly programmed. ML is a set of classifiers and algorithms that can teach themselves to grow and adapt when exposed to new data. Machine Learning can learn. This is a BIG deal. Deep Learning (DL) is a particular technique within Machine Learning. It uses an Artificial Neural Network with many layers to learn optimal model parameters. DL creates an algorithm that will automatically decide which features work best to accomplish a task. Finally, Big Data is a term used to describe LOTS of seemingly unrelated data, that upon further analysis could become very useful. “Machine learning is a core, transformative way by which we’re rethinking how we’re doing everything. We are thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. And we’re in early days, but you will see us — in a systematic way — apply machine learning in all these areas.” Sundar Pichai, Google CEO We are already seeing Machine Learning embedded in services like Gmail, Search, Maps, and even in what ads we see. Let’s look at some examples in Gmail. Priority Inbox automatically identifies your important incoming messages and separates them out from everything else. It learns over time what is important to you, and what isn’t. Smart Reply is another Inbox feature that suggests up to three responses based on the emails you get. For those emails that only need a quick response, it can take care of the thinking and save time spent typing. This is especially helpful on mobile phones. The responses get better over time as the system learns.  Google Search and Google Maps employ Machine Learning too. When you start typing in the search box it automatically anticipates what you might be looking for and provides suggested search terms. The suggestions could be based on past searches, what is popular now, or where you are at the time.  Google Assistant is a new example of Machine Learning on Android, helping you with everyday tasks. Click on the video below to see what it can do for you. Google Assistant makes it easy to buy movie tickets while on the go, to find a perfect restaurant for your family to grab a quick bite before the movie starts, and then help you navigate to the theater. Today, Google Assistant is available on the new Google Pixel phone. Older phones have an earlier version called Google Now.   allowfullscreen="" frameborder="0" height="281" src="https://www.youtube.com/embed/FPfQMVf4vwQ?feature=oembed" width="500"> Self Driving Cars are probably the most sophisticated example of Machine Learning in action. If you drive around Mountain View, California you will likely see a Google self-driving car. They have been on campus for several years, and have logged 700,000 miles of accident-free autonomous driving. Watch this video to see what the onboard computers “see” and how t[...]



Ycombinator - Where unicorns are born

2015-04-06T11:33:15-04:00

Angel investing in tech startups is a gut wrenching and risky business. It sometimes feels like buying $25,000 lottery tickets. Most of them lose, but sometimes you invest in a “unicorn” and make 100 times your money or even more. The MIT Blackjack team figured out how to beat the...Angel investing in tech startups is a gut wrenching and risky business. It sometimes feels like buying $25,000 lottery tickets. Most of them lose, but sometimes you invest in a “unicorn” and make 100 times your money or even more. The MIT Blackjack team figured out how to beat the odds in Las Vegas. Paul Graham from Harvard and Robert Morris from MIT teamed up with Trevor Blackwell and Jessica Livingston to found Ycombinator, and in the process figured out how to beat the odds in tech investing. Ycombinator is the largest and most successful startup incubator in history, and it was started right here in Cambridge, Massachusetts. Startup incubators and accelerators are everywhere today, but were relatively unknown when Ycombinator started 10 years ago. Ycombinator has deep roots in the area. Co-founder Paul Graham got his Masters and Doctorate degrees from Harvard. Robert Morris, another co-founder, was a professor at MIT. Paul decided to start Ycombinator after giving a talk at a Harvard Computer Club on how to start companies. Paul and his co-founders wanted to get involved in Angel investing but wanted to do it in a scalable way, involve lots of friends and advisors, and be more “hands on” than the typical Angel investor. There was no scalable way to do that at the time. Thus was born Ycombinator. Over the past 10 years YCombinator has been amazingly successful, funding 842 companies worth an estimated $30 Billion. Those companies have raised over $3B from outside investors, and 32 of those companies are now worth more than $100 Million each. Some of the most successful companies include; AirBnB, DropBox, Stripe, Twitch, Reddit, Instacart, Zenefits, Mixpanel, Weebly, Parse, Heroku, and OMGpop. At last count 89 Ycombinator companies have been acquired, while at the other end of the spectrum, 84 Ycombinator companies are no longer active and total wipe-outs.The remaining 669 companies are still operating. To put this in perspective, most early stage tech investors expect that half their companies will fail, sometimes very quickly. They all look like winners when you write the check...you just don’t know which ones will fail. But if you invest smartly, and spread your risk over a large portfolio, the winners will pay for all the losers and return a nice overall profit. The return on investment in AirBnB or Dropbox could pay for all other investments. But, no matter how smart we think we are at avoiding risky startups, we can miss on surprising “unicorn” winners too.  DropBox is one of those Ycombinator Cambridge winners that most investors missed, including me. Drew Houston was born in Acton, and met his co-founder Arash Ferdowsi at MIT. They were part of the Ycombinator Cambridge class of 2007, after being rejected by YC in 2005 and 2006. I remember the Demo Day in 2007 where DropBox presented to about 30 Boston area Angels and Venture Capital investors. None of the local VC firms invested. Seeing little opportunity here, Drew and Arash moved the company to Silicon Valley later that year. They got their initial funding of $1.2M from Sequoia Capital and have gone on to raise over $1 Billion from VC investors. Dropbox is expected to IPO in 2015 at a valuation exceeding $10 Billion. In fairness to the investors in the room that day in Cambridge it was not at all obvious that Dropbox would succeed. The problem they were solving was not one I had experienced, and the product demo didn’t work very well at the time. Two years earlier I saw another Boston based startup called Carbonite pitch a similar cloud backup solution to investors. Many investors passed on that too. The reason was that Microsoft, Google, Apple, and other large technology companies already offered[...]



My 5 predictions for 2015 and beyond

2015-01-01T10:49:15-05:00

My 5 predictions for the tech world in 2015 and the next 5 years; Sensors, Indoor Location, Alternative networks, Wearable computers, the demise of cable TV. Billions of sensors will monitor everything, and become the next platform shift in computing. Your home, car, office, and even people will have special...

My 5 predictions for the tech world in 2015 and the next 5 years; Sensors, Indoor Location, Alternative networks, Wearable computers, the demise of cable TV.

Billions of sensors will monitor everything, and become the next platform shift in computing. Your home, car, office, and even people will have special sensors that help us manage the complexities of life.

Indoor Location and Positioning, enabled by Smartphones, will become a part of many existing apps, and enable new services. Think about how web maps started as a standalone application and were later embedded into all sorts of web sites. The same will happen for Indoor Location on mobile apps.

Alternative network for Internet of Things (IoT) will be required to realize the full potential of IoT. Those billions of sensors will require a low cost network to transmit data to the Internet. Wifi is only useful within 100 feet, and cell data plans are too expensive for tiny inexpensive sensors. A new form of low cost, meshed network, will be built to enable the IoT.

Wearable computers integrated with Smartphones to enable the "Quantified Self". Google Glass got people thinking about how wearables could be used. Android Wear watches will eventually do everything your Smartphone can do, and much more. Wearable computers will contain sensors to monitor your body, health, and environment. They will connect to your Smartphone for computing power and network connection.

Cable TV will lose its stranglehold on subscribers as more content creators go direct to consumer. This year we saw HBO, Netflix, CBS, Hulu, NFL offer stand alone web/mobile subscriptions for their content. The "cord cutters" and "cord nevers" already get all the content they want without a cable TV contract. Cable TV will lose lots of subscribers as more sports and entertainment producers offer their content direct over the Internet for a low monthly subscription.

Five years ago I wrote this post on predictions for 2010 and beyond. Pretty accurate so far. How will I do on these 5 predictions for 2015? Time will tell, but I feel pretty good about them now.

Happy New Year!




Indoor Location startups innovating Indoor Positioning

2013-06-19T14:26:23-04:00

Indoor Location and Positioning technology is the Next Big Thing. It is bringing the power of GPS and Maps indoors. We spend most of our time indoors, working, shopping, eating, at the mall, at the office, on campus, etc. Apple and Google are competing on street maps, but are also... Indoor Location and Positioning technology is the Next Big Thing. It is bringing the power of GPS and Maps indoors. We spend most of our time indoors, working, shopping, eating, at the mall, at the office, on campus, etc. Apple and Google are competing on street maps, but are also working on Indoor Location. Lots of startups are going after this market too. In this post I will mention all that I am aware of. One or two winners, and a hundred broken hearts - Most web or social app markets are dominated by one or two big early players due to “First Mover Advantage” or network effects and scale of the user base. Indoor Positioning Systems will be different for two major reasons. First, there are so many potential vertical markets for applications it is unlikely one company or application could serve all the needs of those markets. Second, there are hundreds of thousands of mobile apps that can use Indoor Location in different ways. No clear leader exists today, and isn’t likely to emerge for a long time. Since no single technology is ubiquitous some companies are employing multiple technologies in their product. Many of these companies are technology providers aspiring to be ILPS platforms with APIs for application developers. Some companies may show up in multiple categories below. They are presented in alphabetical order, not order of importance. There are trade-offs to each of the technologies. WiFi is low cost and ubiquitous, but not very accurate. High precision location usually requires higher cost and infrastructure work. Proprietary technologies can be very accurate, but cost more and aren’t ubiquitous...so the apps only work where that infrastructure is installed. High accuracy today is considered to be 1 to 5 meters. Medium accuracy is 6 to 10 meters, and low accuracy is over 11 meters. Cost is a subjective thing but I will attempt a rough guess in the Low, Medium, or High cost range for each, with the symbols, $, $$, or $$$. WiFi Triangualtion - WiFi Triangulation measures signal loss or strength from three or more WiFi hotspots to triangulate position. The app doesn’t need to access the WiFi, it just pings to measure signal strength. Ekahau (Medium/ $$)  Meridian - acquired by Aruba Networks - (Unkown)  Navizon (Medium/ $)  Proximus Mobility  (Unkown)  SenseWhere (Scotland)  (Medium/ $)  WiFiSlam – acquired by Apple (High/ $$)  ZOS Communications (Unkown)  WiFi Fingerprinting - Smartphones turn on WiFi for a few seconds to get a WiFi Fingerprint and associate it with a Check-In location. Compares the current WiFi Fingerprint to a known database of Fingerprint/Location pairs. Aisle 411 (High/ $$)  EveryFit (Unkown)  Guardly (Unkown)  Indoo.rs (Austria) (Unkown)  Insiteo (France) (High/ $$$)  Lighthouse Signal Systems (Unkown)  PoleStar (High/ $$$)  PointInside (High/ $$$)  Qubulus (Sweden)  (High/ $$$)  WalkBase (Finland) (Low/ $)  Wifarer (High/ $$$)  WiFiSlam (High/ $$)  Yfind (Singapore) (High/ $$)  Beacons - Cheap, low power, radio beacons located at known positions within a building. Could be Bluetooth, High frequency radio, radio inference or other proprietary radio signals. Uses the same location triangulation methods as WiFi. BlinkSight (France)  (Unkown)  Ekahau (Medium/ $$$)  Insiteo (High/ $$$)  InvisiTrack (Unknown)  Locata (Medium/ $$$)  OmniSense (England) (Medium/ $$$)  Quuppa (Finland)  (Unknown)  Teldio (Canada) (Medium/ $$$)  UbiSense (England) (Unknown)  WiseSec (Israel) (Unknown)  Zulu Time (Unknown)  BlueTooth - Many electronic devices contain Bluetooth radios,[...]



Leaders in Indoor Location Positioning technology

2013-04-05T13:54:38-04:00

Who are the big players innovating in Indoor Location and Positioning? What technologies are attracting the most attention? How will Indoor Location evolve? In my previous post I covered the different technical approaches to Indoor Location, how they work, and some of the market uses for it. In this post... Who are the big players innovating in Indoor Location and Positioning? What technologies are attracting the most attention? How will Indoor Location evolve? In my previous post I covered the different technical approaches to Indoor Location, how they work, and some of the market uses for it. In this post I will cover some of the leading large players and their technical approaches. In an upcoming post I will cover many startups that are innovating faster than the big companies. Who are the big players? Indoor Location will be a huge market, bigger than Maps or GPS. Many big companies have been researching this technology for years. Some already have products in the market. Here is a quick look at some of the players and where they fit in the technology stack. Chip Sets - Mobile chip manufacturers are consolidating the wifi, NFC (Near Field Communications), Bluetooth, cellular, and GPS radios needed to calculate indoor location, as well as sensors like accelerometers, gyros, altimeters, compass, and magnetometers into the chip sets. Leaders in this space include; Broadcom, Qualcomm, InvenSense, STMicroelectonics and CSR. These chip sets provide the x,y coordinates, signal strength, direction, and other sensor data that Operating Systems and Applications can use to calculate precise location reference points. Mobile Operating Systems - Mobile Operating Systems are also incorporating Indoor Location services that application developers can access via APIs. The big players in this space include Apple, Google, and Microsoft. Apple is late to market with Maps and even further behind with Indoor Location which is one reason why they recently acquired WifiSlam, an indoor location startup. Expect Apple to make significant progress in this area through internal development and acquisitions. Google's Android OS powers many Smartphones which already include Google Maps. Google has provided indoor maps for over 10,000 buildings including office buildings,  airports, shopping malls, and other public buildings for a long time. Google has also piloted Indoor Positioning using Wifi signal triangulation. Do a Google Maps search for Westfield Mall San Francisco. Watch what happens as you zoom in to the location...an Indoor Map of the mall identifies the individual stores, and even where the hand bags are located within a store. Microsoft's Bing Maps has over 3,000 indoor maps of airports, shopping malls, and public buildings. Handset Manufacturers - The large Smartphone handset manufacturers are incorporating the location chip sets and Mobile Operating Systems into their phones. They are also adding their own software and services for location. All the major players are doing research and development on Indoor Location. These include Motorola, Nokia, Samsung, and Sony Ericsson. Motorola already has Indoor Location Manager, and recently announced TRX Indoor Location System. Motorola has been researching indoor location for many years and has a significant patent portfolio that covers wifi signals, Bluetooth technology, Inertial Navigation using sensors, and even using signals from indoor lighting.  Nokia has its own indoor location technology called HAIP (High Accuracy Indoor Positioning) based on BlueTooth Low Energy beacons (BLE). Nokia also started the In-Location Alliance which is an industry trade group focused on Indoor Location. Nokia demoed their indoor location technology at Mobile World Congress 2012. Here is a YouTube video of that demo. Samsung is part of the In-Location Alliance and one of the largest Smartphone manufacturers. Samsung has also done significant research on [...]



Why Indoor Location will be bigger than GPS or Maps, and how it works

2013-04-02T11:31:30-04:00

Indoor Location and Positioning will be huge! Apple recently acquired WifiSlam for its indoor mapping and positioning technology. Why? Because we spend most of our time indoors, working, shopping, eating, at the mall, at the office, on campus, etc. Google already has Indoor Maps for many airports and shopping malls.... Indoor Location and Positioning will be huge! Apple recently acquired WifiSlam for its indoor mapping and positioning technology. Why? Because we spend most of our time indoors, working, shopping, eating, at the mall, at the office, on campus, etc.  Google already has Indoor Maps for many airports and shopping malls. The race is on. The explosion of Smartphones with built in sensors, accelerometer, gyro, wifi radios, and camera make indoor positioning possible.  GPS and Maps are great, but they only work outdoors and with clear line of sight to the sky. GPS was developed by the US military for battlefield location, and navigation for planes and ships. It uses 24 satellites orbiting 12,600 miles above the earth. Your GPS unit searches for 3 or 4 satellites to "lock" your position. Your GPS receiver "knows" the location of the satellites, because that information is included in satellite transmissions. It measures the time it takes for the signal from each satellite to reach your device, calculates the distance from each, then triangulates your position...and updates it every second in real time. GPS is still remarkable decades after it was developed. You may have noticed that your Smartphone mapping system is much faster at findng your initial position than your car GPS. Why? Because your car GPS relies soley on GPS satellite signals. In heavily forested areas, or congested cities with tall buildings, it can take a long time to get a "GPS lock" on 3 or 4 satellites because the "line of sight" is blocked. Your Smartphone mapping system augments the GPS with cellular tower signals and known Wifi hotspot locations. These signals are available where GPS is hard to get. Your Smartphone searches for all types of signals, calculates which is most accurate, and provides your location on a map much faster than a regular car GPS. Smartphone GPS is truly amazing! But, Indoor Location is even more amazing. Now lets explore how it can be used, and understand how it works. Why will indoor location be big? Because indoors is where we spend money, meet friends, and where business happens. How can indoor location be used? Navigation – Navigating inside large shopping malls, museums, airports, office buildings, college campuses, manufacturing plants, conference and convention venues Location sharing for Social or family apps – Sharing your location with family and friends at large, crowded locations, or meeting up after individual activities Shopping list routing – Find specific aisle locations within stores for every item on your shopping list. Enter a search term to find location of any product. Offers/Coupons – Receive discount coupons and offers for products and services you care about located in close proximity. Games – Many mobile games could incorporate indoor location. Games like MyTown, Life is Crime, Tap City, Monopoly, and strategy games like Tower defense, Risk, Coalition Games, and other strategy games.  Advertising by location – Targeted advertising based on precise location, time, and interests. Manufacturing/Inventory/Asset tracking – Track movements of machinery, expensive inventory, assets, robots, vehicles, etc. Workforce location – Real time location of personnel like doctors, supervisors, technicians, team members. No more public intercom announcements asking Dr. Smith to call the Emergency Room. Defense/Intelligence – Tracking team members and assets on missions, in the dark, or in crowded locations. Fire and Police - First Responder team tracking in crowded or dark locations. How does Indo[...]



How Facebook maximized the IPO proceeds, but botched the process

2012-08-22T08:39:59-04:00

Most companies leave a lot of money on the table when they IPO. They price at $12 to $15 per share at the IPO and trade up to $20 - $25 on the first day, and up to $30 to $40 over the next few months. Investors are happy. The...Most companies leave a lot of money on the table when they IPO. They price at $12 to $15 per share at the IPO and trade up to $20 - $25 on the first day, and up to $30 to $40 over the next few months. Investors are happy. The press is writing positive stories. Everyone is happy. But, the company left all that money on the table, the difference between the $12 IPO price and the $25 first day close. This can mean hundreds of millions of dollars for the company. Facebook optimized the value of the IPO to the company by pricing high, and brought in billions of dollars in cash. Facebook stock closed at $38 per share on the first day, and most of that cash went to Facebook. Great result for Facebook. They worked hard to find the share price where they could sell all the IPO shares at the highest possible price, and generate the most cash for the company. But, by doing so they disrupted the age old IPO process. Now investors are paying the price. Investors who bought the IPO shares thinking they would immediately go up 20% to 50% were sadly mistaken. In fact they have gone down 50%. The press is writing negative stories about how Facebook is declining, user growth is slowing, they don't have a good mobile strategy, and that monetization is awful. Facebook hasn't changed their strategy in the past few months...but public perception has changed. The original VC investors in Facebook, and employees who hold stock option grants are "locked up" and normally can't sell their shares until 6 months after the IPO. Normally there would be a Secondary Offering where they could sell their shares in an orderly fashion to institutional investors. This is why they call the first selling of stock the IPO (Initial Public Offering) and the second selling of stock "The Secondary Offering". Facebook also changed up this process by letting some investors sell some stock at the IPO, and letting other early investors and employees sell their stock after 2 months, or 3 months, or some other time period they stipulated. By doing so they kind of messed up the idea of a Secondary Offering because stock was dribbling out...actually, exploding out, in chunks over the first 6 months and beyond. The Secondary Offering is normally supposed to be done about 6 months after the IPO, in a very positive environment for the company. Because there are a limited number of shares sold at the IPO there is more demand for the stock than there is supply. This creates a hot competitive environment for the stock and the price goes steadily upward. Perfect time for a Secondary Offering of the "locked up" shares from early VC investors and employees.  Facebook essentially can't do a Secondary Offering now because the stock price has dropped so far, so fast, that institutional investors are worried. They just heard the Facebook IPO story a few months ago, and now everything looks bleak. The press is writing negative stories. Bad timing. Facebook stock is currently trading at around $19, and has declined to about half of its opening day IPO price of $38. The price could decline even further with the hundreds of millions of shares coming off "lock up" flooding the market over the next several months. Normally this is done in an organized Secondary Offering to institutional investors. Instead, in the current situation, it will be totally disorganized with shares coming out at odd times, and dumped on the market for retail investors and brave mutual fund managers. The flow of shares and price can't be controlled by the IPO investment bankers the way they would with a Secondary Offering. So, Facebook did a great job maximizing the value of the IPO cash procee[...]



Bill Gross IdeaLabs a different kind of incubator

2012-08-16T13:59:42-04:00

Bill Gross has started over 75 companies and invested in many more. Thirty five of his companies have been acquired and 8 have gone the IPO route. Some of those companies include; Goto.com, Overture, CitySearch, NetZero, Tickets.com, CarsDirect.com, Shopping.com, eToys, Compete, Picasa (acquired by Google), InsiderPages, WeddingChannel.com, eSolar, Duron Energy,...Bill Gross has started over 75 companies and invested in many more. Thirty five of his companies have been acquired and 8 have gone the IPO route. Some of those companies include; Goto.com, Overture, CitySearch, NetZero, Tickets.com, CarsDirect.com, Shopping.com, eToys, Compete, Picasa (acquired by Google), InsiderPages, WeddingChannel.com, eSolar, Duron Energy, dotTV, Desktop Factory, Evolution Robotics, and UberMedia. Bill started IdeaLabs in 1996, long before the idea of startup incubators was popular. You have to know Bill to understand why IdeaLabs was necessary. Bill has so many ideas, in so many different market segments, he couldn't possibly do them all himself. So, he started a lab, hired all the support people necessary to build companies, and hired entrepreneurs to build out his ideas.  Bill has started 75 companies, and wants to start more. The limiting factor? Not money. The limiting factor is finding entrepreneurs who want to join the team and build companies. Check out this interview with Bill Gross on my recent trip to IdeaLabs. frameborder="0" height="315" src="http://www.youtube.com/embed/oMyJ7G7c7eg" width="420">  IdeaLabs is located in Pasadena, California in a 45,000 s.f. building. There are 12 companies in the building now, and 25 companies in the IdeaLab portfolio. They include compaines in software, hardware, energy, advertising, ecommerce, robotics, and more. IdeaLab Infrastructure - Everything you need to start and build a company; Engineering, Designers, HR, Recruiters, Finance, Legal, PR, office admin, photo/video services, etc. If more than one company needs it...they buy it or staff it. Everything is done in house. They even have a machine shop to create custom hardware parts. IdeaLab Model - Start with an idea that is vetted by Bill Gross and his team of company builders. Prototype and test the idea using IdeaLab staff engineers. Conduct user tests. If everything looks good fund the idea with up to $250K. Assign a CEO from the lab, or recruit one from outside. Hire the founding team to build the MVP and get a beta version to market. At this point IdeaLabs may bring in VC investors, or they may decide to fund it themselves. IdeaLab synergy - At any given time there are 10 to 15 companies incubating at IdeaLabs. They range in size from 5 people to 50 people. When any company reaches 100 people they need to move out on their own. There are no competing companies in the portfolio so founders easily share information, advice, introductions, and help out on short term needs. Like other incubators, they bring in industry experts and successful founders for talks. Want to help start a company? - You could come up with an idea yourself, recruit a team, pay for it out of your own pocket, build an MVP prototype, and then try to raise money from investors. It is a tough process, even for those that have done it before. Or, you could join Bill Gross at IdeaLabs as a founder and help build a new company. The financial rewards are significant, and the risks are much lower. Not for everyone, but a great opportunity for the right person. Contact Bill Gross at IdeaLabs to find out more. Subscribe - To get an automatic feed of all future posts subscribe here, or to receive them via email go here and enter your email address in the box in the right column. You can also follow me on Twitter @dondodge and on Google+ [...]



Three reasons Microsoft will not buy Nokia at any price

2012-06-18T11:01:15-04:00

Nokia (NOK) stock price is dropping to historic lows with a current market cap of just $9.3 Billion. Nokia has revenues of over $38B, $6B in cash, 30,000 patents, and a great brand. Investors and sharks are circling. Microsoft (MSFT) isn't one of them. Why not? Three reasons; they don't...Nokia (NOK) stock price is dropping to historic lows with a current market cap of just $9.3 Billion. Nokia has revenues of over $38B, $6B in cash, 30,000 patents, and a great brand. Investors and sharks are circling. Microsoft (MSFT) isn't one of them. Why not? Three reasons; they don't want to, they don't need to, the FTC & EU regulators wouldn't let them...even if they wanted to. Techmeme thinks Microsoft might be getting into the hardware business, but not phones. Lets explore these three points. They don't want to - Microsoft has strong DNA as a partner driven company. The success of Windows was driven by thousands of hardware manufacturers and tens of thousands of software companies supporting Windows in their products. For more than 30 years this has been the business model. They view Windows Phone 7 just like Windows on the PC...an operating system platform for any hardware device. They just work with manufacturers and the money pours in. They don't want to mess with the model. It has been a great model, but it doesn't always work. Microsoft has always been the opposite of Apple (APPL). Microsoft makes software available to all manufacturers, while Apple is a closed system. For most of the past 30 years Microsoft had the better model. Not anymore. Apple has proven that a beautifully integrated (closed) system can be very attractive. Apple has DNA too. Apple products have always been integrated hardware and software. It has worked well for the Mac, iPod, iPhone, and iPad. Hmmm...maybe Apple will buy Nokia. Makes more sense than Microsoft, but I digress. Microsoft made one exception to the model I can think of, the Xbox. And that was only because they couldn't convince the game box makers to play nice with them, and because they didn't have any partners in this space. Microsoft spent billions developing the Xbox hardware platform just so they could sell their game software. Eventually, the bet paid off. And, in the future it could be a huge home computing platform if they could shake their legacy DNA. Not likely. Microsoft might enter the Tablet space. This would mark a change in strategy, and create huge channel conflict with partners. Smartphones are a huge market, and the future of personal computing. Microsoft is trying to use their Windows PC distribution model for Smartphones. It isn't working. Manufacturers who once used Windows Mobile have grown tired of the slow pace of innovation at Microsoft and high OEM prices. Many are now using Android. Microsoft responded by making a deal with Nokia, paying them billions of dollars for "marketing" and engineering transition costs. To date that isn't working very well either. Microsoft doesn't need to buy Nokia - Microsoft already gets everything they want from Nokia without buying them. Microsoft wanted distribution from a big brand Smartphone manufacturer. The idea was that other manufacturers would follow after Nokia blazed the trail with Windows Phone 7 and grabbed market share. Nokia was one of the few big manufacturers that hadn't committed to another OS. It was a reasonable strategy for both companies. It hasn't worked out yet, but it still might. The Xbox strategy didn't work in the first year either. These things take years and billions of dollars to execute. Microsoft has plenty of time and money. Nokia doesn't. The FTC and EU wouldn't let them - Almost any big acquisition by Microsoft, or any of the big players, will attract an FTC, EU, and even China review. We live in a world where government regulators decide, not t[...]