
In a rare guest post on TechCrunch, the genius behind Sun Microsystems and Khosla Ventures (Vinod Khosla ), shared his most favorite investment areas. Here is a TL:DR version:
1. Data Reduction or Filters (Siri, Donna, Recorded Future, and many others): “Reducing, filtering and processing data streams to deliver the information or action that is relevant to you.” The web has been expanding what we have access to. It is time for tools (our proxies or agents on the web) to start reducing the amount of information coming at us. News or article feeds, TV shows, YouTube, “must watch” emails — these can all be prioritized for us like our proxy was a virtual assistant who knows our current context and our preferences. Even serendipitous feeds will have a higher probability of being interesting.
2. Big data or Analytics (Ness, Billguard, The Climate Corporation, Kaggle, Datasift): “Analyzing massive amounts of structured and unstructured data to deliver unique services or analysis.” Per the OATV website, so many of the most transformative applications today rely on massive cloud databases — often generated by user participation — with meaning extracted from that data by predictive analytics and powerful machine-learning algorithms. We see the back-ends of many of these applications becoming the functional equivalents of subsystems in a kind of internet-scale operating system driving not just the web but mobile devices. Location, social networks, identity, and personalization are just the tip of the iceberg.
3. Emotion (Foodspotting, Ness, Instagram): “Services that evoke strong emotions in users,” which is often a component of other categories, can also be enough of a driver to be mentioned separately. I include here the applications that because of their emotional appeal are adopted more rapidly or easily (more pull from users than push to them) as a major component of the application.
4. Education 2.0 (it’s early, but Altius, Khan Academy, CK12, Udacity): “Education models that dramatically reduce the cost and increase the availability of quality learning.” The puzzling question is why education has not already changed. My guess is we have not experimented enough with non-linear, rapidly evolving, out-of-the-box approaches but have instead tried to force-fit ‘multi-media textbooks’ and other traditional (often broken) ideas into the “computerized” model.
5. TV 2.0 (Miso, Flingo, Maker Studios, both first and second screen apps as well as content production & sourcing): “TV as an interactive and social experience both on the primary and the second screen.” Most U.S. Internet users, I am told now, have a second screen in front of them when watching TV. Whether it is true or not, it soon will be, and the interaction that is possible will allow for all kinds of creativity and user engagement shows/applications/techniques. More importantly, program production, be it video for TV, audio for radio, or text for next-generation news formats (tomorrow’s “newspapers”?) could be crowdsourced or gamified.
6. Social Next (intersecting with all the interest graph stuff and verticals like Github, Coursekit, and Researchgate): “Social as a useful and productive part of lives—enabling collaboration and deep community building around the world in specific areas.” I include here new uses of social such as Github to do a cooperative task or the kind of social learning Coursekit and others are trying to encourage. I suspect we will see the power of social harnessed for many applications beyond just the Facebook friends network or the Google+ circles implementation.
7. Interest-based networks (where Meebo is pivoting to, Twitter, Snip.it, State): “User driven content that maps to people’s interests both for a better user experience and better targeting.” I was impressed by a post by Naval Ravikant and Adam Rifkin on interest graphs and why they are different from social graphs. I do think a number of startups will either target interest graphs to create a network different from Facebook’s and others will use these graphs as monetization strategies.
8. Health 2.0 (Jawbone UP, Nike Fuelband, Empatica, BodyMedia, MC10, Fitbit, iBike, Recon, Withings, Alivecor): “Exponentially growing data will yield personalized lifestyle suggestions, improved outcomes, predictive diagnostics and applications we can’t imagine.” Health applications will flourish in many directions and are laid out in a separate post. From more data (especially more baseline, or “healthy” data), “health”-care instead of “sick”-care, more DNA and proteomics data, to mobile-based “second opinions” substituting for doctors and more traditional health systems, we will see an influx of non-sick status data and applications leading to what is called the Quantified Self.
9. Internet of Things/Universal ID/NFC/Smart sensors (a technology with the applications still to emerge): “Sensors and authentication technologies which will interconnect everything and remake our interaction with the world around us.” Sensor networks aren’t just for cargo containers anymore. Sensors have found their way into every aspect of our lives — whether it’s the phone in our pocket, the digital photo frames on our desks or the barcodes embedded with information in our local grocery stores, often complemented by NFC, Bluetooth LE, Wi-Fi and other networks.
10. Personal Collaborative Publishing (Pinterest, Tumblr, storify, Snip.it): “Truly free press with no barriers to entry and personalized interest-based curation.” This trend seems to be moving forward fairly rapidly. I’m not sure if it will become more or less verticalized or what new dimensions will emerge but the potential clearly remains promising. Self-publishing on Amazon is becoming real.
11. Utility Apps (Siri, Seatme, Ifttt, Uber, and many, many more): “Leverage device ubiquity and context to deliver valuable services.” It goes without saying that we will continue to see more and more utilities that are just plain helpful to us. I do wonder how many major new categories of utilities there will be. Ideas anyone, for major new categories? Utilities will provide personal assistance, productivity and maybe even decentralized work (new clones of Mechanical Turk or Skype!). They will aggregate experts into marketplaces (see below) or crowdsourced services or just plain telemedicine and remote reading of your radiology scans (yes it is hard to separate any of these applications into clean areas – overlap is inevitable).
12. Marketplaces & Disintermediation (Interview Street, Kaggle, Etsy): “Remove the middle man, increase market efficiency and produce better results, faster“ Marketplaces are about economic efficiency (and active engagement) and more and more of them will keep emerging. My favorite new marketplace is Kaggle, where 13,000 data scientists can compete with their talents and the best ones can benchmark themselves and hopefully get paid accordingly.
Read the whole post here: