Hi Trevor and Jared,<p>My startup is developing technology for natural language understanding (in contrast to NLP). We believe we can approach human-level understanding for standard texts (email, blogs, online articles) in 2.5-4 years.<p>We are currently self-funded and can comfortably do so for about a year--by the end of which, we believe we can develop a fairly advanced demo that surpasses existing techs in some, but not all, areas.<p>What kind of demos do you think would impress best-in-class recruits&#x2F;investors to join our team?  The current options we have in mind are:<p>1) Solving a subset of Winograd schema (commonsense reasoning challenge) with a general approach (i.e., easily extensible with additional investment in knowledge acquisition&#x2F;data sources). No systems known to public can currently solve all of them (or even a subset generally).<p><a href="http:&#x2F;&#x2F;commonsensereasoning.org&#x2F;winograd.html" rel="nofollow">http:&#x2F;&#x2F;commonsensereasoning.org&#x2F;winograd.html</a><p>2) A conversational agent capable of conversing with humans at the level of a 4- or 5-year-old (without resorting to typical chatbot tricks).<p>3) Surpassing the state-of-the-art systems in a couple of standard AI conference tasks or on datasets released by leading companies (Google, Facebook, etc).<p>4) Other tasks we have not thought of...<p>Because of resource and time limitations, we likely need to focus the initial efforts on one, or at most two, of the options above. (A mature system should be able to do all those and beyond, but this is only for about one year from now.)<p>A couple extra questions if you have the time:<p>- Given the startup&#x27;s long-term timescale before monetization and its technical nature, what sorts of investors should we focus on talking with?<p>- Are there chances of IP leaking and causing problems with patenting our tech later on? What should we do to prevent that?<p>Sincerely appreciate your time to answer these questions.<p>-- Ken Noppadon