We just held our latest virtual “pitch+learn” event where we showcase a small selection of very early-stage software startups (alpha-version product, generally only limited/early revenue) from a backlog of spontaneous submissions, as well as sourced by the Badhouse team. Today’s theme was, very broadly, applications of AI. We heard from founders about products ranging from a system for AI-assisted content marketing, to AI to help home builders optimize between cost and energy efficiency, a chatbot for employee engagement, and machine vision for tracking eggs. (Yes, 🥚!)
Post pitches, during judge deliberation, we welcomed guest speaker Annika Lewis (from Vanedge Capital…
A growing number of people are curious to see how much and what type of data the so-called “Big Four”, aka GAFA (Google, Apple, Facebook, Amazon), hold about them. Here’s a super-short, no-nonsense guide of where to go to request all the data accumulated about you by each of these companies. Note that these steps are to be followed from a desktop web browser, as some links will not work from a mobile browser.
Last month, for our June 2020 edition of the Badhouse Ventures “Provocative Startup Stories” pitch+learn event series, we focused on the themes of B2C and social. The finalists pitching were showcasing alpha-stage products ranging from a matchmaking site to connect female apprentices with mentors, a next-generation service looking to disrupt Meetup, a social game discovery platform, and a hybrid Instagram-TikTok app helping anyone become a micro-influencer and connect with local businesses for paid gigs.
For the “learning” portion of the evening (held while the judges were deliberating on the pitch winner), we invited our friend Benjamin Watson to share some of the marketing wisdom he’s accumulated from his time as a product marketing leader at Hootsuite, Yahoo, and Microsoft. Here’s the recording of his talk and the subsequent Q&A.
Since the early days of the COVID-19 pandemic we’ve been running online pitch events for early-stage startups, striving to combine interesting software-focused startups with experienced judges (e.g., ex-founders, like Eric Ly, co-founder of LinkedIn, VCs from around the world, angel investors in North America, and corporate innovation leaders). To fill the time while judges go offline to deliberate on a session's winner, we hold an informal learning session, led by a different subject-matter expert each time, on a topic of interest to most early-stage startup founders and investors.
If you work in venture finance, or are an investor yourself, you’ve certainly heard of the expression du jour echoing through wine and cheese events near you: Impact investing. Behind the hype, it’s simply an extension of the older concept of socially responsible investing (avoiding to invest in ventures that generate external negative effects) combined with a commitment to measuring non-financial outcomes, be it social or environmental performance.
Typically, the “investors” actively involved in impact investing are either non-profit bodies (often, quasi-autonomous non-governmental organizations), originate from the corporate social responsibility initiatives of large corporations, or are purposely-constituted investment funds with…
What’s the point of generalized, on by default, “breaking news” notifications in most news apps?
Having recently installed a few apps from popular news outlets on my iPad, I quickly noticed a plethora of “breaking news” notifications piling up. Unless there’s an imminent natural disaster (seek shelter!) or incoming intercontinental ballistic missile (make your final goodbyes!), nothing is that important and needs to be communicated to the average person, at that very instant.
On a tablet, it’s even more pointless; the notifications pile up and by the time one notices them, they represent old news.
Unless you’re a political consultant…
True “full” anonymization, some argue, is impossible; it’s all relative, as a perfectly anonymized dataset has no utility for analysis. A good way to measure the level of privacy-protection afforded by an anonymization scheme is to try to work backwards, trying to see if given a set of data, it can be associated back to its source, such as re-identifying the person that is described by the data.
This is exactly what a group of researchers in Europe have tried to do, but on a larger scale. …
Yesterday, I setup and switched “on” my first public blockchain node. It was not that complicated, nor was it expensive. One thing I did notice, however, was that existing how-to guides that I came across, outside of those explaining how to use prepackaged binary images on desktop Windows/Mac machines, were lacking some basic system setup details (even a basic thing like making sure the node recovers from a system reboot). This is why I’m writing this, to provide a full A to Z, step-by-step recipe that anyone can follow, even if you don’t have any experience in Linux system administration.