Tesla, software and disruption. A deeper look at Tesla’s business strategy and future. Is Tesla going to completely disrupt the car industry? Or will the incumbents learn to build software faster than Tesla can learn to make cars at scale? (Ben Evans, a16z)
Everybody Dance Now. “Do as I do” motion transfer facilitated by machine learning: given a source video of a person dancing, that performance can be transferred to a novel (amateur) target after only a few minutes of the target subject performing standard moves. (3-min video)
How Old Are Successful Tech Entrepreneurs? A person who is 40 is 2.1x as likely to found a successful startup as a person who is 25. The average founder who had a successful exit through an IPO or an acquisition is 46.7 years old. (Kellogg)
Amazon’s Facial Recognition Wrongly Identifies 28 Lawmakers, A.C.L.U. Says. ACLU used Amazon face recognition software, trained the model on a mugshot database and applied it to pictures of US congressmen. This led to some false positives — 28 members of Congress were identified as people who were arrested. The high false positive rate was mostly due to the low confidence threshold (80%) and the biased training set but the point that this technology can be misused is well taken. (NYT)
Mary Meeker’s 2018 internet trends report. Mobile growth stalled; people are spending more time online; voice interfaces are taking off. 11 of the world’s 20 biggest Internet companies are in the US. The rest are in China. (Recode)
Google I/O 2018 Keynote in 14-min. The announcement of Google Duplex and Smart Compose probably generated most fears excitement. Duplex allows Google Assistant to make calls on your behalf. Smart Compose auto-suggests email responses – paving the way for Yuval Harari’s dystopian vision.
Labor 2030: The Collision of Demographics, Automation, and Inequality. A very detailed report on the impact that automation might have on labor markets. 40M jobs might be eliminated in the US alone. The report offers no insight into the degree to which this loss will be (over)compensated by the creation of new job categories though. (Bain & Company)
Lessons from Spotify. Atypically for tech, Spotify’s marginal cost is not zero as it pays royalties. Since it’s hard to negotiate better rates with the music industry, Spotify will either need to tightly control operational costs or cut out the labels altogether – not a likely option. (Stratechery)
Twitter’s investigation of Russian interference in the US election. Twitter removed Russian government-linked accounts and emailed 678K people in the US who followed, retweeted or liked a tweet from these accounts during the election period. I’m glad social media companies start to accept more responsibility for how their platforms are used and abused.
Intercom on Marketing (ebook). A good intro to marketing and, in particular, product marketing that will be interesting to those who are relatively inexperienced.
How to Design Marketing Campaigns. Basics of marketing segmentation, messaging hierarchy, and campaign management – this article will be useful to those who’re new to marketing or looking for a refresher.
“What’s next in growth?” (video) talk by Andrew Chen who leads the rider growth at Uber. Andrew recommends you ignore “growth hacks” and focus on fundamentals that worked for decades. E.g. user referrals, shareable content, and using discounts to jumpstart demand for new products.
This is an issue of my monthly newsletter. Main topics: technology, startups, business growth, and marketing. See other issues on my blog or subscribe. ~Max
Technology and Startups
Ten-year Futures – a presentation by A16z. New technologies enable new use cases. Seeing them, as well as non-obvious “second order” effects, is key. E.g. mobile enabled Instagram, Instacart, and ride-sharing.
Decrypting Crypto – another presentation by A16z. Bitcoin is a combination of three old technologies: hashcash, public key cryptography, and distributed ledger. Value of cryptocurrencies goes beyond the traditional store of value and medium of exchange. E.g. tokens can help bootstrap new protocol-level innovation and incentivize developers, customers, and investors to contribute.
AlphaGo Zero masters the game of Go from scratch. The ML algorithm learned the game without any pre-existing understanding of rules or strategies. Building a general or at least a-little-bit-less-narrow AI appears to be a big priority for DeepMind. Perhaps this can count as a small step in this direction?
Tacotron 2 is a new text-to-speech technology by Google that is (almost?) indistinguishable from a human voice. If Google manages to make it less computationally demanding and ship it as part of the Android OS, all kinds of interesting use cases will be made possible. I personally will listen to more of my Pocket articles in audio.
Magic Leap is launching its SDK, shipping in 2018. AR/VR is already quite a saturated market. It’s not entirely clear yet how hyped Magic Leap technology will compare to Microsoft HoloLens, as well as to VR headsets: HTC Vive and Oculus Rift.
I just wanted to share these two very well-done and informative primers on AI and quantum computing by A16z. The latter one made a bit less ignorant about the topic. The former one is rather basic but still interesting.
“Kurzweil then takes things a huge leap further. He believes that artificial materials will be integrated into the body more and more as time goes on. First, organs could be replaced by super-advanced machine versions that would run forever and never fail. Then he believes we could begin to redesign the body—things like replacing red blood cells with perfected red blood cell nanobots who could power their own movement, eliminating the need for a heart at all. He even gets to the brain and believes we’ll enhance our brain activities to the point where humans will be able to think billions of times faster than they do now and access outside information because the artificial additions to the brain will be able to communicate with all the info in the cloud.”