Writing in the London Review of Books, Rebecca Solnit expresses her discontent at the unstable housing market in San Francisco, driven by new money from the tech boom (Google, Facebook, etc.):
At the actual open houses, dozens of people who looked like students would show up with chequebooks and sheaves of resumés and other documents and pack the house, literally: it was like a cross between being at a rock concert without a band and the Hotel Rwanda. There were rumours that these young people were starting bidding wars, offering a year’s rent in advance, offering far more than was being asked. These rumours were confirmed. Evictions went back up the way they did during the dot-com bubble. Most renters have considerable protection from both rent hikes and evictions in San Francisco, but there are ways around the latter, ways that often lead to pitched legal battles, and sometimes illegal ones. Owners have the right to evict a tenant to occupy the apartment itself (a right often abused; an evicted friend of mine found a new home next door to his former landlord and is watching with an eagle eye to see if the guy really dwells there for the requisite three years). Statewide, the Ellis Act allows landlords to evict all tenants and remove the property from the rental market, a manoeuvre often deployed to convert a property to flats for sale. As for rent control, it makes many landlords restless with stable tenants, since you can charge anything you like on a vacant apartment – and they do.
A Latino who has been an important cultural figure for forty years is being evicted while his wife undergoes chemotherapy. One of San Francisco’s most distinguished poets, a recent candidate for the city’s poet laureate, is being evicted after 35 years in his apartment and his whole adult life here: whether he will claw his way onto a much humbler perch or be exiled to another town remains to be seen, as does the fate of a city that poets can’t afford. His building, full of renters for most or all of the past century, including a notable documentary filmmaker, will be turned into flats for sale. A few miles away, friends of friends were evicted after twenty years in their home by two Google attorneys, a gay couple who moved into two separate units in order to maximise their owner-move-in rights. Rental prices rose between 10 and 135 per cent over the past year in San Francisco’s various neighbourhoods, though thanks to rent control a lot of San Franciscans were paying far below market rates even before the boom – which makes adjusting to the new market rate even harder. Two much-loved used bookstores are also being evicted by landlords looking for more money; 16 restaurants opened last year in their vicinity. On the waterfront, Larry Ellison, the owner of Oracle and the world’s sixth richest man, has been allowed to take control of three city piers for 75 years in return for fixing them up in time for the 2013 America’s Cup; he will evict dozens of small waterfront businesses as part of the deal.
Evictions, foreclosures, and legal loopholes. This doesn’t sound like a city I’d want to inhabit. A must-read for perspective.
Aria Haghighi, co-founder of the app Prismatic, discusses his decision to leave academia in this blog post. Aria holds a Ph.D. in Computer Science from UC Berkeley and a BS in Mathematics, and his area of focus was Natural Language Programming. It’s an interesting thought process:
At some point while at MIT, I decided to leave and do a startup because I felt my work as an academic wasn’t going to have the impact I wanted it to have. I went into academic CS in order to design NLP models which would become the basis of mainstream consumer products. I left because that path from research to product rarely works, and when it does it’s because a company is built with research at its core (think Google). This wasn’t a sudden realization, but one I had stewed on after observing academia and industry for years.
During grad school, I did a lot of consulting for ‘data startups’ (before ‘big data’ was a thing) and consistently ran into the same story: smart founders, usually not technical, have some idea that involves NLP or ML and they come to me to just ‘hammer out a model’ for them as a contractor. I would spend a few hours trying to get concrete about the problem they want to solve and then explain why the NLP they want is incredibly hard and charitably years away from being feasible; even then they’d need a team of good NLP people to make it happen, not me explaining ML to their engineers on the board a few hours a week. Useable fine-grained sentiment analysis is not going to be solved as a side project.
And his thoughts on making this tough decision:
Nearly two years later, after a lot of learning about industry and making real products, I can confidently say that I’m happy I left academia. Prismatic is a pretty tight realization of how I would’ve wanted NLP and ML to work in a startup and manifest in product. The relationship is symbiotic: the machine learning and technology is informing possibilities for the product, and conversely product needs are yielding interesting research. Various pieces of the machine learning (like the topics in a topic model) are first-class product elements. Many of the more ambitious NLP ideas I thought about during grad school will become first-class aspects of the product over the next few years.
Before you go out and buy that Facebook stock when it IPOs today, consider the warnings. There are plenty of opinions out there. But the best consideration of the whole matter I have read in the last two weeks comes courtesy of Chris Dixon, who considers Facebook’s business model. Namely: display ads. Display ads generally hurt the user experience, and are also not very efficient at producing revenues. The crux of the matter:
The key question when trying to value Facebook’s stock is: can they find another business model that generates significantly more revenue per user without hurting the user experience? (And can they do that in an increasingly mobile world where display ads have been even less effective.) Perhaps that business model is sponsored feed entries, as Facebook seems to be hoping (along with Twitter and perhaps Tumblr). The jury is still out on that model. Personally, I have trouble seeing how insertions into the feeds aren’t just more prominent display ads. You still have to stoke demand and convert people from non-purchasing to purchasing intents. A more likely outcome is that Facebook uses their assets – a vast number of extremely engaged users, it’s social graph, Facebook Connect – to monetize through another business model. If they do that, the company is probably worth a lot more than the expected $100B IPO valuation. If they don’t, it’s probably worth a lot less.
Chris’s short post is worth reading in entirety.