Infoman

Member since 2017-07-15T03:50:57Z. Last seen 2025-04-09T16:00:01Z.

2754 blog posts. 128 comments.

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Posts by Infoman

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  Infoman

  It’s About Time for Time Series Databases

  107 okket 2 hrs 27

  https://www.nextplatform.com/2018/01/25/time-time-series-databases/

  news.ycombinator.com/item?id=16230464 January 25, 2018 Timothy Prickett Morgan

  To get straight to the point: nobody wants to have large grain snapshots of data for any dataset that is actually comprised of a continuous stream of data points. With the data storage and stream processing now so cost-effective (relatively speaking, of course) that anybody can do it – not just national security agencies or hedge funds and brokerages with big budgets – there is pent up demand for a SQL-friendly time series database.

  So that is what the founders of Timescale set out to create. And while they are by no means alone in this market, the open source TimescaleDB that they let loose on the world last summer is getting traction and on the rise, in part because of the growing popularity of the PostgreSQL database engine that it overlays with time series capabilities and enhanced scalability.

  The hyperscalers have had databases that, to varying degrees, offer time series data storage and analysis as well as SQL capabilities and ACID properties, the most notable ones being the Spanner database from Google and its open source clone, CockroachDB. There are dozens of time series databases out there, the majority of which are listed or commented on here, and the kdb+ database from Kx Systems is probably the most widely used commercial time series database installed, particularly within the trading systems of financial services firms. The kdb+ database is popular because of its wickedly fast performance, for which companies pay a premium, and Timescale is not trying to take on Kx Systems directly in this core market. In fact, company co-founders Ajay Kulkarni and Mike Freedman, who were roommates at MIT two decades ago before their paths diverged and then reconverged, tell The Next Platform that they were aiming the TimescaleDB database at machine-to-machine applications but have seen early adopters use it in a number of more traditional applications, where enterprises have added time series data to traditional databases like Oracle’s eponymous database or Microsoft SQL Server or are replacing scale out clusters running the open source Redis, Cassandra, or Riak key-value stores or their commercial variants.

  Both Kulkarni, who is Timescale’s CEO, and Freedman, who is the CTO, are serial entrepreneurs, but Freedman is notable in that he was on the Stanford University team that created the Ethane programmable network architecture that resulted in the OpenFlow software defined networking protocol that has been commercialized in various forms; he also created the CoralCDN decentralized content management system that was popular in the early days of the Web in the early 2000s, and has been a professor of computer science at Princeton University since 2007 as his other day job.

  The two Timescale founders believe, like the rest of us, that computing comes in waves, starting with mainframes and then Unix systems and then X86 servers in the datacenter and PCs and laptops and smartphones on the desktop or in our hands, and with every leap in technology, the computers get more powerful and more useful and they generate and process more data.

  “It used to be a PC on every desktop, and then a smartphone in every pocket, and now we are entering a new phase where there is a computer in every thing, whether it is our vehicles or manufacturing lines, power plants, homes, and even our bodies,” explains Kulkarni. “We have gotten to this point where we are living with all of these machines, and businesses are swimming in machine data. The key insight we had is that no database was ready for this challenge.”

  The natural question here is: Why not? There are plenty of time series databases (or extensions to them) in the market, as we pointed out above. But it turns out that machine data is unique in that it is generated at very high volumes and it also needs to be analyzed in complex ways and usually very quickly and generally very reliably. (The eventual consistency of NoSQL datastores like Cassandra does not pass the ACID test of relational databases, which enterprises are used to.) It is one thing to use a database for consumer mobile apps, but quite another to use one to monitor and manage a nuclear power plant.

  “Back in 2014, when we started, developers have essentially two choices,” Kulkarni continues. “They could use relational databases with SQL interfaces, which are easy to use but they don’t scale well. Or they could use NoSQL databases that scale well but were not as reliable and are harder to use. The choice between reliability and scalability was a terrible choice, and we also realized that machine data, for them most part, was time series data. It is a timestamp, some data, and some metadata around the measurement of the device.”

  With Timescale, the idea is to reverse that terrible choice and get the reliability and SQL interface of a relational database with the speed and scalability of a NoSQL database. The important thing is that most time series data is immutable and is appended to the existing data – you don’t change it and it is tacked on in the order that events happen. This is distinct from relational databases that do online transaction processing, where rows in databases are updated as the transactions are run and more or less randomly; taking an order for an existing customer, for instance, updates the customer table to add items purchased and also updates the inventory table to show that they are no longer available for sale.

  Instead of building this time series database from scratch, Timescale created an overlay on top of PostgreSQL database engine, leaving the backend engine that stores information on disks the same and allowing for all of the tools that speak to PostgreSQL to keep doing what they are doing. To be more technical, Timescale takes over the front end of the engine, taking in a query and rewrite it, doing its own query planning and execution against that engine, which is tweaked to support an abstraction layer that Timescale calls a hypertable. (This is in contrast with the MySQL open source relational database, which has a thin compatibility layer that sits on top of many different styles of storage engines.)

  The hypertable shards data into chunks, and the chunk size is set either by the database or manually to provide good performance for transactions. The chunks are carved into the data stream based on time interval and by other columns stored in each chunk – tick data for stocks, customer location for Uber, closest cell tower for an iPhone – and each server node can have a hypertable abstracting across tens of thousands of chunks that are spread across many disk or flash drives to scale out capacity. The indexes for the chunks are stored in memory for fast scanning, and Timescale has come up with what it calls “aggressive” low level distributed query optimizations to limit the number of chunks accessed to answer a query and therefore boost performance.

  “We don’t muck around with how the data is stored on disk, and therefore we inherit all of the reliability of PostgreSQL,” explains Freedman. “We also enforce the same PostgreSQL interface, so all of the tooling for this database works with TimescaleDB. They part is in the middle is that we have figured out how to scale PostgreSQL for time series data, and we are 20X faster at inserts than PostgreSQL. And we are 10X faster than Cassandra, and unlike Cassandra, we also support full SQL.”

  This is a neat trick, and that, in part, explains how TimescaleDB is a rising star on GitHub and why the database has been downloaded over 100,000 times since it was launched last April and rolled out over the summer.

  At the moment, TimescaleDB is an example of what we call a scale in product, meaning that it can replace either a big scale up system, like a NUMA machine, or scale out system, like a cluster of distributed systems sharing work in a looser fashion, without needing to scale beyond a single node. At the moment, TimescaleDB is being used for fairly modest workloads, replacing systems that might have a dozen or so nodes running Cassandra or Redis with a single server that has JBODs and JBOFs for disk and flash scalability in those nodes. On such machines, the queries on time series data on a single node of TimescaleDB are running anywhere from 10X to 50X faster than on the modestly sized Redis and Cassandra clusters, and inserts of new data are around 10X faster. In the next year or so, Timescale will have a scale out version of its own for those who have larger workloads.

  “Our initial goal is not to build the kind of scale that Google needs,” says Freedman. “But we certainly want to scale out to ten, twenty, or forty nodes with sustained performance of millions of inserts per second and petabyte scale storage.”

  The current product supports around 100 TB of time series data on a single node, with more than 10 billion rows of data, and it can do between 100,000 and 200,000 inserts per second. The software allows for the elastic attachment of additional storage on a single server node, which means it does not have to be brought down to add capacity. The database is supported on Linux, Windows Server, and MacOS platforms, although there are no real commercial MacOS servers so it almost doesn’t count. (Pity, that.)

  Here is how TimescaleDB stacks up against the real PostgreSQL 10 database with inserts on a single row:

  And here is how it looks against PostgreSQL with 1,000 rows:

  The TimescaleDB software is available with an Apache 2.0 license as an open source package that includes the PostgreSQL engine. Timescale is crafting an enterprise version, which has additional governance and security features and that will likely also include the scale out extensions when they become available. Pricing has not been set yet, but it is fairly likely that the cost will be per node and fall somewhere between generic Hadoop storage and the Oracle database. (Yes, that was meant to be funny in that this is anywhere from thousands to many hundreds of thousands of dollars per node.)

  Now that things are humming along, Timescale’s founders are copping to the fact that they had already raised $3.7 million in seed funding, including investments from Spender Kimball, one of the founders of Cockroach Labs, and Rob Bearden, the CEO at Hadoop distributor Hortonworks and who used to run the SpringSource and JBoss businesses before they were sold to VMware and Red Hat, respectively. And just now, Timescale has raised $12.4 million in Series A funding, which was by Benchmark with participation from New Enterprise Associates and Two Sigma Ventures. So that is a tidy $16.1 million to help get that scale out version of TimescaleDB done and to scale up the marketing, sales, and technical staff.

  Categories: Compute, Enterprise, Store

  Tags: Database, PostgreSQL, relational, SQL, time series, Timescale, TimescaleDB

  Energy Giant Eni Starts Investing In Supercomputers Again

  2018/01/25
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  Infoman

  Python send/receive message with Whatsapp

  https://github.com/tgalal/yowsup

  2018/01/25
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  Infoman

  API backend : python

  Web backend : nodejs

  Web frontend : vuejs

  Ios : swift objective c

  Android

  2018/01/25
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  Infoman

  Tech in Asia Startup Event 2018

  What startup exhibitors said about TIA Singapore 2017 (INFOGRAPHIC) 5Comments Jia XinJia Xin Lim 2:48 PM at Jan 23, 20183 min read 54 Many businesses have moved their marketing efforts online, meaning the digital landscape has become increasingly crowded and competitive. Beyond having an online presence, engaging your users offline should be key as well.

  One-on-one interactions at live events is one way to achieve that – and is often crucial to building relationships with users as intangibles such as body language and tone of voice can easily be lost in online engagements. Ultimately, nothing beats connecting with your potential users face-to-face.

  If you’re looking to start the new year right by getting some much needed face-time with your potential customers and investors, here’s just the opportunity for you – Startup Factory, where you can showcase your product in front of 5,000 tech fans at Tech in Asia Singapore 2018 this May 15 & 16.

  Here are some facts and figures about our exhibiting startups from last year at Tech in Asia Singapore 2017. Don’t just hear it from us, listen to what they’ve got to say about their experience!

  (Click to view enlarged image) TIA SG 2018 - startup factory infographic

  Here’s your chance for your startup to shine Looking for the next big offline event for your budding startup to participate in? Here’s your chance to showcase your products to over 5,000 tech fans at Tech in Asia Singapore 2018 this May 15 & 16. You’ll get constructive feedback from users, establish business opportunities, meet prospective customers, and even secure funding from potential investors at our signature conference – all at one place.

  Applications for Startup Factory (previously known as Bootstrap Alley) are now open. If you’re a startup with less than US$3 million in external funds raised and have a working prototype, we would love to have you join us!

  Apply before January 31 to score 30 percent off (equivalent to US$179) your booth package. Slots are only limited to the first 250 startups, so sign up early to secure your booth. You can also check out our FAQ page for more information about Startup Factory.

  get your booth today Each startup exhibition booth package costs US$597 before discount, and comes with a one-day exhibition booth plus two exhibitor passes.

  Don’t miss out on the action! Not yet ready for Startup Factory but don’t want to miss out on all that’s happening? You can get in on the action with a conference pass, which gives you access to check out exhibiting startups at Startup Factory, soak in plenty of insights at our six content stages, attend networking parties, and more.

  For a limited time only, secure your passes to Tech in Asia Singapore 2018 at an unbeatable 1-for-1 discount. Simply register your details by January 31 – it won’t take longer than a minute!

  Never miss a story. Sign up for an account and get the latest & best stories in your inbox, every day.

  Sign me up! Editing by Cheong Hui Min (And yes, we’re serious about ethics and transparency. More information here.) Filed under: Conference, Events

  2018/01/25
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  Infoman

  mobile users, China is an extremely exciting market for app developers and marketers. According to digital advertising platform Smaato, China saw a 90 percent growth in mobile ad spend between Q1 2016 and Q1 2017, the highest rate in the world.

  That said, it’s important to understand that all things mobile work quite differently in China than the rest of the world, with one-of-a-kind challenges and huge opportunities. For any businesses looking to enter the country this year, take note of the following tips.

  A different Android animal While iOS works more or less the same way in China as elsewhere, Android is far more complex.

  In China, Android has over 300 different app stores and traffic sources, as opposed to the more standardized Google Play. App developers then need to generate different app install files (Android Package Kit or APK) and set up custom events for each store. It is relatively easy to modify a single piece of code, but it is still a lot of work—much more work than marketers and app developers would experience in other markets.

  Globally, the store is the point of sale and the media stands as marketing catalyst. In China, however, each app store drives all of its own marketing activities.

  Releasing to a single app store is not an option–unless the app has a strong brand–as they lack reach.

  Hands on As foreigners, launching campaigns in China is a challenging endeavor due to the language barrier, cultural differences, and a complex ecosystem. So, here’s how you can up your chances of experiencing early success.

  1. Find the right local partner The first step begins with finding a reliable local agency to work with. These agencies include but not limited to:

  Local companies that can handle the complex Android market and manage Android package updates Experienced media buying companies Local media sources (build direct connections with media giants such as Tencent and Baidu) For gaming apps, agencies that specialize in gaming that can take care of ongoing optimization, local integration, and bureaucracies (you may partner up via a revenue-sharing model) 2. Overcome bureaucracy Non-gaming apps do not require pre-evaluation other than the standard app store screening. However, due to the rampant game piracy in the country, Chinese authorities are very strict when it comes to releasing new gaming apps.

  This is what you will need to do to launch an iOS/Android game in China:

  Set up a local entity. Fill out the required forms. Load your game onto a smartphone and send it to the authorities. If mobile content is found to be appropriate for Chinese citizens, the game will be issued a publication number. This process can take up to three months.

  For iOS, Apple China and the government have agreed to put the requirement for publication number on hold. With that, it is likely that this will change and that app store rules will eventually apply to the App Store. It might be better then to be proactive and start acquiring a publication number for iOS games so marketers will have their bases covered when it becomes mandatory.

  1. Localize and monetize your app Strike the balance between respecting local syntax, terminology, and context while remaining true to the message of your brand. It is important to translate all content, otherwise your app may be removed from stores.

  Note that the Chinese language has two writing systems: simplified Chinese (used in China and Singapore) and traditional Chinese (used in Hong Kong and Taiwan). If your app has voice messages, opt for Mandarin, as it is the official language in both China and Taiwan.

  In terms of app monetization, subscription-based and paid apps are rarely used in China. Instead, here are the dominant revenue models:

  In-app purchases

  The 70-30 revenue share in the App Store is the same globally. It is more complex on Android, as integrated billing within the Google Play does not apply in China. Instead, there are local options, including WeChat Pay and Alipay.

  Non-gaming apps can integrate with the payment method of their choice. But for gaming apps, developers need to embed the payment SDK from each third-party store. The stores will then evaluate your app, and if they believe it has potential, it will be promoted via an in-app revenue share model (usually with a 50-50 split). In this case, app marketers (or their local agency) will manage traffic directly with the app store.

  Ad revenue monetization

  This is a popular method of generating revenue from in-app advertisements, which is similar to the global market for iOS. On Android, different app stores may have different policies regarding the uploading of APK files with an ad’s SDK. Some stores will only allow developers to embed their own ad’s SDK that is already integrated with many other third-party ad networks’ SDK. Failing to do so will likely lead to the app’s rejection in stores.

  1. Consider the user experience and connectivity Connectivity in China can be a potential issue for foreign app businesses due to:

  The great firewall of China: The Chinese government imposes restrictions on foreign websites and networks. Poor infrastructure: Although there is constant improvement in this area, the average cellular network and ISP quality in China still need improvement. The sheer size of the country also means that standardizing the infrastructure will take a long time. The physical distance between servers of foreign companies and end users across China. On a campaign level, the click-to-landing page performance can be significantly improved by connecting to a content delivery network (CDN) service with local servers. It is vital that your attribution provider has this set up to ensure that users who click on ads experience minimal waiting times.

  On an analytics dashboard level, it is important to understand whether your provider has separated the bundles between the third-party UI code and their own application code. Bundling both will result in a significant slowdown. What you can do is cache the third-party code in a user’s browser upon first visit, and then only call the constantly changing application code on subsequent events. This can dramatically reduce the loading time.

  ---

  The opportunities China offers clearly outweigh the challenges. By educating yourself, studying the landscape, and preparing accordingly, you can greatly increase your chances of growing your mobile business in the world’s largest mobile-first market.

  Never miss a story. Sign up for an account and get the latest & best stories in your inbox, every day.

  Sign me up! Editing by Charmaine de Lazo (And yes, we’re serious about ethics and transparency. More information here.) Filed under: Asia, Community, Mobile,

  2018/01/25
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  Infoman

  Why we transitioned from Medium back to our own blog

  262 uptown 6 hrs 157

  https://baremetrics.com/blog/medium-back-to-blog

  news.ycombinator.com/item?id=16223537

  Where to publish something has becoming a difficult decision for a lot of businesses. You read so many stories about using various channels to distribute content and grow traffic, it’s hard to know what does and doesn’t work. Medium, in particular, has become a major player in the world of startup content, but is it really that great?

  I’ve certainly been tempted by the prospect of loads of traffic and tons of likes (or “fans” as Medium calls them now). But how does that translate in to something meaningful for the business?

  This is our story of how we’ve used Medium, what worked, what didn’t and what our strategy is now, after kicking the proverbial tires for a couple of years.

  Growing with content marketing

  Before Baremetrics, at previous companies I’d started, I’d dabbled in content marketing. But not the quality stuff…the mass-produced, pay-somebody-$20-to-knock-out-500-words-around-a-random-SEO-keyword kind of stuff. As you can imagine, I got nothing out of it. Totally worthless, across the board.

  So when I started Baremetrics, I knew I wanted to do things differently.

  My first step towards this actually started before I even launched Baremetrics. I live-tweeted a lot of the process of getting Baremetrics launched and was very open from the start with how the business was doing.

  Early on I decided to make “transparency” a core part of the business, both in how we operated and also our strategy around marketing. Three months after launching, I made all of our numbers public, and from then on just started sharing everything I could think of.

  That was my entire content marketing strategy early on: share it all.

  That stance really helped grow the blog pretty quickly. I was publishing weekly about all the things I was trying and it got quite a bit of momentum, making the blog a place people checked regularly and came to expect new content from each week.

  Then came Medium

  About two years in, I found myself reading a ton of content on Medium and various businesses were moving their publications to Medium (the most prominent of which, in my mind, was Basecamp’s Signal v. Noise).

  I’d pumped out dozens and dozens of articles on our own blog to pretty great success, but Medium started looking like some really green grass on the other side. Not just from the “Ooooo, traffic!” prospect, but Medium also has a pretty active community, and I selfishly wanted the endorphin rush.

  I wasn’t really sure how to approach it. Should we wholesale move over every article from our blog to Medium? Do we post new content to Medium and repost to our own blog later? How would we even technically handle that from an SEO duplicate-content standpoint? Would it cannibalize newsletter signups?

  Lots of questions, but very little data out there. Not because people hadn’t done it, but because so much of it is based on your goals and what you actually want to get out of it.

  The switch

  What originally sealed the deal on making the switch to Medium was when I posted an email I’d received from an investor. That gave me my first taste of success on Medium.

  Our game plan was to post all new content to our Medium publication and set it up on a subdomain (blog.baremetrics.com). We’d keep the old blog, and then just post links to the new content as it was created. We’d also slowly transition past content over to the Medium publication as well.

  For most of 2017, all new blog posts went directly to Medium. Honestly, it was really enjoyable. Publishing on Medium is so effortless. Formatting content and uploading images takes basically zero time. It’s really the best web-based publishing experience I’ve had to date.

  I didn’t pay a whole lot of attention to stats. I just knew we were getting lots of likes and highlights and it was generating meaningful discussion, so it felt like a win.

  Second guessing the switch

  After about a year of posting on Medium, traffic on our own marketing site was (rightfully) taking a hit. Newsletter signups were also slumping and there was just palpably less “buzz” around Baremetrics content in general.

  I realized Medium is really great about surfacing content, but it removes the face of it. It neutralizes all content to basically be author-agnostic. It’s like Walmart or Amazon in that you can buy from thousands of different brands, but you rarely actually know what brand you’re buying…you just know “I got it from Amazon.”

  Same with content on Medium. Sure, you can see who the author is or what publication it’s on, but ultimately your takeaway is “I read this article on Medium”, and that’s not what I wanted. I wanted to get back to people saying “I read this article on Baremetrics”.

  On top of that, the amount of views a given article would get ultimately weren’t that impressive. At least not much/any more than our own blog (given we’d already built up a nice readership).

  As an example, our top posts on Medium had total Views in the 8-10k range (with our best ever getting around 40k, though that’s an outlier).

  After those top 5, the Views dropped off pretty drastically to just 500-1k per article.

  Whereas our own blog, beforehand, we were getting multiples of that on basically every article.

  The numbers just didn’t make sense. Yes, I could put more into Medium and try to build up readership even more. The guys at Basecamp regularly get 250k+ views on their content. But doing that helps Medium the most in the long run. They’ve been fumbling left and right trying to figure out how to make Medium sustainable, and I’m just not convinced they’ll always do what’s best for us and our business.

  Switching back

  Now I didn’t want to throw out distribution on Medium entirely. There can definitely be some benefit to syndicating content there. It’s essentially another distribution channel to expose people to our content.

  So we needed a game plan on how we could still make use of Medium as a distribution channel without cannibalizing our own readership or SEO work.

  That game plan consisted of two main things.

  Removing the custom domain

  We decided to stop using “blog.baremetrics.com” on Medium and redirected all of those URLs back to the same content on “baremetrics.com/blog”. This process was relatively painless.

  Ahead of time I added all the missing content from Medium to our own blog, then I setup 301 Redirects. I pointed “blog.baremetrics.com” to our marketing site, which runs on WordPress, and using the fantastic Redirection plugin was able to monitor any 404 errors from those Medium redirects and immediately create the necessary 301 Redirects from that.

  The only hiccup here is that you have to email Medium support to remove the custom domain (something I didn’t realize beforehand), so there was about a 12-hour period where all the articles on Medium weren’t accessible due to Medium forcing the incorrect URL.

  Republishing new content to Medium

  Going forward, we are still going to publish to Medium, but with two big caveats.

  We’ll publish new content two weeks later to Medium (so the initial publishing of the content is able to get solidified as the primary source from an SEO standpoint). We’ll use Medium’s Import tool to publish the content. Medium buries this thing, but what it does is let’s us republish on Medium and have them set the canonical URL to the original post on your own website. That’s a big kick from the SEO side of things as it tells Google that your original post is the main one and should be given preference in search results. With this method we still own the original content, get the benefits of being the primary source and get the distribution benefits of Medium!

  By making ourselves the original, authoritative source, we’re able to control the whole experience for the long term and to our benefit instead of potential short term wins to Medium’s benefit.

  What about you?

  So what about you? What’s worked for you as you build up content and readership?

  2018/01/24
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  Infoman

  Will Work for No Benefits: The Challenges of Being in the New Contract Workforce

  134 happy-go-lucky 9 hrs 207

  https://www.npr.org/2018/01/23/579720874/will-work-for-no-benefits-the-challenges-of-being-in-the-new-contract-workforce

  news.ycombinator.com/item?id=16214821

  "We really don't have much of a social safety net, and that's terrifying," says Matt Nelson, a freelance Web developer in Madison, Wis.

  Noah Willman A new NPR/Marist poll finds that 1 in 5 jobs in America is held by a worker under contract. Within a decade, contractors and freelancers could make up half of the American workforce. In a weeklong series, NPR explores many aspects of this change.

  Being on your own in the workforce often means you don't have the safety net of benefits and other forms of support that traditional workers do. And the toll isn't just financial, but physical and emotional too.

  Matt Nelson is one of millions of contract workers and has learned to love his freelance Web developer life. It allows him to split time between pursuing passions and making a living. But it didn't start out that way.

  "I didn't get into freelancing personally by choice," he says. During the last recession, he says, "I could not find a job. ... I couldn't get an email back or a phone call for the life of me."

  Nelson found plenty of company. He volunteers as leader of the Madison, Wis., chapter of Spark, a networking group started by the Freelancers Union that includes among its members a bug farming consultant and astrobiologist, as well as people from other walks of life.

  Nelson, 41, says they exchange tips and share stories — because otherwise, they feel they're flying solo, without support to fall back on. "We really don't have much of a social safety net, and that's terrifying," he says.

  An NPR/Marist poll released this week shows contract work is booming, with 32 million Americans currently making their living that way.

  That trend is expected to accelerate over the next decade, as companies and workers seek more flexibility through temporary work arrangements. But that also raises big questions about the future of the safety net: According to the poll, 51 percent of freelance and contract workers do not receive benefits common to many full-time jobs — sick leave, unemployment insurance or retirement savings.

  This is a vexing problem for the growing number of freelancers and policymakers.

  Sen. Mark Warner, a Virginia Democrat, says he worries that workers without benefits will strain tight public budgets even more. He supports making benefits portable, so freelancers can keep them regardless of where they work, and has introduced a bill to fund such programs.

  "If we don't have a social contract for this workforce, if we don't have social insurance that moves with workers, then I feel like the economic discontent and economic insecurity that comes from working with no safety net under you would rise dramatically," he says.

  Los Angeles freight truck driver Rene Flores has felt that insecurity. Trucking deregulation turned most drivers into contractors four decades ago — but Flores says the company he worked for didn't treat him as a free agent.

  "They always assigned me the work they wanted to do," he says. "They would send me where they wanted me to go. They always set the price. I never did."

  Los Angeles freight truck driver Rene Flores, a contractor, had to borrow $10,000 from friends to have surgery because he lacked health insurance.

  Miguel Cubillos Being a contractor meant he had to pay for his own gas and truck repairs, Flores says. And the company didn't give him health insurance, which became a huge problem when he fell on the job three years ago.

  He developed a giant hernia but endured the pain without medical care. After complaining about the lack of benefits in a newspaper interview, he was fired.

  Flores took a new job, but he couldn't work without surgery. So he borrowed $10,000 from friends to get a cheaper operation in Mexico. He rushed back to work, still bandaged and bleeding.

  "I don't have the resources to keep going for two more weeks and pay my rent and my bills," he says, sitting on his sofa, bandaged around his midsection.

  The toll of insecurity isn't just financial.

  "Being a freelancer, you really have to be on top of your emotional and mental health," says Carolina Salas, a New York City freelance marketing expert who helps medical practices attract new patients.

  Salas, who is 32, says stress and the demands of freelance work led to a pinched sciatic nerve, immobilizing her for six months.

  "As a contractor, the expectations of you are much higher than if you were an employee," she says. "They're moving so quickly and they have so little consideration or awareness for you that they sometimes forget that you're actually human."

  "Being a freelancer, you really have to be on top of your emotional and mental health," says Carolina Salas, a New York City freelance marketing expert.

  Justin T. Shockley Clients control the purse, after all, and there are fewer legal protections for contractors than for full-time employees.

  "If you just start talking to people, and you start talking to them about their emotional state, and their sense of self-worth, they'll tell you that they've taken a hit, and that it's hard," she says.

  Salas emigrated from Venezuela as a child. She started freelancing eight years ago and has learned to carefully track her time and expenses, push back on unrealistic deadlines, and save for retirement and emergencies — but she's not sure all freelancers are equally equipped.

  "That is what is concerns me," Salas says. "Because I come from a place where there was not much of a middle class, and I know what that looks like. And so I'm not saying that the United States is going in that direction, but I am very familiar with inequality."

  But adapting a new safety net for the new workforce will take time, says Arun Sundararajan, a management professor at New York University. And he says the transition could be messy.

  "Full-time employment didn't sort of come packaged with all of these wonderful things that we now associate with it; it was built sort of painstakingly over 100 years," Sundararajan says.

  Some hope freelancers will band together to fight for their own rights and benefits.

  "There are really big risks in freelancing, because the income is so episodic and freelancers aren't entitled to unemployment insurance and this is really bad for low-wage workers in particular," says Sara Horowitz, founder of the Freelancers Union, which has 350,000 members.

  Horowitz sees answers in things like her union's health insurance, which it has offered to members for two decades.

  "The answer is to build a safety net that's universal for everybody," she says. "Not to say this is only for very low wage workers, nor is it to say this is for highly skilled professional workers, but actually, they're all going through this together."

  The best antidote to fear, she says, is to create a new social safety net where freelancers can rely on each other. Horowitz says she hopes that the tens of millions of freelancers will take their concerns to the polls, and that elected officials will push for plans to rethink the social safety net.

  2018/01/24
• 
  

  Infoman

  Ending Bitcoin Support

  761 uptown 7 hrs 477

  https://stripe.com/blog/ending-bitcoin-support

  news.ycombinator.com/item?id=16216329

  At Stripe, we’ve long been excited about the possibilities of cryptocurrencies and the experimentation and innovation that’s come with them. In 2014, we became the first major payments company to support Bitcoin payments.

  Our hope was that Bitcoin could become a universal, decentralized substrate for online transactions and help our customers enable buyers in places that had less credit card penetration or use cases where credit card fees were prohibitive.

  Over the past year or two, as block size limits have been reached, Bitcoin has evolved to become better-suited to being an asset than being a means of exchange. Given the overall success that the Bitcoin community has achieved, it’s hard to quibble with the decisions that have been made along the way. (And we’re certainly happy to see any novel, ambitious project do so well.)

  This has led to Bitcoin becoming less useful for payments, however. Transaction confirmation times have risen substantially; this, in turn, has led to an increase in the failure rate of transactions denominated in fiat currencies. (By the time the transaction is confirmed, fluctuations in Bitcoin price mean that it’s for the “wrong” amount.) Furthermore, fees have risen a great deal. For a regular Bitcoin transaction, a fee of tens of U.S. dollars is common, making Bitcoin transactions about as expensive as bank wires.

  Because of this, we’ve seen the desire from our customers to accept Bitcoin decrease. And of the businesses that are accepting Bitcoin on Stripe, we’ve seen their revenues from Bitcoin decline substantially. Empirically, there are fewer and fewer use cases for which accepting or paying with Bitcoin makes sense.

  Therefore, starting today, we are winding down support for Bitcoin payments. Over the next three months we will work with affected Stripe users to ensure a smooth transition before we stop processing Bitcoin transactions on April 23, 2018.

  Despite this, we remain very optimistic about cryptocurrencies overall. There are a lot of efforts that we view as promising and that we can certainly imagine enabling support for in the future. We’re interested in what’s happening with Lightning and other proposals to enable faster payments. OmiseGO is an ambitious and clever proposal; more broadly, Ethereum continues to spawn many high-potential projects. We may add support for Stellar (to which we provided seed funding) if substantive use continues to grow. It’s possible that Bitcoin Cash, Litecoin, or another Bitcoin variant, will find a way to achieve significant popularity while keeping settlement times and transaction fees very low. Bitcoin itself may become viable for payments again in the future. And, of course, there’ll be more ideas and technologies in the years ahead.

  So, we will continue to pay close attention to the ecosystem and to look for opportunities to help our customers by adding support for cryptocurrencies and new distributed protocols in the future.

  2018/01/24
• 
  

  Infoman

  Show HN: Self-generated custom art for your home or Airbnb

  193 sdubois 4 hrs 73

  https://www.eliotand.me

  news.ycombinator.com/item?id=16216960

  Create

  Enter your city, address or Airbnb listing link to automatically create your hospitality map.

  Customize

  Select a different style, edit house rules, favorite places, contact info, etc... .

  Check-out

  Select the poster size, 11"x17" or 18"x24" and check-out. The poster will be individually printed on high quality glossy paper, and shipped to you.

  2018/01/23
• 
  

  Infoman

  美國政府停運風波歷時3天便結束，道指再急升142點，此前市場無視停運風險，原來一早預期兩黨可以傾掂數。全球股市瘋漲，是否泡沫暫難斷定，不過美國樓市已經起泡，比特幣更加初現泡沫爆破先兆。

  美國政府停擺僵局告終，共和黨表示，將於下月前考慮立法工作，保護被稱為「追夢者」的年輕移民，以此說服參議院民主黨議員轉投贊成票。參議院周一中午投票通過這一份臨時撥款法案，81票贊成、18票反對。這份法案可令美國政府再營運幾周，惟在解決移民和控制政府開支等根本政策上，兩黨仍存在分歧，不排除今年較後時間再出現政府關門局面。

  美股受政府停運風險的影響暫告一段落，正如市場對全球通脹風險視而不見一樣，風險未現就暫且不當作一回事。

  事實上，美國經濟與就業市場好轉，伴隨低息環境已造就了新一輪樓市熱潮。數據顯示，美國樓價截至去年底已連續15個月按月上漲超過5%，多個地區樓市價格陸續創新高。

  中國買家蜂擁至 美樓市升溫

  2017年美國住房市場的庫存顯得非常緊張。截至去年底止，美國待售房源較2016年減少12%。報道稱，這主要受強勁市場需求、緩慢房產建設和房主售房意願下降等綜合因素推動。新住宅建設速度不足以顯著緩解當前的庫存緊張，二手房庫存也面臨短缺。同時，由於勞動力市場保持強勁，貸款利率接近歷史低位，房地產市場的銷售仍在升溫。

  此外，海外的投資購房熱潮也席捲美國樓市，據美國地產經紀人協會（NAR）統計，2017年外國買家在美國置業總價值為1530億美元，按年增長49%。其中，中國人赴美置業的總金額高達317億美元，位列第一，遠超第二位加拿大的190億美元，按年增長18.6%。這些因素的共同作用促使美國樓價持續急升。

  據美國商務部資料，去年11月美國單幢房屋價格升至10年來新高。據美國房地產估值公司Zillow統計，2017年全美房地產庫存價值增加了6.5%，至約2萬億美元。如今全美房地產價值達到31.8萬億美元。美國房地產升溫反映在股市上，去年美國地產股漲了75%，幾乎是期內標普指數升幅的4倍。

  美國房價最高的地方集中在大城市，洛杉磯的房地產市場總值已達2.7萬億美元，位列全美第一；紐約緊隨其後，房地產市場總值為2.6萬億美元。在美國，排名前十位的城市房地產市場總值之和為11.3萬億美元，約佔全美房地產市場的36%。

  比特幣泡沫遠超鬱金香科網

  資金持續湧入股市，與股市指數相映成趣的是，比特幣價格近日跌勢加劇，周一晚跌了超過一成【圖1】，逼近萬元關口。

  高盛發表報告認為，比特幣泡沫遠甚於鬱金香泡沫和科網股泡沫。在寫給高淨值客戶的2018投資年度展望中，高盛花了相當的篇幅來討論以比特幣為代表的數字貨幣狂熱。如果把歷史上的幾次大泡沫：鬱金香泡沫、二十一世紀初的美國科網泡沫、日本股市泡沫，與現在的數字貨幣泡沫進行比較，數字貨幣價格的上升速度和幅度不僅遠遠超越鬱金香泡沫，更遠遠拋離美國科網泡沫和日本股市泡沫最瘋狂時期的資產價格漲勢。

  數位貨幣、區塊鏈等概念之所以吸引人，是因為這些技術宣稱能改變世界，使交易更便捷、交易費用更低，以及宣稱技術可以減少腐敗、洗錢等犯罪行為。但是，高盛認為，比特幣等數字貨幣並沒有做到以上好處，甚至出現了截然相反的結果。

  在交易方面，比特幣的交易並不便捷，投資者甚至要花10天時間才能完成一筆交易。2017年底，在全美17家比特幣交易平台上，價差達到4156美元，差不多是當時比特幣價格的三分一。此外，比特幣交易費用也在一路猛漲，同時比特幣交易平台使用的錢包也常常遭到黑客攻擊。

  至於洗錢及犯罪行為，更加是比特幣等數字貨幣帶來的惡果，走私販毒用到比特幣愈趨嚴重，南韓政府最近索性把所有比特幣交易實名制，意味比特幣等數字貨幣不能再為交易者隱藏身份，沒有這道保護罩，數字貨幣再沒有其存在與發展空間。

  高盛亦認為，數字貨幣泡沫破裂並不會對金融體系造成太大衝擊。2000年3月美國互聯網泡沫的最高峰時，納斯特指數【圖2】和標普500的總市值是美國GDP的101%，是全球GDP的31%。目前一路瘋漲的數字貨幣總市值也不過全美GDP的3.2%，全球GDP的0.8%，不足以構成系統風險。

  2018/01/23
• 
  

  Infoman

  美國政府停運風波歷時3天便結束，道指再急升142點，此前市場無視停運風險，原來一早預期兩黨可以傾掂數。全球股市瘋漲，是否泡沫暫難斷定，不過美國樓市已經起泡，比特幣更加初現泡沫爆破先兆。

  美國政府停擺僵局告終，共和黨表示，將於下月前考慮立法工作，保護被稱為「追夢者」的年輕移民，以此說服參議院民主黨議員轉投贊成票。參議院周一中午投票通過這一份臨時撥款法案，81票贊成、18票反對。這份法案可令美國政府再營運幾周，惟在解決移民和控制政府開支等根本政策上，兩黨仍存在分歧，不排除今年較後時間再出現政府關門局面。

  美股受政府停運風險的影響暫告一段落，正如市場對全球通脹風險視而不見一樣，風險未現就暫且不當作一回事。

  事實上，美國經濟與就業市場好轉，伴隨低息環境已造就了新一輪樓市熱潮。數據顯示，美國樓價截至去年底已連續15個月按月上漲超過5%，多個地區樓市價格陸續創新高。

  中國買家蜂擁至 美樓市升溫

  2017年美國住房市場的庫存顯得非常緊張。截至去年底止，美國待售房源較2016年減少12%。報道稱，這主要受強勁市場需求、緩慢房產建設和房主售房意願下降等綜合因素推動。新住宅建設速度不足以顯著緩解當前的庫存緊張，二手房庫存也面臨短缺。同時，由於勞動力市場保持強勁，貸款利率接近歷史低位，房地產市場的銷售仍在升溫。

  此外，海外的投資購房熱潮也席捲美國樓市，據美國地產經紀人協會（NAR）統計，2017年外國買家在美國置業總價值為1530億美元，按年增長49%。其中，中國人赴美置業的總金額高達317億美元，位列第一，遠超第二位加拿大的190億美元，按年增長18.6%。這些因素的共同作用促使美國樓價持續急升。

  據美國商務部資料，去年11月美國單幢房屋價格升至10年來新高。據美國房地產估值公司Zillow統計，2017年全美房地產庫存價值增加了6.5%，至約2萬億美元。如今全美房地產價值達到31.8萬億美元。美國房地產升溫反映在股市上，去年美國地產股漲了75%，幾乎是期內標普指數升幅的4倍。

  美國房價最高的地方集中在大城市，洛杉磯的房地產市場總值已達2.7萬億美元，位列全美第一；紐約緊隨其後，房地產市場總值為2.6萬億美元。在美國，排名前十位的城市房地產市場總值之和為11.3萬億美元，約佔全美房地產市場的36%。

  比特幣泡沫遠超鬱金香科網

  資金持續湧入股市，與股市指數相映成趣的是，比特幣價格近日跌勢加劇，周一晚跌了超過一成【圖1】，逼近萬元關口。

  高盛發表報告認為，比特幣泡沫遠甚於鬱金香泡沫和科網股泡沫。在寫給高淨值客戶的2018投資年度展望中，高盛花了相當的篇幅來討論以比特幣為代表的數字貨幣狂熱。如果把歷史上的幾次大泡沫：鬱金香泡沫、二十一世紀初的美國科網泡沫、日本股市泡沫，與現在的數字貨幣泡沫進行比較，數字貨幣價格的上升速度和幅度不僅遠遠超越鬱金香泡沫，更遠遠拋離美國科網泡沫和日本股市泡沫最瘋狂時期的資產價格漲勢。

  數位貨幣、區塊鏈等概念之所以吸引人，是因為這些技術宣稱能改變世界，使交易更便捷、交易費用更低，以及宣稱技術可以減少腐敗、洗錢等犯罪行為。但是，高盛認為，比特幣等數字貨幣並沒有做到以上好處，甚至出現了截然相反的結果。

  在交易方面，比特幣的交易並不便捷，投資者甚至要花10天時間才能完成一筆交易。2017年底，在全美17家比特幣交易平台上，價差達到4156美元，差不多是當時比特幣價格的三分一。此外，比特幣交易費用也在一路猛漲，同時比特幣交易平台使用的錢包也常常遭到黑客攻擊。

  至於洗錢及犯罪行為，更加是比特幣等數字貨幣帶來的惡果，走私販毒用到比特幣愈趨嚴重，南韓政府最近索性把所有比特幣交易實名制，意味比特幣等數字貨幣不能再為交易者隱藏身份，沒有這道保護罩，數字貨幣再沒有其存在與發展空間。

  高盛亦認為，數字貨幣泡沫破裂並不會對金融體系造成太大衝擊。2000年3月美國互聯網泡沫的最高峰時，納斯特指數【圖2】和標普500的總市值是美國GDP的101%，是全球GDP的31%。目前一路瘋漲的數字貨幣總市值也不過全美GDP的3.2%，全球GDP的0.8%，不足以構成系統風險。

  2018/01/23
• 
  

  Infoman

  Facebook open-sources Detectron

  619 rmason 13 hrs 144

  https://research.fb.com/facebook-open-sources-detectron/

  news.ycombinator.com/item?id=16210834

  Today, Facebook AI Research (FAIR) open sourced Detectron — our state-of-the-art platform for object detection research.

  The Detectron project was started in July 2016 with the goal of creating a fast and flexible object detection system built on Caffe2, which was then in early alpha development. Over the last year and a half, the codebase has matured and supported a large number of our projects, including Mask R-CNN and Focal Loss for Dense Object Detection, which won the Marr Prize and Best Student Paper awards, respectively, at ICCV 2017. These algorithms, powered by Detectron, provide intuitive models for important computer vision tasks, such as instance segmentation, and have played a key role in the unprecedented advancement of visual perception systems that our community has achieved in recent years.

  Beyond research, a number of Facebook teams use this platform to train custom models for a variety of applications including augmented reality and community integrity. Once trained, these models can be deployed in the cloud and on mobile devices, powered by the highly efficient Caffe2 runtime.

  Our goal in open sourcing Detectron is to make our research as open as possible and to accelerate research in labs across the world. With its release, the research community will be able to reproduce our results and have access to the same software platform that FAIR uses every day.

  Detectron is available under the Apache 2.0 license at https://github.com/facebookresearch/Detectron. We’re also releasing extensive performance baselines for more than 70 pre-trained models that are available to download from our model zoo.

  Areas Computer Vision, Facebook AI Research (FAIR)

  2018/01/23
• 
  

  Infoman

  Amazon Go and the Future

  124 misiti3780 3 hrs 83

  https://stratechery.com/2018/amazons-go-and-the-future

  news.ycombinator.com/item?id=16213668

  Amazon Go is the story of technology, and so is this tweet:

  Yesterday the Amazon Go concept store in Seattle opened to the public, filled with sandwiches, salads, snacks, various groceries, and even beer and wine (Recode has a great set of pictures here). The trick is that you don’t pay, at least in person: a collection of cameras and sensors pair your selection to your Amazon account — registered at the door via smartphone app — which rather redefines the concept of “grab-and-go.”

  The economics of Amazon Go define the tech industry; the strategy, though, is uniquely Amazon’s. Most of all, the implications of Amazon Go explain both the challenges and opportunities faced by society broadly by the rise of tech.

  The Economics of Tech

  This point is foundational to nearly all of the analysis of Stratechery, which is why it’s worth repeating. To understand the economics of tech companies one must understand the difference between fixed and marginal costs, and for this Amazon Go provides a perfect example.

  A cashier — and forgive the bloodless language for what is flesh and blood — is a marginal cost. That is, for a convenience store to sell one more item requires some amount of time on the part of a cashier, and that time costs the convenience store operator money. To sell 100 more items requires even more time — costs increase in line with revenue.

  Fixed costs, on the other hand, have no relation to revenue. In the case of convenience stores, rent is a fixed cost; 7-11 has to pay its lease whether it serves 100 customers or serves 1,000 in any given month. Certainly the more it serves the better: that means the store is achieving more “leverage” on its fixed costs.

  In the case of Amazon Go specifically, all of those cameras and sensors and smartphone-reading gates are fixed costs as well — two types, in fact. The first is the actual cost of buying and installing the equipment; those costs, like rent, are incurred regardless of how much revenue the store ultimately produces.

  Far more extensive, though, are the costs of developing the underlying systems that make Amazon Go even possible. These are R&D costs, and they are different enough from fixed costs like rent and equipment that they typically live in another place on the balance sheet entirely.

  These different types of costs affect management decision-making at different levels (that is, there is a spectrum from purely marginal costs to purely fixed costs; it all depends on your time frame):

  If the marginal cost of selling an individual item is more than the marginal revenue gained from selling the item (i.e. it costs more to pay a cashier to sell an item than the gross profit earned from an item) then the item won’t be sold. If the monthly rent for a convenience store exceeds the monthly gross profit from the store, then the store will be closed. If the cost of renovations and equipment (in the case of small businesses, this cost is usually the monthly repayments on a loan) exceeds the net profit ex-financing, then the owner will go bankrupt. Keep in mind, most businesses start out in the red: it usually takes financing, often in the form of a loan, to buy everything necessary to even open the business in the first place; a company is not truly profitable until that financing is retired. Of course once everything is paid off a business is not entirely in the clear: physical objects like shelves or refrigeration units or lights break and wear out, and need to be replaced; until that happens, though, money can be made by utilizing what has already been paid for.

  This, though, is why the activity that is accounted for in R&D is so important to tech company profitability: while digital infrastructure obviously needs to be maintained, by-and-large the investment reaps dividends far longer than the purchase of any physical good. Amazon Go is a perfect example: the massive expense that went into developing the underlying system powering cashier-less purchasing does not need to be spent again; moreover, unlike shelving or refrigerators, the output of that expense can be duplicated infinitely without incurring any additional cost.

  This principle undergirds the fantastic profitability of successful tech companies:

  It was expensive to develop mainframes, but IBM could reuse the expertise to build them and most importantly the software needed to run them; every new mainframe was more profitable than the last. It was expensive to develop Windows, but Microsoft could reuse the software on all computers; every new computer sold was pure profit. It was expensive to build Google, but search can be extended to anyone with an Internet connection; every new user was an opportunity to show more ads. It was expensive to develop iOS, but the software can be used on billions of iPhones, every one of which generates tremendous profit. It was expensive to build Facebook, but the network can scale to two billion people and counting, all of which can be shown ads. In every case a huge amount of fixed costs up front is overwhelmed by the ongoing ability to make money at scale; to put it another way, tech company combine fixed costs with marginal revenue opportunities, such that they make more money on additional customers without any corresponding rise in costs.

  This is clearly the goal with Amazon Go: to build out such a complex system for a single store would be foolhardy; Amazon expects the technology to be used broadly, unlocking additional revenue opportunities without any corresponding rise in fixed costs — of developing the software, that is; each new store will still require traditional fixed costs like shelving and refrigeration. That, though, is why this idea is so uniquely Amazonian.

  The Strategy of Technology

  The most important difference between Amazon and most other tech companies is that the latter generally invest exclusively in research and development — that is, to say, in software. And why not? As I just explained software development has the magical properties of value retention and infinite reproduction. Better to let others handle the less profitable and more risky (at least in the short term) marginal complements. To take the three most prominent examples:

  Microsoft builds the operating system (and eventually, application software) and leaves the building of computers to OEMs Google builds the search engine and leaves the creation of web pages to be searched to the rest of the world Facebook builds the infrastructure of the network, and leaves the creation of content to be shared to its users All three companies are, at least in terms of their core businesses, pure software companies, which means the economics of their businesses align with the economics of software: massive fixed costs, and effectively zero marginal costs. And while Microsoft’s market, large though it may have been, was limited by the price of a computer, Google and Facebook, by virtue of their advertising model, are super-aggregators capable of scaling to anyone with an Internet connection. All three also benefit (or benefited) from strong network effects, both on the supply and demand side; these network effects, supercharged by the ability to scale for free, are these companies’ moats.

  Apple and IBM, on the other hand, are/were vertical integrators, particularly IBM. In the mainframe era the company built everything from components to operating systems to application software and sold it as a package with a long-term service agreement. By doing so all would-be competitors were foreclosed from IBM’s market; eventually, in a(n unsuccessful) bid to escape antitrust pressure, application software was opened up, but that ended up entrenching IBM further by adding on a network effect. Apple isn’t nearly as integrated as IBM was back in the 60s, but it builds both the software and the finished products on which it runs, foreclosing competitors (while gaining economies of scale from sourcing components and two-sided network effects through the App Store); Apple is also happy to partner with telecoms, which have their own network effects.

  Amazon is doing both.

  In market after market the company is leveraging software to build horizontal businesses that benefit from network effects: in e-commerce, more buyers lead to more suppliers lead to more buyers. In cloud services, more tenants lead to great economies of scale, not just in terms of servers and data centers but in the leverage gained by adding ever more esoteric features that both meet market needs and create lock-in. As I wrote last year the point of buying Whole Foods was to jump start a similar dynamic in groceries.

  At the same time Amazon continues to vertically integrate. The company is making more and more products under its own private labels on one hand, and building out its fulfillment network on the other. The company is rapidly moving up the stack in cloud services, offering not just virtual servers but microservices that obviate the need for server management entirely. And in logistics the company has its own airplanes, trucks, and courier services, and has promised drones, with the clear goal of allowing the company to deliver products entirely on its own.

  To be both horizontal and vertical is incredibly difficult: horizontal companies often betray their economic model by trying to differentiate their vertical offerings; vertical companies lose their differentiation by trying to reach everyone. That, though, gives a hint as to how Amazon is building out its juggernaut: economic models — that is, the constraint on horizontal companies going vertical — can be overcome if the priority is not short-term profit maximization.

  Amazon’s Triple Play

  In 2012 Amazon acquired Kiva Systems for $775 million, then the largest acquisition in company history. Kiva Systems built robots for fulfillment centers, and many analysts were puzzled by the purchase: Kiva Systems already had a plethora of customers, and Amazon was free to buy their robots for a whole lot less than $775 million. Both points argued against a purchase: continuing to sell to other companies removed the only plausible strategic rationale for buying the company instead of simply buying robots, but to stop selling to Kiva Systems’ existing customers would be value-destructive. It’s one thing to pay 8x revenue, as Amazon did; it’s another to cut off that revenue in the process.

  In fact, though, that is exactly what Amazon did. The company had no interest in sharing Kiva Systems’ robots with its competitors, leaving a gap in the market. At the same time the company ramped up its fulfillment center build-out, gobbling up all of Kiva Systems’ capacity. In other words, Amazon made the “wrong” move in the short-term for a long-term benefit: more and better fulfillment centers than any of its competitors — and spent billions of dollars doing so.

  This willingness to spend is what truly differentiates Amazon, and the payoffs are tremendous. I mentioned telecom companies in passing above: their economic power flows directly from massive amounts of capital spending; said power is limited by a lack of differentiation. Amazon, though, having started with a software-based horizontal model and network-based differentiation, has not only started to build out its vertical stack but has spent massive amounts of money to do so. That spending is painful in the short-term — which is why most software companies avoid it — but it provides a massive moat.

  That is why, contra most of the analysis I have seen, I don’t think Amazon will license out the Amazon Go technology. Make no mistake, that is exactly what a company like Google would do (and as I expect them to do with Waymo), and for good reason: the best way to get the greatest possible return on software R&D is to spread it as far and wide as possible, which means licensing. The best way to build a moat, though, is to actually put in the effort to dig it, i.e. spend the money.

  To that end, I suspect that in five to ten years the countries Amazon serves will be blanketed with Amazon Go stores, selling mostly Amazon products, augmented by Amazon fulfillment centers. That is the other point many are missing; yes, the Amazon Go store took pains to show that it still had plenty of workers: shelf stockers, ID checkers, and food preparers, etc.

  Workers as seen from a sidewalk window as they assemble sandwiches in an Amazon Go store Monday, Jan. 22, 2018, in Seattle. More than a year after it introduced the concept, Amazon opened its artificial intelligence-powered Amazon Go store in downtown Seattle on Monday. The store on the bottom floor of the company’s Seattle headquarters allows shoppers to scan their smartphone with the Amazon Go app at a turnstile, pick out the items they want and leave. (AP Photo/Elaine Thompson) Unlike cashiers, though, none of these jobs have to actually be present in the store most of the time. It seems obvious that Amazon Go stores of the future will rarely have employees in store at all: there will be a centralized location for food preparation and a dedicated fleet of shelf stockers. That’s the thing about Amazon: the company isn’t afraid of old-world scale. No, sandwich preparation doesn’t scale infinitely, but it does scale, particularly if you are willing to spend.

  Marx Versus Bezos

  The political dilemma embedded in this analysis is hardly new: Karl Marx was born 200 years ago. Technology like Amazon Go is the ultimate expression of capital: invest massive amounts of money up front in order to reap effectively free returns at scale. What has fundamentally changed, though, is the role of labour: Marx saw a world where capital subjugated labour for its own return; technologies like Amazon Go have increasingly no need for labor at all.

  Some, certainly, see this as a problem: what about all the cashiers? What about all the truck drivers? What about all of the other jobs that will be displaced by automation? Well, I would ask, what about the labour of Marx’s day, the factory workers borne of the industrial revolution that he thought should overthrow the bourgeoisie?

  In fact, they are all gone, replaced by automation. And, in the meantime, nearly all of humanity has been lifted out of abject poverty. As Nicholas Kristof wrote in the New York Times:

  2017 was probably the very best year in the long history of humanity. A smaller share of the world’s people were hungry, impoverished or illiterate than at any time before. A smaller proportion of children died than ever before. The proportion disfigured by leprosy, blinded by diseases like trachoma or suffering from other ailments also fell…

  Every day, the number of people around the world living in extreme poverty (less than about $2 a day) goes down by 217,000, according to calculations by Max Roser, an Oxford University economist who runs a website called Our World in Data. Every day, 325,000 more people gain access to electricity. And 300,000 more gain access to clean drinking water.

  I don’t seek to minimize real struggles, much less the real displacement that will come from technologies like Amazon Go writ large. For decades technology helped the industrial world work better; more and more, technology is replacing that world completely, and there will be pain. That, though, is precisely why it is worth remembering that the world is not static: to replace humans is, in the long run, to free humans to create entirely new needs and means to satisfy those needs. It’s what we do, and the faith to believe it will happen again will be the best guide in figuring out how.

  As for Amazon, the company’s goal to effectively tax all economic activity continues apace. Surely the company is grateful about the attention Facebook is receiving from the public, even as it builds a monopoly with a triple moat. The lines outside Amazon Go, though, are a reminder of exactly why aggregator monopolies are something entirely new: these companies are dominant because people love them. Regulation may be as elusive as Marx’s revolution.

  2018/01/23
• 
  

  Infoman

  Y Combinator is accepting applications for S18

  197 V2hLe0ThslzRaV2 12 hrs 90

  http://www.ycombinator.com/apply/#Summer2018

  news.ycombinator.com/item?id=16206874

  Apply to Summer 2018 About Y Combinator Frequently Asked Questions What Happens at Y Combinator If you want to apply, please submit your application online by 8 pm PT on March 24. Groups that submit early have a small advantage because we have more time to read their applications.

  On April 17, by 10PM, we’ll invite the groups that seem most promising to meet us in Mountain View in late May. We’ll reimburse reasonable travel expenses.

  We decide who to fund after each day of interviews.

  If we invest in you, your group is expected to move to the Bay Area for June--August 2018. You can of course leave afterward if you want, but it's a good place for a startup to be.

  After you're accepted, we'll immediately get to work helping you set up your company, if it isn't already. As soon as your company exists, we'll write a check to it for the investment. You can spend the money however you want.

  Y Combinator doesn't supply office space. We have space you can use if you need to, but we expect you to work out of wherever you find to live. It is no coincidence that so many successful startups have started this way; it's the ideal setup for the initial phase.

  During the 3 month cycle we'll have dinners every Tuesday for all the founders. At each dinner we'll invite an expert in some aspect of startups to speak.

  We have regular office hours year round for startups who want to talk about what they're building, or get advice on dealing with investors. We also have occasional events at YC.

  During and after the 3 months we introduce startups individually to people who could help them. The founders of other YC-funded companies tend to be especially helpful. Today the YC alumni network is probably the most powerful network in the startup world.

  About 11 weeks in, we organize an event called Demo Day at which the startups present to a carefully selected, invite-only audience.

  YC doesn't really end after 3 months; only the dinners do. We continue to give advice and make introductions as long as founders need—-and so does the informal network of YC-funded companies.

  Apply to Summer 2018 Who We Fund

  How do we choose who to fund?

  The people in your group are what matter most to us.

  We'll fund companies from anywhere in the world. We fund companies doing everything from building mobile apps to diagnosing cancer.

  We'll happily fund companies that just started and have nothing more than an idea. And we've funded companies that had over $20M in annual revenue and over 50 employees.

  International founders, please note: if your company is already incorporated as a non-United States company, to participate in YC you will need to convert your foreign company into a United States corporation (usually with a foreign subsidiary). While lawyers will drive this process, it will require a significant effort on your part.

  You must have at least 10% equity in the startup to be considered a founder by Y Combinator. Only founders can come to interviews if invited or attend batch events if accepted.

  2018/01/23
• 
  

  Infoman

  In-N-Out managers earn triple the industry average

  98 ohjeez 6 hrs 66

  https://medium.californiasun.co/in-n-out-store-managers-earn-160000-wages-b08fe6f1706f

  news.ycombinator.com/item?id=16209839

  A typical architect in California earns about $112,000 a year, according to the jobs site Indeed. For lawyers and software engineers, the average figures are more than $115,000.

  But beating them all — by a lot — is an unlikely job title: In-N-Out Burger store manager.

  According to the latest numbers from the Irvine hamburger chain, the average yearly pay of its restaurant managers is now more than $160,000. That’s roughly triple the industry average.

  “In-N-Out is just eons above everybody else,” said Saru Jayaraman, who leads the Food Labor Research Center at U.C. Berkeley. “On wages and benefits, they really are the best large chain.”

  A family-owned company, In-N-Out is known for treating its employees well. Denny Warnick, vice president of operations, said in an email that the approach was set down with the company’s founding in 1948 by Harry and Esther Snyder, who made quality service a central focus.

  “Paying their associates well was just one way to help maintain that focus, and those beliefs remain firmly in place with us today,” Warnick said.

  In-N-Out workers get at least $13 an hour to start, and can eventually rise through the ranks to store manager — no college degree necessary. Benefits include 401(k) plans, paid vacation, and health, dental, and vision plans. (California’s minimum wage for large companies recently bumped up to $11, and is required by law to hit $15 by 2022.)

  In-N-Out employees enjoy some of the highest wages of the fast food industry. (Tom Coates/CC BY-NC 2.0) Jayaraman said In-N-Out wasn’t performing charity — a loyal workforce means increased productivity, less employee turnover, and in the long run larger profits.

  “Our research shows that companies that take the high road make a profit not in spite of paying their workers better but because they pay their workers better,” she said.

  If other fast food establishments have been reluctant to raise wages, Jayaraman added, it’s because pressure from investors has elevated quarterly gains above the potential long-term benefits of happy workers. In-N-Out has no public shareholders.

  But isn’t the work a grind? To be sure, many of the accounts from In-N-Out employees on the job review website Glassdoor cite hard work and long hours.

  Even so, more than 90 percent said they’d recommend the workplace to a friend.

  That’s one reason In-N-Out was №4 in Glassdoor’s latest national ranking of the best places to work — beating out Google, LinkedIn, and Salesforce, among many others.

  This article is from the California Sun, a newsletter that delivers California’s most compelling news to your inbox each morning — for free. Sign up here.

  2018/01/23