I use the Kindle desktop app a fair amount, usually for going back to books Iâve already read for reference, or to review highlights and make notes. Itâs always been a pretty bad application, with a strangely dated interface and extremely rare updates, but lately itâs gotten unusable. Maybe itâs unstable on the M1 Mac mini. It now crashes constantly and corrupts the local data, requiring purge and reinstall to fix it.
Instead of fighting with it, I went back to their Kindle Cloud Reader, a web-based version of the same Kindle client that Amazonâs kept around for a decade. Like the desktop app, it gets almost no attention that I can tell. But since it runs in the browser, it doesnât have the same stability problems as the desktop app, and seems to support all of the same basic reading and annotation features as the other clients.
Until Amazon decides to care about Kindleâs software products, Iâd recommend using the Cloud Reader for desktop reading. Itâs sad to see them flounder around with their massive advantage in the e-reading space. They can get away with this, of course, as the de facto default platform for e-books still, but it seems inevitable that someone will come along and disrupt this position.
Geoff Zeiss on combining satellite imagery and spatial analysis to identify tree encroachment in utilities:
Transmission line inspections are essential in ensuring grid reliability and resilience. They are generally performed by manned helicopters often together with a ground crew. There are serious safety issues when inspections are conducted by helicopter. Data may be collected with cameras and analyzed to detect a variety of conditions including corrosion, evidence of flash over, cracks in cross arms, and right-of-way issues such as vegetation encroachment. in North America annual inspections are mandated by NERC and are not optional. With over 200,000 miles of high-voltage transmission lines and 5.5 million miles of distribution lines in the United States, improving the efficiency and reducing the risk of inspections would have a major impact on the reliability of the power grid.
Google Sheets now supports using BigQuery data inside of Google Sheets features like pivot tables and formulas, which means orders-of-magnitude increase in data limits.
The Kindle launched in 2007, making ebooks accessible as a format not only because of a compelling device, but also a marketplace for content. Suddenly most books were available instantly for $10 a piece. No more trips to the store, expensive hardcovers and paperbacks, and importantly, no more paper taking up shelf space. As much as I love the Kindle, I have a growing list of gripes about the experience. Like with John Gruberâs recent post on the iPad, criticism comes from a place of love for the platform, and a disappointment with how little innovation thereâs been over 13 years.
I still prefer the paperback format for pure experience, but the practicality of Kindle nearly always wins out. With Readwise Iâve gotten so used to heavily highlighting in my books, and itâs too much work to annotate in paper format when Iâve then got to transfer them somewhere else to ever see those notes again.
Iâd used the Kindle iOS app since the beginning, but didnât buy a Kindle device until 2015 (the Paperwhite, third-generation). I use both the app and the device every single day, so over time Iâve built up a back log of feature requests and documented shortcomings. Thereâs great opportunity for Amazon to make some amazing improvements.
But first, letâs start with the things Amazonâs done right.
What Amazon has gotten right
Whispersync â After acquiring Audible in 2008 (audiobooks) and Goodreads in 2013 (social network for readers), theyâve added some integration between the platforms. Whispersync started as their cloud service for syncing progress between devices for ebooks. A few years ago they extended this to sync progress between the text and audio versions, if you own both. For times when Iâve read books that I have on both platforms, this is a fantastic feature. Works pretty reliably, and is a neat technology.
X-Ray â I first saw this on Prime Video. The best description of X-Ray is that itâs like the old âPop-Up Videoâ show on VH1, which would show âdid you know?â style annotations on top of music videos. In video it allows you to see, in real-time, which actors are on screen and quickly look up their filmographies and whatnot. X-Ray for Kindle is similar: it breaks down common terms and keywords, themes, and subjects, with ways to navigate to those parts of the book.
One-tap purchasing â This is always a delightful process. Search for a book (or see one recommended) and in one tap itâs downloading. Iâve bought dozens of books on a whim this way.
Highlighting & annotation â Iâve been an avid book highlighter for years. Readwise now raises the value of annotations 10x. In the Kindle iOS app, the share sheet on a highlighted passage also lets you save a slick shareable screenshot of your highlight on social media.
Audible narration â This is more technically cool than practical. If you own audio and text versions, you can download the audio inside of the Kindle mobile app. When playing the narration, it moves the text along with it. Iâve never used this in practice, but itâs impressive.
Plenty of things to love. But now time for my personal recommendations.
Requests for the Kindle platform
Tighter social integration from Goodreads â Both the Kindle device and mobile apps now have connection to your account on Goodreads. They can see your âto-readâ list, can mark things as read or currently reading, and can sync progress. But they havenât done much of anything with the social aspects of Goodreads. Iâd like to do things like enable seeing highlights my friends made in a book, and maybe an ability to put comments on those highlights just directed to specific friends. It could spark conversation around book topics you might not know had mutual resonance between you and a friend. Goodreads in general hasnât gotten a lot of love since Amazon made the acquisition, but itâs integration with the live reading experience is one of the biggest places to expand into. Itâd make the service more purposeful and engaging.
Progress adjustments â When reading books on multiple platforms, itâs possible for your âfurthest readâ progress to get out of whack (for example, if you flip ahead to look at a footnote, more on those in a second). Then the waterline for where youâve reached in the book gets baked and is impossible to adjust. Itâd be nice to have a quick interface to enter the desired furthest read point that resyncs everywhere.
Better footnotes â If youâve read many nonfiction books (or a heavy footnoter like DFW), youâve been annoyed by the inconsistency in how footnotes are formatted in books. Most of the time, tapping a footnote zooms you to the end of the book. Theyâve recently added contextual back buttons to return where you were from the footnote, but if you flip around pages near the footnote, itâs possible to end up resetting your furthest progress point to 98%, where the footnotes are at the end. Some books (feels like a minority) have more functional overlay footnotes. When you tap those links a small popover appears at the bottom with the footnote text without leaving the page. This is even an improvement over most paper books. The former problem with footnotes at the end of the ebook is actively much worse than page-flipping in paper formats.
More consistent formatting â This one may be largely out of Amazonâs control; I donât know much about the process of authoring ePub/mobi files. But Amazon could certainly help more to provide an âIDEâ for authors and publishers to use best practices for the platform when converting their works into ebook format. It seems like after 13 years thereâd be much less of this inconsistency than I see from book to book. Footnotes are screwy, progress measurement is all over the place. Some books mark the 100% point at the end of the main text, some at the full end of the file (after the index/glossary). Page numbers are also an inconsistent mess.
Deep linked references â The one that Iâm the most interested in. Imagine this: you tap a citation link that displays a popover on the screen, then tapping a particular citation could deep link into an interactive âclipâ from the source materialâs ebook format, also showing links to add that source to your wishlist, or even buy for your library. It could even let you highlight from books you donât yet own, and create a separate shelf of books on your device of referenced works you might be interested in reading in full. Over the years theyâve added both dictionary and Wikipedia lookup on selected text. I see this as a similar way to bridge into related, adjacent content. Would benefit readers and, if well executed, Amazon and publishers by more widely referring users to other works.
Semantic web of references â If citations and references were deeply linked, you could also build a reference graph. If Iâm reading Tom Sowellâs A Conflict of Visions, I could pull up a tab that shows all works referenced within, and also all works that reference it. Go both ways with it. Picking through bibliographies is frequently how new things get added to my reading list. This would give readers an exposed graph of related works or authors they may find interesting.
Book lending â This is probably a long shot, but itâd be neat to be able to temporarily âlendâ access to a book to, say, a friend on Goodreads, with a âreturnâ date you could customize that revokes access and returns to you. Perhaps you could cap the limit to 60 days or something. It could give the social reading experience more of that feeling of sharing knowledge and reading experiences with friends. It could also show your highlights and annotations, like someone reading a highlighted hardcover book you lend them.
Reading metrics â When did I start a book? When did I finish? How many days did it take to read? How many pages did I read each day? Data nerds like me would eat this up. Probably not of mass market interest, understandably. You could add gamification here, but Iâd be reticent about that since the purity of reading doesnât need any more distractions out there to keep you from deep immersion in something. Twitter and Instagram are already doing a great job at stealing usersâ attention away from books.
Have any active Kindle users out there formulated their own lists like this? Iâd love to hear othersâ ideas. Maybe with enough of a conversation about them, Amazon could respond positively.
AWSâs re:Invent conference just wrapped last week. Since weâre so deep into AWS technologies, I keep an eye out each year on the trends visible in Amazonâs product launches. They move at breathtaking speed to fill out their offering suite and keep their current momentum as the leader in the cloud space. Theyâre really nailing the bundling & scale economics that the likes of Microsoft and Oracle were so successful at in years past. When going upmarket, having a product for every problem outweighs the need for having the highest quality in any individual product line. Enterprises often value the ability to buy everythign they need from a single vendor higher than the quality of the products (what Ben Thompson has referred to as the âone throat to chokeâ phenomenon).
Here are a handful of the announcements I found most interesting, in no particular order:
AWS has finally relented to the customer base thatâs been reluctant to move to the cloud for the past decade. With the scale they have now theyâve been able to productize a managed service that puts an âAWS in-a-boxâ type of modular system into a customerâs datacenter, ideally giving the best of all worlds of security, compliance, and exposure to the AWS services and APIs. Itâll be interesting to see what kind of adoption this gets.
SageMaker is their service for creating, training, and deploying ML models. Itâs really an umbrella brand name for about a dozen sub-products for various pieces of the ML workflow. Studio intended to be a full âIDEâ-style interface for working with everything youâve built in SM. Clear indication that this is one of their big strategic plays going forward: lowering the barrier to doing ML and having customers new to the space learning with and expanding from the AWS platform from the start.
Rekognition is AWSâs computer vision service, with endpoints for analyzing video and image data for objects, sentiment, content moderation, and search. One of the barriers for image classification tasks has been the ability to tailor the models to recognize other domain-specific content (like âwhat kind of part is this?â from a list of parts the customer builds). It now lets you upload your own custom labeled image datasets for training custom Rekognition models.
This isnât really a service or expansion on one like the others in the list. This is more a knowledge base of content from Amazon engineers on how they internally build and operate software at scale.
Iâve linked before to pieces about Amazonâs culture of long-form writing and memos in place of PowerPoint for meetings and conveying new business concepts. In their case, the discipline around this kind of thoroughness comes from the top. In this piece by Jean-Louis GassĂŠe, he references Bezosâs own writing in his famous annual shareholder letters. I read these every year. Itâs a great example of a practice I value â using writing and long-form narrative to explain the ins and outs of an idea. Bullets, outlines, and emails leave too much room for ambiguity, and therefore donât force the level of detailed thinking through of an idea.
I love this bit from his 2010 letter, on the ideas that eventually evolved into AWS:
In 2010, he penned a tribute to Amazonâs engineers by explaining, and not just in laymanâs terms, what they do. The tone was just right, neither disingenuously geeky nor overtly tongue-in-cheek:
âThe diversity of products demands that we employ modern regression techniques like trained random forests of decision trees to flexibly incorporate thousands of product attributes at rank time⌠Now, if the eyes of some shareowners dutifully reading this letter are by this point glazing over, I will awaken you by pointing out that, in my opinion, these techniques are not idly pursued â they lead directly to free cash flow.â
What he was doing, although we may not have fully appreciated it at the time, was giving a brief tour of AWS, arguably Amazonâs most important technology.
He has an enviable ability to communicate in narrative format that everyone should strive to get good at.
Another fantastic piece from Eugene Wei on what he terms âinvisible asymptotesâ â the invisible barriers companies collide with in growth:
One way to identify your invisible asymptotes is to simply ask your customers. As I noted at the start of this piece, at Amazon we honed in on how shipping fees were a brake on our business by simply asking customers and non-customers.
Hereâs where the oft-cited quote from Henry Ford is brought up as an objection: âIf I had asked people what they wanted, they would have said faster horses,â he is reputed to have said. Like most truisms in business, it is snappy and lossy all at once.
True, itâs often difficult for customers to articulate what they want. But whatâs missed is that theyâre often much better at pinpointing what they donât want or like. What you should hear when customers say they want a faster horse is not the literal but instead that they find travel by horse to be too slow. The savvy product person can generalize that to the broader need of traveling more quickly, and that problem can be solved any number of ways that donât involve cloning Secretariat or shooting their current horse up with steroids.
This isnât a foolproof strategy. Sometimes customers lie about what they donât like, and sometimes they canât even articulate their discontent with any clarity, but if you match their feedback with good analysis of customer behavior data and even some well-designed tests, you can usually land on a more accurate picture of the actual problem to solve.
A popular sentiment in Silicon Valley is that B2C businesses are more difficult product challenges than B2B because products and services for the business customer can be specified merely by talking to the customer while the consumer market is inarticulate about its needs, per the Henry Ford quote. Again, thatâs only partially true, and so many consumer companies Iâve been advising recently havenât pushed enough yet on understanding or empathizing with the objections of its non-adopters.
Amazon is famous for its âNo PowerPointâ policy for meetings, requiring that those calling meetings for any new idea, project, or effort write a narrative document to describe the ins-and-outs of whatâs on the table for discussion. These documents get circulated to all the right people beforehand for review, so that the team can really drill in on an aligned objective for the meeting with clear data at their fingertips about the pros and cons.
This piece talks about the experience with this process first-hand from a former employee, bulleted out to help understand how it works:
Understand what you are trying to accomplish with the document (as with anything you write). For example, is this a new project that you want to undertake (product you want to build)? Is this a significant change to a planned launch date or feature set (especially of a high-visibility project)? Is this just more of a status update? Is it an answer to a specific question or request that Jeff made, or is this something that you are bringing to him? One of the hardest types of docs to write was basically a âde-commitâ document (Amazon is big on âdisagree and commit,â so if you are coming back and wanting to de-commit to something previously agreed, you really had to have your data and logic clear as to what had changed since the plan was committed.)
Iâve always admired this idea, as Iâm a firm believer that writing is one of the best thinking tools around. Human brains are terrible at holding on to lots of discrete information and webbing it all together. Building these behaviors into the organizational culture would embed critical thinking more deeply and democratically across the whole team.
This piece from Barry Ritholtz does a good job breaking down the real background behind the Amazon NYC HQ issues, how they were attracted and why they bailed:
The heart of the opposition to Amazon was how much the city and state bent the existing rules to offer a very generous package. The arguments are pretty clear: On the one side, net net the deal works to the cityâs benefit, and $3 billion is not all that much.
The other side is less pragmatic and more philosophical. It is the same issue I have with taxpayers subsidizing Football stadiums. GBYOFS and stop asking taxpayers to subsidize your businesses and/or hobbies. The gaming of the safety net by Walmart and McDonalds to push their labor costs onto taxpayers. I railed against in during the financial crisis, and afterwards. Same with the Foxconn debacle â yet another example of corporate overreach combined with an ill equipped governor who got rolled. The taxpayers threw him out of office soon after.
What bothers me about the response to this fiasco is that both sides are complicit in the undesirable behavior: Amazon shouldnât need to twist municipal authorities for benefits (nor should stadium-builders or anyone else), but those in the government are the ones responsible for caving and writing the beneficial legislation.
When any one company gets special treatment, its own sets of rules, taxes, incentives, kickbacks, etc., when specific rules apply only to some but not to all, well, that is much better described as Crony Capitalism.
The reactionary response that Amazon is an âevil corporationâ thatâs run by mean billionaires lets a lot of others off the hook for their own bad behavior. Relatedly, the latest EconTalk episode had Duke economist Michael Munger talking about this exact issue.
During this TED talk from 2003, Jeff Bezos compares the Internet revolution to the early years of electrification. Even 15 years ago he was already describing the core philosophy behind his future products, like Amazon Web Services. AWS is like electricity for technology companies: paying the AWS bill is like paying your utility bill.
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics. You simply point AWS Glue to your data stored on AWS, and AWS Glue discovers your data and stores the associated metadata
Interesting new service from AWS (is there a need in computing they donât cover at this point?), providing serverless ETL transformations on datasets hosted anywhere. The automatic discovery is particularly interesting for applications dealing in highly variable data structures.
Patreon is still tiny compared to Kickstarter, where 13 million backers have funded 128,000 successful campaigns, but itâs rapidly growing. Half its patrons and creators joined in the past year, and itâs set to process $150 million in 2017, compared to $100 million total over the past three years.
This is a fascinating company, creating a funding mechanism for independent creators with a different model than the Kickstarter structure.
Google has built their own custom silicon dedicated to AI processing. The power efficiency gains with these dedicated chips is estimated to have saved them from building a dozen new datacenters.
But about six years ago, as the company embraced a new form of voice recognition on Android phones, its engineers worried that this network wasnât nearly big enough. If each of the worldâs Android phones used the new Google voice search for just three minutes a day, these engineers realized, the company would need twice as many data centers.
An excellent read. Their philosophy of experimentation comes through. I liked this bit, on the âvelocityâ of decision making:
Day 2 companies make high-quality decisions, but they make high-quality decisions slowly. To keep the energy and
dynamism of Day 1, you have to somehow make high-quality, high-velocity decisions. Easy for start-ups and very
challenging for large organizations. The senior team at Amazon is determined to keep our decision-making velocity
high. Speed matters in business â plus a high-velocity decision making environment is more fun too. We donât know all
the answers, but here are some thoughts.
First, never use a one-size-fits-all decision-making process. Many decisions are reversible, two-way doors. Those
decisions can use a light-weight process. For those, so what if youâre wrong? I wrote about this in more detail in
last yearâs letter.
Second, most decisions should probably be made with somewhere around 70% of the information you wish you had. If you
wait for 90%, in most cases, youâre probably being slow. Plus, either way, you need to be good at quickly recognizing
and correcting bad decisions. If youâre good at course correcting, being wrong may be less costly than you think,
whereas being slow is going to be expensive for sure.
The Economist analyzes the state of parking economics. The gist: free or low-cost parking equals congestion and more drivers roaming for longer. Some great statistics in this piece:
As San Franciscoâs infuriated drivers cruise around, they crowd the roads and pollute the air. This is a widespread hidden cost of under-priced street parking. Mr. Shoup has estimated that cruising for spaces in Westwood village, in Los Angeles, amounts to 950,000 excess vehicle miles travelled per year. Westwood is tiny, with only 470 metered spaces.
