As we shoot way past 500 petabytes of data stored, we need a lot of helping hands in the data center to keep those hard drives spinning! We’ve been hiring quite a lot, and our latest addition is Jack. Lets learn a bit more about him, shall we?
What is your Backblaze Title?
Data Center Tech
Where are you originally from?
Walnut Creek, CA until 7th grade when the family moved to Durango, Colorado.
What attracted you to Backblaze?
I had heard about how cool the Backblaze community is and have always been fascinated by technology.
What do you expect to learn while being at Backblaze?
I expect to learn a lot about how our data centers run and all of the hardware behind it.
Where else have you worked?
Garrhs HVAC as an HVAC Installer and then Durango Electrical as a Low Volt Technician.
Where did you go to school?
Durango High School and then Montana State University.
What’s your dream job?
I would love to be a driver for the Audi Sport. Race cars are so much fun!
Favorite place you’ve traveled?
Iceland has definitely been my favorite so far.
Of what achievement are you most proud?
Getting my Eagle Scout badge was a tough, but rewarding experience that I will always cherish.
Star Trek or Star Wars?
Coke or Pepsi?
Coke…I know, it’s bad.
Why do you like certain things?
I tend to warm up to things the more time I spend around them, although I never really know until it happens.
Anything else you’d like to tell us?
I’m a friendly car guy who will always be in love with my European cars and I really enjoy the Backblaze community!
We’re happy you joined us Out West! Welcome aboard Jack!
Classic Bond villain, Elon Musk, has a new plan to create a website dedicated to measuring the credibility and adherence to “core truth” of journalists. He is, without any sense of irony, going to call this “Pravda”. This is not simply wrong but evil.
Musk has a point. Journalists do suck, and many suck consistently. I see this in my own industry, cybersecurity, and I frequently criticize them for their suckage.
But what he’s doing here is not correcting them when they make mistakes (or what Musk sees as mistakes), but questioning their legitimacy. This legitimacy isn’t measured by whether they follow established journalism ethics, but whether their “core truths” agree with Musk’s “core truths”.
An example of the problem is how the press fixates on Tesla car crashes due to its “autopilot” feature. Pretty much every autopilot crash makes national headlines, while the press ignores the other 40,000 car crashes that happen in the United States each year. Musk spies on Tesla drivers (hello, classic Bond villain everyone) so he can see the dip in autopilot usage every time such a news story breaks. He’s got good reason to be concerned about this.
He argues that autopilot is safer than humans driving, and he’s got the statistics and government studies to back this up. Therefore, the press’s fixation on Tesla crashes is illegitimate “fake news”, titillating the audience with distorted truth.
But here’s the thing: that’s still only Musk’s version of the truth. Yes, on a mile-per-mile basis, autopilot is safer, but there’s nuance here. Autopilot is used primarily on freeways, which already have a low mile-per-mile accident rate. People choose autopilot only when conditions are incredibly safe and drivers are unlikely to have an accident anyway. Musk is therefore being intentionally deceptive comparing apples to oranges. Autopilot may still be safer, it’s just that the numbers Musk uses don’t demonstrate this.
And then there is the truth calling it “autopilot” to begin with, because it isn’t. The public is overrating the capabilities of the feature. It’s little different than “lane keeping” and “adaptive cruise control” you can now find in other cars. In many ways, the technology is behind — my Tesla doesn’t beep at me when a pedestrian walks behind my car while backing up, but virtually every new car on the market does.
Yes, the press unduly covers Tesla autopilot crashes, but Musk has only himself to blame by unduly exaggerating his car’s capabilities by calling it “autopilot”.
What’s “core truth” is thus rather difficult to obtain. What the press satisfies itself with instead is smaller truths, what they can document. The facts are in such cases that the accident happened, and they try to get Tesla or Musk to comment on it.
What you can criticize a journalist for is therefore not “core truth” but whether they did journalism correctly. When such stories criticize “autopilot”, but don’t do their diligence in getting Tesla’s side of the story, then that’s a violation of journalistic practice. When I criticize journalists for their poor handling of stories in my industry, I try to focus on which journalistic principles they get wrong. For example, the NYTimes reporters do a lot of stories quoting anonymous government sources in clear violation of journalistic principles.
If “credibility” is the concern, then it’s the classic Bond villain here that’s the problem: Musk himself. His track record on business statements is abysmal. For example, when he announced the Model 3 he claimed production targets that every Wall Street analyst claimed were absurd. He didn’t make those targets, he didn’t come close. Model 3 production is still lagging behind Musk’s twice adjusted targets.
So who has a credibility gap here, the press, or Musk himself?
Not only is Musk’s credibility problem ironic, so is the name he chose, “Pravada”, the Russian word for truth that was the name of the Soviet Union Communist Party’s official newspaper. This is so absurd this has to be a joke, yet Musk claims to be serious about all this.
Yes, the press has a lot of problems, and if Musk were some journalism professor concerned about journalists meeting the objective standards of their industry (e.g. abusing anonymous sources), then this would be a fine thing. But it’s not. It’s Musk who is upset the press’s version of “core truth” does not agree with his version — a version that he’s proven time and time again differs from “real truth”.
Just in case Musk is serious, I’ve already registered “www.antipravda.com” to start measuring the credibility of statements by billionaire playboy CEOs. Let’s see who blinks first.
I stole the title, with permission, from this tweet:
Attention, case modders: take a look at the Brutus 2, an extremely snazzy computer case with a partly transparent, animated side panel that’s powered by a Pi. Daniel Otto and Carsten Lehman have a current crowdfunder for the case; their video is in German, but the looks of the build speak for themselves. There are some truly gorgeous effects here.
Vorbestellungen ab sofort auf https://www.startnext.com/brutus2 Weitere Infos zu uns auf: https://3nb.de https://www.facebook.com/3nb.de https://www.instagram.com/3nb.de Über 3nb: – GbR aus Leipzig, gegründet 2017 – wir kommen aus den Bereichen Elektronik und Informatik – erstes Produkt: der Brutus One ein Gaming PC mit transparentem Display in der Seite Kurzinfo Brutus 2: – Markencomputergehäuse für Gaming- /Casemoddingszene – Besonderheit: animiertes Seitenfenster angesteuert mit einem Raspberry Pi – Vorteile von unserem Case: o Case ist einzeln lieferbar und nicht nur als komplett-PC o kein Leistungsverbrauch der Grafikkarte dank integriertem Raspberry Pi o bessere Darstellung von Texten und Grafiken durch unscharfen Hintergrund
What’s case modding?
Case modding just means modifying your computer or gaming console’s case, and it’s very popular in the gaming community. Some mods are functional, while others improve the way the case looks. Lots of dedicated gamers don’t only want a powerful computer, they also want it to look amazing — at home, or at LAN parties and games tournaments.
The Brutus 2 case
The Brutus 2 case is made by Daniel and Carsten’s startup, 3nb electronics, and it’s a product that is officially Powered by Raspberry Pi. Its standout feature is the semi-transparent TFT screen, which lets you play any video clip you choose while keeping your gaming hardware on display. It looks incredibly cool. All the graphics for the case’s screen are handled by a Raspberry Pi, so it doesn’t use any of your main PC’s GPU power and your gaming won’t suffer.
To use Brutus 2, you just need to run a small desktop application on your PC to choose what you want to display on the case. A number of neat animations are included, and you can upload your own if you want.
So far, the app only runs on Windows, but 3nb electronics are planning to make the code open-source, so you can modify it for other operating systems, or to display other file types. This is true to the spirit of the case modding and Raspberry Pi communities, who love adapting, retrofitting, and overhauling projects and code to fit their needs.
Daniel and Carsten say that one of their campaign’s stretch goals is to implement more functionality in the Brutus 2 app. So in the future, the case could also show things like CPU temperature, gaming stats, and in-game messages. Of course, there’s nothing stopping you from integrating features like that yourself.
If you have any questions about the case, you can post them directly to Daniel and Carsten here.
The crowdfunding campaign
The Brutus 2 campaign on Startnext is currently halfway to its first funding goal of €10000, with over three weeks to go until it closes. If you’re quick, you still be may be able to snatch one of the early-bird offers. And if your whole guild NEEDS this, that’s OK — there are discounts for bulk orders.
In 2015, Middlesbrough-based shopkeeper Brian ‘Tomo’ Thompson shot into the headlines after being raided by police and Trading Standards in the UK.
Thompson had been selling “fully-loaded” piracy-configured Kodi boxes from his shop but didn’t think he’d done anything wrong.
“All I want to know is whether I am doing anything illegal. I know it’s a gray area but I want it in black and white,” he said.
Thompson started out with a particularly brave tone. He insisted he’d take the case to Crown Court and even to the European Court. His mission was show what was legal and what wasn’t, he said.
Very quickly, Thompson’s case took on great importance, with observers everywhere reporting on a potential David versus Goliath copyright battle for the ages. But Thompson’s case wasn’t straightforward.
The shopkeeper wasn’t charged with basic “making available” under the Copyrights, Designs and Patents Acts that would have found him guilty under the earlier BREIN v Filmspeler case. Instead, he stood accused of two offenses under section 296ZB of the Copyright, Designs and Patents Act, which deals with devices and services designed to “circumvent technological measures”.
In the end it was all moot. After entering his official ‘not guilty’ plea, last year Thompson suddenly changed his tune. He accepted the prosecution’s version of events, throwing himself at the mercy of the court with a guilty plea.
In October 2017, Teeside Crown Court heard that Thompson cost Sky around £200,000 in lost subscriptions while the shopkeeper made around £38,500 from selling the devices. But despite the fairly big numbers, Judge Peter Armstrong decided to go reasonably light on the 55-year-old, handing him an 18-month prison term, suspended for two years.
“I’ve come to the conclusion that in all the circumstances an immediate custodial sentence is not called for. But as a warning to others in future, they may not be so lucky,” the Judge said.
But things wouldn’t end there for Thompson.
In the UK, people who make money or obtain assets from criminal activity can be forced to pay back their profits, which are then confiscated by the state under the Proceeds of Crime Act (pdf). Almost anything can be taken, from straight cash to cars, jewellery and houses.
However, it appears that whatever cash Thompson earned from Kodi Box activities has long since gone.
During a Proceeds of Crime hearing reported on by Gazette Live, the Court heard that Thompson has no assets whatsoever so any confiscation order would have to be a small one.
In the end, Judge Simon Hickey decided that Thompson should forfeit a single pound, an amount that could increase if the businessman got lucky moving forward.
“If anything changes in the future, for instance if you win the lottery, it might come back,” the Judge said.
With that seeming particularly unlikely, perhaps this will be the end for Thompson. Considering the gravity and importance placed on his case, zero jail time and just a £1 to pay back will probably be acceptable to the 55-year-old and also a lesson to the authorities, who have gotten very little out of this expensive case.
Who knows, perhaps they might sum up the outcome using the same eight-letter word that Thompson can be seen half-covering in this photograph.
Creating these defenses is the goal of NIST’s lightweight cryptography initiative, which aims to develop cryptographic algorithm standards that can work within the confines of a simple electronic device. Many of the sensors, actuators and other micromachines that will function as eyes, ears and hands in IoT networks will work on scant electrical power and use circuitry far more limited than the chips found in even the simplest cell phone. Similar small electronics exist in the keyless entry fobs to newer-model cars and the Radio Frequency Identification (RFID) tags used to locate boxes in vast warehouses.
All of these gadgets are inexpensive to make and will fit nearly anywhere, but common encryption methods may demand more electronic resources than they possess.
If you’re not already familiar with building visualizations for quick access to business insights using Amazon QuickSight, consider this your introduction. In this post, we’ll walk through some common scenarios with sample datasets to provide an overview of how you can connect yuor data, perform advanced analysis and access the results from any web browser or mobile device.
The following visualizations are built from the public datasets available in the links below. Before we jump into that, let’s take a look at the supported data sources, file formats and a typical QuickSight workflow to build any visualization.
Which data sources does Amazon QuickSight support?
At the time of publication, you can use the following data methods:
Connect to AWS data sources, including:
Upload Excel spreadsheets or flat files (CSV, TSV, CLF, and ELF)
Connect to on-premises databases like Teradata, SQL Server, MySQL, and PostgreSQL
Import data from SaaS applications like Salesforce and Snowflake
Use big data processing engines like Spark and Presto
SPICE is the Amazon QuickSight super-fast, parallel, in-memory calculation engine, designed specifically for ad hoc data visualization. SPICE stores your data in a system architected for high availability, where it is saved until you choose to delete it. Improve the performance of database datasets by importing the data into SPICE instead of using a direct database query. To calculate how much SPICE capacity your dataset needs, see Managing SPICE Capacity.
Typical Amazon QuickSight workflow
When you create an analysis, the typical workflow is as follows:
Connect to a data source, and then create a new dataset or choose an existing dataset.
(Optional) If you created a new dataset, prepare the data (for example, by changing field names or data types).
Create a new analysis.
Add a visual to the analysis by choosing the fields to visualize. Choose a specific visual type, or use AutoGraph and let Amazon QuickSight choose the most appropriate visual type, based on the number and data types of the fields that you select.
(Optional) Modify the visual to meet your requirements (for example, by adding a filter or changing the visual type).
(Optional) Add more visuals to the analysis.
(Optional) Add scenes to the default story to provide a narrative about some aspect of the analysis data.
(Optional) Publish the analysis as a dashboard to share insights with other users.
The following graphic illustrates a typical Amazon QuickSight workflow.
Visualizations created in Amazon QuickSight with sample datasets
Data catalog: The DBG PDS project makes real-time data derived from Deutsche Börse’s trading market systems available to the public for free. This is the first time that such detailed financial market data has been shared freely and continually from the source provider.
The following graph shows the market trend of max trade volume for different EU banks. It builds on the data available on XETRA engines, which is made up of a variety of equities, funds, and derivative securities. This graph can be scrolled to visualize trade for a period of an hour or more.
The following graph shows the common stock beating the rest of the maximum trade volume over a period of time, grouped by security type.
Data catalog: Data derived from different sensor stations placed on the city bridges and surface streets are a core information source. The road weather information station has a temperature sensor that measures the temperature of the street surface. It also has a sensor that measures the ambient air temperature at the station each second.
The following graph shows the present max air temperature in Seattle from different RWI station sensors.
The following graph shows the minimum temperature of the road surface at different times, which helps predicts road conditions at a particular time of the year.
Data catalog: Kaggle has come up with a platform where people can donate open datasets. Data engineers and other community members can have open access to these datasets and can contribute to the open data movement. They have more than 350 datasets in total, with more than 200 as featured datasets. It has a few interesting datasets on the platform that are not present at other places, and it’s a platform to connect with other data enthusiasts.
The following graph shows the trending YouTube videos and presents the max likes for the top 20 channels. This is one of the most popular datasets for data engineers.
The following graph shows the YouTube daily statistics for the max views of video titles published during a specific time period.
Data catalog: NYC Open data hosts some very popular open data sets for all New Yorkers. This platform allows you to get involved in dive deep into the data set to pull some useful visualizations. 2016 Green taxi trip dataset includes trip records from all trips completed in green taxis in NYC in 2016. Records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts.
The following graph presents maximum fare amount grouped by the passenger count during a period of time during a day. This can be further expanded to follow through different day of the month based on the business need.
The following graph shows the NewYork taxi data from January 2016, showing the dip in the number of taxis ridden on January 23, 2016 across all types of taxis.
A quick search for that date and location shows you the following news report:
Using Amazon QuickSight, you can see patterns across a time-series data by building visualizations, performing ad hoc analysis, and quickly generating insights. We hope you’ll give it a try today!
Karthik Odapally is a Sr. Solutions Architect in AWS. His passion is to build cost effective and highly scalable solutions on the cloud. In his spare time, he bakes cookies and cupcakes for family and friends here in the PNW. He loves vintage racing cars.
Pranabesh Mandal is a Solutions Architect in AWS. He has over a decade of IT experience. He is passionate about cloud technology and focuses on Analytics. In his spare time, he likes to hike and explore the beautiful nature and wild life of most divine national parks around the United States alongside his wife.
Ever since we introduced our Groups feature, Backblaze for Business has been growing at a rapid rate! We’ve been staffing up in order to support the product and the newest addition to the sales team, Victoria, joins us as a Sales Development Representative! Let’s learn a bit more about Victoria, shall we?
What is your Backblaze Title?
Sales Development Representative.
Where are you originally from?
Harrisburg, North Carolina.
What attracted you to Backblaze?
The leaders and family-style culture.
What do you expect to learn while being at Backblaze?
How to sell, sell, sell!
Where else have you worked?
The North Carolina Autism Society, an ophthalmologist’s office, home health care, and another tech startup.
Where did you go to school?
The University of North Carolina Chapel Hill and Duke University’s Fuqua School of Business.
What’s your dream job?
Fighter pilot, professional snowboarder or killer whale trainer.
Favorite place you’ve traveled?
Hawaii and Banff.
Basketball and cars.
Of what achievement are you most proud?
Missionary work and helping patients feel better.
Star Trek or Star Wars?
Neither, but probably Star Wars.
Coke or Pepsi?
Neither, bubble tea.
Snow crab legs.
Why do you like certain things?
Because God made me that way.
Anything else you’d like you’d like to tell us?
I’m a germophobe, drink a lot of water and unfortunately, am introverted.
Being on the phones all day is a good way to build up those extroversion skills! Welcome to the team and we hope you enjoy learning how to sell, sell, sell!
Car manufacturers, like most companies, navigate a narrow lane between the
benefits of using free and open-source software and the perceived or real
importance of hiding their trade secrets. Many are using
free software in some of the myriad software components that make up a
modern car, and even work in consortia to develop free software. At the
conference, free-software advocate Jeremiah Foster covered progress in the
automotive sector and made an impassioned case for more free software in their
Subscribers can read on for a report on the talk by guest author Andy Oram.
For owners and landlords of pubs and clubs in the UK, providing top-tier sports on TV can be the key to bringing in plenty of thirsty customers.
That being said, the costs of doing so is viewed by many as extortionate, with companies including Sky and BT Sport demanding huge fees for the privilege.
As a result, there is a growing opportunity for people to step in to provide cheaper alternatives. With satellite-type piracy now on the wane, IPTV is now a rising force and there’s no shortage of companies prepared to sell a device and associated subscription service to a landlord for the fraction of Sky’s fees.
That’s where John Dodds, 65, and Jason Richards, 45, stepped in. From 2009 until 2016, the pair were involved in an operation selling such services to a staggering 270 pubs and clubs in the North-East of England.
While Sky could charge thousands per month, the duo allegedly charged customers less than £200 per month. For this fee, they received a set-top box plus a service, which included Premier League soccer and otherwise PPV boxing matches.
According to local sources, the scheme was incredibly lucrative for the pair. Via a fraudulent company, the duo generated revenues of £1.5m, which provided luxury cars and foreign homes.
Unfortunately, however, the business – which at some point was branded ‘Full Effects HD Sports’ – attracted the attention of the Premier League. In common with the movie industry before them, they carried out a private prosecution on the basis the pair were defrauding the organization.
“What the defendants created was their own, highly professional broadcasting service which was being sold to subscribers at a rate designed to undercut any legitimate broadcaster, which they were able to do as they weren’t paying to make any of the programmes or buy from the owners, such as the Premier League,” Prosecutor David Groome told the court.
The court was convinced by the Premier League’s arguments and this morning, before Newcastle Crown Court, the pair were sentenced to four-and-a-half years each in prison.
“This was a sophisticated fraud committed against numerous broadcasters throughout the world and those who have interests in the contents of broadcasts, particularly the Football Association, Premier League,” the judge said, as quoted by Sunderland Echo.
“You both knew perfectly well you were engaged in fraud because you knew the broadcasters were not being paid any or any appropriate fee for the use of their broadcasts. You were able to mislead customers, tell them that the services were lawful for them to use when you knew they were not.”
Unfortunately for the duo’s customers, a number of publicans who bought the service were also sued or prosecuted, which the judge noted could have negative consequences in relation to their future suitability to hold a liquor license.
“This is a hugely significant judgment as it provides further evidence that selling these devices is illegal and can result in a prison sentence,” said Premier League director of legal services Kevin Plumb.
“We hope this verdict gets the message out that selling or using these devices is simply not worth the risk.”
Are you planning to attend Mobile World Congress 2018 in Barcelona (one of my favorite cities)? If so, please be sure to check out the connected car demo in Hall 5 Booth 5E41.
The AWS Greengrass team has been working on a proof of concept with our friends at Vodafone and Saguna to show you how connected cars can change the automotive industry. The demo is built around the emerging concept of multi-access edge computing, or MEC.
Car manufacturers want to provide advanced digital technology in their vehicles but don’t want to make significant upgrades to the on-board computing resources due to cost, power, and time-to-market considerations, not to mention the issues that arise when attempting to retrofit cars that are already on the road. MEC offloads processing resources to the edge of the mobile network, for instance a hub site in the access network. This model helps car manufacturers to take advantage of low-latency compute resources while building features that can evolve and improve over the lifetime of the vehicle, often 20 years or more. It also reduces the complexity and the cost of the on-board components.
The MWC demo streams a live video feed over Vodafone’s 4G LTE network, with Saguna’s AI-powered MEC solution that leverages AWS Greengrass. The demo focuses on driver safety, with the goal of helping to detect drivers that are distracted by talking to someone or something in the car. With an on-board camera aimed at the driver, backed up by AI-powered movement tracking and pattern detection running at the edge of the mobile network, distractions can be identified and the driver can be alerted. This architecture also allows manufacturers to enhance existing cars since most of the computing is handled at the edge of the mobile network.
If you couldn’t make it to Mobile World Congress, you can also check out the video for this solution, here.
I’m running a game jam, and this announcement is before the jam starts! What a concept!
The idea is simple: you have all of February to make a horny game.
(This jam is, as you may have guessed, NSFW. 🔞)
I think there’s a lot of interesting potential at the intersection of sex and games, but we see very little exploration of it — in large part because mega-platforms like Steam (and its predecessor, Walmart) have historically been really squeamish about anything sexual. Unless it’s scantily-clad women draped over everything, that’s fine. But un-clad women are right out. Also gratuitous high-definition gore is cool. But no nipples!!
The result is a paltry cultural volume of games about sex, but as boundaries continue to be pushed without really being broken, we get more and more blockbuster games with sex awkwardly tacked on top as lazy titillation. “Ah, it’s a story-driven role-playing shooter, but in this one part you can have sex, which will affect nothing and never come up again, but you can see a butt!” Truly revolutionary.
The opposite end of the spectrum also exists, in the form of porn games where the game part is tacked on to make something interactive — you know, click really fast to make clothes fall off or whatever. It’s not especially engaging, but it’s more compelling than staring at a JPEG.
So my secret motive here is to encourage people to explore the vast gulf in the middle — to make games that are interesting as games and that feature sexuality as a fundamental part of the game. Something where both parts could stand alone, yet are so intertwined as to be inseparable.
The one genre that is seeing a lot of experimentation is the raunchy visual novel, which is a great example: they tend to tell stories where sexuality plays a heavy part, but they’re still compelling interactive stories and hold up on those grounds just as well. What, I wonder, would this same sort of harmony look like for other genres, other kinds of interaction? What does a horny racing game look like, or a horny inventory-horror game, or a horny brawler? Hell, why are there no horny co-op games to speak of? That seems obvious, right?
I haven’t said all this on the jam page because it would add half a dozen paragraphs to what is already a lengthy document. I also suspect that I’ll sound like I’m suggesting “a racing game but all the cars are dicks,” which isn’t quite right, and I’d need to blather even more to clarify. Anyway, it seems vaguely improper as the jam organizer to be telling people what kind of games not to make; last year I just tried to lead by example by making fox flux.
If exploring this design space seems interesting to you, please do join in! If you’ve never made a game before, this might be a great opportunity to give it a try — everything is going to be embarrassing and personal regardless. Maybe hop on Discord if you need help or want a teammate. Feel free to flip through last year’s entries, too, or my (super nsfw) thread where I played some and talked about them. Some of them are even open source, cough, cough.
Andre Miron’s Pinewood Derby Instant Replay System (sorry, not sorry for the pun in the title) uses a Raspberry Pi to monitor the finishing line and play back a slow-motion instant replay, putting an end to “No, I won!” squabbles once and for all.
This is the same system I demo in this video (https://youtu.be/-QyMxKfBaAE), but on our actual track with real pinewood derby cars. Glad to report that it works great!
For those unfamiliar with the term, the Pinewood Derby is a racing event for Cub Scouts in the USA. Cub Scouts, often with the help of a guardian, build race cars out of wood according to rules regarding weight, size, materials, etc.
The Cubs then race their cars in heats, with the winners advancing to district and council races.
Andre’s Instant Replay System registers the race cars as they cross the finishing line, and it plays back slow-motion video of the crossing on a monitor. As he explains on YouTube:
The Pi is recording a constant stream of video, and when the replay is triggered, it records another half-second of video, then takes the last second and a half and saves it in slow motion (recording is done at 90 fps), before replaying.
The build also uses an attached Arduino, connected to GPIO pin 5, to trigger the recording and playback as it registers the passing cars via a voltage splitter. Additionally, the system announces the finishing places on a rather attractive-looking display above the finishing line.
The result? No more debate about whose car crossed the line first in neck-and-neck races.
Build your own
Andre takes us through the physical setup of the build in the video below, and you’ll find the complete code pasted in the description of the video here. Thanks, Andre!
See the system on our actual track here: https://youtu.be/B3lcQHWGq88 Raspberry Pi based instant replay system, triggered by Arduino Pinewood Derby Timer. The Pi uses GPIO pin 5 attached to a voltage splitter on Arduino output 11 (and ground-ground) to detect when a car crosses the finish line, which triggers the replay.
Digital making in your club
If you’re a member of an various after-school association such as the Scouts or Guides, then using the Raspberry Pi and our free project resources, or visiting a Code Club or CoderDojo, are excellent ways to work towards various badges and awards. So talk to your club leader to discover all the ways in which you can incorporate digital making into your club!
Last week I attended a talk given by Bryan Mistele, president of Seattle-based INRIX. Bryan’s talk provided a glimpse into the future of transportation, centering around four principle attributes, often abbreviated as ACES:
Autonomous – Cars and trucks are gaining the ability to scan and to make sense of their environments and to navigate without human input.
Connected – Vehicles of all types have the ability to take advantage of bidirectional connections (either full-time or intermittent) to other cars and to cloud-based resources. They can upload road and performance data, communicate with each other to run in packs, and take advantage of traffic and weather data.
Electric – Continued development of battery and motor technology, will make electrics vehicles more convenient, cost-effective, and environmentally friendly.
Shared – Ride-sharing services will change usage from an ownership model to an as-a-service model (sound familiar?).
Individually and in combination, these emerging attributes mean that the cars and trucks we will see and use in the decade to come will be markedly different than those of the past.
On the Road with AWS AWS customers are already using our AWS IoT, edge computing, Amazon Machine Learning, and Alexa products to bring this future to life – vehicle manufacturers, their tier 1 suppliers, and AutoTech startups all use AWS for their ACES initiatives. AWS Greengrass is playing an important role here, attracting design wins and helping our customers to add processing power and machine learning inferencing at the edge.
AWS customer Aptiv (formerly Delphi) talked about their Automated Mobility on Demand (AMoD) smart vehicle architecture in a AWS re:Invent session. Aptiv’s AMoD platform will use Greengrass and microservices to drive the onboard user experience, along with edge processing, monitoring, and control. Here’s an overview:
Another customer, Denso of Japan (one of the world’s largest suppliers of auto components and software) is using Greengrass and AWS IoT to support their vision of Mobility as a Service (MaaS). Here’s a video:
AWS at CES The AWS team will be out in force at CES in Las Vegas and would love to talk to you. They’ll be running demos that show how AWS can help to bring innovation and personalization to connected and autonomous vehicles.
Personalized In-Vehicle Experience – This demo shows how AWS AI and Machine Learning can be used to create a highly personalized and branded in-vehicle experience. It makes use of Amazon Lex, Polly, and Amazon Rekognition, but the design is flexible and can be used with other services as well. The demo encompasses driver registration, login and startup (including facial recognition), voice assistance for contextual guidance, personalized e-commerce, and vehicle control. Here’s the architecture for the voice assistance:
Connected Vehicle Solution – This demo shows how a connected vehicle can combine local and cloud intelligence, using edge computing and machine learning at the edge. It handles intermittent connections and uses AWS DeepLens to train a model that responds to distracted drivers. Here’s the overall architecture, as described in our Connected Vehicle Solution:
Digital Content Delivery – This demo will show how a customer uses a web-based 3D configurator to build and personalize their vehicle. It will also show high resolution (4K) 3D image and an optional immersive AR/VR experience, both designed for use within a dealership.
Autonomous Driving – This demo will showcase the AWS services that can be used to build autonomous vehicles. There’s a 1/16th scale model vehicle powered and driven by Greengrass and an overview of a new AWS Autonomous Toolkit. As part of the demo, attendees drive the car, training a model via Amazon SageMaker for subsequent on-board inferencing, powered by Greengrass ML Inferencing.
To speak to one of my colleagues or to set up a time to see the demos, check out the Visit AWS at CES 2018 page.
Some Resources If you are interested in this topic and want to learn more, the AWS for Automotive page is a great starting point, with discussions on connected vehicles & mobility, autonomous vehicle development, and digital customer engagement.
When you are ready to start building a connected vehicle, the AWS Connected Vehicle Solution contains a reference architecture that combines local computing, sophisticated event rules, and cloud-based data processing and storage. You can use this solution to accelerate your own connected vehicle projects.
Daniel Miessler criticizes my writings about IoT security:
I know it’s super cool to scream about how IoT is insecure, how it’s dumb to hook up everyday objects like houses and cars and locks to the internet, how bad things can get, and I know it’s fun to be invited to talk about how everything is doom and gloom.
I absolutely respect Bruce Schneier a lot for what he’s contributed to InfoSec, which makes me that much more disappointed with this kind of position from him.
InfoSec is full of those people, and it’s beneath people like Bruce to add their voices to theirs. Everyone paying attention already knows it’s going to be a soup sandwich — a carnival of horrors — a tragedy of mistakes and abuses of trust.
It’s obvious. Not interesting. Not novel. Obvious. But obvious or not, all these things are still going to happen.
I actually agree with everything in his essay. “We should obviously try to minimize the risks, but we don’t do that by trying to shout down the entire enterprise.” Yes, definitely.
I don’t think the IoT must be stopped. I do think that the risks are considerable, and will increase as these systems become more pervasive and susceptible to class breaks. And I’m trying to write a book that will help navigate this. I don’t think I’m the prophet of doom, and don’t want to come across that way. I’ll give the manuscript another read with that in mind.
The security of pretty much every computer on the planet has just gotten a lot worse, and the only real solution — which of course is not a solution — is to throw them all away and buy new ones.
On Wednesday, researchersjustannouncedaseries of major security vulnerabilities in the microprocessors at the heart of the world’s computers for the past 15-20 years. They’ve been named Spectre and Meltdown, and they have to do with manipulating different ways processors optimize performance by rearranging the order of instructions or performing different instructions in parallel. An attacker who controls one process on a system can use the vulnerabilities to steal secrets elsewhere on the computer. (The research papers are here and here.)
This means that a malicious app on your phone could steal data from your other apps. Or a malicious program on your computer — maybe one running in a browserwindow from that sketchy site you’re visiting, or as a result of a phishing attack — can steal data elsewhere on your machine. Cloud services, which often share machines amongst several customers, are especially vulnerable. This affects corporate applications running on cloud infrastructure, and end-user cloud applications like Google Drive. Someone can run a process in the cloud and steal data from every other users on the same hardware.
Information about these flaws has been secretly circulating amongst the major IT companies for months as they researched the ramifications and coordinated updates. The details were supposed to be released next week, but the story broke early and everyone is scrambling. By now all the major cloud vendors have patched their systems against the vulnerabilities that can be patched against.
“Throw it away and buy a new one” is ridiculous security advice, but it’s what US-CERT recommends. It is also unworkable. The problem is that there isn’t anything to buy that isn’t vulnerable. Pretty much every major processor made in the past 20 years is vulnerable to some flavor of these vulnerabilities. Patching against Meltdown can degrade performance by almost a third. And there’s no patch for Spectre; the microprocessors have to be redesigned to prevent the attack, and that will take years. (Here’s a running list of who’s patched what.)
This is bad, but expect it more and more. Several trends are converging in a way that makes our current system of patching security vulnerabilities harder to implement.
The first is that these vulnerabilities affect embedded computers in consumer devices. Unlike our computer and phones, these systems are designed and produced at a lower profit margin with less engineering expertise. There aren’t security teams on call to write patches, and there often aren’t mechanisms to push patches onto the devices. We’re already seeing this with home routers, digital video recorders, and webcams. The vulnerability that allowed them to be taken over by the Mirai botnet last August simply can’t be fixed.
The second is that some of the patches require updating the computer’s firmware. This is much harder to walk consumers through, and is more likely to permanently brick the device if something goes wrong. It also requires more coordination. In November, Intel released a firmware update to fix a vulnerability in its Management Engine (ME): another flaw in its microprocessors. But it couldn’t get that update directly to users; it had to work with the individual hardware companies, and some of them just weren’t capable of getting the update to their customers.
We’re already seeing this. Some patches require users to disable the computer’s password, which means organizations can’t automate the patch. Some antivirus software blocks the patch, or — worse — crashes the computer. This results in a three-step process: patch your antivirus software, patch your operating system, and then patch the computer’s firmware.
The final reason is the nature of these vulnerabilities themselves. These aren’t normal software vulnerabilities, where a patch fixes the problem and everyone can move on. These vulnerabilities are in the fundamentals of how the microprocessor operates.
It shouldn’t be surprising that microprocessor designers have been building insecure hardware for 20 years. What’s surprising is that it took 20 years to discover it. In their rush to make computers faster, they weren’t thinking about security. They didn’t have the expertise to find these vulnerabilities. And those who did were too busy finding normal software vulnerabilities to examine microprocessors. Security researchers are starting to look more closely at these systems, so expect to hear about more vulnerabilities along these lines.
Spectre and Meltdown are pretty catastrophic vulnerabilities, but they only affect the confidentiality of data. Now that they — and the research into the Intel ME vulnerability — have shown researchers where to look, more is coming — and what they’ll find will be worse than either Spectre or Meltdown. There will be vulnerabilities that will allow attackers to manipulate or delete data across processes, potentially fatal in the computers controlling our cars or implanted medical devices. These will be similarly impossible to fix, and the only strategy will be to throw our devices away and buy new ones.
This isn’t to say you should immediately turn your computers and phones off and not use them for a few years. For the average user, this is just another attack method amongst many. All the major vendors are working on patches and workarounds for the attacks they can mitigate. All the normal security advice still applies: watch for phishing attacks, don’t click on strange e-mail attachments, don’t visit sketchy websites that might run malware on your browser, patch your systems regularly, and generally be careful on the Internet.
You probably won’t notice that performance hit once Meltdown is patched, except maybe in backup programs and networking applications. Embedded systems that do only one task, like your programmable thermostat or the computer in your refrigerator, are unaffected. Small microprocessors that don’t do all of the vulnerable fancy performance tricks are unaffected. Browsers will figure out how to mitigate this in software. Overall, the security of the average Internet-of-Things device is so bad that this attack is in the noise compared to the previously known risks.
It’s a much bigger problem for cloud vendors; the performance hit will be expensive, but I expect that they’ll figure out some clever way of detecting and blocking the attacks. All in all, as bad as Spectre and Meltdown are, I think we got lucky.
But more are coming, and they’ll be worse. 2018 will be the year of microprocessor vulnerabilities, and it’s going to be a wild ride.
For as long as piracy has been mainstream, people have tried to find ways to monetize the system. While many have had good intentions, only models focusing on the negative (copyright trolling, for example) have enjoyed any level of success.
Blockchain startup White Rabbit is hoping to buck that trend but it’s not going to be easy. Then again, nothing worthwhile is, so what do they have to offer?
White Rabbit begins with the assumption that while they love their pirate sites, a many as 60% of pirates would happily reward creators if it was made easy enough. The startup deals with this by inviting pirates to carry on using the kinds of unauthorized sites and services they’re using already, but with a twist.
By installing the White Rabbit browser plug-in, the company will be able to see what content the user is accessing. It will then attempt to match that download to deals it’s made with the companies behind those movies or TV shows. They’ll then get paid a set amount.
“White Rabbit is a content ecosystem accessed through a plugin that recognizes the film and series you stream. The streaming sites are P2P or open server, meaning users can choose where they want to stream,” White Rabbit CEO Alan R. Milligan informs TF.
“We already have a library of films that have won and been nominated for Oscars, Cannes, Berlin and Venice film festival best film prizes – but will continue adding more films and series as we near launch.”
It’s envisioned that this mechanism will prove popular with reluctant pirates since instead of paying Netflix, Amazon, and dozens of other services, users can pay for content through one channel. And, since White Rabbit uses blockchain technology, rights holders can be ensured complete financial transparency, with user payments going straight to them without delay, cutting out the middleman.
“Users are anonymous but can offer filmmakers, artists or other content right holders (investors, distributors, sales agents) our tokens (WRT) as good faith that they are willing to pay for the content. Should the rights holders accept, we enter into a contract with the rights holder that allows them to receive revenue – and accept P2P streaming. We find, and research shows, that most people that are forced to piracy [do so] because they are just not able to access content,” Milligan adds.
White Rabbit’s CEO, who is a filmmaker himself, also sees opportunities to bring fans and filmmakers closer together. Once users have paid for content, they continue to get access via something called the Rabbit Hole, an interface which provides extras that are normally found on a DVD, such as deleted scenes etc.
The team behind White Rabbit describe themselves as “responsible rebels” hoping to spark a revolution. While that’s clearly the goal, by any measure there is a mountain to climb, not least on the content front.
When TorrentFreak first started speaking with the startup in October last year, we were told they were “closing in on 500 films” with contracts, although they wouldn’t elaborate on who might be on board. Nevertheless, that is quite a lot of movies, especially given the mainstream studios’ hatred of pirate sites and anything they might be involved in.
However, subsequent discussion suggests that those with more niche tastes might be White Rabbit’s initial target audience.
“I believe timing is of big relevance and right now a lot of producers are scared of where they´re going to go now that Netflix is enforcing its 50/50 policy. There are also so many amazing films out there that get no or little digital distribution at all,” Milligan says.
“As a Norwegian film producer there is little chance of the film being streamed in my home country – even if we won awards in Cannes and Venice. My latest film Valley of Shadows got US digital distribution, but in Norway – nada.
“My colleagues around the world are suffering the same way, not to mention all the fans who cant watch local films and series. So the indie part of the industry – which is most of us (and still representing 20-30% of cinema sales) – are very ready for change.”
But while indie producers could benefit nicely from White Rabbit, Milligan highlights problems that the big studios have, and suggests that they might like to see the startup succeed too.
“The studios will likely want to see our business model work – but they also have a problem with Netflix which has become a studio. So they´re competitors now, but Netflix has a 100M subscriber advantage. Will they all break out and create each their streaming site for their content only? That would be terrible for fans,” he notes.
That would indeed be a huge problem and it’s an issue we’ve raised here on TF on several occasions. However, if White Rabbit is to succeed, it needs to overcome significant hurdles. We raised just a handful of these with its CEO. First up, Partner Streaming Sites (PSS).
PSS sites appear to be pirate sites that will partner with White Rabbit, so the latter can tap into the formers’ userbases. When White Rabbit users stream ‘pirate’ content from a PSS, that content will be monetized, with the creator getting paid quickly and transparently. At that point, it seems, the content will become non-infringing.
But while that sounds intriguing in theory, plenty of questions remain. White Rabbit says it will share “up to $1M” from its token sale “with the most innovative, brand conscious, film and series loving streaming sites either already out there, planned or about to launch.”
The start-up says the best projects could get $100,000 each but, since its goal is to convert pirates, that necessarily means doing business with pirate sites.
So we asked; how will it be possible to do business with people that are regularly described as criminals? How will it then become possible to secure deals with filmmakers that will undoubtedly come under huge pressure from industry players not to participate in the White Rabbit scheme?
“What we are trying to do is to change digital distribution to everyone´s benefit. We have no interest in financing illegal content, we are interested in spurring innovation in streaming, access for fans and due payment for the rights holders,” Milligan explains.
“That´s what PSS can help us achieve using the WRT (White Rabbit Token) – that helps us find out who wants to be part of this model. No revenue exchanges hands until rights holders accept the token. What is important for rights holders is that we generate more revenue for them than current business models, and we haven´t even included the Rabbit Hole revenue yet.”
So what happens if a White Rabbit user tries to stream something that isn’t part of the program? According to Milligan, PSS sites must remove the content and let White Rabbit users know they must get the content legally elsewhere.
Clearly, the vast majority of pirate site users aren’t White Rabbit users now, nor will they be so in the future, so the removal of content is massively counter-productive for pirate sites. Indeed, it’s this reluctance to take down infringing content that causes them most of their problems.
So, hypothetically, what happens when the operators of streaming site X (that previously partnered with White Rabbit) get arrested and their site shut down for distributing Hollywood content that isn’t part of the program?
“PSS´s would never distribute illegal content, we are offering an opportunity to monetize. We are allowing a platform to those that see monetized P2P as beneficial to their income stream,” Milligan says.
“Hollywood is tricky though, I admit. The proof is in the pudding, so if we have to prove the value through indie and arthouse films first that´s OK. That is still 30% of the multi-billion dollar film market, so we are OK to start with that.”
The final issue is the price and where revenue goes. White Rabbit envisions a user paying $2 for film and $1 for a TV show, although producers are free to set their own price. That means 11 TV shows or five movies per month, given the Netflix model/budget of roughly $11.00 for the same period.
Revenue generated would then be split, with 75% going to the rightsholders, 15% to White Rabbit, and 10% to PSS sites. There’s also a provision for non-PSS sites to be a part of the program, but they would only get 5%, with the remaining 5% going to White Rabbit.
With an incredibly ambitious project like this, it’s easy to find reasons why it might not succeed or even fail to get off the ground. But the team behind the operation have lots of experience in relevant fields and from what we’ve seen are putting considerable effort into getting things moving, as their white paper (pdf) explains.
Currently, White Rabbit is seeking conversation with prospective Partner Streaming Sites, who will provide the content on which White Rabbit will survive. It will certainly be interesting to see which sites put themselves forward for consideration.
This is one of those projects that raises a dizzying volume of questions, with each living up to their billing as part of the Rabbit Hole. The big question is whether the Rabbit Hole will eventually lead to Wonderland or will render everyone who ventures inside feeling surreal and disorientated.
During Q4, Backblaze deployed 100 petabytes worth of Seagate hard drives to our data centers. The newly deployed Seagate 10 and 12 TB drives are doing well and will help us meet our near term storage needs, but we know we’re going to need more drives — with higher capacities. That’s why the success of new hard drive technologies like Heat-Assisted Magnetic Recording (HAMR) from Seagate are very relevant to us here at Backblaze and to the storage industry in general. In today’s guest post we are pleased to have Mark Re, CTO at Seagate, give us an insider’s look behind the hard drive curtain to tell us how Seagate engineers are developing the HAMR technology and making it market ready starting in late 2018.
What is HAMR and How Does It Enable the High-Capacity Needs of the Future?
Guest Blog Post by Mark Re, Seagate Senior Vice President and Chief Technology Officer
Earlier this year Seagate announced plans to make the first hard drives using Heat-Assisted Magnetic Recording, or HAMR, available by the end of 2018 in pilot volumes. Even as today’s market has embraced 10TB+ drives, the need for 20TB+ drives remains imperative in the relative near term. HAMR is the Seagate research team’s next major advance in hard drive technology.
HAMR is a technology that over time will enable a big increase in the amount of data that can be stored on a disk. A small laser is attached to a recording head, designed to heat a tiny spot on the disk where the data will be written. This allows a smaller bit cell to be written as either a 0 or a 1. The smaller bit cell size enables more bits to be crammed into a given surface area — increasing the areal density of data, and increasing drive capacity.
It sounds almost simple, but the science and engineering expertise required, the research, experimentation, lab development and product development to perfect this technology has been enormous. Below is an overview of the HAMR technology and you can dig into the details in our technical brief that provides a point-by-point rundown describing several key advances enabling the HAMR design.
As much time and resources as have been committed to developing HAMR, the need for its increased data density is indisputable. Demand for data storage keeps increasing. Businesses’ ability to manage and leverage more capacity is a competitive necessity, and IT spending on capacity continues to increase.
History of Increasing Storage Capacity
For the last 50 years areal density in the hard disk drive has been growing faster than Moore’s law, which is a very good thing. After all, customers from data centers and cloud service providers to creative professionals and game enthusiasts rarely go shopping looking for a hard drive just like the one they bought two years ago. The demands of increasing data on storage capacities inevitably increase, thus the technology constantly evolves.
According to the Advanced Storage Technology Consortium, HAMR will be the next significant storage technology innovation to increase the amount of storage in the area available to store data, also called the disk’s “areal density.” We believe this boost in areal density will help fuel hard drive product development and growth through the next decade.
Why do we Need to Develop Higher-Capacity Hard Drives? Can’t Current Technologies do the Job?
Why is HAMR’s increased data density so important?
Data has become critical to all aspects of human life, changing how we’re educated and entertained. It affects and informs the ways we experience each other and interact with businesses and the wider world. IDC research shows the datasphere — all the data generated by the world’s businesses and billions of consumer endpoints — will continue to double in size every two years. IDC forecasts that by 2025 the global datasphere will grow to 163 zettabytes (that is a trillion gigabytes). That’s ten times the 16.1 ZB of data generated in 2016. IDC cites five key trends intensifying the role of data in changing our world: embedded systems and the Internet of Things (IoT), instantly available mobile and real-time data, cognitive artificial intelligence (AI) systems, increased security data requirements, and critically, the evolution of data from playing a business background to playing a life-critical role.
Consumers use the cloud to manage everything from family photos and videos to data about their health and exercise routines. Real-time data created by connected devices — everything from Fitbit, Alexa and smart phones to home security systems, solar systems and autonomous cars — are fueling the emerging Data Age. On top of the obvious business and consumer data growth, our critical infrastructure like power grids, water systems, hospitals, road infrastructure and public transportation all demand and add to the growth of real-time data. Data is now a vital element in the smooth operation of all aspects of daily life.
All of this entails a significant infrastructure cost behind the scenes with the insatiable, global appetite for data storage. While a variety of storage technologies will continue to advance in data density (Seagate announced the first 60TB 3.5-inch SSD unit for example), high-capacity hard drives serve as the primary foundational core of our interconnected, cloud and IoT-based dependence on data.
HAMR Hard Drive Technology
Seagate has been working on heat assisted magnetic recording (HAMR) in one form or another since the late 1990s. During this time we’ve made many breakthroughs in making reliable near field transducers, special high capacity HAMR media, and figuring out a way to put a laser on each and every head that is no larger than a grain of salt.
The development of HAMR has required Seagate to consider and overcome a myriad of scientific and technical challenges including new kinds of magnetic media, nano-plasmonic device design and fabrication, laser integration, high-temperature head-disk interactions, and thermal regulation.
A typical hard drive inside any computer or server contains one or more rigid disks coated with a magnetically sensitive film consisting of tiny magnetic grains. Data is recorded when a magnetic write-head flies just above the spinning disk; the write head rapidly flips the magnetization of one magnetic region of grains so that its magnetic pole points up or down, to encode a 1 or a 0 in binary code.
Increasing the amount of data you can store on a disk requires cramming magnetic regions closer together, which means the grains need to be smaller so they won’t interfere with each other.
Heat Assisted Magnetic Recording (HAMR) is the next step to enable us to increase the density of grains — or bit density. Current projections are that HAMR can achieve 5 Tbpsi (Terabits per square inch) on conventional HAMR media, and in the future will be able to achieve 10 Tbpsi or higher with bit patterned media (in which discrete dots are predefined on the media in regular, efficient, very dense patterns). These technologies will enable hard drives with capacities higher than 100 TB before 2030.
The major problem with packing bits so closely together is that if you do that on conventional magnetic media, the bits (and the data they represent) become thermally unstable, and may flip. So, to make the grains maintain their stability — their ability to store bits over a long period of time — we need to develop a recording media that has higher coercivity. That means it’s magnetically more stable during storage, but it is more difficult to change the magnetic characteristics of the media when writing (harder to flip a grain from a 0 to a 1 or vice versa).
That’s why HAMR’s first key hardware advance required developing a new recording media that keeps bits stable — using high anisotropy (or “hard”) magnetic materials such as iron-platinum alloy (FePt), which resist magnetic change at normal temperatures. Over years of HAMR development, Seagate researchers have tested and proven out a variety of FePt granular media films, with varying alloy composition and chemical ordering.
In fact the new media is so “hard” that conventional recording heads won’t be able to flip the bits, or write new data, under normal temperatures. If you add heat to the tiny spot on which you want to write data, you can make the media’s coercive field lower than the magnetic field provided by the recording head — in other words, enable the write head to flip that bit.
So, a challenge with HAMR has been to replace conventional perpendicular magnetic recording (PMR), in which the write head operates at room temperature, with a write technology that heats the thin film recording medium on the disk platter to temperatures above 400 °C. The basic principle is to heat a tiny region of several magnetic grains for a very short time (~1 nanoseconds) to a temperature high enough to make the media’s coercive field lower than the write head’s magnetic field. Immediately after the heat pulse, the region quickly cools down and the bit’s magnetic orientation is frozen in place.
Applying this dynamic nano-heating is where HAMR’s famous “laser” comes in. A plasmonic near-field transducer (NFT) has been integrated into the recording head, to heat the media and enable magnetic change at a specific point. Plasmonic NFTs are used to focus and confine light energy to regions smaller than the wavelength of light. This enables us to heat an extremely small region, measured in nanometers, on the disk media to reduce its magnetic coercivity,
Moving HAMR Forward
As always in advanced engineering, the devil — or many devils — is in the details. As noted earlier, our technical brief provides a point-by-point short illustrated summary of HAMR’s key changes.
Although hard work remains, we believe this technology is nearly ready for commercialization. Seagate has the best engineers in the world working towards a goal of a 20 Terabyte drive by 2019. We hope we’ve given you a glimpse into the amount of engineering that goes into a hard drive. Keeping up with the world’s insatiable appetite to create, capture, store, secure, manage, analyze, rapidly access and share data is a challenge we work on every day.
With thousands of HAMR drives already being made in our manufacturing facilities, our internal and external supply chain is solidly in place, and volume manufacturing tools are online. This year we began shipping initial units for customer tests, and production units will ship to key customers by the end of 2018. Prepare for breakthrough capacities.
Welcome to our brand new blog post series MQTT 5 – Features and Hidden Gems. Without doubt, the MQTT protocol is the most popular and best received Internet of Things protocol as of today (see the Google Trends Chart below), supporting large scale use cases ranging from Connected Cars, Manufacturing Systems, Logistics, Military Use Cases to Enterprise Chat Applications, Mobile Apps and connecting constrained IoT devices. Of course, with huge amounts of production deployments, the wish list for future versions of the MQTT protocol grew bigger and bigger.
MQTT 5 is by far the most extensive and most feature-rich update to the MQTT protocol specification ever. We are going to explore all hidden gems and protocol features with use case discussion and useful background information – one blog post at a time.
Be sure to read the MQTT Essentials Blog Post series first before diving into our new MQTT 5 series. To get the most out of the new blog posts, it’s important to have a basic understanding of the MQTT 3.1.1 protocol as we are going to highlight key changes as well as all improvements.
If you liked the format, we have fantastic news for you: We’ll release a new MQTT 5 blog post, each one highlighting a specific feature, key change or fun trivia regarding MQTT 5, every Monday. Just subscribe to the weekly newsletter below if you want us to send the articles straight to your inbox.
Let’s have a look at the history of MQTT first: Although the MQTT protocol was invented in 1999, its triumphant march began years later, in 2010, when it was released to the public under a royalty free license as protocol version 3.1. Four years after the initial public release, MQTT 3.1.1 was released as an OASIS and ISO standard in 2014. The 3.1.1 version included predominantly clarifications and minor protocol improvements. At the time of writing (December 2017), the MQTT 5 specification closed its second public review phase at OASIS and is expected to be released in a final version in early 2018.
MQTT 5 Design Goals
The Technical Committee (TC) responsible for specifying and standardizing MQTT at OASIS mastered a balancing act: How to advance the protocol in a way that the protocol would stay as lightweight and easy to use as it was in 3.1.1 and still add features demanded by longtime users without adding unnecessary complexity and without sacrificing performance and scalability.
The goals for the MQTT 5 specification were articulated by the OASIS TC as follows:
Enhancement for scalability and large scale systems
Improved error reporting
Formalize common patterns including capability discovery and request response
Extensibility mechanisms including user properties
Performance improvements and support for small clients
With these goals in mind, the TC managed to specify some extremely useful new features that came from requirements of MQTT 3.1.1 production deployments. The TC also added features back to the standard that sophisticated broker implementations like HiveMQ already provided for MQTT 3.1.1. Popular features like Shared Subscriptions and Time to Live for Messages and Client Sessions are now part of the standard.
An interesting goal of the new specification is the “Enhancement for scalability and large scale systems”. Some new MQTT behaviors allow simple broker implementations to enhance scalability. Enterprise MQTT Brokers like HiveMQ showed that MQTT 3.1.1 is one of the most scalable stateful IoT protocols in the world by benchmarking 10.000.000 MQTT simultaneous connections on cloud infrastructure for a single MQTT broker cluster. The new version of the protocol is designed to make it even easier to scale to immense amounts of concurrent connected clients for brokers.
Trivia: Why Protocol Version 5?
Some readers might ask: Why is the successor of MQTT 3.1.1 called “MQTT 5”?
If you would inspect the CONNECT packet on the wire, you would make an interesting observation: While MQTT 3.1 had the value ‘3’ as protocol version, MQTT 3.1.1 used the value ‘4’. In order to streamline the protocol version on the wire and the official protocol version name, both now use the number 5.
Is it time to upgrade yet?
You might wonder: Should I upgrade yet?
Next week’s blog post will provide a detailed look at this question. If you’d like to receive the next and all upcoming articles directly in your inbox, just use the newsletter subscribe form below.
We hope you enjoyed this first part of the new series. Let us know what you think and what you would like to see in future blog posts in the comment section below.
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The cell phones we carry with us constantly are the most perfect surveillance device ever invented, and our laws haven’t caught up to that reality. That might change soon.
This week, the Supreme Court will hear a case with profound implications on your security and privacy in the coming years. The Fourth Amendment’s prohibition of unlawful search and seizure is a vital right that protects us all from police overreach, and the way the courts interpret it is increasingly nonsensical in our computerized and networked world. The Supreme Court can either update current law to reflect the world, or it can further solidify an unnecessary and dangerous police power.
The case centers on cell phone location data and whether the police need a warrant to get it, or if they can use a simple subpoena, which is easier to obtain. Current Fourth Amendment doctrine holds that you lose all privacy protections over any data you willingly share with a third party. Your cellular provider, under this interpretation, is a third party with whom you’ve willingly shared your movements, 24 hours a day, going back months — even though you don’t really have any choice about whether to share with them. So police can request records of where you’ve been from cell carriers without any judicial oversight. The case before the court, Carpenter v. United States, could change that.
Traditionally, information that was most precious to us was physically close to us. It was on our bodies, in our homes and offices, in our cars. Because of that, the courts gave that information extra protections. Information that we stored far away from us, or gave to other people, afforded fewer protections. Police searches have been governed by the “third-party doctrine,” which explicitly says that information we share with others is not considered private.
The Internet has turned that thinking upside-down. Our cell phones know who we talk to and, if we’re talking via text or e-mail, what we say. They track our location constantly, so they know where we live and work. Because they’re the first and last thing we check every day, they know when we go to sleep and when we wake up. Because everyone has one, they know whom we sleep with. And because of how those phones work, all that information is naturally shared with third parties.
More generally, all our data is literally stored on computers belonging to other people. It’s our e-mail, text messages, photos, Google docs, and more all in the cloud. We store it there not because it’s unimportant, but precisely because it is important. And as the Internet of Things computerizes the rest our lives, even more data will be collected by other people: data from our health trackers and medical devices, data from our home sensors and appliances, data from Internet-connected “listeners” like Alexa, Siri, and your voice-activated television.
All this data will be collected and saved by third parties, sometimes for years. The result is a detailed dossier of your activities more complete than any private investigator – or police officer – could possibly collect by following you around.
The issue here is not whether the police should be allowed to use that data to help solve crimes. Of course they should. The issue is whether that information should be protected by the warrant process that requires the police to have probable cause to investigate you and get approval by a court.
Warrants are a security mechanism. They prevent the police from abusing their authority to investigate someone they have no reason to suspect of a crime. They prevent the police from going on “fishing expeditions.” They protect our rights and liberties, even as we willingly give up our privacy to the legitimate needs of law enforcement.
The third-party doctrine never made a lot of sense. Just because I share an intimate secret with my spouse, friend, or doctor doesn’t mean that I no longer consider it private. It makes even less sense in today’s hyper-connected world. It’s long past time the Supreme Court recognized that a months’-long history of my movements is private, and my e-mails and other personal data deserve the same protections, whether they’re on my laptop or on Google’s servers.
EDITED TO ADD (12/1): Good commentary on the Supreme Court oral arguments.
The collective thoughts of the interwebz
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