jm + google   288

New Google political ad policy
'If the new Google policy was applied by Facebook, nearly every ad running on that platform for #GE2019
[the upcoming UK general election] would have to be pulled (most use custom, lookalike and/or interest-based audience targeting).'
targeting  google  facebook  ads  politics  uk 
20 days ago by jm
Scott Aaronson on Google's quantum supremacy leaked paper
It seems a paper between Google and NASA accidentally leaked a couple of days ago, saying that a group at Google has now achieved quantum computational supremacy with a 53-qubit superconducting device. According to Scott Aaronson, a noted quantum-computation expert, this is a Big Deal and a significant moment in scientific progress:
It’s like, have a little respect for the immensity of what we’re talking about here, and for the terrifying engineering that’s needed to make it reality. Before quantum supremacy, by definition, the QC skeptics can all laugh to each other that, for all the billions of dollars spent over 20+ years, still no quantum computer has even once been used to solve any problem faster than your laptop could solve it, or at least not in any way that depended on its being a quantum computer. In a post-quantum-supremacy world, that’s no longer the case. A superposition involving 250 or 260 complex numbers has been computationally harnessed, using time and space resources that are minuscule compared to 250 or 260.

I keep bringing up the Wright Flyer only because the chasm between what we’re talking about, and the dismissiveness I’m seeing in some corners of the Internet, is kind of breathtaking to me. It’s like, if you believed that useful air travel was fundamentally impossible, then seeing a dinky wooden propeller plane keep itself aloft wouldn’t refute your belief … but it sure as hell shouldn’t reassure you either.
google  programming  quantum-computing  qubits  future  science  qc  history  research 
10 weeks ago by jm
Google release an open-source differential-privacy lib
Differentially-private data analysis is a principled approach that enables organizations to learn from the majority of their data while simultaneously ensuring that those results do not allow any individual's data to be distinguished or re-identified. This type of analysis can be implemented in a wide variety of ways and for many different purposes. For example, if you are a health researcher, you may want to compare the average amount of time patients remain admitted across various hospitals in order to determine if there are differences in care. Differential privacy is a high-assurance, analytic means of ensuring that use cases like this are addressed in a privacy-preserving manner.

Currently, we provide algorithms to compute the following:

Standard deviation
Order statistics (including min, max, and median)
analytics  google  ml  privacy  differential-privacy  aggregation  statistics  obfuscation  approximation  algorithms 
september 2019 by jm
Google Code Review Practices
how Google do code reviews. pretty basic stuff but it's good to have it written down from an authoritative source
google  code-review  prs  pull-requests  best-practices  coding  collaboration 
september 2019 by jm
How YouTube Radicalized Brazil
YouTube’s search and recommendation system appears to have systematically diverted users to far-right and conspiracy channels in Brazil.

A New York Times investigation in Brazil found that, time and again, videos promoted by the site have upended central elements of daily life.

Teachers describe classrooms made unruly by students who quote from YouTube conspiracy videos or who, encouraged by right-wing YouTube stars, secretly record their instructors.

Some parents look to “Dr. YouTube” for health advice but get dangerous misinformation instead, hampering the nation’s efforts to fight diseases like Zika. Viral videos have incited death threats against public health advocates.

And in politics, a wave of right-wing YouTube stars ran for office alongside Mr. Bolsonaro, some winning by historic margins. Most still use the platform, governing the world’s fourth-largest democracy through internet-honed trolling and provocation.

YouTube’s recommendation system is engineered to maximize watchtime, among other factors, the company says, but not to favor any political ideology. The system suggests what to watch next, often playing the videos automatically, in a never-ending quest to keep us glued to our screens.
youtube  politics  brazil  future  grim  engagement  machine-learning  google  zika 
august 2019 by jm
Google Employee Alleges Discrimination Against Pregnant Women in Viral Memo - VICE
“During one conversation with my new manager in which I reiterated an early leave and upcoming bedrest, she told me that she had just listened to an NPR segment that debunked the benefits of bedrest,” she wrote. “She also shared that her doctor had ordered her to take bedrest, but that she ignored the order and worked up until the day before she delivered her son via cesarean section. My manager then emphasized in this same meeting that a management role was no longer guaranteed upon my return from maternity leave, and that she supported my interviewing for other roles at Google.”
pregnancy  life  hr  work  google  peopleops  leaks  bedrest  maternity-leave  career 
august 2019 by jm
David Jeske's answer to Why do some developers at strong companies like Google consider Agile development to be nonsense? - Quora
Wow, this is a great answer. As he notes, the Scrum-style process is flawed for big backend projects:

"This style of short-term planning, direct customer contact, and continuous iteration is well suited to software with a simple core and lots of customer visible features that are incrementally useful. It is not so well suited to software which has a very simple interface and tons of hidden internal complexity, software which isn’t useful until it’s fairly complete, or leapfrog solutions the customer can’t imagine."

And he goes on to come up with something which works better for Google-style projects:

Our highest priority is to increase customer (and programmer) productivity and access to information. Work on the biggest, most frequently used problems you can find, and create the largest net impact. Don’t give the customer what they ask for; understand them, and revolutionize their world.

Developers should create a Google Design Document (a fairly minimal, but structured design doc), explaining the project, what goals it hopes to achieve, and explains why it can’t be done in other ways. This document should be circulated with stakeholders, to get early feedback before the project gets underway. The written record is essential, as it assures there is a clear and agreed understanding of when the project is a success and how it aims to get there.
At all phases of the project, critical design elements for larger components should be concisely explained and captured in a design document.

Innovate in leapfrogs. It’s more important to finish and deploy a leapfrog than to attempt perfection. There is no perfection. Instead be flexible, and plan to constantly reinvent at every level of the stack.

Deliver working software as soon as is reasonably possible, and no sooner. “Dogfood” projects internally before they are shipped externally. Make sure products meet high quality standards before shipping. The quality of the product is more important than the time it takes to achieve it.
agile  architecture  google  scrum  development  coding  projects  project-management  design 
august 2019 by jm
Terrifying thread of Google Maps fails
'This takes you over Hayden Pass Rd. "It’s a real challenging road and a true test of your vehicle and your stamina because the road abounds in twists and turns with wheels sometimes hanging above the precipice."
"There is a very narrow section of shelf road before you get to the top that is very dangerous if icy. There are no rocks to stop you from sliding off the side. This section should not be attempted if there is any ice at all."
I'm a little surprised that Google gave this route to me with no warning. It's also comical to say you can get the drive done in 30 minutes.' [....]

'A couple of years ago I did a drive from Port Headland (Northwest Western Australia) to Perth. When we got onto Nanutarra road (Near Paraburdoo), the maps decided we should take a road that was actually the Lyons River - if we were foreign tourists it would have led us into a spot where we could easily have died. Unfortunately in outback WA, many tourists have experienced this and succumbed to it.'
driving  safety  google-maps  google  mapping  routing  fail  via:danluu 
july 2019 by jm
The New Wilderness (Idle Words)
Our discourse around privacy needs to expand to address foundational questions about the role of automation: To what extent is living in a surveillance-saturated world compatible with pluralism and democracy? What are the consequences of raising a generation of children whose every action feeds into a corporate database? What does it mean to be manipulated from an early age by machine learning algorithms that adaptively learn to shape our behavior?
facebook  google  privacy  future  dystopia  surveillance  society 
june 2019 by jm
New Spam Campaign Controlled by Attackers via DNS TXT Records
Ah, Google, what were you thinking?
When decoded, this string is an URL to Google's public DNS resolve for a particular domain. For example, the above string decodes to[omitted].net&type=TXT.

The attachment's script will use this URL to retrieve the associated domain's TXT record.
A TXT record is a DNS entry that can be used to store textual data. This field is typically used for SPF or DMARC records, but could be used to host any type of textual content.

The nice part about using the Google's DNS resolver is that the information will be returned as JSON, which makes it easy for the malicious script to extract the data it needs.

(via Paul Vixie)
txt  dns  google  resolvers  spam  fail  security  via:paulvixie 
june 2019 by jm
An update on Sunday’s service disruption | Google Cloud Blog
Google posting the most inappropriately upbeat post-mortem I've ever read...
In essence, the root cause of Sunday’s disruption was a configuration change that was intended for a small number of servers in a single region. The configuration was incorrectly applied to a larger number of servers across several neighboring regions, and it caused those regions to stop using more than half of their available network capacity. The network traffic to/from those regions then tried to fit into the remaining network capacity, but it did not. The network became congested, and our networking systems correctly triaged the traffic overload and dropped larger, less latency-sensitive traffic in order to preserve smaller latency-sensitive traffic flows, much as urgent packages may be couriered by bicycle through even the worst traffic jam.

Google’s engineering teams detected the issue within seconds, but diagnosis and correction took far longer than our target of a few minutes. Once alerted, engineering teams quickly identified the cause of the network congestion, but the same network congestion which was creating service degradation also slowed the engineering teams’ ability to restore the correct configurations, prolonging the outage. The Google teams were keenly aware that every minute which passed represented another minute of user impact, and brought on additional help to parallelize restoration efforts.
gcp  google  odd  outages  post-mortems  networking 
june 2019 by jm
What I Learned Trying To Secure Congressional Campaigns (Idle Words)
'on August 22, the DNC had a phishing scare, where they mistook a vulnerability assessment for an actual attack. The next day, DCCC Executive Director Dan Sena sent an email to all campaigns with the subject line "Reminder About Cybersecurity". That email included three attachments, including a file evocatively titled "2-20170712-Falcon.docx".'
politics  security  dnc  democrats  funny  yubikeys  gmail  google  auth  phishing  hacking  congress 
may 2019 by jm
Facebook and Google pressured EU experts to soften fake news regulations, say insiders | openDemocracy
The EU’s expert group met last year as a response to the wildfire spread of fake news and disinformation seen in the Brexit referendum and in the US election of President Donald Trump. Their task was to help prevent the spread of disinformation, particularly at pivotal moments such as this week’s hotly contested European parliamentary elections.

However some of these experts say that representatives of Facebook and Google undermined the work of the group, which was convened by the European Commission and comprised leading European researchers, media entrepreneurs and activists.

In particular, the platforms opposed proposals that would have forced them to be more transparent about their business models. And a number of insiders have raised concerns about how the tech platforms’ funding relationships with experts on the panel may have helped to water down the recommendations.

In the wake of numerous reports of massive disinformation campaigns targeting the European elections, many linked to Russia and to far-right groups, EU politicians and transparency campaigners have called these fresh allegations about the tech platforms’ behaviour a “scandal”.
google  facebook  disinformation  russia  eu  democracy  lobbying 
may 2019 by jm
Federated Learning
Google demonstrates their (extremely cool) privacy-preserving machine learning train/test architecture with a comic
google  comics  ai  ml  federated-learning  privacy  data-protection  encryption  training 
may 2019 by jm
Who’s using your face? The ugly truth about facial recognition
In order to feed this hungry system, a plethora of face repositories — such as IJB-C — have sprung up, containing images manually culled and bound together from sources as varied as university campuses, town squares, markets, cafés, mugshots and social-media sites such as Flickr, Instagram and YouTube.

To understand what these faces have been helping to build, the FT worked with Adam Harvey, the researcher who first spotted Jillian York’s face in IJB-C. An American based in Berlin, he has spent years amassing more than 300 face datasets and has identified some 5,000 academic papers that cite them.

The images, we found, are used to train and benchmark algorithms that serve a variety of biometric-related purposes — recognising faces at passport control, crowd surveillance, automated driving, robotics, even emotion analysis for advertising. They have been cited in papers by commercial companies including Facebook, Microsoft, Baidu, SenseTime and IBM, as well as by academics around the world, from Japan to the United Arab Emirates and Israel.

“We’ve seen facial recognition shifting in purpose,” says Dave Maass, a senior investigative researcher at the EFF, who was shocked to discover that his own colleagues’ faces were in the Iarpa database. “It was originally being used for identification purposes . . . Now somebody’s face is used as a tracking number to watch them as they move across locations on video, which is a huge shift. [Researchers] don’t have to pay people for consent, they don’t have to find models, no firm has to pay to collect it, everyone gets it for free.”
data  privacy  face-recognition  cameras  creative-commons  licensing  flickr  open-data  google  facebook  surveillance  instagram  ijb-c  research  iarpa 
april 2019 by jm
YouTube Executives Ignored Warnings, Let Toxic Videos Run Rampant - Bloomberg
As of 2017, YouTube’s policy for how content moderators handle conspiracy theories didn’t exist, according to a former moderator who specialized in foreign-language content.  At the end of the year, fewer than twenty people were on the staff for “trust and safety,” the unit overseeing content policies, according to a former staffer. The team had to “fight tooth and nail” for more resources from the tech giant, this person said. A YouTube spokeswoman said that the division has grown “significantly” since but declined to share exact numbers.

In February of 2018, the video calling the Parkland shooting victims “crisis actors” went viral on YouTube’s trending page. Policy staff suggested soon after limiting recommendations on the page to vetted news sources. YouTube management rejected the proposal, according to a person with knowledge of the event. The person didn’t know the reasoning behind the rejection, but noted that YouTube was then intent on accelerating its viewing time for videos related to news. 
youtube  google  alphabet  moderation  conspiracy-theories  news  virality  engagement 
april 2019 by jm
Cloud Shell - Google Cloud Platform
I had no idea about this -- every google user has instant in-browser shell access to a Linux VM with 1.7GB of RAM
shell  servers  linux  google  gcp  cloudshell 
march 2019 by jm
The end of open: BBC blocks its podcasts on Google
Talking to Podnews, a BBC spokesperson said that Google is required to sign a licence to link to their podcasts; and that the Distribution Policy also requires Google to supply user data to the BBC. There has been a “consultation with Google”, and the BBC “has no choice but to stop Google from making podcasts available via Google products.”
bbc  facepalm  fail  google  licensing  podcasts  radio 
march 2019 by jm
Thought-provoking thread on Facebook/YouTube content moderation
Extremely thought-provoking thread on the horrors of Facebook/YouTube content moderation, from Andrew Strait:
My time doing this work convinced me there is no ultimate mitigation measure for the mental harm it causes. Automation is not a silver bullet - it requires massive labeled data sets by moderators on a continuing basis to ensure accuracy and proper model fit.

There are steps to make this process less worse, but IMO it all comes back to a basic question - what technologies are worth the incredible human suffering and cost that moderators will inevitably experience? Is image search worth it? Is YouTube? Is Facebook?

I don't have an answer. But these platforms create the need for this kind of horrific work and that must be considered at the forefront of design and deployment of any platform, not as an afterthought.
horror  moderation  youtube  facebook  video  content  mental-health  andrew-strait  image-search  images  labelling  google 
march 2019 by jm
Live Transcribe
Google's new live transcription app -- 'see instant captions anywhere.
Whether you’re ordering a coffee or meeting someone new, Live Transcribe helps you communicate in the moment.'

If this works, it'd be fantastic for the deaf and hard of hearing... nifty!
android  google  deaf  hearing  transcription  accessibility 
february 2019 by jm
Google Hired Gig Economy Workers for Project Maven
Other tech giants are reportedly interested in engaging the military as it continues to deploy artificial intelligence technology. Much larger machine-learning projects may require vastly new engagement from gig economy workers, who may unknowingly engage in the work.

“Workers absolutely should have the right to know what they are working on, and especially when moral or politically controversial activities are involved,” said Juliet Schor, a sociology professor at Boston College, in an email to The Intercept. “It’s a basic dimension of democracy, which should not stop at either the factory or the platform ‘door.’ For too long, the country has tolerated erosion of basic civil rights in the workplace, as corporations assume ever-more control over their workforces. It’s time to win them back.”
google  project-maven  ai  training  labelling  work  ethics  military 
february 2019 by jm
'The goal is to automate us': welcome to the age of surveillance capitalism
“Surveillance capitalism,” she writes, “unilaterally claims human experience as free raw material for translation into behavioural data. Although some of these data are applied to service improvement, the rest are declared as a proprietary behavioural surplus, fed into advanced manufacturing processes known as ‘machine intelligence’, and fabricated into prediction products that anticipate what you will do now, soon, and later. Finally, these prediction products are traded in a new kind of marketplace that I call behavioural futures markets. Surveillance capitalists have grown immensely wealthy from these trading operations, for many companies are willing to lay bets on our future behaviour.”

While the general modus operandi of Google, Facebook et al has been known and understood (at least by some people) for a while, what has been missing – and what Zuboff provides – is the insight and scholarship to situate them in a wider context. She points out that while most of us think that we are dealing merely with algorithmic inscrutability, in fact what confronts us is the latest phase in capitalism’s long evolution – from the making of products, to mass production, to managerial capitalism, to services, to financial capitalism, and now to the exploitation of behavioural predictions covertly derived from the surveillance of users.
advertising  technology  surveillance  facebook  google  adtech  capitalism  business 
january 2019 by jm
slides from "Distributed Log-Processing Design Workshop", SRECon Americas 2018
Fantastic presentation discussing the kinds of design criteria used when architecting a large-scale data processing and storage service. Interesting to see some Google terminology, e.g. "dimensioning" -- ballparking the expected scalability numbers, bandwidth, qps, and limits.
distributed-systems  coding  design  architecture  google  photon  logs  log-storage  slides  srecon 
december 2018 by jm
Google used a Baidu front-end to scrape user searches without consent
The engineers used the data they pulled from [acquired Baidu front-end site] to learn about the kinds of things that people located in mainland China routinely search for in Mandarin. This helped them to build a prototype of Dragonfly. The engineers used the sample queries from, for instance, to review lists of websites Chinese people would see if they typed the same word or phrase into Google. They then used a tool they called “BeaconTower” to check whether any websites in the Google search results would be blocked by China’s internet censorship system, known as the Great Firewall. Through this process, the engineers compiled a list of thousands of banned websites, which they integrated into the Dragonfly search platform so that it would purge links to websites prohibited in China, such as those of the online encyclopedia Wikipedia and British news broadcaster BBC.

Under normal company protocol, analysis of people’s search queries is subject to tight constraints and should be reviewed by the company’s privacy staff, whose job is to safeguard user rights. But the privacy team only found out about the data access after The Intercept revealed it, and were “really pissed,” according to one Google source.
china  search  tech  google  privacy  baidu  interception  censorship  great-firewall  dragonfly 
december 2018 by jm
Google Tried to Patent My Work After a Job Interview
I looked up the patent application and luckily, this time the patent application was still being reviewed by the patent examiner.  It had not issued! The provisional was filed August 29, 2014, months after my first interview and visit back in March 2014.  Two of the inventors listed were the same people who had interviewed me. 

This is frankly appalling behaviour from Google -- total abuse of the patent system. If Joi Ito hadn't been around to mediate this patent probably would have issued and this researcher's life's work stolen from her through IP dirty tricks.

(Also, patents need to die)
patents  software-patents  google  dirty-tricks  interviewing  ip  mit  medialab  paper  jie-qi 
november 2018 by jm
Some notes about HTTP/3
Robert Graham from ErrataSec on QUIC aka HTTP/3:

'Google (pbuh) has both the most popular web browser (Chrome) and the two most popular websites (#1 #2 Therefore, they are in control of future web protocol development.'

Faster connection setup and latency; better bandwidth negotiation when using multiplexing; user-mode stacks by building on UDP and using recvmmsg(); and better mobile support for roaming IPs.
google  http3  quic  protocols  ip 
november 2018 by jm
Google 'betrays patient trust' with DeepMind Health move | Technology | The Guardian

Now that Streams is a Google product itself, that promise appears to have been broken, says privacy researcher Julia Powles: “Making this about semantics is a sleight of hand. DeepMind said it would never connect Streams with Google. The whole Streams app is now a Google product. That is an atrocious breach of trust, for an already beleaguered product.”

A DeepMind spokesperson emphasised that the core of the promise remains intact: “All patient data remains under our partners’ strict control, and all decisions about its use lie with them. This data remains subject to strict audit and access controls and its processing remains subject to both our contracts and data protection legislation. The move to Google does not affect this.”

google  deepmind  health  nhs  data-protection  privacy  healthcare 
november 2018 by jm
Jeff Bezos is wrong, tech workers are not bullies
I decided to leave my job as a staff engineer at Google because of Project Maven, and because I believe that the artificial intelligence ethical guidelines they published afterwards were not strict enough: they allowed surveillance within “internationally accepted norms”.

I am now joining forces with current and former Google employees who also opposed Maven and the Dragonfly search engine. We do not wish to be complicit in human rights violations and we believe that workers, and the public, deserve a voice. We support employees at Amazon, Microsoft, Salesforce, McKinsey and Deloitte who have similarly stood up to their employers.

We also have a right to not contribute to killing. Most workers at Google or Amazon did not join those companies to work on military applications. Both companies are international employers with engineering offices across the world, and many of their workers are neither US citizens nor residents. I worked as an engineer in Google's European headquarters in Dublin, Ireland. To me, the US military is not our military (as Google Cloud chief executive Diane Greene referred to it in a blog post), nor is it a force we should automatically support as a matter of patriotism.

As an engineer, I believe it is my responsibility to speak up for human rights and accountable decision making. As an industry, we in technology cannot compromise our principles or allow ourselves to be bullied by billionaires who stand to be enriched by our silence.
project-maven  dragonfly  google  amazon  surveillance  us-politics  politics  ai  silicon-valley  ethics  work  life 
november 2018 by jm
Your Kid’s Apps Are Crammed With Ads - The New York Times
In apps marketed for children 5 and under in the Google Play store, there were pop-up ads with disturbing imagery. There were ads that no child could reasonably be expected to close out of, and which, when triggered, would send a player into more ads. Dancing treasure chests would give young players points for watching video ads, potentially endlessly. The vast majority of ads were not marked at all. Characters in children’s games gently pressured the kids to make purchases, a practice known as host-selling, banned in children’s TV programs in 1974 by the Federal Trade Commission. At other times an onscreen character would cry if the child did not buy something.

“The first word that comes to mind is furious,” said Dr. Radesky, an assistant professor of developmental behavioral pediatrics at the University of Michigan Medical School. “I’m a researcher. I want to stay objective. We started this study really just trying to look at distraction. My frustrated response is about all the surprising, potentially deceptive stuff we found.”

brb, installing Pi-Hole.
children  kids  ads  advertising  apps  android  google  ftc  games  iap 
october 2018 by jm
ChromeCast HTTP APIs
similar to the Google Home hackable APIs, it seems Chromecasts are easily hacked/scripted with no auth
auth  http  apis  security  chromecast  google 
october 2018 by jm
Google Home (in)Security
0 authentication on some setup APIs, including 'delete the current wifi network config' -- pretty major lack of security
auth  security  fail  google  google-home 
october 2018 by jm
Wild camping spots - Google My Maps
A GMaps version of the list of wild camping spots around Ireland
gmaps  google  mapping  wild-camping  camping  ireland 
october 2018 by jm
Google spent $60 million on building Content ID
That's how much it costs to build a not-particularly-accurate UGC copyright filter:
Google’s new report takes aim at this claim. It asserts that Content ID is a highly effective solution, with over 98 percent of copyright management on YouTube happening through Content ID, and just 2 percent coming from humans filing copyright removal notices. Google also says the music industry opts to monetize more than 95 percent of its copyright claims, meaning they leave the videos up on the service. It claims a whopping half of the music industry's YouTube revenue comes from fan content — covers, remixes, dance versions, etc. — claimed via Content ID. The report also puts a hard figure on how much Google has spent so far on Content ID: $60 million.
filtering  copyright  eu  article-13  copyfight  content-id  google  web  ugc 
september 2018 by jm
Google Online Security Blog: Introducing the Tink cryptographic software library
Tink aims to provide cryptographic APIs that are secure, easy to use correctly, and hard(er) to misuse. Tink is built on top of existing libraries such as BoringSSL and Java Cryptography Architecture, but includes countermeasures to many weaknesses in these libraries, which were discovered by Project Wycheproof, another project from our team.
With Tink, many common cryptographic operations such as data encryption, digital signatures, etc. can be done with only a few lines of code.
tink  google  java  c++  boringssl  ssl  jca  crypto 
august 2018 by jm
This Music Theory Professor Just Showed How Stupid and Broken Copyright Filters Are - Motherboard
Kaiser then decided to test Google’s system more fully. He opened a new YouTube account named Labeltest, and began sharing additional examples of copyright-free music.

“I quickly received Content ID notifications for copyright-free music by Bartok, Schubert, Puccini, and Wagner,” Kaiser said. “Again and again, YouTube told me that I was violating the copyright of these long-dead composers, despite all of my uploads existing in the public domain.”

Google’s Content ID is the result of more than $100 million in investment funds and countless development hours. Yet Kaiser found the system was largely incapable of differentiating between copyrighted music and content in the public domain. And the appeals process that Google has erected to tackle these false claims wasn’t any better.
content-id  copyright  copyright-filtering  youtube  fail  google  public-domain  ip  music  filtering  bartok  schubert  wagner  puccini 
august 2018 by jm
"rsync for cloud storage" - Google Drive, Amazon Drive, S3, Dropbox, Backblaze B2, One Drive, Swift, Hubic, Cloudfiles, Google Cloud Storage, Yandex Files
backup  github  sync  cloud  s3  storage  rsync  rclone  google  aws  dropbox  backblaze  yandex  onedrive 
august 2018 by jm
Google Cloud Platform Blog: Introducing Jib
'build Java Docker images better':
Jib takes advantage of layering in Docker images and integrates with your build system to optimize Java container image builds in the following ways:

Simple - Jib is implemented in Java and runs as part of your Maven or Gradle build. You do not need to maintain a Dockerfile, run a Docker daemon, or even worry about creating a fat JAR with all its dependencies. Since Jib tightly integrates with your Java build, it has access to all the necessary information to package your application. Any variations in your Java build are automatically picked up during subsequent container builds.

Fast - Jib takes advantage of image layering and registry caching to achieve fast, incremental builds. It reads your build config, organizes your application into distinct layers (dependencies, resources, classes) and only rebuilds and pushes the layers that have changed. When iterating quickly on a project, Jib can save valuable time on each build by only pushing your changed layers to the registry instead of your whole application.

Reproducible - Jib supports building container images declaratively from your Maven and Gradle build metadata, and as such can be configured to create reproducible build images as long as your inputs remain the same.
build  google  java  docker  maven  gradle  coding  builds  jars  fat-jars  packaging 
july 2018 by jm
Cory Doctorow: Zuck’s Empire of Oily Rags
the sophisticated targeting systems available through Facebook, Google, Twitter, and other Big Tech ad platforms made it easy to find the racist, xenophobic, fearful, angry people who wanted to believe that foreigners were destroying their country while being bankrolled by George Soros.

Remember that elections are generally knife-edge affairs, even for politicians who’ve held their seats for decades with slim margins: 60% of the vote is an excellent win. Remember, too, that the winner in most races is “none of the above,” with huge numbers of voters sitting out the election. If even a small number of these non-voters can be motivated to show up at the polls, safe seats can be made contestable. In a tight race, having a cheap way to reach all the latent Klansmen in a district and quietly inform them that Donald J. Trump is their man is a game-changer.

Cambridge Analytica are like stage mentalists: they’re doing something labor-intensive and pretending that it’s something supernatural. A stage mentalist will train for years to learn to quickly memorize a deck of cards and then claim that they can name your card thanks to their psychic powers. You never see the unglamorous, unimpressive memorization practice. Cambridge Analytica uses Facebook to find racist jerks and tell them to vote for Trump and then they claim that they’ve discovered a mystical way to get otherwise sensible people to vote for maniacs.
facebook  politics  surveillance  cory-doctorow  google  twitter  advertising  elections  cambridge-analytica  racism  nazis 
july 2018 by jm
This is why you're still seeing referendum ads online
summary: Google can't block ads placed via their own exchanges
advertising  adtech  google  ireland  ads  repealthe8th 
may 2018 by jm
Gravis McElroy on Twitter: "The thing that really kills me about the silicon valley hypercapitalist hell spiral...."
Epic shouty thread about modern Silicon Valley software products.
We know that no company, regardless of size, can be trusted with this information. We KNOW it will not stay private, our photos of our partners genitals and tax documents will become public either deliberately or accidentally.

We know that any company that tries to buck this trend can't be trusted, and even if they are completely, absolutely transparent, it doesn't matter because we will wake up one day to discover they were purchased at 2 AM and the data transfer /already started/

We represent billions in revenue but they hold our info in escrow and that means we don't have enough money to buy their loyalty, because a business considers business money more real than person money.
money  funding  capitalism  silicon-valley  internet  web  google  facebook  banks  banking 
april 2018 by jm
What worries me about AI – François Chollet – Medium
One path leads to a place that really scares me. The other leads to a more humane future. There’s still time to take the better one. If you work on these technologies, keep this in mind. You may not have evil intentions. You may simply not care. You may simply value your RSUs more than our shared future. But whether or not you care, because you have a hand in shaping the infrastructure of the digital world, your choices affect us all. And you may eventually be held responsible for them.
ai  facebook  newsfeed  technology  future  silicon-valley  google 
april 2018 by jm
YouTube, the Great Radicalizer - The New York Times
It seems as if you are never “hard core” enough for YouTube’s recommendation algorithm. It promotes, recommends and disseminates videos in a manner that appears to constantly up the stakes. Given its billion or so users, YouTube may be one of the most powerful radicalizing instruments of the 21st century.
youtube  culture  politics  radicalization  crazy  machine-learning  google  zeynep-tufekci 
march 2018 by jm
The Codex - I Do Not Like Go
Some gripes about Go from this blog, specifically around developer ergonomics (syntax highlighting and language-inherent error detection), politics, packaging and distribution, GOPATH, and the tuple-oriented error handling idiom. As R. I. Pienaar noted, the Go community seems full of "at-Google-wes", which is an excellent way of putting it.
golang  go  criticism  blogs  syntax-highlighting  coding  languages  google  at-google-we 
february 2018 by jm
'Fiction is outperforming reality': how YouTube's algorithm distorts truth
"no matter which political side the researcher started from, the platform pushed pro-Trump, anti-Clinton videos."
youtube  truth  fake-news  conspiracy-theories  google  algorithms  politics  brexit  trump 
february 2018 by jm
OpenCensus: A Stats Collection and Distributed Tracing Framework
Google open sourcing their internal Census lib for service metrics and distributed tracing
google  monitoring  service-metrics  metrics  census  opencensus  open-source  tracing  zipkin  prometheus 
january 2018 by jm
google/highwayhash: Fast strong hash functions: SipHash/HighwayHash
HighwayHash: 'We have devised a new way of mixing inputs with AVX2 multiply and permute instructions. The multiplications are 32x32 -> 64 bits and therefore infeasible to reverse. Permuting equalizes the distribution of the resulting bytes. The internal state occupies four 256-bit AVX2 registers. Due to limitations of the instruction set, the registers are partitioned into two 512-bit halves that remain independent until the reduce phase. The algorithm outputs 64 bit digests or up to 256 bits at no extra cost. In addition to high throughput, the algorithm is designed for low finalization cost. The result is more than twice as fast as SipTreeHash.

We also provide an SSE4.1 version (80% as fast for large inputs and 95% as fast for short inputs), an implementation for VSX on POWER and a portable version (10% as fast). A third-party ARM implementation is referenced below.

Statistical analyses and preliminary cryptanalysis are given in'

(via Tony Finch)
siphash  highwayhash  via:fanf  hashing  hashes  algorithms  mac  google  hash 
january 2018 by jm
Google Maps’s Moat
pretty cool stuff from Google, has to be said
google  maps  apple  tom-tom  data  big-data  ml  mapping 
december 2017 by jm
How Syria's White Helmets became victims of an online propaganda machine | World news | The Guardian
The way the Russian propaganda machine has targeted the White Helmets is a neat case study in the prevailing information wars. It exposes just how rumours, conspiracy theories and half-truths bubble to the top of YouTube, Google and Twitter search algorithms.

“This is the heart of Russian propaganda. In the old days they would try and portray the Soviet Union as a model society. Now it’s about confusing every issue with so many narratives that people can’t recognise the truth when they see it,” said David Patrikarakos, author of War in 140 Characters: How Social Media is Reshaping Conflict in the 21st Century.
propaganda  white-helmets  russia  disinfo  syria  facebook  assad  google  youtube  fud  algorithms 
december 2017 by jm
The Case for Learned Index Structures
'Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, we start from this premise and posit that all existing index structures can be replaced with other types of models, including deep-learning models, which we term learned indexes. The key idea is that a model can learn the sort order or structure of lookup keys and use this signal to effectively predict the position or existence of records. We theoretically analyze under which conditions learned indexes outperform traditional index structures and describe the main challenges in designing learned index structures. Our initial results show, that by using neural nets we are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets. More importantly though, we believe that the idea of replacing core components of a data management system through learned models has far reaching implications for future systems designs and that this work just provides a glimpse of what might be possible.'

Excellent follow-up thread from Henry Robinson:

'The fact that the learned representation is more compact is very neat. But also it's not really a surprise that, given the entire dataset, we can construct a more compact function than a B-tree which is *designed* to support efficient updates.' [...] 'given that the model performs best when trained on the whole data set - I strongly doubt B-trees are the best we can do with the current state-of-the art.'
data-structures  ml  google  b-trees  storage  indexes  deep-learning  henry-robinson 
december 2017 by jm
Fooling Neural Networks in the Physical World with 3D Adversarial Objects · labsix
This is amazingly weird stuff. Fooling NNs with adversarial objects:
Here is a 3D-printed turtle that is classified at every viewpoint as a “rifle” by Google’s InceptionV3 image classifier, whereas the unperturbed turtle is consistently classified as “turtle”.

We do this using a new algorithm for reliably producing adversarial examples that cause targeted misclassification under transformations like blur, rotation, zoom, or translation, and we use it to generate both 2D printouts and 3D models that fool a standard neural network at any angle. Our process works for arbitrary 3D models - not just turtles! We also made a baseball that classifies as an espresso at every angle! The examples still fool the neural network when we put them in front of semantically relevant backgrounds; for example, you’d never see a rifle underwater, or an espresso in a baseball mitt.
ai  deep-learning  3d-printing  objects  security  hacking  rifles  models  turtles  adversarial-classification  classification  google  inceptionv3  images  image-classification 
november 2017 by jm
Google and Facebook Have Failed Us - The Atlantic
There’s no hiding behind algorithms anymore. The problems cannot be minimized. The machines have shown they are not up to the task of dealing with rare, breaking news events, and it is unlikely that they will be in the near future. More humans must be added to the decision-making process, and the sooner the better.
algorithms  facebook  google  las-vegas  news  filtering  hoaxes  4chan  abuse  breaking-news  responsibility  silicon-valley 
october 2017 by jm
Anthony Levandowski has founded an AI religion
In September 2015, the multi-millionaire engineer at the heart of the patent and trade secrets lawsuit between Uber and Waymo, Google’s self-driving car company, founded a religious organization called Way of the Future. Its purpose, according to previously unreported state filings, is nothing less than to “develop and promote the realization of a Godhead based on Artificial Intelligence.”

this article is full of bananas.
google  crazy  uber  waymo  self-driving-cars  cars  religion  way-of-the-future  ai  god 
september 2017 by jm
a new common C++ library from Google, Apache-licensed.
c++  coding  abseil  google  commons  libraries  open-source  asl2  c++17 
september 2017 by jm
How to Easily Unsubscribe from Bulk Emails in Gmail - Alternative
nice Google Script which runs in the background and scrapes out unsubscribe links. I'm drowning in single-opt-in mainsleaze newsletters at this stage so this is very welcome
mainsleaze  unsubscribe  spam  gmail  google  email  one-bite-of-the-apple 
august 2017 by jm
Going Multi-Cloud with AWS and GCP: Lessons Learned at Scale
Metamarkets splits across AWS and GCP, going into heavy detail here
aws  gcp  google  ops  hosting  multi-cloud 
august 2017 by jm
Allen curve - Wikipedia
During the late 1970s, [Professor Thomas J.] Allen undertook a project to determine how the distance between engineers’ offices affects the frequency of technical communication between them. The result of that research, produced what is now known as the Allen Curve, revealed that there is a strong negative correlation between physical distance and the frequency of communication between work stations. The finding also revealed the critical distance of 50 meters for weekly technical communication.

With the fast advancement of internet and sharp drop of telecommunication cost, some wonder the observation of Allen Curve in today's corporate environment. In his recently co-authored book, Allen examined this question and the same still holds true. He says[2]

"For example, rather than finding that the probability of telephone communication increases with distance, as face-to-face probability decays, our data show a decay in the use of all communication media with distance (following a "near-field" rise)." [p. 58]

Apparently a few years back in Google, some staff mined the promotion data, and were able to show a Allen-like curve that proved a strong correlation between distance from Jeff Dean's desk, and time to getting promoted.
jeff-dean  google  history  allen-curve  work  communication  distance  offices  workplace  teleworking  remote-work 
august 2017 by jm provide non standard time · Issue #437 · systemd/systemd
Google ask systemd not to use due to nonstandard ticking behaviour; systemd dev tells them to FO. lovely
systemd  systemdsucks  fail  google  ntp  time 
july 2017 by jm
Everybody lies: how Google search reveals our darkest secrets | Technology | The Guardian
What can we learn about ourselves from the things we ask online? US data scientist Seth Stephens‑Davidowitz analysed anonymous Google search results, uncovering disturbing truths about [America's] desires, beliefs and prejudices

Fascinating. I find it equally interesting how flawed the existing methodologies for polling and surveying are, compared to Google's data, according to this
science  big-data  google  lying  surveys  polling  secrets  data-science  america  racism  searching 
july 2017 by jm
The Guardian view on patient data: we need a better approach | Editorial | Opinion | The Guardian

The use of privacy law to curb the tech giants in this instance, or of competition law in the case of the EU’s dispute with Google, both feel slightly maladapted. They do not address the real worry. It is not enough to say that the algorithms DeepMind develops will benefit patients and save lives. What matters is that they will belong to a private monopoly which developed them using public resources. If software promises to save lives on the scale that drugs now can, big data may be expected to behave as big pharma has done. We are still at the beginning of this revolution and small choices now may turn out to have gigantic consequences later. A long struggle will be needed to avoid a future of digital feudalism. Dame Elizabeth’s report is a welcome start.

Hear hear.
privacy  law  uk  nhs  data  google  deepmind  healthcare  tech  open-source 
july 2017 by jm
AIY Projects Voice Kit
This looks nifty!
This project demonstrates how to get a natural language recognizer up and running and connect it to the Google Assistant. Along with everything the Google Assistant already does, you can add your own question and answer pairs. All in a handy little cardboard cube, powered by a Raspberry Pi.

(via sergio)
voice  google  aiy-projects  cardboard  hacks  raspberry-pi 
may 2017 by jm
Towards true continuous integration – Netflix TechBlog – Medium
Netflix discuss how they handle the eternal dependency-management problem which arises with lots of microservices:
Using the monorepo as our requirements specification, we began exploring alternative approaches to achieving the same benefits. What are the core problems that a monorepo approach strives to solve? Can we develop a solution that works within the confines of a traditional binary integration world, where code is shared? Our approach, while still experimental, can be distilled into three key features:

Publisher feedback — provide the owner of shared code fast feedback as to which of their consumers they just broke, both direct and transitive. Also, allow teams to block releases based on downstream breakages. Currently, our engineering culture puts sole responsibility on consumers to resolve these issues. By giving library owners feedback on the impact they have to the rest of Netflix, we expect them to take on additional responsibility.

Managed source — provide consumers with a means to safely increment library versions automatically as new versions are released. Since we are already testing each new library release against all downstreams, why not bump consumer versions and accelerate version adoption, safely.

Distributed refactoring — provide owners of shared code a means to quickly find and globally refactor consumers of their API. We have started by issuing pull requests en masse to all Git repositories containing a consumer of a particular Java API. We’ve run some early experiments and expect to invest more in this area going forward.

What I find interesting is that Amazon dealt effectively with the first two many years ago, in the form of their "Brazil" build system, and Google do the latter (with Refaster?). It would be amazing to see such a system released into an open source form, but maybe it's just too heavyweight for anyone other than a giant software company on the scale of a Google, Netflix or Amazon.
brazil  amazon  build  microservices  dependencies  coding  monorepo  netflix  google  refaster 
may 2017 by jm
'What’s your ML Test Score? A rubric for ML production systems'
'Using machine learning in real-world production systems is complicated by a host of issues not found in small toy examples or even large offline research experiments. Testing and monitoring are key considerations for assessing the production-readiness of an ML system. But how much testing and monitoring is enough? We present an ML Test Score rubric based on a set of actionable tests to help quantify these issues.'

Google paper on testable machine learning systems.
machine-learning  testing  ml  papers  google 
april 2017 by jm sold your data to Uber
'Uber devoted teams to so-called competitive intelligence, purchasing data from Slice Intelligence, which collected customers' emailed Lyft receipts via and sold the data to Uber'.

Also: ' allegedly "kept a copy of every single email that you sent or received" in "poorly secured S3 buckets"': CEO: 'felt bad “to see that some of our users were upset to learn about how we monetise our free service”.'
uber  gmail  google  privacy  data-protection  lyft  scumbags  slice-intelligence 
april 2017 by jm
Build a Better Monster: Morality, Machine Learning, and Mass Surveillance

We built the commercial internet by mastering techniques of persuasion and surveillance that we’ve extended to billions of people, including essentially the entire population of the Western democracies. But admitting that this tool of social control might be conducive to authoritarianism is not something we’re ready to face. After all, we're good people. We like freedom. How could we have built tools that subvert it?

As Upton Sinclair said, “It is difficult to get a man to understand something, when his salary depends on his not understanding it.”

I contend that there are structural reasons to worry about the role of the tech industry in American political life, and that we have only a brief window of time in which to fix this.
advertising  facebook  google  internet  politics  surveillance  democracy  maciej-ceglowski  talks  morality  machine-learning 
april 2017 by jm
How Google Book Search Got Lost – Backchannel
There are plenty of other explanations for the dampening of Google’s ardor: The bad taste left from the lawsuits. The rise of shiny and exciting new ventures with more immediate payoffs. And also: the dawning realization that Scanning All The Books, however useful, might not change the world in any fundamental way.
books  reading  google  library  lawsuits  legal  scanning  book-search  search 
april 2017 by jm
Research Blog: Federated Learning: Collaborative Machine Learning without Centralized Training Data
Great stuff from Google - this is really nifty stuff for large-scale privacy-preserving machine learning usage:

It works like this: your device downloads the current model, improves it by learning from data on your phone, and then summarizes the changes as a small focused update. Only this update to the model is sent to the cloud, using encrypted communication, where it is immediately averaged with other user updates to improve the shared model. All the training data remains on your device, and no individual updates are stored in the cloud.

Federated Learning allows for smarter models, lower latency, and less power consumption, all while ensuring privacy. And this approach has another immediate benefit: in addition to providing an update to the shared model, the improved model on your phone can also be used immediately, powering experiences personalized by the way you use your phone.

Papers: ,
google  ml  machine-learning  training  federated-learning  gboard  models  privacy  data-privacy  data-protection 
april 2017 by jm
The Uber Bombshell About to Drop
Alphabet's IP theft allegations regarding Waymo, Otto and Anthony Levandowski are pretty hardcore
alphabet  google  uber  lawsuits  ip  waymo 
march 2017 by jm
Annotated tenets of SRE
A google SRE annotates the Google SRE book with his own thoughts. The source material is great, but the commentary improves it alright.

Particularly good for the error budget concept.

Also: when did "runbooks" become "playbooks"? Don't particularly care either way, but needless renaming is annoying.
runbooks  playbooks  ops  google  sre  error-budget 
march 2017 by jm
Zeynep Tufekci: "Youtube is a crucial part of the misinfomation ecology"
This is so spot on. I hope Google address this issue --
YouTube is crucial part of the misinformation ecology. Not just a demand issue: its recommender algo is a "go down the rabbit hole" machine.
You watch a Trump rally: you get suggested white supremacist videos, sometimes, auto-playing. Like a gateway drug theory of engagement.
I've seen this work across the political spectrum. YouTube algo has discovered out-flanking and "red-pilling" is.. engaging. So it does.

This thread was in response to this Buzzfeed article on the same topic:
youtube  nazis  alt-right  lies  politics  google  misinformation  recommendations  ai  red-pill 
february 2017 by jm
'Software Engineering at Google'
20 pages of Google's software dev practices, with emphasis on the build system (since it was written by the guy behind Blaze). Naturally, some don't make a whole lot of sense outside of Google, but still some good stuff here
development  engineering  google  papers  software  coding  best-practices 
february 2017 by jm
Google - Site Reliability Engineering
The Google SRE book is now online, for free
sre  google  ops  books  reading 
january 2017 by jm
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