Blog
The latest news from Google AI
Google at the Joint Statistical Meetings in Miami
Monday, August 22, 2011
Posted by Marianna Dizik, Statistician
The Joint Statistical Meetings (JSM) were held in Miami, Florida, this year. Nearly 5,000 participants from academia and industry came to present and discuss the latest in statistical research, methodology, and applications. Similar to previous years, several Googlers shared expertise in large-scale experimental design and implementation, statistical inference with massive datasets and forecasting, data mining, parallel computing, and much more.
Our session "Statistics: The Secret Weapon of Successful Web Giants" attracted over one hundred people; surprising for an 8:30 AM session! Revolution Analytics reviewed this in their official blog post
"How Google uses R to make online advertising more effective"
The following talks were given by Googlers at JSM 2011. Please check the upcoming Proceedings of the JSM 2011 for the full papers.
Statistical Plumbing: Effective use of classical statistical methods for large scale applications
Author(s): Ni Wang, Yong Li, Daryl Pregibon, and Rachel Schutt
Parallel Computations in R, with Applications for Statistical Forecasting
Author(s): Murray Stokely and Farzan Rohani and Eric Tassone
Conditional Regression Models
Author(s): William D. Heavlin
The Effectiveness of Display Ads
Author(s): Tim Hesterberg and Diane Lambert and David X. Chan and Or Gershony and Rong Ge
Measuring Ad Effectiveness Using Continuous Geo Experiments
Author(s): Jon Vaver and Deepak Kumar and Jim Koehler
Post-Stratification and Network Sampling
Author(s): Rachel Schutt and Andrew Gelman and Tyler McCormick
Google has participated at JSM each year since 2004. We have been increasing our involvement significantly by providing sponsorship, organizing and giving talks at sessions and roundtables, teaching courses and workshops, hosting a booth with new Google products demo, submitting posters, and more. This year Googlers participated in sessions sponsored by ASA sections for Statistical Learning and Data Mining, Statistics and Marketing, Statistical Computing, Bayesian Statistical Science , Health Policy Statistics, Statistical Graphics, Quality and Productivity, Physical and Engineering Sciences, and Statistical Education.
We also hosted the Google faculty reception, which was well-attended by faculty and their promising students. Google hires a growing number of statisticians and we were happy to participate in JSM again this year. People had a chance to talk to Googlers, ask about working here, encounter elements of Google culture (good food! T-shirts! 3D puzzles!), meet old and make new friends, and just have fun!
Thanks to everyone that presented, attended, or otherwise engaged with the statistical community at JSM this year. We’re looking forward to seeing you in San Diego next year.
A new MIT center for mobile learning, with support from Google
Tuesday, August 16, 2011
Posted by Hal Abelson, Professor of Computer Science and Engineering, MIT
MIT and Google have a
long-standing relationship
based on mutual interests in education and technology. Today, we took another step forward in our shared goals with the establishment of the MIT Center for Mobile Learning, which will strive to transform learning and education through innovation in mobile computing. The new center will be actively engaged in studying and extending
App Inventor for Android
, which Google recently announced it will be open sourcing.
The new center, housed at MIT’s Media Lab, will focus on designing and studying new mobile technologies that enable people to learn anywhere, anytime, with anyone. The center was made possible in part by support from
Google University Relations
and will be run by myself and two distinguished MIT colleagues: Professors Eric Klopfer (science education) and Mitchel Resnick (media arts and sciences).
App Inventor for Android—a programming system that makes it easy for learners to create mobile apps for Android smartphones—currently supports a community of about 100,000 educators, students and hobbyists. Through the new initiatives at the MIT Center for Mobile Learning, App Inventor will be connected to MIT’s premier research in educational technology and MIT’s long track record of creating and supporting open software.
Google first launched App Inventor internally in order to move it forward with speed and focus, and then developed it to a point where it started to gain critical mass. Now, its impact can be amplified by collaboration with a top academic institution. At MIT, App Inventor will adopt an enriched research agenda with increased opportunities to influence the educational community. In a way, App Inventor has now come full circle, as I actually initiated App Inventor at Google by proposing it as a project during my sabbatical with the company in 2008. The core code for App Inventor came from Eric Klopfer’s
lab
, and the inspiration came from Mitch Resnick’s
Scratch project
. The new center is a perfect example of how industry and academia can collaborate effectively to create change enabled by technology, and we look forward to seeing what we can do next, together.
Our Faculty Institute brings faculty back to the drawing board
Friday, August 12, 2011
Posted by Nina Kim Schultz, Google Education Research
Cross-posted with the
Official Google Blog
School may still be out for summer, but teachers remain hard at work. This week, we hosted Google’s inaugural Faculty Institute at our Mountain View, Calif. headquarters. The three-day event was created for esteemed faculty from schools of education and math and science to explore teaching paradigms that leverage technology in K-12 classrooms. Selected via a rigorous nomination and application process, the 39 faculty members hail from 19 California State Universities (CSUs), as well as Stanford and UC Berkeley, and teach high school STEM (Science, Technology, Engineering and Math) teachers currently getting their teaching credentials. CSU programs credential 60 percent of California’s teachers—or 10 percent of all U.S. K-12 teachers—and one CSU campus alone can credential around 1,000 new teachers in a year. The purpose of gathering together at the Institute was to ensure our teachers’ teachers have the support they need to help educators adjust to a changing landscape.
There is so much technology available to educators today, but unless they learn how to use it effectively, it does little to change what is happening in our classrooms. Without the right training and inspiration, interactive displays become merely expensive projection screens, and laptops simply replace paper rather than shifting the way teachers teach and students learn. Although the possibilities for technology use in schools are endless, teacher preparation for the 21st century classroom also has many constraints. For example: beyond the expense involved, there’s the time it costs educators to match a technological innovation to the improvement of pedagogy and curriculum; there’s a distinct shift in thinking that needs to take place to change classrooms; and there’s an essential challenge to help teachers develop the dispositions and confidence to be lifelong evaluators, learners and teachers of technology, instead of continuing to rely on traditional skill sets that will soon be outdated.
The Institute featured keynote addresses from respected professors from Stanford and Berkeley, case studies from distinguished high school teachers from across California, hands-on technology workshops with a variety of Google and non-Google tools, and panels with professionals in the tech-education industry. Notable guests included representatives from
Teach for America
,
The New Teacher Project
, the
Department of Education
and
Edutopia
. Topics covered the ability to distinguish learning paths, how to use technology to transform classrooms into project-based, collaborative spaces and how to utilize a more interactive teaching style rather than the traditional lecture model.
On the last day of the Institute, faculty members were invited to submit grant proposals to scale best practices outside of the meeting. Deans of the participating universities will convene at the end of the month to further brainstorm ways to scale new ideas in teacher preparation programs. Congratulations to all of the faculty members who were accepted into the inaugural Institute, and thank you for all that you do to help bring technology and new ways of thinking into the classroom.
This program is a part of Google’s continued commitment to supporting STEM education. Details on our other programs can be found on
www.google.com/education
.
Culturomics, Ngrams and new power tools for Science
Wednesday, August 10, 2011
Posted by Erez Lieberman Aiden and Jean-Baptiste Michel, Visiting Faculty at Google
Four years ago, we set out to create a research engine that would help people explore our cultural history by statistically analyzing the world’s books. In January 2011, the resulting method,
culturomics
, was featured on the cover of the journal
Science
. More importantly, Google implemented and launched a web-based version of our prototype research engine, the Google Books Ngram Viewer.
Now scientists, scholars, and web surfers around the world can take advantage of the Ngram Viewer to study a vast array of phenomena. And that's exactly what they've done. Here are a few of our favorite examples.
Poverty
Martin Ravallion, head of the Development Research Group at the World Bank, has been using the ngrams to study the history of poverty. In a
paper
published in the journal Poverty and Public Policy, he argues for the existence of two ‘poverty enlightenments’ marked by increased awareness of the problem: one towards the end of the 18th century, and another in the 1970s and 80s. But he makes the point that only the second of these enlightenments brought with it a truly enlightened idea: that poverty can be and should be completely
eradicated
.
The Science Hall of Fame
Adrian Veres and John Bohannon wondered who the most famous scientists of the past two centuries were. But there was no hall of fame for scientists, or a committee that determines who deserves to get into such a hall. So they used the ngrams data to define a metric for celebrity – the milliDarwin – and algorithmically created a
Science Hall of Fame
listing the most famous scientists born since 1800. They found that things like a popular book or a major controversy did more to increase discussion of a scientist than, for instance, winning a Nobel Prize.
(Other users have been exploring the history of particular sciences with the Ngram Viewer, covering everything from
neuroscience
to the
nuclear
age.)
The History of Typography
When we introduced the Ngram Viewer, we pointed out some potential pitfalls with the data. For instance, the ‘medial s’ ( ſ ), an older form of the letter s that looked like an integral sign and appeared in the beginning or middle of words, tends to be classified as an instance of the letter ‘f’ by the OCR algorithm used to create our version of the data. Andrew West, blogging at
Babelstone
, found a clever way to exploit this error: using queries like ‘husband’ and ‘hufband’ to study the history of medial s typography, he pinned down the precise moment when the medial s disappeared from English (around 1800), French (1780), and Spanish (1760).
People are clearly having a good time with the Ngram Viewer, and they have been learning a few things about science and history in the process. Indeed, the tool has proven so popular and so useful that Google recently announced that its imminent graduation from Google Labs to become a permanent part of Google Books.
Similar ‘big data’ approaches can also be applied to a wide variety of other problems. From books to maps to the structure of the web itself, 'the world's information' is one amazing dataset.
Erez Lieberman Aiden is Visiting Faculty at Google and a Fellow of the Harvard Society of Fellows. Jean-Baptiste Michel is Visiting Faculty at Google and a Postdoctoral Fellow in Harvard's Department of Psychology.
Labels
accessibility
ACL
ACM
Acoustic Modeling
Adaptive Data Analysis
ads
adsense
adwords
Africa
AI
Algorithms
Android
Android Wear
API
App Engine
App Inventor
April Fools
Art
Audio
Augmented Reality
Australia
Automatic Speech Recognition
Awards
BigQuery
Cantonese
Chemistry
China
Chrome
Cloud Computing
Collaboration
Computational Imaging
Computational Photography
Computer Science
Computer Vision
conference
conferences
Conservation
correlate
Course Builder
crowd-sourcing
CVPR
Data Center
Data Discovery
data science
datasets
Deep Learning
DeepDream
DeepMind
distributed systems
Diversity
Earth Engine
economics
Education
Electronic Commerce and Algorithms
electronics
EMEA
EMNLP
Encryption
entities
Entity Salience
Environment
Europe
Exacycle
Expander
Faculty Institute
Faculty Summit
Flu Trends
Fusion Tables
gamification
Gboard
Gmail
Google Accelerated Science
Google Books
Google Brain
Google Cloud Platform
Google Docs
Google Drive
Google Genomics
Google Maps
Google Photos
Google Play Apps
Google Science Fair
Google Sheets
Google Translate
Google Trips
Google Voice Search
Google+
Government
grants
Graph
Graph Mining
Hardware
HCI
Health
High Dynamic Range Imaging
ICLR
ICML
ICSE
Image Annotation
Image Classification
Image Processing
Inbox
India
Information Retrieval
internationalization
Internet of Things
Interspeech
IPython
Journalism
jsm
jsm2011
K-12
KDD
Keyboard Input
Klingon
Korean
Labs
Linear Optimization
localization
Low-Light Photography
Machine Hearing
Machine Intelligence
Machine Learning
Machine Perception
Machine Translation
Magenta
MapReduce
market algorithms
Market Research
Mixed Reality
ML
MOOC
Moore's Law
Multimodal Learning
NAACL
Natural Language Processing
Natural Language Understanding
Network Management
Networks
Neural Networks
Nexus
Ngram
NIPS
NLP
On-device Learning
open source
operating systems
Optical Character Recognition
optimization
osdi
osdi10
patents
Peer Review
ph.d. fellowship
PhD Fellowship
PhotoScan
Physics
PiLab
Pixel
Policy
Professional Development
Proposals
Public Data Explorer
publication
Publications
Quantum AI
Quantum Computing
renewable energy
Research
Research Awards
resource optimization
Robotics
schema.org
Search
search ads
Security and Privacy
Semantic Models
Semi-supervised Learning
SIGCOMM
SIGMOD
Site Reliability Engineering
Social Networks
Software
Sound Search
Speech
Speech Recognition
statistics
Structured Data
Style Transfer
Supervised Learning
Systems
TensorBoard
TensorFlow
TPU
Translate
trends
TTS
TV
UI
University Relations
UNIX
User Experience
video
Video Analysis
Virtual Reality
Vision Research
Visiting Faculty
Visualization
VLDB
Voice Search
Wiki
wikipedia
WWW
YouTube
Archive
2018
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2017
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2016
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2015
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2014
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2013
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2012
Dec
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2011
Dec
Nov
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2010
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2009
Dec
Nov
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2008
Dec
Nov
Oct
Sep
Jul
May
Apr
Mar
Feb
2007
Oct
Sep
Aug
Jul
Jun
Feb
2006
Dec
Nov
Sep
Aug
Jul
Jun
Apr
Mar
Feb
Feed
Google
on
Follow @googleai
Give us feedback in our
Product Forums
.
