4. • 2.5 billion content items
shared per day
• 2.7 billion Likes per day
• 300 million photos
uploaded per day
• 500+terabytes of new data
every day (equivalent to
1,500,000,000 books)
Company Orientation 4
30. My Real World Experience
30
Virtual Extraction Engine
•Developed 2008-2009
•80+% accuracy is not acceptable
•Consider other external factors
Lessons Learned:
•Present solution accordingly
•High Cost of R&D
32. Goal
32
“The only way to come up with something new—something world
changing—is to think outside of the constraints everyone else has.
You have to think outside of the artificial limits everyone else has
already set.” - Steve Jobs
80% of world’s data is generated in the last 2 years
The zettabyte is a multiple of the unit byte for digital information.
The prefix zetta indicates multiplication by the seventh power of 1000 or 1021 in the International System of Units (SI).
equal to a thousand exabytes or a billion terabytes
PredictionIO is an open-source Machine Learning server for developers and data scientists to build and deploy predictive applications in a fraction of the time.
Skymind: Deep Learning for Industry. world’s first open-source, distributed, commercial-grade deep-learning framework: Deeplearning4j.org. We also built ND4J, a scientific computing library for the JVM.
AlgorithMIA: We're building a community around state-of-the-art algorithm development. Users can create, share, and build on other algorithms and then instantly make them available as a web service.
500 million tweets, raised $130M usd
Catch story and threats before public, journalist. Predicts twitter moods.
Dataminr transforms the Twitter stream and other public datasets into actionable signals, discovering must-know information in real-time for clients in Finance, the Public Sector, News, Security and Crisis Management.
ALP can combine evidence from a variety of contexts to create a unified psychometric profile for each learner. As these profiles grow with each child, they’ll provide you with rich insight into not only your learners’ strengths and interests but also the efficacy of your own educational product.
Because it was designed to incorporate data from a range of sources, ALP can support personalized learning in any domain and at any age level to provide the optimal learning experience for your users. These data are used to create an adaptive learning environment, generate personalized insights and activity suggestions for each learner and their parents, and update the learner’s psychometric profile to provide a meaningful picture of their learning journey.