SoftBank Capital
Investor
Fred Tanada (He/Him)
@SoftBank Capital @Draper Fisher Jurvetson DragonFund • @Chestnut Street Ventures @Flight Ventures • @crimson-growth-partners • d.school @Stanford.
@SoftBank Capital @Draper Fisher Jurvetson DragonFund • @Chestnut Street Ventures @Flight Ventures • @crimson-growth-partners • d.school @Stanford.
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Experience
Co-investor
Draper Fisher Jurvetson DragonFund
Finance Manager: Venture Capital
Flight Ventures
Venture Capital (Data and Finance Analysis)
Venture Partner
moolave
Co-founder
U.S. Department of Defense
Employee
SunRun
Employee
Oracle / salesforce.com
Tracti.on
Board Member
moolave
Founder
Employee
Oracle
Employee
DFJ
Employee
Entrepreneurial Advisory Network
Advisor
Founder
Employee
Advisor
Board Member
Projects
Improvements to the Neural GPU to reduce training time
Machine Learning, Data Science, Big Data, Psychometrics, Adaptive Learning · Algorithm learning is a core problem in artificial intelligence with… · More significant implications on automation level that can be achieved by machines. Recently deep learning methods are emerging for synthesizing an algorithm from its input-output examples, the most successful being the Neural GPU, capable of learning multiplication.
Item Response Theory allows for ML measuring ability
Machine Learning, Data Science, Big Data, Psychometrics, Adaptive Learning · Item Response Theory (IRT) allows for measuring ability of Machine… · More Learning models as compared to a human population. However, it is difficult to create a large dataset to train the ability of deep neural network models (DNNs). We propose fine-tuning as a new training process,
where a model pre-trained on a large dataset is fine-tuned with a small supplemental training set.
where a model pre-trained on a large dataset is fine-tuned with a small supplemental training set.
Using Computer Vision, Python, and Machine Learning
Self-Driving Car Engineer, Python, OpenCV, TensorFlow · Using Computer Vision, Python, and Machine Learning to Detect Lanes and Traffic… · More Signs
Machine Learning and Computer Vision
Machine Learning and Computer Vision
Chatbot on Stocks, Silicon Valley, and Trends Analysis
Founder, Html5, Css3, Php5, Java Script, Json, Xml, My Sql · Find stock news and analysis with a bot without leaving Facebook Messenger
Development
Development
science of how people relate to each other to social tech
Developer Advocate · Understanding the science of how 900+ million Facebook users relate with each other in terms of social mitigation, conflict… · More resolution, and compassion as an essential trait in understanding relationships better.
Partnered with researchers from Columbia, Berkeley, and Yale in the field of communicating emotion and social-emotional learning. Led by Arturo Bejar, Director of Engineering at Facebook.
Partnered with researchers from Columbia, Berkeley, and Yale in the field of communicating emotion and social-emotional learning. Led by Arturo Bejar, Director of Engineering at Facebook.
D.school founders project
UX Designer · Concept #1
d.radio allows you to tune into and listen to d.classes or spaces which are currently broadcasting their audio. You not… · More only listen but are becoming an active participant thru – our secret sauce here
Concept #2
d.mix and match allows teachers, students, professional and anyone to build their own ideal learning experience, based on:
- d.school content
- external sources: e.g. YouTube, TED Talks, Blogs etc
and share it with the world.
The overall problem we tackle is how do we turn passive observers, who just browse the d.website, into active participants, who create, contribute and make the world a better place.
d.radio allows you to tune into and listen to d.classes or spaces which are currently broadcasting their audio. You not… · More only listen but are becoming an active participant thru – our secret sauce here
Concept #2
d.mix and match allows teachers, students, professional and anyone to build their own ideal learning experience, based on:
- d.school content
- external sources: e.g. YouTube, TED Talks, Blogs etc
and share it with the world.
The overall problem we tackle is how do we turn passive observers, who just browse the d.website, into active participants, who create, contribute and make the world a better place.
Education
About
Achievements
Experience in early stage startups to late stage SaaS companies (>50bn annual revenue) Funds managed from early stage (1.8 billion AUM) to late-stage (100 billion). Worked as operator on self-driving car portfolio companies besides being on the other side of the table. Involved in Typhoon Haiyan relief effort; managed to raise funding to educate out-of-school children. Initiated non-profit agencies with Johns Hopkins for homeless families in Baltimore, outreach meal programs for homeless with UPenn in San Francisco during winter.
Traded futures and Foreign Exchange for Wall Street. Worked at California State Senate and Defense companies. Stanford d.school hack.d Founding Member.
Describe the most impressive thing you've done.
Skills
Locations