Posts
Adam DrakeIntroduction As part of my work with scale-up companies, a critical component of the process I follow during an on-site visit is having interviews and discussions with a variety of people. I have these discussions with everyone at the company, not just the CEO and CTO with whom I most often closely work. People who are lower on the organizational chart often know more than the executive team about what is actually going on in the company. In most cases, they know a great deal more. They have a front-line view, on the ground, every day.
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read more Adam DrakeNote: This article will likely be revised and expanded before being submitted for review and publication. At the moment it is missing critical sections, that will be added later. If we have suggestions for improvement, please send them to me directly.
Abstract In this article I will discuss the well-known technique of feature hashing, but with the modification of performing the hashing step on the client-side before sending data to a server or daemon performing model training and prediction. By using this approach, we can ensure that the system performing the training cannot have any knowledge of the underlying data being received, since the learning takes place only using the hashed representation of the data. Since the hash values are not reversible, this approach allows for data to be shared across business units and regulatory jurisdictions while maintaining privacy and security. Additionally, this approach has well-documented scalability properties, and in our testing can perform model fitting and classification tasks at a rate of over 350,000 records per second on a commodity laptop.
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read more Adam DrakeIntroduction I was honored to be invited by DevTO to give a talk at their May meetup. The organizers were keen to have someone speak about high-performance machine learning, and I was happy to oblige.
The general thesis of the talk is that, for the purposes of machine learning, setting up large compute clusters is wholly unnecessary. Furthermore, it should generally be considered harmful as those efforts are extremely time consuming and detract from solving the actual machine learning problem at hand.
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read more Adam DrakeHello Recruiter!
Thank you very much for your message and your consideration.
In order for me to consider the role more fully and determine if a call is warranted, would you please provide more information? Please send over a JD/role description including the following:
The specific company that is hiring How they see the role and its associated responsibilities fitting into the future of the company Composition, size, and working style of the current team Reporting line for the role (up to Board/investors and two levels down) Compensation details, including a breakdown between fixed/variable cash and options/equity/bonus, if any Any additional information that you think would be relevant in considering if the role is a good fit I’m happy to consider the above information and determine if the role is a good fit for me. If it isn’t, perhaps it’s a good fit for someone in my network and I can make the requisite introductions.
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read more Adam DrakeIntroduction I gave a talk at MaRS on this topic. The event was put on by Steve O’Neil and his team, who all did an excellent job. The venue was packed to standing-room only with a fantastic audience of 300-400 people.
The goal of the event was to have a discussion around “Rational AI in the Enterprise.” I think all of the speakers did a wonderful job of honoring the topic. We wanted to present the facts as they are, on the ground, in real-world projects and situations.
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