- Why The Unicorn Financing Market Just Became Dangerous to Everyone — read with Fortune’s take on the Tech IPO Market. “They profess to take a long-term view, but the data shows post-IPO stocks are very volatile in the case of tech IPOs, and that is not a problem the underwriters try to address.” Damning breakdown of the current state. As Bryce said, Single-horned, majestic, Weapons of Mass Extraction.
- Brainprints (Kurzweil) — 50 subjects, 500 images, EEG headset, 100% accuracy identifying person from their brain’s response to the images. We’ll need much larger studies, but this is promising.
- Generating News Headlines with Recurrent Neural Networks — We find that the model is quite effective at concisely paraphrasing news articles.
- Anthropic Capitalism And The New Gimmick Economy — market capitalism struggles with “public goods” (those which are inexhaustible and non-excludable, like infinitely copyable bits that any number of people can have copies of at once), yet much of the world is being recast as an activity where software manipulates information, thus becoming a public good. Capitalism and Communism, which briefly resembled victor and vanquished, increasingly look more like Thelma and Louise; a tragic couple sent over the edge by forces beyond their control. What comes next is anyone’s guess and the world hangs in the balance.
The O’Reilly Data Show podcast: Fang Yu on data science in security, unsupervised learning, and Apache Spark.
In this episode of the O’Reilly Data Show, I spoke with Fang Yu, co-founder and CTO of DataVisor. We discussed her days as a researcher at Microsoft, the application of data science and distributed computing to security, and hiring and training data scientists and engineers for the security domain.
DataVisor is a startup that uses data science and big data to detect fraud and malicious users across many different application domains in the U.S. and China. Founded by security researchers from Microsoft, the startup has developed large-scale unsupervised algorithms on top of Apache Spark, to (as Yu notes in our chat) “predict attack vectors early among billions of users and trillions of events.”
Several years ago, I found myself immersed in the security space and at that time tools that employed machine learning and big data were still rare. More recently, with the rise of tools like Apache Spark and Apache Kafka, I’m starting to come across many more security professionals who incorporate large-scale machine learning and distributed systems into their software platforms and consulting practices.