- Zero Knowledge and Homomorphic Encryption (ZDNet) — coverage of a few startups working on providing databases that don’t need to decrypt the data they store and retrieve.
- How Not to Suck at Making Products — Never confuse “category you’re in” with the “value you deliver.” Customers only care about the latter.
- Google Patenting Machine Learning Developments (Reddit) — I am afraid that Google has just started an arms race, which could do significant damage to academic research in machine learning. Now it’s likely that other companies using machine learning will rush to patent every research idea that was developed in part by their employees. We have all been in a prisoner’s dilemma situation, and Google just defected. Now researchers will guard their ideas much more combatively, given that it’s now fair game to patent these ideas, and big money is at stake.
- Machine Ethics (Nature) — machine learning ethics versus rule-driven ethics. Logic is the ideal choice for encoding machine ethics, argues Luís Moniz Pereira, a computer scientist at the Nova Laboratory for Computer Science and Informatics in Lisbon. “Logic is how we reason and come up with our ethical choices,” he says. I disagree with his premises.
The O'Reilly Radar Podcast: Pilgrim Beart on the scale, challenges, and opportunities of the IoT.
Subscribe to the O’Reilly Radar Podcast to track the technologies and people that will shape our world in the years to come.
In this week’s Radar Podcast, O’Reilly’s Mary Treseler chatted with Pilgrim Beart about co-founding his company, AlertMe, and about why the scale of the Internet of Things creates as many challenges as it does opportunities. He also talked about the “gnarly problems” emerging from consumer wants and behaviors.
Key insights from Strata + Hadoop World 2015 in London.
People from across the data world came together this week for Strata + Hadoop World 2015 in London. Below we’ve assembled notable keynotes, interviews, and insights from the event.
Shazam already knows the next big hit
“With relative accuracy, we can predict 33 days out what song will go to No. 1 on the Billboard charts in the U.S.,” says Cait O’Riordan, VP of product for music and platforms at Shazam. O’Riordan walks through the data points and trendlines — including the “shape of a pop song” — that give Shazam hints about hits.