Sunday, March 01, 2020


Strange. Clearview matches your face, but then doesn’t know your name? What do they give law enforcement?
Here’s the File Clearview AI Has Been Keeping on Me, and Probably on You Too
After a recent, extensive, and rather withering bout of bad press, the facial recognition company Clearview AI has changed its homepage, which now touts all the things it says its technology can do, and a few things it can’t. Clearview’s system, the company says, is “an after-the-fact research tool. Clearview is not a surveillance system and is not built like one. For example, analysts upload images from crime scenes and compare them to publicly available images.” In doing so, it says, it has the power to help its clients—which include police departments, ICE, Macy’s, Walmart, and the FBI, according to a recent Buzzfeed report stop criminals: “Clearview helps to identify child molesters, murderers, suspected terrorists, and other dangerous people quickly, accurately, and reliably to keep our families and communities safe.”
If you live in California, under the rules of the newly enacted California Consumer Privacy Act, you can see what Clearview has gathered on you, and request that they stop it.
I recently did just that. In mid-January, I emailed privacy-requests@clearview.ai and requested information on any of my personal data that Clearview obtained, the method by which they obtained it, and how it was used. (You can read the guidelines they claim to follow under the CCPA here.) I also asked that all said data be deleted after it was given to me and opted out of Clearview's data collection systems in the future. In response, 11 days later, Clearview emailed me back asking for “a clear photo” of myself and a government-issued ID.
Clearview does not maintain any sort of information other than photos,” the company wrote. “To find your information, we cannot search by name or any method other than image. Additionally, we need to confirm your identity to guard against fraudulent access requests. Finally, we need your name to maintain a record of removal requests as required by law.”
The images seen here range from around 2004 to 2019; some are from my MySpace profile (RIP) and some from Instagram, Twitter, and Facebook. What’s curious is that, according to Clearview, many of them weren't scraped from social media directly, but from a collection of utterly bizarre and seemingly random websites.
Nicholas Weaver, a senior researcher at the International Computer Science Institute at UC Berkeley, said that the response "gives you an insight into the various sources being scraped." He noted that Clearview is not just obtaining images from social media sites like Instagram themselves, but also from other sites that have already scraped Instagram, like Insta Stalker.




Sell now, plan later. Sounds like Marketing is in charge.
THE IOT TRAP
I’m sure that you’ve heard about the Sonos speaker debacle. (If not, read about it on Hackaday.) Basically, a company that sells a premium Internet-connected speaker wanted to retire an older product line, and offered a 30% discount to people who would “trade in” their old speakers for new ones. The catch: they weren’t really trading them in, but instead flashing a “self-destruct” firmware and then taking it to the recycling.
Naturally, Sonos’ most loyal customers weren’t happy about intentionally bricking their faithful devices, a hubbub ensued, and eventually the CEO ended up reversing course and eating crow.
This puts these companies in a tough spot. The more a customer loves the device, the longer they’ll want to keep it running, and the worse the blowback will be when the firm eventually has to try to weasel its way out of a “lifetime” contract. And they are alienating exactly their most loyal customers — those who want to keep their widget running longer than might even be reasonable. Given that this whole business model is new, it’s not surprising that some firms will get it wrong. What’s surprising to me is how many fall into the IoT trap.




Should someone say, “On your mark, get set...”
It’s not just AI, this is a change in the entire computing industry,’ says SambaNova CEO
The rise in deep learning forms of AI, and the abundance of real-world data behind it, is pressing the need for a new kind of computer to replace the typical Von Neumann machines expressed in processors from Intel and AMD, and graphics chips from Nvidia.
But that AI revolution in hardware, as big as it is, may be just the tip of the iceberg.
The last thirty years in computing, said Liang, has been "focused on instructions and operations, in terms of what you optimize for."
"The next five, to ten, to twenty years, large amounts of data and how it flows through a system is really what's going to drive performance."
It's not just a novel computer chip, said Liang, rather, "we are focused on the complete system," he told ZDNet. "To really provide a fundamental shift in computing, you have to obviously provide a new piece of silicon at the core, but you have to build the entire system, to integrate across several layers of hardware and software."
Another co-founder is Stanford machine learning professor Christopher Ré, whose work includes how to develop neural networks trained with very little labeled data, known as "weak supervision."
These scientists' research provides clues to what new systems perhaps should do. Olukotun's work has included "Spatial," a computing language that can take programs and de-compose them into operations that can be run in parallel, for the purpose of making chips that can be "reconfigurable," able to change their circuitry on the fly.




The notes you should have been taking all along.
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