Tech Today w/ Ken May

Archive for July 9th, 2017

An anonymous reader writes: The author of the original Petya ransomware — a person/group going by the name of Janus Cybercrime Solutions — has released the master decryption key of all past Petya versions. This key can decrypt all ransomware families part of the Petya family except NotPetya, which isn’t the work of Janus, but is believed to be the work of a nation-state actor that targeted Ukraine. Most (original) Petya campaigns happened in 2016, and very few campaigns have been active this year. Users that had their files locked have wiped drives or paid the ransom many months before. The key will only help those victims who cloned their drives and saved a copy of the encrypted data. Experts believe that Janus released Petya’s decryption key as a result of the recent NotPetya outbreak, and he might have decided to shut down his operation to avoid further scrutiny, or being accused of launching NotPetya. Read more of this story at Slashdot.

Categories: reader

Enlarge (credit: NASA ) Back in 2012, I had the pleasure of visiting the IBM Watson research center. Among the people I talked with was George Tulevski , who was working on developing carbon nanotubes as a possible replacement for silicon in some critical parts of transistors. IBM likes to think about developing technology with about a 10-year time window, which puts us about halfway to when the company might expect to be making nanotube-based hardware. So, how’s it going? This week, there was a bit of a progress report published in Nature Nanotechnology (which included Tulevski as one of its authors). In it, IBM researchers describe how they’re now able to put together test hardware that pushes a carbon nanotube-based processor up to 2.8GHz. It’s not an especially useful processor, but the methods used for assembling it show that some (but not all) of the technology needed to commercialize nanotube-based hardware is nearly ready. Semiconducting hurdles The story of putting together a carbon nanotube processor is largely one of overcoming hurdles. You wouldn’t necessarily expect that; given that the nanotubes can be naturally semiconducting, they’d seem like a natural fit for existing processor technology. But it’s a real challenge to get the right nanotubes in the right place and play nicely with the rest of the processor. In fact, it’s a series of challenges. Read 11 remaining paragraphs | Comments

Categories: reader

Tesla makes its first Model 3 (update: picture!)

Posted by kenmay on July - 9 - 2017

After months of waiting and no shortage of hype , Tesla’s first Model 3 is finally rolling off the production line. Elon Musk has revealed that the initial production unit is ready (not pictured as of this writing) pending a “final checkout.” Musk will get the first car, as he has with earlier models, but he didn’t call dibs — while Ira Ehrenpreis was the first to plunk down a full deposit, he gave that spot to Musk as a birthday present. It’s safe to say that either would be part of an exclusive club given that a mere 30 Model 3s will reach buyers by the end of July. It’s not certain just how much has changed on the Model 3 since it was unveiled back in 2016. You likely won’t get the full scoop on that until a handover party scheduled for July 28th. However, Musk has already hinted that there shouldn’t be any dramatic changes versus the release candidate prototypes that appeared in March. The past few months have largely been spent tweaking and testing components to ensure the Model 3 is ready for the road. It’s a largely symbolic announcement when most Model 3 pre-order customers won’t even get their vehicles until 2018. Production is only slated to ramp up to 20, 000 cars per month by December, which hardly puts a dent in the hundreds of thousands of reservations made since last spring. With that said, you really are looking at the start of Tesla’s next chapter. Musk and crew can now say they’re producing EVs aimed at the mainstream (albeit the higher end), not just a subset of the luxury car crowd. Production unit 1 of Model 3 is now built and going through final checkout. Pics soon. — Elon Musk (@elonmusk) July 9, 2017 Update (7/9): As promised, Musk just tweeted the above picture of the first production Model 3. First Production Model 3 pic.twitter.com/TCa2NSUNI3 — Elon Musk (@elonmusk) July 9, 2017 Source: Elon Musk (Twitter) , (2)

Categories: reader

Ever-changing memory could lead to faster processors

Posted by kenmay on July - 9 - 2017

Virtually every central processor in your devices uses a tiered set of memory caches to speed things up by fetching commonly used data. But it’s not very efficient — in trying to accommodate everything, it’s rarely the fastest at anything. MIT’s CSAIL researchers want to fix that. They’ve developed a cache system (appropriately named Jenga ) that creates new cache structures on the spot to optimize for a specific app. As Jenga knows the physical locations of each memory bank, it can calculate how to store data to reduce the travel time (and thus lag) as much as possible, even if that means changing the hierarchy. Whether an app would benefit from multiple cache levels or one gigantic cache, this system would be ready. The gains could be huge. A simulated 36-core chip ran up to 30 percent faster just by adopting Jenga, and could use up to 85 percent less power. You wouldn’t necessarily face a penalty for having many cores in a chip, even in laptops and smartphones where every watt counts. Of course, there’s one major problem: Jenga is just a simulation. It could take a while before you see real-world examples of this cache, and longer still before chip manufacturers adopt it (assuming they like the idea, that is). This also assumes that Jenga scales neatly across different core counts. Will you see similar gains with ‘just’ an 8-core chip? It’s easy to imagine CPU giants like Intel or Qualcomm leaping on this concept, though. Chip makers frequently boost performance by moving to ever-smaller manufacturing processes, but they’re gradually running into physical limits . So long as there’s software to take advantage of it, Jenga could wring extra performance out of chips with relatively little effort. Source: MIT News

Categories: reader