Watch Volunteers Emerge After Living One Year in a Mars Simulation
And you can watch the “welcome home” ceremony’s livestream starting at 5 p.m. EST on NASA TV (also embedded in Engadget’s story). More det ails from NASA:
For more than a year, the crew simulated Mars mission operations, including “Marswalks,” grew and harvested several vegetables to supplement their shelf-stable food, maintained their equipment and habitat, and operated under additional stressors a Mars crew will experience, including communication delays with Earth, resource limitations, and isolation.
One of the mission’s crew members told the Houston Chronicle they were “very excited to go back to ‘Earth,’ but of course there is a bittersweet aspect to it just like any time you reach the completion of something that has dominated one’s life for several years.”
Various crew members left behind their children or long-term partner for this once-in-a-lifetime experience, according to an earlier article, which also notes that NASA is paying the participants $10 per hour “for all waking hours, up to 16 hours per day. That’s as much as $60,480 for the 378-day mission.”
Engadget points out there are already plans for two more one-year “missions” — with the second one expected to begin next spring…
I’m curious. Would any Slashdot readers be willing to spend a year in a mock Mars habitat?
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‘How Good Is ChatGPT at Coding, Really?’
A study published in the June issue of IEEE Transactions on Software Engineering evaluated the code produced by OpenAI’s ChatGPT in terms of functionality, complexity and security. The results show that ChatGPT has an extremely broad range of success when it comes to producing functional code — with a success rate ranging from anywhere as poor as 0.66 percent and as good as 89 percent — depending on the difficulty of the task, the programming language, and a number of other factors. While in some cases the AI generator could produce better code than humans, the analysis also reveals some security concerns with AI-generated code.
The study tested GPT-3.5 on 728 coding problems from the LeetCode testing platform — and in five programming languages: C, C++, Java, JavaScript, and Python. The results?
Overall, ChatGPT was fairly good at solving problems in the different coding languages — but especially when attempting to solve coding problems that existed on LeetCode before 2021. For instance, it was able to produce functional code for easy, medium, and hard problems with success rates of about 89, 71, and 40 percent, respectively. “However, when it comes to the algorithm problems after 2021, ChatGPT’s ability to generate functionally correct code is affected. It sometimes fails to understand the meaning of questions, even for easy level problems,” said Yutian Tang, a lecturer at the University of Glasgow. For example, ChatGPT’s ability to produce functional code for “easy” coding problems dropped from 89 percent to 52 percent after 2021. And its ability to generate functional code for “hard” problems dropped from 40 percent to 0.66 percent after this time as well…
The researchers also explored the ability of ChatGPT to fix its own coding errors after receiving feedback from LeetCode. They randomly selected 50 coding scenarios where ChatGPT initially generated incorrect coding, either because it didn’t understand the content or problem at hand. While ChatGPT was good at fixing compiling errors, it generally was not good at correcting its own mistakes… The researchers also found that ChatGPT-generated code did have a fair amount of vulnerabilities, such as a missing null test, but many of these were easily fixable.
“Interestingly, ChatGPT is able to generate code with smaller runtime and memory overheads than at least 50 percent of human solutions to the same LeetCode problems…”
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New SnailLoad Attack Exploits Network Latency To Spy On Users’ Web Activities
To perform such a fingerprinting attack and glean what video or a website a user might be watching or visiting, the attacker conducts a series of latency measurements of the victim’s network connection as the content is being downloaded from the server while they are browsing or viewing. It then involves a post-processing phase that employs a convolutional neural network (CNN) trained with traces from an identical network setup to make the inference with an accuracy of up to 98% for videos and 63% for websites. In other words, due to the network bottleneck on the victim’s side, the adversary can deduce the transmitted amount of data by measuring the packet round trip time (RTT). The RTT traces are unique per video and can be used to classify the video watched by the victim. The attack is so named because the attacking server transmits the file at a snail’s pace in order to monitor the connection latency over an extended period of time.
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Christie’s Likens Microsoft’s Work On MS-DOS To Einstein’s Work In Physics
Christie’s auction and characterization of MS-DOS as an Allen and Microsoft innovation comes 30 years after the death of Gary Kildall, whose unpublished memoir, the Seattle Times reported in Kildall’s July 1994 obituary, called DOS “plain and simple theft” of Kildall’s CP/M OS. PC Magazine’s The Rise of DOS: How Microsoft Got the IBM PC OS Contract notes that Paul Allen himself traced the genesis of MS-DOS back to a phone call Allen made to Seattle Computer Products owner Rod Brock in which Microsoft licensed Tim Paterson’s CP/M-inspired QDOS (Quick and Dirty Operating System) for $10,000 plus a royalty of $15,000 for every company that licensed the software. A shrewd buy-low-sell-high business deal, yes, but hardly an Einstein-caliber breakthrough idea.
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Nvidia Forecasted To Make $12 Billion Selling GPUs In China
In contrast, Huawei’s Ascend 910B is claimed to have performance on a par with that of Nvidia’s A100 GPU. It is believed to be an in-house design manufactured by Chinese chipmaker SMIC using a 7nm process technology, unlike the older Ascend 910 product. If this forecast proves accurate, it will be a relief for Nvidia, which earlier disclosed that its sales in China delivered a “mid-single digit percentage” of revenue for its Q4 of FY2024, and was forecast to do the same in Q1 of FY 2025. In contrast, the Chinese market had made up between 20 and 25 percent of the company’s revenue in recent years, until the export restrictions landed.
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Kien, the Most-Delayed Video Game in History, Released After 22 Years
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