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C# (and C) Grew in Popularity in 2025, Says TIOBE

Slashdot.org - 3 hours 49 min ago

For a quarter century, the TIOBE Index has attempted to rank the popularity of programming languages by the number of search engine results they bring up — and this week they had an announcement. Over the last year the language showing the largest increase in its share of TIOBE's results was C#. TIOBE founder/CEO Paul Jansen looks back at how C++ evolved: From a language-design perspective, C# has often been an early adopter of new trends among mainstream languages. At the same time, it successfully made two major paradigm shifts: from Windows-only to cross-platform, and from Microsoft-owned to open source. C# has consistently evolved at the right moment. For many years now, there has been a direct battle between Java and C# for dominance in the business software market. I always assumed Java would eventually prevail, but after all this time the contest remains undecided. It is an open question whether Java — with its verbose, boilerplate-heavy style and Oracle ownership — can continue to keep C# at bay. While C# remains stuck in the same #5 position it was in a year ago, its share of TIOBE's results rose 2.94% — the largest increase of the 100 languages in their rankngs. But TIOBE's CEO notes that his rankings for the top 10 highest-scoring languages delivered "some interesting movements" in 2025: C and C++ swapped positions. [C rose to the #2 position — behind Python — while C++ dropped from #2 to the #4 rank that C held in January of 2025]. Although C++ is evolving faster than ever, some of its more radical changes — such as the modules concept — have yet to see widespread industry adoption. Meanwhile, C remains simple, fast, and extremely well suited to the ever-growing market of small embedded systems. Even Rust has struggled to penetrate this space, despite reaching an all-time high of position #13 this month. So who were the other winners of 2025, besides C#? Perl made a surprising comeback, jumping from position #32 to #11 and re-entering the top 20. Another language returning to the top 10 is R, driven largely by continued growth in data science and statistical computing. Of course, where there are winners, there are also losers. Go appears to have permanently lost its place in the top 10 during 2025. The same seems true for Ruby, which fell out of the top 20 and is unlikely to return anytime soon. What can we expect from 2026? I have a long history of making incorrect predictions, but I suspect that TypeScript will finally break into the top 20. Additionally, Zig, which climbed from position #61 to #42 in 2025, looks like a strong candidate to enter the TIOBE top 30. Here's how TIOBE estimated the 10 most popularity programming languages at the end of 2025 PythonCJavaC++C#JavaScriptVisual BasicSQLDelphi/Object PascalR

Linux Restores Performance on Older PCs and Keeps Them Fast - gHacks Technology News

Linux News - 4 hours 30 min ago

Linux Restores Performance on Older PCs and Keeps Them Fast gHacks Technology News

Categories: Linux

Elon Musk: X's New Algorithm Will Be Made Open Source in Seven Days

Slashdot.org - 6 hours 49 min ago

"We will make the new ð algorithm...open source in 7 days," Elon Musk posted Saturday on X.com. Musk says this is "including all code used to determine what organic and advertising posts are recommended to users," and "This will be repeated every 4 weeks, with comprehensive developer notes, to help you understand what changed." Some context from Engadget: Musk has been making promises of open-sourcing the algorithm since his takeover of Twitter, and in 2023 published the code for the site's "For You" feed on GitHub. But the code wasn't all that revealing, leaving out key details, according to analyses at the time. And it hasn't been kept up to date. Bloomberg also reported on Saturday's announcement: The billionaire didn't say why X was making its algorithm open source. He and the company have clashed several times with regulators over content being shown to users. Some X users had previously complained that they were receiving fewer posts on the social media platform from people they follow. In October, Musk confirmed in a post on X that the company had found a "significant bug" in the platform's "For You" algorithm and pledged a fix. The company has also been working to incorporate more artificial intelligence into its recommendation algorithm for X, using Grok, Musk's artificial intelligence chatbot... In September, Musk wrote that the goal was for X's recommendation engine to "be purely AI" and that the company would share its open source algorithm about every two weeks. "To the degree that people are seeing improvements in their feed, it is not due to the actions of specific individuals changing heuristics, but rather increasing use of Grok and other AI tools," Musk wrote in October. The company was working to have all of the more than 100 million daily posts published to X evaluated by Grok, which would then offer individual users the posts most likely to interest them, Musk wrote. "This will profoundly improve the quality of your feed." He added that the company was planning to roll out the new features by November.

Nature-Inspired Computers Are Shockingly Good At Math

Slashdot.org - Sat, 01/10/2026 - 21:34

An R&D lab under America's Energy Department annnounced this week that "Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex mathematical problems that underpin scientific and engineering challenges." Phys.org publishes the announcement from Sandia National Lab: In a paper published in Nature Machine Intelligence, Sandia National Laboratories computational neuroscientists Brad Theilman and Brad Aimone describe a novel algorithm that enables neuromorphic hardware to tackle partial differential equations, or PDEs — the mathematical foundation for modeling phenomena such as fluid dynamics, electromagnetic fields and structural mechanics. The findings show that neuromorphic computing can not only handle these equations, but do so with remarkable efficiency. The work could pave the way for the world's first neuromorphic supercomputer, potentially revolutionizing energy-efficient computing for national security applications and beyond... "We're just starting to have computational systems that can exhibit intelligent-like behavior. But they look nothing like the brain, and the amount of resources that they require is ridiculous, frankly," Theilman said.For decades, experts have believed that neuromorphic computers were best suited for tasks like recognizing patterns or accelerating artificial neural networks. These systems weren't expected to excel at solving rigorous mathematical problems like PDEs, which are typically tackled by traditional supercomputers. But for Aimone and Theilman, the results weren't surprising. The researchers believe the brain itself performs complex computations constantly, even if we don't consciously realize it. "Pick any sort of motor control task — like hitting a tennis ball or swinging a bat at a baseball," Aimone said. "These are very sophisticated computations. They are exascale-level problems that our brains are capable of doing very cheaply..." Their research also raises intriguing questions about the nature of intelligence and computation. The algorithm developed by Theilman and Aimone retains strong similarities to the structure and dynamics of cortical networks in the brain. "We based our circuit on a relatively well-known model in the computational neuroscience world," Theilman said. "We've shown the model has a natural but non-obvious link to PDEs, and that link hasn't been made until now — 12 years after the model was introduced." The researchers believe that neuromorphic computing could help bridge the gap between neuroscience and applied mathematics, offering new insights into how the brain processes information. "Diseases of the brain could be diseases of computation," Aimone said. "But we don't have a solid grasp on how the brain performs computations yet." If their hunch is correct, neuromorphic computing could offer clues to better understand and treat neurological conditions like Alzheimer's and Parkinson's.