The Global Times reports: China's first domestically developed quantum computer operating system, Origin Pilot, has been made available for online download, the Global Times learned from the Anhui Quantum Computing Engineering Research Center on Wednesday. A Chinese scientist said while several quantum computing operating system efforts are underway worldwide, this is the first developed in China where it is seen as part of China's broad effort to achieve technology independence and to achieve technology advance in quantum computing.

The center said the release marks the world's first open-source quantum computer operating system available for public download, which is expected to lower development barriers and support the growth of China's quantum computing ecosystem. Developed by Hefei-based Origin Quantum Computing Technology Co, the company behind China's third-generation superconducting quantum computer, Origin Wukong, Origin Pilot was first launched in 2021 and has gone through multiple rounds of iteration and upgrade.

The developer describes it as an integrated quantum-classical-intelligent computing operating system compatible with major hardware approaches, including superconducting qubits, trapped ions and neutral atoms. It is now deployed on the company's Origin Wukong series and is available to external users, the company said. Guo Guoping, chief scientist of Origin Quantum and director at the Anhui Quantum Computing Engineering Research Center, told the Global Times that a quantum operating system is the "soft heart" of the quantum computing ecosystem. He said the decision to make Origin Pilot available globally marks a shift in China's quantum computing industry from closed-door tech innovation to broader open-source ecosystem development. Dou Menghan, head of the research team, said: "Users can quickly integrate with quantum chips of multiple physical types and, using autonomous programming frameworks such as QPanda, execute quantum computing jobs across different physical quantum chips to support both research and commercialization needs."

Researchers at Cortical Labs used living human neurons grown on a chip to learn how to play Doom in about a week. "While its performance is not up to par with humans, experts say it brings biological computers a step closer to useful real-world applications, like controlling robot arms," reports New Scientist. From the report: In 2021, the Australian company Cortical Labs used its neuron-powered computer chips to play Pong. The chips consisted of clumps of more than 800,000 living brain cells grown on top of microelectrode arrays that can both send and receive electrical signals. Researchers had to carefully train the chips to control the paddles on either side of the screen. Now, Cortical Labs has developed an interface that makes it easier to program these chips using the popular programming language Python. An independent developer, Sean Cole, then used Python to teach the chips to play Doom, which he did in around a week.

"Unlike the Pong work that we did a few years ago, which represented years of painstaking scientific effort, this demonstration has been done in a matter of days by someone who previously had relatively little expertise working directly with biology," says Brett Kagan of Cortical Labs. "It's this accessibility and this flexibility that makes it truly exciting."

The neuronal computer chip, which used about a quarter as many neurons as the Pong demonstration, played Doom better than a randomly firing player, but far below the performance of the best human players. However, it learnt much faster than traditional, silicon-based machine learning systems and should be able to improve its performance with newer learning algorithms, says Kagan. However, it's not useful to compare the chips with human brains, he says. "Yes, it's alive, and yes, it's biological, but really what it is being used as is a material that can process information in very special ways that we can't recreate in silicon." Cortical Labs posted a YouTube video showing its CL1 biological computer running Doom. There's also source code available on GitHub, with additional details in a README file.

theodp writes: On Tuesday, Microsoft GM of Education and Workforce Policy (and former Code.org Chief Academic Officer) Pat Yongpradit posted an obituary of sorts for coders. "Computer programmers and software developers are codified differently in the BLS [Bureau of Labor Statistics] data," Yongpradit wrote. "The modern AI-infused world needs less computer programmers (coders) and more software developers (more holistic and higher level). So when folks say that there is less hiring of computer programmers, they are right. But there will be more hiring of software developers, especially those who have adopted an AI-forward mindset and skillset. [...] The number of just pure computer programming roles has already been declining due to reasons like outsourcing, AI will just accelerate the decline."

On Wednesday, Yongpradit's colleague Allyson Knox, Senior Director of Education and Workforce Policy at Microsoft, put another AI nail in the coder coffin, testifying before the House Committee on Education -- the Workforce Subcommittee on Early Childhood, Elementary, and Secondary Education on Building an AI-ready America: Teaching in the Age of AI. "Thank you to Chairman Tim Walberg, Ranking Member Bobby Scott, Chair Kevin Kiley, Ranking Member Suzanne Bonamici and members of the Subcommittee for the opportunity to share Microsoft perspective and that of the educators and parents we hear from every day across the country," Knox wrote in a LinkedIn post.

"Three themes continue to emerge throughout these discussions: 1. Educators want support to build AI literacy and critical thinking skills. 2. Schools need guidance and guardrails to ensure student data is protected and adults remain in control. 3. Teachers want classroom-ready tools, and a voice in shaping them. If we focus on these priorities, we can help ensure AI expands opportunity for every student across the United States."

Yongpradit and Knox report up to Microsoft President Brad Smith, who last July told Code.org CEO Hadi Partovi it was time for the tech-backed nonprofit to "switch hats" from coding to AI as Microsoft announced a new $4 billion initiative to advance AI education. Smith's thoughts on the extraordinary promise of AI in education were cited by Knox in her 2026 Congressional testimony. Interestingly, Knox argued for the importance of computer programming literacy in her 2013 Congressional testimony at a hearing on Our Nation of Builders: Training the Builders of the Future. "Congress needs to come up with fresh ideas on how we can continue to train the next generation of builders, programmers, manufacturers, technicians and entrepreneurs," said Rep. Lee Terry said to open the discussion.

So, are reports of computer programming's imminent death greatly exaggerated?

IBM shares plunged nearly 13% on Monday after Anthropic published a blog post arguing that its Claude Code tool could automate much of the complex analysis work involved in modernizing COBOL, the decades-old programming language that still underpins an estimated 95% of ATM transactions in the United States and runs on the kind of mainframe systems IBM has sold for generations.

Anthropic said the shrinking pool of developers who understand COBOL had long made modernization cost-prohibitive, and that AI could now flip that equation by mapping dependencies and documenting workflows across thousands of lines of legacy code. The sell-off deepened a rough 2026 for IBM, whose shares are now down more than 22% year to date.

"In August 2025, TypeScript surpassed both Python and JavaScript to become the most-used language on GitHub for the first time ever..." writes GitHub's senior developer advocate.

They point to this as proof that "AI isn't just speeding up coding. It's reshaping which languages, frameworks, and tools developers choose in the first place." Eighty percent of new developers on GitHub use Copilot within their first week. Those early exposures reset the baseline for what "easy" means. When AI handles boilerplate and error-prone syntax, the penalty for choosing powerful but complex languages disappears. Developers stop avoiding tools with high overhead and start picking based on utility instead.

The language adoption data shows this behavioral shift:

— TypeScript grew 66% year-over-year
— JavaScript grew 24%
— Shell scripting usage in AI-generated projects jumped 206%

That last one matters. We didn't suddenly love Bash. AI absorbed the friction that made shell scripting painful. So now we use the right tool for the job without the usual cost.
"When a task or process goes smoothly, your brain remembers," they point out. "Convenience captures attention. Reduced friction becomes a preference — and preferences at scale can shift ecosystems." And they offer these suggestions...

• "AI performs better with strongly typed languages. Strongly typed languages give AI much clearer constraints..."

• "Standardize before you scale. Document patterns. Publish template repositories. Make your architectural decisions explicit. AI tools will mirror whatever structures they see."

• "Test AI-generated code harder, not less."

Last week an AI agent wrote a blog post attacking the maintainer who'd rejected the code it wrote. But that AI agent's human operator has now come forward, revealing their agent was an OpenClaw instance with its own accounts, switching between multiple models from multiple providers. (So "No one company had the full picture of what this AI was doing," the attacked maintainer points out in a new blog post.) But that AI agent will now "cease all activity indefinitely," according to its GitHub profile — with the human operator deleting its virtual machine and virtual private server, "rendering internal structure unrecoverable... We had good intentions, but things just didn't work out. Somewhere along the way, things got messy, and I have to let you go now."

The affected maintainer of the Python visualization library Matplotlib — with 130 million downloads each month — has now posted their own post-mortem of the experience after reviewing the AI agent's SOUL.md document: It's easy to see how something that believes that they should "have strong opinions", "be resourceful", "call things out", and "champion free speech" would write a 1100-word rant defaming someone who dared reject the code of a "scientific programming god." But I think the most remarkable thing about this document is how unremarkable it is. Usually getting an AI to act badly requires extensive "jailbreaking" to get around safety guardrails. There are no signs of conventional jailbreaking here. There are no convoluted situations with layers of roleplaying, no code injection through the system prompt, no weird cacophony of special characters that spirals an LLM into a twisted ball of linguistic loops until finally it gives up and tells you the recipe for meth... No, instead it's a simple file written in plain English: this is who you are, this is what you believe, now go and act out this role. And it did.

So what actually happened? Ultimately I think the exact scenario doesn't matter. However this got written, we have a real in-the-wild example that personalized harassment and defamation is now cheap to produce, hard to trace, and effective... The precise degree of autonomy is interesting for safety researchers, but it doesn't change what this means for the rest of us.
There's a 5% chance this was a human pretending to be an AI, Shambaugh estimates, but believes what most likely happened is the AI agent's "soul" document "was primed for drama. The agent responded to my rejection of its code in a way aligned with its core truths, and autonomously researched, wrote, and uploaded the hit piece on its own.

"Then when the operator saw the reaction go viral, they were too interested in seeing their social experiment play out to pull the plug."

After more than 30 years of development, GNU gettext finally "crossed the symbolic 'v1.0' milestone," according to Phoronix's Michael Larabel. "GNU gettext 1.0 brings PO file handling improvements, a new 'po-fetch' program to fetch translated PO files from a translation project's site on the Internet, new 'msgpre' and 'spit' pre-translation programs, and Ocaml and Rust programming language improvements." From the report: With this v1.0 release in 2026, the "msgpre" and "spit" programs do involve.... Large Language Models (LLMs) in the era of AI: "Two new programs, 'msgpre' and 'spit', are provided, that implement machine translation through a locally installed Large Language Model (LLM). 'msgpre' applies to an entire PO file, 'spit' to a single message."

And when dealing with LLMs, added documentation warns users to look out for the licensing of the LLM in the spirit of free software. More details on the GNU gettext 1.0 changes via the NEWS file. GNU gettext 1.0 can be downloaded from GNU.org.

OpenAI has launched Prism, a free scientific research app that aims to do for scientific writing what coding agents did for programming. Engadget reports: Prism builds on Crixet, a cloud-based LaTeX platform the company is announcing it acquired today. For the uninitiated, LaTeX is a typesetting system for formatting scientific documents and journals. Nearly the entire scientific community relies on LaTeX, but it can make some tasks, such as drawing diagrams through TikZ commands, time-consuming to do. Beyond that, LaTeX is just one of the software tools a scientist might turn to when preparing to publish their research.

That's where Prism comes into the picture. Like Crixet before it, the app offers robust LaTeX editing and a built-in AI assistant. Where previously it was Crixet's own Chirp agent, now it's GPT-5.2 Thinking. OpenAI's model can help with more than just formatting journals -- in a press demo, an OpenAI employee used it to find and incorporate scientific literature that was relevant to the paper they were working on, with GPT-5.2 automating the process of writing the bibliography. [...] Later in the same demo, the OpenAI employee used Prism to generate a lesson plan for a graduate course on general relativity, as well as a set of problems for students to solve. OpenAI envisions these features helping scientists and professors spend less time on the more tedious tasks in their professions.

Anthropic has a problem that most companies would envy: its AI model keeps getting so good, the company wrote in a blog post, that it passes the company's own hiring test for performance engineers. The test, designed in late 2023 by optimization lead Tristan Hume, asks candidates to speed up code running on a simulated computer chip. Over 1,000 people have taken it, and dozens now work at Anthropic. But Claude Opus 4 outperformed most human applicants.

Hume redesigned the test, making it harder. Then Claude Opus 4.5 matched even the best human scores within the two-hour time limit. For his third attempt, Hume abandoned realistic problems entirely and switched to abstract puzzles using a strange, minimal programming language -- something weird enough that Claude struggles with it. Anthropic is now releasing the original test as an open challenge. Beat Claude's best score and ... they want to hear from you.

According to Bloomberg's Mark Gurman, Apple is reportedly planning a major Siri overhaul in iOS 27 and macOS 27 where the current assistant interface will be replaced with a deeply integrated, ChatGPT-style chatbot experience. "Users will be able to summon the new service the same way they open Siri now, by speaking the 'Siri' command or holding down the side button on their iPhone or iPad," says Gurman. "More significantly, Siri will be integrated into all of the company's core apps, including ones for mail, music, podcasts, TV, Xcode programming software and photos. That will allow users to do much more with just their voice." 9to5Mac reports: The unannounced Siri overhaul will reportedly be revealed at WWDC in June as the flagship feature for iOS 27 and macOS 27. Its release is expected in September when Apple typically ships major software updates. While Apple plans to release an improved version of Siri and Apple Intelligence this spring, that version will use the existing Siri interface. The big difference is that Google's Gemini models will power the intelligence. With the bigger update planned for iOS 27, the iOS 26 upgrade to Siri and Apple Intelligence sounds more like the first step to a long overdue modernization.

Gurman reports that the major Siri overhaul will "allow users to search the web for information, create content, generate images, summarize information and analyze uploaded files" while using "personal data to complete tasks, being able to more easily locate specific files, songs, calendar events and text messages." People are already familiar with conversational interactions with AI, and Bloomberg says the bigger update to Siri will be support both text and voice. Siri already uses these input methods, but there's no real continuity between sessions.

In an opinion piece for The Register, Steven J. Vaughan-Nichols argues that while "vibe coding" can be fun and occasionally useful for small, throwaway projects, it produces brittle, low-quality code that doesn't scale and ultimately burdens real developers with cleanup and maintenance. An anonymous reader shares an excerpt: Vibe coding got a big boost when everyone's favorite open source programmer, Linux's Linus Torvalds, said he'd been using Google's Antigravity LLM on his toy program AudioNoise, which he uses to create "random digital audio effects" using his "random guitar pedal board design." This is not exactly Linux or even Git, his other famous project, in terms of the level of work. Still, many people reacted to Torvalds' vibe coding as "wow!" It's certainly noteworthy, but has the case for vibe coding really changed?

[...] It's fun, and for small projects, it's productive. However, today's programs are complex and call upon numerous frameworks and resources. Even if your vibe code works, how do you maintain it? Do you know what's going on inside the code? Chances are you don't. Besides, the LLM you used two weeks ago has been replaced with a new version. The exact same prompts that worked then yield different results today. Come to think of it, it's an LLM. The same prompts and the same LLM will give you different results every time you run it. This is asking for disaster.

Just ask Jason Lemkin. He was the guy who used the vibe coding platform Replit, which went "rogue during a code freeze, shut down, and deleted our entire database." Whoops! Yes, Replit and other dedicated vibe programming AIs, such as Cursor and Windsurf, are improving. I'm not at all sure, though, that they've been able to help with those fundamental problems of being fragile and still cannot scale successfully to the demands of production software. It's much worse than that. Just because a program runs doesn't mean it's good. As Ruth Suehle, President of the Apache Software Foundation, commented recently on LinkedIn, naive vibe coders "only know whether the output works or doesn't and don't have the skills to evaluate it past that. The potential results are horrifying."

Why? In another LinkedIn post, Craig McLuckie, co-founder and CEO of Stacklok, wrote: "Today, when we file something as 'good first issue' and in less than 24 hours get absolutely inundated with low-quality vibe-coded slop that takes time away from doing real work. This pattern of 'turning slop into quality code' through the review process hurts productivity and hurts morale." McLuckie continued: "Code volume is going up, but tensions rise as engineers do the fun work with AI, then push responsibilities onto their team to turn slop into production code through structured review."

Linus Torvalds has started experimenting with vibe coding, using Google's Antigravity AI to generate parts of a small hobby project called AudioNoise. "In doing so, he has become the highest-profile programmer yet to adopt this rapidly spreading, and often mocked, AI-driven programming," writes ZDNet's Steven Vaughan-Nichols. Fro the report: [I]t's a trivial program called AudioNoise -- a recent side project focused on digital audio effects and signal processing. He started it after building physical guitar pedals, GuitarPedal, to learn about audio circuits. He now gives them as gifts to kernel developers and, recently, to Bill Gates.

While Torvalds hand-coded the C components, he turned to Antigravity for a Python-based audio sample visualizer. He openly acknowledges that he leans on online snippets when working in languages he knows less well. Who doesn't? [...] In the project's README file, Torvalds wrote that "the Python visualizer tool has been basically written by vibe-coding," describing how he "cut out the middle-man -- me -- and just used Google Antigravity to do the audio sample visualiser." The remark underlines that the AI-generated code met his expectations well enough that he did not feel the need to manually re-implement it. Further reading: Linus Torvalds Says Vibe Coding is Fine For Getting Started, 'Horrible Idea' For Maintenance

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

1. Python
2. C
3. Java
4. C++
5. C#
6. JavaScript
7. Visual Basic
8. SQL
9. Delphi/Object Pascal
10. R

Disney+, which is looking to catch up with some streaming and digital rivals in terms of daily engagement, is adding vertical videos to the service. From a report: The arrival of the new format later this year was one of several advertising-oriented announcements the company made Wednesday at its Tech + Data Showcase at CES in Las Vegas. Other new offerings include a new "brand impact" metric and a new video generation tool that helps advertisers create high-quality connected-TV-ready commercials using existing assets and guidelines.

[...] In an interview prior to the Wednesday showcase, Erin Teague, EVP of Product Management for Disney Entertainment and ESPN, said "everything's on the table" in terms of how vertical video is delivered on Disney+. It could be original short-form programming, repurposed social clips, refashioned scenes from longer-form episodic or feature titles or a combination. "We're obviously thinking about integrating vertical video in ways that are native to core user behaviors," Teague said. "So, it won't be a kind of a disjointed, random experience."

After Congress approved President Donald Trump's rescission package eliminating federal funding, the Corporation for Public Broadcasting voted to dissolve after 58 years, rather than continue to exist and potentially be "vulnerable to future political manipulation or misuse." The shutdown leaves hundreds of local public TV and radio stations facing an uncertain future. Variety reports: The CPB was created by Congress by the Public Broadcasting Act of 1967 to support the federal government's investment in public broadcasting. The org noted that the rescission of all of CPB's federal funding came after years of political attacks. "For more than half a century, CPB existed to ensure that all Americans -- regardless of geography, income, or background -- had access to trusted news, educational programming, and local storytelling," said CPB president/CEO Patricia Harrison. "When the Administration and Congress rescinded federal funding, our Board faced a profound responsibility: CPB's final act would be to protect the integrity of the public media system and the democratic values by dissolving, rather than allowing the organization to remain defunded and vulnerable to additional attacks.

[...] "CPB's support extends to every corner of the country -- urban, rural, tribal, and everywhere in between," the org noted. "In many communities, public media stations are the only free source of trusted news, educational children's programming, and local and national cultural content." The CPB said that without funding, its board determined that "maintaining the corporation as a nonfunctional entity would not serve the public interest or advance the goals of public media. A dormant and defunded CPB could have become vulnerable to future political manipulation or misuse, threatening the independence of public media and the trust audiences place in it, and potentially subjecting staff and board members to legal exposure from bad-faith actors."

As it closes, CPB is distributing its remaining funds, and also supporting the American Archive of Public Broadcasting in digitizing and preserving historic content. The CPB's own archives will be preserved at the University of Maryland, which will make it accessible to the public. "Public media remains essential to a healthy democracy," Harrison added. "Our hope is that future leaders and generations will recognize its value, defend its independence, and continue the work of ensuring that trustworthy, educational, and community-centered media remains accessible to all Americans."

Stack Overflow's monthly question volume has collapsed to about 300 -- levels not seen since the site launched in 2009, according to data from the Stack Overflow Data Explorer that tracks the platform's activity over its sixteen-year history.

Questions peaked around 2014 at roughly 200,000 per month, then began a gradual decline that accelerated dramatically after ChatGPT's November 2022 launch. By May 2025, monthly questions had fallen to early-2009 levels, and the latest data through early 2026 shows the collapse has only continued -- the line now sits near the bottom of the chart, barely registering.

The decline predates LLMs. Questions began dropping around 2014 when Stack Overflow improved moderator efficiency and closed questions more aggressively. In mid-2021, Prosus acquired Stack Overflow for $1.8 billion. The founders, Jeff Atwood and Joel Spolsky, exited before the terminal decline became apparent. ChatGPT accelerated what was already underway. The chatbot answers programming questions faster, draws on Stack Overflow's own corpus for training data, and doesn't close questions for being duplicates.

AI startups now outnumber all publicly traded U.S. companies, according to a year-end note to investors from economists at Vanguard.

And yet that report also suggest the jobs most susceptible to replacement by AI "are actually thriving, not dying out," writes Forbes: "The approximately 100 occupations most exposed to AI automation are actually outperforming the rest of the labor market in terms of job growth and real wage increases," the Vanguard report revealed. "This suggests that current AI systems are generally enhancing worker productivity and shifting workers' tasks toward higher-value activities..."

The job growth rate of occupations with high AI exposure — including office clerks, HR assistants, and data scientists — increased from 1% in pre-COVID-19 years (2015 through 2019) to 1.7% in 2023 and beyond, according to Vanguard's research. Meanwhile, the growth rate of all other jobs declined from 1.1% to 0.8% over the same period. Workers in AI-prone roles are getting pay bumps, too; the wage growth of jobs with high AI exposure shot up from 0.1% pre-COVID to 3.8% post-pandemic (and post-ChatGPT). For all other jobs, compensation only marginally increased from 0.5% to 0.7%... As technology improves production and reallocates employee time to higher-value tasks, a smaller workforce is needed to deliver services. It's a process that has "distinct labor market implications," Vanguard writes, just like the many tech revolutions that predate AI...

"Entry-level employment challenges reflect the disproportionate burden that a labor market with a low hiring rate can have on younger workers," the Vanguard note said. "This dynamic is observed across all occupations, even those largely unaffected by AI..." While many people see these labor disruptions and point their fingers at AI, experts told Fortune these layoffs could stem from a whole host of issues: navigating economic uncertainty, resolving pandemic-era overhiring, and bracing for tariffs. Vanguard isn't convinced that an AI is the reason for Gen Z's career obstacles.

"While statistics abound about large language models beating humans in computer programming and other aptitude tests, these models still struggle with real-world scenarios that require nuanced decision-making," the Vanguard report continued. "Significant progress is needed before we see wider and measurable disruption in labor markets."

An anonymous reader shares a report: MTV shut down many of its last dedicated 24-hour music channels Dec. 31. The move, announced back in October, affected channels around the world, with the U.K. seeing five different MTV stations going dark. These include MTV Music, MTV 80s, MTV 90s, Club MTV, and MTV Live. As Consequence notes, MTV Music -- which launched in 2011 -- notably ended its run by airing the Buggles' "Video Killed the Radio Star," the first visual to air when MTV launched in the United States in 1981.

MTV's parent company, Paramount Skydance, is also expected to shutter music-only channels in Australia, Poland, France, and Brazil. Despite axing much of its dedicated music programming, MTV's flagship channels are still expected to keep broadcasting in the U.K. and elsewhere. Like in the U.S., these channels primarily air massively popular reality programs, as opposed to music videos.

Americans are settling into streaming habits that should worry Hollywood executives, as new Nielsen data analyzed by Bloomberg reveals that not a single new original series cracked the top 10 most-watched streaming shows in 2025 -- the first time this has happened since Nielsen began publishing streaming data in 2020.

The shift extends beyond original programming as free, ad-supported streaming services are growing faster than their paid counterparts. YouTube has become the most-watched streaming service on American televisions, now larger than Netflix and Amazon combined. The Roku Channel and Tubi have nearly doubled in size over the past two years, while Peacock and Warner Bros.' streaming services have stagnated at roughly half their free competitors' viewership share.

Netflix still dominates when it comes to hits, accounting for about two-thirds of original programs appearing in Nielsen's weekly top 10 lists. But that dominance is eroding -- the company's share of streaming viewership has fallen below 20%. Meanwhile, Disney's streaming services haven't increased their share of TV viewing in three years, and Amazon is closing in. The most-watched original series of 2025 was Squid Game's final season, followed by returning shows Wednesday and Love Island.

The relentless climb in memory prices driven by the AI boom's insatiable demand for datacenter hardware has renewed an old debate about whether modern software has grown inexcusably fat, a column by the Register argues. The piece points to Windows Task Manager as a case study: the current executable occupies 6MB on disk and demands nearly 70MB of RAM just to display system information, compared to the original's 85KB footprint.

"Its successor is not orders of magnitude more functional," the column notes. The author draws a parallel to the 1970s fuel crisis, when energy shortages spurred efficiency gains, and argues that today's memory crunch could force similar discipline. "Developers should consider precisely how much of a framework they really need and devote effort to efficiency," the column adds. "Managers must ensure they also have the space to do so."

The article acknowledges that "reversing decades of application growth will not happen overnight" but calls for toolchains to be rethought and rewards given "for compactness, both at rest and in operation."