AI's downside for software engineers for now seems to be a change in the quality of their work," reports the New York Times. "Some say it is becoming more routine, less thoughtful and, crucially, much faster paced... The new approach to coding at many companies has, in effect, eliminated much of the time the developer spends reflecting on his or her work."

And Amazon CEO Andy Jassy even recently told shareholders Amazon would "change the norms" for programming by how they used AI. Those changing norms have not always been eagerly embraced. Three Amazon engineers said managers had increasingly pushed them to use AI in their work over the past year. The engineers said the company had raised output goals [which affect performance reviews] and had become less forgiving about deadlines. It has even encouraged coders to gin up new AI productivity tools at an upcoming hackathon, an internal coding competition. One Amazon engineer said his team was roughly half the size it was last year, but it was expected to produce roughly the same amount of code by using AI.

Other tech companies are moving in the same direction. In a memo to employees in April, the CEO of Shopify, a company that helps entrepreneurs build and manage e-commerce websites, announced that "AI usage is now a baseline expectation" and that the company would "add AI usage questions" to performance reviews. Google recently told employees that it would soon hold a companywide hackathon in which one category would be creating AI tools that could "enhance their overall daily productivity," according to an internal announcement. Winning teams will receive $10,000.

The shift has not been all negative for workers. At Amazon and other companies, managers argue that AI can relieve employees of tedious tasks and enable them to perform more interesting work. Jassy wrote last year that the company had saved "the equivalent of 4,500 developer-years" by using AI to do the thankless work of upgrading old software... As at Microsoft, many Amazon engineers use an AI assistant that suggests lines of code. But the company has more recently rolled out AI tools that can generate large portions of a program on its own. One engineer called the tools "scarily good." The engineers said that many colleagues have been reluctant to use these new tools because they require a lot of double-checking and because the engineers want more control.

"It's more fun to write code than to read code," said Simon Willison, an AI fan who is a longtime programmer and blogger, channelling the objections of other programmers. "If you're told you have to do a code review, it's never a fun part of the job. When you're working with these tools, it's most of the job."
"This shift from writing to reading code can make engineers feel like bystanders in their own jobs," the article points out (adding "The automation of coding has special resonance for Amazon engineers, who have watched their blue-collar counterparts undergo a similar transition..."

"While there is no rush to form a union for coders at Amazon, such a move would not be unheard of. When General Motors workers went on strike in 1936 to demand recognition of their union, the United Auto Workers, it was the dreaded speedup that spurred them on."

Mojo (the programming language) reached a milestone today.

The story so far... Chris Lattner created the Swift programming language (and answered questions from Slashdot readers in 2017 on his way to new jobs at Tesla, Google, and SiFive). But in 2023, he'd created a new programming language called Mojo — a superset of Python with added functionality for high performance code that takes advantage of modern accelerators — as part of his work at AI infrastructure company Modular.AI.

And today Modular's product manager Brad Larson announced Python users can now call Mojo code from Python. (Watch for it in Mojo's latest nightly builds...) The Python interoperability section of the Mojo manual has been expanded and now includes a dedicated document on calling Mojo from Python. We've also added a couple of new examples to the modular GitHub repository: a "hello world" that shows how to round-trip from Python to Mojo and back, and one that shows how even Mojo code that uses the GPU can be called from Python. This is usable through any of the ways of installing MAX [their Modular Accelerated Xecution platform, an integrated suite of AI compute tools] and the Mojo compiler: via pip install modular / pip install max, or with Conda via Magic / Pixi.

One of our goals has been the progressive introduction of MAX and Mojo into the massive Python codebases out in the world today. We feel that enabling selective migration of performance bottlenecks in Python code to fast Mojo (especially Mojo running on accelerators) will unlock entirely new applications. I'm really excited for how this will expand the reach of the Mojo code many of you have been writing...

It has taken months of deep technical work to get to this point, and this is just the first step in the roll-out of this new language feature. I strongly recommend reading the list of current known limitations to understand what may not work just yet, both to avoid potential frustration and to prevent the filing of duplicate issues for known areas that we're working on.
"We are really interested in what you'll build with this new functionality, as well as hearing your feedback about how this could be made even better," the post concludes.

Mojo's licensing makes it free on any device, for any research, hobby or learning project, as well as on x86 or ARM CPUs or NVIDIA GPU.

Richard Speed writes via The Register: It was 30 years ago when the first public release of the Java programming language introduced the world to Write Once, Run Anywhere -- and showed devs something cuddlier than C and C++. Originally called "Oak," Java was designed in the early 1990s by James Gosling at Sun Microsystems. Initially aimed at digital devices, its focus soon shifted to another platform that was pretty new at the time -- the World Wide Web.

The language, which has some similarities to C and C++, usually compiles to a bytecode that can, in theory, run on any Java Virtual Machine (JVM). The intention was to allow programmers to Write Once Run Anywhere (WORA) although subtle differences in JVM implementations meant that dream didn't always play out in reality. This reporter once worked with a witty colleague who described the system as Write Once Test Everywhere, as yet another unexpected wrinkle in a JVM caused their application to behave unpredictably. However, the language soon became wildly popular, rapidly becoming the backbone of many enterprises. [...]

However, the platform's ubiquity has meant that alternatives exist to Oracle Java, and the language's popularity is undiminished by so-called "predatory licensing tactics." Over 30 years, Java has moved from an upstart new language to something enterprises have come to depend on. Yes, it may not have the shiny baubles demanded by the AI applications of today, but it continues to be the foundation for much of today's modern software development. A thriving ecosystem and a vast community of enthusiasts mean that Java remains more than relevant as it heads into its fourth decade.

Longtime Slashdot reader theodp writes: In what reads a bit like a Sopranos plot, The Information suggests some of those in the recent batch of terminated Microsoft engineers may have in effect been forced to dig their own AI graves.

The (paywalled) story begins: "Jeff Hulse, a Microsoft vice president who oversees roughly 400 software engineers, told the team in recent months to use the company's artificial intelligence chatbot, powered by OpenAI, to generate half the computer code they write, according to a person who heard the remarks. That would represent an increase from the 20% to 30% of code AI currently produces at the company, and shows how rapidly Microsoft is moving to incorporate such technology. Then on Tuesday, Microsoft laid off more than a dozen engineers on Hulse 's team as part of a broader layoff of 6,000 people across the company that appeared to hit engineers harder than other types of roles, this person said."

The report comes as tech company CEOs have taken to boasting in earnings calls, tech conferences, and public statements that their AI is responsible for an ever-increasing share of the code written at their organizations. Microsoft's recent job cuts hit coders the hardest. So how much credence should one place on CEOs' claims of AI programming productivity gains -- which researchers have struggled to measure for 50+ years -- if engineers are forced to increase their use of AI, boosting the numbers their far-removed-from-programming CEOs are presenting to Wall Street?

The US tech sector shed 214,000 jobs in April amid continuing economic uncertainty, according to CompTIA analysis of Bureau of Labor Statistics data. Companies are extending hiring timelines to two or three times longer than last year while significantly raising skill requirements, particularly for AI competencies.

"It's the great hesitation," said George Denlinger of Robert Half, noting employers now demand 10-12 skills instead of 6-7 previously. Entry-level programming positions are disappearing as AI assumes those functions, with Janco Associates CEO Victor Janulaitis observing that "a job that has been eliminated from almost all IT departments is an entry-level IT programmer."

OpenAI CEO and Sam Altman believe Artificial General Intelligence could arrive within the next few years. But the speculations of some technologists "are getting ahead of reality," writes the New York Times, adding that many scientists "say no one will reach AGI without a new idea — something beyond the powerful neural networks that merely find patterns in data. That new idea could arrive tomorrow. But even then, the industry would need years to develop it." "The technology we're building today is not sufficient to get there," said Nick Frosst, a founder of the AI startup Cohere who previously worked as a researcher at Google and studied under the most revered AI researcher of the last 50 years. "What we are building now are things that take in words and predict the next most likely word, or they take in pixels and predict the next most likely pixel. That's very different from what you and I do." In a recent survey of the Association for the Advancement of Artificial Intelligence, a 40-year-old academic society that includes some of the most respected researchers in the field, more than three-quarters of respondents said the methods used to build today's technology were unlikely to lead to AGI.

Opinions differ in part because scientists cannot even agree on a way of defining human intelligence, arguing endlessly over the merits and flaws of IQ tests and other benchmarks. Comparing our own brains to machines is even more subjective. This means that identifying AGI is essentially a matter of opinion.... And scientists have no hard evidence that today's technologies are capable of performing even some of the simpler things the brain can do, like recognizing irony or feeling empathy. Claims of AGI's imminent arrival are based on statistical extrapolations — and wishful thinking. According to various benchmark tests, today's technologies are improving at a consistent rate in some notable areas, like math and computer programming. But these tests describe only a small part of what people can do.

Humans know how to deal with a chaotic and constantly changing world. Machines struggle to master the unexpected — the challenges, small and large, that do not look like what has happened in the past. Humans can dream up ideas that the world has never seen. Machines typically repeat or enhance what they have seen before. That is why Frosst and other sceptics say pushing machines to human-level intelligence will require at least one big idea that the world's technologists have not yet dreamed up. There is no way of knowing how long that will take. "A system that's better than humans in one way will not necessarily be better in other ways," Harvard University cognitive scientist Steven Pinker said. "There's just no such thing as an automatic, omniscient, omnipotent solver of every problem, including ones we haven't even thought of yet. There's a temptation to engage in a kind of magical thinking. But these systems are not miracles. They are very impressive gadgets."
While Google's AlphaGo could be humans in a game with "a small, limited set of rules," the article points out that the real world "is bounded only by the laws of physics. Modelling the entirety of the real world is well beyond today's machines, so how can anyone be sure that AGI — let alone superintelligence — is just around the corner?" And they offer this alternative perspective from Matteo Pasquinelli, a professor of the philosophy of science at Ca' Foscari University in Venice, Italy.

"AI needs us: living beings, producing constantly, feeding the machine. It needs the originality of our ideas and our lives."

IBM laid off "a couple hundred" HR workers and replaced them with AI agents. "It's becoming a huge thing," says Mike Peditto, a Chicago-area consultant with 15 years of experience advising companies on hiring practices. He tells Slate "I do think we're heading to where this will be pretty commonplace." Although A.I. job interviews have been happening since at least 2023, the trend has received a surge of attention in recent weeks thanks to several viral TikTok videos in which users share videos of their A.I. bots glitching. Although some of the videos were fakes posted by a creator whose bio warns that his content is "all satire," some are authentic — like that of Kendiana Colin, a 20-year-old student at Ohio State University who had to interact with an A.I. bot after she applied for a summer job at a stretching studio outside Columbus. In a clip she posted online earlier this month, Colin can be seen conducting a video interview with a smiling white brunette named Alex, who can't seem to stop saying the phrase "vertical-bar Pilates" in an endless loop...

Representatives at Apriora, the startup company founded in 2023 whose software Colin was forced to engage with, did not respond to a request for comment. But founder Aaron Wang told Forbes last year that the software allowed companies to screen more talent for less money... (Apriora's website claims that the technology can help companies "hire 87 percent faster" and "interview 93 percent cheaper," but it's not clear where those stats come from or what they actually mean.)
Colin (first interviewed by 404 Media) calls the experience dehumanizing — wondering why they were told dress professionally, since "They had me going the extra mile just to talk to a robot." And after the interview, the robot — and the company — then ghosted them with no future contact. "It was very disrespectful and a waste of time."

Houston resident Leo Humphries also "donned a suit and tie in anticipation for an interview" in which the virtual recruiter immediately got stuck repeating the same phrase. Although Humphries tried in vain to alert the bot that it was broken, the interview ended only when the A.I. program thanked him for "answering the questions" and offering "great information" — despite his not being able to provide a single response. In a subsequent video, Humphries said that within an hour he had received an email, addressed to someone else, that thanked him for sharing his "wonderful energy and personality" but let him know that the company would be moving forward with other candidates.

Thursday was Rust's 10-year anniversary for its first stable release. "To say I'm surprised by its trajectory would be a vast understatement," writes Rust's original creator Graydon Hoare. "I can only thank, congratulate, and celebrate everyone involved... In my view, Rust is a story about a large community of stakeholders coming together to design, build, maintain, and expand shared technical infrastructure." It's a story with many actors:

- The population of developers the language serves who express their needs and constraints through discussion, debate, testing, and bug reports arising from their experience writing libraries and applications.

- The language designers and implementers who work to satisfy those needs and constraints while wrestling with the unexpected consequences of each decision.

- The authors, educators, speakers, translators, illustrators, and others who work to expand the set of people able to use the infrastructure and work on the infrastructure.

- The institutions investing in the project who provide the long-term funding and support necessary to sustain all this work over decades.

All these actors have a common interest in infrastructure.
Rather than just "systems programming", Hoare sees Rust as a tool for building infrastructure itself, "the robust and reliable necessities that enable us to get our work done" — a wide range that includes everything from embedded and IoT systems to multi-core systems. So the story of "Rust's initial implementation, its sustained investment, and its remarkable resonance and uptake all happened because the world needs robust and reliable infrastructure, and the infrastructure we had was not up to the task." Put simply: it failed too often, in spectacular and expensive ways. Crashes and downtime in the best cases, and security vulnerabilities in the worst. Efficient "infrastructure-building" languages existed but they were very hard to use, and nearly impossible to use safely, especially when writing concurrent code. This produced an infrastructure deficit many people felt, if not everyone could name, and it was growing worse by the year as we placed ever-greater demands on computers to work in ever more challenging environments...

We were stuck with the tools we had because building better tools like Rust was going to require an extraordinary investment of time, effort, and money. The bootstrap Rust compiler I initially wrote was just a few tens of thousands of lines of code; that was nearing the limits of what an unfunded solo hobby project can typically accomplish. Mozilla's decision to invest in Rust in 2009 immediately quadrupled the size of the team — it created a team in the first place — and then doubled it again, and again in subsequent years. Mozilla sustained this very unusual, very improbable investment in Rust from 2009-2020, as well as funding an entire browser engine written in Rust — Servo — from 2012 onwards, which served as a crucial testbed for Rust language features.
Rust and Servo had multiple contributors at Samsung, Hoare acknowledges, and Amazon, Facebook, Google, Microsoft, Huawei, and others "hired key developers and contributed hardware and management resources to its ongoing development." Rust itself "sits atop LLVM" (developed by researchers at UIUC and later funded by Apple, Qualcomm, Google, ARM, Huawei, and many other organizations), while Rust's safe memory model "derives directly from decades of research in academia, as well as academic-industrial projects like Cyclone, built by AT&T Bell Labs and Cornell."

And there were contributions from "interns, researchers, and professors at top academic research programming-language departments, including CMU, NEU, IU, MPI-SWS, and many others." JetBrains and the Rust-Analyzer OpenCollective essentially paid for two additional interactive-incremental reimplementations of the Rust frontend to provide language services to IDEs — critical tools for productive, day-to-day programming. Hundreds of companies and other institutions contributed time and money to evaluate Rust for production, write Rust programs, test them, file bugs related to them, and pay their staff to fix or improve any shortcomings they found. Last but very much not least: Rust has had thousands and thousands of volunteers donating years of their labor to the project. While it might seem tempting to think this is all "free", it's being paid for! Just less visibly than if it were part of a corporate budget.

All this investment, despite the long time horizon, paid off. We're all better for it.
He looks ahead with hope for a future with new contributors, "steady and diversified streams of support," and continued reliability and compatability (including "investment in ever-greater reliability technology, including the many emerging formal methods projects built on Rust.")

And he closes by saying Rust's "sustained, controlled, and frankly astonishing throughput of work" has "set a new standard for what good tools, good processes, and reliable infrastructure software should be like.

"Everyone involved should be proud of what they've built."

An anonymous reader quotes a report from Ars Technica: Google's DeepMind research division claims its newest AI agent marks a significant step toward using the technology to tackle big problems in math and science. The system, known as AlphaEvolve, is based on the company's Gemini large language models (LLMs), with the addition of an "evolutionary" approach that evaluates and improves algorithms across a range of use cases. AlphaEvolve is essentially an AI coding agent, but it goes deeper than a standard Gemini chatbot. When you talk to Gemini, there is always a risk of hallucination, where the AI makes up details due to the non-deterministic nature of the underlying technology. AlphaEvolve uses an interesting approach to increase its accuracy when handling complex algorithmic problems.

According to DeepMind, this AI uses an automatic evaluation system. When a researcher interacts with AlphaEvolve, they input a problem along with possible solutions and avenues to explore. The model generates multiple possible solutions, using the efficient Gemini Flash and the more detail-oriented Gemini Pro, and then each solution is analyzed by the evaluator. An evolutionary framework allows AlphaEvolve to focus on the best solution and improve upon it. Many of the company's past AI systems, for example, the protein-folding AlphaFold, were trained extensively on a single domain of knowledge. AlphaEvolve, however, is more dynamic. DeepMind says AlphaEvolve is a general-purpose AI that can aid research in any programming or algorithmic problem. And Google has already started to deploy it across its sprawling business with positive results. DeepMind's AlphaEvolve AI has optimized Google's Borg cluster scheduler, reducing global computing resource usage by 0.7% -- a significant cost saving at Google's scale. It also outperformed specialized AI like AlphaTensor by discovering a more efficient algorithm for multiplying complex-valued matrices. Additionally, AlphaEvolve proposed hardware-level optimizations for Google's next-gen Tensor chips.

The AI remains too complex for public release but that may change in the future as it gets integrated into smaller research tools.

Microsoft quietly announced earlier this week that it plans to shut down a long-standing tool supplying search engine startups and other software developers with a raw feed of Bing search results. From a report: The Bing Search APIs, or application programming interfaces, were once vital to many niche Google alternatives, but fell out of favor more recently as Microsoft hiked fees for the service and restricted its use.

The shutoff, which is scheduled to begin on August 11, still came as a surprise to several developers who spoke with WIRED. Customers learned of it on Monday via an email from Microsoft and a post on its website. They were directed to consider using "Grounding with Bing Search as part of Azure AI Agents," a Microsoft service that allows chatbots like ChatGPT to augment AI-generated responses with "real-time public web data." Some developers view the AI-centric alternative as an insufficient replacement. Larger customers like DuckDuckGo told Wired they won't be affected.

Chungin Lee used ChatGPT to help write the essay that got him into Columbia University — and then "proceeded to use generative artificial intelligence to cheat on nearly every assignment," reports New York magazine's blog Intelligencer: As a computer-science major, he depended on AI for his introductory programming classes: "I'd just dump the prompt into ChatGPT and hand in whatever it spat out." By his rough math, AI wrote 80 percent of every essay he turned in. "At the end, I'd put on the finishing touches. I'd just insert 20 percent of my humanity, my voice, into it," Lee told me recently... When I asked him why he had gone through so much trouble to get to an Ivy League university only to off-load all of the learning to a robot, he said, "It's the best place to meet your co-founder and your wife."
He eventually did meet a co-founder, and after three unpopular apps they found success by creating the "ultimate cheat tool" for remote coding interviews, according to the article. "Lee posted a video of himself on YouTube using it to cheat his way through an internship interview with Amazon. (He actually got the internship, but turned it down.)" The article ends with Lee and his co-founder raising $5.3 million from investors for one more AI-powered app, and Lee says they'll target the standardized tests used for graduate school admissions, as well as "all campus assignments, quizzes, and tests. It will enable you to cheat on pretty much everything."

Somewhere along the way Columbia put him on disciplinary probation — not for cheating in coursework, but for creating the apps. But "Lee thought it absurd that Columbia, which had a partnership with ChatGPT's parent company, OpenAI, would punish him for innovating with AI." (OpenAI has even made ChatGPT Plus free to college students during finals week, the article points out, with OpenAI saying their goal is just teaching students how to use it responsibly.) Although Columbia's policy on AI is similar to that of many other universities' — students are prohibited from using it unless their professor explicitly permits them to do so, either on a class-by-class or case-by-case basis — Lee said he doesn't know a single student at the school who isn't using AI to cheat. To be clear, Lee doesn't think this is a bad thing. "I think we are years — or months, probably — away from a world where nobody thinks using AI for homework is considered cheating," he said...

In January 2023, just two months after OpenAI launched ChatGPT, a survey of 1,000 college students found that nearly 90 percent of them had used the chatbot to help with homework assignments.
The article points out ChatGPT's monthly visits increased steadily over the last two years — until June, when students went on summer vacation. "College is just how well I can use ChatGPT at this point," a student in Utah recently captioned a video of herself copy-and-pasting a chapter from her Genocide and Mass Atrocity textbook into ChatGPT.... It isn't as if cheating is new. But now, as one student put it, "the ceiling has been blown off." Who could resist a tool that makes every assignment easier with seemingly no consequences?
After using ChatGPT for their final semester of high school, one student says "My grades were amazing. It changed my life." So she continued used it in college, and "Rarely did she sit in class and not see other students' laptops open to ChatGPT."

One ethics professor even says "The students kind of recognize that the system is broken and that there's not really a point in doing this." (Yes, students are even using AI to cheat in ethics classes...) It's not just the students: Multiple AI platforms now offer tools to leave AI-generated feedback on students' essays. Which raises the possibility that AIs are now evaluating AI-generated papers, reducing the entire academic exercise to a conversation between two robots — or maybe even just one.

IBM CEO Arvind Krishna said the tech giant has used AI, and specifically AI agents, to replace the work of a couple hundred human resources workers. As a result, it has hired more programmers and salespeople, he said. From a report: Krishna's comments on Monday come as businesses sort through the workforce impacts of AI and AI agents, the independent bots that can autonomously perform tasks like analyze spreadsheets, conduct research and draft emails.

While there haven't yet been widespread layoffs or downsizing as a result of AI across the economy, some business leaders have said they are holding down head count as they investigate the use of the technology.

Meanwhile, the information-technology workforce has continued to shrink as AI weighs on hiring and some workers leave the field. For IBM, which this week hosts its annual Think conference in Boston, AI adoption has led it to boost hiring in some functions.

Longtime Slashdot reader RoccamOccam shares a blog post from the Trifecta Tech Foundation, a nonprofit organization that creates secure, open source building blocks for infrastructure software. The foundation is also the developer behind Sudo-rs. From the report: Ubuntu 25.10 is set to adopt sudo-rs by default. Sudo-rs is a memory-safe reimplementation of the widely-used sudo utility, written in the Rust programming language. This move is part of a broader effort by Canonical to improve the resilience and maintainability of core system components. [...]

The decision to adopt sudo-rs is in line with Canonical's commitment to Carefully But Purposefully increase the resilience of critical system software, by adopting Rust. Rust is a programming language with strong memory safety guarantees that eliminates many of the vulnerabilities that have historically plagued traditional C-based software. Sudo-rs is part of the Trifecta Tech Foundation's Privilege Boundary initiative, which aims to handle privilege escalation with memory-safe alternatives.

The Open Source Initiative is joining "a global community of contributors" for GitHub's annual event "honoring the individuals who steward and sustain Open Source projects."

And the theme of the 5th Annual "Maintainer Month" will be: securing Open Source: Throughout the month, OSI and our affiliates will be highlighting maintainers who prioritize security in their projects, sharing their stories, and providing a platform for collaboration and learning... Maintainer Month is a time to gather, share knowledge, and express appreciation for the people who keep Open Source projects running. These maintainers not only review issues and merge pull requests — they also navigate community dynamics, mentor new contributors, and increasingly, adopt security best practices to protect their code and users....

- OSI will publish a series of articles on Opensource.net highlighting maintainers whose work centers around security...

- As part of our programming for May, OSI will host a virtual Town Hall [May 21st] with our affiliate organizations and invite the broader Open Source community to join....

- Maintainer Month is also a time to tell the stories of those who often work behind the scenes. OSI will be amplifying voices from across our affiliate network and encouraging communities to recognize the people whose efforts are often invisible, yet essential.
"These efforts are not just celebrations — they are opportunities to recognize the essential role maintainers play in safeguarding the Open Source infrastructure that underpins so much of our digital world," according to the OSI's announcement. And this year they're focusing on three key areas of open source security:

• Adopting security best practices in projects and communities

• Recognizing contributors who improve project security

• Collaborating to strengthen the ecosystem as a whole

An anonymous reader shares a report: Apple is teaming up with startup Anthropic on a new "vibe-coding" software platform that will use AI to write, edit and test code on behalf of programmers.

The system is a new version of Xcode, Apple's programming software, that will integrate Anthropic's Claude Sonnet model, according to people with knowledge of the matter. Apple will roll out the software internally and hasn't yet decided whether to launch it publicly, said the people, who asked not to be identified because the initiative hasn't been announced.

The work shows how Apple is using AI to improve its internal workflow, aiming to speed up and modernize product development. The approach is similar to one used by companies such as Windsurf and Cursor maker Anysphere, which offer advanced AI coding assistants popular with software developers. Further reading: 'Vibe Coding' is Letting 10 Engineers Do the Work of a Team of 50 To 100, Says YC CEO.

An anonymous reader quotes a report from PCWorld: Windows 7 came onto the market in 2009 and put Microsoft back on the road to success after Windows Vista's annoying failures. But Windows 7 was not without its faults, as this curious story proves. Some users apparently encountered a vexing problem at the time: if they set a single-color image as the background, their Windows 7 PC always took 30 seconds to start the operating system and switch from the welcome screen to the desktop.

In a recent blog post, Microsoft veteran Raymond Chen explains the exact reason for this. According to him, a simple programming error meant that users had to wait longer for the system to boot. After logging in, Windows 7 first set up the desktop piece by piece, i.e. the taskbar, the desktop window, icons for applications, and even the background image. The system waited patiently for all components to finish loading and received feedback from each individual component. Or, it switched from the welcome screen to the desktop after 30 seconds if it didn't receive any feedback.

The problem here: The code for the message that the background image is ready was located within the background image bitmap code, which means that the message never appeared if you did not have a real background image bitmap. And a single color is not such a bitmap. The result: the logon system waited in vain for the message that the background has finished loading, so Windows 7 never started until the 30 second fallback activated and sent users to the desktop. The problem could also occur if users had activated the "Hide desktop icons" group policy. This was due to the fact that such policies were only added after the main code had been written and called by an If statement. However, Windows 7 was also unable to recognize this at first and therefore took longer to load.

An anonymous reader quotes a report from Ars Technica: Multiple studies and investigations have found that about half of American households watch TV and movies with subtitles on, but only a relatively small portion of those include someone with a hearing disability. That's because of the trouble many people have understanding dialogue in modern viewing situations, and Netflix has now introduced a subtitles option to help.

The closed captioning we've all been using for years includes not only the words the people on-screen are saying, but additional information needed by the hard of hearing, including character names, music cues ("dramatic music intensifies") and sound effects ("loud explosion"). For those who just wanted to make sure they didn't miss a word here and there, the frequent descriptions of sound effects and music could be distracting. This new format omits those extras, just including the spoken words and nothing else -- even in the same language as the spoken dialogue. The feature will be available in new Netflix original programming, starting with the new season of You in multiple languages. Netflix says it's looking at bringing the option to older titles in the library (including those not produced by Netflix) in the future.

Traditional closed captions are still available, of course. Those are labeled "English CC" whereas this new option is simply labeled "English" (or whatever your preferred language is).

US government agencies and Fortune 500 companies are turning to AI to modernize mission-critical systems built on COBOL, a programming language dating back to the late 1950s. The US Social Security Administration plans a three-year, $1 billion AI-assisted upgrade of its legacy COBOL codebase [alternative source], according to Bloomberg.

Treasury Secretary Scott Bessent has repeatedly stressed the need to overhaul government systems running on COBOL. As experienced programmers retire, organizations face growing challenges maintaining these systems that power everything from banking applications to pension disbursements. Engineers now use tools like ChatGPT and IBM's watsonX to interpret COBOL code, create documentation, and translate it to modern languages.

OpenAI has released Codex CLI, an open-source coding agent that runs locally in users' terminal software. Announced alongside the company's new o3 and o4-mini models, Codex CLI directly connects OpenAI's AI systems with local code and computing tasks, enabling them to write and manipulate code on users' machines.

The lightweight tool allows developers to leverage multimodal reasoning capabilities by passing screenshots or sketches to the model while providing access to local code repositories. Unlike more ambitious future plans for an "agentic software engineer" that could potentially build entire applications from descriptions, Codex CLI focuses specifically on integrating AI models with command-line interfaces.

To accelerate adoption, OpenAI is distributing $1 million in API credits through a grant program, offering $25,000 blocks to selected projects. While the tool expands AI's role in programming workflows, it comes with inherent risks -- studies show AI coding models frequently fail to fix security vulnerabilities and sometimes introduce new bugs, particularly concerning when given system-level access.

Stanford law school graduate Peter Thiel later co-founded Facebook, PayPal, and Palantir. But in 2010 Thiel also created the Thiel Fellowship, which annually gives 20 to 30 people under the age of 23 $100,000 "to encourage students to not stick around college." (College students must drop out in order to accept the fellowship.)

And now Palantir "is taking a similar approach as it maneuvers to attract new talent," reports financial news site The Street: The company has launched what it refers to as the "Meritocracy Fellowship," a four-month internship program for recent high school graduates who have not enrolled in college. The position pays roughly $5,400 per month, more than plenty of post-college internship programs. Palantir's job posting suggests that the company is especially interested in candidates with experience in programming and statistical analysis.
Palantir's job listing specifically says they launched their four-month fellowship "in response to the shortcomings of university admissions," promising it would be based "solely on merit and academic excellence" (requiring an SAT score over 1459 or an ACT score above 32.) "Opaque admissions standards at many American universities have displaced meritocracy and excellence..." As a result, qualified students are being denied an education based on subjective and shallow criteria. Absent meritocracy, campuses have become breeding grounds for extremism and chaos... Skip the debt. Skip the indoctrination. Get the Palantir Degree...

Upon successful completion of the Meritocracy Fellowship, fellows that have excelled during their time at Palantir will be given the opportunity to interview for full-time employment at Palantir.