The major gaming platform Roblox has suffered a major data breach, leading to the release of personal information including addresses from those who attended the Roblox Developer Conference between 2017-2020. PCGamer reports: The leak contains almost 4,000 names, phone numbers, email addresses, dates of birth, and physical addresses. Such identifying information is gold dust for bad actors, and raises serious questions about the data security of one of the largest gaming platforms around. The website haveibeenpwned says the original breach date was 18 December 2020, with the information becoming available on 18 July 2023, with a total of 3,943 compromised accounts. The site notes that as well as all the above information, the leak even includes each individual's t-shirt size.

The implications of this for those affected are identity theft and scams, with the quantity of data especially worrying: this is basically all you need to effectively impersonate someone. Beyond the above statement, Roblox has made no further comment, and it's likely that the ramifications of this will continue to unfold for some time, especially if anyone on the list is indeed targeted. Anyone concerned should search on haveibeenpwned and enable two-factor authentication on all accounts (as well as keeping an especially close eye on bank transactions for a while). Troy Hunt, the engineer behind haveibeenpwned, said the leak was posted in 2021 but according to an unnamed source didn't spread outside of niche Roblox communities, while at the time the company did not publicly disclose the leak or alert anyone affected. The leak then appeared on a public forum a few days ago. "Roblox is aware of a third-party security issue where there were indications of unauthorized access to limited personal information of a subset of our creator community," said a Roblox spokesperson to PC Gamer. "We engaged independent experts to support the investigation led by our information security team. Those who are impacted will receive an email communicating the next steps we are taking to support them. We will continue to be vigilant in monitoring and vetting the cyber security posture of Roblox and our third-party vendors."

Roblox is offering developers another way to earn money by allowing them to offer subscriptions within their experiences, according to a blog post published Tuesday. The Verge reports: Roblox already offers developers a lot of ways to monetize their experiences, including the ability to sell virtual items in an experience or on the Roblox marketplace, offering in-experience passes to certain content and gating experiences behind paid access. However, those examples are all one-time fees, and Roblox argues that subscriptions would offer a way for developers to "establish a recurring economic relationship with their users and potentially increase the predictability of their earnings." (Other monetization options include subscriptions to private servers, engagement-based payouts, and slotting in Roblox's "Immersive Ads.")

Subscriptions would also give Roblox another thing it can point to as a reason to develop for its metaverse platform instead of others. Epic Games' new system for Fortnite, for example, rewards creators based on factors like how long people play their experiences but doesn't allow creators to directly sell virtual goods or subscriptions inside those experiences. Developers looking for more flexibility in how they monetize might choose Roblox instead.

Most outsourced programmers in India will see their jobs wiped out in the next year or two, Stability AI CEO Emad Mostaque said. CNBC reports: Mostaque, on a call with UBS analysts, said that most of the country's outsourced coders will lose their jobs as the effects of AI mean that it is now possible for software to be developed with far fewer people. "I think that it affects different types of jobs in different ways," Mostaque said on a call with analysts at the Swiss investment bank last week. "If you're doing a job in front of a computer, and no one ever sees you, then it's massively impactful, because these models are like really talented grads."

According to Mostaque, not everyone will be affected in the same way, however. That is due in no small part to differing rules and regulations around the world. Countries with stronger labor laws, like France, will be less likely to see such an impact, for example. In India, Mostaque said, "outsourced coders up to level three programmers will be gone in the next year or two, whereas in France, you'll never fire a developer." "So it affects different models in different countries in different ways in different sectors."

Mostaque reiterated a previous statement he made saying that there will be "no more programmers" in five years' time -- however, he caveated this to say that he meant coders in the traditional sense. "Why would you have to write code where the computer can write code better? When you deconstruct the programming thing from bug testing to unit testing to ideation, an AI can do that, just better," Mostaque said. "But it won't be doing it automatically, it will be AI 'co-pilots,'" Mostaque said. "That means less people are needed for classical programming, but then are they needed for other things? This is the question and this is the balance that we have to understand, because different areas are also affected differently."

Wix, a longtime fixture of the web building space, is betting that today's customers don't particularly care to spend time customizing every aspect of their site's appearance. TechCrunch: The company's new AI Site Generator tool, announced today, will let Wix users describe their intent and generate a website complete with a homepage, inner pages and text and images -- as well as business-specific sections for events, bookings and more. Avishai Abrahami, Wix's co-founder and CEO, says that the goal was to provide customers with "real value" as they build their sites and grow their businesses. [...] AI Site Generator takes several prompts -- any descriptions of sites -- and uses a combination of in-house and third-party AI systems to create the envisioned site. In a chatbot-like interface, the tool asks a series of questions about the nature of the site and business, attempting to translate this into a custom web template. ChatGPT generates the text for the website while Wix's AI creates the site design and images.

Long-time Slashdot reader theodp writes: The tech-backed and directed nonprofit Code.org is back with a new call for America's Governors, announcing its "10th policy recommendation for all states." Their recommendation? "To require all students to take computer science to earn a high school diploma."

Arguing that "artificial intelligence has increased the urgency to ensure our students are adequately prepared for a rapidly changing world," Code.org explains its vision: that states have "a policy that requires all students to earn a credit named 'computer science' or has a related name that includes 'computer science'". Heretofore, Code.org has said, "Our vision is that every student in every school has the opportunity to learn computer science, just like biology, chemistry, or algebra."

Code.org's call for a high school CS graduation requirement in response to recent AI breakthroughs comes two months after the non-profit launched TeachAI, a Code.org-led and seed-funded effort supported by a coalition of tech and educational organizations, including Microsoft, OpenAI, Amazon, Meta, and (newly AI-powered) Khan Academy. "TeachAI," the initiative's website explains, "is committing to provide thought leadership to guide governments and educational leaders in aligning education with the needs of an increasingly AI-driven world and connecting the discussion of teaching with AI to teaching about AI and computer science."

Steven Vaughan-Nichols writes via ZDNet: I'd been waiting for Oracle to throw its hat into the ring for the Red Hat Enterprise Linux (RHEL) Linux source-code fight. I knew it was only a matter of time. On July 10, Oracle's Edward Screven, chief corporate architect, and Wim Coekaerts, head of Oracle Linux development, declared: "IBM's actions are not in your best interest. By killing CentOS as a RHEL alternative and attacking AlmaLinux and Rocky Linux, IBM is eliminating one way your customers save money and make a larger share of their wallet available to you."

In fact, Oracle now presents itself as an open-source Linux champion: "Oracle has always made Oracle Linux binaries and source freely available to all. We do not have subscription agreements that interfere with a subscriber's rights to redistribute Oracle Linux. On the other hand, IBM subscription agreements specify that you're in breach if you use those subscription services to exercise your GPLv2 rights." As of June 21, IBM no longer publicly releases RHEL source code -- in short, the gloves are off, and the fight's on. But this is also just the latest move in a fight that's older than many of you. [...]

Mike McGrath, Red Hat's vice president of core platforms, explained why Red Hat would no longer be releasing RHEL's code, but only CentOS Stream's code, because "thousands of [Red Hat] people spend their time writing code to enable new features, fixing bugs, integrating different packages and then supporting that work for a long time ... We have to pay the people to do that work." That sentiment is certainly true. But I also feel that Oracle takes the worst possible spin, with Screven and Coekaerts commenting: "IBM doesn't want to continue publicly releasing RHEL source code because it has to pay its engineers? That seems odd, given that Red Hat as a successful independent open source company chose to publicly release RHEL source and pay its engineers for many years before IBM acquired Red Hat in 2019 for $34 billion."

So, what will Oracle do now? For starters, Oracle Linux will continue to be RHEL-compatible through RHEL 9.2. After that release -- and without access to the published RHEL source code -- there are no guarantees. But Screven and Coekaerts suggest that "if an incompatibility does affect a customer or ISV, Oracle will work to remediate the problem." As for Oracle Linux's code: "Oracle is committed to Linux freedom. Oracle makes the following promise: as long as Oracle distributes Linux, Oracle will make the binaries and source code for that distribution publicly and freely available. Furthermore, Oracle welcomes downstream distributions of every kind, community, and commercial. We are happy to work with distributors to ease that process, work together on the content of Oracle Linux, and ensure Oracle software products are certified on your distribution."

Long-time Slashdot reader theodp writes: Recalling a past Computer History Museum look at the evolution of programming languages, Doug Meil ponders the age-old question of Why Are There So Many Programming Languages? in a new Communications of the ACM blog post.

"It's worth noting and admiring the audacity of PL/I (1964)," Meil writes, "which was aiming to be that 'one good programming language.' The name says it all: Programming Language 1. There should be no need for 2, 3, or 4. [Meil expands on this thought in Lessons from PL/I: A Most Ambitious Programming Language.] Though PL/I's plans of becoming the Highlander of computer programming didn't play out like the designers intended, they were still pulling on a key thread in software: why so many languages? That question was already being asked as far back as the early 1960's."

One of PL/I's biggest fans was Digital Research Inc. (DRI) founder Gary Kildall, who crafted the PL/I-inspired PL/M (Programming Language for Microcomputers) in 1973 for Intel. But IBM priced PL/I higher than the languages it sought to replace, contributing to PL/I's failure to gain traction. (Along the lines of how IBM's deal with Microsoft gave rise to a price disparity that was the undoing of Kildall's CP/M OS, bundled with every PC in a 'non-royalty' deal. Windows was priced at $40 while CP/M was offered 'a la carte' at $240.) As a comp.lang.pl1 poster explained in 2006, "The truth of the matter is that Gresham's Law: 'Bad money drives out good' or Ruskin's principle: 'The hoi polloi always prefer an inferior, cheap product over a superior, more expensive one' are what govern here."

Perl 5.38 was released this week "after being in development for more than one year," reports Phoronix. "Perl 5.38 brings a new experimental syntax for defining object classes where per-instance data is stored in 'field' variables that behave like lexicals."

"Maybe, just maybe, the new features introduced into the language in this newest version will attract much sought new talent," writes the site I Programmer, noting the argument that Perl is installed by default everywhere — and has the "fun factor... The class keyword is part of the plan to bring effective object-oriented programming to the Perl core while still keeping Perl being Perl."

The Perl docs warn that "This remains a new and experimental feature, and is very much still under development. It will be the subject of much further addition, refinement and alteration in future releases." But "Since Perl 5, support for objects revolved around the concept of blessing references with a package name," notes updated documentation, which points out this new class syntax "isn't a bless wrapper, but a completely new system built right into the perl interpreter." The class keyword declares a new package which is intended to be a class... classes automatically get a constructor named new... Just like with other references, when object reference count reaches zero it will automatically be destroyed.
Phoronx notes that Perl 5.38 also brings a new PERL_RAND_SEED environment variable "for controlling seed behavior for random number generation," along with some new APIs. And I Programmer adds that Perl 5.38 also adds support for Unicode 15.0, adding 4, 489 characters, for a total of 149,186 characters. Other additions include enhanced regular expressions, plus defined-or and logical-or assignment default expressions in signatures.

According to NBC News, the FBI created a national online database in May to facilitate information sharing between hundreds of police departments and law enforcement agencies across the country pertaining to swatting incidents. From the report: No central agency has tracked swatting incidents or suspects in the U.S., so official statistics are not available. By 2019, there were an estimated 1,000 swatting incidents domestically each year, according to a report from the Anti-Defamation League, and each incident is estimated to cost at least $10,000 to affected communities, even before expenditures on follow-up work like investigations, property repairs and counseling. Swatting is increasingly enabled by technology that can be used to mask a caller's real voice, their phone number or IP address (also called "spoofing") or to make their false report sound more credible.

[Chief Scott Schubert with the bureau's Criminal Justice Information Services headquarters in Clarksburg, West Virginia] told NBC News that the FBI's new centralized database should help the agency "get that common picture of what's going on across our nation so we can learn from that." [...] While the earliest recorded case of swatting occurred in 2002, to this day, there is no specific law criminalizing swatting in the U.S., says John Jay's Shapiro. "Without a statute in place, there's no designated resources or training for investigating swatting incidents," she said. "And the 911 dispatchers do not have the resources and training they need to differentiate between actual emergencies and false reports."

Legally, the False Information and Hoaxes statute, also known as section 1038, is most frequently used to prosecute swatting. Other statutes can sometimes apply -- one pertaining to interstate threats involving explosives and another pertaining to interstate communications, which refers to extortion or threats to injure or kidnap somebody. "Too often, perpetrators are getting a slap on the wrist compared to the consequences suffered by their victims," Shapiro said.

Oracle is spending "billions" of dollars on chips from Nvidia as it expands a cloud computing service targeting a new wave of artificial intelligence companies, Oracle founder and Chairman Larry Ellison said. From a report: Oracle's cloud division is working to gain ground against larger rivals such as Amazon Web Services and Microsoft. To get an edge, Oracle has focused on building fast networks that can shuffle around the huge amount of data needed to create AI systems similar to ChatGPT.

Oracle is also buying huge numbers of GPUs designed to crunch that data for AI work. Oracle is also spending "billions" of dollars on Nvidia chips but even more on CPUs from Ampere Computing, a chip startup it has invested in, and AMD, Ellison said at an Ampere event.

96,000 American students took this year's [Java-based] AP Computer Science A test. And more than a third — a full 34% — missed question #4.

It asks test-takers to write two methods for the class BoxOfCandy — one that moves a Candy object to the first row (of a column), and one that finds and returns a Candy object of a specfic flavor, removing it from the box.

Long-time Slashdot reader theodp shares some thoughts: - "If 34% of students are not getting any points, it's a test question problem, not a student one," argued one commenter on Twitter. [Question 4 is 5-pages long.]

- Here's a stab at an Excel VBA solution to Question 4 for comparison-to-Java purposes. It's a little bit clunkier due to how VBA functions return results compared to Java, but it's still pretty concise and allows code to be easily tested and results to be easily visualized using the 2D Excel worksheet grid.

- AI-powered Bing refuses to provide the answer to the question that completely eluded 32,000+ AP CS A exam takers ("I'm sorry but I cannot provide you with the answer to that question. It is not ethical to share the answers to an exam question". [But] it does tip one off to a suggested Java solution for Q4 that can be found in A+ Computer Science's 2023 AP CS A Exam Review.

Elissaveta M. Brandon writes via Fast Company: There's a new font in town -- and it's already causing rifts on Reddit. The font is called Intel One Mono, and as its name implies, it was designed by tech giant Intel, together with New York-based type design practice Frere-Jones Type and marketing agency VMLY&R. It joins a group of monospaced fonts designed primarily for developers -- think JetBrains Mono, Fira Code, and Consolas. By definition, monospaced fonts consist of characters that have the same width and occupy the same horizontal space, making it easy for coders and programmers to tell the difference between long strings of characters. But here's where Intel One Mono stands out: it was designed with and for low-vision developers. (It's free to download on GitHub and will soon be available on Google Fonts, too.)

To ensure the font was legible and readable to its target audience, the team ran more than a dozen "live testing sessions" with visually impaired developers who were asked to write code using Intel One Mono. [...] Some of the feedback the designers received was particularly surprising. For example, some people were struggling to tell apart a capital "M" from a capital "N," most likely because both letters have two vertical stems and some diagonals in between, which can be confusing. To make the letters more legible, the designers sloped the vertical stems on the "M" so it looks close to an inverted W. "The point at which the two diagonals meet in the middle gets shifted up to make it clearly a V shape in the middle, and then the two verticals get flared out a little bit to give it slightly more differentiable shape from the capital N," says Fred Shallcrass, a type designer at Frere-Jones Type.

Similar challenges kept coming back with the "x" and the "y" which people struggled to distinguish, and the "e" and the "c." In every instance, the designers meticulously tweaked the letters to make them highly distinctive, resulting in a fairly idiosyncratic font where every glyph is as different as possible from the other -- all the way down to the curly brackets, which can best be described as extra curly. This brings us to that Reddit rift. "This font would be great were it not for those curly braces," one person wrote. "For someone that hates fonts sometimes because of curly brackets not being clear and evident, I'm officially switching to this font set because of the curly brackets," wrote another. The developers were equally torn, but the designers stand by them. "Part of our thinking in negotiating those responses is that reinforcing the identity of any shape is not just amplifying what is unique about that letter, but also making it clearly not some other letter, so foreclosing any confusion," says Tobias Frere-Jones, the founder and lead designer at his eponymous studio. "If there's a thing the curly braces do, which is that extra back and forth movement, the parentheses don't do that, the brackets don't do that, therefore these ought to do a lot of that."

Prominent KDE developer Nate Graham believes that Plasma 6 is now "fairly livable" and recommends KDE developers and power users / enthusiasts start giving it a try. Phoronix reports: He characterized Plasma 6 as: "Basically everything in Plasma compiles with Qt 6, and at this point Plasma 6 is fairly livable. To give you a sense of how livable, it's good enough that over the past 2 months, I've gone on three KDE-related trips from the USA to Europe, with my only computer running Plasma 6 in "current git master" state, with work-in-progress merge requests applied! Its stability has been good enough that this has caused me no apprehension, and indeed, it's been totally fine on each trip. So seriously, if you're a KDE developer or an adventurous user, start living on Plasma 6! Jump right in, the water's fine. :)"

He went on to write more about the current development activities around Plasma 6. He also shared his personal beliefs around Plasma 6.0 release timing although no official release schedule is yet to be determined. Nate's belief is that Plasma 6.0 will likely be ready for release sometime between December and March.

Long-time Slashdot reader theodp writes: Y Combinator founder Paul Graham last week took to Twitter to lament those who use AI or other excuses for not learning to code. "A generation ago some people were saying there was no point in learning to program because all the programming jobs would be outsourced to India," Graham wrote. "Now they're saying you don't need to because AI will do it all. If you don't want to learn to program, you can always find a reason."

BloomTech Coding Bootcamp CEO Austen Allred this week doubled-down on Graham's tweet, offering his own history of excuses people have made for not learning to code... Allred's tweet reads:

"Don't learn to code. Soon GUIs will do it all for you." — 1985

"Don't learn to code. Soon that will all be done offshore for pennies." — 2003

"Don't learn to code. Soon nocode tools will do it all for you." — 2015

"Don't learn to code. Soon AI will do it all for you." — 2023

Among the many retweeting Allred's cautionary message was Code.org, the tech-backed nonprofit that aims to make computer science a high school graduation requirement by 2030, whose CEO also replied to Graham with a reassuring tweet suggesting people's days of being able to avoid learning to code will soon be over. "Now that 27 states require that every school must teach computer science, and 7 states require a CS course to graduate high school," explained Code.org CEO Hadi Partovi, "the argument is basically behind us. Computer science won."
On a related note, this month in Communications of the ACM, a CS professor shared their own contrary opinion about the possibility of a professional programmer using AI assistants to do a better job.

"It doesn't work." I would love to have an assistant who keeps me in check, alerting me to pitfalls and correcting me when I err. A effective pair-programmer. But that is not what I get. Instead, I have the equivalent of a cocky graduate student, smart and widely read, also polite and quick to apologize, but thoroughly, invariably, sloppy and unreliable. I have little use for such supposed help...

Fascinating as they are, AI assistants are not works of logic; they are works of words. Large language models: smooth talkers (like the ones who got all the dates in high school). They have become incredibly good at producing text that looks right. For many applications that is enough. Not for programming.

An anonymous reader quotes a report from ZDNet: [A]ccording to a new GitHub programmer survey, "92% of US-based developers are already using AI coding tools both in and outside of work." GitHub partnered with Wakefield Research to survey 500 US-based enterprise developers. They found that 70% of programmers believe AI is providing significant benefits to their code. Specifically, developers said AI coding tools can help them meet existing performance standards with improved code quality, faster outputs, and fewer production-level incidents.

This is more than just people working on external open-source projects or just fooling around. Only 6% of developers said they solely use these tools outside of work. In other words, today, AI programming tools are part and parcel of modern business IT. Why has this happened so quickly? It's all about the programmers' bottom line. Developers say AI coding tools help them meet existing performance standards with improved code quality, faster outputs, and fewer production-level incidents. It's also all about simply producing more lines of code. "Engineering leaders will need to ask whether measuring code volume is still the best way to measure productivity and output," added Inbal Shani, GitHub's chief product officer. "Ultimately, the way to innovate at scale is to empower developers by improving their productivity, increasing their satisfaction, and enabling them to do their best work -- every day."

According to the survey, "Developers want to upskill, design solutions, get feedback from end users, and be evaluated on their communication skills."

"In other words, generating code with AI is a means to an end, not an end to itself," writes ZDNet's Steven Vaughan-Nichols. "Developers believe they should be judged on how they handle those bugs and issues, which is more important to performance than just lines of code. [...] Yes, you can have ChatGPT write a program for you, but if you don't understand what you're doing in the first place or the code you're 'writing,' the code will still be garbage. So, don't think for a minute that just because you can use ChatGPT to write a Rust bubble-sort routine, it means you're a programmer now, You're not."

Google has launched its script editor tool, offering advanced automations for Google Home-powered smart homes. The Verge reports: Available starting Tuesday, June 13th, to those in the Google Home public preview, the script editor is part of Google's new home.google.com web interface, which also has live feeds for any Nest cams on your account. The script editor will be coming to the new Google Home app preview starting June 14th. There's no date for general availability.

Along with allowing for multiple starters and actions, the script editor adds more advanced conditions. For example, you can set an automation to run only if the TV is on and it's after 6PM but before midnight. The script editor automations are created in the new Google Home web interface, you can apply for the public preview here.

The script editor allows you to do everything you can in the Home app when setting up automations, plus "more than 100 new features and capabilities to fit your unique understanding of your home and what you want it to do," according to a blog post by Anish Kattukaran, director of product management at Google Home. This includes access to nearly 100 starters and actions, including Matter sensors -- something not currently possible in the Home app. For example, an Eve Motion sensor connected via Matter to Google Home can't currently be used as a starter for automations in the Home app but can be used as one in the script editor. Google has some example automations that you can view here.

20 miles west of Portland, engineers at an Intel lab are dunking expensive racks of servers "in a clear bath" made of motor oil-like petrochemicals, reports the Oregonian, where the servers "give off a greenish glow as they silently labor away on ordinary computing tasks." Intel's submerged computers operate just as they would on a dry server rack because they're not bathing in water, even though it looks just like it. They're soaking in a synthetic oil that doesn't conduct electricity. So the computers don't short out.

They thrive, in fact, because the fluid absorbs the heat from the hardworking computers much better than air does. It's the same reason a hot pan cools off a lot more quickly if you soak it in water than if you leave it on the stove.

As data centers grow increasingly powerful, the computers are generating so much heat that cooling them uses exorbitant amounts of energy. The cooling systems can use as much electricity as the computers themselves. So Intel and other big tech companies are designing liquid cooling systems that could use far less electricity, hoping to lower data centers' energy costs by as much as a third — and reducing the facilities' climate impact. It's a wholesale change in thinking for data centers, which already account for 2% of all the electricity consumption in the U.S... Skeptics caution that it may be difficult or prohibitively expensive to overhaul existing data centers to adapt to liquid cooling. Advocates of the shift, including Intel, say a transition is imperative to accommodate data centers' growing thirst for power. "It's really starting to come to a head as we're hitting the energy crisis and the need for climate action globally," said Jen Huffstetler, Intel's chief product sustainability officer...

Cooler computers can be packed more tightly together in data centers, since they don't need space for airflow. Computer manufacturers can pack chips together more tightly on the motherboard, enabling more computing power in the same space. And liquid cooling could significantly reduce data centers' environmental and economic costs. Conventional data centers' evaporative cooling systems require tremendous volumes of water and huge amounts of electricity...

Many other tech companies are backing immersion cooling, too. Google, Facebook and Microsoft are all helping fund immersion cooling research at Oregon State... [T]he timing may finally be right for data centers operators to make the shift away from air cooling to something far more efficient. Intel's Huffstetler said she expects to see liquid cooling become widespread in the next three to five years.
The article notes other challenges:

• liquid adds more weight than some buildings' upper floors can support
• Some metals degrade faster in liquid than they do in air.
• And the engineers had to modify the servers by removing their fans — "because they serve no purpose while immersed."

InfoWorld explores how the new Mojo program language "resembles Python, how it's different, and what it has to offer." The newly unveiled Mojo language is being promoted as the best of multiple worlds: the ease of use and clear syntax of Python, with the speed and memory safety of Rust. Those are bold claims, and since Mojo is still in the very early stages of development, it will be some time before users can see for themselves how the language lives up to them. But Mojo's originator — a company named Modular — has provided early access [through a limited-enrollment preview program] to an online playground: a Jupyter Notebook environment where users can run Mojo code and learn about the language's features and behavior...

Mojo can be described as a "superset" of Python. Programs written in Python are valid Mojo programs, although some Python behaviors haven't yet been implemented... It's also possible to use the actual Python runtime for working with existing Python modules, although there is a performance cost. When Mojo introduces new syntax, it's for system-level programming features, chiefly manual memory handling. In other words, you can write Python code (or something almost exactly like it) for casual use cases, then use Mojo for more advanced, performance-intensive programming scenarios... Mojo's other big difference from Python is that Mojo's not interpreted through a runtime, as Python is. Mojo is compiled ahead-of-time to machine-native code, using the LLVM toolchain. To that end, the best performance comes from using features specific to Mojo. Python features are likely to come at the cost of emulating Python's dynamic behaviors, which are inherently slow — or again, by just using the Python runtime.

Many of Mojo's native language features do one of two things. They're either entirely new features not found in Python at all, or expansions of a Python feature that make it more performant, although with less of Python's dynamism.
For example, Mojo has its own fn keyword which defines a function with explicitly-typed and immutable-by-default arguments, and its own struct keyword which is less like a Python class and more like its C/C++ and Rust counterpart "with fixed layouts determined at compile time but optimized for machine-native speed."

But "At a glance, the code closely resembles Python. Even the new Mojo-specific keywords integrate well with existing Python syntax, so you can run your eye down the code and get a general idea of what's happening." And then there's the speed... The notebook demos also give examples of how Mojo code can be accelerated via parallelism, vectorizing, and "tiling" (increasing cache locality for operations). One of the demos, a 128x128 matrix multiplication demo, yielded a claimed 17-times speedup over Python (using the Python runtime in the Mojo playground) by simply running as-is with no special modification. Mojo added 1866x speedup by adding type annotations, 8500x speedup by adding vectorized operations, and 15000x speedup by adding parallelization.

ZDNet asks the million-dollar question. "Despite the potential for vast productivity gains from generative AI tools such as ChatGPT or GitHub Copilot, will technology professionals' jobs actually grow more complicated? " People can now pump out code on demand in an abundance of languages, from Java to Python, along with helpful recommendations. Already, 95% of developers in a recent survey from Sourcegraph report they use Copilot, ChatGPT, and other gen AI tools this way.

But auto-generating new code only addresses part of the problem in enterprises that already maintain unwieldy codebases, and require high levels of cohesion, accountability, and security.

For starters, security and quality assurance tasks associated with software jobs aren't going to go away anytime soon. "For programmers and software engineers, ChatGPT and other large language models help create code in almost any language," says Andy Thurai, analyst with Constellation Research, before talking about security concerns. "However, most of the code that is generated is security-vulnerable and might not pass enterprise-grade code. So, while AI can help accelerate coding, care should be taken to analyze the code, find vulnerabilities, and fix it, which would take away some of the productivity increase that AI vendors tout about."

Then there's code sprawl. An analogy to the rollout of generative AI in coding is the introduction of cloud computing, which seemed to simplify application acquisition when first rolled out, and now means a tangle of services to be managed. The relative ease of generating code via AI will contribute to an ever-expanding codebase — what the Sourcegraph survey authors refer to as "Big Code". A majority of the 500 developers in the survey are concerned about managing all this new code, along with code sprawl, and its contribution to technical debt. Even before generative AI, close to eight in 10 say their codebase grew five times over the last three years, and a similar number struggle with understanding existing code generated by others.

So, the productivity prospects for generative AI in programming are a mixed bag.

We already have automated processes that detect bugs, test solutions, and generate documentation, notes a new post on Stack Overflow's blog. But beyond that, several developers "have written in the past on the idea of self-healing code. Head over to Stack Overflow's CI/CD Collective and you'll find numerous examples of technologists putting this ideas into practice."

Their blog post argues that self-healing code "is the future of software development." When code fails, it often gives an error message. If your software is any good, that error message will say exactly what was wrong and point you in the direction of a fix. Previous self-healing code programs are clever automations that reduce errors, allow for graceful fallbacks, and manage alerts. Maybe you want to add a little disk space or delete some files when you get a warning that utilization is at 90% percent. Or hey, have you tried turning it off and then back on again?

Developers love automating solutions to their problems, and with the rise of generative AI, this concept is likely to be applied to both the creation, maintenance, and the improvement of code at an entirely new level... "People have talked about technical debt for a long time, and now we have a brand new credit card here that is going to allow us to accumulate technical debt in ways we were never able to do before," said Armando Solar-Lezama, a professor at the Massachusetts Institute of Technology's Computer Science & Artificial Intelligence Laboratory, in an interview with the Wall Street Journal. "I think there is a risk of accumulating lots of very shoddy code written by a machine," he said, adding that companies will have to rethink methodologies around how they can work in tandem with the new tools' capabilities to avoid that.
Despite the occasional "hallucination" of non-existent information, Stack Overflow's blog acknowledges that large-language models improve when asked to review their response, identify errors, or show its work.

And they point out the project manager in charge of generative models at Google "believes that some of the work of checking the code over for accuracy, security, and speed will eventually fall to AI." Google is already using this technology to help speed up the process of resolving code review comments. The authors of a recent paper on this approach write that, "As of today, code-change authors at Google address a substantial amount of reviewer comments by applying an ML-suggested edit. We expect that to reduce time spent on code reviews by hundreds of thousands of hours annually at Google scale. Unsolicited, very positive feedback highlights that the impact of ML-suggested code edits increases Googlers' productivity and allows them to focus on more creative and complex tasks...."

Recently, we've seen some intriguing experiments that apply this review capability to code you're trying to deploy. Say a code push triggers an alert on a build failure in your CI pipeline. A plugin triggers a GitHub action that automatically send the code to a sandbox where an AI can review the code and the error, then commit a fix. That new code is run through the pipeline again, and if it passes the test, is moved to deploy... Right now his work happens in the CI/CD pipeline, but [Calvin Hoenes, the plugin's creator] dreams of a world where these kind of agents can help fix errors that arise from code that's already live in the world. "What's very fascinating is when you actually have in production code running and producing an error, could it heal itself on the fly?" asks Hoenes...

For now, says Hoenes, we need humans in the loop. Will there come a time when computer programs are expected to autonomously heal themselves as they are crafted and grown? "I mean, if you have great test coverage, right, if you have a hundred percent test coverage, you have a very clean, clean codebase, I can see that happening. For the medium, foreseeable future, we probably better off with the humans in the loop."
Last month Stack Overflow themselves tried an AI experiment that helped users to craft a good title for their question.