The Boston Globe reports that U.S. Senator Ed. Markey just sent a letter to more than 20 car manufacturers asking them to continue including AM radios in future car models — including electric vehicles: Some EV manufacturers have raised concerns even as far back as 2016 about how the battery power of an EV can interfere with AM radio signals. However, Markey addressed these concerns saying, "car manufacturers appear to have developed innovative solutions to this problem."
"The last time I listened to AM radio was in the late 1970s," writes long-time Slashdot reader non-e-moose. "And then it was mostly because there were either no FM stations in reception range, or I was riding my bicycle and only had a transistor radio."

But the Senator sees it differently: AM radio has long been an important source of information for consumers. Before the COVID-19 pandemic, nearly 90 percent of Americans ages 12 and older — totaling hundreds of millions of people — listened to AM or FM radio each week, higher than the percentage that watch television (56 percent) or own a computer (77 percent).... Moreover, 33 percent of new car buyers say that AM radio is a very important feature in a vehicle — higher than dedicated Wi-Fi (31 percent), SiriusXM satellite radio (27 percent), and personal assistants such as Google Assistant (12 percent) and Amazon Alexa (9 percent). In other words, broadcast AM and FM radio remain an essential vehicle feature for consumers.

Moreover, broadcast AM radio, in particular, is a critical mechanism for government authorities to communicate with the public during natural disasters, extreme weather events, and other emergencies. AM radio operates at lower frequencies and has longer wavelengths than FM radio, so AM radio waves more easily pass through solid objects. As a result, AM radio signals can travel long distances, making them well-suited for broadcasting emergency alerts....

Despite innovations such as the smartphone and social media, AM/FM broadcast radio remains the most dependable, cost-free, and accessible communication mechanism for public officials to communicate with the public during times of emergency. As a result, any phase-out of broadcast AM radio could pose a significant communication problem during emergencies.... Given AM radio's importance for emergency communications and continued consumer demand, I urge your company to maintain the feature in its new vehicles...

"Rust is awesome, for certain things. But think twice before picking it up for a startup that needs to move fast," Matt Welsh, co-founder and chief executive of Fixie.ai and former Google engineering director, writes in a blog post. From the post: I hesitated writing this post, because I don't want to start, or get into, a holy war over programming languages. (Just to get the flame bait out of the way, Visual Basic is the best language ever!) But I've had a number of people ask me about my experience with Rust and whether they should pick up Rust for their projects. So, I'd like to share some of the pros and cons that I see of using Rust in a startup setting, where moving fast and scaling teams is really important. Right up front, I should say that Rust is very good at what it's designed to do, and if your project needs the specific benefits of Rust (a systems language with high performance, super strong typing, no need for garbage collection, etc.) then Rust is a great choice. But I think that Rust is often used in situations where it's not a great fit, and teams pay the price of Rust's complexity and overhead without getting much benefit.

My primary experience from Rust comes from working with it for a little more than 2 years at a previous startup. This project was a cloud-based SaaS product that is, more-or-less, a conventional CRUD app: it is a set of microservices that provide a REST and gRPC API endpoint in front of a database, as well as some other back-end microservices (themselves implemented in a combination of Rust and Python). Rust was used primarily because a couple of the founders of the company were Rust experts. Over time, we grew the team considerably (increasing the engineering headcount by nearly 10x), and the size and complexity of the codebase grew considerably as well. As the team and codebase grew, I felt that, over time, we were paying an increasingly heavy tax for continuing to use Rust. Development was sometimes sluggish, launching new features took longer than I would have expected, and the team was feeling a real productivity hit from that early decision to use Rust. Rewriting the code in another language would have, in the long run, made development much more nimble and sped up delivery time, but finding the time for the major rewrite work would have been exceedingly difficult.

So we were kind of stuck with Rust unless we decided to bite the bullet and rewrite a large amount of the code. Rust is supposed to be the best thing since sliced bread, so why was it not working so well for us? [...] Despite being some of the smartest and most experienced developers I had worked with, many people on the team (myself included) struggled to understand the canonical ways to do certain things in Rust, how to grok the often arcane error messages from the compiler, or how to understand how key libraries worked (more on this below). We started having weekly "learn Rust" sessions for the team to help share knowledge and expertise. This was all a significant drain on the team's productivity and morale as everyone felt the slow rate of development. As a comparison point of what it looks like to adopt a new language on a software team, one of my teams at Google was one of the first to switch entirely from C++ to Go, and it took no more than about two weeks before the entire 15-odd-person team was quite comfortably coding in Go for the first time.

An anonymous reader quotes a report from Ars Technica: The Comcast "Broadcast TV" fee that isn't included in the company's advertised prices is rising again, tacking as much as $27 onto the monthly bills of cable TV users. Comcast's Broadcast TV and Regional Sports Network fees combined could add nearly $40 to a customer's monthly TV bill after next month's price hikes, all while Comcast advertises much lower prices than people actually pay. "Comcast has started notifying customers and municipalities that it plans to raise video and Internet prices next month, including a whopping $7.35 a month increase for the Broadcast TV fee in one town," a TV Answer Man article said on Saturday. The $7.35-per-month increase is in Taunton, Massachusetts, where Comcast said the Broadcast TV fee will rise from $18.65 to $26.

The Broadcast TV fee is rising from $24.95 a month to $27.25 a month starting on December 20 in Sandown, New Hampshire, a letter (PDF) from Comcast to town government officials said. In Sandown, the Regional Sports Network fee is rising from $11.85 to $12. The TV Answer Man report also said several towns in Michigan were "alerted that the Broadcast Fee will rise from $14.80 to $20.70 a month while the monthly Regional Sports fee will go from $9.50 to $10.15." These are just a few examples as Comcast is raising prices nationwide.

The Broadcast TV charges added to customer bills vary by region. Comcast says the fees are based on the amounts that "broadcast stations charge us to carry them on our cable systems." It's true that Comcast has to pay retransmission consent fees to carry the stations, even though stations can be accessed for free over the air with an antenna. But the sneaky manner in which Comcast and other cable companies pass those costs on to customers can lead to bill shock and unexpected price increases. Comcast's advertised prices do not include the Broadcast TV or the Regional Sports Network fees even though these fees account for a large portion of customers' actual monthly bills. On Comcast's ordering website, the base prices are listed along with a message stating that Broadcast TV and Regional Sports fees are "extra" and that the price is "subject to change." The Broadcast TV and Regional Sports fees also aren't included in how Comcast calculates promotional pricing and thus can be raised even when a customer's promotional rate hasn't expired. Comcast says it's also raising the base prices of monthly service plans, saying the average increase nationwide is 3.8 percent.

Comcast's statement on the price increases blamed the rising cost of video programming but said the overall increases are lower than the most recent inflation rate: "TV networks and other video programmers continue to raise their prices, with broadcast television and sports being the biggest drivers of increases in customers' bills. We're continuing to work hard to manage these costs for our customers while investing in our broadband network to provide the best, most reliable Internet service in the country and to give our customers more low-cost choices in video and connectivity so they can find a package that fits their lifestyle and budget. Our national average increase of 3.8 percent is about half of the most recent rate of inflation."

Long-time Slashdot reader destinyland writes: A new book identifies "26 Lines of Code That Changed the World." But its cheeky title also incorporates a comment from Unix's source code — "You are Not Expected to Understand This". From a new interview with the book's editor:

With chapter titles like "Wear this code, go to jail" and "the code that launched a million cat videos," each chapter offers appreciations for programmers, gathering up stories about not just their famous lives but their sometimes infamous works. (In Chapter 10 — "The Accidental Felon" — journalist Katie Hafner reveals whatever happened to that Harvard undergraduate who went on to inadvertently create one of the first malware programs in 1988...) The book quickly jumps from milestones like the Jacquard Loom and the invention of COBOL to bitcoin and our thought-provoking present, acknowledging both the code that guided the Apollo 11 moon landing and the code behind the 1962 videogame Spacewar. The Smithsonian Institution's director for their Center for the Study of Invention and Innovation writes in Chapter 4 that the game "symbolized a shift from computing being in the hands of priest-like technicians operating massive computers to enthusiasts programming and hacking, sometimes for the sheer joy of it."

I contributed chapter 9, about a 1975 comment in some Unix code that became "an accidental icon" commemorating a "momentary glow of humanity in a world of unforgiving logic." This chapter provided the book with its title. (And I'm also responsible for the book's index entry for "Linux, expletives in source code of".) In a preface, the book's editor describes the book's 29 different authors as "technologists, historians, journalists, academics, and sometimes the coders themselves," explaining "how code works — or how, sometimes, it doesn't work — owing in no small way to the people behind it."

"I've been really interested over the past several years to watch the power of the tech activists and tech labor movements," the editor says in this interview. "I think they've shown really immense power to effect change, and power to say, 'I'm not going to work on something that doesn't align with what I want for the future.' That's really something to admire.

"But of course, people are up against really big forces...."

Linux 6.1 (released last month) included what Linus Torvalds described as "initial Rust scaffolding," remembers this update from SD Times But now, "work has already been done since the 6.1 release to add more infrastructure for Rust in the kernel, though still none of the code interacts with any C code."

And there's still no actual Rust code in Linux: "You need to get all those things that can make sure that Rust can compile, and you can do the debugging and all these things," explained Joel Marcey, director of advocacy and operations for the Rust Foundation, "and make sure that the memory safety is there and all that sort of stuff. And that has to happen first before you can actually write any real code in Rust for the Linux kernel itself."

Marcey explained that Linux is going to be doing this inclusion very piecemeal, with lots of little integrations here and there over time so they can see how it is working. "I would imagine that over the next year, you're going to see more small incremental changes to the kernel with Rust, but as people are seeing that it's actually kind of working out, you'll be able to maybe, for example, write Linux drivers or whatever with Rust," said Marcey....

According to Bec Rumbul, executive director of the Rust Foundation, Rust being added to the kernel is an "enormous vote of confidence in the Rust programming language." She explained that in the past other languages have been planned to make it into the kernel and ended up not getting put in. "I think having someone with the kind of intellectual gravity of Linus Torvalds saying 'No, it's going in there,' that kind of says an awful lot about how reliable Rust already is and how much potential there is for the future as well," she said.

Rumbul believes that there will be an increased interest in the language, which is still relatively new (It first made its debut in 2010) compared to some of the other languages out there to choose from. "I suspect that because Rust is now in the kernel, and it's just being talked about much ... more widely, that it will seem like an attractive prospect to a lot of people that are looking to develop their skills and their knowledge," she said. Rumbul hopes people will also be inspired to participate in the language as contributors and maintainers, because those are some of the less popular roles within open source, but are extremely critical to the health of a language, she explained.
The Rust Foundation also launched a new security team in September to ensure best practices (including a dedicated security engineer). Their first initiative will be a security audit and threat modeling exercises. "We want to basically shore up," Rust operations director Marcey tells SD Times, "to ensure that Rust itself is actually as secure as we always say it is."

In this year's Stack Overflow Developer Survey, 86.73% of developers said they love Rust.

Google is working on a secretive project that uses machine learning to train code to write, fix, and update itself. From a report: This project is part of a broader push by Google into so-called generative artificial intelligence, which uses algorithms to create images, videos, code, and more. It could have profound implications for the company's future and developers who write code. The project, which began life inside Alphabet's X research unit and was codenamed Pitchfork, moved into Google's Labs group this summer, according to people familiar with the matter. By moving into Google, it signaled its increased importance to leaders. Google Labs pursues long-term bets, including projects in virtual and augmented reality.

Pitchfork is now part of a new group at Labs named the AI Developer Assistance team run by Olivia Hatalsky, a long-term X employee who worked on Google Glass and several other moonshot projects. Hatalsky, who ran Pitchfork at X, moved to Labs when it migrated this past summer. Pitchfork was built for "teaching code to write and rewrite itself," according to internal materials seen by Insider. The tool is designed to learn programming styles and write new code based on those learnings, according to people familiar with it and patents reviewed by Insider. "The team is working closely with the Research team," a Google representative said. "They're working together to explore different use cases to help developers."

Kite, a start-up that has been developing artificial intelligence technology to help developers write code for nearly a decade, is saying farewell and open-sourcing its code. Silicon Republic reports: Based in San Francisco, Kite was founded in 2014 as an early pioneer in the emerging field of AI that assists software developers in writing code -- an 'autocomplete' for programming of sorts. But now, after eight years of pursuing its vision to be a leader in AI-assisted programming, founder Adam Smith announced on the company website that the business is now wrapping up. According to him, even state-of-the-art machine learning models today don't understand the structure of code -- and too few developers are willing to pay for available services. "We failed to deliver our vision of AI-assisted programming because we were 10-plus years too early to market, ie, the tech is not ready yet," Smith explained. "You can see this in GitHub Copilot, which is built by GitHub in collaboration with OpenAI. As of late 2022, Copilot shows a lot of promise but still has a long way to go."

Copilot was first revealed in June 2021 as an AI assistant for programmers that essentially does for coding what predictive text does for writing emails. Developed in collaboration with OpenAI, GitHub had kept Copilot in technical preview until this summer, during which time it had been used by more than 1.2m developers. The AI was made available to all developers in June, at a cost of $10 a month or $100 a year. However, Smith said that the inadequacy of machine learning models in understanding the structure of code, such as non-local context, has been an insurmountable challenge for the Kite team. "We made some progress towards better models for code, but the problem is very engineering intensive. It may cost over $100m to build a production-quality tool capable of synthesizing code reliably, and nobody has tried that quite yet."

While the business could have still been successful without necessarily increasing developer productivity by 10 times using AI, Smith said he thinks that Kite's delay and unsuccessful attempt at monetizing the service prevented the start-up from taking flight. "We sequenced building our business in the following order: First we built our team, then the product, then distribution and then monetization," he explained, adding that Kite did not reach product-market fit until 2019, five years after starting the company. Despite the time taken to get to the market, Smith said Kite was able to capture 500,000 monthly active developers using its AI with "almost zero marketing spend." But the product failed to generate revenue because the developers refused to pay for it. Smith says most of their code has been open sourced on GitHub, including their "data-driven Python type inference engine, Python public-package analyzer, desktop software, editor integrations, GitHub crawler and analyzer, and more more."

While the popularity of jQuery is decreasing, React.JS "is currently the most widely used client-side framework," reports ZDNet, citing SlashData's 23rd State of the Developer Nation report (compiled from more than 26,000 developers last summer from 163 countries).

ZDNet believe it shows developers "experimenting less and sticking with what they know and what works." JavaScript remains the largest programming language community, SlashData found. According to its research, there are an estimated 19.6 million developers worldwide using JavaScript every day in everything from web development and mobile apps to backend coding, cloud and game design. Java, meanwhile, is growing rapidly. In the last two years, the size of the Java community has more than doubled from 8.3 million to 16.5 million, SlashData found. For perspective, the global developer population grew about half as fast over the same period....

Python also continued to grow strongly, adding about eight million new developers over the last two years, according to SlashData. It accredited the rise of data science and machine learning as "a clear factor in Python's growing popularity". Approximately 63% of machine-learning developers and data scientists report using Python, whereas less than 15% use R, another programming language often associated with data science.
Both the Kotlin and Rust communities doubled in size in the past two years, the article points out. But according to the survey, only 9% of developers were involved in blockchain technologies.

Yet 27% of respondents reported they were learning about (if not currently working on) cryptocurrency-based projects. ZDNet summarizes the findings: Of the three blockchain technologies covered in the report, non-fungible tokens (NFTs) were found to be of least interest to developers: 58% showed "no interest" in NFTs, which SlashData said was "likely due to its perception as a novelty".

The report found that one-quarter (25%) of developers currently work on, or are learning about, blockchain applications other than cryptocurrencies.

The CTO of a software company argues the software industry's current trajectory "is toward increasing complexity, longer product-development times, and greater fragility of production systems" — not to mention nightmarish problems maintaining code.

"To address such issues, companies usually just throw more people at the problem: more developers, more testers, and more technicians who intervene when systems fail. Surely there must be a better way," they write in IEEE Spectrum. "I'm part of a growing group of developers who think the answer could be functional programming...." Today, we have a slew of dangerous practices that compromise the robustness and maintainability of software. Nearly all modern programming languages have some form of null references, shared global state, and functions with side effects — things that are far worse than the GOTO ever was. How can those flaws be eliminated? It turns out that the answer has been around for decades: purely functional programming languages....

Indeed, software based on pure functions is particularly well suited to modern multicore CPUs. That's because pure functions operate only on their input parameters, making it impossible to have any interactions between different functions. This allows the compiler to be optimized to produce code that runs on multiple cores efficiently and easily....

Functional programming also has a solution to Hoare's "billion-dollar mistake," null references. It addresses that problem by disallowing nulls. Instead, there is a construct usually called Maybe (or Option in some languages). A Maybe can be Nothing or Just some value. Working with Maybe s forces developers to always consider both cases. They have no choice in the matter. They must handle the Nothing case every single time they encounter a Maybe. Doing so eliminates the many bugs that null references can spawn.

Functional programming also requires that data be immutable, meaning that once you set a variable to some value, it is forever that value. Variables are more like variables in math...

Pure functional programming solves many of our industry's biggest problems by removing dangerous features from the language, making it harder for developers to shoot themselves in the foot.... I anticipate that the adoption of pure functional languages will improve the quality and robustness of the whole software industry while greatly reducing time wasted on bugs that are simply impossible to generate with functional programming. It's not magic, but sometimes it feels like that, and I'm reminded of how good I have it every time I'm forced to work with a non-functional codebase.

This week the Adacore blog shared a story about the NVIDIA Security Team: Like many other security-oriented teams in our industry today, they were looking for a measurable answer to the increasingly hostile cybersecurity environment and started questioning their software development and verification strategies. "Testing security is pretty much impossible. It's hard to know if you're ever done," said Daniel Rohrer, VP of Software Security at NVIDIA.

In my opinion, this is the most important point of the case study — that test-oriented software verification simply doesn't work for security. Once you come out of the costly process of thoroughly testing your software, you can have a metric on the quality of the features that you provide to the users, but there's not much you can say about security.

Rohrer continues, "We wanted to emphasize provability over testing as a preferred verification method." Fortunately, it is possible to prove mathematically that your code behaves in precise accordance with its specification. This process is known as formal verification, and it is the fundamental paradigm shift that made NVIDIA investigate SPARK, the industry-ready solution for software formal verification.

Back in 2018, a Proof-of-Concept (POC) exercise was conducted. Two low-level security-sensitive applications were converted from C to SPARK in only three months. After an evaluation of the return on investment, the team concluded that even with the new technology ramp-up (training, experimentation, discovery of new tools, etc.), gains in application security and verification efficiency offered an attractive trade-off. They realized major improvements in the security robustness of both applications (See NVIDIA's Offensive Security Research D3FC0N talk for more information on the results of the evaluation).

As the results of the POC validated the initial strategy, the use of SPARK spread rapidly within NVIDIA. There are now over fifty developers trained and numerous components implemented in SPARK, and many NVIDIA products are now shipping with SPARK components.

In an press release published earlier today, the National Security Agency (NSA) says it will be making a strategic shift to memory safe programming languages. The agency is advising organizations explore such changes themselves by utilizing languages such as C#, Go, Java, Ruby, or Swift. From the report: The "Software Memory Safety" Cybersecurity Information Sheet (PDF) highlights how malicious cyber actors can exploit poor memory management issues to access sensitive information, promulgate unauthorized code execution, and cause other negative impacts. "Memory management issues have been exploited for decades and are still entirely too common today," said Neal Ziring, Cybersecurity Technical Director. "We have to consistently use memory safe languages and other protections when developing software to eliminate these weaknesses from malicious cyber actors."

Microsoft and Google have each stated that software memory safety issues are behind around 70 percent of their vulnerabilities. Poor memory management can lead to technical issues as well, such as incorrect program results, degradation of the program's performance over time, and program crashes. NSA recommends that organizations use memory safe languages when possible and bolster protection through code-hardening defenses such as compiler options, tool options, and operating system configurations. The full report is available here (PDF).

A new article from Wired calls Rust "the 'viral' secure programming language that's taking over tech."

"Rust makes it impossible to introduce some of the most common security vulnerabilities. And its adoption can't come soon enough...." [A] growing movement to write software in a language called Rust is gaining momentum because the code is goof-proof in an important way. By design, developers can't accidentally create the most common types of exploitable security vulnerabilities when they're coding in Rust, a distinction that could make a huge difference in the daily patch parade and ultimately the world's baseline cybersecurity....

[B]ecause Rust produces more secure code [than C] and, crucially, doesn't worsen performance to do it, the language has been steadily gaining adherents and now is at a turning point. Microsoft, Google, and Amazon Web Services have all been utilizing Rust since 2019, and the three companies formed the nonprofit Rust Foundation with Mozilla and Huawei in 2020 to sustain and grow the language. And after a couple of years of intensive work, the Linux kernel took its first steps last month to implement Rust support. "It's going viral as a language," says Dave Kleidermacher, vice president of engineering for Android security and privacy. "We've been investing in Rust on Android and across Google, and so many engineers are like, 'How do I start doing this? This is great'...."

By writing new software in Rust instead, even amateur programmers can be confident that they haven't introduced any memory-safety bugs into their code.... These types of vulnerabilities aren't just esoteric software bugs. Research and auditing have repeatedly found that they make up the majority of all software vulnerabilities. So while you can still make mistakes and create security flaws while programming in Rust, the opportunity to eliminate memory-safety vulnerabilities is significant....

"Yes, it's a lot of work, it will be a lot of work, but the tech industry has how many trillions of dollars, plus how many talented programmers? We have the resources," says Josh Aas, executive director of the Internet Security Research Group, which runs the memory-safety initiative Prossimo as well as the free certificate authority Let's Encrypt. "Problems that are merely a lot of work are great."
Here's how Dan Lorenc, CEO of the software supply-chain security company Chainguard, explains it to Wired. "Over the decades that people have been writing code in memory-unsafe languages, we've tried to improve and build better tooling and teach people how to not make these mistakes, but there are just limits to how much telling people to try harder can actually work.

"So you need a new technology that just makes that entire class of vulnerabilities impossible, and that's what Rust is finally bringing to the table."

"We serve about 100 million monthly visitors worldwide," says the CEO of Stack Overflow, "making us one of the most popular websites in the world. I think we are in the top 50 of all websites in the world by traffic."

In a new interview, he says the site's been accessed about 50 billion times over the past 14 years — and then shares his thoughts on the notion that programmers could be replaced by no-code, low-code, or AI-driven pair programming: A: Over the years, there have many, many tools, trying to democratize software development. That's a very positive thing. I actually love the fact that programming is becoming easier to do with these onramps. I was speaking at Salesforce recently, and they've got people in sales organizations writing workflows, and that's low code. You've got all these folks who are not software engineers that are creating their own automations and applications.

However, there is this trade-off. If you're making software easier to build, you're sacrificing things like customizability and a deeper understanding of how this code actually works. Back in the day, you might remember Microsoft FrontPage [an early HTML web page editor] as an example of that. You were limited to certain basic things, but you could get web work done. So similarly, these tools will work for general use cases. But, if they do that, without learning the fundamental principles of code, they will inevitably have some sort of a limit. For example, having to fix something that broke, I think they're going to be really dumbfounded.

Still, I think it's important, and I'm a believer. It's a great way to get people engaged, excited, and started. But you got to know what you're building. Access to sites like Stack Overflow help, but with more people learning as they're building, it's essential to make learning resources accessible at every stage of their journey....

Q: Is Stack Overflow considering any kind of certification? Particularly, as you just mentioned, since it's so easy now for people to step in and start programming. But then there's that big step from "Yes, I got it to work," but now "I have to maintain it for users using it in ways I never dreamed of."

A: "It's very much part of our vision for our company. We see Stack Overflow going from collective knowledge to collective learning. Having all the information is fine and dandy, but are you learning? Now, that we're part of Prosus's edtech division, we're very much looking forward to offering educational opportunities. Just as today, we can get knowledge to developers at the right place and time, we think we can deliver learning at just the right place and time. We believe we can make a huge impact with education and by potentially getting into the certification game.

Q: Some of the open-source nonprofits are moving into education as well. The Linux Foundation, in particular, has been moving here with the LF Training and Certification programs. Are you exploring that?

A: This is very much part of our vision....
Stack Overflow's CEO adds that the site's hot topics now include blockchain, machine learning, but especially technical cloud questions, "rising probably about 50% year over year over the past 10 years.... Related to this is an increase in interest in containerization and cloud-native services."

The newest stable version of Rust, 1.65.0 includes generic associated types (GATs) — the ability to declare lifetime, type, and const generics on associated types. "It's hard to put into few words just how useful these can be," writes the official Rust blog.

An earlier post pointed out that "There have been a good amount of changes that have had to have been made to the compiler to get GATs to work," noting that the request-for-comments for this feature was first opened in 2016.

And Rust's types team also created a blog post with more detail: Note that this is really just rounding out the places where you can put generics: for example, you can already have generics on freestanding type aliases and on functions in traits. Now you can just have generics on type aliases in traits (which we just call associated types)....

In general, GATs provide a foundational basis for a vast range of patterns and APIs. If you really want to get a feel for how many projects have been blocked on GATs being stable, go scroll through either the tracking issue: you will find numerous issues from other projects linking to those threads over the years saying something along the lines of "we want the API to look like X, but for that we need GATs" (or see this comment that has some of these put together already). If you're interested in how GATs enable a library to do zero-copy parsing, resulting in nearly a ten-fold performance increase, you might be interested in checking out a blog post on it by Niko Matsakis.

All in all, even if you won't need to use GATs directly, it's very possible that the libraries you use will use GATs either internally or publically for ergonomics, performance, or just because that's the only way the implementation works.... [A]ll the various people involved in getting this stabilization to happen deserve the utmost thanks. As said before, it's been 6.5 years coming and it couldn't have happened without everyone's support and dedication.
Rust 1.65.0 also contains let-else statements — a new kind of let statement "with a refutable pattern and a diverging else block that executes when that pattern doesn't match," according to the release announcement.

And it highlights another new feature: Plain block expressions can now be labeled as a break target, terminating that block early. This may sound a little like a goto statement, but it's not an arbitrary jump, only from within a block to its end. This was already possible with loop blocks, and you may have seen people write loops that always execute only once, just to get a labeled break.

Now there's a language feature specifically for that! Labeled break may also include an expression value, just as with loops, letting a multi-statement block have an early "return" value.

"Microsoft's GitHub Copilot is being sued in a class action lawsuit that claims the AI product is committing software piracy on an unprecedented scale," reports IT Pro.

Programmer/designer Matthew Butterick filed the case Thursday in San Francisco, saying it was on behalf of millions of GitHub users potentially affected by the $10-a-month Copilot service: The lawsuit seeks to challenge the legality of GitHub Copilot, as well as OpenAI Codex which powers the AI tool, and has been filed against GitHub, its owner Microsoft, and OpenAI.... "By training their AI systems on public GitHub repositories (though based on their public statements, possibly much more), we contend that the defendants have violated the legal rights of a vast number of creators who posted code or other work under certain open-source licences on GitHub," said Butterick.

These licences include a set of 11 popular open source licences that all require attribution of the author's name and copyright. This includes the MIT licence, the GNU General Public Licence, and the Apache licence. The case claimed that Copilot violates and removes these licences offered by thousands, possibly millions, of software developers, and is therefore committing software piracy on an unprecedented scale.

Copilot, which is entirely run on Microsoft Azure, often simply reproduces code that can be traced back to open-source repositories or licensees, according to the lawsuit. The code never contains attributions to the underlying authors, which is in violation of the licences. "It is not fair, permitted, or justified. On the contrary, Copilot's goal is to replace a huge swath of open source by taking it and keeping it inside a GitHub-controlled paywall...." Moreover, the case stated that the defendants have also violated GitHub's own terms of service and privacy policies, the DMCA code 1202 which forbids the removal of copyright-management information, and the California Consumer Privacy Act.
The lawsuit also accuses GitHub of monetizing code from open source programmers, "despite GitHub's pledge never to do so."

And Butterick argued to IT Pro that "AI systems are not exempt from the law... If companies like Microsoft, GitHub, and OpenAI choose to disregard the law, they should not expect that we the public will sit still." Butterick believes AI can only elevate humanity if it's "fair and ethical for everyone. If it's not... it will just become another way for the privileged few to profit from the work of the many."

Reached for comment, GitHub pointed IT Pro to their announcement Monday that next year, suggested code fragments will come with the ability to identify when it matches other publicly-available code — or code that it's similar to.

The article adds that this lawsuit "comes at a time when Microsoft is looking at developing Copilot technology for use in similar programmes for other job categories, like office work, cyber security, or video game design, according to a Bloomberg report."

An anonymous reader quotes a report from TechCrunch: OpenAI, the San Francisco-based lab behind AI systems like GPT-3 and DALL-E 2, today launched a new program to provide early-stage AI startups with capital and access to OpenAI tech and resources. Called Converge, the cohort will be financed by the OpenAI Startup Fund, OpenAI says. The $100 million entrepreneurial tranche was announced last May and was backed by Microsoft and other partners. The 10 or so founders chosen for Converge will receive $1 million each and admission to five weeks of office hours, workshops and events with OpenAI staff, as well as early access to OpenAI models and "programming tailored to AI companies." The deadline to apply is November 25, but OpenAI notes that it'll continue to evaluate applications after that date for future cohorts.

With Converge, OpenAI is no doubt looking to cash in on the increasingly lucrative industry that is AI. The Information reports that OpenAI -- which itself is reportedly in talks to raise cash from Microsoft at a nearly $20 billion valuation -- has agreed to lead financing of Descript, an AI-powered audio and video editing app, at a valuation of around $550 million. AI startup Cohere is said to be negotiating a $200 million round led by Google, while Stability AI, the company supporting the development of generative AI systems, including Stable Diffusion, recently raised $101 million. The size of the largest AI startup financing rounds doesn't necessarily correlate with revenue, given the enormous expenses (personnel, compute, etc.) involved in developing state-of-the-art AI systems. (Training Stable Diffusion alone cost around $600,000, according to Stability AI.) But the continued willingness of investors to cut these startups massive checks -- see Inflection AI's $225 million raise, Anthropic's $580 million in new funding and so on -- suggests that they have confidence in an eventual return on investment. "We're excited to meet groups across all phases of the seed stage, from pre-idea solo founders to co-founding teams already working on a product," OpenAI writes in a blog post. "Engineers, designers, researchers, and product builders ... from all backgrounds, disciplines, and experience levels are encouraged to apply, and prior experience working with AI systems is not required."

It's been one week since Python 3.11 was released — and it's "faster than ever!" So says Jay Miller, a Microsoft developer writing about Microsoft's six-person "Faster CPython" team (which includes Python creator Guido van Rossum, and offers assistance to other core developers). Miller cites the team's report that Python 3.11 has already seen speedups of 10-60% in some areas of the language -- and offers this inside look at their work.

First, how the team came together: In 2020, Core Developer Mark Shannon drafted an Implementation plan for speeding up CPython (the most common implementation) by five times. This plan proposed a 4-stage process that, as Python's creator Guido van Rossum says, "was an effort that was too much for one volunteer to accomplish".

"Right from the start, my thought was well, we should try to see if Microsoft can hire Mark and a small team of people to support him." In the previous year Van Rossum came out of retirement and joined Microsoft as a Distinguished Engineer. "It was an important effort and it was too much for one person." Microsoft was open to the idea and a team of 6 engineers, including Van Rossum were established. That team has assisted other core developers in acting on this plan.
But the blog post also looks at how the team functions: Every contributor that made the switch from part-time to full-time contribution mentioned being able to get deeper into their work on the language.... The team meets regularly to discuss these things. "All six of us meet every Monday," says Van Rossum. "There's always more than enough to talk about. That is very different than as a core dev community getting together for a Sprint twice a year, like one day after the conference. That is a very special event, of course, but it doesn't feed me throughout the year." Van Rossum believes that knowledge of one another and their collaborative work gave the team a "leg up" because everyone "knows what communication styles people have and what everybody's weaknesses and strengths are...."

Shannon's original 4 stage plan has continued to evolve to have continuous optimizations for the next several years. "To make that as smooth as possible, you have to think in terms of smaller steps, right?" says [team member] Michael Droettboom. Droettboom has worked on long-term projects in the scientific community including the Hubble Space Telescope and more recently the James Web Space Telescope.... "We hope we can bring some knowledge from really large proprietary systems into what we develop for the Community." says Droettboom. "I think that's really valuable because then you're not just doing it in the abstract. Not just imagining what's going to make Python faster for real use cases, but actually measuring it." [Team member] Brandt Bucher adds in that developers working with these teams can test the impact of changes, "getting useful insights and contributions from people who maintain large, diverse codebases...." Many of the team's meetings feature core developers from other teams and companies.
The blog post highlights specific activities of team members:

• L Pereira is working on a change to how integers are represented inside Python, and "intends to change smaller integers to use native computation instead of the slower algorithms for arbitrarily large numbers."

• Irit Katriel implemented the new Exception groups and except* features in Python 3.11, and reports that "By simplifying the interpreter's internal representation of raised exceptions, I reduced the time it takes to raise and catch an exception by about 10%."

• Brandt Bucher (who helped create structural pattern matching for Python 3.10) is working on a Specialized Adaptive Interpreter (and tools like Specialist to help users move to Python).

• Long-time contributor Eric Snow is working on a per-interpreter Global Interpreter Lock.

And they've already begun working on features for future versions of Python. "You can also find out more about what the Faster CPython Team has in mind for 3.12 in their ideas repo on Github."

Developer Dan Leveille received "a sketchy voicemail from a random number about a class action lawsuit settlement..." he posted on Twitter. "I thought it was a scam and almost ignored it."

But he didn't — and ended up with $8,064.88 in his Venmo account.

Back in 2019 a lawsuit by U.S. developers accused Apple of "profit-killing" App Store commissions, reports TechForge Media. Apple settled that suit by agreeing to create a $100 million Small Developer Assistance Fund (for developers who sold in Apple's app store between June of 2015 and April of 2021). And this month Apple has finally started sending out those payments, Apple Insider reports: Developers had until May 20 to submit a request to an independent administrator to become a "Settlement Class Member." If they met the criteria, the developers stood to receive a payment from $250 to $30,000 in value....

Along with the fund, the settlement also introduced a number of changes to App Store policies, including modifications relating to customer and developer communication, new pricing tiers, and a promise by Apple to continue offering its 15% reduced App Store commission for at least three years.

Long-time Slashdot reader theodp writes: "What is your biggest pain point?", North Carolina State University PhD student Samim Mirhosseini and Microsoft Researchers Austin Z. Henley & Chris Parnin asked 32 computer science instructors at universities and community colleges. Their feedback is summed up in a just-posted paper that will be presented at SIGCSE 2023.

Instructors cited understanding what students are struggling with, answering students' questions, limited teaching assistant (TA) support, grading & feedback, course material preparation, and administrative tasks as challenges, pain points, and things they wish they could change. Interestingly, instructors indicated that some of the attempts to address pain points — including the increased use of TA's, interactive textbooks/exercises, automated grading, "flipped" classrooms [where lectures are assigned as video homework, with classtime reserved for interaction], and peer instruction — aren't always what they're cracked up to be.

- "Some TAs are not mature programmers," instructors noted. "TAs sometimes only run the unit tests and never read the code, [so] two submissions that were nearly identical, but one got [high] marks and the other got [low] marks."

- Automation brings its own challenges, instructors added, citing the problem of interactive textbooks that give grades but deduct points even if there is only a whitespace difference with the solution ("My students struggle so much with it and they spend hours trying to get the white space correct in their program when in reality that's not what I want them spending time on").

- Instructors also cited struggles with "how to design 'Copilot-proof' assignments, to prevent students from completing homework assignments in seconds with little conceptual knowledge.

- Regarding the flipped classroom, one instructor confessed, "I've checked and there's very few people watching these videos."

While grading was cited as "probably the biggest burden of the courses" and "an impossible task," one instructor still noted a preference to grade things themselves even if they have TAs "because [of] the feedback I can get from [...] their homework and assignments." Along the same lines, another noted that while they also wish for more automation of mundane tasks, they are strongly opposed to automating feedback to students because "I think this is the wrong direction for education. Striping away community and humanity from learning."

"Kathleen Booth, who has died aged 100, co-designed of one of the world's first operational computers and wrote two of the earliest books on computer design and programming," the Telegraph wrote this week.

"She was also credited with the invention of the first assembly language, a programming language designed to be readable by users." In 1946 she joined a team of mathematicians under Andrew Booth at Birkbeck College undertaking calculations for the scientists working on the X-ray crystallography images which contributed to the discovery of the double helix shape of DNA....

To help the number-crunching involved Booth had embarked on building a computing machine called the Automatic Relay Calculator or ARC, and in 1947 Kathleen accompanied him on a six-month visit to Princeton University, where they consulted John von Neumann, who had developed the idea of storing programs in a computer. On their return to England they co-wrote General Considerations in the Design of an All Purpose Electronic Digital Computer, and went on to make modifications to the original ARC to incorporate the lessons learnt.

Kathleen devised the ARC assembly language for the computer and designed the assembler.

In 1950 Kathleen took a PhD in applied mathematics and the same year she and Andrew Booth were married. In 1953 they cowrote Automatic Digital Calculators, which included the general principles involved in the new "Planning and Coding"programming style.

The Booths remained at Birkbeck until 1962 working on other computer designs including the All Purpose Electronic (X) Computer (Apexc, the forerunner of the ICT 1200 computer which became a bestseller in the 1960s), for which Kathleen published the seminal Programming for an Automatic Digital Calculator in 1958. The previous year she and her husband had co-founded the School of Computer Science and Information Systems at Birkbeck.
"The APE(X)C design was commercialized and sold as the HEC by the British Tabulating Machine Co Ltd, which eventually became ICL," remembers the Register, sharing a 2010 video about the machine (along with several links for "Further Reading.")