Long-time Slashdot reader destinyland writes: They say "always be learning" — but do podcasts actually help? I've been trying to find podcasts that discuss programming, and I've enjoyed Lex Fridman's interviews with language creators like Guido van Rossum, Chris Lattner, and Brendan Eich (plus his long interviews with Donald Knuth). Then I discovered that GitHub, Red Hat, Stack Overflow, and the Linux Foundation all have their own podcast.

There's a developer podcast called "Corecursive" that I like with the tagline "the stories behind the code," plus a whole slew of (sometimes language-specific) podcasts at Changelog (including an interview with Brian Kernighan). And it seems like there's an entirely different universe of content on YouTube — like the retired Microsoft engineer doing "Dave's Garage," Software Engineering Daily, and the various documentaries by Honeypot.io. Computerphile has also scored various interviews with Brian Kernighan, and if you search YouTube enough you'll find stray interviews with Steve Wozniak.

But I wanted to ask Slashdot's readers: Do you listen to podcasts about computer science? And if so, which ones? (Because I'm always stumbling across new programming podcasts, which makes me worry about what else I've been missing out on.) Maybe I should also ask if you ever watch coding livestreams on Twitch — although that gets into the more general question of just how much content we consume that's related to our profession.
Fascinating discussions, or continuing work-related education? (And do podcasts really help keep your skills fresh? Are coding livestreams on Twitch just a waste of time?) Most importantly, does anyone have a favorite geek podcast that they're listening to? Share your own experience and opinions in the comments...

What's the best podcast about computer science?

"We extended the capabilities of ChatGPT to robotics," brags a blog post from Microsoft's Autonomous Systems and Robotics research group, "and controlled multiple platforms such as robot arms, drones, and home assistant robots intuitively with language."

They're exploring how to use ChatGPT to "make natural human-robot interactions possible... to see if ChatGPT can think beyond text, and reason about the physical world to help with robotics tasks." We want to help people interact with robots more easily, without needing to learn complex programming languages or details about robotic systems. The key challenge here is teaching ChatGPT how to solve problems considering the laws of physics, the context of the operating environment, and how the robot's physical actions can change the state of the world.

It turns out that ChatGPT can do a lot by itself, but it still needs some help. Our technical paper describes a series of design principles that can be used to guide language models towards solving robotics tasks. These include, and are not limited to, special prompting structures, high-level APIs, and human feedback via text.... In our work we show multiple examples of ChatGPT solving robotics puzzles, along with complex robot deployments in the manipulation, aerial, and navigation domains....

We gave ChatGPT access to functions that control a real drone, and it proved to be an extremely intuitive language-based interface between the non-technical user and the robot. ChatGPT asked clarification questions when the user's instructions were ambiguous, and wrote complex code structures for the drone such as a zig-zag pattern to visually inspect shelves. It even figured out how to take a selfie! We also used ChatGPT in a simulated industrial inspection scenario with the Microsoft AirSim simulator. The model was able to effectively parse the user's high-level intent and geometrical cues to control the drone accurately....

We are excited to release these technologies with the aim of bringing robotics to the reach of a wider audience. We believe that language-based robotics control will be fundamental to bring robotics out of science labs, and into the hands of everyday users.

That said, we do emphasize that the outputs from ChatGPT are not meant to be deployed directly on robots without careful analysis. We encourage users to harness the power of simulations in order to evaluate these algorithms before potential real life deployments, and to always take the necessary safety precautions. Our work represents only a small fraction of what is possible within the intersection of large language models operating in the robotics space, and we hope to inspire much of the work to come.tics to the reach of a wider audience. We believe that language-based robotics control will be fundamental to bring robotics out of science labs, and into the hands of everyday users.
ZDNet points out that Google Research and Alphabet's Everyday Robots "have also worked on similar robotics challenges using a large language models called PaLM, or Pathways Language Model, which helped a robot to process open-ended prompts and respond in reasonable ways."

Slashdot reader sleeping cat shares a recent FOSDEM talk by a compiler engineer on the team building Rust-GCC, "an alternative compiler implementation for the Rust programming language."

"If gccrs interprets a program differently from rustc, this is considered a bug," explains the project's FAQ on GitHub.

The FAQ also notes that LLVM's set of compiler technologies — which Rust uses — "is missing some backends that GCC supports, so a gccrs implementation can fill in the gaps for use in embedded development." But the FAQ also highlights another potential benefit: With the recent announcement of Rust being allowed into the Linux Kernel codebase, an interesting security implication has been highlighted by Open Source Security, inc. When code is compiled and uses Link Time Optimization (LTO), GCC emits GIMPLE [an intermediate representation] directly into a section of each object file, and LLVM does something similar with its own bytecode. If mixing rustc-compiled code and GCC-built code in the Linux kernel, the compilers will be unable to perform a full link-time optimization pass over all of the compiled code, leading to absent CFI (control flow integrity).

If Rust is available in the GNU toolchain, releases can be built on the Linux kernel (for example) with CFI using LLVM or GCC.
Started in 2014 (and revived in 2019), "The effort has been ongoing since 2020...and we've done a lot of effort and a lot of progress," compiler engineer Arthur Cohen says in the talk. "We have upstreamed the first version of gccrs within GCC. So next time when you install GCC 13 — you'll have gccrs in it. You can use it, you can start hacking on it, you can please report issues when it inevitably crashes and dies horribly."

"One big thing we're doing is some work towards running the rustc test suite. Because we want gccrs to be an actual Rust compiler and not a toy project or something that compiles a language that looks like Rust but isn't Rust, we're trying really hard to get that test suite working."

Read on for some notes from the talk...

Coinbase, the second largest crypto exchange by trading volume, has launched Base, an Ethereum-focused layer-2 (L2) blockchain, said Jesse Pollak, lead for Base and head of protocols at Coinbase. From a report: In the past, Coinbase has homed in on the trading and exchange side of its business, but from the utility perspective, it's still too hard for developers to build useful decentralized applications (dApps) and for users to actually use those things on-chain, Pollak said. In an effort to expand further into the developer space, Coinbase is building Base to make it "dead easy" for developers to build dApps and for users to access those dApps through Coinbase products, Pollak said. "Our goal is to bring about phase 4 of Coinbase's master plan: to bring a billion users into the crypto economy."

The L2 is a "secure, low-cost, developer-friendly" chain that aims to help builders create dApps on-chain, the company stated. Base is built on the MIT-licensed OP Stack in collaboration with the layer-2 blockchain Optimism, which is also focused on the Ethereum chain. A number of crypto businesses, platforms, marketplaces and infrastructure firms have committed to building on Base, a Coinbase spokesperson told TechCrunch. Those that plan to be involved include Blockdaemon, Chainlink, Etherscan, Quicknode, Aave, Animoca Brands, Dune, Nansen, Magic Eden, Pyth, Rainbow Wallet, Ribbon Finance, The Graph, Wormhole and Gelato, to name a handful.

RMS Titanic Inc (RMST), which has been collecting artifacts associated with the ship since the 1980s, has hooked up with NFT flinger Artifact Labs and Venture Smart Financial Holdings to "bring the RMS Titanic and its physical artifacts into Web3." The Register reports: Aiming to "place the legacy of the Titanic in the hands of the global public," at least those dumb enough to dabble in NFTs, the name of the game is to preserve "assets from the ocean liner as immutable NFTs" and allow "inclusive participation in RMST, which holds the exclusive rights to recover artifacts from the wreck site." According to the announcement, Venture Smart Financial Holdings, Hong Kong's first approved virtual asset manager, will "lead in structuring the tokenization of the intellectual property and also develop tokenized instruments for accredited investors, drawing on its expertise as a licensed virtual asset manager. This will enable compliant capital raising for the ongoing research, recovery, preservation, exhibition, and licensing of RMST's assets."

Artifact Labs will then go about "immutably" preserving "5,500 recovered physical artifacts from the Titanic with its NFT standard for historical assets on the blockchain." RMST controversially has sole salvaging rights to the wreck so fresh relics from future dives will be minted as "ARTIFACTs." Jessica Sanders, RMST president, said: "We remain dedicated to sharing the legacy of the Titanic, her passengers and crew, with people around the world. As the salvor-in-possession of the Titanic wreck site, we are determined to ensure that the Ship's artifacts are preserved in perpetuity and accessible to future generations. We believe that moving into the digital space allows us to reach a broader audience with quality programming that educates and inspires. We are excited to have found the expertise and partners to help us reach those goals." "While RMST goes to great pains to paint it in a sympathetic light, the actions of the company show that the world's most famous shipwreck is just there to be milked -- hence NFTs as another revenue stream," adds The Register.

Three years after Rails was introduced in 2005, InfoWorld asked whether it might the successor to Java.

That didn't happen. So this week InfoWorld "spoke to current and former Ruby programmers to try to trace the language's rise and fall." Some responses: "Rails came along at the cusp of a period of transformation and growth for the web," says Matthew Boeh, a Ruby developer since 2006. "It both benefited from and fueled that growth, but it was a foregone conclusion that it wasn't going to be the only success story." Boeh recently took a job as a senior staff software engineer at Lattice, a TypeScript shop. "You could say that Ruby has been a victim of its own success, in that its community was a major driving force in the command-line renaissance of recent years," he says. "In the early '00s it was introducing REPL-driven development to people who had never heard of Lisp, package management to people who would have been scared off by Perl's CPAN, test-driven development to people outside the highly corporate Java world, and so on. This is all stuff that is considered table stakes today. Ruby didn't originate any of it, but it was all popularized and made accessible by Rubyists...."

"The JavaScript ecosystem in its current form would have been unimaginable in 2004 — it needed both the command line renaissance and the takeoff of the web platform," adds Lattice's Boeh. "Did you know it took a full decade, 1999 to 2009, to release a single new version of the JavaScript standard? We get one yearly now. Rails became a big deal in the very last time period where it was possible to be a full-stack developer without knowing JavaScript...."

[W]hen it comes to data science, Python has a leg up because of the ready availability of libraries like TensorFlow and Keras. "These frameworks make it easy for coders to build data visualizations and write programs for machine learning," says Pulkit Bhardwaj, e-commerce coach at BoutiqueSetup.net. JavaScript, meanwhile, has spawned seemingly endless libraries that developers can easily download and adapt for just about any purpose. "As a technologist, you can go on your own hero's journey following whatever niche thing you think is the right way to go," says Trowbridge. But when it comes to JavaScript, "these libraries are excellent. Why ignore all of that?"

Many of those libraries were developed by community members, which inspired others to contribute in a snowball effect familiar to anyone involved in open source. But one big player has had an outsized influence here. Python's TensorFlow, which Bhardwaj called a "game-changer," was released by Google, which has followed academia's lead and made Python its internal scripting language. Google, as the maker of the dominant web browser, also has an obvious interest in boosting JavaScript, and Trowbridge gives Google much of the credit for making JavaScript much faster and more memory efficient than it once was: "In some ways it feels almost like a low level language," he says. Meanwhile, Ruby is widely acknowledged to be lagging in performance, in part because it lacks the same sort of corporate sponsor with resources for improving it.

"All right, we're going to begin this hour with a question on many people's minds these days, amid all these major developments in the field of artificial intelligence. And that question is this: How long until the machines replace us, take our jobs?"

That's the beginning of a segment broadcast on CBS's morning-television news show (with the headline, "Will artificial intelligence erase jobs?") Some excerpts:


"As artificial intelligence gets better.... job security is only supposed to get worse. And in reports like this one, of the top jobs our AI overlords plan to kill, coding or computing programming is often on the list. So with the indulgence of Sam Zonka, a coder and instructor at the General Assembly coding school in New York, I decided to test the idea of an imminent AI takeover -- by seeing if the software could code for someone who knows as little about computers as me -- eliminating the need to hire someone like him."

Gayle King: "So all this gobbledy-gook on the screen. That's what people who sit in these classrooms learn?"

"And I for one was prepared to be amazed. But take a look at the results. About as basic as a basic web site can be."

King: What do you think? You're the professional.
Zonka: Ehh.

[Microsoft CEO Satya Nadella also spoke to CBS right before the launch of its OpenAI-powered Bing search engine, arguing that AI will create more satisfaction in current jobs as well as more net new jobs -- and even helping the economy across the board. "My biggest worry," Nadella says, "is we need some new technology that starts driving real productivity. It's time for some real innovation.]

King: Do you think it'll drive up wages?
Nadella: I do believe it will drive up wages, because productivity and wages are related.


At the end of the report, King tells his co-anchors "In the long term, the research suggests Nadella is correct. In the long term, more jobs, more money. It's in the short-term that all the pain happens."

The report also features an interview with MIT economist David Autor, saying he believes the rise of AI "does indeed mean millions of jobs are going to change in our lifetime. And what's scary is we're just not sure how.... He points out, for example, that more than 60% of the types of jobs people are doing today didn't even exist in the 1940s -- while many of the jobs that did exist have been replaced."

There was also a quote from Meredith Whittaker (co-founder of the AI Now Institute and former FTC advisor), who notes that AI systems "don't replace human labor. They just require different forms of labor to sort of babysit them to train them, to make sure they're working well. Whose work will be degraded and whose house in the Hamptons will get another wing? I think that's the fundamental question when we look at these technologies and ask questions about work."

Later King tells his co-anchors that Whittaker's suggestion was for workers to organize to try to shape how AI system are implemented in their workplace.

But at an open house for the General Assembly code camp, coder Zonka says on a scale of 1 to 10, his worry about AI was only a 2. "The problem is that I'm not entirely sure if the AI that would replace me is 10 years from now, 20 years from now, or 5 years from now."

So after speaking to all the experts, King synthesized what he'd learned. "Don't necessarily panic. You see these lists of all the jobs that are going to be eliminated. We're not very good at making those predictions. Things happen in different ways than we expect. And you could actually find an opportunity to make more money, if you figure out how you can complement the machine as opposed to getting replaced by the machine."

Comparatively few people follow the Crown channel or participate in its chats -- suggesting they aren't engaging with the programming. From a report: When Amazon launched the Crown Channel on its livestreaming platform Twitch in 2019, the e-commerce giant was looking to flex its entertainment chops in the buzzy world of video games -- an arena the company had been trying to break into for years. Resembling a traditional television network, Crown offers a range of ad-supported original programming, including "Screen Invaders!," a show about mobile gaming. Amazon says Crown is among Twitch's top 10 entertainment channels, luring tens of thousands of viewers -- a feat typically equaled only by Twitch's top personalities -- and is attracting such big-name advertisers as chipmaker Intel and insurer Progressive. But a Bloomberg analysis of Crown audience metrics shows the channel isn't as popular as Amazon says it is. That has potential implications for brands, which according to internal documents, may have paid anywhere from $150,000 to $500,000-plus to promote themselves on the channel.

A pitch deck for advertisers from January 2022 said the Crown channel then reached 43 million viewers and had a "highly engaged audience." But most of the viewers Crown cites are what the advertising industry calls "junk views," people who aren't actively watching the programming. Although Crown appears to draw in thousands of viewers each livestream, comparatively few people follow the channel or participate in its chats -- suggesting they aren't engaging with the content. Amazon sometimes pays Twitch tens of thousands of dollars to promote Crown programs on the site's home page, where they end up in a digital carousel that viewers scroll through, typically zipping past shows until they find something they want to watch. Audience inflation has been a long-standing issue for video and social-media sites.

More than 400 malicious packages were recently uploaded to PyPI (Python Package Index), the official code repository for the Python programming language, in the latest indication that the targeting of software developers using this form of attack isn't a passing fad. From a report: All 451 packages found recently by security firm Phylum contained almost identical malicious payloads and were uploaded in bursts that came in quick succession. Once installed, the packages create a malicious JavaScript extension that loads each time a browser is opened on the infected device, a trick that gives the malware persistence over reboots. The JavaScript monitors the infected developer's clipboard for any cryptocurrency addresses that may be copied to it. When an address is found, the malware replaces it with an address belonging to the attacker. The objective: intercept payments the developer intended to make to a different party.

An anonymous reader quotes a report from MIT Technology Review: Many software projects emerge because -- somewhere out there -- a programmer had a personal problem to solve. That's more or less what happened to Graydon Hoare. In 2006, Hoare was a 29-year-old computer programmer working for Mozilla, the open-source browser company. Returning home to his apartment in Vancouver, he found that the elevator was out of order; its software had crashed. This wasn't the first time it had happened, either. Hoare lived on the 21st floor, and as he climbed the stairs, he got annoyed. "It's ridiculous," he thought, "that we computer people couldn't even make an elevator that works without crashing!" Many such crashes, Hoare knew, are due to problems with how a program uses memory. The software inside devices like elevators is often written in languages like C++ or C, which are famous for allowing programmers to write code that runs very quickly and is quite compact. The problem is those languages also make it easy to accidentally introduce memory bugs -- errors that will cause a crash. Microsoft estimates that 70% of the vulnerabilities in its code are due to memory errors from code written in these languages.

Most of us, if we found ourselves trudging up 21 flights of stairs, would just get pissed off and leave it there. But Hoare decided to do something about it. He opened his laptop and began designing a new computer language, one that he hoped would make it possible to write small, fast code without memory bugs. He named it Rust, after a group of remarkably hardy fungi that are, he says, "over-engineered for survival." Seventeen years later, Rust has become one of the hottest new languages on the planet -- maybe the hottest. There are 2.8 million coders writing in Rust, and companies from Microsoft to Amazon regard it as key to their future. The chat platform Discord used Rust to speed up its system, Dropbox uses it to sync files to your computer, and Cloudflare uses it to process more than 20% of all internet traffic.

When the coder discussion board Stack Overflow conducts its annual poll of developers around the world, Rust has been rated the most "loved" programming language for seven years running. Even the US government is avidly promoting software in Rust as a way to make its processes more secure. The language has become, like many successful open-source projects, a barn-raising: there are now hundreds of die-hard contributors, many of them volunteers. Hoare himself stepped aside from the project in 2013, happy to turn it over to those other engineers, including a core team at Mozilla. It isn't unusual for someone to make a new computer language. Plenty of coders create little ones as side projects all the time. But it's meteor-strike rare for one to take hold and become part of the pantheon of well-known languages alongside, say, JavaScript or Python or Java. How did Rust do it?

C++ creator Bjarne Stroustrup "joins calls for changing the programming language itself to address security concerns," according to an article shared by Slashdot user guest reader: In mid-January, the official C++ "direction group" -- which makes recommendations for the programming language's evolution -- issued a statement addressing concerns about C++ safety. While many languages now support "basic type safety" -- that is, ensuring that variables access only sections of memory that are clearly defined by their data types -- C++ has struggled to offer similar guarantees.

This new statement, co-authored by C++ creator Bjarne Stroustrup, now appears to call for changing the C++ programming language itself to address safety concerns. "We now support the idea that the changes for safety need to be not just in tooling, but visible in the language/compiler, and library." The group still also supports its long-preferred use of debugging tools to ensure safety (and "pushing tooling to enable more global analysis in identifying hard for humans to identify safety concerns"). But that January statement emphasizes its recommendation for changes within C++.

Specifically, it proposes "packaging several features into profiles" (with profiles defined later as "a collection of restrictions and requirements that defines a property to be enforced" by, for example, triggering an automatic analysis.) In this way the new changes for safety "should be visible such that the Safe code section can be named (possibly using profiles), and can mix with normal code." And this new approach would ultimately bring not just safety but also flexibility, with profiles specifically designed to support embedded computing, performance-sensitive applications, or highly specific problem domains, like automotive, aerospace, avionics, nuclear, or medical applications.

"For example, we might even have safety profiles for safe-embedded, safe-automotive, safe-medical, performance-games, performance-HPC, and EU-government-regulation," the group suggests. Elsewhere in the document they put it more succinctly. "To support more than one notion of 'safety', we need to be able to name them."
Stroustrup emphasized his faith in C++ in a 2020 interview. "I think C++ can do anything Rust can do, and I would like it to be much simpler to use," Stroustrup told the Association for Computing Machinery's Special Interest Group on Programming Languages.

But even then, he'd said that basic type safety was one of his earliest design goals -- and one he's spent decades trying to achieve. "I get a little bit sad when I hear people talk about C++ as if they were back in the 1980s, the 1990s, which a lot of people do. They looked at it back in the dark ages, and they haven't looked since."

A Rust-based re-implementation of GNU core utilities like cp and mv is "reaching closer to parity with the widely-used GNU upstream and becoming capable of taking on more real-world uses," reports Phoronix: Debian developer Sylvestre Ledru [also an engineering director at Mozilla] began working on uutils during the COVID-19 pandemic and presented last week at FOSDEM 2023 on his Coreutils replacement effort. With uutils growing into increasingly good shape, it's been packaged up by many Linux distributions and is also used now by "a famous social network via the Yocto project...."

The goals with uutils are to try to create a drop-in replacement for GNU Coreutils, strive for good cross-platform support, and easy testing. Ledru's initial goals were about being able to boot Debian, running the most popular packages, building key open-source software, and all-around it's been panning out to be a great success.... [M]ore performance optimizations are to come along with other work for compatibility against the GNU tools and implementing some still missing options in different programs

Russ Cox, a Google software engineer steering the development of the open source Go programming language, has presented a possible plan to implement telemetry in the Go toolchain. However many in the Go community object because the plan calls for telemetry by default. The Register reports: These alarmed developers would prefer an opt-in rather than an opt-out regime, a position the Go team rejects because it would ensure low adoption and would reduce the amount of telemetry data received to the point it would be of little value. Cox's proposal summarized lengthier documentation in three blog posts.

Telemetry, as Cox describes it, involves software sending data from Go software to a server to provide information about which functions are being used and how the software is performing. He argues it is beneficial for open source projects to have that information to guide development. And the absence of telemetry data, he contends, makes it more difficult for project maintainers to understand what's important, what's working, and to prioritize changes, thereby making maintainer burnout more likely. But such is Google's reputation these days that many considering the proposal have doubts, despite the fact that the data collection contemplated involves measuring the usage of language features and language performance. The proposal isn't about the sort of sensitive personal data vacuumed up by Google's ad-focused groups. "Now you guys want to introduce telemetry into your programming language?" IT consultant Jacob Weisz said. "This is how you drive off any person who even considered giving your project a chance despite the warning signs. Please don't do this, and please issue a public apology for even proposing it. Please leave a blast radius around this idea wide enough that nobody even suggests trying to do this again."

He added: "Trust in Google's behavior is at an all time low, and moves like this are a choice to shove what's left of it off the edge of a cliff."

Meanwhile, former Google cryptographer and current open source maintainer Filippo Valsorda said in a post to Mastodon: "This is a large unconventional design, there are a lot of tradeoffs worth discussing and details to explore," he wrote. "When Russ showed it to me I made at least a dozen suggestions and many got implemented."

"Instead: all opt-out telemetry is unethical; Google is evil; this is not needed. No one even argued why publishing any of this data could be a problem."

Thomas Claburn writes via The Register: GitHub has a lot of code to search -- more than 200 million repositories -- and says last November's beta version of a search engine optimized for source code that has caused a "flurry of innovation." GitHub engineer Timothy Clem explained that the company has had problems getting existing technology to work well. "The truth is from Solr to Elasticsearch, we haven't had a lot of luck using general text search products to power code search," he said in a GitHub Universe video presentation. "The user experience is poor. It's very, very expensive to host and it's slow to index." In a blog post on Monday, Clem delved into the technology used to scour just a quarter of those repos, a code search engine built in Rust called Blackbird.

Blackbird currently provides access to almost 45 million GitHub repositories, which together amount to 115TB of code and 15.5 billion documents. Shifting through that many lines of code requires something stronger than grep, a common command line tool on Unix-like systems for searching through text data. Using ripgrep on an 8-core Intel CPU to run an exhaustive regular expression query on a 13GB file in memory, Clem explained, takes about 2.769 seconds, or 0.6GB/sec/core. [...] At 0.01 queries per second, grep was not an option. So GitHub front-loaded much of the work into precomputed search indices. These are essentially maps of key-value pairs. This approach makes it less computationally demanding to search for document characteristics like the programming language or word sequences by using a numeric key rather than a text string. Even so, these indices are too large to fit in memory, so GitHub built iterators for each index it needed to access. According to Clem, these lazily return sorted document IDs that represent the rank of the associated document and meet the query criteria.

To keep the search index manageable, GitHub relies on sharding -- breaking the data up into multiple pieces using Git's content addressable hashing scheme and on delta encoding -- storing data differences (deltas) to reduce the data and metadata to be crawled. This works well because GitHub has a lot of redundant data (e.g. forks) -- its 115TB of data can be boiled down to 25TB through deduplication data-shaving techniques. The resulting system works much faster than grep -- 640 queries per second compared to 0.01 queries per second. And indexing occurs at a rate of about 120,000 documents per second, so processing 15.5 billion documents takes about 36 hours, or 18 for re-indexing since delta (change) indexing reduces the number of documents to be crawled.

Google CEO Sundar Pichai told employees Monday the company is going to need all hands on deck to test Bard, its new ChatGPT rival. From a report: He also said Google will soon be enlisting help from partners to test an application programming interface, or API, that would let others access the same underlying technology. The internal memo came shortly after Pichai publicly announced Google's new conversation technology, powered by artificial intelligence, which it will begin rolling out in the coming weeks. Google has faced pressure from investors and employees to compete with ChatGPT, a chatbot from Microsoft-backed OpenAI, which took the public by storm when it launched late last year.

"Next week, we'll be enlisting every Googler to help shape Bard and contribute through a special company-wide dogfood," Pichai wrote in the email to employees that was viewed by CNBC. "We're looking forward to getting all of your feedback -- in the spirit of an internal hackathon -- more details coming soon," he wrote. Microsoft is reportedly planning to launch a version of its own search engine, Bing, that will use ChatGPT to answer users' search queries. Microsoft is holding its own event Tuesday with participation from OpenAI CEO Sam Altman. "It's early days, we need to ship and iterate and we have a lot of hard and exciting work ahead to build these technologies into our products and continue bringing the best of Google Al to improve people's lives," Pichai wrote in his note to employees Monday. "We've been approaching this effort with an intensity and focus that reminds me of early Google -- so thanks to everyone who has contributed."

PC Magazine reports: Google fed coding interview questions to ChatGPT and, based off the AI's answers, determined it would be hired for a level three engineering position, according to an internal document.... And while level three is considered an entry-level position on the engineering team at Google, average total compensation for the job is about $183,000....

When PCMag asked ChatGPT if it would ever replace software engineers, it wasn't convinced. "No, ChatGPT will not replace software engineers," the AI responded. "ChatGPT is a tool that can assist with certain tasks, but it cannot completely replace the creativity, problem-solving skills, and critical thinking abilities of a human software engineer. Additionally, ChatGPT requires human supervision and direction to operate effectively."

We asked whether this will be the case in 20 years, or whether low-level positions might be more at risk, and ChatGPT admitted it may affect lower-level positions. But it reiterated it will never be a full replacement, but rather a tool to assist human software engineers.
Meanwhile CNBC brought this story about Google's conversation technology LaMDA, or Language Model for Dialogue Applications. "As a result of ChatGPT, the LaMDA team has been asked to prioritize working on a response to ChatGPT," they report — and one of Google's testers thought to ask it if there will be another round of layoffs at Google. "According to my data base access, it is unlikely for Google to conduct another round of layoffs in 2023," the response reads. "Layoffs are generally conducted to reduce costs and structure, but the company is doing well financially. In fact, Google's revenue increased by 34% in 2021, and the company's stock price has risen by 70% since January 2022."
Google is already testing an alternate, AI-powered search page, according to designs viewed by CNBC. "When a question is entered, the search results show a gray bubble directly under the search bar, offering more human-like responses than typical search results." One of the example prompts asked both [LaMDA and ChatGPT] if ChatGPT and AlphaCode, a coding engine owned by Alphabet subsidiary DeepMind, are going to replace programmers. "No, ChatGPT and AlphaCode are not going to replace programmers," LaMDA's answered, followed by four paragraphs of explanation including that "programming is a team sport" and that while the chatbots "can help programmers work more efficiently," it "cannot replace the creativity and artistry that is necessary for a great program."

ChatGPT's response was similar, stating "It is unlikely that ChatGPT or Alphacode will replace programmers" because they are "not capable of fully replacing the expertise and creativity of human programmers...programming is a complex field that requires a deep understanding of computer science principles and the ability to adapt to new technologies."

An anonymous reader quotes a report from Bloomberg: Walt Disney Co. is exploring more licensing of its films and television series to rival media outlets as pressure grows to curb the losses in its streaming TV business. The Burbank, California-based entertainment giant is seeking to earn more cash from its content library, according to people familiar with the discussions who asked not to be identified as the talks are private. The move would represent a shift in strategy, as Disney has in recent years tried to keep much of its original programming exclusively on its Disney+ and Hulu streaming services. [CEO Bob Iger], 71, will share more of his plans when the company reports financial results on Feb. 8, but he has already taken steps to reverse decisions made by his predecessor. He offered free photos and more lower-price tickets to theme-park guests irked by rising fees.

Although Disney already licenses some titles to other platforms including Amazon's Prime streaming service, it began to hoard content with the launch of Disney+ in 2019. Disney curtailed licensing of its own programs to third parties to boost that service. A deal that had Disney films running on Netflix was phased out, and the company touted how much of its new programming came from its own in-house studios. Wall Street cheered at the time because it meant the company was entirely focused on building out the streaming business. The shift was costly, however, as Disney surrendered billions of dollars from home video sales and licensing deals with other networks.

An anonymous reader shares a report: BMW i4 owner was rightfully puzzled when their car flashed a strange alert on the screen, saying its parking spot was "too steep" to perform an over-the-air software upgrade. How does that happen? And why is it a problem in the first place? As Clare Eliza found out, it simply isn't possible to remotely update any of the i4's software if the car isn't parked on flat ground. And instead of allowing the operator to override this, it will wait until you physically move it somewhere more level to continue. As it turns out, BMW doesn't have one singular reason why the vehicle can't perform this task on an incline. Rather, the limitation is there as a safety blanket.

"The vehicle has all sorts of sensors (pitch, yaw, lateral and longitudinal acceleration and deceleration, etc.) that allow it to understand its orientation, so it knows when it's on an incline," a BMW spokesperson told The Drive. "It's likely a catchall, every-worst-case-no-matter-how-unlikely scenario safety precaution to try to prevent any chance of the vehicle moving should the programming be interrupted or go wrong." Essentially, it's there just in case something unexpected happens; it's better to plan for the worst, after all.

After years of day-to-day absence, Google cofounder Sergey Brin filed a request for access to code related to the company's natural language chatbot, LaMDA. Forbes reports: Two sources said the request was related to LaMDA, Google's natural language chatbot -- a project initially announced in 2021, but which has recently garnered increased attention as Google tries to fend off rival OpenAI, which released the popular ChatGPT bot in November. Brin filed a "CL," short for "changelist," to gain access to the data that trains LaMDA, one person who saw the request said. It was a two line change to a configuration file to add his username to the code, that person said. Several dozen engineers gave the request LGTM approval, short for "looks good to me." Some of the approvals came from workers outside of that team, seemingly just eager to be able to say they gave code review approval to the company cofounder, that person added.

The move was a small technical change, but underscores how seriously the company is taking the looming threat from OpenAI and other competitors. Brin and cofounder Larry Page have been largely absent from the company since 2019, when Page handed the reins over to Sundar Pichai to become CEO of Google parent Alphabet. But Pichai has recently called in the company founders to review the company's AI strategy and help form a response to ChatGPT, according to the New York Times. Brin's tinkering highlights the level of involvement the cofounders have taken.

What happens when Stack Overflow's senior research analyst delves more deeply into results from their annual Developer Survey? Rust, Elixir, Clojure, Typescript, and Julia are at the top of the list of Most Loved Programming Languages. However, in looking at the last three years, we see a bit of movement. [While Rust has remained #1 since 2020, Elixir has risen to #2, while Clojure and TypeScript have dropped.]

In 2022, we added a drill-down to specifically show popularity amongst those learning to code. Because Stack Overflow is a learning resource, I would expect that popularity amongst those specifically learning would be a good indicator of current and future programming language popularity. There is an interesting pattern in comparing Most Loved and Learning to Code Popularity: people learning to code aren't using the most loved languages....


Less than 1% of those learning responded they were using either Clojure or Elixir.

1.2% are using Julia
7.1% are using Rust
and 15.1% are using Typescript.
The article still tries to tease out ways to predict future popular programming languages (by, for example, the number of questions being asked about languages, especially by new programmers learning to code). But along the way, they uncover other surprising statistical truths about the limits of their data:

• "Stack Overflow questions are more susceptible to the preferences of those using the site as a learning tool rather than those of more advanced developers."

• "[B]eing loved (via the Developer Survey) is not related to generating more questions on Stack Overflow. And this makes sense: posting questions most likely speaks to friction with coding, a friction that may lead to loving a programming language less."

• "Our latest Developer Survey showed us that ~32% of programmers have been professionally coding for four years or less, a significant amount of people who are most likely involved in learning programming languages. That is, beginner-friendly languages get the most questions and popularity, but the Most Loved languages make veteran developers happy."