Longtime Slashdot reader theodp writes: Python in Excel is now generally available for Windows users of Microsoft 365 Business and Enterprise," Microsoft announced in a Monday blog post. "Last August, in partnership with Anaconda, we introduced an exciting new addition to Excel by integrating Python, making it possible to seamlessly combine Python and Excel analytics within the same workbook, no setup required. Since then, we've brought the power of popular Python analytics libraries such as pandas, Matplotlib, and NLTK to countless Excel users." Microsoft also announced the public preview of Copilot in Excel with Python, which will take users' natural language requests for analysis and automatically generate, explain, and insert Python code into Excel spreadsheets.

While drawing criticism for limiting Python execution to locked-down Azure cloud containers, Python in Excel has also earned accolades from the likes of Python creator Guido van Rossum, now a Microsoft Distinguished Engineer, as well as Pandas creator Wes McKinney.

Left unmentioned in Monday's announcement is that Microsoft managed to convince the USPTO to issue it a patent in July 2024 on the Enhanced Integration of Spreadsheets With External Environments (alt. source), which Microsoft explains covers the "implementation of enhanced integrations of native spreadsheet environments with external resources such as-but not limited to-Python." All of which may come as a surprise to software vendors and individuals that were integrating Excel and external programming environments years before Microsoft filed its patent application in September 2022.

IBM has acquired Kubecost, a FinOps startup that helps teams at companies like Allianz, Audi, Rakuten, and GitLab monitor and optimize their Kubernetes clusters with a focus on efficiency and, ultimately, cost. From a report: Tuesday's announcement follows IBM's $4.3 billion acquisition of Apptio in 2023, another company in the FinOps space. In previous years, we also saw IBM acquire companies like cloud app and network management firm Turbonomic and application performance management startup Instana. Now with the acquisition of KubeCost, IBM continues this effort to bolster its IT and FinOps capabilities as enterprises increasingly look to better manage their increasingly complex cloud and on-prem infrastructure.

Oracle cofounder Larry Ellison envisions AI as the backbone of a new era of mass surveillance, positioning Oracle as a key player in AI infrastructure through its unique networking architecture and partnerships with AWS and Microsoft. The Register reports: Ellison made the comments near the end of an hour-long chat at the Oracle financial analyst meeting last week during a question and answer session in which he painted Oracle as the AI infrastructure player to beat in light of its recent deals with AWS and Microsoft. Many companies, Ellison touted, build AI models at Oracle because of its "unique networking architecture," which dates back to the database era.

"AI is hot, and databases are not," he said, making Oracle's part of the puzzle less sexy, but no less important, at least according to the man himself - AI systems have to have well-organized data, or else they won't be that valuable. The fact that some of the biggest names in cloud computing (and Elon Musk's Grok) have turned to Oracle to run their AI infrastructure means it's clear that Oracle is doing something right, claimed now-CTO Ellison. "If Elon and Satya [Nadella] want to pick us, that's a good sign - we have tech that's valuable and differentiated," Ellison said, adding: One of the ideal uses of that differentiated offering? Maximizing AI's pubic security capabilities.

"The police will be on their best behavior because we're constantly watching and recording everything that's going on," Ellison told analysts. He described police body cameras that were constantly on, with no ability for officers to disable the feed to Oracle. Even requesting privacy for a bathroom break or a meal only meant sections of recording would require a subpoena to view - not that the video feed was ever stopped. AI would be trained to monitor officer feeds for anything untoward, which Ellison said could prevent abuse of police power and save lives. [...] "Citizens will be on their best behavior because we're constantly recording and reporting," Ellison added, though it's not clear what he sees as the source of those recordings - police body cams or publicly placed security cameras. "There are so many opportunities to exploit AI," he said.

On Tuesday Ivanti issued a "high severity vulnerability" announcement for version 4.6 of its Cloud Service Appliance (or CSA). "Successful exploitation could lead to unauthorized access to the device running the CSA." And Friday that announcement got an update: Ivanti "has confirmed exploitation of this vulnerability in the wild."

While Ivanti released a security update, they warned that "with the end-of-life status this is the last fix that Ivanti will backport for this version. Customers must upgrade to Ivanti CSA 5.0 for continued support."

This prompted a response from CISA (the Cybersecurity and Infrastructure Security Agency, part of the U.S. Department of Homeland Security). The noted that Ivanti is urging customers to upgrade to version 5.0, as "Ivanti no longer supports CSA 4.6 (end-of-life)." But in addition, CISA "ordered all federal civilian agencies to remove CSA 4.6. from service or upgrade to the 5.0. by October 4," reports the Record: Ivanti said users will know they are impacted by exploitation of the bug by looking to see if there are modified or newly added administrative users. They also urged customers to check security alerts if they have certain security tools involved.

The issue arose one day after another Ivanti bug caused alarm among defenders. The company pledged a security overhaul in April after a cascade of headline-grabbing nation-state attacks broke through the systems of government agencies in the U.S. and Europe using vulnerabilities in Ivanti products.

An anonymous reader shared this report from DevClass: A report from developer-focused analyst Redmonk finds "there does not seem to be a clear link between moving from an open source to proprietary license and increasing the company's value."

Senior analyst Rachel Stevens studied the question of whether the companies that changed from open source to proprietary licenses have since reported better financial positions. In particular, she looked at MongoDB, which changed from AGPL (GNU Affero General Public License) to its SSPL (Server Side Public License) in 2018; Elastic Co, which changed from Apache 2 to SSPL or Elastic License in early 2021; HashiCorp, which changed from MPL (Mozilla Public License 2.0) a year ago, and Confluent, which checked from Apache 2 to its own Confluent Community License in 2018.

The report is too recent to take account of Elastic's reversion to AGPL; and the financial impact of that is of course yet to be known, though it is perhaps unlikely that the switch back would have been made if the company considered it detrimental to its finances. Rather, Elastic's latest licensing change reinforces the view that proprietary licenses are not necessarily more profitable... All the companies studied increased their revenue after their license change, Stevens said, but added that the rate of change was similar to that before the change...

MongoDB stated in 2018 that "once an open source project becomes interesting or popular, it becomes too easy for the cloud vendors to capture all the value and give nothing back to the community." Six years later, it remains the case that the large cloud vendors are highly profitable, but that these companies who changed their license are not. In February this year, Bruce Perens, creator of the 1998 Open Source Definition, described open source as "a great corporate welfare program" and not at all what he had intended...

The new Redmonk report suggests that such license manoeuvres are neither fatal nor beneficial to the finances of the companies involved — though there are so many caveats that it is impossible to draw firm conclusions.
The report's final sentence concludes that "there does not seem to be a clear link between moving from an open source to proprietary license and increasing the company's value."

Wired published some thoughts from Hans Peter Brondmo, the former head of "Google's seven-year mission to give AI a robot body".

An anonymous reader shared this report from Axios: Building AI-powered robots that can flexibly operate in the real world is going to take much longer than Silicon Valley believes and promises, according to the former head of Google's robotics moonshot project, writing in Wired...

Everyday Robotics spent seven years and a small Google fortune developing a one-armed robot on a wheeled platform. By the time Google pulled the plug on the project in February 2023, the robots were helping clean up researchers' desks and sorting trash during the daytime; in the evening, they were improvising dances. [Google hired a professional dancer as an artist-in-residence who teamed with "a few other engineers" to build an AI algorithm trained on the dancer's choreography preferences...]

Google founder Larry Page — favored moving directly to "end to end" (e2e) learning, where you'd hand robots a general task and they'd be able to figure out how to execute it. That, Page felt, was a goal worthy of a moonshot. But it also turned out to be out of reach. "I have come to believe," Brondmo writes, "it will take many, many thousands, maybe even millions of robots doing stuff in the real world to collect enough data to train e2e models that make the robots do anything other than fairly narrow, well-defined tasks...." ["Building robots that perform useful services — like cleaning up and wiping all the tables in a restaurant, or making the beds in a hotel — will require both AI and traditional programming for a long time to come. In other words, don't expect robots to go running off outside our control, doing something they weren't programmed to do, anytime soon."]

The bottom line: So far, robot hype is outpacing robot reality. Boston Dynamics' back-flipping humanoid and quadruped bots have wowed YouTube viewers — but you wouldn't want to let them anywhere near your office or home.
It's an interesting look back. "My job: help figure out what to do with the employees and technology left over from nine robot companies that Google had acquired," Brondmo writes: Andy "the father of Android" Rubin, who had previously been in charge, had suddenly left. Larry Page and Sergey Brin kept trying to offer guidance and direction during occasional flybys in their "spare time...." I knew from firsthand experience how hard it was to build a company that, in Steve Jobs' famous words, could put a dent in the universe, and I believed that Google was the right place to make certain big bets. AI-powered robots, the ones that will live and work alongside us one day, was one such audacious bet.

Eight and a half years later — and 18 months after Google decided to discontinue its largest bet in robotics and AI — it seems as if a new robotics startup pops up every week. I am more convinced than ever that the robots need to come. Yet I have concerns that Silicon Valley, with its focus on "minimum viable products" and VCs' general aversion to investing in hardware, will be patient enough to win the global race to give AI a robot body. And much of the money that is being invested is focusing on the wrong things...

When I arrived, the lab had already hatched Waymo, Google Glass, and other science-fiction-sounding projects like flying energy windmills and stratospheric balloons that would provide internet access to the underserved... [But] in January 2023, two months after OpenAI introduced ChatGPT, Google shut down Everyday Robots, citing overall cost concerns. The robots and a small number of people eventually landed at Google DeepMind to conduct research. In spite of the high cost and the long timeline, everyone involved was shocked.
They'd tackled the problem with earnestness. ("[S]even robots working for months to learn how to pick up a rubber duckling? That wasn't going to cut it... So we built a cloud-based simulator and, in 2021, created more than 240 million robot instances in the sim.ma")

Brondmo adds this his mother had advanced Parkinson's disease, and hoped that one day robots could support her. "Our frequent conversations toward the end of her life convinced me more than ever that a future version of what we started at Everyday Robots will be coming. In fact, it can't come soon enough.

"So the question we are left to ponder becomes: How does this kind of change and future happen? I remain curious, and concerned."

Cybersecurity giant Fortinet has confirmed it suffered a data breach after a threat actor claimed to steal 440GB of files from the company's Microsoft Sharepoint server. From a report: Fortinet is one of the largest cybersecurity companies in the world, selling secure networking products like firewalls, routers, and VPN devices. The company also offers SIEM, network management, and EDR/XDR solutions, as well as consulting services.

Early this morning, a threat actor posted to a hacking forum that they had stolen 440GB of data from Fortinet's Azure Sharepoint instance. The threat actor then shared credentials to an alleged S3 bucket where the stolen data is stored for other threat actors to download. The threat actor, known as "Fortibitch," claims to have tried to extort Fortinet into paying a ransom, likely to prevent the publishing of data, but the company refused to pay. In response to our questions about incident, Fortinet confirmed that customer data was stolen from a "third-party cloud-based shared file drive."

An anonymous reader quotes a report from Ars Technica: Microsoft has updated a key cryptographic library with two new encryption algorithms designed to withstand attacks from quantum computers. The updates were made last week to SymCrypt, a core cryptographic code library for handing cryptographic functions in Windows and Linux. The library, started in 2006, provides operations and algorithms developers can use to safely implement secure encryption, decryption, signing, verification, hashing, and key exchange in the apps they create. The library supports federal certification requirements for cryptographic modules used in some governmental environments. Despite the name, SymCrypt supports both symmetric and asymmetric algorithms. It's the main cryptographic library Microsoft uses in products and services including Azure, Microsoft 365, all supported versions of Windows, Azure Stack HCI, and Azure Linux. The library provides cryptographic security used in email security, cloud storage, web browsing, remote access, and device management. Microsoft documented the update in a post on Monday. The updates are the first steps in implementing a massive overhaul of encryption protocols that incorporate a new set of algorithms that aren't vulnerable to attacks from quantum computers. [...]

The first new algorithm Microsoft added to SymCrypt is called ML-KEM. Previously known as CRYSTALS-Kyber, ML-KEM is one of three post-quantum standards formalized last month by the National Institute of Standards and Technology (NIST). The KEM in the new name is short for key encapsulation. KEMs can be used by two parties to negotiate a shared secret over a public channel. Shared secrets generated by a KEM can then be used with symmetric-key cryptographic operations, which aren't vulnerable to Shor's algorithm when the keys are of a sufficient size. [...] The other algorithm added to SymCrypt is the NIST-recommended XMSS. Short for eXtended Merkle Signature Scheme, it's based on "stateful hash-based signature schemes." These algorithms are useful in very specific contexts such as firmware signing, but are not suitable for more general uses. Monday's post said Microsoft will add additional post-quantum algorithms to SymCrypt in the coming months. They are ML-DSA, a lattice-based digital signature scheme, previously called Dilithium, and SLH-DSA, a stateless hash-based signature scheme previously called SPHINCS+. Both became NIST standards last month and are formally referred to as FIPS 204 and FIPS 205. In Monday's post, Microsoft Principal Product Manager Lead Aabha Thipsay wrote: "PQC algorithms offer a promising solution for the future of cryptography, but they also come with some trade-offs. For example, these typically require larger key sizes, longer computation times, and more bandwidth than classical algorithms. Therefore, implementing PQC in real-world applications requires careful optimization and integration with existing systems and standards."

Nvidia is banking on its software expertise and broad GPU ecosystem to stay ahead in the fiercely competitive AI chip market, CEO Jensen Huang said in an interview with Goldman Sachs Wednesday. Huang pointed to NVIDIA's large base of installed GPUs and their software compatibility as key strengths.

Huang highlighted three key elements of Nvidia's competitive moat: a large installed base of GPUs across multiple platforms, the ability to enhance hardware with software like domain-specific libraries, and expertise in building rack-level systems. The CEO said Nvidia's chip design prowess, noting the company has developed seven different chips for its upcoming Blackwell platform.

These comments come as Nvidia faces increasing competition from rivals. Addressing supply chain concerns, Huang said NVIDIA has sufficient in-house intellectual property to shift manufacturing if necessary without significant disruption. The company plans to begin shipping Blackwell-based products in the fourth quarter of fiscal 2025, with volume production ramping up in fiscal 2026, according to Huang.

From the note that Goldman Sachs sent to its clients: 1) Accelerated Computing: Mr. Huang highlighted his long-held view that Moore's Law was no longer delivering the rate of innovation it had in the past and, as such, was driving computation inflation in Data Centers. Further, he noted that the densification and acceleration of the $1 trillion data center infrastructure installed base alone would drive growth over the next 10 years, as it would deliver material performance improvement and/or cost savings.

2) Customer ROI: Mr. Huang noted that we have hit the end of transistor scaling that enabled better utilization rates and cost reductions in the previous virtualization and cloud computing cycles. He explained that, while using a GPU to augment a CPU will drive an increase in cost in absolute terms (~2x) in the case of Spark (distributed processing system and analytics engine for big data), the net cost benefit could be as large as ~10x for an application like Spark given the speed up of ~20x. From a revenue generation perspective, Mr. Huang shared that hyperscale customers can generate $5 in rental revenue for every $1 spent on Nvidia's infrastructure, given sustained strength in the demand for accelerated computing.

Microsoft today announced significant strides in its Azure Quantum Cloud service, including the demonstration of logical operations using the largest number of error-corrected qubits ever achieved. This progress brings the industry closer to building reliable quantum computers capable of solving complex problems beyond the reach of classical systems, the company said.

In a significant partnership, Microsoft is collaborating with Atom Computing to integrate their neutral-atom hardware into Azure Quantum. Atom Computing has already shown promise with hardware exceeding 1,000 qubits. Key to Microsoft's advancements is the implementation of the "tesseract code" error correction scheme on Quantinuum's trapped-ion quantum hardware. This led to a 22-fold reduction in error rates, a critical step towards reliable quantum computations. Microsoft is also committed to simplifying quantum programming. Azure's Q# language will now automatically handle complex error correction, making quantum development more accessible.

Oracle missed the tech industry's move to cloud computing last decade and ended up an also-ran. Now the AI boom has given it another shot. WSJ: The 47-year-old company that made its name on relational database software has emerged as an attractive cloud-computing provider for AI developers such as OpenAI, sending its long-stagnant stock to new heights. Oracle shares are up 34% since January, well outpacing the Nasdaq's 14% rise and those of bigger competitors Microsoft, Amazon.com and Google.

It is a surprising revitalization for a company many in the tech industry had dismissed as a dinosaur of a bygone, precloud era. Oracle appears to be successfully making a case to investors that it has become a strong fourth-place player in a cloud market surging thanks to AI. Its lateness to the game may have played to its advantage, as a number of its 162 data centers were built in recent years and are designed for the development of AI models, known as training.

In addition, Oracle isn't developing its own large AI models that compete with potential clients. The company is considered such a neutral and unthreatening player that it now has partnerships with Microsoft, Google and Amazon, all of which let Oracle's databases run in their clouds. Microsoft is also running its Bing AI chatbot on Oracle's servers.

An anonymous reader quotes a report from Reuters: The U.S. Commerce Department said Monday it is proposing to require detailed reporting requirements for advanced artificial intelligence developers and cloud computing providers to ensure the technologies are safe and can withstand cyberattacks. The proposal from the department's Bureau of Industry and Security would set mandatory reporting to the federal government about development activities of "frontier" AI models and computing clusters. It would also require reporting on cybersecurity measures as well as outcomes from so-called red-teaming efforts like testing for dangerous capabilities including the ability to assist in cyberattacks or lowering barriers to entry for non-experts to develop chemical, biological, radiological, or nuclear weapons. External red-teaming has been used for years in cybersecurity to identify new risks, with the term referring to U.S. Cold War simulations where the enemy was termed the "red team." [...] Commerce said the information collected under the proposal "will be vital for ensuring these technologies meet stringent standards for safety and reliability, can withstand cyberattacks, and have limited risk of misuse by foreign adversaries or non-state actors." Further reading: Biden Signs Executive Order To Oversee and Invest in AI

An anonymous reader shares a report: Passport numbers for a group of Disney cruise line workers. Disney+ streaming revenue. Sales of Genie+ theme park passes. The trove of data from Disney that was leaked online by hackers earlier this summer includes a range of financial and strategy information that sheds light on the entertainment giant's operations, according to files viewed by The Wall Street Journal. It also includes personally identifiable information of some staff and customers.

The leaked files include granular details about revenue generated by such products as Disney+ and ESPN+; park pricing offers the company has modeled; and what appear to be login credentials for some of Disney's cloud infrastructure. (The Journal didn't attempt to access any Disney systems.) "We decline to comment on unverified information The Wall Street Journal has purportedly obtained as a result of a bad actor's illegal activity," a Disney spokesman said. Disney told investors in an August regulatory filing that it is investigating the unauthorized release of "over a terabyte of data" from one of its communications systems. It said the incident hadn't had a material impact on its operations or financial performance and doesn't expect that it will.

Data that a hacking entity calling itself Nullbulge released online spans more than 44 million messages from Disney's Slack workplace communications tool, upward of 18,800 spreadsheets and at least 13,000 PDFs, the Journal found. The scope of the material taken appears to be limited to public and private channels within Disney's Slack that one employee had access to. No private messages between executives appear to be included. Slack is only one online forum in which Disney employees communicate at work.

Safe Superintelligence (SSI), co-founded by OpenAI's former chief scientist Ilya Sutskever, has raised $1 billion to develop safe AI systems that surpass human capabilities. The company, valued at $5 billion, plans to use the funds to hire top talent and acquire computing power, with investors including Andreessen Horowitz, Sequoia Capital, and DST Global. Reuters reports: Sutskever, 37, is one of the most influential technologists in AI. He co-founded SSI in June with Gross, who previously led AI initiatives at Apple, and Daniel Levy, a former OpenAI researcher. Sutskever is chief scientist and Levy is principal scientist, while Gross is responsible for computing power and fundraising. Sutskever said his new venture made sense because he "identified a mountain that's a bit different from what I was working on."

SSI is currently very much focused on hiring people who will fit in with its culture. Gross said they spend hours vetting if candidates have "good character", and are looking for people with extraordinary capabilities rather than overemphasizing credentials and experience in the field. "One thing that excites us is when you find people that are interested in the work, that are not interested in the scene, in the hype," he added. SSI says it plans to partner with cloud providers and chip companies to fund its computing power needs but hasn't yet decided which firms it will work with. AI startups often work with companies such as Microsoft and Nvidia to address their infrastructure needs.

Sutskever was an early advocate of scaling, a hypothesis that AI models would improve in performance given vast amounts of computing power. The idea and its execution kicked off a wave of AI investment in chips, data centers and energy, laying the groundwork for generative AI advances like ChatGPT. Sutskever said he will approach scaling in a different way than his former employer, without sharing details. "Everyone just says scaling hypothesis. Everyone neglects to ask, what are we scaling?" he said. "Some people can work really long hours and they'll just go down the same path faster. It's not so much our style. But if you do something different, then it becomes possible for you to do something special."

After an initial euphoric rush to the cloud, admins are questioning the value and promise of the tech giant's services. The Register: According to a report published by UK cloud outfit Civo, more than a third of organizations surveyed reckoned that their move to the cloud had failed to live up to promises of cost-effectiveness. Over half reported a rise in their cloud bill. Although the survey, unsurprisingly, paints Civo in a flattering light, some of its figures may make uncomfortable reading for customers sold on the promises from hyperscalers. Like-for-like comparisons for a simple three-node cluster with 200 GB of persistent storage and a 5 TB data transfer showed prices going from $1,278.58 in 2022 to $1,458.68 in 2024 on Microsoft Azure.

For Google, the price went from $1,107.61 to $1,250.35. According to Civo's figures, the cost at AWS increased from $1,142.46 to $1,234.59. "The Kubernetes prices were taken from the hyperscalers' very own pricing calculators," a Civo spokesperson told The Register. In the IT world, there is an expectation that bang for buck increases as time goes by, but in this example, prices are rising faster than the rate of inflation, and what customers receive for their money remains unchanged.

Firefox 130 introduces several enhancements, including improved local translation handling, better Android page load performance, and the WebCodecs API for low-level audio/video processing on desktop platforms. Notably, it also supports third-party AI chatbots like ChatGPT and Google Gemini via the new Firefox Labs feature. Phoronix reports: The WebCodecs API is particularly useful for web-based apps like video/audio editors and video conferencing that may want control over individual frames of a video stream or audio chunks. For any web software interested in that low-level audio/video encode/decode handling there is now WebCodecs API working on the Firefox desktop builds. As for the third-party AI chatbots, here's what Mozilla's Ian Carmichael said back in June: "If you want to use AI, we think you should have the freedom to use (or not use) the tools that best suit your needs. Instead of juggling between tabs or apps for assistance, those who opt-in will have the option to access their preferred AI service from the Firefox sidebar to summarize information, simplify language, or test their knowledge, all without leaving their current web page."

You can learn more about Firefox 130 via developer.mozilla.org. Binaries for Linux can be found at Mozilla.org.

Elastic, creator of popular search engine Elasticsearch and visualization tool Kibana, plans to introduce the AGPL open-source license alongside its existing licenses. The move comes three years after Elastic ditched the Apache 2.0 license, sparking controversy in the tech community.

Founder Shay Banon says the change aims to clarify Elastic's market position following AWS's creation of OpenSearch, a fork of Elasticsearch. Despite initial friction, Banon claims Elastic's relationship with AWS has improved, citing growth in Elastic Cloud revenue and customer base.

Long-time Slashdot reader theodp writes: The Contingency Contingent, is Leigh Claire La Berge's amazing tale of what she calls her "fake job in Y2K preparedness." La Berge offers an insider's view of the madness that ensued when Y2K panic gave rise to seemingly-limitless spending at mega-corporations for massive enterprise-wide Y2K remediation projects led by management consulting firms that left clients with little to show for their money. (La Berge was an analyst for consulting firm Arthur Andersen, where "the Andersen position was that 'Y2K is a documentation problem, not a technology problem'.... At a certain point all that had happened yesterday was our documenting, so then we documented that. Then, exponentially, we had to document ourselves documenting our own documentation."). In what reads like the story treatment for an Office Space sequel, La Berge writes that it was a fake job "because Andersen was faking it."
From the article: The firm spent the late 1990s certifying fraudulent financial statements from Enron, the Texas-based energy company that made financial derivatives a household phrase, until that company went bankrupt in a cloud of scandal and suicide and Andersen was convicted of obstruction of justice, surrendered its accounting licenses, and shuttered. But that was later.

Finally, it was a fake job because the problem that the Conglomerate had hired Andersen to solve was not real, at least not in the sense that it needed to be solved or that Andersen could solve it. The problem was known variously as Y2K, or the Year 2000, or the Y2K Bug, and it prophesied that on January 1, 2000, computers the world over would be unable to process the thousandth-digit change from 19 to 20 as 1999 rolled into 2000 and would crash, taking with them whatever technology they were operating, from email to television to air-traffic control to, really, the entire technological infrastructure of global modernity. Hospitals might have emergency power generators to stave off the worst effects (unless the generators, too, succumbed to the Y2K Bug), but not advertising firms.

With a world-ending scenario on the horizon, employment standards were being relaxed. The end of the millennium had produced a tight labor market in knowledge workers, and new kinds of companies, called dot-coms, were angling to dominate the emergent world of e-commerce. Flush with cash, these companies were hoovering up any possessors of knowledge they could find. Friends from my gradeless college whose only experience in business had been parking-lot drug deals were talking stock options.
Looking back, the author remembers being "surprised by how quickly Y2K disappeared from office discourse as though censored..."

Their upcoming book is called Fake Work: How I Began to Suspect Capitalism is a Joke.

Casey Newton, former senior editor at the Verge, weighs in on Platformer about the arrest of Telegram CEO Pavel Durov.

"Fending off onerous speech regulations and overzealous prosecutors requires that platform builders act responsibly. Telegram never even pretended to." Officially, Telegram's terms of service prohibit users from posting illegal pornographic content or promotions of violence on public channels. But as the Stanford Internet Observatory noted last year in an analysis of how CSAM spreads online, these terms implicitly permit users who share CSAM in private channels as much as they want to. "There's illegal content on Telegram. How do I take it down?" asks a question on Telegram's FAQ page. The company declares that it will not intervene in any circumstances: "All Telegram chats and group chats are private amongst their participants," it states. "We do not process any requests related to them...."

Telegram can look at the contents of private messages, making it vulnerable to law enforcement requests for that data. Anticipating these requests, Telegram created a kind of jurisdictional obstacle course for law enforcement that (it says) none of them have successfully navigated so far. From the FAQ again:

To protect the data that is not covered by end-to-end encryption, Telegram uses a distributed infrastructure. Cloud chat data is stored in multiple data centers around the globe that are controlled by different legal entities spread across different jurisdictions. The relevant decryption keys are split into parts and are never kept in the same place as the data they protect. As a result, several court orders from different jurisdictions are required to force us to give up any data. [...] To this day, we have disclosed 0 bytes of user data to third parties, including governments.

As a result, investigation after investigation finds that Telegram is a significant vector for the spread of CSAM.... The company's refusal to answer almost any law enforcement request, no matter how dire, has enabled some truly vile behavior. "Telegram is another level," Brian Fishman, Meta's former anti-terrorism chief, wrote in a post on Threads. "It has been the key hub for ISIS for a decade. It tolerates CSAM. Its ignored reasonable [law enforcement] engagement for YEARS. It's not 'light' content moderation; it's a different approach entirely.
The article asks whether France's action "will embolden countries around the world to prosecute platform CEOs criminally for failing to turn over user data." On the other hand, Telegram really does seem to be actively enabling a staggering amount of abuse. And while it's disturbing to see state power used indiscriminately to snoop on private conversations, it's equally disturbing to see a private company declare itself to be above the law.

Given its behavior, a legal intervention into Telegram's business practices was inevitable. But the end of private conversation, and end-to-end encryption, need not be.

"Dirk Hohndel, a Linux kernel developer and long-time open source leader, wanted his audience at KubeCon + CloudNativeCon + Open Source Summit China 2024 Summit China to know he's not a Valkey developer," writes Steven J. Vaughan-Nichols. "He's a Valkey user and fan." [Hohndel] opened his speech by recalling how the open source, high-performance key/value datastore Valkey had been forked from Redis... Hohndel emphasized that "forks are good. Forks are one of the key things that open source licenses are for. So, if the maintainer starts doing things you don't like, you can fork the code under the same license and do better..." In this case, though, Redis had done a "bait-and-switch" with the Redis code, Hohndale argued. This was because they had made an all-too-common business failure: They hadn't realized that "open source is not a business model...."

While the licensing change is what prompted the fork, Hohndel sees leadership and technical reasons why the Valkey fork is likely to succeed. First, two-thirds of the formerly top Redis maintainers and developers have switched to Valkey. In addition, AWS, Google Cloud, and Oracle, under the Linux Foundation's auspices, all support Valkey. When both the technical and money people agree, good things can happen.

The other reason is that Valkey already looks like it will be the better technical choice. That's because the recently announced Valkey 8.0, which builds upon the last open source version of Redis, 7.2.4, introduces serious speed improvements and new features that Redis users have wanted for some time. As [AWS principal engineer Madelyn] Olson said at Open Source Summit North America earlier this year, "Redis really didn't want to break anything." Valkey wants to move a bit faster. How much faster? A lot. Valkey 8.0 overhauls Redis's single-threaded event loop threading model with a more sophisticated multithreaded approach to I/O operations. Hohndel reported that on his small Valkey-powered aircraft tracking system, "I see roughly a threefold improvement in performance, and I stream a lot of data, 60 million data points a day."
The article notes that Valkey is already being supported by major Linux distros including AlmaLinux, Fedora, and Alpine.