The big picture: The past several years have seen some of the worst figures in Intel's 56-year history. The company faces trouble on all fronts, from foundry to consumer processors and server chips. As Intel reorganizes its foundry operations, new analysis paints a grim picture of its server business's current trajectory. According to SemiAnalysis, Intel's 2024 server processor volume declined for the third year straight. Following the precipitous drop in 2023, the company's data center business has reached a 14-year low.Based on data from Intel's 10K reports, analysts have charted Intel's data center CPU volume since 2011. The numbers aren't exact and appear as a percentage of 2011's total, but they reveal a peak in 2021, followed by an ongoing decline. The most dramatic fall occurred in 2023 when server processor volume plummeted by 50 percent of 2011's count. Intel's volume has fallen by over half since 2021.Chipzilla is losing ground to AMD in the consumer and server CPU markets. Late last year, the company admitted that it has no plans to answer to the 3D V-Cache that has made Team Red's Ryzen chips the undisputed masters of gaming desktops. Instead, Intel is bringing similar technology to its upcoming Clearwater Forest data center processors because it considers servers a more critical market.Set for launch sometime this year, Clearwater Forest and Intel's laptop-focused Panther Lake CPUs will also decide the fate of another business the company struggles with: semiconductor manufacturing. Both will prove whether the company's 18A node can compete against TSMC's leading 3nm and 2nm processes. // Related StoriesAlso read: Intel's takeover dilemma: A Gordian knot of funding and politicsHowever, Intel already turned to TSMC for last year's Lunar Lake notebook CPUs and may do so again for future chips in all sectors. The desktop Nova Lake processors, expected to emerge in 2026, will use transistors from Intel and another manufacturer, likely TSMC.Amid questions over the survival of Intel semiconductors, the company spun its foundry division into a separate entity that it admits will have to "earn" its business just like TSMC or Samsung. Intel claims that other prospective clients have successfully powered on products based on 18A, suggesting that the node's development is progressing smoothly.Sliding revenue and other problems led to the recent departure of CEO Pat Gelsinger, prompting Bill Gates to say that Intel has "lost its way." The Microsoft co-founder noted that Intel has fallen behind in foundry and chip design over the last decade.Rumors of a buyout are circulating, but it remains unclear who, if anyone, would want to acquire Intel.

Why it matters: Everyone's coming up with new and innovative ways to work around the massive costs involved with training and creating new AI models. After DeepSeek's impressive debut, which shook Silicon Valley, a group of researchers has developed an open rival that reportedly matches the reasoning abilities of OpenAI's o1. Stanford and University of Washington researchers devised a technique to create a new AI model dubbed "s1." They have already open-sourced it on GitHub, along with the code and data used to build it. A paper published last Friday explained how the team achieved these results through clever technical tricks.Rather than training a reasoning model from scratch, an expensive endeavor costing millions, they took an existing off-the-shelf language model and "fine-tuned" it using distillation. They extracted the reasoning capabilities from one of Google's AI models specifically, Gemini 2.0 Flash Thinking Experimental. They then trained the base model to mimic its step-by-step problem-solving process on a small dataset.Others have used this approach before. In fact, distillation is what OpenAI was accusing DeepSeek of doing. However, the Stanford/UW team found an ultra-low-cost way to implement it through "supervised fine-tuning."This process involves explicitly teaching the model how to reason using curated examples. Their full dataset consisted of only 1,000 carefully selected questions and solutions pulled from Google's model.TechCrunch notes that the training process took 30 minutes, using 16 Nvidia H100 GPUs. Of course, these GPUs cost a small fortune around $25,000 per unit but renting works out to under $50 in cloud compute credits. // Related StoriesThe researchers also discovered a neat trick to boost s1's capabilities even further. They instructed the model to "wait" before providing its final answer. This command allowed it more time to check its reasoning to arrive at slightly improved solutions.The model is not without its caveats. Since the team used Google's model as its teacher, there is the question that s1's skills, while impressive for its minuscule cost, may not be able to scale up to match the best AI has to offer just yet. There is also the potential for Google to protest. It could be waiting to see how OpenAI's case goes.

Table of ContentsTable of ContentsWhat are Super Bowl squares?How do Super Bowl squares work?What are the Super Bowl squares?This weekend marks Super Bowl LIX between the Kansas City Chiefs and Philadelphia Eagles. The Super Bowl is a huge day for gambling, as the Big Game represents the most bet-on single event in the United States. According to the American Gaming Association, nearly $1.39 billion is expected to be legally wagered on Super Bowl LIX.One of the most popular betting games involves Super Bowl squares. Football novices and experts can play in a squares pool, making it an appealing game for a Super Bowl party. How do you play? Below youll find information on how to play Super Bowl squares.Recommended VideosESPNSuper Bowl squares begin with a blank 1010 grid with 100 empty squares. As you can see in the grid (via ESPN), the Philadelphia Eagles (home team) are on the horizontal axis at the top, and the Kansas City Chiefs (away team) are on the vertical axis at the left. Participants will pick a random square and mark it with their name. Each square is one entry. The size of the pool and the cost of each square will vary from group to group. Buy as few or as many squares as you like. It all depends on your budget.RelatedWith every spot filled, its time to draw numbers. The horizontal and vertical axes will be labeled with numbers 0-9. These numbers are randomly selected and then assigned to a column or row. To pick the numbers, use a hat, deck of cards, or online number generator. Just make sure its a random process to determine the numbers of each column and row.Lets use this completed square (via FanDuel) as an example. The object of the game is to have a square that matches the end digits of each teams point total at the end of each quarter. For example, lets say the score after the first quarter is Chiefs 7, Eagles 3. Using the grid, the person with the square that corresponds with Chiefs 7 and Eagles 3 is Gabby. Therefore, Gabby is the winner of the first quarter.Lets go again. At halftime, the score is Chiefs 17, Eagles 14. Remember that only the last digit matters. Looking at the grid, the person with the square that corresponds with Chiefs 7 and Eagles 4 is Anne, who wins the second quarter. Anne keeps that square for the entire game, so if the final score is Chiefs 27, Eagles 24, Anne wins again.Prizes are typically awarded at the end of each quarter and for the final score. The amount one can win depends on your prize pool. Make sure to know the winning purses for each quarter before the game starts.John Higgins / Digital TrendsAfter the squares are assigned, several have significant advantages over others. ESPN broke down the scores per team by quarter. The results stated that 0 and 7 are the best numbers to own during the Big Game. Behind those numbers are 3, 4, and 6. If you own several of these five numbers on Super Bowl Sunday, your chances of winning will increase.Watch Super Bowl LIX at 6:30 p.m. ET on Sunday, February 9, 2025. The game will air on Fox.Editors Recommendations

This week, Amazon sent out invitations to an upcoming event hosted by Amazon Senior Vice President Panos Panay and the Amazon Devices & Services team in New York City on February 26. As can be seen in the image above, the invite Digital Trends received had the signature Amazon swoop with Hi there. front and center, and the date towards the bottom, all on top of a shaded blue background that included what on the surface looked like some attractive, curved design elements.Sure, the design gave off a feeling of Amazon Alexa, but beyond speculation around what the event might be about, the innocuous email didnt seem to divulge any useful information. That is, until The Verge did some impressive sleuthing and discovered that there wasnt one email invite sent out, but five. That attractive, curved background was actually part of some cursive text that, when all five invitation were put together, spelled out alexa. Pretty strong confirmation to those Alexa feels.Recommended VideosAccording to information obtained by Reuters, the event will announce the launch of a new generative AI-powered Alexa, but the extent of the features is as yet unknown. While the expectation is that the new service will be rolled out to a limited number of users free of charge, something that has apparently been floated internally by Amazon is including a $5-10 subscription fee for the new AI-powered Alexa. The current version referred to as Classic Alexa will continue to be available at no charge, although development of new features for Classic Alexa has reportedly ceased.Please enable Javascript to view this contentAmazon has been surprisingly behind the curve for the past couple years when it comes to generative AI integration, with an LLM announcement back in 2023 that hasnt fully materialized yet. But considering the amount of Amazon devices such as the Echo speaker and Omni Fire TV in average households, its important that they catch up. The big question around this potential new service and its integration is how it will separate and stand out from the string of generative AI models that have come out in the past couple years.Editors Recommendations

The company spent a record amount on capital expenditures during its artificial-intelligence build-out.

A staffer for Elon Musks Department of Government Efficiency, whose access to Treasury payment systems was approved by a judge, has links to a deleted social-media account that advocated for racism and eugenics.

The Oscar-winning actor stars alongside fellow honoree Ariana DeBose in director Jonathan Eusebios awkward action-comedy about a former assassin, who is pulled out of his normal new life as a real-estate agent and back into a world of bloodshed.

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GOT HTTPS? DeepSeek iOS app sends data unencrypted to ByteDance-controlled servers Apple's defenses that protect data from being sent in the clear are globally disabled. Dan Goodin Feb 6, 2025 5:06 pm | 5 Credit: Getty Images Credit: Getty Images Story textSizeSmallStandardLargeWidth *StandardWideLinksStandardOrange* Subscribers only Learn moreA little over two weeks ago, a largely unknown China-based company named DeepSeek stunned the AI world with the release of an open source AI chatbot that had simulated reasoning capabilities that were largely on par with those from market leader OpenAI. Within days, the DeepSeek AI assistant app climbed to the top of the iPhone App Store's "Free Apps" category, overtaking ChatGPT.On Thursday, mobile security company NowSecure reported that the app sends sensitive data over unencrypted channels, making the data readable to anyone who can monitor the traffic. More sophisticated attackers could also tamper with the data while it's in transit. Apple strongly encourages iPhone and iPad developers to enforce encryption of data sent over the wire using ATS (App Transport Security). For unknown reasons, that protection is globally disabled in the app, NowSecure said.Basic security protections MIAWhats more, the data is sent to servers that are controlled by ByteDance, the Chinese company that owns TikTok. While some of that data is properly encrypted using transport layer security, once it's decrypted on the ByteDance-controlled servers, it can be cross-referenced with user data collected elsewhere to identify specific users and potentially track queries and other usage.More technically, the DeepSeek AI chatbot uses an open weights simulated reasoning model. Its performance is largely comparable with OpenAI's o1 simulated reasoning (SR) model on several math and coding benchmarks. The feat, which largely took AI industry watchers by surprise, was all the more stunning because DeepSeek reported spending only a small fraction on it compared with the amount OpenAI spent.A NowSecure audit of the app has found other behaviors that researchers found potentially concerning. For instance, the app uses a symmetric encryption scheme known as 3DES or triple DES. The scheme was deprecated by NIST following research in 2016 that showed it could be broken in practical attacks to decrypt web and VPN traffic. Another concern is that the symmetric keys, which are identical for every iOS user, are hardcoded into the app and stored on the device.The app is not equipped or willing to provide basic security protections of your data and identity, NowSecure co-founder Andrew Hoog told Ars. There are fundamental security practices that are not being observed, either intentionally or unintentionally. In the end, it puts your and your companys data and identity at risk.Hoog said the audit is not yet complete, so there are many questions and details left unanswered or unclear. He said the findings were concerning enough that NowSecure wanted to disclose what is currently known without delay.In a report, he wrote:NowSecure recommends that organizations remove the DeepSeek iOS mobile app from their environment (managed and BYOD deployments) due to privacy and security risks, such as:Privacy issues due to insecure data transmissionVulnerability issues due to hardcoded keysData sharing with third parties such as ByteDanceData analysis and storage in ChinaHoog added that the DeepSeek app for Android is even less secure than its iOS counterpart and should also be removed.Representatives for both DeepSeek and Apple didnt respond to an email seeking comment.Data sent entirely in the clear occurs during the initial registration of the app, including:organization idthe version of the software development kit used to create the appuser OS versionlanguage selected in the configurationApple strongly encourages developers to implement APS to ensure the apps they submit don't transmit any data insecurely over HTTP channels. For reasons that Apple hasn't explained publicly, Hoog said, this protection isn't mandatory. DeepSeek has yet to explain why APS is globally disabled in the app or why it uses no encryption when sending this information over the wire.This data, along with a mix of other encrypted information, is sent to DeepSeek over infrastructure provided by Volcengine a cloud platform developed by ByteDance. While the IP address the app connects to geo-locates to the US and is owned by US-based telecom Level 3 Communications, the DeepSeek privacy policy makes clear that the company "store[s] the data we collect in secure servers located in the People's Republic of China." The policy further states that DeepSeek:may access, preserve, and share the information described in "What Information We Collect" with law enforcement agencies, public authorities, copyright holders, or other third parties if we have good faith belief that it is necessary to: comply with applicable law, legal process or government requests, as consistent with internationally recognised standards.NowSecure still doesn't know precisely the purpose of the app's use of 3DES encryption functions. The fact that the key is hardcoded into the app, however, is a major security failure that's been recognized for more than a decade when building encryption into software.The NowSecure report comes a week after research from security firm Wiz uncovered a publicly accessible, fully controllable database belonging to DeepSeek. It contained more than 1 million instances of "chat history, backend data, and sensitive information, including log streams, API secrets, and operational details," Wiz reported. An open web interface also allowed for full database control and privilege escalation, with internal API endpoints and keys available through the interface and common URL parameters.On Thursday, US lawmakers began pushing to immediately ban DeepSeek from all government devices, citing national security concerns that the Chinese Communist Party may have built a backdoor into the service to access Americans' sensitive private data. If passed, DeepSeek could be banned within 60 days.Dan GoodinSenior Security EditorDan GoodinSenior Security Editor Dan Goodin is Senior Security Editor at Ars Technica, where he oversees coverage of malware, computer espionage, botnets, hardware hacking, encryption, and passwords. In his spare time, he enjoys gardening, cooking, and following the independent music scene. Dan is based in San Francisco. Follow him at here on Mastodon and here on Bluesky. Contact him on Signal at DanArs.82. 5 Comments

A bad seed? Torrenting from a corporate laptop doesnt feel right: Meta emails unsealed Meta's alleged torrenting and seeding of pirated books complicates copyright case. Ashley Belanger Feb 6, 2025 4:26 pm | 47 Credit: Devonyu | iStock / Getty Images Plus Credit: Devonyu | iStock / Getty Images Plus Story textSizeSmallStandardLargeWidth *StandardWideLinksStandardOrange* Subscribers only Learn moreNewly unsealed emails allegedly provide the "most damning evidence" yet against Meta in a copyright case raised by book authors alleging that Meta illegally trained its AI models on pirated books.Last month, Meta admitted to torrenting a controversial large dataset known as LibGen, which includes tens of millions of pirated books. But details around the torrenting were murky until yesterday, when Meta's unredacted emails were made public for the first time. The new evidence showed that Meta torrented "at least 81.7 terabytes of data across multiple shadow libraries through the site Annas Archive, including at least 35.7 terabytes of data from Z-Library and LibGen," the authors' court filing said. And "Meta also previously torrented 80.6 terabytes of data from LibGen.""The magnitude of Metas unlawful torrenting scheme is astonishing," the authors' filing alleged, insisting that "vastly smaller acts of data piracyjust .008 percent of the amount of copyrighted works Meta piratedhave resulted in Judges referring the conduct to the US Attorneys office for criminal investigation."Seeding expands authors distribution theoryBook authors had been pressing Meta for more information on the torrenting because of the seemingly obvious copyright concern of Meta seeding, and thus seemingly distributing, the pirated books in the dispute.But Meta resisted those discovery attempts after an order denied authors' request to review Meta's torrenting and seeding data. That didn't stop authors from gathering evidence anyway, including a key document that starts with at least one staffer appearing to uncomfortably joke about the possible legal risks, eventually growing more serious about raising his concerns."Torrenting from a corporate laptop doesnt feel right," Nikolay Bashlykov, a Meta research engineer, wrote in an April 2023 message, adding a smiley emoji. In the same message, he expressed "concern about using Meta IP addresses 'to load through torrents pirate content.'"By September 2023, Bashlykov had seemingly dropped the emojis, consulting the legal team directly and emphasizing in an email that "using torrents would entail seeding the filesi.e., sharing the content outside, this could be legally not OK."Emails discussing torrenting prove that Meta knew it was "illegal," authors alleged. And Bashlykov's warnings seemingly landed on deaf ears, with authors alleging that evidence showed Meta chose to instead hide its torrenting as best it could while downloading and seeding terabytes of data from multiple shadow libraries as recently as April 2024.Meta allegedly concealed seedingSupposedly, Meta tried to conceal the seeding by not using Facebook servers while downloading the dataset to "avoid" the "risk" of anyone "tracing back the seeder/downloader" from Facebook servers, an internal message from Meta researcher Frank Zhang said, while describing the work as in "stealth mode." Meta also allegedly modified settings "so that the smallest amount of seeding possible could occur," a Meta executive in charge of project management, Michael Clark, said in a deposition.Now that new information has come to light, authors claim that Meta staff involved in the decision to torrent LibGen must be deposed again, because allegedly the new facts "contradict prior deposition testimony."Mark Zuckerberg, for example, claimed to have no involvement in decisions to use LibGen to train AI models. But unredacted messages show the "decision to use LibGen occurred" after "a prior escalation to MZ," authors alleged.Meta did not immediately respond to Ars' request for comment and has maintained throughout the litigation that AI training on LibGen was "fair use."However, Meta has previously addressed its torrenting in a motion to dismiss filed last month, telling the court that "plaintiffs do not plead a single instance in which any part of any book was, in fact, downloaded by a third party from Meta via torrent, much less that Plaintiffs books were somehow distributed by Meta."While Meta may be confident in its legal strategy despite the new torrenting wrinkle, the social media company has seemingly complicated its case by allowing authors to expand the distribution theory that's key to winning a direct copyright infringement claim beyond just claiming that Meta's AI outputs unlawfully distributed their works.As limited discovery on Meta's seeding now proceeds, Meta is not fighting the seeding aspect of the direct copyright infringement claim at this time, telling the court that it plans to "set... the record straight and debunk... this meritless allegation on summary judgment."Ashley BelangerSenior Policy ReporterAshley BelangerSenior Policy Reporter Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience. 47 Comments