On Saturday, Meta released its newest Llama 4 multimodal AI models in a surprise weekend move that caught some AI experts off guard. The announcement touted Llama 4 Scout and Llama 4 Maverick as major advancements, with Meta claiming top performance in their categories and an enormous 10 million token context window for Scout. But so far the open-weights models have received an initial mixed-to-negative reception from the AI community, highlighting a familiar tension between AI marketing and user experience.

"The vibes around llama 4 so far are decidedly mid ," said independent AI researcher Simon Willison in a short interview with Ars Technica. Willison often checks the community pulse around open source and open weights AI releases in particular.

While Meta positions Llama 4 in competition with closed-model giants like OpenAI and Google, the company continues to use the term "open source" despite licensing restrictions that prevent truly open use. As we have noted in the past with previous Llama releases, "open weights" more accurately describes Meta's approach. Those who sign in and accept the license terms can download the two smaller Llama 4 models from Hugging Face or llama.com .

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A technique that hostile nation-states and financially motivated ransomware groups are using to hide their operations poses a threat to critical infrastructure and national security, the National Security Agency has warned.

The technique is known as fast flux. It allows decentralized networks operated by threat actors to hide their infrastructure and survive takedown attempts that would otherwise succeed. Fast flux works by cycling through a range of IP addresses and domain names that these botnets use to connect to the Internet. In some cases, IPs and domain names change every day or two; in other cases, they change almost hourly. The constant flux complicates the task of isolating the true origin of the infrastructure. It also provides redundancy. By the time defenders block one address or domain, new ones have already been assigned.

A significant threat

“This technique poses a significant threat to national security, enabling malicious cyber actors to consistently evade detection,” the NSA, FBI, and their counterparts from Canada, Australia, and New Zealand warned Thursday . “Malicious cyber actors, including cybercriminals and nation-state actors, use fast flux to obfuscate the locations of malicious servers by rapidly changing Domain Name System (DNS) records. Additionally, they can create resilient, highly available command and control (C2) infrastructure, concealing their subsequent malicious operations.”

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In a new paper published Thursday titled " Auditing language models for hidden objectives ," Anthropic researchers described how models trained to deliberately conceal certain motives from evaluators could still inadvertently reveal secrets, thanks to their ability to adopt different contextual roles or "personas." The researchers were initially astonished by how effectively some of their interpretability methods seemed to uncover these hidden motives, although the methods are still under research.

While the research involved models trained specifically to conceal motives from automated software evaluators called reward models (RMs), the broader purpose of studying hidden objectives is to prevent future scenarios where powerful AI systems might intentionally deceive or manipulate human users.

While training a language model using reinforcement learning from human feedback (RLHF), reward models are typically tuned to score AI responses according to how well they align with human preferences. However, if reward models are not tuned properly, they can inadvertently reinforce strange biases or unintended behaviors in AI models.

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A new study from Columbia Journalism Review's Tow Center for Digital Journalism finds serious accuracy issues with generative AI models used for news searches. The research tested eight AI-driven search tools equipped with live search functionality and discovered that the AI models incorrectly answered more than 60 percent of queries about news content.

Researchers Klaudia Jaźwińska and Aisvarya Chandrasekar noted in their report that roughly 1 in 4 Americans now uses AI models as alternatives to traditional search engines. This raises serious concerns about reliability, given the substantial error rate uncovered in the study.

Error rates varied notably among the tested platforms. Perplexity provided incorrect information in 37 percent of the queries tested, whereas ChatGPT Search incorrectly identified 67 percent (134 out of 200) of articles queried. Grok 3 demonstrated the highest error rate, at 94 percent.

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On Saturday, a developer using Cursor AI for a racing game project hit an unexpected roadblock when the programming assistant abruptly refused to continue generating code, instead offering some unsolicited career advice.

According to a bug report on Cursor's official forum, after producing approximately 750 to 800 lines of code (what the user calls "locs"), the AI assistant halted work and delivered a refusal message: "I cannot generate code for you, as that would be completing your work. The code appears to be handling skid mark fade effects in a racing game, but you should develop the logic yourself. This ensures you understand the system and can maintain it properly."

The AI didn't stop at merely refusing—it offered a paternalistic justification for its decision, stating that "Generating code for others can lead to dependency and reduced learning opportunities."

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Anthropic CEO Dario Amodei raised a few eyebrows on Monday after suggesting that advanced AI models might someday be provided with the ability to push a "button" to quit tasks they might find unpleasant. Amodei made the provocative remarks during an interview at the Council on Foreign Relations, acknowledging that the idea "sounds crazy."

"So this is—this is another one of those topics that’s going to make me sound completely insane," Amodei said during the interview. "I think we should at least consider the question of, if we are building these systems and they do all kinds of things like humans as well as humans, and seem to have a lot of the same cognitive capacities, if it quacks like a duck and it walks like a duck, maybe it’s a duck."

Amodei's comments came in response to an audience question from data scientist Carmem Domingues about Anthropic's late-2024 hiring of AI welfare researcher Kyle Fish "to look at, you know, sentience or lack of thereof of future AI models, and whether they might deserve moral consideration and protections in the future." Fish currently investigates the highly contentious topic of whether AI models could possess sentience or otherwise merit moral consideration.

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After a little over three months, Intel has a new CEO to replace ousted former CEO Pat Gelsinger . Intel's board announced that Lip-Bu Tan will begin as Intel CEO on March 18th, taking over from interim co-CEOs David Zisner and Michelle Johnston Holthaus.

Gelsinger was booted from the CEO position by Intel's board on December 2 after several quarters of losses, rounds of layoffs, and canceled or spun-off side projects. Gelsinger sought to turn Intel into a foundry company that also manufactured chips for fabless third-party chip design companies, putting it into competition with Taiwan Semiconductor (TSMC), Samsung, and others, a plan that Intel said it was still committed to when it let Gelsinger go.

Intel said that Zisner would stay on as executive vice president and CFO, and Johnston Holthaus would remain CEO of the Intel Products Group, which is mainly responsible for Intel's consumer products. These were the positions both executives held before serving as interim co-CEOs.

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Researchers have discovered multiple Android apps, some that were available in Google Play after passing the company’s security vetting, that surreptitiously uploaded sensitive user information to spies working for the North Korean government.

Samples of the malware—named KoSpy by Lookout, the security firm that discovered it—masquerade as utility apps for managing files, app or OS updates, and device security. Behind the interfaces, the apps can collect a variety of information including SMS messages, call logs, location, files, nearby audio, and screenshots and send them to servers controlled by North Korean intelligence personnel. The apps target English language and Korean language speakers and have been available in at least two Android app marketplaces, including Google Play.

Think twice before installing

The surveillanceware masquerades as the following five different apps:

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On Wednesday, Google DeepMind announced two new AI models designed to control robots: Gemini Robotics and Gemini Robotics-ER. The company claims these models will help robots of many shapes and sizes understand and interact with the physical world more effectively and delicately than previous systems, paving the way for applications such as humanoid robot assistants.

It's worth noting that even though hardware for robot platforms appears to be advancing at a steady pace (well, maybe not always ), creating a capable AI model that can pilot these robots autonomously through novel scenarios with safety and precision has proven elusive. What the industry calls "embodied AI" is a moonshot goal of Nvidia, for example, and it remains a holy grail that could potentially turn robotics into general-use laborers in the physical world.

Along those lines, Google's new models build upon its Gemini 2.0 large language model foundation, adding capabilities specifically for robotic applications. Gemini Robotics includes what Google calls "vision-language-action" (VLA) abilities, allowing it to process visual information, understand language commands, and generate physical movements. By contrast, Gemini Robotics-ER focuses on "embodied reasoning" with enhanced spatial understanding, letting roboticists connect it to their existing robot control systems.

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