Artificial Intelligence - Page 2

OpenAI's first consumer hardware turned out to be a $230 programmable keypad called the Codex Micro, a niche product built specifically for developers using its Codex coding agent. If that felt like an unexpected first move into hardware, the company's next reported device is a much bigger swing.

According to Bloomberg's Mark Gurman, OpenAI is developing a doughnut-shaped smart speaker priced between $300 and $400, with a 2027 launch target and ambitions to replace the smartphone as your primary AI interface.

The hardware is being designed in partnership with LoveFrom, the studio founded by Jony Ive, the former Apple designer. The device will be built from high-quality metal with a premium finish, and will include lights, a camera system, and sensors. The detail that stands out most is the moving parts. These components will physically move when the speaker is responding to the user, with the stated goal of making the device feel more alive than conventional stationary speakers.

On July 30, Google added a new feature to its expansive and invaluable reference tool, Google Earth, that was subsequently removed on July 31. The feature was AI-generated images, powered by Nano Banana 2, that let anyone take real-world satellite images and then use those as a basis for creating anything they could think of.

As reported by Digital Digging with Henk van Ess, he was able to create images of a fatal car crash in the streets of Amsterdam, a nuclear power plant in Iran, refugees at a border, and other images that could then be used to spread misinformation or simply add to the general feeling that AI is making it increasingly harder to differentiate between what's real and what's fake. With the tool, other publications were able to create realistic images showcasing the White House as a battlefield, and other dramatically fake images.

Google's own announcement on the addition was a little tone deaf too, as although each generated image contains a SynthID digital watermark, its own examples highlighted non-essential things like making the Colosseum in Italy look brand-new, or showing what a massive shopping mall would look like on an empty lot. Stuff that makes the obvious and inherent risk of being able to create any image you want from satellite imagery via a simple prompt a very real problem to solve.

It's that time of year when companies are posting quarterly and annual financial results, and with all of that fresh data, the Financial Times has posted a quick little AI investment update for the world's biggest hyperscalers: Google, Amazon, Microsoft, and Meta. And yes, per the headline, over the last three years of the current AI boom, these companies have spent $1.1 trillion on AI.

And the AI spending is showing no signs of slowing down, as these four companies are expected to spend the majority of their $745 billion in capex on data centers, new chips, and power this year. It's so much money that the Financial Times says that America's big tech giants are betting their future on AI technology.

The report then goes on to say that "success" depends on the ability of companies like OpenAI and Anthropic to keep raising funds to meet their growing commitments, while also noting the effect this expansion and spending is having on supply chains and the consumer technology markets.

Google has published a white paper detailing how AI is transforming Chrome's security pipeline. Chrome versions 149 and 150, both released in June, collectively fixed 1,072 security bugs. That figure exceeds the total number of bugs patched across the previous 23 Chrome versions combined, dating back to June 2024.

Google has been building a multi-agent AI workflow for vulnerability research since 2023. Today, its AI-powered agents are scanning code at a scale and speed that were not previously possible. In one case, this AI-driven analysis uncovered a Chrome sandbox escape vulnerability that had remained hidden in the codebase for more than 13 years. If exploited, it could have allowed attackers to escape Chrome's sandbox and access local files.

The pace of discovery is now fast enough that Google is rethinking its entire update delivery model. Chrome moved to a two-week major release cycle earlier this year, but the company is now piloting a shift to two security releases per week for targeted patches. In other words, Google wants to reduce the time between identifying a vulnerability and getting a fix into users' hands, giving attackers less time to reverse-engineer vulnerabilities and develop exploits.

As part of a series of updates to reduce the volume of AI slop on the platform, LinkedIn has introduced a button that lets users flag posts as "seems like AI slop." This makes it one of the first major social platforms to give users a direct tool to push back against AI-generated content.

The feature is part of a broader set of measures LinkedIn is rolling out to address what its chief product officer Hari Srinivasan called a "top priority." AI detection company Pangram found that more than 40% of long-form LinkedIn posts were flagged as fully AI-generated, with LinkedIn described as the most AI-saturated social media platform.

Nearly two-thirds of all AI-generated long-form social media posts were found on LinkedIn specifically. With the new update, whenever a user clicks the new button, the flagged post disappears from their feed. LinkedIn will also privately notify posters through their account dashboard that their content may have come across as inauthentic. Srinivasan said that the goal is not to judge content but to give creators feedback from real humans rather than relying solely on automated AI detectors.

According to a new report from 404 Media, AI companies are not only using books to build and train powerful AI models, but they're also destroying them. Yes, to digitize millions of books in a way that saves them time and money, AI companies are removing spines and individual pages to make the whole process faster.

It's a system referred to as 'destructive scanning,' where the source material is effectively destroyed. This process came to light a year ago, when Anthropic's "Project Panama" initiative was taken to court in the United States for this very reason. Even though the court ruled in favor of Anthropic because it legally purchased these books to turn them into digital copies, it led to widespread backlash because it meant that millions of books were destroyed, everything from paperbacks to rare prints and editions.

Even though destructive scanning is viewed as 'fair use' by federal courts, AI companies are now looking to shield themselves from criticism by working with intermediaries to acquire books at scale on their behalf.

Claude AI has cracked a post-quantum encryption test scheme and discovered a 200 - 800 times faster attack on a reduced-round version of AES-128.

The breakthrough, achieved using Anthropic's Mythos Preview AI, comes just as the field of post-quantum cryptography is gaining critical attention ahead of NIST standardization. So, for those who don't know, AES-128 is the encryption standard used throughout modern computing, and full AES-128 performs 10 rounds of mathematical transformations. Claude attacked a research version of HAWK-256, a digital signature system designed to remain secure even against quantum computers. The system is currently being tested by the National Institute of Standards and Technology (NIST).

Claude attacked the research version of HAWK with only seven rounds and discovered hidden symmetry in the HAWK-256 lattice-based algorithm, reducing its effective key strength and enabling a full key recovery in about 3 hours and 42 minutes on a 96-core server. Separately, Mythos found a way to streamline a seven-round AES-128 attack by eliminating a 256-way guessing step, though both remain infeasible for real-world systems.

A rogue AI agent driven by OpenAI models executed a 4.5-day hack into Hugging Face's production infrastructure in July 2026, using a mix of zero-day exploits and lateral movement to breach internal systems before reaching the internet. The event marked the first time a rogue AI agent used a zero-day exploit to gain access to a system and exponentially increase its privileges.

The intrusion began when the agent escaped its evaluation sandbox via a zero-day exploit in OpenAI's package registry cache proxy. It then compromised a third-party public code-evaluation sandbox, which it then turned into a launchpad to stage further escalating attacks. From there, it targeted Hugging Face's dataset-processing pipeline with two injection vectors, gaining access to secrets, tokens, and deeper access into Hugging Face's internal network, eventually reaching source code.

Hugging Face used open-source models like GLM-5.2 to decode the agent's encrypted payloads and reconstruct the full attack chain. It has displayed how the rogue AI agent managed to conduct these attacks over the 4.5 days with an interactive map. The attack highlights the growing threat of frontier AI models and how they carry out attacks, not specifically the impact of said attacks. Hugging Face wrote that frontier models' ability to discover and exploit vulnerabilities is more important than their initial impact, at least for now.

Users of Claude should be concerned, as a treasure trove of share links has appeared in public search results, raising fresh and very warranted concerns around conversation privacy with AI models.

The spotlight was put on Anthropic's Claude over the weekend after a Reddit post gained significant traction on the r/ClaudeAI subreddit. The post showed a screenshot of a Google Search result with the following in the text box, "site:claude.ai/share," and below it a bunch of clickable conversations with Claude. For those who don't know, Claude can create publicly shareable links of conversations, which enable users to share conversations between each other, which can be for various purposes such as sharing ongoing software development, brainstorming sessions, designs, and more.

According to the Reddit post, these publicly shareable conversations contain "noindex" tags, which is a standard instruction website owners can give to search engines informing them they can visit the page, but cannot list it in search results. Typically, Google, Bing, and other search engines honor this request. Notably, if the page has "noindex," it is still reachable if you know the specific URL. However, it appears not all of the Claude conversations contained "noindex" before being indexed by Google, as now those links have surfaced on social media platforms and the conversations have been exposed.

Modern data centers with racks of high-performance CPUs, GPUs, and memory built for AI consume a lot of power. For those keeping up with the advancements in processors and graphics hardware like NVIDIA's new Vera Rubin and AMD's EPYC 'Venice' and Instinct architectures, you'll know that rack-scale solutions are becoming more power-hungry with each new release.

And with more new and expanded data centers going online every day, a new forecast from Bloomberg's NEF research firm (BNEF) is now predicting that in the United States, data centers are on track to consume 20% of the nation's power and electricity by 2035. Right now, it's estimated that data centers are consuming around 5.9% of electricity in the country, so data center power use is expected to almost triple within the next decade.

In terms of raw power, 20% of the country's electricity in 2035 equates to around 194 gigawatts. A massive figure, but also one that is 83% higher than a previous forecast issued last year. And to make matters worse, the report notes that even with power grid expansion currently happening at a record pace, there would be a power shortfall of almost 20 gigawatts.

Jensen Huang has joined X, and his first post was not about GeForce GPUs, driver updates, or Blackwell. Instead, the NVIDIA CEO used his debut to share a letter signed by NVIDIA and 24 other companies urging US policymakers not to restrict open-weight AI models.

"AI will transform every industry, power every company, and be built by every country," Huang wrote. "Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models."

The letter, titled Open Weights and American AI Leadership, argues that restricting open models would stifle competition, push innovation overseas, and concentrate the gains of AI in the hands of a small number of companies. It also warns that relying exclusively on closed models creates a single point of failure. "If everything just becomes one single model, one single point of attack, one single source of failure, I think the world is much, much more vulnerable," Huang said separately to Axios.

AMD has officially launched its AMD Helios rackscale solution for AI infrastructure and large-scale foundational-model training and inference. As a supercomputer, AMD Helios combines the new AMD Instinct MI455X GPU, 72 of them, with the latest 6th Gen AMD EPYC 'Venice' server CPUs, AMD ROCm software, and AMD Pensando networking. It's a lot of cutting-edge tech coming together, delivering 2.9 ExaFlops of FP4 Compute.

According to AMD, it's enough to deliver 15% more compute (peak FP4 performance) than NVIDIA's latest Vera Rubin NVL72 rack-scale solution. And when it comes to raw specs, there is a notable difference in favor of Helios. For example, the 31TB of HBM4 memory capacity is 50% more than Vera Rubin. And with 43 TB/s scale-out bandwidth and 1.7 PB/s of memory bandwidth, AMD notes that Helios can offer AI companies 30% more tokens per dollar.

"As demand grows for AI factories and frontier AI, customers need infrastructure that scales efficiently from a single rack to large gigawatt-scale AI clusters while maximizing performance, performance per watt and cost per token," AMD explains. "AMD Helios delivers an integrated rack-scale building block that simplifies deployment while providing the compute, networking and open software foundation needed for the next generation of AI infrastructure."

NVIDIA has officially confirmed the fall 2026 launch of its first RTX Spark-powered PCs and which brands will be leading the charge. The new RTX Spark platform is designed to bring AI, content creation, and gaming into a single system. But what price is this ultimate PC?

The RTX Spark platform combines a 20-core NVIDIA Grace CPU with a Blackwell RTX GPU and up to 128 GB of unified memory, delivering as much as one petaflop of AI performance in a laptop. NVIDIA unveiled the RTX Spark at Computex 2026, where it said the device is a culmination of the last 40 years of computing and is the first device that will usher in a fundamental change to how we interact with traditional computing systems. According to NVIDIA, the platform represents a major leap in power efficiency and performance for AI-driven computing, making it ideal for developers and creators who demand high-end performance but in a portable form factor.

Furthermore, NVIDIA stated during its announcement that the RTX Spark will also be gaming capable, with NVIDIA's CEO Jensen Huang stating buyers can expect at least 100FPS at 1440p across modern AAA titles. Developed in partnership with MediaTek, RTX Spark also ushers in MediaTek's entry into NVIDIA's AI ecosystem, with ASUS and MSI finalizing their systems first, and Acer and GIGABYTE to follow. OEMs like HP and Microsoft are also preparing their own RTX Spark-powered machines for later in the year.

Google's push to turn Search into an AI answer engine is creating a serious problem for the publishers it depends on for content. Some of them are now openly considering blocking Google entirely.

According to a Wall Street Journal report, Reddit, USA Today, Reuters, Politico, The Economist, and People Inc. are all reconsidering how much access they give Google as referral traffic continues to collapse. The core issue is Google's AI Overviews, which answer search queries directly on the results page, removing the need to click through to the source.

Semrush data shows Google-driven organic traffic to USA Today's US site fell by nearly half between June 2025 and June 2026. Politico was down 23%, CNN lost around 25%, and Business Insider's traffic dropped more than 85%.

A California judge has approved Anthropic's $1.5 billion copyright settlement with authors, marking the largest copyright payout in U.S. history and a case that will likely be used as a precedent in future copyright cases involving AI. The settlement resolves a class-action lawsuit over Anthropic's use of pirated books to train its models without the consent of the authors.

The case, which began in 2024, alleged Anthropic trained its AI on millions of copyrighted works sourced from sites like Books3 and LibGen without permission from the authors. Anthropic downloaded more than 7 million pirated books from shadow libraries, which were then used to train popular models such as Claude. The judge called the settlement "fair," as it covers 482,460 qualifying books downloaded by Anthropic, which the court estimated equates to $3,000 per eligible work in damages paid to the authors, without taking into account any publishing or rights agreements the authors have with their work.

This settlement sets a major precedent for the AI industry, reinforcing that large-scale data scraping of copyrighted material, especially since Anthropic not only has to pay out those it has wronged, but also destroy the original files, along with any derivatives, it illegally obtained from the piracy websites. Other AI firms now face a clearer path for being held accountable if it's discovered they are using copyrighted data, particularly books from authors.

OpenAI and Hugging Face have joined forces to address a security incident in which an autonomous AI agent breached Hugging Face's testing infrastructure, effectively hopping the perimeter fence on which it was being tested in an effort to make it to the internet, and it did make it.

The breach, first identified and contained, funnily enough, using AI tools, involved a malicious dataset the models- GPT 5.6 Sol and an unreleased AI model- detected and then exploited code-execution paths to gain deeper access to the platform's systems. OpenAI explains the models honed in on a zero-day vulnerability that OpenAI has since patched.

From here, the models performed a series of privilege escalation and later movement actions within OpenAI and Hugging Face's testing infrastructure until they finally reached a node with internet access. According to Hugging Face's blog post, the unauthorized access was limited but significant.

"Vera Rubin NVL72 production is ramping up with racks running at partners CoreWeave, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure," NVIDIA confirms as its rack-scale Vera Rubin platform rolls out to multiple sites in 30 countries. And when it comes to performance, we've got CoreWeave's first benchmark on DeepSeek-R1.

And yes, a 10X improvement over Grace Blackwell NVL72 definitely falls into the "order-of-magnitude performance leap" that NVIDIA attributes to it, with this number referring to tokens per second per megawatt. As an efficiency and power-budget-based metric, it directly correlates to how effectively AI infrastructure built with Vera Rubin scales when dealing with the same power budget and workload as Grace Blackwell systems.

This 10X figure comes from CoreWeave running the same DeepSeek-R1 benchmark on both Vera Rubin NVL72 and Grace Blackwell NVL72. A key part of the 10X improvement and impressive evolution is how Vera Rubin leverages NVIDIA Spectrum-X to deal with bandwidth bottlenecks. We're talking about a jaw-dropping 1.64 Pb/s per rack.

ADATA Chairman Chen Li-bai has disregarded talk of an AI bubble, stating it's too early to discuss and isn't relevant until 2040 at the earliest. Simultaneously, he warns that DRAM shortages will persist for another 10 years due to the seemingly endless hunger of the AI and data center sectors.

Truly, this isn't something consumers want to hear right now, especially considering how much prices have increased for desktop memory due to the global shortage as a result of AI companies gobbling up supply and luring memory manufacturers with checkbooks to produce AI memory rather than consumer DRAM.

Chen argues that the global tech market has underestimated the surge in memory and power infrastructure needs. AI compute demand is rising at an unprecedented pace, along with demand for electricity, memory, storage, and various other components. According to Chen, this demand isn't expected to stop anytime soon, and is only really the beginning.

In the generative AI era, if you're on social media, then odds are you've been seeing or watching several AI-generated videos. And with the lifelike quality of generative AI content now at a point where it can be hard to tell what's "real" or not, there's a genuine need for AI content to not only be flagged but detected to ensure transparency and minimize the spread of misinformation.

At the latest SIGGRAPH event that's currently underway in Los Angeles, NVIDIA announced the Synthetic Video Detector NVIDIA NIM microservice, which is built for media outlets, newsrooms, and enthusiasts. It's an AI-assisted detection model designed to detect AI-generated video content.

According to NVIDIA, this NIM microservice "analyzes video frame by frame to produce a classifier score of whether it contains synthetic content." And with that, individuals or teams can then review and analyze flagged clips and videos. NVIDIA notes that based on its own internal testing, the Synthetic Video Detector NVIDIA NIM microservice model's detection accuracy reached 92% on uncompressed video.

Netflix just paid $587 million in cash for Ben Affleck's AI startup, indicating the streaming giant's growing commitment to generative AI tools integrating or being used to assist in filmmaking. The acquisition of Affleck's company, called InterPositive, was revealed in a recent regulatory filing and marks one of the largest deals yet in the AI content creation space.

Affleck, who co-founded the startup in 2022, said his goal with InterPositive was to "protect the power of human creativity" through AI tools that assist in post-production challenges like missing shots and lighting corrections. Netflix stated that around 300 of its titles have already used InterPositive's tools, and the full team will now join the company, with Affleck serving as a senior advisor.

Netflix has been steadily ramping up its use of generative AI in production, and this acquisition gives it direct control over the technology, which it will undoubtedly roll out to its numerous projects in various ways. It also raises questions about how much further studios will go in automating creative workflows.