An anonymous reader quotes a report from Inside Climate News: Just 32 companies accounted for over half of global fossil carbon emissions in 2024, according to a report published Wednesday by the U.K.-based think tank InfluenceMap. That is down from 36 companies responsible for half the global CO2 emissions in 2023, and 38 companies five years ago. The analysis is the latest update to the Carbon Majors database, which tracks the world’s largest oil, gas, coal and cement producers and uses production data to calculate the carbon emissions from each entity’s production. The database, first developed by researcher Richard Heede and now hosted by InfluenceMap, quantifies current and historical emissions attributable to nearly 180 companies and provides annual updates. It is the only database of its kind tracking corporate-generated carbon emissions dating back to the start of the Industrial Revolution, research that’s being used in efforts to hold major polluters accountable for climate harms.

Despite dire warnings from scientists about the consequences of accelerating climate change, fossil fuel production is continuing apace. Last year, fossil fuel CO2 emissions reached a record high, topping 38 billion metric tons. In 2024 these emissions were 37.4 billion metric tons — up 0.8 percent from 2023 — and traceable to 166 oil, gas, coal and cement producers, according to the report. Much of the global carbon emissions in 2024 came from state-owned entities, which represented 16 of the top 20 emitters. The five largest emitters overall — Saudi Arabia’s Aramco, Coal India, China’s CHN Energy, National Iranian Oil Co. and Russia’s Gazprom — were all state-controlled, and accounted for 18 percent of the total fossil CO2 emissions in 2024.

ExxonMobil, Chevron, Shell, ConocoPhillips and BP — the top five emitting investor-owned companies — together were responsible for 5.5 percent of the total emissions in that year. Historically, ExxonMobil and Chevron rank in the top five for fossil carbon emissions generated from 1854 through 2024, accounting for 2.79 percent and 3.08 percent of overall carbon pollution, respectively. According to the analysis, the 178 entities in the database have generated 70 percent of fossil CO2 emissions since the start of the Industrial Revolution, and just 22 entities are responsible for one-third of these emissions. “Each year, global emissions become increasingly concentrated among a shrinking group of high-emitting producers, while overall production continues to grow. Simultaneously, these heavy emitters continue to use lobbying to obstruct a transition that the scientific community has known for decades is essential,” said Emmett Connaire, senior analyst at InfluenceMap. The findings of the new analysis, he added, “underscore the growing importance of this kind of rigorous evidence in efforts to determine accountability for climate-related losses.”

Read more of this story at Slashdot.

If you’re thinking about upgrading to a new graphics card this year, your window for doing so at MSRP has closed. When I first reported on this at the start of December, things were looking bleak but you could still find GPUs from both AMD and NVIDIA at close to their recommended prices. That changed last week when YouTube channel Hardware Unboxed reported that ASUS had stopped producing the RTX 5070 Ti and 5060 Ti 16GB due to ongoing memory shortages. 

After Engadget published the news, NVIDIA disputed the report. “Demand for GeForce RTX GPUs is strong, and memory supply is constrained. We continue to ship all GeForce SKUs and are working closely with our suppliers to maximize memory availability,” a company spokesperson told us. 

The next day, ASUS walked back its previous statements. After “explicitly” telling Hardware Unboxed it had placed the 5060 Ti 16GB and 5070 Ti into “end-of-life status,” the company said “certain media may have received incomplete information from an ASUS PR representative regarding these products,” adding it had “no plans to stop selling these models.”  

Whether or not the 5060 Ti 16GB and 5070 Ti remain in production, one thing is certain: the AI boom has created a great deal of uncertainty in the GPU market. After the news, panic buying sent the price of the 5070 Ti through the roof. Right now, it’s impossible to find that model priced at its MSRP of $749. As of the writing of this article, the most affordable version of the 5070 Ti I could find on Newegg was $1,199. 

The bigger problem is that the 5070 Ti isn’t the only GPU selling for far more than MSRP. Tom’s Hardware has been tracking GPU prices for months, and there’s not a single model you can buy at either AMD or NVIDIA’s recommended price. That puts PC builders in a tough spot. What do you do if you want to upgrade to a new graphics card this year? 

If you’re sitting on an older GPU, the best advice I can give is to stick with your current hardware. If you’re fine with the performance of your video card right now, it’s best to wait a year or two for the market to settle down.

On the other hand, if your current GPU is not up to the task of running the games you want to play, try to buy a card with at least 12GB of VRAM — preferably 16GB if your budget allows for it. Unless you plan to play mostly older games on a 1080p monitor, it’s not worth considering a model with 8GB of VRAM — it won’t last you long enough to warrant the purchase price. 

For the most part, the recommendations in Engadget’s recent GPU guide are still as relevant today as they were a few months ago. The recommendations I provide here are pulled from that guide and are grouped from most affordable to most expensive. Where possible, I’ve tried to find options from both Newegg and Amazon. As you go about looking for a new GPU, your best friend is a website like PCPartPicker where you can track pricing across multiple retailers.  

Recommendations

AMD Radeon RX 9060 XT 16GB

Devindra Hardawar for Engadget

Unfortunately if you’re on a tight budget, there aren’t many great options under $400. For that reason, I would steer you to the Radeon RX 9060 XT as the best “entry-level” option. AMD offers two different versions of this GPU: one with 8GB of VRAM and the other with 16GB. Of the two, the latter is the better purchase, but if it’s outside your budget, the more affordable model is probably the best 8GB GPU on the market right now.

While I couldn’t find the 16GB variant at its recommended price of $350, I did find a few models that weren’t far off. Newegg has options from ASRock and Sapphire priced at $400 and $450. At Amazon, meanwhile, you can find models from PowerColor for $400 and $430.     

NVIDIA GeForce RTX 5070 

Devindra Hardawar for Engadget

I’m somewhat hesitant to recommend the RTX 5070. Don’t get me wrong, it’s a decent enough card, but with only 12GB of VRAM, you may end up replacing it sooner than you think. That said, it’s one of the few NVIDIA GPUs that hasn’t shot up massively in price, and I suspect that’s because people have been passing it over in favor of other 50-series models. If you value NVIDIA’s feature set over raw frames, then the 5070 is about the only GPU that makes sense to buy from the company right now.    

On Newegg, I found a 5070 model from Gigabyte for $650. The retailer also has a handful of different MSI variants priced at $630. Amazon has fewer options, but it does have one 5070 from Gigabyte for $585, which is the closest to the card’s $549 MSRP.    

AMD Radeon RX 9070 

Devindra Hardawar for Engadget

For a card that offers better price-to-performance than the 5070, the Radeon RX 9070 is your best bet. AMD’s take on NVIDIA features like DLSS aren’t as polished, but the RX 9070 offers more VRAM and excellent performance across the latest AAA games. 

It’s unlikely you’ll find one at its MSRP of $550, which was always more of an aspirational price, but I found a few models priced between $590 and $640. Both Newegg and Amazon have a PowerColor model for $590. The two also have a Gigabyte model priced at $600 after $40 rebate with coupon.      

AMD Radeon RX 9070XT

For those with more to spend, the RX 9070 XT is probably where I would cap things. Beyond that, you’re looking at GPUs like the 5080 that cost far more than MSRP. On Newegg, I found a model from ASRock selling for $730. Amazon, meanwhile, has options from Gigabyte and ASUS for $720. None of those are great deals, but that’s to be expected with a card that’s at the top of the stack.    

This article originally appeared on Engadget at https://www.engadget.com/gaming/pc/how-to-find-an-affordable-gpu-during-the-great-ramageddon-of-2026-130000654.html?src=rss

As we move through 2026, the narrative surrounding Artificial Intelligence has shifted from the breathless hype of “what if” to the cold, hard reality of execution. For the technology industry, 2026 is becoming a year of reckoning. We are seeing a massive bifurcation between the promise of “Agentic AI” and the fragmented, often frustrating experience of the “AI-PC.” While data centers continue to inhale silicon and power, the devices on our desks and in our pockets are struggling to define their new identity.

The AI-PC Identity Crisis: Fragmentation and Friction

The “AI-PC” was supposed to be the Great PC Renaissance. Instead, it has hit a significant wall characterized by a lack of local application support and a jarring lack of consistency between hardware OEMs. While Microsoft has pushed its Copilot+ standards, the actual user experience varies wildly depending on whether you are running an Intel, AMD, or Qualcomm-based system.

The most significant friction point remains the battle over the Neural Processing Unit (NPU). Microsoft’s vision for the AI-PC is centered on the NPU—a low-power engine designed for always-on background tasks like eye contact correction and local data indexing. However, NVIDIA, the undisputed king of AI hardware, has largely refused to play by Microsoft’s NPU rules. NVIDIA argues, quite effectively, that their RTX GPUs offer significantly more TOPS (Trillion Operations Per Second) than any integrated NPU, making the dedicated NPU redundant for high-end users.

This creates a “split-brain” problem for developers. Do they code for the low-power NPU to ensure battery efficiency, or do they target the massive power of the NVIDIA GPU? Because there is no unified execution layer, we are entering 2026 with a dearth of “killer” local AI apps. Most users are still just using their “AI-PC” to access cloud-based tools, which defeats the purpose of the expensive hardware sitting under the hood.

Generative AI: The Survival of the Smartest

In the realm of Generative AI, the landscape in 2026 is dominated by a few “God-models.” GPT-5 and Claude 4 have moved beyond simple text generation into complex “chain-of-thought” reasoning. These platforms are no longer just predicting the next word; they are simulating outcomes before they present them.

Google’s Gemini 3 is currently performing exceptionally well due to its deep integration into the Android ecosystem and Google Workspace, making it the most “convenient” AI for the average user. However, the shift in 2026 is moving away from these monolithic chat interfaces toward specialized, multimodal models. We are seeing a rise in “Sovereign AI,” where companies and even nations are training smaller, high-quality models on proprietary data rather than relying on the “strip-mined” public internet data that fueled the early versions of GPT.

The Rise of Agentic AI: From Tools to Teammates

If 2024 was the year of the Chatbot, 2026 is the year of the Agent. We are moving from “Prompt-based AI” to “Goal-based AI.” An agentic platform doesn’t wait for you to tell it what to do every step of the way; you give it a goal (e.g., “Organize a marketing campaign for the new Jaguar club newsletter”), and it coordinates with other agents to execute the task.

Microsoft’s AutoDev and Palantir’s AIP are currently the frontrunners in this space, providing robust frameworks for multi-agent orchestration. On the flip side, we are seeing “Agentic Bloat” in the consumer sector, where poorly designed agents from smaller startups are failing due to “jagged intelligence”—the tendency for an AI to solve a complex coding problem but fail at basic scheduling. In 2026, the best-performing agentic systems are those that treat AI as a “microservice,” where specialized agents handle discrete tasks under a central controller.

The AGI Mirage: Is 2026 the Turning Point?

The debate over Artificial General Intelligence (AGI) has reached a fever pitch. While Elon Musk and some tech optimists have predicted AGI could appear in 2026, the consensus among researchers is more tempered.

We are seeing “sparks” of AGI, particularly in the way models can now transfer knowledge between completely unrelated domains. However, the “scaling wall” is real. We are running out of high-quality human data to train on, and synthetic data is creating “model collapse” in some instances. While 2026 may be remembered as the year AI became “useful enough” to replace many white-collar functions, a true, self-aware, or fully autonomous AGI remains just out of reach for most.

The Memory Shortage: A Logistics War

The AI explosion has created a catastrophic shortage of High Bandwidth Memory (HBM) and DDR5. AI servers are consuming the world’s supply of DRAM, driving up costs for PCs and smartphones. This is where the “logistics advantage” becomes the primary competitive differentiator.

Lenovo is currently in the best position to weather this storm. Their massive, vertically integrated supply chain and deep relationships with memory suppliers in Asia have allowed them to stockpile components while others are forced to cut production or raise prices. In 2026, the “best” PC will often be the one that is actually available and affordable, giving Lenovo a significant edge in the enterprise market.

AI Security: The New Arms Race

As AI agents become more autonomous, the attack surface for corporations has exploded. “Prompt injection” has evolved into “Agent hijacking,” where a malicious actor can trick an AI agent into exfiltrating data or bypassing security protocols.

Companies like HP are positioning themselves as the “safe” harbor in this storm. HP’s Wolf Security has pivoted to address AI-specific threats, focusing on hardware-level isolation. By using “Privileged Access Workstations” and strong application isolation, they are aiming to contain AI-assisted attacks that traditional antivirus software simply cannot catch. In 2026, security is no longer about detecting the threat; it’s about isolating the AI so that even if it is compromised, it cannot touch the core enterprise data.

Hardware Roadmaps: Smartphones vs. PCs vs. The New Class

Smartphones continue to eclipse PCs in the AI race because they are “always-on” and “always-with-you.” The Pixel 10 and iPhone 17 (expected later this year) are becoming the primary interfaces for personal AI agents.

However, we are seeing the emergence of a new class of AI-centric hardware—wearables like refined AI glasses and “neck-worn” compute units—that threaten to make both the smartphone and the PC obsolete. These devices prioritize voice and visual “intent” over keyboards and touchscreens. If these devices gain enough traction in late 2026, the PC may be relegated to a specialized tool for “heavy lifting,” much like the mainframe became a back-end tool for the PC.

Transportation: The Level 4 Inflection Point

2026 is the year autonomous vehicles (AVs) move from “beta” to “baseline” in major urban centers. Companies like Waymo and Zoox are expanding rapidly, but the real story is the integration of AI into personal vehicles.

We are seeing Level 3 (L3) autonomy—where the car drives itself but the driver must be ready to take over—becoming a standard option in high-end models from BMW and Mercedes. Meanwhile, the partnership between Lucid and Nuro is pushing the boundaries of “personal robocars.” The AI in these vehicles is no longer just following rules; it is using “World Models” to predict the behavior of pedestrians and other drivers with uncanny accuracy.

Preparing for the AI-Driven 2026

For individuals and companies to survive this transition, the priorities must shift:

1. Redesign Work, Don’t Just Automate: Follow the 80/20 rule. 80% of the value comes from redesigning workflows so agents can handle the routine, allowing humans to focus on strategy.
2. Fix the Data Foundation: AI is only as good as the data it accesses. Companies must prioritize “data hygiene” to ensure their agents aren’t making decisions based on “garbage” data.
3. Invest in “AI-Forward” Talent: The most valuable employees in 2026 are not those who can “prompt” an AI, but those who can orchestrate multiple AI systems.

Wrapping Up

The AI landscape of 2026 is one of incredible power but deep fragmentation. The AI-PC is struggling to find its footing due to hardware-software friction and a lack of local apps, while the cloud-based “Agentic AI” revolution is moving at light speed. Companies like Lenovo and HP are leveraging logistics and security to maintain their dominance, even as new classes of hardware threaten the traditional PC model. Whether or not we reach AGI this year is almost secondary to the fact that AI is now a permanent, autonomous “partner” in the global economy. The winners of 2026 won’t be those with the fastest chips, but those who can most effectively manage the “Supersonic Tsunami” of intelligent automation.

Snapchat is updating its parental control features to give parents more detailed information about who their kids are connecting with in the app and which features they use the most. The app’s Family Center already gives parents visibility into their child’s friend list, but it will now surface contextual details when a new friend is added.

For example, the feature could highlight that the two share mutual friends or have each other’s contact info saved in their phones. It could also indicate that they are classmates if both users have joined the same in-app “community.” If the two have no commonalities, then that could be a sign for a parent to “start a productive conversation,” Snap says. 

The company has long been criticized for making it too easy for teenagers to talk to strangers. The issue has come up in safety-related lawsuits, including an ongoing case brought by New Mexico’s Attorney General. Snap says that adding additional “trust signals” to its parental control features “make it easier for parents to understand new connections and have greater confidence that their teen is chatting with someone they know in real life.”

The update is also adding more granular stats about how exactly teens are spending their time in the app. Family Center’s screen time dashboard now includes a breakdown of how much of their time spent in the app is in its messaging, camera, map or shortform video features. It will still be up to parents to decide what, if any, limits they want to put on their teens. But at a time when there’s increasing conversation around banning teens from social media entirely, having access to more stats could better help parents understand their kids’ relationship with Snapchat.

This article originally appeared on Engadget at https://www.engadget.com/social-media/snapchat-gives-parents-more-info-on-who-their-kids-are-talking-to-120000077.html?src=rss

Ars Technica’s Benj Edwards reports: On Saturday, tech entrepreneur Siqi Chen released an open source plugin for Anthropic’s Claude Code AI assistant that instructs the AI model to stop writing like an AI model. Called “Humanizer,” the simple prompt plugin feeds Claude a list of 24 language and formatting patterns that Wikipedia editors have listed as chatbot giveaways. Chen published the plugin on GitHub, where it has picked up over 1,600 stars as of Monday. “It’s really handy that Wikipedia went and collated a detailed list of ‘signs of AI writing,'” Chen wrote on X. “So much so that you can just tell your LLM to… not do that.”

The source material is a guide from WikiProject AI Cleanup, a group of Wikipedia editors who have been hunting AI-generated articles since late 2023. French Wikipedia editor Ilyas Lebleu founded the project. The volunteers have tagged over 500 articles for review and, in August 2025, published a formal list of the patterns they kept seeing.

Chen’s tool is a “skill file” for Claude Code, Anthropic’s terminal-based coding assistant, which involves a Markdown-formatted file that adds a list of written instructions (you can see them here) appended to the prompt fed into the large language model (LLM) that powers the assistant. Unlike a normal system prompt, for example, the skill information is formatted in a standardized way that Claude models are fine-tuned to interpret with more precision than a plain system prompt. (Custom skills require a paid Claude subscription with code execution turned on.)

But as with all AI prompts, language models don’t always perfectly follow skill files, so does the Humanizer actually work? In our limited testing, Chen’s skill file made the AI agent’s output sound less precise and more casual, but it could have some drawbacks: it won’t improve factuality and might harm coding ability. […] Even with its drawbacks, it’s ironic that one of the web’s most referenced rule sets for detecting AI-assisted writing may help some people subvert it.

Read more of this story at Slashdot.

Blue Origin has unveiled an enterprise-focused satellite internet network called TeraWave, which promises up to 6 Tbps speeds via a mixed low- and medium-Earth orbit constellation. TechCrunch reports: The TeraWave constellation will use a mix of 5,280 satellites in low-Earth orbit and 128 in medium-Earth orbit, and Blue Origin plans to deploy the first ones in late 2027. It’s not immediately clear how long Blue Origin expects it will take to build out the whole network. The low-Earth orbit satellites Blue Origin is building will use RF connectivity and have a max data transfer speed of 144 Gbps, while the medium-Earth variety will use an optical link that can achieve the much higher 6 Tbps speed. For reference, SpaceX’s Starlink currently maxes out at 400 Mbps — though it plans to launch upgraded satellites that will offer 1 Gbps data transfer in the future. “We identified an unmet need with customers who were seeking enterprise-grade internet access with higher speeds, symmetrical upload/download speeds, more redundancy, and rapid scalability for their networks. TeraWave solves for these problems,” Blue Origin said in a statement.

Read more of this story at Slashdot.

X is rolling out a new feature called “Starterpacks” to all users in the coming weeks, the company’s head of product has announced. It’s made up of compilations of accounts new users can follow based on their interests. If that sounds familiar, it’s because Bluesky launched a very similar feature that’s also called “starter packs” back in 2024. Bluesky allows ordinary users to curate their own packs as long as each one doesn’t exceed 50 accounts. They can then share those lists broadly on the platform or directly with new users via QR code. X, on the other hand, compiled and curated its own lists.

In his announcement, X head of product Nikita Bier said the company “scoured the world for the top posters in every niche and country.” X then compiled them into Starterpacks “to help new users find the best accounts — big or small — for their interests.” Before X announced its own take on the feature, other social media services had already launched their clones of Bluesky’s tool. Threads’ version, which rolled out in late 2024, puts collections of recommended profiles as suggestions in the feeds of new users. Mastodon launched its own in 2025, which gives existing users the freedom to choose whether they can or can’t be included in the lists.

This article originally appeared on Engadget at https://www.engadget.com/social-media/x-is-also-launching-bluesky-like-starter-packs-050057033.html?src=rss