If you’ve ever played video games on a laptop that sounded like a small aircraft trying to take off, Intel has heard you (and your laptop). The company’s Chinese division has launched “AI Quiet Plus,” a new certification and optimization program for gaming laptops (via VideoCardz). 

As the name suggests, the feature uses artificial intelligence to dramatically reduce fan noise and surface heat while maintaining performance. 

How does AI Quiet Plus actually work?

It might be a bit confusing at first, since AI Quiet Plus isn’t a chip or a software update that you can download on the go. As mentioned earlier, it’s a certification standard that OEM partners must meet to carry the label.

The program uses the Neural Processing Unit (NPU) built into Intel’s Core Ultra 200HX Plus processors to monitor temperature, workload, power consumption, and fan speed in real-time. 

Rather than running the cooling fan at maximum speed a few minutes into a game (when the motherboard starts to heat up a bit), the system claims to intelligently read gaming conditions and adjust cooling only when it is actually required. 

What does this mean for everyday gamers?

OEMs meeting the new standard must meet more stringent targets across acoustics, keyboard and chassis temperatures, and battery efficiency. The technology builds directly on Intel China’s “AI Quiet Gaming Laptop” initiative. 

For everyday gamers, the AI Quiet Plus should translate to less disturbance and annoyance from the rocket engines on the laptop, less heat for your wrists, should you hop onto an urgent mail trail in the middle of your gaming session, and a longer battery life between charging sessions.

The first laptops certified under this program are expected to reach the market by the end of 2026. These would include laptops from brands like Asus, MSI, Lenovo, and Acer. For now, the program is tied to the Core Ultra 200HX Plus chips, which came out in March 2026. 

I can rip through a book or three a week, depending on my schedule. I just truly feel like there’s nothing better than becoming immersed in the plot and, specifically, diving into the minds of the characters. I’ve always gravitated toward fantasy books, with their mesmeric world-building and action-packed scenes. Like many people, I literally ached to be at Hogwarts when I was reading the Harry Potter series for the first time. With the progress of artificial intelligence, we’re getting closer to a reality where we can dive into those favorite stories. 

A new feature for Character.AI, launched Thursday, is an AI-powered role-play experience that allows you to play as a character inside your classic literature text. Called Books, the feature will launch with more than 20 public-domain titles, including Alice in Wonderland, Pride and Prejudice, Dracula, Frankenstein, Romeo and Juliet, and The Great Gatsby.

This new feature moves beyond Character.AI’s standard interactive open-ended chatting to an immersive storytelling experience and narrative-driven entertainment. 

Character.AI seems to be taking a step back from just offering open-ended chat functionality, which can be risky for emotionally vulnerable users or teens. Google and Character.AI both settled lawsuits earlier this year related to claims that these AI chatbots caused emotional harm to minors and led children to die by suicide. Last year, Character.AI made sweeping policy and safety changes, barring anyone under the age of 18 from using the platform for open-ended chats.

Read also: Character.AI: What to Know About the Role-Playing AI Tool and Its New Video Features

How Books works 

To get started, you can log into the Character.AI website and decide if you want to interact with Story Modes or Alternate Universe Remixes.

In Story Modes, you can choose to role-play as a specific character from a book or as your own from Character.AI. You can then choose to follow the original plot of the story with Book arc mode or create your own narrative with Go off script mode. Character.AI plans to launch more modes soon, such as TapTale, a more guided mode that offers prewritten prompts that you can choose to drive the narrative. 

Read also: Teens Can’t Talk to Character.AI’s Chatbots Anymore. Here’s What They Can Do Instead

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You can also completely remix the universe of classic literature with Alternate Universe Remixes. In this mode, you can set Alice in Wonderland in space or make Elizabeth Bennet a modern rom-com heroine. 

Books is now available for Character.AI Plus subscribers on both mobile and web as part of Character.AI Labs.

After launching in China, the Vivo X300 Ultra is now expected to go global on April 24. Although vivo hasn’t officially confirmed the timeline, signs point toward an upcoming rollout. India may not have to wait much longer, as the launch is expected soon after, with the phone aiming to stand out mainly for its camera capabilities. Europe is expected to get the phone first, with other regions likely to follow soon after.

Key Specifications of Vivo X300 Ultra

From a specifications standpoint, the Vivo X300 Ultra will take the X300 Pro’s features to the next level. It will come with a 6.82-inch 2K LTPO OLED display with a 144 Hz refresh rate. It may also pack a 7,000mAh battery and use the Snapdragon 7 Elite Gen 5 chipset. Even though these are solid features, they are not the primary reason this phone stands out.

One of the standout features of the Vivo X300 Ultra is its camera system. The device is said to be equipped with two 200MP cameras, with one serving as the main camera and the other as the periscope telephoto lens. In addition, the device will have a 50MP ultrawide camera and a 50MP front-facing selfie camera. A separate teleconverter module will be available for this device, enabling users to capture high-zoom images.

India Launch Timeline and Availability

The Vivo X300 Ultra is expected to launch in India around May, with sources suggesting a May 7 release date. However, the official release date has yet to be confirmed, and the launch is expected soon after this. The phone has already been showcased in India, with a recent picture posted showing it in the hands of Indian cricketer Shreyas Iyer.

Expected Price and Market Positioning

The upcoming Vivo X300 Ultra will likely have a high price point, particularly when considering international markets. In China, Vivo sells the 16GB + 1TB variant for about Rs 1.3 lakh, but in Europe, the company could price it at around EUR 1,900 (roughly Rs 2.08 lakh). At this price, it goes beyond devices like the iPhone 17 Pro Max and Samsung Galaxy S26 Ultra.

• Former PlayStation exec Shawn Layden has suggested Xbox can’t save Game Pass
• Layden said Xbox is “trying so hard to will this into health” despite the current issues
• This comes after a leaked memo from Xbox CEO Asha Sharma revealed plans to “evolve” the “expensive” service

Former PlayStation executive Shawn Layden has suggested Microsoft can’t save Xbox Game Pass, following comments made by Xbox CEO Asha Sharma about wanting to “evolve” the service.

Earlier this week, a leaked memo to employees obtained and reported on by The Verge showed Sharma admitting that the subscription service is now too expensive for members as she outlined a brief plan for how she aims to change things, writing, “Game Pass is central to gaming value on Xbox. It’s also clear that the current model isn’t the final one.

Slash, the vertical banking platform built by two college dropouts, has raised a $100M Series C backed by Khosla Ventures and Ribbit Capital. The company’s valuation has nearly quadrupled since its May 2025 Series B, the latest leg of a comeback story that began when its core market evaporated overnight.

Slash, the San Francisco-based vertical banking platform, has raised $100 million in a Series C round at a $1.4 billion valuation, backed by Khosla Ventures and Ribbit Capital, Bloomberg reported on Wednesday.

The raise marks a sharp acceleration in the company’s trajectory: less than a year ago, Slash closed its Series B at a $370 million valuation. The new round values the company at nearly four times that figure.

Slash was founded by Victor Cardenas, a Stanford dropout, and Kevin Bai, who left the University of Waterloo, and its origin story is one of the more unusual in recent fintech. The pair initially built banking services for sneaker resellers, a niche that took off quickly.

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Then Kanye West made a series of antisemitic public statements in late 2022. Adidas terminated its partnership with the rapper, collapsing the Yeezy market that was the backbone of the sneaker reselling economy.

According to Cardenas, Slash’s revenue fell by 80% almost overnight. The company had raised $19 million and built a team around a market that had suddenly ceased to exist.

Rather than fold, Cardenas and Bai pivoted to a broader thesis: vertical banking for online businesses. Instead of competing horizontally against Ramp, Mercury, and Brex, platforms that serve businesses across all industries, Slash builds tailored financial products for specific sectors.

The first post-pivot target was performance marketing firms, which run digital advertising campaigns on behalf of e-commerce companies.

A key pain point: these firms needed to create distinct accounts within their banking system for each end client to track prepayment and spending separately. Slash built that. By the time of its Series B announcement in May 2025, Cardenas told Fortune that more than 1% of all Facebook ads are bought with a Slash-issued card.

The pivot worked. Slash now serves verticals including web3, e-commerce, agencies, contractors, affiliate marketers, healthcare suppliers, online travel agencies, and wholesalers, alongside a stablecoin payments product and treasury and working capital tools.

The company’s product suite has expanded considerably since the early days of virtual debit cards for teenagers. Current offerings include corporate cards, business banking, stablecoin payments, treasury management, working capital, global USD accounts, invoicing, and a platform layer with multi-entity support, accounting integration, expense management, global payments, an API, analytics, and AI agents.

The platform is built on Column, a chartered bank co-founded by a Plaid executive that was designed from the ground up to serve tech-forward fintech companies, a relationship Cardenas has credited with helping Slash navigate the turbulence that hit the fintech middleware sector when Synapse, a major banking-as-a-service intermediary, collapsed.

Khosla Ventures has a long record of early fintech bets that have paid off at scale, the firm was an early investor in Stripe, Affirm, and Ramp. Ribbit Capital specialises exclusively in financial services and has backed Robinhood, Coinbase, and Credit Karma.

Their joint involvement in this round signals a conviction that Slash’s vertical model, winning in niche after niche rather than fighting for share across a horizontal market, has the structural advantages to compound into something large.

In the Series B announcement, Cardenas articulated the longer-term ambition: “If we continue solving these niche, vertical, specific financial workflows for businesses across different industries, then we can sneakily become one of the largest commercial credit card issuers in the country.”

The Copenhagen fintech has built a platform of specialised AI agents that handle KYC and KYB work, document reviews, ownership mapping, risk rationale, in minutes rather than hours. NEA led the Series A; Northzone, Seedcamp, and PSV Tech participated.

Spektr, a Copenhagen-based startup building AI infrastructure for financial compliance, has raised $20 million in a Series A round led by NEA, with continued participation from existing investors Northzone, Seedcamp, and PSV Tech.

The round brings total funding to just under $26 million, and will be used to expand Spektr’s engineering team, accelerate adoption among banks and large financial institutions, and open offices in London and New York. 

Spektr’s pitch is built on a specific frustration: that despite years of investment in compliance technology, most KYC and KYB work is still done by analysts manually.

The typical compliance review at a bank involves searching company registries, cross-referencing documents from multiple sources, mapping beneficial ownership structures, and writing risk rationales by hand, work that looks the same every day, is difficult to audit consistently, and scales poorly as regulatory volume increases.

Most of the tools built to address this have focused on workflow management and data aggregation, which reduces friction but does not eliminate the underlying analytical labour.

Spektr’s response is a platform of specialised AI agents that perform the analytical work itself, researching companies, verifying business activity, interpreting documents from multiple sources, generating structured risk assessments, with compliance teams reviewing and approving results rather than producing them from scratch.

According to the company, work that previously took an analyst hours completes in minutes. Financial institutions can design their own onboarding and monitoring workflows and deploy networks of these agents within them, turning manual analyst-driven processes into automated operations that can run at the scale of a large bank’s customer portfolio.

The platform handles both onboarding and ongoing monitoring, covering KYC, KYB, source-of-funds checks, document review, and false-positive reduction across the compliance lifecycle.

NEA partner Luke Pappas, who led the investment, told Crunchbase News he believes Spektr wins through “taste” and deep domain expertise in a market where AI can mass-produce functionality.

The company’s customers include Pleo, Santander Leasing, Mercuryo, Phantom, and Monta, as well as what the company describes as major US marketplace clients.

Pappas characterised Spektr’s differentiation as the ability to “coexist with existing solutions” while providing orchestration for compliance teams that are not yet ready to consolidate onto a single vendor.

CEO and co-founder Mikkel Skarnager described the core problem in the company’s announcement:

“Compliance technology has mostly focused on workflow and data collection. But the real bottleneck has always been the work itself, analysts researching companies, interpreting information, and documenting decisions.”

The company was seeded in February 2024 and has grown to 45 employees, with the new capital earmarked to scale engineering capacity for the more complex technical requirements of serving Tier 1 banks and large fintechs.

from the dumb-questions,-asked-unseriously dept

I cut my teeth as a telecom reporter, so I spent a lot of time writing about how broadband monopolies and cable TV giants rip off consumers with sleazy, misleading fees. I also spent a lot of that time writing about how lobbying and regulatory capture have ensured that big companies see no meaningful penalties should they falsely advertise one price, then sock you with a bunch of spurious surcharges.

The Biden administration, for its faults, at least tried to tackle some of this. The Biden FTC considered new and popular rules outlawing “junk fees”. The Biden FCC also implemented rules that didn’t ban sleazy fees (unfortunately), but forced broadband ISPs to clearly list them out at the point of sale (something recently dismantled by the Trump administration).

The Trump administration (and its courts) has taken an absolute hatchet to U.S. consumer protection on regulatory autonomy, ensuring that the problem of predatory fees is much worse across every sector you interface with. So it was funny to see Wall Street Journal reporters recently openly wondering why there are so many shitty fees all of a sudden (non-paywalled alternative):

“An extra 3% for paying with a credit card. A 5% involuntary contribution to a restaurant’s employee wellness fund. $25 a month in addition to rent for trash collection.  

Consumers already weary of rising inflation are now contending with a new crop of costs that are hidden in plain sight. New fees or surcharges are popping up everywhere as companies search for ways to recoup their own rising costs while blaming outside pressures.”

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The WSJ reporters and editors decided to cover soaring sleazy fees, but at no point in the article do they mention (even in passing) that Trump has dismantled most of the (already fleeting) efforts to rein in such predation. Or that the Trump Supreme Court has issued numerous rulings effectively making it almost impossible for regulators to fine corporations or hold them accountable for bad behavior.

The article mentions that the Trump FTC did grudgingly implement the Biden-era plan to ban junk fees, but they don’t think it’s worth mentioning that the Trump administration refuses to enforce it:

“The Federal Trade Commission banned drip pricing in short-term lodging and live-event ticketing in 2025, citing research showing that consumers were manipulated by low initial prices even when the full cost was eventually disclosed.”

They also don’t think it’s worth mentioning that the worst offenders of this kind of stuff, like Ticketmaster, were recently let off the hook by the Trump FTC via a piddly settlement (that left states, which had partnered with the FTC legally, high and dry). They’ve chosen to cover consumer protection, but not really. Not with any sort of interest in full, contextual reality.

While this particular instance is the Wall Street Journal, you’ll notice this same habit across most of corporate media. They’re dedicated to an alternate reality where Trump isn’t historically corrupt, and the regulators you’ve historically trusted to be at least semi-present to police the worst offenses are still dutifully on the beat protecting the public interest.

It’s of course a reflection of ownership bias seeping into editorial (most media owners are affluent Conservatives or Libertarians who like tax cuts, rubber stamped merger approvals, and mindless deregulation). But it’s also a form of weird normalization bias, where the reporters assume that because regulators have always been there (with natural partisan ebb and flow) they’ll always be there.

But they’re not there anymore. The damage will likely be deadly and permanent, impacting far more than just shitty, sneaky fees. And the press is doing a terrible job informing the public of that fact.

This is particularly amusing because the Wall Street Journal’s own reporting recently highlighted how even the semi-consistent folks within MAGA who sometimes supported things like functional antitrust reform have been easily ousted by lobbyists, but the reporters exploring “why are we getting ripped off more than ever by predatory corporations” aren’t willing to make the obvious connection.

Filed Under: antitrust, consumer protection, corruption, fees, ftc, hidden fees, junk fees, regulations, surcharges, trump

A new cybercrime platform called ATHR can harvest credentials via fully automated voice phishing attacks that use both human operators and AI agents for the social engineering phase.

The malicious operation is advertised on underground forums for $4,000 and a 10% comission from profits, and can steal login data for multiple services, including Google, Microsoft, and Coinbase.

Automation covers the entire telephone-oriented attack delivery (TOAD) stages, from luring targets over email to conducting voice-based social engineering and harvesting account credentials.

ATHR attack chain

According to researchers at cloud email security company Abnormal, ATHR is a complete phishing/vishing attack generator that offers brand-specific email templates, per-target customization, and spoofing mechanisms to make it appear as if the message originates from a trusted sender.

At the time of their analysis, the researchers observed that ATHR supported eight online services: Google, Microsoft, Coinbase, Binance, Gemini, Crypto.com, Yahoo, and AOL.

The attack starts with the victim receiving an email crafted to pass casual verification and even technical authentication checks.

“The lure is typically a fake security alert or account notification – something urgent enough to prompt a phone call but generic enough to avoid triggering content-based filters,” Abnormal notes in a report today.

Calling the phone number in the email routes the victim through Asterisk and WebRTC to AI voice agents driven by carefully crafted prompts that guide the victim through the data theft process.

The agents follow a multi-step script simulating a security incident. For Google accounts, they replicate the account recovery and verification process, using preset prompts that shape their tone, approach, persona, and behavior to mimic professional support staff.

The purpose of the fake recovery process is to extract a six-digit verification code that allows the attacker to gain access to the victim’s account.

Although ATHR does offer the option to route the call to a human operator, the ability to use an AI agent is what sets it apart.

ATHR’s dashboard gives operators control over the entire process and real-time data for each attack per target.

Through the ATHR panel, they control email distribution, handle calls, and manage phishing operations, monitoring outcomes in real time and receiving logs containing the stolen data.

Researchers at Abnormal warn that ATHR significantly reduces the manual effort for the operator and provides threat actors with an integrated platform that can handle all stages of a TOAD attack without the need to configure individual components.

This allows less technical attackers with no infrastructure to deploy automated vishing attacks from start to finish.

“The shift from a fragmented, manually intensive operation to a productized, largely automated one means TOAD attacks no longer require large teams or specialized infrastructure,” Abnormal warns.

With the rise of ATHR-like cybercrime platforms, the researchers expect vishing attacks to become more frequent and more difficult to distinguish from legitimate communications.

Defending against such attacks requires a different approach, since the lure emails carry no reliable indicators, are customized to authenticate correctly, and appear as valid notifications.

However, detection is possible by checking the communication behavioral patterns between a sender and a recipient, and identifying if similar lures containing a phone number reached the organization within a short time frame.

Abnormal researchers say that modeling normal communication behavior across the organization can help AI-powered detection flag anomalies before targets make a call.

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