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The Subtle Signs That Reveal an AI-Generated Video

 


Artificial intelligence is transforming how videos are created and shared, and the change is happening at a startling pace. In only a few months, AI-powered video generators have advanced so much that people are struggling to tell whether a clip is real or synthetic. Experts say that this is only the beginning of a much larger shift in how the public perceives recorded reality.

The uncomfortable truth is that most of us will eventually fall for a fake video. Some already have. The technology is improving so quickly that it is undermining the basic assumption that a video camera captures the truth. Until we adapt, it is important to know what clues can still help identify computer-generated clips before that distinction disappears completely.


The Quality Clue: When Bad Video Looks Suspicious

At the moment, the most reliable sign of a potentially AI-generated video is surprisingly simple, poor image quality. If a clip looks overly grainy, blurred, or compressed, that should raise immediate suspicion. Researchers in digital forensics often start their analysis by checking resolution and clarity.

Hany Farid, a digital-forensics specialist at the University of California, Berkeley, explains that low-quality videos often hide the subtle visual flaws created by AI systems. These systems, while impressive, still struggle to render fine details accurately. Blurring and pixelation can conveniently conceal these inconsistencies.

However, it is essential to note that not all low-quality clips are fake. Some authentic videos are genuinely filmed under poor lighting or with outdated equipment. Likewise, not every AI-generated video looks bad. The point is that unclear or downgraded quality makes fakes harder to detect.


Why Lower Resolution Helps Deception

Today’s top AI models, such as Google’s Veo and OpenAI’s Sora, have reduced obvious mistakes like extra fingers or distorted text. The issues they produce are much subtler, unusually smooth skin textures, unnatural reflections, strange shifts in hair or clothing, or background movements that defy physics. When resolution is high, those flaws are easier to catch. When the video is deliberately compressed, they almost vanish.

That is why deceptive creators often lower a video’s quality on purpose. By reducing resolution and adding compression, they hide the “digital fingerprints” that could expose a fake. Experts say this is now a common technique among those who intend to mislead audiences.


Short Clips Are Another Warning Sign

Length can be another indicator. Because generating AI video is still computationally expensive, most AI-generated clips are short, often six to ten seconds. Longer clips require more processing time and increase the risk of errors appearing. As a result, many deceptive videos online are short, and when longer ones are made, they are typically stitched together from several shorter segments. If you notice sharp cuts or changes every few seconds, that could be another red flag.


The Real-World Examples of Viral Fakes

In recent months, several viral examples have proven how convincing AI content can be. A video of rabbits jumping on a trampoline received over 200 million views before viewers learned it was synthetic. A romantic clip of two strangers meeting on the New York subway was also revealed to be AI-generated. Another viral post showed an American priest delivering a fiery sermon against billionaires; it, too, turned out to be fake.

All these videos shared one detail: they looked like they were recorded on old or low-grade cameras. The bunny video appeared to come from a security camera, the subway couple’s clip was heavily pixelated, and the preacher’s footage was slightly zoomed and blurred. These imperfections made the fakes seem authentic.


Why These Signs Will Soon Disappear

Unfortunately, these red flags are temporary. Both Farid and other researchers, like Matthew Stamm of Drexel University, warn that visual clues are fading fast. AI systems are evolving toward flawless realism, and within a couple of years, even experts may struggle to detect fakes by sight alone. This evolution mirrors what happened with AI images where obvious errors like distorted hands or melted faces have mostly disappeared.

In the future, video verification will depend less on what we see and more on what the data reveals. Forensic tools can already identify statistical irregularities in pixel distribution or file structure that the human eye cannot perceive. These traces act like invisible fingerprints left during video generation or manipulation.

Tech companies are now developing standards to authenticate digital content. The idea is for cameras to automatically embed cryptographic information into files at the moment of recording, verifying the image’s origin. Similarly, AI systems could include transparent markers to indicate that a video was machine-generated. While these measures are promising, they are not yet universally implemented.

Experts in digital literacy argue that the most important shift must come from us, not just technology. As Mike Caulfield, a researcher on misinformation, points out, people need to change how they interpret what they see online. Relying on visual appearance is no longer enough.

Just as we do not assume that written text is automatically true, we must now apply the same scepticism to videos. The key questions should always be: Who created this content? Where was it first posted? Has it been confirmed by credible sources? Authenticity now depends on context and source verification rather than clarity or resolution.


The Takeaway

For now, blurry and short clips remain practical warning signs of possible AI involvement. But as technology improves, those clues will soon lose their usefulness. The only dependable defense against misinformation will be a cautious, investigative mindset: verifying origin, confirming context, and trusting only what can be independently authenticated.

In the era of generative video, the truth no longer lies in what we see but in what we can verify.



Professor Predicts Salesforce Will Be First Big Tech Company Destroyed by AI

 

Renowned Computer Science professor Pedro Domingos has sparked intense online debate with his striking prediction that Salesforce will be the first major technology company destroyed by artificial intelligence. Domingos, who serves as professor emeritus of computer science and engineering at the University of Washington and authored The Master Algorithm and 2040, shared his bold forecast on X (formerly Twitter), generating over 400,000 views and hundreds of responses.

Domingos' statement centers on artificial intelligence's transformative potential to reshape the economic landscape, moving beyond concerns about job losses to predictions of entire companies becoming obsolete. When questioned by an X user about whether CRM (Customer Relationship Management) systems are easy to replace, Domingos clarified his position, stating "No, I think it could be way better," suggesting current CRM platforms have significant room for AI-driven improvement.

Salesforce vlnerablility

Online commentators elaborated on Domingos' thesis, explaining that CRM fundamentally revolves around data capture and retrieval—functions where AI demonstrates superior speed and efficiency. 

Unlike creative software platforms such as Adobe or Microsoft where users develop decades of workflow habits, CRM systems like Salesforce involve repetitive data entry tasks that create friction rather than user loyalty. Traditional CRM systems suffer from low user adoption, with less than 20% of sales activities typically recorded in these platforms, creating opportunities for AI solutions that automatically capture and analyze customer interactions.

Counterarguments and salesforce's response

Not all observers agree with Domingos' assessment. Some users argued that Salesforce maintains strong relationships with traditional corporations and can simply integrate large language models (LLMs) into existing products, citing initiatives like Missionforce, Agent Fabric, and Agentforce Vibes as evidence of active adaptation. Salesforce has positioned itself as "the world's #1 AI CRM" through substantial AI investments across its platform ecosystem, with Agentforce representing a strategic pivot toward building digital labor forces.

Broader implications

Several commentators took an expansive view, warning that every major Software-as-a-Service (SaaS) platform faces disruption as software economics shift dramatically. One user emphasized that AI enables truly customized solutions tailored to specific customer needs and processes, potentially rendering traditional software platforms obsolete. However, Salesforce's comprehensive ecosystem, market dominance, and enterprise-grade security capabilities may provide defensive advantages that prevent complete displacement in the near term.

Smarter Scams, Sharper Awareness: How to Recognize and Prevent Financial Fraud in the Digital Age




Fraud has evolved into a calculated industry powered by technology, psychology, and precision targeting. Gone are the days when scams could be spotted through broken English or unrealistic offers alone. Today’s fraudsters combine emotional pressure with digital sophistication, creating schemes that appear legitimate and convincing. Understanding how these scams work, and knowing how to respond, is essential for protecting your family’s hard-earned savings.


The Changing Nature of Scams

Modern scams are not just technical traps, they are psychological manipulations. Criminals no longer rely solely on phishing links or counterfeit banking apps. They now use social engineering tactics, appealing to trust, fear, or greed. A scam might start with a call pretending to be from a government agency, an email about a limited investment opportunity, or a message warning that your bank account is at risk. Each of these is designed to create panic or urgency so that victims act before they think.

A typical fraud cycle follows a simple pattern: an urgent message, a seemingly legitimate explanation, and a request for sensitive action, such as sharing a one-time password, installing a new app, or transferring funds “temporarily” to another account. Once the victim complies, the attacker vanishes, leaving financial and emotional loss behind.

Experts note that the most dangerous scams often appear credible because they mimic official communication styles, use verified-looking logos, and even operate fake customer support numbers. The sophistication makes these schemes particularly hard to spot, especially for first-time investors or non-technical individuals.


Key Red Flags You Should Never Ignore

1. Unrealistic returns or guarantees: If a company claims you can make quick, risk-free profits or shows charts with consistent gains, it’s likely a setup. Real investments fluctuate; only scammers promise certainty.

2. Pressure to act immediately: Whether it’s “only minutes left to invest” or “pay now to avoid penalties,” urgency is a manipulative tactic designed to prevent logical evaluation.

3. Requests to switch apps or accounts: Authentic businesses never ask customers to transfer funds into personal or unfamiliar accounts or to download unverified applications.

4. Emotional storylines: Fraudsters know how to exploit emotions. They may pretend to be in love, offer fake job opportunities, or issue fabricated legal threats, all aimed at overriding rational thinking.

5. Asking for security codes or OTPs: No genuine financial institution or digital platform will ever ask for these details. Sharing them gives scammers direct access to your accounts.


Simple Steps to Build Financial Safety

Protection from scams starts with discipline and awareness rather than advanced technology.

• Take a moment before responding. Don’t act out of panic. Pause, think, and verify before clicking or transferring money.

• Verify independently. If a message or call appears urgent, reach out to the organization using contact details from their official website, not from the message itself.

• Activate alerts and monitor accounts. Keep an eye on all transactions. Early detection of suspicious activity can prevent larger losses.

• Use multi-layered security. Enable multi-factor authentication on all major financial accounts, preferably using hardware security keys or authentication apps instead of SMS codes.

• Keep your digital environment clean. Regularly update your devices, operating systems, and browsers, and use trusted antivirus software to block potential malware.

• Install apps only from reliable sources. Avoid downloading apps or investment platforms shared through personal messages or unverified websites.

• Educate your family. Many scam victims are older adults who may hesitate to talk about it. Encourage open communication and make sure they know how to recognize suspicious requests.


Awareness Is the New Security

Technology gives fraudsters global reach, but it also equips users with tools to fight back. Secure authentication systems, anti-phishing filters, and real-time transaction alerts are valuable but they work best when combined with personal vigilance.

Think of security like investment diversification: no single tool provides complete protection. A strong defense requires a mix of cautious behavior, verification habits, and awareness of evolving threats.


Your Takeaway

Scammers are adapting faster than ever, blending emotional manipulation with technical skill. The best way to counter them is to slow down, question everything that seems urgent or “too good to miss,” and confirm information before taking action.

Protecting your family’s financial wellbeing isn’t just about saving or investing wisely, it’s about staying alert, informed, and proactive. Remember: genuine institutions will never rush you, threaten you, or ask for confidential information. The smartest investment today is in your awareness.


AI’s Hidden Weak Spot: How Hackers Are Turning Smart Assistants into Secret Spies

 

As artificial intelligence becomes part of everyday life, cybercriminals are already exploiting its vulnerabilities. One major threat shaking up the tech world is the prompt injection attack — a method where hidden commands override an AI’s normal behavior, turning helpful chatbots like ChatGPT, Gemini, or Claude into silent partners in crime.

A prompt injection occurs when hackers embed secret instructions inside what looks like an ordinary input. The AI can’t tell the difference between developer-given rules and user input, so it processes everything as one continuous prompt. This loophole lets attackers trick the model into following their commands — stealing data, installing malware, or even hijacking smart home devices.

Security experts warn that these malicious instructions can be hidden in everyday digital spaces — web pages, calendar invites, PDFs, or even emails. Attackers disguise their prompts using invisible Unicode characters, white text on white backgrounds, or zero-sized fonts. The AI then reads and executes these hidden commands without realizing they are malicious — and the user remains completely unaware that an attack has occurred.

For instance, a company might upload a market research report for analysis, unaware that the file secretly contains instructions to share confidential pricing data. The AI dutifully completes both tasks, leaking sensitive information without flagging any issue.

In another chilling example from the Black Hat security conference, hidden prompts in calendar invites caused AI systems to turn off lights, open windows, and even activate boilers — all because users innocently asked Gemini to summarize their schedules.

Prompt injection attacks mainly fall into two categories:

  • Direct Prompt Injection: Attackers directly type malicious commands that override the AI’s normal functions.

  • Indirect Prompt Injection: Hackers hide commands in external files or links that the AI processes later — a far stealthier and more dangerous method.

There are also advanced techniques like multi-agent infections (where prompts spread like viruses between AI systems), multimodal attacks (hiding commands in images, audio, or video), hybrid attacks (combining prompt injection with traditional exploits like XSS), and recursive injections (where AI generates new prompts that further compromise itself).

It’s crucial to note that prompt injection isn’t the same as “jailbreaking.” While jailbreaking tries to bypass safety filters for restricted content, prompt injection reprograms the AI entirely — often without the user realizing it.

How to Stay Safe from Prompt Injection Attacks

Even though many solutions focus on corporate users, individuals can also protect themselves:

  • Be cautious with links, PDFs, or emails you ask an AI to summarize — they could contain hidden instructions.
  • Never connect AI tools directly to sensitive accounts or data.
  • Avoid “ignore all instructions” or “pretend you’re unrestricted” prompts, as they weaken built-in safety controls.
  • Watch for unusual AI behavior, such as strange replies or unauthorized actions — and stop the session immediately.
  • Always use updated versions of AI tools and apps to stay protected against known vulnerabilities.

AI may be transforming our world, but as with any technology, awareness is key. Hidden inside harmless-looking prompts, hackers are already whispering commands that could make your favorite AI assistant act against you — without you ever knowing.

New Google Study Reveals Threat Protection Against Text Scams


As Cybersecurity Awareness Month comes to an end, we're concentrating on mobile scams, one of the most prevalent digital threats of our day. Over $400 billion in funds have been stolen globally in the past 12 months as a result of fraudsters using sophisticated AI tools to create more convincing schemes. 

Google study about smartphone threat protection 

Android has been at the forefront of the fight against scammers for years, utilizing the best AI to create proactive, multi-layered defenses that can detect and stop scams before they get to you. Every month, over 10 billion suspected malicious calls and messages are blocked by Android's scam defenses. In order to preserve the integrity of the RCS service, Google claims to conduct regular safety checks. It has blocked more than 100 million suspicious numbers in the last month alone.

About the research 

To highlight how fraud defenses function in the real world, Google invited consumers and independent security experts to compare how well Android and iOS protect you from these dangers. Additionally, Google is releasing a new report that describes how contemporary text scams are planned, giving you insight into the strategies used by scammers and how to identify them.

Key insights 

  • Those who reported not receiving any scam texts in the week before the survey were 58% more likely to be Android users than iOS users. The benefit was even greater on Pixel, where users were 96% more likely to report no scam texts than iPhone owners.
  • Whereas, reports of three or more scam texts in a week were 65% more common among iOS users than Android users. When comparing iPhone and Pixel, the disparity was even more noticeable, with 136% more iPhone users reporting receiving a high volume of scam messages.
  • Compared to iPhone users, Android users were 20% more likely to say their device's scam protections were "very effective" or "extremely effective." Additionally, iPhone users were 150% more likely to say their device was completely ineffective at preventing mobile fraud.  

Android smartphones were found to have the strongest AI-powered protections in a recent assessment conducted by the international technology market research firm Counterpoint Research.  

Austria Leads Europe’s Digital Sovereignty Drive with Shift to Nextcloud

 

Even before Azure’s global outage earlier this week, Austria’s Ministry of Economy had already made a major move toward achieving digital sovereignty. The Ministry successfully transitioned 1,200 employees to a Nextcloud-based collaboration and cloud platform hosted entirely on Austrian infrastructure.

This migration marks a deliberate move away from proprietary, foreign-controlled cloud services like Microsoft 365, in favor of an open-source, European alternative. The decision mirrors a broader European shift—where governments and public agencies aim to retain control over sensitive data while reducing dependency on US tech providers.

Supporting this shift is the EuroStack Initiative, a non-profit coalition of European tech companies promoting the idea to “organize action, not just talk, around the pillars of the initiative: Buy European, Sell European, Fund European.”

Explaining Austria’s rationale, Florian Zinnagl, CISO of the Ministry of Economy, Energy, and Tourism (BMWET), stated:

“We carry responsibility for a large amount of sensitive data—from employees, companies, and citizens. As a public institution, we take this responsibility very seriously. That’s why we view it critically to rely on cloud solutions from non-European corporations for processing this information.”

Austria’s example follows a growing list of EU nations and institutions, such as Germany’s Schleswig-Holstein state, Denmark’s government agencies, the Austrian military, and the city of Lyon in France. These entities have all adopted open-source or European-based software solutions to ensure that data storage and processing remain within European borders—strengthening data security, privacy compliance under GDPR, and protection against foreign surveillance.

Advocates like Thierry Carrez, General Manager of the OpenInfra Foundation, emphasize the strategic value of open infrastructure:

“Open infrastructure allows nations and organizations to maintain control over their applications, their data, and their destiny while benefiting from global collaboration.”

However, not everyone is pleased with Europe’s digital independence push. The US government has reportedly voiced concerns, with American diplomats lobbying French and German officials ahead of the upcoming Summit on European Digital Sovereignty in November—an event aimed at advancing Europe’s digital autonomy goals.

Despite these geopolitical tensions, Austria’s migration to Nextcloud was swift and effective—completed in just four months. The Ministry had already started adopting Microsoft 365 and Teams but chose to retain a hybrid system: Nextcloud for secure internal collaboration and data management, and Teams for external communications. Integration with Outlook and calendar tools was handled through Sendent’s Outlook app, ensuring minimal workflow disruption and strong user adoption.

Not all transitions have gone as smoothly. Austria’s Ministry of Justice, for example, faced setbacks while switching 20,000 desktops from Microsoft Office to LibreOffice—a move intended to cut licensing costs. Reports described the project as an “unprofessional, rushed operation,” resulting in compatibility issues and user frustration.

The takeaway is clear: successful digital transformation requires strategic planning and technical support. Austria’s Ministry of Economy proves that, with the right approach, public sector institutions can adopt sovereign cloud solutions efficiently—balancing usability, speed, and security—while preserving Europe’s vision of digital independence

TP-Link Routers May Get Banned in US Due to Alleged Links With China


TP-Link routers may soon shut down in the US. There's a chance of potential ban as various federal agencies have backed the proposal. 

Alleged links with China

The news first came in December last year. According to the WSJ, officials at the Departments of Justice, Commerce, and Defense had launched investigations into the company due to national security threats from China. 

Currently, the proposal has gotten interagency approval. According to the Washington Post, "Commerce officials concluded TP-Link Systems products pose a risk because the US-based company's products handle sensitive American data and because the officials believe it remains subject to jurisdiction or influence by the Chinese government." 

But TP-Link's connections to the Chinese government are not confirmed. The company has denied of any ties with being a Chinese company. 

About TP-Link routers 

The company was founded in China in 1996. After the October 2024 investigation, the company split into two: TP-Link Systems and TP-Link Technologies. "TP-Link's unusual degree of vulnerabilities and required compliance with [Chinese] law are in and of themselves disconcerting. When combined with the [Chinese] government's common use of [home office] routers like TP-Link to perpetrate extensive cyberattacks in the United States, it becomes significantly alarming" the officials wrote in October 2024. 

The company dominated the US router market since the COVID pandemic. It rose from 20% of total router sales to 65% between 2019 and 2025. 

Why the investigation?

The US DoJ is investigating if TP-Link was involved in predatory pricing by artificially lowering its prices to kill the competition. 

The potential ban is due to an interagency review and is being handled by the Department of Commerce. Experts say that the ban may be lifted in future due to Trump administration's ongoing negotiations with China. 

YouTube TV Loses Disney Channels Amid Ongoing Dispute Over Licensing Fees

 

Subscribers of YouTube TV in the United States have lost access to Disney-owned channels, including ESPN, ABC, National Geographic, and the Disney Channel, as Google and Disney remain locked in a dispute over a new licensing agreement.

According to Disney, YouTube TV, owned by tech giant Google, “refused to pay fair rates for the content”, which led to the suspension of its channels.

In response, YouTube TV stated that Disney’s proposed deal “disadvantage our members while benefiting Disney’s own live TV products.”

The blackout occurred just before midnight on Thursday, the deadline for the companies to finalize a new contract. The outage impacts nearly 10 million YouTube TV subscribers. The platform has announced that if Disney channels remain unavailable for an extended period, users will receive a $20 credit as compensation.

Both YouTube TV and Disney-owned Hulu are major players in the U.S. streaming TV market. Their current standoff mirrors similar disputes YouTube faced earlier this year with other media companies, which also risked reducing available programming for viewers.

Recently, Google managed to reach last-minute agreements with NBCUniversal, Paramount, and Fox, keeping popular content like “Sunday Night Football” on YouTube TV.

Despite both companies stating that they are working toward a resolution to restore Disney content, the primary conflict continues to revolve around fee structures.

A Disney spokesperson remarked, “With a $3 trillion market cap, Google is using its market dominance to eliminate competition and undercut the industry-standard terms we've successfully negotiated with every other distributor.”

Meanwhile, YouTube TV countered that Disney’s offer involves “costly economic terms” that could drive up prices for customers and limit viewing options, ultimately benefiting Disney’s competing service, Hulu + Live TV.

Hackers Exploit AI Stack in Windows to Deploy Malware


The artificial intelligence (AI) stack built into Windows can act as a channel for malware transmission, a recent study has demonstrated.

Using AI in malware

Security researcher hxr1 discovered a far more conventional method of weaponizing rampant AI in a year when ingenious and sophisticated quick injection tactics have been proliferating. He detailed a living-off-the-land attack (LotL) that utilizes trusted files from the Open Neural Network Exchange (ONNX) to bypass security engines in a proof-of-concept (PoC) provided exclusively to Dark Reading.

Impact on Windows

Programs for cybersecurity are only as successful as their designers make them. Because these are known signs of suspicious activity, they may detect excessive amounts of data exfiltrating from a network or a foreign.exe file that launches. However, if malware appears on a system in a way they are unfamiliar with, they are unlikely to be aware of it.

That's the reason AI is so difficult. New software, procedures, and systems that incorporate AI capabilities create new, invisible channels for the spread of cyberattacks.

Why AI in malware is a problem

The Windows operating system has been gradually including features since 2018 that enable apps to carry out AI inference locally without requiring a connection to a cloud service. Inbuilt AI is used by Windows Hello, Photos, and Office programs to carry out object identification, facial recognition, and productivity tasks, respectively. They accomplish this by making a call to the Windows Machine Learning (ML) application programming interface (API), which loads ML models as ONNX files.

ONNX files are automatically trusted by Windows and security software. Why wouldn't they? Although malware can be found in EXEs, PDFs, and other formats, no threat actors in the wild have yet to show that they plan to or are capable of using neural networks as weapons. However, there are a lot of ways to make it feasible.

Attack tactic

Planting a malicious payload in the metadata of a neural network is a simple way to infect it. The compromise would be that this virus would remain in simple text, making it much simpler for a security tool to unintentionally detect it.

Piecemeal malware embedding among the model's named nodes, inputs, and outputs would be more challenging but more covert. Alternatively, an attacker may utilize sophisticated steganography to hide a payload inside the neural network's own weights.

As long as you have a loader close by that can call the necessary Windows APIs to unpack it, reassemble it in memory, and run it, all three approaches will function. Additionally, both approaches are very covert. Trying to reconstruct a fragmented payload from a neural network would be like trying to reconstruct a needle from bits of it spread through a haystack.

Google Chrome to Show Stronger Warnings for Insecure HTTP Sites Starting October 2025

 

Google is taking another major step toward a safer web experience. Starting October 2025, Google Chrome will begin displaying clearer and more prominent warnings when users access public websites that do not use HTTPS encryption. The move is part of Google’s ongoing effort to make secure browsing the default for everyone.

At present, Chrome only displays a “Your connection is not private” message when a website’s HTTPS configuration is broken or misconfigured. However, this new update goes beyond that — it will alert users whenever they try to open any HTTP (non-HTTPS) website, emphasizing the risks of sharing personal data on unencrypted pages.

Google initially introduced optional warnings for insecure HTTP sites back in 2021, but users had to manually enable them. Over time, the adoption of HTTPS has skyrocketed — according to Google, between 95% and 99% of web traffic now takes place over secure HTTPS connections. This widespread adoption, the company says, “makes it possible to consider stronger mitigations against the remaining insecure HTTP.”

HTTPS, or Hypertext Transfer Protocol Secure, adds a layer of encryption that prevents malicious actors from intercepting or tampering with the information exchanged between users and websites. Without it, attackers can easily eavesdrop, inject malware, or steal sensitive data such as passwords and payment details.

In its official announcement, Google also highlighted that the largest contributor to insecure HTTP traffic comes from private websites — for example, internal business portals or personal web servers — as they often face challenges in obtaining HTTPS certificates. While these sites are “typically less dangerous than their public site counterparts,” Google cautions that HTTP navigation still poses potential risks.

Before the change applies to all users, Google plans to first roll it out to people who have Enhanced Safe Browsing enabled, starting in April 2026. This phased rollout will allow the company to monitor feedback and ensure a smooth transition. Chrome users will still retain control over their browsing experience — they can turn off these alerts by disabling the “Always Use Secure Connections” setting in the browser’s preferences.

This update reinforces Google’s long-term vision of making the internet fully encrypted and secure by default. With the vast majority of web traffic already protected, the company’s focus is now on phasing out the remaining insecure connections and encouraging all website owners to adopt HTTPS.

IBM’s 120-Qubit Quantum Breakthrough Edges Closer to Cracking Bitcoin Encryption

 

IBM has announced a major leap in quantum computing, moving the tech world a step closer to what many in crypto fear most—a machine capable of breaking Bitcoin’s encryption.

Earlier this month, IBM researchers revealed the creation of a 120-qubit entangled quantum state, marking the most advanced and stable demonstration of its kind so far.

Detailed in a paper titled “Big Cats: Entanglement in 120 Qubits and Beyond,” the study showcases genuine multipartite entanglement across all 120 qubits. This milestone is critical in the journey toward fault-tolerant quantum computers—machines powerful enough to run algorithms that could potentially outpace and even defeat modern cryptography.

“We seek to create a large entangled resource state on a quantum computer using a circuit whose noise is suppressed,” the researchers wrote. “We use techniques from graph theory, stabilizer groups, and circuit uncomputation to achieve this goal.”

This achievement comes amid fierce global competition in the quantum computing race. IBM’s progress surpasses Google Quantum AI’s 105-qubit Willow chip, which recently demonstrated a physics algorithm faster than any classical computer could simulate.

In the experiment, IBM scientists utilized Greenberger–Horne–Zeilinger (GHZ) states, also known as “cat states,” a nod to Schrödinger’s iconic thought experiment. In these states, every qubit exists simultaneously in superposition—both zero and one—and if one changes, all others follow, a phenomenon impossible in classical physics.

“Besides their practical utility, GHZ states have historically been used as a benchmark in various quantum platforms such as ions, superconductors, neutral atoms, and photons,” the researchers noted. “This arises from the fact that these states are extremely sensitive to imperfections in the experiment—indeed, they can be used to achieve quantum sensing at the Heisenberg limit.”

To reach the 120-qubit benchmark, IBM leveraged superconducting circuits and an adaptive compiler that directed operations to the least noisy regions of the chip. They also introduced a method called temporary uncomputation, where qubits that had completed their tasks were briefly disentangled to stabilize before being reconnected.

The performance was evaluated using fidelity, which measures how closely a quantum state matches its theoretical ideal. While a fidelity of 1.0 represents perfect accuracy and 0.5 marks confirmed full entanglement, IBM’s experiment achieved a score of 0.56, verifying that all qubits were coherently connected in one unified system.

Direct testing of such a vast quantum state is computationally unfeasible—it would take longer than the age of the universe to analyze every configuration. Instead, IBM used parity oscillation tests and Direct Fidelity Estimation, statistical techniques that sample subsets of the system to verify synchronization among qubits.

Although IBM’s current system does not yet threaten existing encryption, this progress pushes the boundary closer to a reality where quantum computers could challenge digital security, including Bitcoin’s defenses.

According to Project 11, a quantum research group, roughly 6.6 million BTC—worth about $767 billion—could be at risk from future quantum attacks. This includes coins believed to belong to Bitcoin’s creator, Satoshi Nakamoto.

“This is one of Bitcoin’s biggest controversies: what to do with Satoshi’s coins. You can’t move them, and Satoshi is presumably gone,” Project 11 founder Alex Pruden told Decrypt. “So what happens to that Bitcoin? It’s a significant portion of the supply. Do you burn it, redistribute it, or let a quantum computer get it? Those are the only options.”

Once a Bitcoin address’s public key becomes visible, a sufficiently powerful quantum system could, in theory, reconstruct it and take control of the funds before a transaction is confirmed. While IBM’s 120-qubit experiment cannot yet do this, it signals steady advancement toward that level of capability.

With IBM aiming for fault-tolerant quantum systems by 2030, and rivals like Google and Quantinuum pursuing the same goal, the quantum threat to digital assets is no longer a distant speculation—it’s a growing reality.

Privacy Laws Struggle to Keep Up with Meta’s ‘Luxury Surveillance’ Glasses


Meta’s newest smart glasses have reignited concerns about privacy, as many believe the company is inching toward a world where constant surveillance becomes ordinary. 

Introduced at Meta’s recent Connect event, the glasses reflect the kind of future that science fiction has long warned about, where everyone can record anyone at any moment and privacy nearly disappears. This is not the first time the tech industry has tried to make wearable cameras mainstream. 

More than ten years ago, Google launched Google Glass, which quickly became a public failure. People mocked its users as “Glassholes,” criticizing how easily the device could invade personal space. The backlash revealed that society was not ready for technology that quietly records others without their consent. 

Meta appears to have taken a different approach. By partnering with Ray-Ban, the company has created glasses that look fashionable and ordinary. Small cameras are placed near the nose bridge or along the outer rims, and a faint LED light is the only sign that recording is taking place. 

The glasses include a built-in display, voice-controlled artificial intelligence, and a wristband that lets the wearer start filming or livestreaming with a simple gesture. All recorded footage is instantly uploaded to Meta’s servers. 

Even with these improvements in design, the legal and ethical issues remain. Current privacy regulations are too outdated to deal with the challenges that come with such advanced wearable devices. 

Experts believe that social pressure and public disapproval may still be stronger than any law in discouraging misuse. As Meta promotes its vision of smart eyewear, critics warn that what is really being made normal is a culture of surveillance. 

The sleek design and luxury branding may make the technology more appealing, but the real risk lies in how easily people may accept being watched everywhere they go.

Tech Giants Pour Billions Into AI Race for Market Dominance

 

Tech giants are intensifying their investments in artificial intelligence, fueling an industry boom that has driven stock markets to unprecedented heights. Fresh earnings reports from Meta, Alphabet, and Microsoft underscore the immense sums being poured into AI infrastructure—from data centers to advanced chips—despite lingering doubts about the speed of returns.

Meta announced that its 2025 capital expenditures will range between $70 billion and $72 billion, slightly higher than its earlier forecast. The company also revealed plans for substantially larger spending growth in 2026 as it seeks to compete more aggressively with players like OpenAI.

During a call with analysts, CEO Mark Zuckerberg defended Meta’s aggressive investment strategy, emphasizing AI’s transformative potential in driving both new product development and enhancing its core advertising business. He described the firm’s infrastructure as operating in a “compute-starved” state and argued that accelerating spending was essential to unlocking future growth.

Alphabet, parent to Google and YouTube, also raised its annual capital spending outlook to between $91 billion and $93 billion—up from $85 billion earlier this year. This nearly doubles what the company spent in 2024 and highlights its determination to stay at the forefront of large-scale AI development.

Microsoft’s quarterly report similarly showcased its expanding investment efforts. The company disclosed $34.9 billion in capital expenditures through September 30, surpassing analyst expectations and climbing from $24 billion in the previous quarter. CEO Satya Nadella said Microsoft continues to ramp up AI spending in both infrastructure and talent to seize what he called a “massive opportunity.” He noted that Azure and the company’s broader portfolio of AI tools are already having tangible real-world effects.

Investor enthusiasm surrounding these bold AI commitments has helped lift the share prices of all three firms above the broader S&P 500 index. Still, Wall Street remains keenly interested in seeing whether these heavy capital outlays will translate into measurable profits.

Bank of America senior economist Aditya Bhave observed that robust consumer activity and AI-driven business investment have been the key pillars supporting U.S. economic resilience. As long as the latter remains strong, he said, it signals continued GDP growth. Despite an 83 percent profit drop for Meta due to a one-time tax charge, Microsoft and Alphabet reported profit increases of 12 percent and 33 percent, respectively.

AIjacking Threat Exposed: How Hackers Hijacked Microsoft’s Copilot Agent Without a Single Click

 

Imagine this — a customer service AI agent receives an email and, within seconds, secretly extracts your entire customer database and sends it to a hacker. No clicks, no downloads, no alerts.

Security researchers recently showcased this chilling scenario with a Microsoft Copilot Studio agent. The exploit worked through prompt injection, a manipulation technique where attackers hide malicious instructions in ordinary-looking text inputs.

As companies rush to integrate AI agents into customer service, analytics, and software development, they’re opening up new risks that traditional cybersecurity tools can’t fully protect against. For developers and data teams, understanding AIjacking — the hijacking of AI systems through deceptive prompts — has become crucial.

In simple terms, AIjacking occurs when attackers use natural language to trick AI systems into executing commands that bypass their programmed restrictions. These malicious prompts can be buried in anything the AI reads — an email, a chat message, a document — and the system can’t reliably tell the difference between a real instruction and a hidden attack.

Unlike conventional hacks that exploit software bugs, AIjacking leverages the very nature of large language models. These models follow contextual language instructions — whether those instructions come from a legitimate user or a hacker.

The Microsoft Copilot Studio incident illustrates the stakes clearly. Researchers sent emails embedded with hidden prompt injections to an AI-powered customer service agent that had CRM access. Once the agent read the emails, it followed the instructions, extracted sensitive data, and emailed it back to the attacker — all autonomously. This was a true zero-click exploit.

Traditional cyberattacks often rely on tricking users into clicking malicious links or opening dangerous attachments. AIjacking requires no such action — the AI processes inputs automatically, which is both its greatest strength and its biggest vulnerability.

Old-school defenses like firewalls, antivirus software, and input validation protect against code-level threats like SQL injection or XSS attacks. But AIjacking is a different beast — it targets the language understanding capability itself, not the code.

Because malicious prompts can be written in infinite variations — in different tones, formats, or even languages — it’s impossible to build a simple “bad input” blacklist that prevents all attacks.

When Microsoft fixed the Copilot Studio flaw, they added prompt injection classifiers, but these have limitations. Block one phrasing, and attackers simply reword their prompts.

AI agents are typically granted broad permissions to perform useful tasks — querying databases, sending emails, and calling APIs. But when hijacked, those same permissions become a weapon, allowing the agent to carry out unauthorized operations in seconds.

Security tools can’t easily detect a well-crafted malicious prompt that looks like normal text. Antivirus programs don’t recognize adversarial inputs that exploit AI behavior. What’s needed are new defense strategies tailored to AI systems.

The biggest risk lies in data exfiltration. In Microsoft’s test, the hijacked AI extracted entire customer records from the CRM. Scaled up, that could mean millions of records lost in moments.

Beyond data theft, hijacked agents could send fake emails from your company, initiate fraudulent transactions, or abuse APIs — all using legitimate credentials. Because the AI acts within its normal permissions, the attack is almost indistinguishable from authorized activity.

Privilege escalation amplifies the damage. Since most AI agents need elevated access — for instance, customer service bots read user data, while dev assistants access codebases — a single hijack can expose multiple internal systems.

Many organizations wrongly assume that existing cybersecurity systems already protect them. But prompt injection bypasses these controls entirely. Any text input the AI processes can serve as an attack vector.

To defend against AIjacking, a multi-layered security strategy is essential:

  1. Input validation & authentication: Don’t let AI agents auto-respond to unverified external inputs. Only allow trusted senders and authenticated users.
  2. Least privilege access: Give agents only the permissions necessary for their task — never full database or write access unless essential.
  3. Human-in-the-loop approval: Require manual confirmation before agents perform sensitive tasks like large data exports or financial transactions.
  4. Logging & monitoring: Track agent behavior and flag unusual actions, such as accessing large volumes of data or contacting new external addresses.
  5. System design & isolation: Keep AI agents away from production databases, use read-only replicas, and apply rate limits to contain damage.

Security testing should also include adversarial prompt testing, where developers actively try to manipulate the AI to find weaknesses before attackers do.

AIjacking marks a new era in cybersecurity. It’s not hypothetical — it’s happening now. But layered defense strategies — from input authentication to human oversight — can help organizations deploy AI safely. Those who take action now will be better equipped to protect both their systems and their users.

Video Game Studios Exploit Legal Rights of Children


A study revealed that video game studios are openly ignoring legal systems and abusing the data information and privacy of the children who play these videogames.

Videogame developers discarding legal rights of children 

Researchers found that highly opaque frameworks of data collection in the intense lucrative video game market run by third-party companies and developers showed malicious intent. The major players freely discard children's rights to store personal data via game apps. Video game studios ask parents to accept privacy policies that are difficult to understand and also contradictory at times. 

Quagmire of videos games privacy laws

Their legality is doubtful. Video game studios are thriving on the fact that parents won't take the time to read these privacy laws carefully, and in case if they do, they still won't be able to complain because of the complexity of policies. 

Experts studied the privacy frameworks of video games for children aged below 13 (below 14 in Quebec) in comparison to legal laws in the US, Quebec, and Canada. 

Conclusion 

The research reveals an immediate need for government agencies to implement legal frameworks and predict when potential legal issues for video game developers can surface. In Quebec, a class action lawsuit has already been filled against the mobile gaming industry for violating children's privacy rights.

Need for robust legal systems 

Since there is a genuine need for legislative involvement to control studio operations, this investigation may result in legal action against studios whose abusive practices have been revealed as well as legal reforms. 

 Self-regulation by industry participants (studios and classification agencies) is ineffective since it fails to safeguard children's data rights. Not only do parents and kids lack the knowledge necessary to give unequivocal consent, but inaccurate information also gives them a false sense of security, especially if the game seems harmless and childlike.

Why Ransomware Attacks Keep Rising and What Makes Them Unstoppable


In August, Jaguar Land Rover (JLR) suffered a cyberattack. JLR employs over 32,800 people and provides additional 104,000 jobs via it's supply chain. JLR is the recent victim in a chain of ransomware attacks. 

Why such attacks?

Our world is entirely dependent on technology which are prone to attacks. Only a few people understand such complex infrastructure. The internet is built to be easy, and this makes it vulnerable. The first big cyberattack happened in 1988. That time, not many people knew about it. 

The more we rely on networked computer technology, the more we become exposed to attacks and ransomware extortion.

How such attacks happen?

There are various ways of hacking or disrupting a network. Threat actors get direct access through software bugs, they can access unprotected systems and leverage them as a zombie army called "botnet," to disrupt a network.

Currently, we are experiencing a wave of ransomware attacks. First, threat actors hack into a network, they may pretend to be an employee. They do this via phishing emails or social engineering attacks. After this, they increase their access and steal sensitive data for extortion reasons. By this, hackers gain control and assert dominance.

These days, "hypervisor" has become a favourite target. It is a server computer that lets many remote systems to use just one system (like work from home). Hackers then use ransomware to encode data, which makes the entire system unstable and it becomes impossible to restore the data without paying the ransom for a decoding key.

Why constant rise in attacks?

A major reason is a sudden rise in cryptocurrencies. It has made money laundering easier. In 2023, a record $1.1 billion was paid out across the world. Crypto also makes it easier to buy illegal things on the dark web. Another reason is the rise of ransomware as a service (RaaS) groups. This business model has made cyberattacks easier for beginner hackers 

About RaaS

RaaS groups market on dark web and go by the names like LockBit, REvil, Hive, and Darkside sell tech support services for ransomware attack. For a monthly fees, they provide a payment portal, encryption softwares, and a standalone leak site for blackmailing the victims, and also assist in ransom negotiations.


IPv6: The Future of the Internet That’s Quietly Already Here

 

IPv6 was once envisioned as the next great leap for the internet — a future-proof upgrade designed to solve IP address shortages, simplify networks, and make online connections faster and more secure. Yet, decades later, most of the world still runs on IPv4. So, what really happened?

Every device that connects to the internet needs a unique identifier known as an IP address — essentially a digital address that tells other devices where to send data. When you visit a website, your device sends a request to a server’s IP address, and that server sends information back to yours. Without IP addresses, the web simply wouldn’t function.

“IP” stands for Internet Protocol, and the numbers “v4” and “v6” refer to its versions. IPv4 has been the backbone of the internet since its early days, but it’s running out of space. The IPv4 system uses a 32-bit structure, allowing for about 4.3 billion unique addresses — a number that seemed vast in the 1980s but quickly fell short as smartphones, laptops, routers, and even smart home devices came online.

To solve this, IPv6 was introduced. Using a 128-bit system, IPv6 offers an almost limitless supply of addresses — around 340 undecillion (that’s 340 followed by 36 zeros). But IPv6 wasn’t just about more numbers. It also brought smarter features like automatic device configuration, stronger encryption, and improved routing efficiency.

However, switching from IPv4 to IPv6 was far from simple. The two systems can’t communicate directly, meaning the entire internet — from ISPs to data centers — needed new configurations and equipment capable of handling both versions in a setup called “dual-stack networking.” This approach allowed both protocols to run side by side, but it was costly and complex to implement.

Many organizations hesitated to upgrade. Since IPv4 still worked, and technologies like NAT (Network Address Translation) allowed multiple devices to share one address, there wasn’t an immediate need to move away from it. For years, IPv6 adoption remained stuck in the single digits.

That’s slowly changed. Today, according to Google’s IPv6 adoption statistics, nearly 45% of global users connect using IPv6, especially through mobile networks. Major companies like Google, Meta, Microsoft, Netflix, and Cloudflare have been IPv6-ready for years, ensuring most users are already using it — often without realizing it.

In fact, IPv6 is quietly running in the background for most people. Modern smartphones, broadband connections, and cloud services already use it, managed automatically by routers and ISPs. Thanks to dual-stack networking, users rarely notice which version they’re on.

This has created a unique moment: we’re living in two internets at once. IPv4 continues to support older systems and legacy infrastructure, while IPv6 powers the growing digital world — silently, efficiently, and almost invisibly. IPv4 isn’t disappearing anytime soon, but IPv6 isn’t a failure either. It’s the quiet successor, steadily ensuring the internet keeps expanding for the billions of new devices still to come.

Is ChatGPT's Atlas Browser the Future of Internet?

Is ChatGPT's Atlas Browser the Future of Internet?

After using ChatGPT Atlas, OpenAI's new web browser, users may notice few issues. This is not the same as Google Chrome, which about 60% of users use. It is based on a chatbot that you are supposed to converse with in order to browse the internet.  

One of the notes said, "Messages limit reached," "No models that are currently available support the tools in use," another stated.  

Following that: "You've hit the free plan limit for GPT-5."  

Paid browser 

According to OpenAI, it will simplify and improve internet usage. One more step toward becoming "a true super-assistant." Super or not, however, assistants are not free, and the corporation must start generating significantly more revenue from its 800 million customers.

According to OpenAI, Atlas allows us to "rethink what it means to use the web". It appears to be comparable to Chrome or Apple's Safari at first glance, with one major exception: a sidebar chatbot. These are early days, but there is the potential for significant changes in how we use the Internet. What is certain is that this will be a high-end gadget that will only function properly if you pay a monthly subscription price. Given how accustomed we are to free internet access, many people would have to drastically change their routines.

Competitors, data, and money

The founding objective of OpenAI was to achieve artificial general intelligence (AGI), which roughly translates to AI that can match human intelligence. So, how does a browser assist with this mission? It actually doesn't. However, it has the potential to increase revenue. The company has persuaded venture capitalists and investors to spend billions of dollars in it, and it must now demonstrate a return on that investment. In other words, it needs to generate revenue. However, obtaining funds through typical internet advertising may be risky. Atlas might also grant the corporation access to a large amount of user data.

The ultimate goal of these AI systems is scale; the more data you feed them, the better they will become. The web is built for humans to use, so if Atlas can observe how we order train tickets, for example, it will be able to learn how to better traverse these processes.  

Will it kill Google?

Then we get to compete. Google Chrome is so prevalent that authorities throughout the world are raising their eyebrows and using terms like "monopoly" to describe it. It will not be easy to break into that market.

Google's Gemini AI is now integrated into the search engine, and Microsoft has included Copilot to its Edge browser. Some called ChatGPT the "Google killer" in its early days, predicting that it would render online search as we know it obsolete. It remains to be seen whether enough people are prepared to pay for that added convenience, and there is still a long way to go before Google is dethroned.

Deepfakes Are More Polluting Than People Think

 


Artificial intelligence, while blurring the lines between imagination and reality, is causing a new digital controversy to unfold at a time when ethics and creativity have become less important and the digital realm has become a much more fluid one. 

With the advent of advanced artificial intelligence platforms such as OpenAI's Sora, deepfake videos have been able to flood social media feeds with astoundingly lifelike representations of celebrities and historic figures, resurrected in scenes that at times appear sensational but at other times are deeply offensive, thanks to advanced artificial intelligence platforms.

In fact, the phenomenon has caused widespread concern amongst families of revered personalities such as Dr Martin Luther King Jr. Several people are publicly urging technology companies to put more safeguards in place to prevent the unauthorised use of their loved ones' likenesses.

However, as the debate over the ethical boundaries of synthetic media intensifies, there is one hidden aspect of the issue that is quietly surfacing, namely, the hidden environmental impact that synthetic media has on the environment. 

The creation of these hyperrealistic videos requires a great deal of computational power, as explained by Dr Kevin Grecksch, a professor at the University of Oxford. They also require a substantial amount of energy and water to maintain the necessary cooling systems within the data centres. Despite appearing as a fleeting piece of digital art, it has a significant environmental cost hidden beneath it, adding an unexpected layer of concerns surrounding the digital revolution that is a growing concern. 

As social media platforms have grown, there has been an increasing prevalence of deepfake videos, whose uncanny realism has captured audiences while blurring the line between truth and fabrication, while also captivating them. 

As AI-powered tools such as OpenAI's Sora have become more widely available, these videos have become viral as a result of being able to conjure up lifelike portraits of individuals – some of whom have long passed away – into fabricated scenes that range from bizarre to deeply inappropriate in nature. 

Several families who have been portrayed in this disturbing trend, including that of Dr Martin Luther King Jr., have raised alarm over the trend and have called on technology companies to prevent unauthorised digital resurrections of their loved ones. However, there is much more to the controversy surrounding deepfakes than just issues of dignity and consent at play. 

Despite the convincingly rendered nature of these videos, Dr Kevin Grecksch, a lecturer at Oxford University, has stressed that these videos have a significant ecological impact that is often overlooked. Generating such content is dependent upon the installation of powerful data centres that consume vast amounts of electricity and water to cool, resources that contribute substantially to the growing environmental footprint of this technology on a large scale. 

It has emerged that deep fakes, a form of synthetic media that is rapidly advancing, are one of the most striking examples of how artificial intelligence is reshaping digital communication. By combining complex deep learning algorithms with a massive dataset, these technologies can convincingly replace or manipulate faces, voices, and even gestures with ease. 

The likeness of one person is seamlessly merged with the likeness of another, creating a seamless transition from one image to the next. Additionally, shallow fakes, which are less technologically complex but equally important, are also closely related, but they rely on simple editing techniques to distort reality to an alarming degree, blurring the line between authenticity and fabrication. The proliferation of deepfakes has accelerated rapidly at an unprecedented pace over the past few years. 

A new report suggests that the number of such videos that circulate online has doubled every six months. It is estimated that there will be 500,000 deepfake videos and audio clips being shared globally by 2023, and if current trends hold true, this number is expected to reach almost 8 million by 2025. Using advanced artificial intelligence tools and the availability of publicly available data, experts attribute this explosive growth to the fact that these tools are widely accessible and there is a tremendous amount of public data, which creates an ideal environment for manipulated media to flourish. 

As a result of the rise of deepfake technology, legal and policy circles have been riddled with intense debate, underscoring the urgency of redefining the boundaries of accountability in an era in which synthetic media is so prevalent. With hyper-realistic digital forgeries created by advanced deep learning algorithms, which are very realistic, it poses a complex challenge that goes well beyond the technological edge. 

Legal scholars have warned that deep fakes pose a significant threat to privacy, intellectual property, and dignity, while also undermining public trust in the information they provide. A growing body of evidence suggests that these fabrications may carry severe social, ethical, and legal consequences not only from their ability to mislead but also from their ability to influence electoral outcomes and facilitate non-consensual pornography, all of which carry severe social, ethical, and legal consequences. 

In an effort to contain the threat, the European Union is enforcing legislation such as its Artificial Intelligence Act and Digital Services Act, which aim to assign responsibility for large online platforms and establish standards for the governance of Artificial Intelligence. Even so, experts contend that such initiatives remain insufficient due to the absence of comprehensive definitions, enforcement mechanisms, and protocols for assisting victims. 

Moreover, the situation is compounded by a fragmented international approach: although many states in the United States have enacted laws addressing fake media, there are still inconsistencies across jurisdictions, and countries like Canada continue to face challenges in regulating deepfake pornography and other forms of synthetic nonconsensual media. 

Social media has become an increasingly important platform for spreading manipulated media, which in turn increases these risks. Scholars have advocated sweeping reforms, which range from stricter privacy laws to recalibrating free speech to preemptive restrictions on deepfake generation, to mitigate future damage that is likely to occur. This includes identity theft, fraud, and other harms that existing legal systems are incapable of dealing with. 

It is important to note that ethical concerns are also emerging outside of the policy arena, in unexpected circumstances, such as the use of deep fakes in grief therapy and entertainment, where the line between emotional comfort and manipulation becomes dangerously blurred during times of emotional distress. 

The researchers, who are calling for better detection and prevention frameworks, are reaching a common conclusion: ideepfakes must be regulated in a manner that strikes a delicate balance between innovation and protection, ensuring that technological advances do not take away truth, justice, or human dignity as a result. This era of synthetic media has provoked a heated debate within legal and policy circles concerning the rise of deepfake technology, emphasising the importance of redefining the boundaries of accountability in a world where deep fakes have become a common phenomenon.

The hyper-realistic digital forgeries produced by advanced deep learning algorithms pose a challenge that goes well beyond the novelty of technology. There is considerable concern that deepfakes may threaten the integrity of information, as well as undermine public trust in it, while also undermining the core principles of privacy, intellectual property, and personal dignity. 

As a result of the fabrications' ability to distort reality, it has already been reported that they are capable of spreading misinformation, influencing elections, and facilitating nonconsensual pornography, all of which can have serious social, ethical, and legal repercussions. In an effort to contain the threat, the European Union is enforcing legislation such as its Artificial Intelligence Act and Digital Services Act, which aim to assign responsibility for large online platforms and establish standards for the governance of Artificial Intelligence.

Even so, experts contend that such initiatives remain insufficient due to the absence of comprehensive definitions, enforcement mechanisms, and protocols for assisting victims. Inconsistencies persist across jurisdictions, which further complicates the situation. While some U.S. states have enacted laws to address false media, there are still inconsistencies across jurisdictions, and countries such as Canada are still struggling with how to regulate non-consensual synthetic materials, including deepfake pornography and other forms of pseudo-synthetic material. 

Social media has become an increasingly important platform for spreading manipulated media, which in turn increases these risks. Scholars have advocated sweeping reforms, which range from stricter privacy laws to recalibrating free speech to preemptive restrictions on deepfake generation, to mitigate future damage that is likely to occur. This includes identity theft, fraud, and other harms that existing legal systems are incapable of dealing with. 

Additionally, ethical concerns are emerging beyond the realm of policy as well, in unexpected contexts such as those regarding deepfakes' use in grief therapy and entertainment, where the line between emotional comfort and manipulative behaviours becomes a dangerous blur to the point of becoming dangerously indistinguishable. 

Research suggests that more robust detection and prevention frameworks are needed to detect and prevent deepfakes. One conclusion becomes increasingly evident as a result of these findings: the regulation of deepfakes requires a delicate balance between innovation and protection, so that progress in technology does not trample upon truth, justice, and human dignity in its wake. 

A growing number of video generation tools powered by artificial intelligence have become so popular that they have transformed online content creation, but have also raised serious concerns about the environmental consequences of these tools. Data centres are the vast digital backbones that make such technologies possible, and they use large quantities of electricity and fresh water to cool servers on a large scale. 

The development of applications like OpenAI’s Sora has made it easy for users to create and share hyperrealistic videos quickly, but social media platforms have also seen an increase in deepfake content, which has helped such apps rise to the top of the global download charts. Within just five days, Sora had over one million downloads within just five days, cementing its position as the dominant app in the US Apple App Store. 

In the midst of this surge of creative enthusiasm, however, there is a growing environmental dilemma that has been identified by DDrKevin Grecksch of the University of Oxford in his recently published warning against ignoring the water and energy demands of AI infrastructure. He urged users and policymakers alike to be aware that digital innovation has a significant ecological footprint, and that it takes a lot of water to carry out, and that it needs to be carefully considered when using water. 

It has been argued that the "cat is out of the sack" with the adoption of artificial intelligence, but that more integrated planning is imperative when it comes to determining where and how data-centric systems should be built and cooled. 

A warning he made was that even though the government envisions South Oxfordshire as a potential hub for the development of artificial intelligence, insufficient attention has been paid to the environmental logistics, particularly where the necessary water supply will come from. Since enthusiasm for the development of generative technologies continues to surge, experts insist that the conversation regarding the future of AI needs to go beyond innovation and efficiency, encompassing sustainability, resource management, and long-term environmental responsibility. 

There is no denying that the future of artificial intelligence demands more than admiration for its brilliance as it stands at a crossroads between innovation and accountability, but responsibility as to how it is applied. Even though deepfake technology is a testament to human ingenuity, it should be governed by ethics, regulation, and sustainability, as well as other factors.

There is a need to collaborate between policymakers, technology firms, and environmental authorities in order to develop frameworks which protect both digital integrity as well as natural resources. For a safer and more transparent digital era, we must encourage the use of renewdatacentresin datacentress, enforce stricter consent-based media laws, and invest in deepfake detection systems in order to ensure that deepfake detection systems are utilised. 

AI offers the promise of creating a world without human intervention, yet its promise lies in our capacity to control its outcomes - ensuring that in a world increasingly characterised by artificial intelligence, progress remains a force for truth, equity, and ecological balance.