#FactCheck - Viral Video of Aircraft Carrier Destroyed in Sea Storm Is AI-Generated

Introduction

The mysteries of the universe have been a subject of curiosity for humans over thousands of years. To solve these unfolding mysteries of the universe, astrophysicists are always busy, and with the growing technology this seems to be achievable. Recently, with the help of Artificial Intelligence (AI), scientists have discovered the depths of the cosmos. AI has revealed the secret equation that properly “weighs” galaxy clusters. This groundbreaking discovery not only sheds light on the formation and behavior of these clusters but also marks a turning point in the investigation and discoveries of new cosmos. Scientists and AI have collaborated to uncover an astounding 430,000 galaxies strewn throughout the cosmos. The large haul includes 30,000 ring galaxies, which are considered the most unusual of all galaxy forms. The discoveries are the first outcomes of the "GALAXY CRUISE" citizen science initiative. They were given by 10,000 volunteers who sifted through data from the Subaru Telescope. After training the AI on 20,000 human-classified galaxies, scientists released it loose on 700,000 galaxies from the Subaru data. 

Brief Analysis

A group of astronomers from the National Astronomical Observatory of Japan (NAOJ) have successfully applied AI to ultra-wide field-of-view images captured by the Subaru Telescope. The researchers achieved a high accuracy rate in finding and classifying spiral galaxies, with the technique being used alongside citizen science for future discoveries.

Astronomers are increasingly using AI to analyse and clean raw astronomical images for scientific research. This involves feeding photos of galaxies into neural network algorithms, which can identify patterns in real data more quickly and less prone to error than manual classification. These networks have numerous interconnected nodes and can recognise patterns, with algorithms now 98% accurate in categorising galaxies.

Another application of AI is to explore the nature of the universe, particularly dark matter and dark energy, which make up over 95% energy of the universe. The quantity and changes in these elements have significant implications for everything from galaxy arrangement.

AI is capable of analysing massive amounts of data, as training data for dark matter and energy comes from complex computer simulations. The neural network is fed these findings to learn about the changing parameters of the universe, allowing cosmologists to target the network towards actual data.

These methods are becoming increasingly important as astronomical observatories generate enormous amounts of data. High-resolution photographs of the sky will be produced from over 60 petabytes of raw data by the Vera C. AI-assisted computers are being utilized for this.

Data annotation techniques for training neural networks include simple tagging and more advanced types like image classification, which classify an image to understand it as a whole. More advanced data annotation methods, such as semantic segmentation, involve grouping an image into clusters and giving each cluster a label.

This way, AI is being used for space exploration and is becoming a crucial tool. It also enables the processing and analysis of vast amounts of data. This advanced technology is fostering the understanding of the universe. However, clear policy guidelines and ethical use of technology should be prioritized while harnessing the true potential of contemporary technology. 

Policy Recommendation

• Real-Time Data Sharing and Collaboration - Effective policies and frameworks should be established to promote real-time data sharing among astronomers, AI developers and research institutes. Open access to astronomical data should be encouraged to facilitate better innovation and bolster the application of AI in space exploration. 
  

• Ethical AI Use - Proper guidelines and a well-structured ethical framework can facilitate judicious AI use in space exploration. The framework can play a critical role in addressing AI issues pertaining to data privacy, AI Algorithm bias and transparent decision-making processes involving AI-based tech. 
• Investing in Research and Development (R&D) in the AI sector - Government and corporate giants should prioritise this opportunity to capitalise on the avenue of AI R&D in the field of space tech and exploration. Such as funding initiatives focusing on developing AI algorithms coded for processing astronomical data, optimising telescope operations and detecting celestial bodies.
• Citizen Science and Public Engagement - Promotion of citizen science initiatives can allow better leverage of AI tools to involve the public in astronomical research. Prominent examples include the SETI @ Home program (Search for Extraterrestrial Intelligence), encouraging better outreach to educate and engage citizens in AI-enabled discovery programs such as the identification of exoplanets, classification of galaxies and discovery of life beyond earth through detecting anomalies in radio waves. 
• Education and Training - Training programs should be implemented to educate astronomers in AI techniques and the intricacies of data science. There is a need to foster collaboration between AI experts, data scientists and astronomers to harness the full potential of AI in space exploration. 
• Bolster Computing Infrastructure - Authorities should ensure proper computing infrastructure should be implemented to facilitate better application of AI in astronomy. This further calls for greater investment in high-performance computing devices and structures to process large amounts of data and AI modelling to analyze astronomical data. 

Conclusion

AI has seen an expansive growth in the field of space exploration. As seen, its multifaceted use cases include discovering new galaxies and classifying celestial objects by analyzing the changing parameters of outer space. Nevertheless, to fully harness its potential, robust policy and regulatory initiatives are required to bolster real-time data sharing not just within the scientific community but also between nations. Policy considerations such as investment in research, promoting citizen scientific initiatives and ensuring education and funding for astronomers. A critical aspect is improving key computing infrastructure, which is crucial for processing the vast amount of data generated by astronomical observatories. 

References

• https://mindy-support.com/news-post/astronomers-are-using-ai-to-make-discoveries/
• https://www.space.com/citizen-scientists-artificial-intelligence-galaxy-discovery
• https://www.sciencedaily.com/releases/2024/03/240325114118.htm
• https://phys.org/news/2023-03-artificial-intelligence-secret-equation-galaxy.html
• https://www.space.com/astronomy-research-ai-future

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Introduction 

In a major policy shift aimed at synchronizing India's fight against cyber-enabled financial crimes, the government has taken a landmark step by bringing the Indian Cyber Crime Coordination Centre (I4C) under the ambit of the Prevention of Money Laundering Act (PMLA). In the notification released in the official gazette on 25th April, 2025, the Department of Revenue, Ministry of Finance, included the Indian Cyber Crime Coordination Centre (I4C) under Section 66 of the Prevention of Money Laundering Act, 2002 (hereinafter referred to as “PMLA”). The step comes as a significant attempt to resolve the asynchronous approach of different agencies (Enforcement Directorate (ED), State Police, CBI, CERT-In, RBI) set up under the government responsible for preventing and often possessing key information regarding cyber crimes and financial crimes. As it is correctly put, "When criminals sprint and the administration strolls, the finish line is lost.” 

The gazetted notification dated 25th April, 2025, read as follows:

“In exercise of the powers conferred by clause (ii) of sub-section (1) of section 66 of the Prevention of Money-laundering Act, 2002 (15 of 2003), the Central Government, on being satisfied that it is necessary in the public interest to do so, hereby makes the following further amendment in the notification of the Government of India, in the Ministry of Finance, Department of Revenue, published in the Gazette of India, Extraordinary, Part II, section 3, sub-section (i) vide number G.S.R. 381(E), dated the 27th June, 2006, namely:- In the said notification, after serial number (26) and the entry relating thereto, the following serial number and entry shall be inserted, namely:— “(27) Indian Cyber Crime Coordination Centre (I4C).”.

Outrunning Crime: Strengthening Enforcement through Rapid Coordination 

The usage of cyberspace to commit sophisticated financial crimes and white-collar crimes is a one criminal parallel passover that no one was looking forward to. The disenchanted reality of today’s world is that the internet is used for as much bad as it is for good. The internet has now entered the financial domain, facilitating various financial crimes. Money laundering is a financial crime that includes all processes or activities that are in connection with the concealment, possession, acquisition, or use of proceeds of crime and projecting it as untainted money. In the offence of money laundering, there is an intricate web and trail of financial transactions that are hard to track, as they are, and with the advent of the internet, the transactions are often digital, and the absence of crucial information hampers the evidentiary chain. With this new step, the Enforcement Directorate (ED) will now make headway into the investigation with the information exchange under PMLA from and to I4C, removing the obstacles that existed before this notification.

Impact

The decision of the finance ministry has to be seen in terms of all that is happening around the globe, with the rapid increase in sophisticated financial crimes. By formally empowering the I4C to share and receive information with the Enforcement Directorate under PMLA, the government acknowledges the blurred lines between conventional financial crime and cybercrime. It strengthens India’s financial surveillance, where money laundering and cyber fraud are increasingly two sides of the same coin. The assessment of the impact can be made from the following facilitations enabled by the decision: 

• Quicker internet detection of money laundering
• Money trail tracking in real time across online platforms
• Rapid freeze of cryptocurrency wallets or assets obtained fraudulently

Another important aspect of this decision is that it serves as a signal that India is finally equipping itself and treating cyber-enabled financial crimes with the gravitas that is the need of the hour. This decision creates a two-way intelligence flow between cybercrime detection units and financial enforcement agencies. 

Conclusion

To counter the fragmented approach in handling cyber-enabled white-collar crimes and money laundering, the Indian government has fortified its legal and enforcement framework by extending PMLA’s reach to the Indian Cyber Crime Coordination Centre (I4C). All the decisions and the brainstorming that led up to this notification are crucial at this point in time for the cybercrime framework that India needs to be on par with other countries. Although India has come a long way in designing a robust cybercrime intelligence structure, as long as it excludes and works in isolation, it will be ineffective. So, the current decision in discussion should only be the beginning of a more comprehensive policy evolution. The government must further integrate and devise a separate mechanism to track “digital footprints” and incorporate a real-time red flag mechanism in digital transactions suspected to be linked to laundering or fraud. 

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Introduction

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Fundamentally, artificial intelligence (AI) is the greatest extension of human intelligence. It is the culmination of centuries of logic, reasoning, math, and creativity, machines trained to reflect cognition. However, such intelligence no longer resembles intelligence at all when it is put in the hands of the irresponsible, the one with malice, or the perverse, unleashed into the wild with minimal safeguards. Instead, distortion seems as a tool of debasement rather than enlightenment. 

Recent incidents involving sexually explicit photographs created by AI on social media sites reveal an extremely unsettling reality. When intelligence is detached from accountability, morality, and governance, it corrodes society rather than elevates it. We are seeing a failure of stewardship rather than just a failure of technology.

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The Cost of Unchecked Intelligence

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The AI chatbot Grok, which operates under Elon Musk’s X (formerly Twitter), is the subject of a debate that goes beyond a single platform or product. The romanticisation of “unfiltered” knowledge and the perilous notion that innovation should come before accountability are signs of a bigger lapse in the digital ecosystem. We have allowed mechanisms that can be used as weapons against human dignity, especially the dignity of women and children, in the name of freedom. 

We are no longer discussing artistic expression or experimental AI when a machine can digitally undress women, morph photos, or produce sexualised portrayals of kids with a few keystrokes. We stand in the face of algorithmic violence. Even if the physical touch is absent, the harm caused by it is genuine, long-lasting, and extremely personal. 

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The Regulatory Red Line

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A major inflexion was reached when the Indian government responded by ordering a thorough technical, procedural, and governance-level audit. It acknowledges that AI systems are not isolated entities. Platforms that use them are not neutral pipes, but rather intermediaries with responsibilities. The Bhartiya Nyay Sanhita, the IT Act, the IT Rules 2021, and the possible removal of Section 79 safe-harbour safeguards all make it quite evident that innovation is not automatic immunity.

However, the fundamental dilemma cannot be resolved by legislation alone. AI is hailed as a force multiplier for innovation, productivity, and advancement, but when incentives are biased towards engagement, virality, and shock value, its misuse shows how easily intelligence can turn into ugliness. The output receives greater attention the more provocative it is. Profit increases with attention. Restraint turns into a business disadvantage in this ecology. 

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The Aftermath

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Grok’s own acknowledgement that “safeguard lapses” enabled the creation of pictures showing children wearing skimpy attire underscores a troubling reality, safety was not absent due to impossibility, but due to insufficiency. It was always possible to implement sophisticated filtering, more robust monitoring, and stricter oversight. They were simply not prioritised. When a system asserts that “no system is 100% foolproof,” it must also acknowledge that there is no acceptable margin of error when it comes to child protection.

The casual normalisation of such lapses is what is most troubling. By characterising these instances as “isolated cases,” systemic design decisions run the risk of being trivialised. In addition to intelligence, AI systems that have been taught on enormous amounts of human data also inherit bias, misogyny, and power imbalances. 

Conclusion

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What is required today is recalibration. Platforms need to shift from reactive compliance to proactive accountability. Safeguards must be incorporated at the architectural level; they cannot be cosmetic or post-facto. Governance must encompass enforced ethical boundaries in addition to terms of service. The idea that “edgy” AI is a sign of advancement must also be rejected by society.

Artificial Intelligence has never promised freedom under the guise of vulgarity. It was improvement, support, and augmentation. The fundamental core of intelligence is lost when it is used as a tool for degradation.So what’s left is a decision between principled innovation and unbridled novelty. Between responsibility and spectacle, between intelligence as purpose and intellect as power. 

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References

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https://www.rediff.com/news/report/govt-orders-x-review-of-grok-over-explicit-content/20260103.htm