#FactCheck: Viral Deepfake Video of Modi, Shah, Jaishankar Apologize for Operation Sindoor Blunder

Executive Summary:

A viral claim circulated in social media that Anant Ambani and Radhika Merchant wore clothes made of pure gold during their pre-wedding cruise party in Europe.  Thorough analysis revealed abnormalities in image quality, particularly between the face, neck, and hands compared to the claimed gold clothing, leads to possible AI manipulation. A keyword search found no credible news reports or authentic images supporting this claim. Further analysis using AI detection tools, TrueMedia and Hive Moderator, confirmed substantial evidence of AI fabrication, with a high probability of the image being AI-generated or a deep fake. Additionally, a photo from a previous event at Jio World Plaza matched with the pose of the manipulated image, further denying the claim and indicating that the image of Anant Ambani and Radhika Merchant wearing golden outfit during their pre-wedding cruise was digitally altered.

Claims:

Anant Ambani and Radhika Merchant wore clothes made of pure gold during their pre-wedding cruise party in Europe.

Fact Check:

When we received the posts, we found anomalies that were usually found in edited images or AI manipulated images, particularly between the face, neck, and hands.

It’s very unusual in any image. So we then checked in AI Image detection software named Hive Moderation detection tool and found it to be 95.9% AI manipulated.

We also checked with another widely used AI detection tool named True Media. True Media also found it to be 100% to be made using AI.

This implies that the image is AI-generated. To find the original image that has been edited, we did keyword search. We found an image with the same pose as in the manipulated image, with the title "Radhika Merchant, Anant Ambani pose with Mukesh Ambani at Jio World Plaza opening”.  The two images can be compared to verify that the digitally altered image is the same.

Hence, it’s confirmed that the viral image is digitally altered and has no connection with the 2nd Pre-wedding cruise party in Europe.  Thus the viral image is fake and misleading.

Conclusion:

The claim that Anant Ambani and Radhika Merchant wore clothes made of pure gold at their pre-wedding cruise party in Europe is false. The analysis of the image showed signs of manipulation, and a lack of credible news reports or authentic photos supports that it was likely digitally altered. AI detection tools confirmed a high probability that the image was fake, and a comparison with a genuine photo from another event revealed that the image had been edited. Therefore, the claim is false and misleading.

• Claim:  Anant Ambani and Radhika Merchant wore clothes made of pure gold during their pre-wedding cruise party in Europe.
• Claimed on: YouTube, LinkedIn, Instagram
• Fact Check: Fake & Misleading

Introduction

The Ministry of Electronics and Information Technology ( MeitY) through its Information Security Education & Awareness ( ISEA ) came up with an advisory regarding the growing cases of e-challan fraud. Cybercriminals are exploiting the beliefs of individuals by attracting them into clicking malicious links under the impression of paying traffic fines. Cybercriminals employ sending phishing messages and impersonating official e-challan notifications as a primary method. These messages are crafted in such a way that portrays a sense of urgency, provoking individuals to click on a link for spontaneous payment. For building trust, the messages are deviously created by scammers depicting official communication, which in actuality are fake messages targeting individuals for committing online financial fraud.

Unveiling the E-Challan Scam

Scammers send a text message to your phones that closely resembles e-challan alerts. The text appears from the traffic police, informing the netizens of a traffic violation that requires a fine payment. These messages contain a link and a text message urging the recipient to settle the fine by clicking on the links to make the payment.  Scammers have started trapping innocent individuals through such fake messages. These scammers are creating and sending fake messages that look like traffic challan alert messages. However, it is a completely deceptive and fake message. Such messages contain malicious links to fake website, leading users to visit the fake website and enter their bank account details, or make the payment which ultimately leads to financial loss to victims. Cyber scammers have meticulously copied the format used by the traffic authorities however a close examination can help us spot the trap. The modus operandi of such type of scam is to get the targeted individuals to click on a malicious link for payment of traffic e-challan. Once you click on such malicious payment link to pay for the e-challan the individuals unknowingly will end up paying the cyber criminals instead of the police in a bid to discharge the traffic e-challan.

How to spot a fake E-Challan?

• Verify the Vehicle Number: Make sure that the vehicle number mentioned in the message matches your vehicle’s number. Cross-check this information with your vehicle’s number plate or the smart card ( blue book) issued by the Regional Transport Office ( RTO).
• Verify the E-challan Number: Verify the validity of the e-challan number by logging into the official traffic police website or app. Legitimate e-challans will have a corresponding record that can be cross-checked for authenticity. The challan number can be verified by logging in to the official e-challan website. It is always advisable to Visit the official government website to check if you have actually been fined.
• Inspect the Message Content: Give attention to the language inculcated in the message. Hackers' messages may contain grammatical errors or unusual phrases. For example, cybercriminals might encourage victims to visit the RTO office in person. Trying to build up confidence among the victims. Also, it is important that you do not make such payments in haste. Vehicle owners must check such messages carefully before clicking on any link.

Best Practices to Stay Safe

• Be aware of unbidden messages: Be cautious when you receive unsolicited e- challan notifications. Abstain yourself by clicking on links or downloading attachments from unknown sources. 
• Always stick to legitimate or official websites: The scammers use links which look similar to the official link, and a casual glance can miss the difference. Hence it is strictly advisable to visit the official websites only. Also do note that government websites will always have the domain '.gov.in'.  The official website of Traffic Challan is https://echallan.parivahan.gov.in/ 
• Get it cross-checked through official channels: Always cross-check the authenticity of an e-challan by directly accessing official channels, such as the official traffic police website or application. 
• Connect with the RTO directly: If in doubt, independently connect with the Regional Transport Office ( RTO) using official contact details to verify the authenticity of the e-challan.  It is best not to solely rely on information received from suspicious messages. 
• Software update: Make sure that your device’s security software is up to date to protect against malware and phishing scams.

Conclusion:

Cybercriminals are exploiting the fear of traffic fines to trick individuals into clicking on malicious links and revealing their personal and financial information. These scams can lead to significant financial losses for the victims. To stay safe, it is important to be cautious of unsolicited messages, verify the authenticity of e-challans through official channels, and avoid clicking on links or downloading attachments from unknown sources. Awareness is the first line of defence in the evolving landscape of online threats. 

References:

• https://economictimes.indiatimes.com/news/new-updates/ahmedabad-residents-duped-out-of-lakhs-in-e-challan-scam-cops-arrest-jharkhand-man/articleshow/103528317.cms
• https://economictimes.indiatimes.com/wealth/save/new-traffic-e-challan-fraud-heres-how-to-identify-scam-messages-and-avoid-getting-duped/articleshow/104960817.cms
• https://www.ndtv.com/india-news/explained-the-new-e-challan-scam-how-we-can-escape-it-4342129

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Introduction

Generative AI models are significant consumers of computational resources and energy required for training and running models. While AI is being hailed as a game-changer, however underneath the shiny exterior, cracks are present which significantly raises concerns for its environmental impact. The development, maintenance, and disposal of AI technology all come with a large carbon footprint. The energy consumption of AI models, particularly large-scale models or image generation systems, these models rely on data centers powered by electricity, often from non-renewable sources, which exacerbates environmental concerns and contributes to substantial carbon emissions.

As AI adoption grows, improving energy efficiency becomes essential. Optimising algorithms, reducing model complexity, and using more efficient hardware can lower the energy footprint of AI systems. Additionally, transitioning to renewable energy sources for data centers can help mitigate their environmental impact. There is a growing need for sustainable AI development, where environmental considerations are integral to model design and deployment.

A breakdown of how generative AI contributes to environmental risks and the pressing need for energy efficiency:

• Gen AI during the training phase has high power consumption, when vast amounts of computational power which is often utilising extensive GPU clusters for weeks or at times even months, consumes a substantial amount of electricity. Post this phase, the inference phase where the deployment of these models takes place for real-time inference, can be energy-extensive especially when we take into account the millions of users of Gen AI.
• The main source of energy used for training and deploying AI models often comes from non-renewable sources which then contribute to the carbon footprint. The data centers where the computations for Gen AI take place are a significant source of carbon emissions if they rely on the use of fossil fuels for their energy needs for the training and deployment of the models. According to a study by MIT, training an AI can produce emissions that are equivalent to around 300 round-trip flights between New York and San Francisco. According to a report by Goldman Sachs, Data Companies will use 8% of US power by 2030, compared to 3% in 2022 as their energy demand grows by 160%.
• The production and disposal of hardware (GPUs, servers) necessary for AI contribute to environmental degradation. Mining for raw materials and disposing of electronic waste (e-waste) are additional environmental concerns. E-waste contains hazardous chemicals, including lead, mercury, and cadmium, that can contaminate soil and water supplies and endanger both human health and the environment. 

Efforts by the Industry to reduce the environmental risk posed by Gen AI 

There are a few examples of how companies are making efforts to reduce their carbon footprint, reduce energy consumption and overall be more environmentally friendly in the long run. Some of the efforts are as under:

• Google's TPUs in particular the Google Tensor are designed specifically for machine learning tasks and offer a higher performance-per-watt ratio compared to traditional GPUs, leading to more efficient AI computations during the shorter periods requiring peak consumption. 
• Researchers at Microsoft, for instance, have developed a so-called “1 bit” architecture that can make LLMs 10 times more energy efficient than the current leading system. This system simplifies the models’ calculations by reducing the values to 0 or 1, slashing power consumption but without sacrificing its performance.
• OpenAI has been working on optimizing the efficiency of its models and exploring ways to reduce the environmental impact of AI and using renewable energy as much as possible including the research into more efficient training methods and model architectures.

Policy Recommendations

We advocate for the sustainable product development process and press the need for Energy Efficiency in AI Models to counter the environmental impact that they have. These improvements would not only be better for the environment but also contribute to the greater and sustainable development of Gen AI.  Some suggestions are as follows:

• AI needs to adopt a Climate justice framework which has been informed by a diverse context and perspectives while working in tandem with the UN’s (Sustainable Development Goals) SDGs.
• Working and developing more efficient algorithms that would require less computational power for both training and inference can reduce energy consumption. Designing more energy-efficient hardware, such as specialized AI accelerators and next-generation GPUs, can help mitigate the environmental impact. 
• Transitioning to renewable energy sources (solar, wind, hydro) can significantly reduce the carbon footprint associated with AI. The World Economic Forum (WEF) projects that by 2050, the total amount of e-waste generated will have surpassed 120 million metric tonnes.
• Employing techniques like model compression, which reduces the size of AI models without sacrificing performance, can lead to less energy-intensive computations. Optimized models are faster and require less hardware, thus consuming less energy.
• Implementing scattered learning approaches, where models are trained across decentralized devices rather than centralized data centers, can lead to a better distribution of energy load evenly and reduce the overall environmental impact.
• Enhancing the energy efficiency of data centers through better cooling systems, improved energy management practices, and the use of AI for optimizing data center operations can contribute to reduced energy consumption.

Final Words

The UN Sustainable Development Goals (SDGs) are crucial for the AI industry just as other industries as they guide responsible innovation. Aligning AI development with the SDGs will ensure ethical practices, promoting sustainability, equity, and inclusivity. This alignment fosters global trust in AI technologies, encourages investment, and drives solutions to pressing global challenges, such as poverty, education, and climate change, ultimately creating a positive impact on society and the environment. The current state of AI is that it is essentially utilizing enormous power and producing a product not efficiently utilizing the power it gets. AI and its derivatives are stressing the environment in such a manner which if it continues will affect the clean water resources and other non-renewable power generation sources which contributed to the huge carbon footprint of the AI industry as a whole.  

References

• https://cio.economictimes.indiatimes.com/news/artificial-intelligence/ais-hunger-for-power-can-be-tamed/111302991
• https://earth.org/the-green-dilemma-can-ai-fulfil-its-potential-without-harming-the-environment/ 
• https://www.technologyreview.com/2019/06/06/239031/training-a-single-ai-model-can-emit-as-much-carbon-as-five-cars-in-their-lifetimes/
• https://www.scientificamerican.com/article/ais-climate-impact-goes-beyond-its-emissions/ ‍
• https://insights.grcglobalgroup.com/the-environmental-impact-of-ai/