#FactCheck – False Claim of Lord Ram's Hologram in Srinagar - Video Actually from Dehradun

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/

Introduction

The Telecom Regulatory Authority of India (TRAI) has directed all telcos to set up detection systems based on Artificial Intelligence and Machine Learning (AI/ML) technologies in order to identify and control spam calls and text messages from unregistered telemarketers (UTMs).

The TRAI Directed telcos

The telecom regulator, TRAI, has directed all Access Providers to detect Unsolicited commercial communication (UCC)by systems, which is based on Artificial Intelligence and Machine Learning to detect, identify, and act against senders of Commercial Communication who are not registered in accordance with the provisions of the Telecom Commercial Communication Customer Preference Regulations, 2018 (TCCCPR-2018). Unregistered Telemarketers (UTMs) are entities that do not register with Access Providers and use 10-digit mobile numbers to send commercial communications via SMS or calls.

TRAI steps to curb Unsolicited commercial communication

TRAI has taken several initiatives to reduce Unsolicited Commercial Communication (UCC), which is a major source of annoyance for the public. It has resulted in fewer complaints filed against Registered Telemarketers (RTMs). Despite the TSPs’ efforts, UCC from Unregistered Telemarketers (UTMs) continues. Sometimes, these UTMs use messages with bogus URLs and phone numbers to trick clients into revealing crucial information, leading to financial loss.

To detect, identify, and prosecute all Unregistered Telemarketers (UTMs), the TRAI has mandated that Access Service Providers implement the UCC.

Detect the System with the necessary functionalities within the TRAI’s Telecom Commercial Communication Customer Preference Regulations, 2018 framework.

Access service providers have implemented such detection systems based on their applicability and practicality. However, because UTMs are constantly creating new strategies for sending unwanted communications, the present UCC detection systems provided by Access Service providers cannot detect such UCC.

TRAI also Directs Telecom Providers to Set Up Digital Platform for Customer Consent to Curb Promotional Calls and Messages.

Unregistered Telemarketers (UTMs) sometimes use messages with fake URLs and phone numbers to trick customers into revealing essential information, resulting in financial loss.

TRAI has urged businesses like banks, insurance companies, financial institutions, and others to re-verify their SMS content templates with telcos within two weeks. It also directed telecom companies to stop misusing commercial messaging templates within the next 45 days.

The telecom regulator has also instructed operators to limit the number of variables in a content template to three. However, if any business intends to utilise more than three variables in a content template for communicating with their users, this should be permitted only after examining the example message, as well as adequate justifications and justification.

In order to ensure consistency in UCC Detect System implementations, TRAI has directed all Access Providers to deploy UCC and detect systems based on artificial intelligence and Machine Learning that are capable of constantly evolving to deal with new signatures, patterns, and techniques used by UTMs.

Access Providers have also been directed to use the DLT platform to share intelligence with others. Access Providers have also been asked to ensure that such UCC Detect System detects senders that send unsolicited commercial communications in bulk and do not comply with the requirements. All Access Providers are directed to follow the instructions and provide an update on actions done within thirty days.

The move by TRAI is to curb the menacing calls as due to this, the number of scam cases is increasing, and now a new trend of scams started as recently, a Twitter user reported receiving an automated call from +91 96681 9555 with the message “This call is from Delhi Police.” It then asked her to stay in the queue since some of her documents needed to be picked up. Then he said he works as a sub-inspector at the Kirti Nagar police station in New Delhi. He then inquired whether she had recently misplaced her Aadhaar card, PAN card, or ATM card, to which she replied ‘no’. The scammer then poses as a cop and requests that she authenticate the last four digits of her card because they have found a card with her name on it. And a lot of other people tweeted about it.

Conclusion

TRAI directed the telcos to check the calls and messages from Unregistered numbers. This step of TRAI will curb the pesky calls and messages and catch the Frauds who are not registered with the regulation. Sometimes the unregistered sender sends fraudulent links, and through these fraudulent calls and messages, the sender tries to take the personal information of the customers, which results in financial losses.

Executive Summary:

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A viral video claiming the crash site of Air India Flight AI-171 in Ahmedabad has misled many people online. The video has been confirmed not to be from India or a recent crash, but was filmed at Universal Studios Hollywood on a TV or movie set meant to look like a plane crash set piece for a movie.

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Claim:

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A video that purportedly shows the wreckage of Air India Flight AI-171 after crashing in Ahmedabad on June 12, 2025, has circulated among social media users. The video shows a large amount of aircraft wreckage as well as destroyed homes and a scene reminiscent of an emergency, making it look genuine.

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Fact check:

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In our research, we took screenshots from the viral video and used reverse image search, which matched visuals from Universal Studios Hollywood. It became apparent that the video is actually from the most famous “War of the Worlds" set, located in Universal Studios Hollywood. The set features a 747 crash scene that was constructed permanently for Steven Spielberg's movie in 2005. We also found a YouTube video. The set has fake smoke poured on it, with debris scattered about and additional fake faceless structures built to represent a scene with a larger crisis. Multiple videos on YouTube here, here, and here can be found from the past with pictures of the tour at Universal Studios Hollywood, the Boeing 747 crash site, made for a movie.

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The Universal Studios Hollywood tour includes a visit to a staged crash site featuring a Boeing 747, which has unfortunately been misused in viral posts to spread false information.

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While doing research, we were able to locate imagery indicating that the video that went viral, along with the Universal Studios tour footage, provided an exact match and therefore verified that the video had no connection to the Ahmedabad incident. A side-by-side comparison tells us all we need to know to uncover the truth.

                                                                        

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Conclusion:

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The viral video claiming to show the aftermath of the Air India crash in Ahmedabad is entirely misleading and false. The video is showing a fictitious movie set from Universal Studios Hollywood, not a real disaster scene in India. Spreading misinformation like this can create unnecessary panic and confusion in sensitive situations. We urge viewers to only trust verified news and double-check claims before sharing any content online.

• Claim: Massive explosion and debris shown in viral video after Air India crash.‍
• Claimed On: Social Media‍
• Fact Check: False and Misleading

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