Society
Meet the 14-year-old boy who teaches his own teachers

Picture this: a 14-year-old boy teaching classes to his own teachers at his school. Raul John Aju, a young prodigy from Edappally Government Vocational Higher Secondary School, Kerala, India, had the unique opportunity to do just that at Huddle Global 2024, India’s flagship startup festival, organized by Kerala Startup Mission (KSUM) at Kovalam.
Raul’s extraordinary achievement is the result of his exceptional expertise in Artificial Intelligence and Robotics, which he has acquired through years of dedication and passion since childhood.
The teen’s profound knowledge of AI and Robotics was showcased during the opening session of the three-day festival.
In his session titled ‘Dream Big, Code Bigger – Shaping the Future with Technology’, Raul captivated the audience by demonstrating how AI tools can empower anyone to start a business on their own.
“AI applications can be leveraged to build a startup from the ground up. Whether it’s developing a business model or assessing the feasibility of your product, AI can help create websites, design logos, and assist in business presentations and marketing,” Raul explained, drawing enthusiastic responses from the crowd.
He further emphasized that AI can streamline every aspect of a startup’s verticals, making the process more efficient and accessible.
Raul has also created an AI-powered legal assistant called ‘Nyaya Sathi’. This free bot provides instant legal information to ordinary citizens, making legal advice more accessible to the public.
Apart from his innovations, Raul teaches AI to international students and employees in the US and UK, covering topics like machine learning, deep learning, and AI language models.
“I use AI to generate presentations for my classes, which saves me a lot of time while balancing my studies and other activities,” Raul shared. He strongly believes that AI isn’t going to replace jobs, but rather, people who are skilled at using AI will shape the future workforce.
“AI is both the present and the future. It boosts productivity, increases revenue, and will unlock a world of new possibilities,” Raul asserted, citing statistics that show how AI has improved efficiency for major corporations.
Society
How Scientists and Investigators Decode Air Crashes — The Black Box and Beyond
The final report may take months, but it will be critical in issuing safety directives or revising standard procedures.

As rescue and recovery operations continue following the June 12, 2025, plane crash in Ahmedabad, aviation safety experts are now focusing on the technical investigation phase. With 241 lives lost, the search for the cause isn’t just about accountability—it’s about prevention.
The Black Box: Aviation’s Memory Keeper
1. What Is the Black Box?
Despite the name, the black box is actually orange — for visibility. It consists of two components:
- Cockpit Voice Recorder (CVR): Captures conversations and audio from the flight deck.
- Flight Data Recorder (FDR): Logs dozens to hundreds of parameters — speed, altitude, engine status, control inputs.
These devices are housed in titanium or steel and can withstand:
- Temperatures above 1,000°C
- Underwater pressures up to 20,000 feet
- Crashes with up to 3,600 G-force
They also emit underwater locator beacons for up to 30 days.
2. Forensic Engineering & Flight Reconstruction
Beyond black boxes, investigators use:
- Radar data and air traffic control logs
- Wreckage analysis for structural failure clues
- Satellite-based tracking systems like ADS-B
- Weather data for turbulence or wind shear insights
Forensic teams often reconstruct the flight path virtually or even physically using recovered debris to determine failure points.
3. Human Factors & AI in Modern Investigation
New tools like machine learning and human factors analysis are used to identify procedural errors or lapses in judgement.
In many modern investigations, AI helps:
- Filter large datasets (e.g., over 1,000 flight parameters per second)
- Detect patterns missed by the human eye
- Predict similar risk scenarios in future flights
What Happens Next in the Ahmedabad Crash?
Authorities, in coordination with the Directorate General of Civil Aviation (DGCA), are likely:
- Retrieving and analyzing the black box
- Interviewing air traffic controllers
- Reconstructing the aircraft’s final seconds using both data and simulation
The final report may take months, but it will be critical in issuing safety directives or revising standard procedures.
Society
Researchers Unveil Light-Speed AI Chip to Power Next-Gen Wireless and Edge Devices
This could transform the future of wireless communication and edge computing

In a breakthrough that could transform the future of wireless communication and edge computing, engineers at MIT have developed a novel AI hardware accelerator capable of processing wireless signals at the speed of light. The new optical chip, built for signal classification, achieves nanosecond-level performance—up to 100 times faster than conventional digital processors—while consuming dramatically less energy.
With wireless spectrum under growing strain from billions of connected devices, from teleworking laptops to smart sensors, managing bandwidth has become a critical challenge. Artificial intelligence offers a path forward, but most existing AI models are too slow and power-hungry to operate in real time on wireless devices.
The MIT solution, known as MAFT-ONN (Multiplicative Analog Frequency Transform Optical Neural Network), could be a game-changer.
“There are many applications that would be enabled by edge devices that are capable of analyzing wireless signals,” said Prof. Dirk Englund, senior author of the study, in a media statement. “What we’ve presented in our paper could open up many possibilities for real-time and reliable AI inference. This work is the beginning of something that could be quite impactful.”
Published in Science Advances, the research describes how MAFT-ONN classifies signals in just 120 nanoseconds, using a compact optical chip that performs deep-learning tasks using light rather than electricity. Unlike traditional systems that convert signals to images before processing, the MIT design processes raw wireless data directly in the frequency domain—eliminating delays and reducing energy usage.
“We can fit 10,000 neurons onto a single device and compute the necessary multiplications in a single shot,” said Ronald Davis III, lead author and recent MIT PhD graduate.
The device achieved over 85% accuracy in a single shot, and with multiple measurements, it converges to above 99% accuracy, making it both fast and reliable.
Beyond wireless communications, the technology holds promise for edge AI in autonomous vehicles, smart medical devices, and future 6G networks, where real-time response is critical. By embedding ultra-fast AI directly into devices, this innovation could help cars react to hazards instantly or allow pacemakers to adapt to a patient’s heart rhythm in real-time.
Future work will focus on scaling the chip with multiplexing schemes and expanding its ability to handle more complex AI tasks, including transformer models and large language models (LLMs).
Society
Ahmedabad Plane Crash: The Science Behind Aircraft Take-Off -Understanding the Physics of Flight
Take-off is one of the most critical phases of flight, relying on the precise orchestration of aerodynamics, propulsion, and control systems. Here’s how it works:

On June 12, 2025, a tragic aviation accident struck Ahmedabad, India when a regional passenger aircraft, Air India flight A1-171, crashed during take-off at Sardar Vallabhbhai Patel International Airport. According to preliminary reports, the incident resulted in over 200 confirmed casualties, including both passengers and crew members, and several others are critically injured. The aviation community and scientific world now turn their eyes not just toward the cause but also toward understanding the complex science behind what should have been a routine take-off.
How Do Aircraft Take Off?
Take-off is one of the most critical phases of flight, relying on the precise orchestration of aerodynamics, propulsion, and control systems. Here’s how it works:
1. Lift and Thrust
To leave the ground, an aircraft must generate lift, a force that counters gravity. This is achieved through the unique shape of the wing, called an airfoil, which creates a pressure difference — higher pressure under the wing and lower pressure above — according to Bernoulli’s Principle and Newton’s Third Law.
Simultaneously, engines provide thrust, propelling the aircraft forward. Most commercial jets use turbofan engines, which accelerate air through turbines to generate power.
2. Critical Speeds
Before takeoff, pilots calculate critical speeds:
- V1 (Decision Speed): The last moment a takeoff can be safely aborted.
- Vr (Rotation Speed): The speed at which the pilot begins to lift the nose.
- V2 (Takeoff Safety Speed): The speed needed to climb safely even if one engine fails.
If anything disrupts this process — like bird strikes, engine failure, or runway obstructions — the results can be catastrophic.

Environmental and Mechanical Challenges
Factors like wind shear, runway surface condition, mechanical integrity, or pilot error can interfere with safe take-off. Investigators will be analyzing these very aspects in the Ahmedabad case.
The Bigger Picture
Take-off accounts for a small fraction of total flight time but is disproportionately associated with accidents — approximately 14% of all aviation accidents occur during take-off or initial climb.
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