80% of Gen-Z Want to Marry an AI Bot Vantage with Palki Sharma
Gen Z isn't just using AI — they're befriending it, dating it, and asking it for life advice. From 'Should I dump my partner?' to 'Should I dye my hair?', ChatGPT is the new best friend, therapist, and career coach rolled into one. Studies show 70% of Gen Z have AI companions, and 80% would even marry one. It's convenient, funny, and always online but are we forgetting how to be human? Palki Sharma tells you.
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Hans India
21 minutes ago
- Hans India
TGBIE hosts training session on integrating AI in education
Hyderabad: The Telangana Board of Intermediate Education (TGBIE) conducted a one-day training program for AI Champions and District Academic Monitoring Officers (DAMOs) at its headquarters in Vidya Bhavan on Thursday. The session focused on the implementation of Artificial Intelligence (AI) tools and Facial Recognition Systems (FRS) in Government Junior Colleges across the state. The initiative was led by Dr Yogita Rana, Secretary to the Government, Education Department, who emphasized the transformative potential of AI in academic progress. She highlighted tools like Gemini, ChatGPT, Meta, and Google's LLM as powerful resources for enhancing student learning outcomes. During the workshop, TGBIE officials instructed participants to actively adopt AI-based solutions tailored to student needs. A key highlight was the planned rollout of Facial Recognition Systems to monitor student attendance more effectively. The FRS will be integrated with the Centre for Good Governance (CGG) portal for real-time tracking and accountability. The Director of Intermediate Education stressed the importance of field-level implementation and urged officers to organize Mega Parent-Teacher Meetings in every Government Junior College. These meetings aim to foster greater parental involvement and awareness of technological advancements in education. The training also underscored the broader vision of the Telangana government to incorporate AI-driven learning environments. AI Champions and DAMOs were briefed on the strategic role of AI in curriculum delivery, student assessment, and personalized learning pathways. This move aligns with national efforts to digitize education and equip institutions with cutting-edge tools. By integrating AI and FRS, the Board aims to improve transparency, attendance tracking, and academic performance monitoring. Officers were urged to ensure swift and effective implementation of these technologies, making Telangana a model for AI-enabled education in India.
India.com
34 minutes ago
- India.com
Hey Millennials & Gen Z, Heres The Movie You Will Never See, 100 Years Kept In A Bulletproof Glass Vault Till 2115
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Hindustan Times
2 hours ago
- Hindustan Times
AI-powered robots can take your phone apart
THE WORLD'S rubbish heaps are filling up with valuable electronics. According to the UN, some 62m tonnes of e-waste were produced in 2022, enough to fill a line of lorries parked bumper-to-bumper around the equator. Only 22% is recycled. Most of the rest ends up in landfills or incinerators, where in 2024 recoverable raw materials worth $63bn went to waste. That figure is expected to grow to more than $80bn by 2030. Getting those materials out of the rubbish is a challenge. Many are contaminated when e-waste is crushed during recycling, which can limit the effectiveness of specialist extraction techniques. The process is made more straightforward if products are disassembled and their components sorted by composition before crushing. Copper can then be recovered from wiring. Gold, silver and other precious metals can be leached from circuit boards, along with cobalt, lithium, manganese and nickel from batteries. Rare-earth magnets can be pulled from electric motors. The trouble is that disassembly is labour-intensive and costly. Automation is also tricky: robots are good at putting together a specific item but struggle to recognise and take apart the thousands of different devices that end up in the rubbish. A new generation of robots powered by artificial-intelligence (AI) models, however, looks to be up to the job. Some of these AI-assisted robots are being developed for in-house recycling schemes run by manufacturers, who have an intimate knowledge of how their products are put together. Apple, for example, uses a system called Daisy. A decade ago, an early version could dismantle only one type of iPhone; now, with the help of AI, Daisy can handle more than 20. Microsoft is developing a robot to disassemble computer hard drives. These are usually crushed whole to destroy any sensitive data, but if the drives are dismantled, only the platters containing data need be crushed. ABB, a Swedish-Swiss electrical-engineering group, is working with Molg, an American recycler, on a network of robotic 'minifactories' to dismantle and recover material from the electronics used in vast data centres. José Saenz and his team at the Fraunhofer Institute for Factory Operation and Automation in Magdeburg, Germany have a still more ambitious goal. They are developing a robotic system that can be used in a general recycling centre, where it would need to be flexible enough to dismantle a wide variety of e-waste, ranging from phones to electric-vehicle batteries, LED screens and solar panels. Their starting point is an AI-assisted robot that can disassemble old desktop PCs, many of which are more than a decade old. The first thing the team's robot does is identify any product it is offered. A camera photographs the item and compares the snap with pictures of different PCs. The robot also scans any labels and product codes to check whether service manuals or other disassembly tips are available online. It can search for other clues, in much the same way ChatGPT might, when asked a similar question, turn up videos posted online by people who have done the job before. All this information is analysed and stored in the robot's memory, where it can be updated and used for reference the next time such a product comes into the recycling centre. Once the identification is complete, the AI system then determines which components are worth removing, either in the form of raw materials or as complete parts to be refurbished and used again. It also checks the integrity of rivets, screws and other fasteners, because years of wear, tear and repair mean some parts may need to be cut out. Analysis done, the AI generates a disassembly sequence to operate the robot's arms. These are equipped with a selection of tools, such as drills, grippers and screwdrivers, to remove and sort items. So far, the team has got each stage in the disassembly process working in separate machines. They are now linking these together into a single robotic device able to complete the whole process. Once dismantling PCs has been mastered the team will train robots to tackle other products. The learning process will take time. Dr Saenz thinks it could be five years until they develop a commercial disassembly robot that could usefully work at a recycling centre taking apart anything from PCs to white goods and televisions. Firms that want to recycle their own, limited range of products could probably put together something more quickly. A multi-purpose robot would probably be popular, since companies are under increasingly fierce legislative pressure to take responsibility for the end-of-life management of their products, either directly or by employing specialists to recycle for them. The rise of smarter spanner-wielding robots, therefore, should encourage more firms to ensure their products are useful in death, as they were in life.
