Astronaut Shubhanshu Shukla to interact with school students at NESAC on Tuesday
Empower your mind, elevate your skills
Astronaut Shubhanshu Shukla is set to interact with school students at ISRO 's North East Space Application Centre (NESAC) from his orbital post on the International Space Station via ham radio on Tuesday afternoon.The interaction is planned via a telebridge set up NESAC in Shillong, said the Amateur Radio on International Space Station (ARISS), which facilitates interaction of school students with astronauts on the orbital laboratory.Shukla is on a 14-day scientific expedition on the International Space Station (ISS) as part of the Axiom-4 mission , along with three other astronauts.The ARISS programme inspires students worldwide to pursue their interests and careers in science, technology, engineering and mathematics through amateur radio communication opportunities with the ISS on-orbit crew."Axiom_Space #Ax4 crew member Shubhanshu Shukla, VU2TNI, will talk with students at NESAC in Meghalaya via ham radio," ARISS said in a post on X about Tuesday's interaction.On Friday, Shukla interacted with students at the U R Rao Satellite Centre in Bengaluru. Ham radio enthusiasts tuned in to the designated frequency to listen in to the conversation.Ham radio, also known as amateur radio, is a non-commercial radio communication service operated by licensed enthusiasts and is considered a reliable mode of communication during disasters, when conventional modes of communication are not available. PTI
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
&w=3840&q=100)
Business Standard
2 hours ago
- Business Standard
AI may now match humans in spotting emotion, sarcasm in online chats
When we write something to another person, over email or perhaps on social media, we may not state things directly, but our words may instead convey a latent meaning – an underlying subtext. We also often hope that this meaning will come through to the reader. But what happens if an artificial intelligence (AI) system is at the other end, rather than a person? Can AI, especially conversational AI, understand the latent meaning in our text? And if so, what does this mean for us? Latent content analysis is an area of study concerned with uncovering the deeper meanings, sentiments and subtleties embedded in text. For example, this type of analysis can help us grasp political leanings present in communications that are perhaps not obvious to everyone. Understanding how intense someone's emotions are or whether they're being sarcastic can be crucial in supporting a person's mental health, improving customer service, and even keeping people safe at a national level. These are only some examples. We can imagine benefits in other areas of life, like social science research, policy-making and business. Given how important these tasks are – and how quickly conversational AI is improving – it's essential to explore what these technologies can (and can't) do in this regard. Work on this issue is only just starting. Current work shows that ChatGPT has had limited success in detecting political leanings on news websites. Another study that focused on differences in sarcasm detection between different large language models – the technology behind AI chatbots such as ChatGPT – showed that some are better than others. Finally, a study showed that LLMs can guess the emotional 'valence' of words – the inherent positive or negative 'feeling' associated with them. Our new study published in Scientific Reports tested whether conversational AI, inclusive of GPT-4 – a relatively recent version of ChatGPT – can read between the lines of human-written texts. The goal was to find out how well LLMs simulate understanding of sentiment, political leaning, emotional intensity and sarcasm – thus encompassing multiple latent meanings in one study. This study evaluated the reliability, consistency and quality of seven LLMs, including GPT-4, Gemini, Llama-3.1-70B and Mixtral 8 × 7B. We found that these LLMs are about as good as humans at analysing sentiment, political leaning, emotional intensity and sarcasm detection. The study involved 33 human subjects and assessed 100 curated items of text. For spotting political leanings, GPT-4 was more consistent than humans. That matters in fields like journalism, political science, or public health, where inconsistent judgement can skew findings or miss patterns. GPT-4 also proved capable of picking up on emotional intensity and especially valence. Whether a tweet was composed by someone who was mildly annoyed or deeply outraged, the AI could tell – although, someone still had to confirm if the AI was correct in its assessment. This was because AI tends to downplay emotions. Sarcasm remained a stumbling block both for humans and machines. The study found no clear winner there – hence, using human raters doesn't help much with sarcasm detection. Why does this matter? For one, AI like GPT-4 could dramatically cut the time and cost of analysing large volumes of online content. Social scientists often spend months analysing user-generated text to detect trends. GPT-4, on the other hand, opens the door to faster, more responsive research – especially important during crises, elections or public health emergencies. Journalists and fact-checkers might also benefit. Tools powered by GPT-4 could help flag emotionally charged or politically slanted posts in real time, giving newsrooms a head start. There are still concerns. Transparency, fairness and political leanings in AI remain issues. However, studies like this one suggest that when it comes to understanding language, machines are catching up to us fast – and may soon be valuable teammates rather than mere tools. Although this work doesn't claim conversational AI can replace human raters completely, it does challenge the idea that machines are hopeless at detecting nuance. Our study's findings do raise follow-up questions. If a user asks the same question of AI in multiple ways – perhaps by subtly rewording prompts, changing the order of information, or tweaking the amount of context provided – will the model's underlying judgements and ratings remain consistent? Further research should include a systematic and rigorous analysis of how stable the models' outputs are. Ultimately, understanding and improving consistency is essential for deploying LLMs at scale, especially in high-stakes settings.
Time of India
3 hours ago
- Time of India
AI might now be as good as humans at detecting emotion, political leaning, sarcasm in online conversations
Academy Empower your mind, elevate your skills When we write something to another person, over email or perhaps on social media, we may not state things directly, but our words may instead convey a latent meaning - an underlying subtext. We also often hope that this meaning will come through to the what happens if an artificial intelligence (AI) system is at the other end, rather than a person? Can AI, especially conversational AI, understand the latent meaning in our text? And if so, what does this mean for us? Latent content analysis is an area of study concerned with uncovering the deeper meanings, sentiments and subtleties embedded in text. For example, this type of analysis can help us grasp political leanings present in communications that are perhaps not obvious to how intense someone's emotions are or whether they're being sarcastic can be crucial in supporting a person's mental health, improving customer service, and even keeping people safe at a national are only some examples. We can imagine benefits in other areas of life, like social science research, policy-making and business. Given how important these tasks are - and how quickly conversational AI is improving - it's essential to explore what these technologies can (and can't) do in this on this issue is only just starting. Current work shows that ChatGPT has had limited success in detecting political leanings on news websites. Another study that focused on differences in sarcasm detection between different large language models - the technology behind AI chatbots such as ChatGPT - showed that some are better than a study showed that LLMs can guess the emotional "valence" of words - the inherent positive or negative "feeling" associated with them. Our new study published in Scientific Reports tested whether conversational AI, inclusive of GPT-4 - a relatively recent version of ChatGPT - can read between the lines of human-written goal was to find out how well LLMs simulate understanding of sentiment, political leaning, emotional intensity and sarcasm - thus encompassing multiple latent meanings in one study. This study evaluated the reliability, consistency and quality of seven LLMs, including GPT-4, Gemini, Llama-3.1-70B and Mixtral 8 x found that these LLMs are about as good as humans at analysing sentiment, political leaning, emotional intensity and sarcasm detection. The study involved 33 human subjects and assessed 100 curated items of spotting political leanings, GPT-4 was more consistent than humans. That matters in fields like journalism, political science, or public health, where inconsistent judgement can skew findings or miss also proved capable of picking up on emotional intensity and especially valence. Whether a tweet was composed by someone who was mildly annoyed or deeply outraged, the AI could tell - although, someone still had to confirm if the AI was correct in its assessment. This was because AI tends to downplay emotions. Sarcasm remained a stumbling block both for humans and study found no clear winner there - hence, using human raters doesn't help much with sarcasm does this matter? For one, AI like GPT-4 could dramatically cut the time and cost of analysing large volumes of online content. Social scientists often spend months analysing user-generated text to detect trends. GPT-4, on the other hand, opens the door to faster, more responsive research - especially important during crises, elections or public health and fact-checkers might also benefit. Tools powered by GPT-4 could help flag emotionally charged or politically slanted posts in real time, giving newsrooms a head are still concerns. Transparency, fairness and political leanings in AI remain issues. However, studies like this one suggest that when it comes to understanding language, machines are catching up to us fast - and may soon be valuable teammates rather than mere this work doesn't claim conversational AI can replace human raters completely, it does challenge the idea that machines are hopeless at detecting study's findings do raise follow-up questions. If a user asks the same question of AI in multiple ways - perhaps by subtly rewording prompts, changing the order of information, or tweaking the amount of context provided - will the model's underlying judgements and ratings remain consistent?Further research should include a systematic and rigorous analysis of how stable the models' outputs are. Ultimately, understanding and improving consistency is essential for deploying LLMs at scale, especially in high-stakes settings.
NDTV
3 hours ago
- NDTV
India's $70 Million Ticket To Space Redefines A Global Collaboration
With India's nearly $70 million investment leap, Astronaut Shubhanshu Shukla's space mission ignites global space commerce. In a landmark moment for India's space ambitions, Group Captain Shubhanshu Shukla is currently aboard the International Space Station (ISS) as part of a commercial spaceflight mission organized by Axiom Space. This mission, known as Axiom Mission 4 (Ax-4), marks India's first paid seat on a private astronaut mission, signalling a new era of international cooperation and commercial engagement in human spaceflight. Super simplified it is a glorified shared Uber taxi ride with Hungary and Poland also sharing the costs. India's participation in Ax-4 is the result of a nearly $70 million investment, a strategic move that allows the country to gain first-hand experience in human spaceflight operations ahead of its own Gaganyaan mission. The mission was borne by Axiom Space seeking to sell a seat to ISRO, followed by a bilateral agreement between the Indian and US governments, with the intent to deepen space collaboration and accelerate India's capabilities in crewed missions. The Ax-4 mission is a complex orchestration of multiple entities. Axiom Space, a private US company aiming to build its own commercial space station, won NASA's tender to operate private astronaut missions. Axiom does not own a launch vehicle, so it partnered with SpaceX, which provided the Falcon 9 rocket and Crew Dragon capsule, now named Grace. The mission was certified and overseen by NASA and the Federal Aviation Administration (FAA), and coordinated with the international consortium that manages the ISS. This intricate framework-described by aerospace engineer and space entrepreneur George Winemann as "G2-B2-B2-G"-involves government-to-business (India to Axiom), business-to-business (Axiom to SpaceX), and business-to-government (SpaceX to NASA and ISS partners) interactions. According to Winemann, the success of this model demonstrates the growing maturity of commercial spaceflight and the ability of diverse stakeholders to collaborate effectively despite regulatory and operational complexities. George Winemann, aerospace engineer and space entrepreneur The mission faced several technical challenges, including delays due to weather, oxidizer leaks, and docking issues at the ISS. However, these hiccups were resolved through coordinated efforts among all parties. Winemann emphasized that the decorum and responsiveness shown by SpaceX and Axiom in addressing ISRO's heightened concerns, where at one stage ISRO threatened to withdraw its astronaut from the Axiom-4 mission were exemplary, especially given the constraints imposed by US export control laws like International Traffic in Arms Regulations (ITAR). For India, the mission is not just symbolic but deeply practical. ISRO has used the opportunity to conduct microgravity experiments aboard the ISS, with seven Indian research proposals selected for execution. These experiments span areas such as biomedical science, material physics, and space agriculture, contributing to a broader pool of 60 studies from 31 countries. The presence of Group Captain Shukla on the ISS also marks a diplomatic milestone. It reflects India's emergence as a credible space power and its ability to engage in high-level international partnerships. The mission has been dubbed "Mission Akash Ganga" in India, echoing the country's cultural and scientific aspirations in space. Winemann noted that the mission's success is a testament to the power of communication and trust. Despite the challenges and hiccups involvement of multiple governments and private entities, the stakeholders managed to align their priorities and execute the mission smoothly. He also highlighted the role of India's newly formed space promotion agency, InSpace, in facilitating private sector participation and international collaboration. Looking ahead, the Ax-4 mission sets a precedent for future commercial spaceflights involving emerging space nations. It demonstrates that with the right framework, countries can access the ISS and other orbital platforms without being formal partners in the consortium. This opens the door for broader participation in space research, technology development, and even commercial ventures such as manufacturing and biopharma in microgravity. The mission also reinforces the strategic importance of space diplomacy. With India and the US continuing to strengthen their space ties, including upcoming collaborations like the NISAR satellite launch, the Ax-4 mission serves as a blueprint for how commercial and governmental entities can work together to achieve shared goals. India's participation in Axiom Mission 4 is a bold and successful step into the realm of commercial human spaceflight. It showcases the country's readiness to engage with global space leaders, leverage private sector capabilities, and contribute meaningfully to the future of space exploration. As Group Captain Shukla continues his work aboard the ISS, the mission stands as a powerful symbol of what can be achieved through innovation, diplomacy, and collaboration, since space unifies nations as the perch of space shows no national boundaries to astronauts like Group Captain Shukla. Now, a whole new commercialisation of the low Earth orbit is being paved by India's first foray into the space station. Group Captain Shukla, literally, opened the doors to increased commerce in space.
