OpenAI Academy & NxtWave (NIAT) Launch India's Largest GenAI Innovation Challenge for Students
A Hybrid Challenge Driving Real-World AI Innovation
The Buildathon will be conducted in a hybrid format, combining online workshops and activities with regional offline finals, culminating in a grand finale where the best teams pitch live to expert judges from OpenAI India.
The participants will first complete a 6-hour online workshop focused on GenAI fundamentals, intro to building agents, OpenAI API usage training, and responsible AI development best practices. This foundational sprint ensures all participants are well-prepared to develop innovative and impactful AI solutions using OpenAI's cutting-edge technologies.
The Buildathon unfolds over three competitive stages: Stage 1: Screening Round — Post-workshop, teams submit problem statements, project ideas, and execution plans online. A panel of mentors reviews submissions to shortlist the most promising entries.
Stage 2: Regional Finals — Shortlisted teams participate in an intensive 48-hour offline Buildathon held across 25–30 STEM colleges, with hands-on mentor support. Regional winners are announced following this stage.
Stage 3: Grand Finale — The top 10–15 teams from regional finals compete in the Grand Finale, pitching their solutions live to expert judges.
Build with the Best Tools in AI
Participants will have access to the latest in AI innovation, including GPT-4.1, GPT-4o, GPT-4o Audio, and GPT-4o Realtime models, supporting multimodal inputs like text, image, and audio. Additionally, tools like LangChain, vector databases (Pinecone, Weaviate), MCPs, and the OpenAI Agents SDK. These tools will empower students to build high-impact, multimodal, action-oriented GenAI applications. Hands-on mentorship and structured support will guide participants throughout the process.
Widespread Reach, Diverse Participation
The Buildathon aims to empower 25,000+ students across seven states — Telangana, Karnataka, Maharashtra, Andhra Pradesh, Tamil Nadu, Rajasthan, and Delhi NCR. The Grand Finale will be hosted in Hyderabad or Delhi. With coverage across all major zones of India, the event ensures nationwide representation and diversity.
Evaluation Criteria Across All Stages
The participants will be evaluated in three stages. In the Screening Round, mentors will assess submissions based on problem relevance, idea feasibility, and the proposed use of OpenAI APIs. During the Regional Finals, on-ground judges will evaluate the prototypes for innovation, depth of OpenAI API integration, societal impact, and business viability. Finally, in the Grand Finale, an expert panel will judge the top teams using the same criteria, with greater weightage given to execution quality and the effectiveness of live pitching.
Exciting Rewards & Career-Boosting Opportunities
Participants in the Buildathon will gain access to a wide range of exclusive benefits designed to boost their skills, visibility, and career prospects. All selected teams will receive hands-on training along with mentorship from leading AI experts across the country. Top-performing teams will earn certificates, GPT+ credits for prototyping, and national-level recognition. They'll also gain a rare opportunity to pitch directly to the OpenAI Academy's India team during the Grand Finale. Winners will receive prize money worth ₹10,00,000 in total along with Career opportunities in the OpenAI ecosystem.
A National Movement for GenAI Talent
Driven by NxtWave (NIAT), the Buildathon aligns with India's mission to skill its youth in future technologies. With OpenAI Academy bringing in expert guidance, branding, and cutting-edge tools, this initiative is poised to become a defining moment in India's AI journey along with offering students across the country a real chance to build and shine on a national stage.
This landmark initiative aims to position OpenAI Academy at the forefront of India's AI talent development, activating over 25,000 students across 500+ campuses and generating more than 2,000 AI projects tackling real-world challenges. Through collaborative efforts, OpenAI Academy and NxtWave seek to foster a vibrant community of AI builders ready to drive innovation and impact across India.
By enabling thousands of OpenAI-powered projects, the OpenAI Academy x NxtWave Buildathon sets the stage for a new wave of AI builders ready to innovate for India and beyond.
NIAT website – https://bit.ly/4jH4aJ5
Disclaimer: The above press release comes to you under an arrangement with Business Wire. Business Upturn takes no editorial responsibility for the same.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
CNET
an hour ago
- CNET
Do You Really Learn When You Use AI? What MIT Researchers Found
Your brain works differently when you're using generative AI for a task than when you use your brain alone. Namely, you're less likely to remember what you did. That's the somewhat obvious-sounding conclusion of an MIT study that looked at how people think when they write an essay -- one of the earliest scientific studies of how using gen AI affects us. The study, a preprint that has not yet been peer-reviewed, is pretty small (54 participants) and preliminary, but it points toward the need for more research into how using tools like OpenAI's ChatGPT is affecting how our brains function. OpenAI did not immediately respond to a request for comment on the research (Disclosure: Ziff Davis, CNET's parent company, in April filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.) The findings show a significant difference in what happens in your brain and with your memory when you complete a task using an AI tool rather than when you do it with just your brain. But don't read too much into those differences -- this is just a glimpse at brain activity in the moment, not long-term evidence of changes in how your brain operates all the time, researchers said. "We want to try to give some first steps in this direction and also encourage others to ask the question," Nataliya Kosmyna, a research scientist at MIT and the lead author of the study, told me. The growth of AI tools like chatbots is quickly changing how we work, search for information and write. All of this has happened so fast that it's easy to forget that ChatGPT first emerged as a popular tool just a few years ago, at the end of 2022. That means we're just now beginning to see research on how AI use is affecting us. Here's a look at what the MIT study found about what happened in the brains of ChatGPT users, and what future studies might tell us. Now Playing: Testing OpenAI's New ChatGPT Search Engine 06:01 This is your brain on ChatGPT The MIT researchers split their 54 research participants into three groups and asked them to write essays during separate sessions over several weeks. One group was given access to ChatGPT, another was allowed to use a standard search engine (Google), and the third had none of those tools, just their own brains. The researchers analyzed the texts they produced, interviewed the subjects immediately after they wrote the essays, and recorded the participants' brain activity using electroencephalography, or EEG. An analysis of the language used in the essays found that those in the "brain-only" group wrote in more distinct ways, while those who used large language models produced fairly similar essays. More interesting findings came from the interviews after the essays were written. Those who used their brains alone showed better recall and were better able to quote from their writing than those who used search engines or LLMs. It might be unsurprising that those who relied more heavily on LLMs, who may have copied and pasted from the chatbot's responses, would be less able to quote what they had "written." Kosmyna said these interviews were done immediately after the writing happened, and the lack of recall is notable. "You wrote it, didn't you?" she said. "Aren't you supposed to know what it was?" The EEG results also showed significant differences between the three groups. There was more neural connectivity -- interaction between the components of the brain -- among the brain-only participants than in the search engine group, and the LLM group had the least activity. Again, not an entirely surprising conclusion. Using tools means you use less of your brain to complete a task. But Kosmyna said the research helped show what the differences were: "The idea was to look closer to understand that it's different, but how is it different?" she said. Nataliya Kosmyna shares a picture of a research subject writing an essay while an EEG monitors the brain activity. The Washington Post/Contributor/Getty Images The LLM group showed "weaker memory traces, reduced self-monitoring and fragmented authorship," the study authors wrote. That can be a concern in a learning environment: "If users rely heavily on AI tools, they may achieve superficial fluency but fail to internalize the knowledge or feel a sense of ownership over it." After the first three essays, the researchers invited participants back for a fourth session in which they were assigned to a different group. The findings there, from a significantly smaller group of subjects (just 18), found that those who were in the brain-only group at first showed more activity even when using an LLM, while those in the LLM-only group showed less neural connectivity without the LLM than the initial brain-only group had. This isn't 'brainrot' When the MIT study was released, many headlines claimed it showed ChatGPT use was "rotting" brains or causing significant long-term problems. That's not exactly what the researchers found, Kosmyna said. The study focused on the brain activity that happened while the participants were working -- their brain's internal circuitry in the moment. It also examined their memory of their work in that moment. Understanding the long-term effects of AI use would require a longer-term study and different methods. Kosmyna said future research could look at other gen AI use cases, like coding, or use technology that examines different parts of the brain, like functional magnetic resonance imaging, or fMRI. "The whole idea is to encourage more experiments, more scientific data collection," she said. While the use of LLMs is still being researched, it's also likely that the effect on our brains isn't as significant as you might think, said Genevieve Stein-O'Brien, assistant professor of neuroscience at Johns Hopkins University, who was not involved in the MIT study. She studies how genetics and biology help develop and build the brain -- which occurs early in life. Those critical periods tend to close during childhood or adolescence, she said. "All of this happens way before you ever interact with ChatGPT or anything like that," Stein-O'Brien told me. "There is a lot of infrastructure that is set up, and that is very robust." The situation might be different in children, who are increasingly coming into contact with AI technology, although the study of children raises ethical concerns for scientists wanting to research human behavior, Stein-O'Brien said. You can have a chatbot help you write an essay, but will you remember what you write? ThaiWhy care about essay writing anyway? The idea of studying the effect of AI use on essay writing might sound pointless to some. After all, wasn't the point of writing an essay in school to get a grade? Why not outsource that work to a machine that can do it, if not better, then more easily? The MIT study gets to the point of the task: Writing an essay is about developing your thinking, about understanding the world around you. "We start out with what we know when we begin writing, but in the act of writing, we end up framing the next questions and thinking about new ideas or new content to explore," said Robert Cummings, a professor of writing and rhetoric at the University of Mississippi. Cummings has done similar research on the way computer technologies affect how we write. One study involved sentence completion technology -- what you might know informally as autocomplete. He took 119 writers and tasked them with writing an essay. Roughly half had computers with Google Smart Compose enabled, while the rest didn't. Did it make writers faster, or did they spend more time and write less because they had to navigate the choices proposed? The result was that they wrote about the same amount in the same time period. "They weren't writing in different sentence lengths, with different levels of complexity of ideas," he told me. "It was straight-up equal." Read more: AI Essentials: 29 Ways to Make Gen AI Work for You, According to Our Experts ChatGPT and its ilk are a different beast. With a sentence completion technology, you still have control over the words, you still have to make writing choices. In the MIT study, some participants just copied and pasted what ChatGPT said. They might not have even read the work they turned in as their own. "My personal opinion is that when students are using generative AI to replace their writing, they're kind of surrendering, they're not actively engaged in their project any longer," Cummings said. The MIT researchers found something interesting in that fourth session, when they noticed that the group who had written three essays without tools had higher levels of engagement when finally given tools. "Taken together, these findings support an educational model that delays AI integration until learners have engaged in sufficient self-driven cognitive effort," they wrote. "Such an approach may promote both immediate tool efficacy and lasting cognitive autonomy." Cummings said he has started teaching his composition class with no devices. Students write by hand in class, generally on topics that are more personal and would be harder to feed into an LLM. He said he doesn't feel like he's grading papers written by AI, that his students are getting a chance to engage with their own ideas before seeking help from a tool. "I'm not going back," he said.
Yahoo
an hour ago
- Yahoo
Sam Altman enters his dad influencer era by setting a baby crib trend
Sam Altman's endorsement boosted Cradlewise's site traffic in 24 hours. His recommendation of the Cradlewise crib also led to a peak in related Google searches. The crib, priced at $1,999, features a baby monitor and sound machine. Sam Altman can officially add "baby influencer" to his resumé. The OpenAI CEO announced the birth of his son in February, and shortly after shared his take on the parenting supplies he and his husband stocked up on before welcoming their baby. Some of it was "silly baby things" that weren't necessary. For one crib maker, however, the Altman shout-out paid off handsomely. "Definitely i recommend a cradlewise crib," he said in an X post. Within a day, Cradlewise's organic site traffic jumped by over 30% and it saw daily sales increase too, Radhika Patil, cofounder and CEO of Cradlewise, told Business Insider. Searches for Cradlewise over the past 90 days peaked the day Altman made his post on April 13, according to Google Trends. The company features Altman's post on its official website with the caption, "Sam Altman said it. We just bounced with it." Altman's crib choice retails for $1,999, a few hundred dollars more than that of its larger competitor, the Snoo. The Cradlewise bounces babies gently to soothe them, with a built-in baby monitor and sound machine. It also grows with your child by converting from a bassinet into a crib. "Sam Altman's mention of Cradlewise was a surreal and humbling moment for our team," Patil said. "But more than the numbers, what stayed with me was seeing a tech visionary resonate with a product built with empathy, intention, and science," Patil said. Read the original article on Business Insider
Business Insider
2 hours ago
- Business Insider
I'm a CEO running an 8-figure AI company. I'm also an extreme procrastinator — and I think that's a good thing.
This as-told-to essay is based on a transcribed conversation with Richard White, CEO of AI note-taking company Fathom. The following has been edited for length and clarity. Everyone talks about procrastination as a personal failing. I disagree. I'm an extreme procrastinator, and I've been building successful companies, like UserVoice and, most recently, Fathom, for 15 years. It's been one of my greatest assets as an entrepreneur. I see procrastination as ruthless prioritization in disguise. Consider procrastination as data collection Procrastination is a way to gather more information before making critical decisions. When I delay a choice, I'm not being lazy; I'm waiting for the optimal moment when I have enough data to make the right call. In college, I judged the size of a project and left it to the last achievable minute. I might have frustrated my peers or not gotten the most out of every seminar, but I'd do exactly what was needed and nothing more. Since then, I've learned to be more thoughtful about my approach. I used this philosophy to build Fathom, which now has an eight-figure valuation. We started building the company in 2020. Instead of rushing to market with whatever technology was available, we waited. We gathered data. We watched AI capabilities evolve. For example, prior to the rollout of GPT-4 and Claude 2, Fathom would yield basic call summaries. When GPT-4 was made available, we saw its capabilities and knew concerted investment on our side would yield massive gains. It was a foundation for our more advanced call summary features, and any earlier investment wouldn't have been as useful to our company. The same principle applies to my personal life. I plan trips at the last minute because I want to see what opportunities emerge, what's actually happening in my life, and what I might miss out on if I commit too early. In other work environments or even relationships, being a procrastinator can annoy people. However, the real and most common downside of procrastinating is underestimating the effort required and starting something too late to meet the deadline. As a CEO, I get to define the deadlines or, in our case, create a deadline-free environment. Urgent matters to trump important matters I've adopted an unfashionable approach for a CEO: urgent trumps important. This keeps our entire company moving forward without anyone waiting on me to make progress. It means that sometimes important but non-urgent things languish. I tell my team that if something's truly important, they should keep tagging me until I respond. This creates a culture where people at all levels in the company can advocate for what matters, and truly important tasks don't get lost. I've developed what I call the "Jenga model" for running my company. Like the game, when a piece looks too difficult or risky to move, I leave it and come back to it later. I can think about a problem and then put it back down without fear. Months later, I'll pick it up again, and suddenly, the answer falls right out. I'll prioritize problems that will get bigger with time, such as making an important product change, as well as problems where the solutions are low stakes or reversible. Higher-stakes decisions that are non-reversible should be deferred to gather data as long as possible, or broken out into lower-stakes decisions that help gather data to inform the larger issue. For product development, we circulate ideas internally while waiting for technological improvements. We don't rush features to market. Instead, we wait for the AI to get better, watch for what could go wrong, and optimize our timing. I don't think I have ever missed out on an opportunity. The reality in startups is that few things have a "hard" deadline. Implementing a deadline-free environment at Fathom means there hasn't been much negative feedback on this model. My team understands what we're prioritizing versus what we're doing later. CEOs need to play to their strengths Working alongside great entrepreneurs over the years has taught me that you can't build something around yourself that doesn't play to your strengths. My strength isn't planning or rigid schedules. My strength is recognizing optimal timing, gathering information, and making high-impact decisions. I delegate open-ended goals to my teams rather than micromanaging tasks. I encourage people at every level to make decisions. Most people think efficiency means doing things as quickly as possible. I think efficiency means doing things at the right time. You might be wrong about when something is needed or the time cost of execution, but that's the risk you take using your best collective judgment. This mindset has served Fathom incredibly well. We're exploring ways to use AI to take better notes, reduce unnecessary meetings, and democratize information sharing within companies. The next time someone tells you that procrastination is holding you back, ask yourself: Are you really procrastinating, or are you waiting for better information? Are you being lazy, or are you being strategically patient? Sometimes the best thing you can do is put the problem down and come back to it when you can solve it easily and effectively.
