Are we at the "knee" of the AI curve?

My 7-year old was peeking over my shoulder this weekend as I was recording a walkthrough video for creating models using Teachable Machine, and she was intrigued to see me “teach AI”. I asked her to take in what she saw and think of something that she would want to solve, something that nags her everyday. She came to be after a day and asked me if AI could make a pill for cancer. As I proceeded to say no, I thought for a moment - maybe not now, but with the advancements of AI in clinical trials, it could very well be a possibility!

Speaking about possibilities, Ayesha, CTO of Flintolabs, sent me this blog and as I read through it, I found myself going down a rabbit hole about the Singularity. Sam Altman writes about how humans and AI will eventually merge, not in some distant sci-fi future, but perhaps within our lifetimes. This led me to Ray Kurzweil's "The Singularity Is Near," where he predicted (in 2005) that by 2045, machine intelligence would merge with human intelligence in ways that irreversibly transform human capability. What struck me most was Kurzweil's concept of the "law of accelerating returns" - the idea that technological progress doesn't advance linearly but exponentially, appearing nearly flat at first until it hits what he calls "the knee in the curve," then rises almost vertically. Looking at how AI has evolved just in the past two years, I can't help but wonder if we're approaching that knee right now, making the question of how we prepare today’s students more urgent than we realize.

-Janani

Registration Deadline: January 2026
Competition Period: January - April 2026

What: The Conrad Challenge invites students to design practical solutions for pressing global issues like renewable energy, healthcare, cybersecurity, and food security. Blending entrepreneurship and innovation, this competition challenges students to create business-ready innovations that address real-world problems.

Who: Students aged 13-18 worldwide, working in teams of 2-5 members

Format: Multi-phase competition including concept submission, semi-finals, and finals where top teams present their innovations. Teams develop comprehensive business plans alongside technical solutions.

Focus Areas:

Prizes:

What Makes It Special: Past participants have launched successful startups from their Conrad Challenge projects, showcasing the competition's focus on real-world impact. Winners gain access to an extensive network of entrepreneurs, investors, and industry leaders.

Perfect for: Students passionate about using innovation and AI to solve meaningful problems while developing entrepreneurial skills. Ideal for those ready to move beyond classroom projects to create solutions with genuine market potential.

According to Cengage Group's 2025 AI in Education report, 65% of higher ed students believe they know more about AI than their instructors, and 45% wish their professors actually taught AI skills in relevant courses. The data reveals a striking disconnect in AI education.

Students aren't just asking for AI access - they're asking for guidance. While 69% of high school students reported using ChatGPT for assignments in May 2025, many feel unprepared. Research shows that 58% of students report insufficient AI knowledge or skills, and 48% don't feel ready for a workforce that relies heavily on AI technologies.

The gap isn't about student capability. It's about institutional readiness. Students quickly moved beyond using AI as a shortcut for cheating to recognizing its potential as a powerful learning tool. The Teen and Young Adult Perspectives on Generative AI report shows the most common uses of GenAI are now gathering information (53%) and brainstorming ideas (51%).

What students need most isn't restrictions - it's structured, ethical guidance on responsible AI use. They want to understand how AI systems work, recognize their limitations, apply them critically, and engage in informed dialogue about societal impact. As one student noted: "Not all kids use it to cheat in school."

The reality? AI literacy has become foundational for academic and professional success. Students are immersed in AI regardless of institutional policy. The question isn't whether to teach AI - it's whether schools will provide the guidance students are actively requesting.

Read more: AI's Impact on Education in 2025

Universities across the country are racing to make students "AI fluent." Ohio State promises every graduate will be fluent in AI applications. Schools everywhere are rolling out AI literacy programs, frameworks, and requirements.

There's just one problem: nobody actually knows what AI fluency means yet.

According to Justin Reich from MIT, we're seeing a familiar pattern. A new technology emerges, experts hastily define skills around it as a "literacy," and schools rush to teach it before anyone really understands what needs to be taught. We've been down this road with tablets, smartphones, and social media - and the results speak for themselves.

Here's what makes AI different and harder: generating AI content is easy. The real challenge is knowing when that content is good or garbage. Can students distinguish between a hallucination and a genuinely useful insight? Can they spot when AI has confidently delivered complete nonsense?

Reich argues that the students best prepared to evaluate AI output won't be the ones with "AI fluency training." They'll be the ones with deep knowledge in their actual disciplines. You don't need special AI training to know if a historical claim is accurate - you need to actually understand history.

Instead of rushing to proclaim what AI literacy is, Reich suggests we should lead with our uncertainty. We should experiment, explore where AI proves genuinely useful, and figure out together what practices actually help versus harm learning.

Most importantly, we should avoid confusing speed with learning. Yes, AI makes students produce work faster. But does faster mean they've actually learned anything?

What works? Hands-on experimentation with real projects. Students who build actual applications, make mistakes, debug problems, and figure out through experience where AI helps and where human thinking is irreplaceable - these students develop genuine understanding that no checklist can provide.

The future doesn't belong to students who completed an "AI fluency" checklist. It belongs to those who learned how to think critically, evaluate carefully, and adapt continuously.

Read the full post: Mastering the Art of Teaching AI

Ever let a voicemail sit for days because you just couldn't deal with listening to it? Or worse - missed something important buried in a long, rambling message?

This week, we're highlighting Rishi Madiraju, a 10th grader from New Jersey who recognized a problem we've all experienced: voicemail is broken. In a world where we text, email, and message instantly, voicemail feels stuck in the past. You can't scan it quickly, you can't search it, and you definitely can't prioritize which ones actually matter.

So Rishi built an AI-powered voicemail assistant that transforms how we handle voice messages.

Here's how it works: the AI automatically transcribes every voicemail, extracts key information like names, dates, and callback numbers, categorizes messages by urgency and topic, and provides quick summaries so you can scan messages in seconds rather than listening to each one.

Think about the applications: busy professionals who need to triage dozens of voicemails, students managing calls from colleges, internships, and part-time jobs, anyone juggling multiple responsibilities who can't afford to miss critical information, people with accessibility needs who benefit from text over audio.

Rishi's solution demonstrates a key principle of effective innovation: sometimes the best ideas come from fixing everyday frustrations rather than chasing flashy new concepts. He saw a pain point everyone experiences, recognized that AI could solve it elegantly, and built a practical tool that genuinely improves people's lives.

As one potential user noted: "This would be a game-changer for anyone in customer service or sales who gets bombarded with voicemails daily."

Watch Rishi's pitch and like/comment: Student Pitch - AI Voicemail Assistant

Our November cohort is already building real AI applications and discovering what hands-on AI learning actually looks like. These students aren't just learning about AI - they're using it to solve genuine problems. They

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That's right - your high schooler can earn real, transferable college credit from an accredited university while building hands-on AI skills, all with just one hour per week of commitment.

The future belongs to students who can work with AI effectively - not just use it, but understand when and how to apply it strategically.

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