Growth Ritual #65
📋 IN THIS ISSUE: AI’s Unexpected Champions ~ Voice-Controlled Revolution ~ China’s Silent Sprint Toward General AI ~ A Lost Language in Knots
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AI’s Unexpected Champions: Non-Techies Leading the Charge
You’d think the biggest AI fans would be coders or data scientists, right?
Nope!
The study titled “Lower Artificial Intelligence Literacy Predicts Greater AI Receptivity” published in the Journal of Marketing and conducted on 19,000 people flipped that assumption on its head.
It turns out, folks with lower technical knowledge of AI are 31% more likely to use it daily.
Why?
Because they see AI as a bit magical—like a trusty sidekick that makes life easier without needing to understand the nuts and bolts.
They’re not sweating the tech details—they just want tools that make life easier.
This trend is reshaping how we think about AI adoption, especially in non-tech industries.
Let’s unpack why this matters and what’s driving it.
Survey Insights: The 2025 study, spanned 28 countries and included diverse demographics, from students to small business owners. It found that 62% of low-AI-literacy users (those with basic or no understanding of AI mechanics) used AI tools daily, compared to 47% of high-literacy users.
The “Magic” Factor: Non-tech users often view AI as a near-magical helper. Tools like Grammarly, Canva’s AI design features, or ChatGPT feel like shortcuts to getting stuff done—whether it’s drafting emails, creating presentations, or writing school essays.
Task Adoption:
Writing Assistance: 74% of low-literacy users relied on AI for writing tasks, like emails or reports, compared to 53% of tech-savvy users.
Creative Work: Tools like MidJourney for art or Jasper for content creation were popular among non-techies, who used them 28% more than tech experts.
Daily Convenience: From AI-powered shopping recommendations to voice assistants like Siri, non-tech users embraced AI for quick, practical solutions.
Marketing Opportunities: Companies are catching on. By targeting non-tech sectors like retail, education, or healthcare, firms can pitch AI as a time-saver. For example, a restaurant owner might use an AI scheduler to manage bookings, while a teacher could generate quizzes in seconds.
Why It Works: Non-tech users are less skeptical about AI’s limitations and more focused on results. Their willingness to experiment drives adoption, with daily usage rates climbing as tools become simpler. In 2024, global generative AI users hit 250 million, showing how mainstream this tech is becoming.
This trend flips the script on who’s shaping AI’s future. It’s not just coders—it’s everyday people, and businesses smart enough to market to them will ride the wave.
Superwhisper and the Voice-Controlled Revolution
Imagine ditching your keyboard and just talking to get work done.
That’s where Superwhisper comes in, a voice-controlled AI that’s making typing feel like a chore from the Stone Age.
It’s not just about transcribing—it’s about streamlining how we work and communicate in over 100 languages with crazy accuracy.
Core Features:
Multilingual Mastery: Supports 100+ languages, from Spanish to Swahili, with real-time transcription accuracy hitting 95% in optimal conditions.
Custom Modes: Users can set specific instructions, like “format meeting notes as bullet points” or “exclude sensitive terms for privacy.” This makes it adaptable for everyone from CEOs to students.
On-Device Processing: All data stays local, ensuring top-notch security. No cloud uploads mean no worries about data breaches.
Use Cases:
Professionals: Lawyers dictating case notes, doctors recording patient summaries, or executives drafting emails hands-free.
Students: Transcribing lectures or brainstorming essays aloud, cutting study time by up to 30%.
Multitasking: Busy parents or freelancers can jot down ideas while cooking or commuting, reducing “typing fatigue” (that wrist ache we all know too well).
Productivity Boost: Early 2025 user reviews report saving 2-3 hours daily by using Superwhisper for tasks like meeting summaries or content creation. A study by TechTrend Analytics found voice AI users were 40% more efficient at repetitive tasks.
Why It’s Game-Changing: Voice tech leverages advances in natural language processing (NLP), with models like Whisper (Superwhisper’s backbone) trained on massive datasets. This ensures it catches nuances, accents, and even slang, unlike older systems that stumbled over anything but perfect diction.
Future Outlook: Voice-controlled AI is projected to grow 25% annually, with tools like Superwhisper leading the charge. By 2030, 60% of workplace interactions could be voice-driven, especially in hybrid work setups.
Superwhisper isn’t just a tool—it’s a glimpse into a world where our voices, not our fingers, drive tech. It’s making work faster, easier, and honestly, kinda fun.
China’s Silent Sprint Toward General AI
While we’re all jazzed about voice tech, China’s been quietly building an AI empire that’s got the world’s attention.
Their goal?
Be the global AI leader by 2030, with a focus on artificial general intelligence (AGI)—AI that can think, reason, and act like a human across any task.
With billions invested and 30 institutions pushing open-source research, China’s playing the long game. Here’s the scoop.
National Strategy: Launched in 2017, China’s AI plan aims for global dominance by 2030. It includes:
Funding: Over $20 billion annually in AI research, dwarfing most countries’ budgets.
Talent Pool: Training 500,000 AI researchers and engineers by 2030, with top universities like Tsinghua leading the charge.
AGI Focus: Developing “general AI” that can autonomously handle complex tasks, from medical diagnosis to urban planning.
Generative Models: China’s betting big on large language models (LLMs) like Baidu’s Ernie or Alibaba’s Tongyi Qianwen, seen as stepping stones to AGI. These models rival Western counterparts, with Ernie 4.0 reportedly matching GPT-4 in some benchmarks.
Supermind Platform: A 2024 Newsweek report highlighted China’s “Supermind” an AI system tracking global researchers to accelerate innovation. It’s a bold (and slightly controversial) move to stay ahead.
Open-Source Edge: Unlike some Western firms hoarding tech, China’s 30+ institutions share research on platforms like GitHub, driving global collaboration. In 2024, Chinese researchers published 40% of top-tier AI papers, per Stanford’s AI Index.
Global Concerns: The push for AGI sparks ethical debates. Experts worry about autonomous AI’s potential misuse, like in surveillance or military applications. X posts reflect mixed sentiment—some praise China’s innovation, others fear a lack of oversight.
Impact: China’s work is accelerating AI’s global evolution. Their open-source contributions mean even Western startups benefit, but the race to AGI raises questions about who’ll set the rules.
China’s AI surge is a wake-up call. They’re not just keeping up—they’re setting the pace, and the world’s watching closely.
Decoding the Inca Khipus: A Lost Language in Knots
Now, let’s travel back 500 years to the Andes, where the Inca empire left behind a mystery: khipus.
These knotted cords of cotton and animal hair aren’t just artifacts—they’re a potential Rosetta Stone for a lost civilization.
Anthropologist Sabine Hyland is leading the charge to decode over 1,400 khipus, and recent discoveries are sparking excitement. Let’s untangle this ancient puzzle.
What Are Khipus?:
Structure: Bundles of cords with knots, colors, and twists, often made from cotton or alpaca hair. Each khipu can have dozens of cords, some with up to 1,500 knots.
Purpose: Long thought to be accounting tools for tracking goods (like livestock or taxes), but new evidence suggests they encoded narratives, laws, or even poetry.
Scale: Over 1,400 khipus exist in museums and private collections, with 650 new finds since 2010, per Hyland’s research.
Recent Breakthroughs:
Collata Khipus: In 2018, Hyland studied khipus from San Juan de Collata, Peru. Their 14 colors and 95 cord patterns suggest a logosyllabic system, where knots and colors represent syllables or words, like Mayan glyphs.
Narrative Potential: AI analysis of 800+ khipus revealed grammatical patterns, hinting at stories or messages, possibly about resistance to Spanish colonizers.
Color Coding: Hyland’s work in Jucul village found khipus with specific color sequences (e.g., red-blue-white) that may denote names or verbs, not just numbers.
Decoding Challenges:
Complexity: Khipus have up to 2,000 unique knot types and color combos, requiring statistical models and cultural context to decipher.
Fragility: Many cords are degraded, tangled, or incomplete, making analysis a logistical nightmare.
Cultural Gap: Without a “key” (like the Rosetta Stone), scholars rely on Andean oral traditions and Spanish colonial records, which are often biased.
Why It Matters: Decoding khipus could reveal Inca history—laws, stories, or rituals—directly from their perspective, not Spanish accounts. It’s also a cultural lifeline for Andean communities eager to reclaim their heritage.
Tech’s Role: AI tools are helping map knot patterns, but human insight remains key. Hyland’s team combines linguistics, anthropology, and data science for progress.
The khipus are a reminder that technology isn’t just silicon—it’s any system, from AI to ancient cords, that captures human thought. If Hyland cracks the code, we’ll hear the Incas’ voices again.