Human-AI-Human Collaboration: Accessible and Scalable Growth
Accessibility is the cornerstone of both career growth and innovation. There’s often a significant gap between cutting-edge advancements in research and technology and their practical, real-world applications. This disconnect can frustrate everyday users, especially when thought leaders and hype muddy the waters, leaving many feeling left out. To bridge this gap, we need to focus on building transformative tools and fostering relationships—whether through accessible AI platforms or mentorship opportunities—that empower individuals to grow, rethink problem spaces, and push boundaries.
Collaboration is the key to driving meaningful outcomes. Whether human-to-human, human-to-robot, or human-to-AI interactions, these relationships allow us to combine strengths, overcome limitations, and achieve our intended impact. By making tools and systems accessible and fostering connections that challenge and support us, we can create a future where innovation is inclusive and transformative for everyone.
Thanks, NVIDIA: Big Wins at CES 2025 for Hard Tech Innovators
NVIDIA’s announcements at CES 2025 mark a big moment for AI and robotics, mirroring the transition from mainframes to personal computers. The $3,000 Digits personal AI supercomputer democratizes access to LLM development, breaking free from cloud-only constraints. This is a significant leap for researchers and enterprises, offering desktop access to powerful compute capabilities that simplify adoption and accelerate innovation. NVIDIA’s Cosmos platform further pushes the boundaries by enabling scalable data collection, simulation, and AI training for robotics. By addressing the challenges of data transformation and procurement, Cosmos helps robotics companies reduce overhead and risk while accelerating go-to-market strategies.
What’s most exciting is NVIDIA’s cohesive approach to embedding users within their ecosystem. Tools like Digits, Cosmos, and the Jetson lineup simplify the integration of onboard and centralized compute, creating a feedback loop that drives development. With robot hardware becoming increasingly commoditized, data and simulation are the real differentiators. NVIDIA’s platforms are paving the way for billions of robots to assist in diverse real-world applications backed by efficient fleet management and robust AI training pipelines. This shift is not just about tools—it’s about operationalizing robotics at scale.
On a personal note, I’m incredibly proud to see the work of my former team showcased on stages like CES alongside NVIDIA and Jensen. As the former CTO of 1X, it’s inspiring to see the robots and AI technologies we built together featured globally. These moments are a testament to hard tech builders' incredible talent and dedication, enabled by tools like NVIDIA’s platforms.
The State of AI: A New Baseline for Problem-Solving
The past month’s AI advancements are nothing short of transformative, signaling a paradigm shift in hard tech and how we approach problem-solving. Models once considered groundbreaking, like GPT-4, are now ubiquitous, with open-weight options like Meta’s Llama 3.3 and Microsoft’s Phi 4 bringing advanced AI capabilities to personal devices. This democratization of AI removes barriers, enabling new innovation pathways for autonomous agents and intelligent systems. But it’s not just about accessibility—it’s about a new baseline for what’s possible. As Ethan Mollick captures in his blog post, we’re in a moment that demands we step back and rethink how to approach problem spaces with this unprecedented level of computational intelligence at our fingertips.
What stands out to me—and why I believe in human-AI collaboration—is that these systems, while incredibly intelligent, lack wisdom. Think of them as the Skippy AI from Expeditionary Force or a character in Dungeons & Dragons with a 20 Intelligence score but minimal Wisdom. They’re book smart, with incredible memory and knowledge, but human wisdom brings understanding, context, and nuance. Together, we’re greater than the sum of our parts. These systems excel at processing and analyzing vast datasets while humans contextualize problems and develop meaningful solutions. This collaborative dynamic holds the potential to design impactful solutions to challenges we couldn’t have tackled before.
Mentorship: A Crucial Ingredient for Career and Technical Growth
Gergely Orosz’s post on mentoring is a great read, especially as we kick off 2025 and reflect on where we want to take our careers. While it’s focused on software engineering, the principles apply broadly to all types of engineering and even other career paths. Mentorship is central to growth, and finding the right mentor—a balance between a cheerleader and someone who challenges you—is essential. A great mentor pushes you to think outside the box, ask tough questions, and grow beyond your current perspective. It’s not about comfort but about expanding your boundaries and becoming more impactful in what you do.
I often share the idea that you’re either learning or earning in a career or job. Some roles pay so well that personal growth may take a backseat, while others are pure learning experiences. The key is being honest with yourself—if you’re not getting mentorship, growth, or meaningful compensation, it’s time to reassess. Personally, my best mentors have been the ones who didn’t just cheer me on but called me out when I was wrong, helping me avoid distractions like rabbit holes or reinventing the wheel. They taught me to focus on being impactful rather than just busy. As Gergely highlights, mentorship isn’t just about guidance—it’s about unlocking the next level in your career and delivering real value in your work.