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NVIDIA CEO's AI Advice You Can’t Afford to Ignore

Nvidia CEO Jensen Huang has one piece of advice for anyone trying to keep up with the future: Get yourself an AI tutor.

Over 80% of Fortune 500 companies have integrated ChatGPT into their workflows, and with more than 300 million weekly active users, AI tools have quickly become part of everyday work.

Still, not everyone is optimistic. A recent survey found that 40% of U.S. workers fear AI will replace their jobs, with 62% of Gen Z believing it could happen within the next decade. As AI takes on more tasks, concerns about job security continue to grow.

Huang, however, doesn’t see AI as a threat—he sees it as an opportunity.

“I’m surrounded by superhuman people and super intelligence… yet it never one day caused me to think, all of a sudden, I’m no longer necessary,” he said.

Most people rely on tools like ChatGPT and Perplexity for productivity and automation, but Huang sees another valuable use case that’s often overlooked: learning. He believes AI tutors can help people stay ahead by making knowledge more accessible and breaking down complex topics in a way that adapts to individual needs.

Rather than replacing workers, Huang believes AI will enhance their abilities, helping them learn faster and work more efficiently.

My take? People worry about AI taking their jobs, but the bigger risk is not knowing how to use it. The way I see it, using AI to learn will soon be necessary to stay updated and informed. The world is moving fast, and if you’re not using AI to build new skills and stay sharp, you’re the one falling behind.

Google’s X Wants to Grow Smarter Crops

Google’s moonshot factory, X, has launched its latest independent venture: Heritable Agriculture, a startup using AI and data science to improve crop yields.

Agriculture is an ancient industry, yet it remains one of the biggest environmental challenges we face today. It accounts for 25% of greenhouse gas emissions, consumes more freshwater than any other sector, and contributes to soil erosion and pollution.

Heritable is taking a different approach: Instead of modifying plant DNA with gene editing, it’s using AI to optimize traditional breeding, creating crops that yield more, need less water, and store more carbon. 

Here’s how it works:

Heritable’s AI models analyze plant genomes at scale to identify the best breeding combinations for stronger, more climate-resilient crops.

• AI-Powered Genomics: The system studies thousands of plant genomes to spot beneficial traits for farmers.

• Precision Breeding: Instead of genetic modification, the company focuses on traditional plant breeding with AI-driven selection.

• Field-Tested Insights: AI simulates plant growth to predict which varieties will perform best in real-world conditions.

This isn’t just a theory – the approach has already been tested across multiple locations, from Google X’s growth chambers to farms in California, Nebraska, and Wisconsin.

With climate change disrupting agriculture worldwide, AI-driven farming could prove to be very useful. Smarter crop breeding means higher food security, lower environmental impact, and better resilience to extreme weather.

While Heritable Agriculture is still in its early days, it has the potential to change the farming industry. Google has taken an undisclosed equity stake, and the startup has raised a seed round from FTW Ventures, Mythos Ventures, and SVG Ventures.

With AI in the mix, what if we could predict the best crops before they’re even planted? 🤔

Can We Trust an AI That Doesn’t Know Its Cheeses?

Google’s Super Bowl ad showed off its Gemini AI helping small businesses—but it also served up a hot mistake. In one clip, the AI confidently claimed that Gouda makes up “50 to 60 percent of the world’s cheese consumption,” which does not seem to be true at all.

A cheesy mix-up like this isn’t a big deal on its own, but when it happens in a Super Bowl ad seen by over 100 million people, it does make you think.

While Google defended the claim, sharing that the information came from several websites, some have pointed out how much we rely on AI tools like these for research, decision-making, and important work—where accuracy matters a whole lot more. Do we trust AI too much?