A Better Tech #8

Namaste🙏

“Now is the most important time,” Jensen Huang responded when journalists asked why he doesn't wear a watch. This resonated with me as I have not worn a watch for ages as well.

Nvidia has achieved an extremely crazy feat. Originally designed as a GPU to accelerate graphics processing for gamers, it has become the ultimate machine for processing AI computation. The math needed to build complex AI systems dovetails with how graphics chips work—by doing many calculations at once.

Jensen Huang has made Nvidia the most valuable company, with a $3 trillion valuation. Its order book contains one year's worth of sales, it commands a 76% gross margin, and it has increased investor wealth multifold.

Jensen Huang achieved this incredible position for himself and Nvidia with persistence. He told a Chinese semiconductor professionals group recently, “I’m not very fast, but I’m very persistent, I work on something for a very long time. So it allows me, if I choose problems and our company chooses problems that are very hard to do, we have a long time to work on them.”

Here are some of the interesting reads I have found, read and enjoyed this week:

7 Tips to Crush Your Onboarding from an Apple Staff Engineer

A Staff Engineer at Apple shares seven tips to help you successfully onboard in a new company. Key points include creating a 30/60/90-day plan, setting daily goals, finding an onboarding buddy, identifying key people to network with, securing a mentor, embracing the company culture, and networking beyond your team.

Follow the strategies to accelerate career growth, build confidence, and foster strong professional relationships.

Ask HN: What would you spend your time working on if you didn't need money?

Most of us do our jobs because we need to earn our livelihood. This discussion thread on Hacker News takes down the imaginary lane, asking what your ideal job would be if you didn't have to make money. Would you contribute to making society more rational, healthy, and well-coordinated? Or do you have better ideas?

Ask HN: What would you spend your time working on if you didn't need money?

What We Learned from a Year of Building with LLMs (Part I)

While the barrier to entry for building AI products has lowered, creating something effective beyond a demo remains a deceptively difficult endeavour. This article dives deeper, finding key insights into the experiences and challenges faced by developers working with large language models (LLMs) over the past year. The main takeaways include recognising the substantial computational resources required to train and deploy these models and the complexities involved in fine-tuning them for specific applications. The authors emphasise the importance of understanding the limitations and biases inherent in LLMs and the need for robust evaluation frameworks to assess their performance effectively.

How AI will create more successful founders

AI has a huge new opportunities open up for founders that get in on the ground floor. Fortunes were made when the app store came out, when online payments became easy, and when the web itself was brand new.

Watch the YouTube video to learn about the opportunities created by the advancements in AI and also create products and services that were previously unimaginable. The key highlight is understanding the importance of adapting to and embracing new technologies to remain competitive in the evolving business landscape.

That's it for this week.

I am eager to get your feedback on this newsletter.

Best Always,

Ishwar Jha