👇 tl;dr

Today, instead of one photo, I share a full series. I also talk about education, imagination, intelligence, natural or artificial, and the evolution of wearable technology from a dream to (almost) reality over 14 years.

📷 Photo (series) of the week

Focus

The smartphone is the ultimate equalizer.

Age, gender, origin, or profession no longer matter; we are all identical when we focus on our mobile devices.

Check the full series on my blog.

👋 Good Morfternight!

School was pretty hard for me at the beginning. My mother taught me how to read before I got to school, and so when I got there I really just wanted to do two things: I wanted to read books, because I loved reading books, and I wanted to go outside and chase butterflies. You know, do the things that five-year-olds like to do. I encountered authority of a different kind than I had ever encountered before, and I did not like it. And they really almost got me. They came this close to really beating any curiosity out of me. —Steve Jobs

This quote comes from “Make Something Wonderful, Steve Jobs in his own words,” a free digital book by the Steve Jobs Archive. You can read it in your browser, in Apple Books, or download it for other e-readers.

The school experience for me was an entirely different beast. Early on, I found comfort in the system, coasting through from elementary to high school with great ease. Later, I realized that effortlessly achieving top grades, although satisfying, was pointless.

Why? Because I had spent twelve years mastering problems that had already been solved.

I later learned that in the real world, to create value, one must identify overlooked problems that people face and then find solutions for them.

Fast forward three decades, and I found myself following our two daughters through the same experience. Disappointingly, I must report that the system had stagnated, continuing to snuff out the spark of imagination rather than fueling it.

🗺️ A few places to visit

1. As we were talking about Steve Jobs, I feel compelled to share Tim Cook on Shaping the Future of Apple, a profile of the man who replaced him and, against all odds, made Apple an even more valuable company.

2. You might be familiar with “10x engineers,” who are so productive that they generate the value of 10 fellow engineers. They aren’t mythical creatures of the tech universe. They exist; I met some. Less spoken about but real all the same are the “-10x engineers.” An excellent read, tongue-in-cheek, but also very truthful.

3. I recently expressed my curiosity about the creativity emerging when everyone can program a computer. The article “A New Kind of Startup is Coming” shares a similar idea from a startup’s viewpoint. With AI reducing the cost of experimentation, how many unusual products will now come to life?

📺 Two videos, 14 years apart

A few weeks ago, snippets of Imran Chaudhri’s Ted talk circulated online. Chaudhri, a former Apple employee and co-founder of Humane, caught people’s attention. However, I decided to wait for the full video before sharing it, as I wanted to compare it with Pranav Ministry’s Sixth Sense talk from 2009.

Pranav Ministry’s demonstration was inspiring at the time. Seeing technology advance enough to implement such tools just fourteen years later is fascinating.

🤖 Are we there yet?

We stand at a fascinating intersection of possibilities in the realm of technology and artificial intelligence. We have seen tremendous progress in the field of AI with the advent of Large Language Models (LLMs) like GPT-4. But are we there yet? Have we reached the General Artificial Intelligence singularity (AGI)? The answer, as you might expect, is not as straightforward as a simple yes or no.

This question of whether we have achieved AGI is not binary anymore but rather a spectrum of progress and potential. Yes, we have made leaps and bounds in the field of AI, particularly with LLMs. They can understand our queries with precision, generate coherent responses, and even mimic creativity in ways we didn’t think machines could. But no, we’re not there yet.

This debate, like any conversation today, is highly polarized. Either we’re on the brink of AGI, or worse, or we’re merely dressing up complex algorithms and calling it intelligence.

In this high-stakes conversation, both evangelists and skeptics have their valid points.

I find myself not firmly planted on either side but rather treading the ever-shifting middle ground. As a result, I’m both exhilarated by the achievements we’ve made and vigilant about the challenges ahead.

It’s Not What They Say; It’s What They Hear.

Here’s the thing about these LLMs. Some people are excited about them, while others just see them as a hyped-up gadget. But to me, the whole debate is missing the point. Everybody is so focused on whether these things can give correct responses or not.

Sure, they’re not perfect. They’ve been trained on old data, they can’t check facts in real-time, and let’s not forget about the potential biases in the training data. Even we, the humans of 2023, struggle to fact-check our affirmations.

But do you know what makes these LLMs impressive? They understand what we’re saying with an almost spooky precision. Remember when we used to carefully craft our queries for Siri, Alexa, or Google to understand? Well, those days are behind us. LLMs understand us when we talk, and that, my friends, is the real revolution.”

For the first time in the history of computers, humans can use them without having to learn a computer-specific language.

What’s intelligence anyway?

But here’s the thing. There’s a lot of chatter out there saying that these models, these LLMs, are nothing more than fancy parrots. They just predict the next word, and that’s not real intelligence, they say. On the surface, that might seem like a reasonable argument. But let’s take a step back and think about it.

What do we, as humans, do when we’re having a conversation or making a decision? We take in information, process it based on our past experiences, and then predict the most appropriate response. Isn’t that just like what these models are doing? It makes you wonder if we’re not so different after all.

Universe in a box

At the core of their existence, LLMs are prediction engines. Given a set of words and some context, they predict what is most likely to come next. In a sense, these models simulate our linguistic universe by capturing the patterns and nuances of our human language.

Now, let’s take this concept of prediction and apply it to a completely different field: quantum physics. What if we had a machine so advanced that it could predict quantum states at the particle level? Given the state of a particle and its context, it could then predict the next state. It’s as if we would have a high-definition simulation of the physical universe right at our fingertips.

This idea of prediction, whether applied to language or the universe, is fascinating. It makes us question the nature of intelligence and existence itself. Is intelligence merely the ability to predict the next word or action based on a set of rules? Is the universe simply a series of predictable states following a set of physical laws?

And if we can extend this idea of predictive intelligence from language to the very fabric of the universe, then the potential applications of AI seem limitless.

Get Ready to Forget Everything You Know

Let’s take a journey into the worlds of analog and digital, using music as an example.

Each of these worlds has its own charm, its own set of rules, and its unique bests. In the analog world, we’ve retained vinyl but bid farewell to cassette tapes. Vinyl, with its nostalgic charm and warm sound, holds a place in our hearts that cassettes just couldn’t match.

Now, enter the digital world. Here, streaming has taken over CDs, becoming our go-to medium for consuming music. The convenience of having an entire music library at our fingertips is a clear winner over the physical limitation of CDs.

This evolution is a testament to how we embrace the best and let go of the rest.

And this brings me to a bold prediction: AI is set to take over the digital world. Our current apps, websites, and digital media might soon become this era's ‘audio CDs.’

We’re heading towards a future where AI will redefine our digital experiences in ways we might not yet fully grasp.

Conclusion

As we look to the future of AI, I can’t confidently say whether we’ll ever reach the singularity. What I can assert, however, is that we’ve taken a gigantic leap forward in our technological journey, a leap that will revolutionize our world regardless of whether we ever achieve AGI.

The advent of LLMs has changed the game. It’s like we’ve opened a new chapter in the story of human-computer interaction, one where computers don’t just follow instructions but understand our language and respond in kind. This is not science fiction anymore; it’s our reality.

This leap, however, comes with its set of challenges and responsibilities. We need to invest heavily in understanding these powerful tools we’ve created. We need to delve deeper into how they function, how they make decisions, and, most importantly, how they can be regulated and guided by ethical considerations. As we stand at this crossroads, it’s up to us to ensure the path we choose leads to a future where technology serves humanity, not the other way around.

AGI has moved from the realm of science fiction to a realm of possibility. As we stand at this intersection, we must remember that with great power comes great responsibility. It’s up to us to shape the future of AI, ensuring it’s a future where technology serves humanity, not the other way around.