Drivers are also disappearing from vehicles

One of the developments in the automotive world that has caught my attention most recently is the Tesla Cybercab. The first new model Tesla has developed in years has no steering wheel, no gas pedal, and no brake pedal. The vehicle is designed from start to finish for autonomous driving. Elon Musk is positioning this model as the cornerstone of a robotaxi service. As someone who follows automotive history closely, I can say this: This is not just a new model, but a step that changes the very idea of the automobile. Because for a hundred years, the automobile has been designed with the driver at the center. With the Cybercab, for the first time, the driver is being removed from the design entirely.

The interesting part of this transformation is that it is not just technology companies but also traditional manufacturers entering this race. For example, Mercedes-Benz appears quite ambitious on the autonomous vehicle front following its electric transformation. Models like the Mercedes-Benz VLE and Mercedes-Benz VLR, which will be featured on the new generation platforms the company is working on, are signs of this. In contrast, another part of the industry still revolves around modification, exhaust sound, and classic performance culture. The culture formed around brands like Audi, BMW, or the Volkswagen Passat still centers on the driving experience. My impression is this: The automotive world is divided into two different eras. On one side, the driver behind the wheel is still being discussed, while on the other, the steering wheel itself is disappearing. That is why it is not just parts that are disappearing from cars in this new era. The driver themselves is slowly being removed from the equation.

Does Higher Education Guarantee You a Job?

For many years, a university diploma was seen as the most reliable door to the business world. However, in recent years, this assumption is being questioned more and more. An analysis published in the Harvard Business Review shares a striking piece of data: More than 40% of young people aged 25-34 in OECD countries, and nearly 50% in America, are university graduates. Education still has a positive impact on income. However, as the number of graduates increases, the additional advantage provided by a diploma gradually decreases. Indeed, according to the same study, while a university diploma increases income by more than 20% in Sub-Saharan Africa, this increase remains at only around 9% in Scandinavian countries, where university graduates are very common.

What is more interesting is this: Research shows that the relationship between education level and job performance is quite weak. In contrast, cognitive ability, learning capacity, and problem-solving skills are much stronger indicators. The business world has begun to realize this as well. Today, many companies look for learnability, curiosity, communication skills, and adaptability in candidates rather than a diploma. In other words, a diploma may still be useful; however, it is not a career insurance policy on its own. For universities to maintain their value in this new world, they need to stop being institutions that only transfer information and become places that develop human skills such as critical thinking, empathy, and leadership.

Einstein Was Right Again

In my childhood, I had a great admiration for Isaac Asimov's books. One day, I got my hands on "Exploding Suns," which was published in Turkish under the title "Patlayan Güneşler." I had started reading it thinking it was science fiction, but it was actually a popular science book explaining how stars are born and how they die. At that age, I couldn't understand most of it. Years later, when I took an astrophysics course from John Freely at Boğaziçi University, I realized that my childhood curiosity had actually touched on the right place. I had enjoyed the course immensely; my grade was an A. But my real gain was not the grade, but an unending curiosity about the universe.

A news story I read in Gazete Oksijen the other day reminded me of this curiosity again. The story described how astronomers observed the existence of a newborn *Magnetar* by studying an extremely bright supernova named SN 2024afav. It is stated that the strange vibrations in the light show that this massive, rapidly rotating body drags space-time along with it. In physics, this is called Lense–Thirring precession, and this effect was predicted exactly a century ago in Albert Einstein's theory of General Relativity. In short, the universe described in those books I struggled to understand as a child is being confirmed by telescopes today. And with every new observation, the same sentence is formed again: Einstein was right again.

Sinan Canan Stalled While Trying to Produce Philosophy Through Artificial Intelligence

I heard Sinan Canan make an assessment in a speech about artificial intelligence, saying, "these are actually language models, people who do not know how to use language correctly cannot use artificial intelligence efficiently." Saying "artificial intelligence is actually a language model" is a finding that even the person on the street knows today. There is not much point in presenting this as if it were a special discovery. Yes, systems like ChatGPT or Claude that we use today are technically built on Large Language Model (LLM) architectures. Transformer-based neural networks, billions of parameters, massive datasets, and huge GPU clusters constitute the engineering behind these systems. However, repeating this technical fact does not mean explaining what artificial intelligence is changing.

The problem starts right here. When you confine artificial intelligence only to the "language model" framework, you miss the real breakthrough of the technology. What LLMs do is not just process language; it is to reunite the linguistic fragmentation that humanity has experienced since the Tower of Babel in a mathematical representation space. Different human languages are becoming meaningful within the same semantic field. Moreover, this is not limited to human languages. The same systems can switch between programming languages, generate code, and free software developers from being confined to the limits of a single language. Therefore, saying "those who cannot use language well cannot use artificial intelligence" is reading the issue backward. The real power of artificial intelligence lies in its ability to compensate for human language flaws. That is why, instead of reducing the discussion to the level of grammar, it is necessary to talk about how artificial intelligence is changing humanity's information architecture. Perhaps what Sinan Canan was trying to do was to produce philosophy; but it appears that he stopped at the very beginning of the road and turned back.