First off: this thing is a blast to drive. I got the performance model with >500 HP and a 0-100 km/h acceleration of 3.4 seconds. To this day I can’t hide the “Tesla grin” when accelerating.

Sometimes I open the rear camera while at a stop just to see how small the car behind me gets once the traffic light turns green and I floor it. It’s also safe insofar as it allows for quick acceleration in tricky situations.

Unsurprisingly this is one of the first things I demonstrate to people sitting in a Tesla for the first time. The reactions are always one of the two comments: “Holy shit this feels like an airplane taking off” or “Holy shit this feels like the Blue Fire Megacoaster”.

Another feature I love to demonstrate is summoning the car which is especially useful in my garage since it has a tight parking spot; wide enough for the car but not wide enough to easily get in/out of the car without doing some involuntary yoga exercises. The Tesla gets out/parks into the spot on its own daily.

What about long distance trips? This car works as a daily driver just as well as for road-tripping. I’m surprised some people still aren’t aware that Tesla has a vast Supercharging network allowing for quickly topping up one’s car. See here.

More Superchargers are constructed on a monthly basis.

I’ve driven:

• Zurich - Vienna - Zurich
• Zurich - Calabria - Zurich (~3000 km total)

without any issues.

The road-trip to Calabria took us 19 hours (my brother and I weren’t in a rush and spent over an hour in a restaurant despite the car having reached 100% state of charge for a while). We stopped 7 times for charging sessions of ~15-20 mins each.

Those charging stops were also used as bathroom and breakfast/lunch/dinner breaks. Therefore our 19h trip consisted of over 16h of driving and about 2 hours of (productive) charging + 1 hour spent in a restaurant (where the car patiently waited for us, fully charged). We arrived refreshed at our destination since Autopilot did about 99% of the driving.

Due the fact that we used a referral code (thanks @NYKChannel) granting us 6 months of free supercharging the trip did not cost us anything in terms of electricity.

Speaking of electricity, 1300 kWh were added to the battery during this year just via regenerative braking. Coincidentally, this is the amount of electricity our household (my brother and I) uses in a year! The fact that this causes a longer lifetime for the brakes is also quite nice.

So what about charging without the Supercharging network? Unfortunately I can’t charge at home, however, there’s a charging station 500 meters from my home which I basically never use. Why? Because I already charge at various destinations.

E.g. when I go bouldering, there’s a charging station in a garage close-by. When I do @Freeletics with friends in Zurich, there’s a charging station near-by, when I go indoor skydiving at @Windwerk_Winti there are free charging stations provided by them.

~100 meters in either direction from @Windwerk_Winti there are two more free charging stations. Also, I spend less time actively charging (i.e. plugging in), than I used to spend filling up my gasoline car during daily use.

The fact that electricity is cheap is convenient. Using @EnBW’s card, I pay 0.28€/kWh which amounts to about 22€ (~26$) per full charge (480 km / 300 miles range). But most of the time I use free charging options, such as the one provided by @StadtwerkWin which offers electricity generated via solar 🌞.

Sometimes I do what I refer to as “car-office”. The Tesla is comfortable and it has an impressive audio system which is amazing when watching YouTube or Netflix via the car’s own 15” screen, so I’m inclined to spend time in the car while charging.

The audio is comparable to a cinema imho. Sometimes I review the dash cam or sentry footage which the car records while driving or while being parked and someone getting too close to the car.

Thanks to this feature I caught someone bumping into the front of my car while it was parked and she was reversing out of the parking spot. The license plate is visible and perfectly readable. Aside from that I have 20GB of footage of curious people checking out the car.

YouTube, Netflix, Sentry Mode, games etc. are features provided by Tesla via free over-the-air updates. That’s another thing making a Tesla a blast to own. I get around 2 updates/month providing new features, games, power (e.g. +20 HP) or improvements suggested to @elonmusk etc.

As a software engineer, I love playing with Tesla’s APIs and data. The API shows data about the car’s status and location and with an OBD2 dongle I have a vast amount of live data (e.g. current torque of each motor, battery cell temperatures and voltages etc.)

Recently the rear window got chipped (looks like there was an impact there but I can’t tell what caused it). There are lots of stories about waiting for spare parts from Tesla taking weeks to months.

I informed @diemobiliar about the damage and they referred me to Desa Autoglass. Apparently the rear window was available in a few days (less than a week). I was able to bring my car to Desa Autoglass and they replaced the huge rear window in ~2 hours.

Everything worked flawlessly, @Tesla quickly had the part available and @diemobiliar quickly referred me to Desa Autoglass in Winterthur which did a great job. I didn’t have to pay anything but was surprised to learn the rear glass cost less than 500.-.

So, what are the actual disadvantages with a Tesla? The only negative experience I had with Tesla was the delivery experience & customer support. The delivery process a year ago was pure chaos, I was informed that my delivery should take place in March.

March passed and I did not receive any further info. No communication whatsoever, Tesla was just silent. Ended up going to the delivery center 3 times and finally got a loaner Tesla Model S until the Model 3 was ready for pickup in June 2019.

When I had an issue logging into my account neither the service center nor delivery center were able to help. Had to send an email to Tesla, but was never answered after months of follow-up. Finally someone in the delivery center wrote an email to the same email address and got an answer.

In order not to end on a negative note, I’d like to stress that the positives far outweigh the negatives and I would definitely buy a Model 3 again, even if it meant the chaos during the delivery process would repeat itself (which they seem to have fixed by now).

Thank you @elonmusk and @Tesla team for such an enjoyable, incredible, amazing and fun car. I will never be able to go back to an internal combustion engine car.

Thank you for accelerating the world’s transition to sustainable energy! ☀️🔋🚗🌱

Bonus: The frunk even fits a Swiss Army rifle!

Bonus: Cats seem to like the Tesla too.

This blog post is following my first blog about A.I. After 14 weeks I am writing about my views concerning AI, referencing my first post, i.e. how my views have changed or stayed the same. The lectures about artificial intelligence have thaught me a lot and I would like to share some of the nuggets I got to know.

First off, the relevant article for this conclusion¹ is one that is supposed to change my views or at least nudge them into a different direction, than the articles I referenced in the first blog post. The topic is partially about how wrong we are, when it comes to making predictions about A.I. to which I tend to disagree.

My post-A.I.-module-1-course-views

If people like Elon Musk and Ray Kurzweil make bold predictions about the future of A.Is. and how we need to be wary of their development is not something to be taken lightly in my opinion. We have to reconcile this with the fact that Elon Musk owns OpenAI - a company devoted to progressing the development of A.I. and democratizing such advancements by making those accessible to the public. Musk thus has very detailed day-to-day insights into the wide A.I. topic. If he issues warnings, it is definitely warranted.

Even though I now have insight into some Machine Learning techniques and how much manual labor is still involved, i.e. to clean the data and employ the correct ML method, I still belive that an AGI is not too far away. My educated guess would be that AGI is reached in a few decades if not years, but no order of magnitude greater than that. Once AGI is in place, ASI won’t be far away either by having AGI develop a smarter intelligence. I think this effect of exponential progression is not to be underestimated.

Keep in mind that ML is very hot right now and money is being thrown at the buzzword alone. While this certainly attracts bullshitters, it will likely benefit some serious A.I. undertakings. This will move us in a faster pace towards AGI, on a year-to-year basis.

Interesting Lessons

Thanks to our artificial intelligence course at ZHAW I got to know a wider range of A.I. applications than I used to know. I was aware about Machine Learning and its subcategorization in supervised, unsupervised, neural networks, deep learning, etc. However I was less informed about the simpler types of A.I.

Two things I first heard of during the lectures and of which I greatly enjoyed the concepts are Constraint satisfaction problem and Prolog.

Constraint satisfaction problem is a way to solve a problem by setting enough constraints, to make the solution evident to the computer.

Three constraints of type “unique constraint” would be sufficient to solve a Sudoku practically immediately. You just need to tell the CSP library to make the vertical, horizontal and 3x3 fields unique.

Prolog works similarly but allows much richer statements, since the programmer can define its own keywords and then create references and inferences, allowing the problem to be solved “automagically” by the computer, following the established logic in the Prolog language.

Conclusion

I am hopeful and positive that the A.I. future will be a good one. Another industrial revolution, once again removing more rather low-skilled labor jobs but this time it will also hit white collar jobs. However this, as always, will enable humanity to go one step beyond menial tasks once again and find more meaningful work.

We are still a lot of years away, until we will ever face a true AGI. But I strongly belive that we will get there sooner than later. And instead of ignoring or belitteling this topic, we should all pay close attention, embrace this revolution, prepare for it, deal with the risks beforehand, make legislature aware and prepare for possible effects on a rather big chunk of the labor force facing automation, e.g. by seriously discussing universal basic income. It won’t be easy, but if we’re serious about it, I’m sure we’ll be moving towards the most prosperous phase of humanity yet.

At ZHAW I’m taking a class on artificial intelligence. This blog post is part of the course and mainly discusses the waitbutwhy article which constitutes a mandatory reading for the course.

Types of A.I. Thinking

There are many ways of how a superintelligence can spring into existence as shown with the test-taking-kid analogy in the blog article¹, in which the author explains that we might try to write an A.I. fit for taking such a test, or we could make the test take itself. The difference is that some ways of thinking revolve around making A.I.s that help and guide us through our day, whereas another way of thinking is about creating A.I.s that would do everything by themselves and render us obsolete.

Simulate the Brain?

The human brain project showed how difficult it would be to create an A.I. simulating the whole brain, especially considering that right now we barely have the computing power to simulate 1 second of human brain cognition, but once this is possible, an A.I. could operate much more efficiently since our synapsis pathways are limited to 120m/s whereas simulated neurons in an A.I. could virtually travel at the speed of light, rendering thought processes a lot faster, if not better.

A.I. Levels

Artificial Narrow Intelligence

A.k.a. ANI is a limited intelligence able to complete specific tasks efficiently such as playing chess. This has been around for a while now and can be found in a lot of different computer games.

Artificial General Intelligence

A.k.a. AGI is a general intelligence able to operate at a level of a typical human. Experts suggest that it wouldn’t take long going from an AGI to an ASI using recursive improvement methods, e.g. the AGI is tasked with creating a smarter intelligence which in turn is tasked with the same ad infinitum until the result will be an ASI.

Artificial Superintelligence

A.k.a. ASI is a superintelligence able to operate at order of magnitude higher intelligence than humans. There are many possile scenarios and theories how such an intelligence would operate and what would happen to us humans. What people seem to agree on is that the event of such an ASI arising will either be extremely beneficial to us humans or possibly render us extinct. As to the advantages, imagine ASIs bebing able to perform tasks on nanotechnological level such as an ‘eating condom’ whereby smart nanobots in your intestines filter bad food and stop the accumulation of excess fat or nanobots curing damaged cells. On the flip side an ASI might use nanobots to kill us humans in order to free more resources to reach its own goal(s).

My View on A.I.:

Since Elon Musk is an idol for me I’ve always wondered why he is so cautios about A.I., in fact he once called it ‘summoning the demon’. After reading the ‘Wait but Why?’ article on A.I.¹ I am aware of a lot of possible dangers, however with our current technology it’s still not possible to render a person immortal and thus we need to die anyway. Why not take the chance and speed up the development of A.I.? We’ll all die eventually, won’t we?