awra

GILMORE GIRLS (2000-2007)

2025 January 1

Alpha Centauri: The Closest Star System Image Credit & Copyright: Telescope Live, Heaven’s Mirror Observatory; Processing: Chris Cantrell

Explanation: The closest star system to the Sun is the Alpha Centauri system. Of the three stars in the system, the dimmest – called Proxima Centauri – is actually the nearest star. The bright stars Alpha Centauri A and B form a close binary as they are separated by only 23 times the Earth- Sun distance - slightly greater than the distance between Uranus and the Sun. The Alphasystem is not visible in much of the northern hemisphere. Alpha Centauri A, also known as Rigil Kentaurus, is the brightest star in the constellation of Centaurus and is the fourth brightest star in the night sky. Sirius is the brightest even though it is more than twice as far away. By an exciting coincidence, Alpha Centauri A is the same type of star as our Sun, and Proxima Centauri is now known to have a potentially habitable exoplanet.

What's it for?

What's it for?

Why would anyone want this?

I sit in so many meetings and listen to genuinely very intelligent people talk until steam is rising off their skulls about genAI, and wonder how fast I'd get fired if I asked: do real people actually want this product, or are the only people excited about this technology the shareholders who want to see lines go up?

like you realize this is a bubble, right, guys? because nobody actually needs this? because it's not actually very good? normal people are excited by the novelty of it, and finance bro capitalists are wetting their shorts about it because they want to get rich quick off of the Next Big Thing In Tech, but the novelty will wear off and the bros will move on to something else and we'll just be left with billions and billions of dollars invested in technology that nobody wants.

and I don't say it, because I need my job. And I wonder how many other people sitting at the same table, in the same meeting, are also not saying it, because they need their jobs.

A metaphor I've been using lately is that being a tech-interested person and watching the AI hype is like if you had followed the development of blenders for years. You watched them go from prototypes that were basically just a spinning open blade all the way to a design that has the potential to be a consumer Vitamix! It's really cool! Blenders have come such a long way, and they're ready for prime time!

And then you turn on the news and see otherwise rational, intelligent people saying "gosh, imagine, soon we'll replace all of our chefs, and our surgeons, and our high school teachers with blenders!" and your friends and family all nod and agree and say things like "wow, blenders can basically do everything now!" And when you ask people "are you HIGH?!" they show you the new blender they bought, and how well it makes a smoothie, and then they act like that's evidence for a statement like "blenders will replace 90% of the workforce" not being utterly nonsensical and deranged.

"Scientists just have to fix the hallucination problem!" they say. When you ask what the hallucination problem is, they say "I'll show you" and then they put their unfinished math homework into the blender and hit pulse. "You see, I wanted it to solve those math problems, but it just shredded the paper. It must have hallucinated a world where the answer to 2+2 was puree." When you point out that it did exactly what it was designed to do, because a blender cannot do math and it will never do math and expecting it to be able to do math just because it can make both smoothies and soup is ludicrous and bizarre, they tell you that they're sure that blenders will be able to do math any day now, just you wait, "I mean, look how far they've come! A year ago I would have said that blenders could never be strong enough to blend ice into sorbet, but now they can. So who are you to say they'll never do math???"

The thing is, there are plenty of things that LLMs and generative AI are good for. OCR is still a vital need, and AI is excellent at it. Facial recognition is an area where AI has a lot of potential. It can be used as a screening step for the analysis of all sorts of large datasets. Better autocomplete on your phone is a real thing that real people want. There are a ton of problems that these tools genuinely do solve!

...But none of them are trillion dollar problems, and that's an issue, because no one wanted to pour a trillion dollars into "improved OCR" and "somewhat better autocomplete".

1. It's so important that you do a first read thru of the text as fast as possible. Stick to annotations and brief summarizing notes/outlines. Our brain is constantly making connections even when we're sleeping, so even if you don't understand something at first, getting stuck on it is a waste of your present time AND sleep time. Some things will click while you're doing chores because your brain is still working in the background! But it can't happen if there is nothing to click. Try to expose yourself to all the material as early as possible. [If you're studying math, skip the derivations and proofs in the first read thru and just do the example problems and focus on the underlying assumptions. Depending on the class/exam objective, you might not even be tested on the proof]

2. The breaks. Even if you know you can study 4 hours straight - don't. I used to do this especially when I was anxious, but it just burned me out. Even as quickly as the next day! If you're doing your first pom of the day and you feel really fresh to the point that you feel like you can skip that first break - dont.. it will pile up!

3. The water and the sugar!! This might sound really obvious, but studying burns up so many resources. On days I don't study, I might be okay with 60-70 oz of water, but on days I do, it's normal for me to hit 100 oz. I also ate way more food in general and ate more sugar too, and I think that's pretty normal.

4. Flashcards and practice problems > annotations > having nice notes. It kills me to say it, but the last exam I took (and passed!), I relied on my very disorganized notes/screenshots on my tablet. I didn't have time to organize and transfer them nicely onto paper in order even though every perfectionist cell in my body wanted to soo badly. Making your own textbook can be helpful but I seriously just didn't have the time. Focus on what will actually get you that pass score!

5. Find the note-taking app you like BEFORE your study period or exam season and practice using it! The last thing you want is to fight the syncing mechanism as you're trying to study. I like to use Flexil because of the split screen feature, the linked screenshots, and the cross-platform sync. If you are studying math, either learn latex over the summer/off period so you can use it in Obsidian/Anki or commit to manually written flashcards and notes the whole way. Dont try to switch halfway through because that will be a waste of your time. I personally think writing out the math is faster than typing it out in Latex, but it's your poison (they're both poison). (And if you study any type of math, I 10000% recommend using a tablet)

6. Unless you are studying for fun, orient everything around the class/exam objectives. Unfortunately, you're not gonna have time to be curious. If you don't think something will be tested, quickly cut it out and move on.