marrowgari

5 anni fadiscuss

A slightly more verbose (less abstract) version of k would be q. Kx (proprietary owners of k/q) have a nice reference page if you're interested in learning more about the language, e.g., where it's used and how it's used... https://code.kx.com/q/ref/

marrowgari

5 anni fadiscuss

Correct. I'm in trad-fi (traditional finance). The job security is fantastic and the offers are plentiful. The community and support groups are quite small, but very supportive. It just requires a lot more research and effort (compared to JavaScript, Python, Rust, etc.) to find solutions to your problems.

marrowgari

5 anni fadiscuss

Love seeing the random k/q code mentions here. All too often I feel as though I'm coding in a black box. This shines a little light letting me know others are out there too. Nice work.

marrowgari

5 anni fadiscuss

Also a NYC resident. Been casually looking at apartments to take advantage of the decrease in price of the rental market. Found out 2 things; (1) that if you see an apartment you like you have to act instantly and submit an application otherwise it'll be off the market the next day, (2) the decrease in price is largely a myth. Some are cheaper but it's mostly negligible and temporary. These both tell me that the city is going to be fine. There's still a demand to be here. It's not just work. It's opportunity for culture and lifestyle that people are seeking as well. NYC is still at a premium for both of those.

marrowgari

6 anni fadiscuss

I use a reverse osmosis system with an added remineralization filter at the final stage. The unit I have is a counter top model from Apec and can be easily set up to use with your kitchen sink. I swear by it and as added bonus to clean drinking water from the tap you no longer have to purchase plastic bottles of water. The only maintenance is filter replacement, which is relatively straight forward. I tend to replace them every 6 months, though apparently they're good for up to a year. You can find more info on it here... https://www.freedrinkingwater.com/ro-counter-detail.htm

marrowgari

6 anni fadiscuss

The reason the 1% is able to utterly dominate the remaining 99% is they are hyper organized. They're even organized around the concept, idea, and execution of organization.

marrowgari

6 anni fadiscuss

The STPIHKAL reference to the Shulgin's PIHKAL / TIHKAL books is what sold me. https://stpihkal.docs.buttplug.io/

marrowgari

6 anni fadiscuss

I work with KDB daily. This comment is misleading and uninformed. I'll agree the language is cryptic but that's what makes it fast. In regards to single threaded, that's just false. There are many options from slave threads to parallel processing you can use to speed up processing if your data sets are large (billions +) or you need to query historical data that is in the size of petabytes. Also once you learn the syntax and error handling it's not bad, just like every other language.

marrowgari

7 anni fadiscuss

As someone who grew up in the triple cities (surrounding Binghamton area) I'm sorry but also what exciting news.

marrowgari

7 anni fadiscuss

Yes. But that's a network finely tuned on facial images, which is more complex than landscapes. GANs can create all types of images, it's just that landscapes happen to be the type of media currently created with the least complexity due to the more abstract nature of the details involved.

marrowgari

7 anni fadiscuss

All future media should be watermarked with immutable metadata linking it back to it's original source to verify authenticity and combat fake news.

marrowgari

7 anni fadiscuss

If you run in debug mode it listens on port 18001 allowing for RCE on host machine

marrowgari

8 anni fadiscuss

Life 3.0 by Max Tegmark - great glimpse into the current and potential future of AI

Leonardo da Vinci by Walter Issacson - fascinating look into the real life of Leonardo, demystifying the genius

Excession by Iain M Banks - a bit of a let down

Bluets by Maggie Nelson - lyrical and philosophical and explicit ruminations on the color blue

How to Change Your Mind by Michael Pollan - a lot of already known and rehashed info on psychedelics

Lost City of the Incas by Hirham Bingham - Yale professor who discovered Machu Pichu. Good history of the Incas and region

Farenheit 451 by Ray Bradbuy - Classic!

2041 by Kim Stanley Robinson - NYC underwater in the future. A bit of a let down compared to his Mars series

Shiver by Junji Ito - short stories from the king of Japanese horror manga

Lenin: The man, the dictator, the master of terror by Victor Sebestyen - great bio on Vladimir Lenin. Knew very little about him before reading this. Fantastic!

Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville - definitive text book on Deep Learning

The Curse of Bigness by Tim Wu - interesting read into the history of Antitrust and the Sherman Act and how they relate to modern tech giants like Amazon, Google, Facebook

Connecting the Dots by John Chambers - a bit dry. Lessons Chambers learned while CEO of Cisco

marrowgari

8 anni fadiscuss

Nearly finished reading Walter Issacson's Da Vinci and highly recommend it for anyone interested in his life story. It paints a beautiful picture and demystifies his life into a way we can easily see ourselves, if we only take enough time to carefully observe our surroundings, question dogmas, and stay endlessly curious about the subtle and little things in life.

marrowgari

8 anni fadiscuss

This is great. But I find the advantage of Coursera is that it incorporates quizzes and programming homework into the lectures reinforcing the learning. Also, the material is updated and more relevant to today's ML problems then his 2008 lectures on youtube.

marrowgari

8 anni fadiscuss

this one... https://www.coursera.org/learn/neural-networks-deep-learning...

marrowgari

8 anni fadiscuss

If you're looking at this with the intention of getting started in Deep Learning and feeling overwhelmed by the math then Andrew Ng offers a great course on Coursera that goes over all of the formulas needed to calculate the forward propagation, loss computation, backward propagation, and gradient descent. Highly recommend it for anyone interested in breaking into the field of machine learning.

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