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dewhelmed

Re:Apple Debuts VisionOS 2 on Monday June 10, 2024 @11:44PM (#40642075)
Same thought here when I saw Singapore on the list, but my god it's >S$5000. Is there a cheaper way to get hold of one?
Fair point.
Wow, what an unpleasant hate-filled response to a single paragraph taken out of context from the entire post.

The fact that his work is still referenced, is still part of the game, and wanted by people on t-shirts/mugs/etc is significantly more contribution than the moronic made-up "0.000000000001%" number you claim.

He is a flawed person and he admits it several times in his post. But he also uses his story to highlight some good points about how broken the tech-capitalist system can be for artists, and that is my takeaway from this post. So please have a little empathy, it is not easy to know if you are being treated fairly in this complicated world today.

Based on my experience, it is possible, and the key factor is something she highlighted:

> I worked in venture capital for two years at a fund specializing in the area my Loyal is in (so I had a preexisting VC network, was seen as a bit of an ‘insider’, and the fund invested in Loyal, which was good signaling).

What sort of gaming-related workload do you think an FPGA would be suitable for? I don't know much about the gaming world, but isn't the majority of the computational workload graphics-rendering related, in which case, the GPU architecture is the best candidate to iterate on?
Re:EasyOCR: Ready-to-use OCR with 40 languages on Wednesday July 08, 2020 @01:41PM (#23772223)
If you don't mind disclosing, what was your particular use-case (the labeled dataset you trained on)?
Re:Ask HN: Who wants to be hired? (November 2019) on Saturday November 02, 2019 @03:54AM (#21426413)
Location: Sydney, Australia (soon to be Singapore)

Remote: Open to the possibility

Willing to relocate: Unlikely, but willing to discuss

Technologies: (System)Verilog/Python/PyTorch/Tensorflow/FPGAs/C/C++/command-line tools

Resume: https://sidmontu.github.io/one_page_cv/cv.pdf

Email: sidmontu {at} gmail {dot} com

I come from a fairly academic background, and I'm seeking a fresh challenge in the next stage of my career. My strengths lie in hardware design (especially FPGA-based), and lately, my projects have involved a lot of deep learning-related content. I am a competent programmer who is very experienced with Linux command-line tools, but I'm also open to learning new technology stacks if required. I hope to be part of an exciting project with ambitious goals.

The second one reads like a Buzzfeed article...

> What 99% of programmers don't know about memory... number 17 will shock you!

He mentions his reason for the title:

> The title of this paper is an homage to David Goldberg’s classic paper “What Every Computer Scientist Should Know About Floating-Point Arithmetic”

Re:A History of Singapore in 10 Dishes on Tuesday February 26, 2019 @06:23PM (#19259371)
Singaporean in Sydney here -- I've barely found any decent Asian food in my time here, not to mention the exorbitant prices. Could you recommend some options? I'll love to improve my food options here.
Re:Makefiles – Best Practices on Monday February 04, 2019 @09:54PM (#19082715)
My bad, I felt like I've seen that error pop up before in my Makefiles, but I should have double-checked before commenting.
Re:Makefiles – Best Practices on Monday February 04, 2019 @09:54PM (#19082713)
My bad, I felt like I've seen that error pop up before in my Makefiles, but I should have double-checked before commenting.
Re:Makefiles – Best Practices on Friday February 01, 2019 @12:00PM (#19055869)
Because CFLAGS may not be set in the environment, resulting in concatenation to an undefined variable error.
Re:Really Big Numbers (2015) on Wednesday September 12, 2018 @02:02AM (#17965892)
Just to add, I really enjoyed Scott Aaronson's essay on this topic: https://www.scottaaronson.com/writings/bignumbers.html
If you don't mind, could you share some resources on existing models that approximate the neuron behaviour more accurately? If you're talking about feedback-driven models like RNNs/LSTMs/GRUs/etc, then I can safely say that there are people working on realising these models on custom computing architectures. The simple feed-forward neural network could be thought of as the low-hanging fruit in this regard, which, nevertheless, is still an impressive feat.
So does that mean the network is now demanding each ether be mined every 12 seconds (20% harder statistic mentioned in the linked article), or the difficulty has increased naturally? E.g. there has been a large spike in the number of ether miners lately, which has caused the network to naturally readjust the difficulty to maintain the 15s/ether mining rate? If so, these GPU miners leaving the field would readjust the difficulty back again towards the original levels, or is this difficulty change a more permanent thing due to some underlying change in the technology?
Re:Gpu.js – GPU Accelerated JavaScript on Friday July 14, 2017 @11:21PM (#14774879)
From their post-hackathon devpost at https://devpost.com/software/gpu-js,

What I learned: Not to make a compiler during a hackathon.