Anonymous wrote:Instead of showing racist attitude towards Indian American community, let's be thankful for their service and contributions to the tech world:


Sanjay Mehrotra is the CEO of Micron Technology; Shantanu Narayen is the CEO of Adobe; Satya Nadella is Chairman and CEO of Microsoft; Sunder Pichai is the CEO of Alphabet and Google; Jay Chaudhry is the CEO of Zscaler which is a cloud security company; Arvind Krishna is the CEO of IBM; Neal Mohan is the CEO of YouTube; and George Kurian is the CEO of NetApp, among the top tech giants.

Anonymous wrote:Instead of showing racist attitude towards Indian American community, let's be thankful for their service and contributions to the tech world:


Sanjay Mehrotra is the CEO of Micron Technology; Shantanu Narayen is the CEO of Adobe; Satya Nadella is Chairman and CEO of Microsoft; Sunder Pichai is the CEO of Alphabet and Google; Jay Chaudhry is the CEO of Zscaler which is a cloud security company; Arvind Krishna is the CEO of IBM; Neal Mohan is the CEO of YouTube; and George Kurian is the CEO of NetApp, among the top tech giants.

Anonymous wrote:https://arxiv.org/abs/2208.06749

Tensor algebra lies at the core of computational science and machine learning. Due to its high usage, entire libraries exist dedicated to improving its performance. Conventional tensor algebra performance boosts focus on algorithmic optimizations, which in turn lead to incremental improvements. In this paper, we describe a method to accelerate tensor algebra a different way: by outsourcing operations to an optical microchip. We outline a numerical programming language developed to perform tensor algebra computations that is designed to leverage our optical hardware's full potential. We introduce the language's current grammar and go over the compiler design. We then show a new way to store sparse rank-n tensors in RAM that outperforms conventional array storage (used by C++, Java, etc.). This method is more memory-efficient than Compressed Sparse Fiber (CSF) format and is specifically tuned for our optical hardware. Finally, we show how the scalar-tensor product, rank-$n$ Kronecker product, tensor dot product, Khatri-Rao product, face-splitting product, and vector cross product can be compiled into operations native to our optical microchip through various tensor decompositions.

Impressive that FCPS kids are showing "a new way to store sparse rank-n tensors in RAM that outperforms conventional array storage".

Anonymous wrote:Instead of showing racist attitude towards Indian American community, let's be thankful for their service and contributions to the tech world:


Sanjay Mehrotra is the CEO of Micron Technology; Shantanu Narayen is the CEO of Adobe; Satya Nadella is Chairman and CEO of Microsoft; Sunder Pichai is the CEO of Alphabet and Google; Jay Chaudhry is the CEO of Zscaler which is a cloud security company; Arvind Krishna is the CEO of IBM; Neal Mohan is the CEO of YouTube; and George Kurian is the CEO of NetApp, among the top tech giants.

Anonymous wrote:That rendering is bogus as well there's no way there are any lasers or PDs in that package, I don't see any fiber optic interfaces either. Just a fluff piece.

Anonymous wrote:https://arxiv.org/abs/2208.06749

Tensor algebra lies at the core of computational science and machine learning. Due to its high usage, entire libraries exist dedicated to improving its performance. Conventional tensor algebra performance boosts focus on algorithmic optimizations, which in turn lead to incremental improvements. In this paper, we describe a method to accelerate tensor algebra a different way: by outsourcing operations to an optical microchip. We outline a numerical programming language developed to perform tensor algebra computations that is designed to leverage our optical hardware's full potential. We introduce the language's current grammar and go over the compiler design. We then show a new way to store sparse rank-n tensors in RAM that outperforms conventional array storage (used by C++, Java, etc.). This method is more memory-efficient than Compressed Sparse Fiber (CSF) format and is specifically tuned for our optical hardware. Finally, we show how the scalar-tensor product, rank-$n$ Kronecker product, tensor dot product, Khatri-Rao product, face-splitting product, and vector cross product can be compiled into operations native to our optical microchip through various tensor decompositions.

Impressive that FCPS kids are showing "a new way to store sparse rank-n tensors in RAM that outperforms conventional array storage".

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Anonymous wrote:https://www.forbes.com/sites/gabrielasilva/2023/09/26/procyon-photonics---the-high-school-run-start-up-that-could-revolutionize-computing/

Clearly articulated by Gabriel A. Silva, Professor of Bioengineering and Neurosciences at the University of California San Diego

Notice how carefully the article and the quotes avoid saying that their invention actually exists. No measurements of real world performance. No measurements at all. Nothing real on their website or their self-published "research paper".

Not even a photograph. Only a rendering.

This is a 10 year plan to invent something in the future, not an invention now. It's like Theranos.

There's Professor Silva providing insight after meeting these kids and reviewing their research. And here you are, without meeting these young scientific minds or knowing a thing about their research, showing us what a bitter and envious adult you are.

A professor showing up for a photo op and publicity? Do they even have a patent application? This sounds a lot like dad founding a company, them coming up with something they thing sounds novel and then trying to get enough publicity to help college applications

Oh so now it's not just the students, you are insinuating the university professor who's impressed with them. Perhaps if you do some self reflection and go past your racist views, maybe ... just maybe, you can start to appreciate and encourage these young scientific minds.

First, cut out your race baiting garbage.

Second understand the difference between smart high schoolers and fully educated, professional researchers who were once smart high schoolers too.

No one likes arrogant blowhards who don't know what they don't know and don't accept the possibility that they aren't experts, no matter how smart they are.

The more you express your hatred for these talented scientific students, the more your words seem tinged with racism.

Anonymous wrote:https://arxiv.org/abs/2208.06749

Tensor algebra lies at the core of computational science and machine learning. Due to its high usage, entire libraries exist dedicated to improving its performance. Conventional tensor algebra performance boosts focus on algorithmic optimizations, which in turn lead to incremental improvements. In this paper, we describe a method to accelerate tensor algebra a different way: by outsourcing operations to an optical microchip. We outline a numerical programming language developed to perform tensor algebra computations that is designed to leverage our optical hardware's full potential. We introduce the language's current grammar and go over the compiler design. We then show a new way to store sparse rank-n tensors in RAM that outperforms conventional array storage (used by C++, Java, etc.). This method is more memory-efficient than Compressed Sparse Fiber (CSF) format and is specifically tuned for our optical hardware. Finally, we show how the scalar-tensor product, rank-$n$ Kronecker product, tensor dot product, Khatri-Rao product, face-splitting product, and vector cross product can be compiled into operations native to our optical microchip through various tensor decompositions.

Impressive that FCPS kids are showing "a new way to store sparse rank-n tensors in RAM that outperforms conventional array storage".

Anonymous wrote:Another pay to play admissions strategy

Indian culture is full of cheating for educational purposes including admissions

Google indian cheating college

There are 1000s of examples of reddit and news articles, it's the get ahead academically at any costs