Microsoft Blog

"I haven't read them but I'm familiar with the area of discussion."
"What we are doing now is a thundering herd attack on the global mind-space of algorithms+data."

Nice way to put it. Ok, you really need to read those references since most programming is supposed to suck if it's done by humans. It used to bother me when I was younger but I accept it as inevitable. Much like evolution itself producing tons of waste on its way to overall dominance of most of the search space. Once you get basic principles driving it, you must then work within that to squeeze as much of that good engineering as possible into those constraints. It's only way to have high impact or shift segments of the herd in better directions. Hell, it's a little like CLP for people & development processes. ;)

I'm including original essay, a great commentary tie-in in historical proof, and one by ex-high assurance guy Steve Lipner at Microsoft:

http://www.dreamsongs.com/RiseOfWorseIsBetter.html

http://yosefk.com/blog/what-worse-is-better-vs-the-right-thing-is-really-about.html

https://blogs.microsoft.com/microsoftsecure/2007/08/23/the-ethics-of-perfection/

" The Prolog version is less than a page of code and half of that is direct translations of the puzzle hints to CLP constraints (the other half just sets up the variables and such.)"

It was beautifully concise compared to the others. Of course, they were trying to re-invent the parts like execution strategy that are hidden in Prolog. Your point seems…

> Steven Gonzales Monserrate is an anthropologist and a PhD candidate

Maybe this person should stick to studying skull sizes or whatever it is an anthropologist studies these days. I'm sorry to say, but what a load of horse shit.

Yes, data centers use energy. Essentially all of the big cloud providers have committed to carbon neutrality, most of them are pretty far done with getting there, and essentially all of them already source the vast majority of their power from renewables at this point. That's not just because it is greener, but also because it is cheaper.

Amazon, Google, Microsoft, etc. each maintain nice web pages on how far they are with these plans.

- Amazon is shooting for 2025 for 100% carbon neutral energy. https://sustainability.aboutamazon.com/environment/the-cloud?energyType=true

- Microsoft plans for carbon negative by 2030: https://blogs.microsoft.com/blog/2020/01/16/microsoft-will-be-carbon-negative-by-2030/

- Google claims to have been carbon neutral since 2007 and plans to be carbon free by 2030 as well: https://sustainability.google/commitments-europe/

That's a trend with many other manufacturers as well. E.g. lots of automotive manufacturers. If there's a deep conspiracy where these companies are lying about what they are doing, that would be news worthy of course. But, I suspect that most of these companies are simply getting very good at managing absurdly high degrees of energy and water efficiency and cost.

Kind of counters the message of…

Microsoft also just released a book on AI and its role in society.

https://blogs.microsoft.com/blog/2018/01/17/future-computed-artificial-intelligence-role-society/

"...Beyond our personal lives, AI will enable breakthrough advances in areas like healthcare, agriculture, education and transportation. It’s already happening in impressive ways.

...

But as we’ve witnessed over the past 20 years, new technology also inevitably raises complex questions and broad societal concerns.

...

To answer these tough questions, technologists will need to work closely with government, academia, business, civil society and other stakeholders. At Microsoft, we’ve identified six ethical principles – fairness, reliability and safety, privacy and security, inclusivity, transparency, and accountability – to guide the cross-disciplinary development and use of artificial intelligence. The better we understand these or similar issues — and the more technology developers and users can share best practices to address them — the better served the world will be as we contemplate societal rules to govern AI.

We must also pay attention to AI’s impact on workers. What jobs will AI eliminate? What jobs will it create? If there has been one constant over 250 years of technological change, it has been the ongoing impact of technology on jobs — the creation of new jobs, the elimination of existing jobs and the evolution of job tasks and content. This too is certain to continue.

...

As computers behave…

SRE who deals with some .Net stuff that uses MSSQL but is converting to MySQL. so I feel somewhat qualified to talk about MSSQL. TL;DR: Nothing interesting going on.

There is nothing to talk about here. It's boring database engine that powers boring business applications. It's pretty efficient and can scale vertically pretty well. With state of modern hardware, that vertical limit is high enough most people won't encounter it.

It's also going the way of Windows Server which is to say, it's being sold but not a ton of work is being done on it. Companies that are still invested in it are likely because they don't care about cost ultimately or cost of switching is too high to greenlight the switch.

Anyone who does care about cost like my current company has switched to OSS solutions like PostGres/MySQL/$RandomNoSQLOSSOption. My company switched away when turned into SaaS business and those MSSQL server costs ate into bottom line.

This has been happening throughout the ecosystem. Proget which is THE solution for .Net Artifacts is switching to PostGres: https://blog.inedo.com/inedo/so-long-sql-server-thanks-for-all-the-fetch/

Also, I saw this article from Brent Ozar, who I see as MSSQL smart person, which basically said if you have the option, just go with PostGres: https://www.brentozar.com/archive/2023/11/the-real-problem-with-sql-servers-licensing-costs/

It's also worth noting that Microsoft even bought PostGres scaling solution called Citus so they read the writing on…

Disclaimer: Self-plug but I do feel it may be relevant to people here who wish to take responsibility for their greenhouse gas footprint.

If you're looking at CO₂ emissions and want to do something about your own footprint please consider removing your own emissions.

Reductions are great and all (definitely part of the necessary solution) however they do not address the existing excess of CO₂ in the atmosphere

I started "Carbon Removed"[0] for the exact purpose to bring carbon removal to everyone and make it easy for us all to compensate the damage we have done to the environment. We support carbon removal methods so you can turn your emissions into trees and stone.

If you're more interested in removal methods I suggest researching:

* tree planting - cheap and easy but slow to see results
* direct air capture and storage - new, innovative technology that can permanently remove CO₂ through mineralisation but is expensive at this stage. Search "climeworks"
* enhanced weathering - "olivine stones" and "project vesta" are good steps here that can slowly and naturally capture CO₂
* blue carbon - naturally removing carbon dioxide through ocean ecosystems
* biochar - "carbonise" organic material and use it as a soil supplement (as well as a carbon sink)

Personally I have been exceptionally happy to see the transition from "carbon credits" (which, IMHO provide dubious value and are hard to quantify) to net-zero emissions - the thought leading concept of…

Yes, definitely to your first and last two questions!

It's not as viable as it resulting in a large scale FPGA movement anytime soon since the the industry and academia is heavy experienced with using GPUs. The software and libraries on GPUs, like CUDA, TensorFlow and other open source libraries are very mature and are optimized for GPUs. There will have to be libraries in Verilog (I for one I'm hoping to be a part of this movement for some time now, so I'd love it if anyone can guide me to anything going on)

There are some major to minor hurdles. Although some of them might not seem like much[0], here they are:

1. Till now deep learning/machine learning researchers have been okay with learning the software stack related to GPUs and there are widespread tutorials on how to get started, etc. Verilog/VHDL is a whole different ball game and a very different thought process. (I will address using OpenCL later)

2. The toolchain being used is not open source and it's not really hackable. Although that is not that important in this case, since you're starting off writing gates from scratch, there will be problems with licensing, bugs that will be fixed at snail's pace (if ever) till there will be a performant open source toolchain (if ever, but I have hope in the community). You'll have to learn to give up at a customer service rep if you try to get help, unlike open source libraries where to head to github's issue page and get help quickly with the main devs.

3. Although…