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Comment by mattferderer | Hacker News Reader

My "guess" is they're offering $1B worth of Azure services. Which costs MSFT probably much less than $1B.

My "guess" is that it means MSFT has access to sell products based off the research OpenAI does to MSFT's customers. Having early access to advanced research means MSFT could easily make this money back by selling better AI tools to their customers.

Also a great time to point out that while "Microsoft is not a charity foundation" it does offer a ton of free Azure to charities. https://www.microsoft.com/en-us/nonprofits/azure This has been an awesome thing to use when helping small non-profits with little money to spend on "administrative costs".

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> My "guess" is they're offering $1B worth of Azure services. Which costs MSFT probably much less than $1B.

It's a cash investment. We certainly do plan to be a big Azure customer though.

> My "guess" is that it means MSFT has access to sell products based off the research OpenAI does to MSFT's customers. Having early access to advanced research means MSFT could easily make this money back by selling better AI tools to their customers.

I'm flattered that you think our research is that valuable! (As I say in the blog post: we intend to license some of our pre-AGI technologies, with Microsoft becoming our preferred partner for commercializing them.)

OpenAI has achieved some amazing results and I congratulate them for their accomplishments, but labeling any of that as "pre-AGI" is intellectually dishonest and misleading at best. They haven't shown any meaningful progress toward true AGI.

When I was 10 I created some "pre-time travel" technology by designing an innovative control panel for my time machine. Sadly I ran into some technical obstacles later in the project. OpenAI is at about the same phase with AGI.

Sorry for the cowardice of this throwaway account, but it freaks me out that Musk left, and Thiel is still there.

Going back in time:

> Musk has joined with other Silicon Valley notables to form OpenAI, which was launched with a blog post Friday afternoon. The group claimed to have the goal “to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return.”

What happened here?

I know it’s far off, but I am concerned about AGI misanthropy and the for-profit turn of OpenAI. Who is the humanist anchor, of Elon’s gravitas, left at OpenAI?

What happened to the original mission? Are any of you concerned about this? Can you get rid of Peter Thiel please? Can we buy him out as a species? I respect the man’s intellect yet truly fear his misanthropy and influence.

Apologies for the rambling, but you all got me freaked out a bit. I had, and still do have such high hopes for OpenAI.

Please don’t lose the forest for the trees.

They left in good terms, Musk was competing in terms of talent (e.g Andrej Karpathy leaving OpenAI for Tesla).

See: https://twitter.com/elonmusk/status/1096987465326374912?lang...

>but it freaks me out that Musk left,

Why? He left due to possible conflict of interest, Tesla is researching AI for self-driving vehicles and it wouldn't surprise me if SpaceX does at some point too (assuming they aren't already).

If your team ever gets frustrated by ARM, have them shoot me an email for my old proposal on how to fix it (source: used to work at Azure and perennially frustrated by ARM design)

I'm interested to hear more about this proposal! What problems does it aim to fix? Would you be willing to share?

Can I say "most of them"? Basically it simplifies ARM and the Azure API significantly and makes Azure operate more like "infrastructure as code". But I'd need to look at the latest version of Azure to see specifically what the remaining pain points are now. I could have a more specific conversation in a different setting.

I remember the first meetings about ARM when the resource IDs were presented, and a few people immediately asked "what if someone wants to rename a resource"? Years later you still could not do that (I'm hoping they've fixed that by now?).

It seemed to me that ARM was the result of some design by super smart committee, and got a lot wrong. When I was there more senior folks told me not to worry, that's just the Microsoft way (wait for version 3). I do have to admit that it's turning out they knew more than me (shocking!), as over time I've seen some of the stuff that was inexplicably terrible in v1 become much, much better in later versions.

If you manually rename a resource and refer to it by resource ID, I don't think ARM understands anything about it and assumes it's a new resource. That's just from using ARM, though, I don't know it's internals.

They are investing a good amount in ARM lately though. The vs code language server is pretty good and export template got much better

> They are investing a good amount in ARM lately though. The vs code language server is pretty good and export template got much better

Awesome! I sheepishly have been using GCP, AWS, and DO. Last gave Azure a shot last year, but perhaps it's time to take another look.

Thank you for taking the time to clarify & correct my statements!

Just saw this post. Wow, that’s a big cash investment and certainly makes this very significant.

> by selling better AI tools to their customers

Microsoft really needs this. ML.NET is quite anemic compared to the industry-standard AI toolkits: TensorFlow, theano, scikit-learn, Torch, Keras, etc.

https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotn...

Disclosure: I work at Azure in AI/ML

Another way to think about it is that for folks building in .NET, ML.NET makes it easy for them to start using many of the ML techniques without having to learn something new.

On top of that, we FULLY support all the industry standard tools - TF, Keras, PyTorch, Kubeflow, SciKit, etc etc. We even ship a VM that lets you get started with any of them in one click (https://azure.microsoft.com/en-us/services/virtual-machines/...) and our hosted offering supports them as well! (e.g. TF - https://docs.microsoft.com/en-us/azure/machine-learning/serv...)

Nice, thanks for the info. Maybe it's proper to think of ML.NET as training wheels, then!

For what it's worth, we are pretty proud of the performance as well - I wouldn't call it training wheels :)

On both scale up and run times, it measures up as among the best-in-class[1]. That is to say, for the scenarios which people use it most commonly (GBT, linear learners), it's a great fit!

[1] https://arxiv.org/pdf/1905.05715.pdf

Microsoft has Windows.AI tho.

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