C Corp is a legal entity classification, along the lines of S Corp, LLC, partnership, and sole proprietorship. What might be confusing is that S corps can use pass-through taxation or retained earnings (C Corp) depending on what the owners choose. There are various forms of partnerships with different levels of liabilities to the partners: general partnership, limited partnership (LP), limited liability partnership (LLP), etc. Partnerships generally provide much less protection than a C Corp.
One situation I found where AWS saves money is in over-capacity situations. If the a company builds a data center that is too large, they are incurring costs for under-utilization. Paying a 50% premium on 100% of resources might still be better than paying 0% premium on 200% of resources. The cloud versus on-premise discussion has many variables, so it all depends on the situation.
As an aside, you should generally avoid grid search in favor of random search or an evolutionary algorithm. Grid search can waste your time budget on likely bad combinations of hyperparameters instead of looking for combinations local to or nearby a known-good combination.
Tangentially related, I recommend learning and getting certified in Lean Six Sigma. It's PM * stats * MBA. The systems analysis / theory of constraints perspective also completely explains why agile falls short in the face of external road blocks.
The report should show what you are working on, where you are spending your time, etc. It is about time spent more than achievements per se. It can alert your senior that you need training on a particular task that is taking too much time or that the task itself is too difficult.
I would just like to express my gratitude to [Kevin Hartnett](https://www.wired.com/author/kevin-hartnett/) for making an enjoyable article that I could almost follow as a quantitatively minded programmer / non-mathematician. It makes sense saying that graphs are somehow a form of matroid. Even without knowing what a matroid is, I get a sense of the importance of spatial relationships.
I don't believe AlphaGo's MCTS, policy NN, or value NN support your last paragraph. Could you please explain what it is about Somehow construction that supports strategic categories with associated probabilities or why only tactical decisions are being made? I'm a bit confused by your last statement actually. Are you saying AlphaGo decides how much to emphasize certain strategic goals or that it doesn't (only makes tactical decisions)?
The idea of a super-human strong AI is really just anthropomorphizing computer programs. The only realistic way this could occur is by emulating or uploading a human mind.
I don't understand your statement that AlphaGo doesn't have strategic considerations. Its neural networks evaluate positions for strength, including long-term (strategic) potential.
I take issue with the two assumptions implies by this quote:
"Any resolve to invest in themselves and to improve their lives through work would be put to the test every day..."
1. "Seeking employment is the only important reason for investing in oneself." I believe that a duty to family is important to most people.
2. "The loss of work as a motivator for self-improvement would be bad." Perhaps other motivations would take the place of work, and people could focus on achieving other ends in their self-improvement.
Something related to functional programming, databases, data analysis, dev methodology, or system architecture. I use a procedural language in my job, but this doesn't seem relevant to it. My degree isn't in CS, if that helps.
What could it teach? Compiler design? Imperative language design? By "bootstrapping", are you referring to building a higher-level language that compiles to T3X?
”I want to expose a local server behind a NAT or firewall to the internet.”
This is genius. It immediately simply told me exactly what your and service does. A few common, short examples beneath that would also be great. I would see this being great to show off an app on the development branch to a client in a meeting.
I think that's not quite the whole picture. We also make judgments about the consciousness of others, and those judgments are based at least partially on physical criteria. Think about judgments of consciousness regarding those suspected to be "brain dead" or in vegetative states.
I prefer the term "conjecture based on deductive reasoning." It is reasonable to presume that something is theoretically possible unless we have specific evidence that it is impossible. For example, even though it is impossible today, most people would agree that it's theoretically possible to create self sustaining colonies in other solar systems. "Faith" usually implies less, or even no, basis in reason. If you still feel "faith" is the more appropriate term, please explain your reasoning.
I must disagree. Skepticism, moral epistemology, the origin of reality, etc., are metaphysical concepts. Consciousness, in its various definitions, clearly has physical descriptions and criteria. Once consensus is reached about a definition, it will be much easier to determine the causes and requirements for it. As neuroscience, computer science, and information technology progress, it will eventually become possible to precisely manipulate and/or create/simulate consciousness.
One of the big gains they still have to make IIRC is providing partial compilation. That will be significant with the good developer practice of breaking source code into multiple files.
One way to define that is in terms of the customer: quality (no defects), calendar time to deliver, benefit to customer, and value (cost-benefit ratio). So you can say things like, "if we refactor this code now, we can schedule less time on maintaining it in the future, spend less unscheduled time fixing bugs in the future, and deliver features in less time with less effort."