p4wnc6

126 ms·

751.
by p4wnc6 11y ago
Idea averaging is a wonderful thing, and you should probably do it way more than you already do, and it should probably be your default mode when looking to choose between ideas. A lot of this is spelled out in the literature about why ense
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by p4wnc6 11y ago
This is one of those questions that is extremely hard to predict. Even though I was part of that team, it doesn't mean I have any special insight into what will happen. A lot will depend on sources of funding. Will folks like Nvidia st
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by p4wnc6 11y ago
I think you misunderstood what I meant. In pairing, a bi-directional pathway is established between Person A and Person B. This means that, during the activity of pairing, Person A's influence is exclusively dedicated to Person B, and
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by p4wnc6 11y ago
Well, "professionalism" is pretty much the black-hole escape valve of HR. It has to do with your hair style, your political beliefs, your religious beliefs, how much (or how little) you drink alcohol, where you choose to live, whe
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by p4wnc6 11y ago
I also just wanted to clarify about scaling: taking some (semi-large) number like 120 and claiming this means "pairing does scale" seems totally wrong to me. "Scaling" does not refer to taking some large number and divid
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by p4wnc6 11y ago
Numba certainly does not obviate all of these issues. I think user `tadlan` is referring to some of the compiler optimizations, like loop unrolling or fusion (e.g. noticing that two subsequent loops can be 'fused' into the subordi
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by p4wnc6 11y ago
> Pivotal Labs That explains it. We're lucky this thread was merely about pair programming and not about the orders-of-magnitude worse phenomenon of Agile/Scrum.
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by p4wnc6 11y ago
Managing one's emotional state is a critical skill for anything -- making marriages work, raising kids successfully, closing an important deal, delivering a eulogy for someone you care about, and doing your job. But, like all critica
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by p4wnc6 11y ago
While I agree broadly that the benchmark example in the post is not representative or useful as a comparison between D and NumPy, I disagree with your strong insistence on Numba in this case. There is still a lot of Python code that the N
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by p4wnc6 11y ago
The central claim of the post seems summarized by this quote: > For example, when using a non-numpy API or functions that don't use Numpy that return regular arrays, you either have to use the normal Python functions (slow), or use
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by p4wnc6 11y ago
I agree with your distinction between groups who care about "causal inference" like the debates between Judea Pearl and Andrew Gelman on the role of toy problems in statistics, and groups who care more about "prediction engin
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by p4wnc6 11y ago
Similar question as with the other Uber posting: some of the positions look interesting... but can you share whether the SF or NY offices provide private office space or only open-plan offices?
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by p4wnc6 11y ago
Performing the task of weightlifting is incredibly different than performing the task of programming. Much evidence suggests that programmers perform better solo because they can more easily reach states of psychological flow, and because t
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by p4wnc6 11y ago
I gave up on Asana when it started retooling to focus more exclusively on Agile/Scrum stuff. No tool should be allowed to claim to be about improving productivity if it also goes out of its way to support constructs taken from Agile&#x
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by p4wnc6 11y ago
Thank you for the reply! I appreciate the philosophy of hiring generally good people and letting them learn new stacks as needed. However, there's also something to be said for specialization. For example, I work in scientific computin
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by p4wnc6 11y ago
Your working philosophy is great! However, it's very difficult to determine from your web page what types of engineers you're looking for. Can you elaborate on the particular skill set you need, and a little on the primary technol
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by p4wnc6 11y ago
Some of these positions look very interesting! Can you also share whether the Pittsburgh office has private office space, or if it is open-plan office layout only?
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by p4wnc6 11y ago
There will always be political deception in the debate over choosing metrics. But one thing that indicates a good management structure is that after metrics have been chosen, there is a very strict and quantitative process for holding peopl
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by p4wnc6 11y ago
> There's another angle as well at play... My command chain cares about delivery of services and products at our below the budget, period. This is classic duplicitous manager babble that really just means, "I want authority to
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by p4wnc6 11y ago
Most managers won't agree to the types of metrics that you say. Yet most will agree to more arbitrary metrics, like much of what makes up Agile/Scrum. Many managers do this intentionally, because the greater degree of control over
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by p4wnc6 11y ago
I agree. I don't like C++ much and I feel some very strong, objective arguments can be made that it is often not the right tool for many of the jobs that it is chosen for. And yet, Effective C++ was one of the pivotal development boo
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by p4wnc6 11y ago
True. It's not necessary. But most times in real life when this happens, the scientific rigor is the first thing to go. This can manifest itself in a lot of ways. One way is an explicit mandate to find that a pre-determined conclusion
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by p4wnc6 11y ago
Machine learning is one subfield of mathematics that generalizes another, further subfield (statistics).
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by p4wnc6 11y ago
I disagree. Most of the egregious stuff is in published statistics literature, particularly in econometrics, psychology, medicine, and biology, from researchers whose full-time job is to use statistics to solve applied problems ("domai
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by p4wnc6 11y ago
The problem is not about how to take a scientific conclusion and make it suitably less scientific to serve as a business explanation. The problem is to replace inept employees who believe "business decisions" are not scientific qu
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by p4wnc6 11y ago
I have had the exact opposite experience with machine learning and statistics. In my experience, those who come from the 'statistics' side tend to use constructs, like null hypothesis significance testing, which are not consistent
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by p4wnc6 11y ago
What is commonly understood as 'statistics' is just a specialized subset of machine learning. Machine learning generalizes statistics. The correct complement to machine learning is cryptography -- trying to intentionally build thi
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by p4wnc6 11y ago
I don't mean any offense when I say this, but I kind of resent this type of perspective. I can't say for sure but I suspect if we knew each other, I would fall into the "non-addict friend with problems" type category. Yo
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by p4wnc6 11y ago
I don't think I missed your point. I think I said that a rational duopoly won't bother worrying about what economical solution best prevents a third entrant, when there is always the possibility of simply paying from established w
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by p4wnc6 11y ago
I'm not sure I buy this because even if a third competitor entered and claimed nearly half of the market, the people far out in the tail of that claimed half would not experience any improvement in service. To them, they would be nearl

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