0x1221

So let's assume that building immunity is even a possibility even though there is no evidence to support this while there exists substantial evidence to the contrary (people getting reinfected)?

Not happy to be living in the UK if that's really the plan.

Making a claim without providing evidence is different from "wild speculations and conspiracy theories".

I would say that The Big Short is more impactful if you already have some general understanding of the markets.

No. Infecting large numbers of people at the same time is the exact opposite of what everyone is trying to achieve.

It's in cash.

All of the advice here is good but it's also convincing me that I really don't want to be working from home long term - I just need a better office environment and a shorter/more pleasant commute.

If it's clean and clear cut you probably don't need deep learning either.

It's surprising how many companies out there are selling similar datasets.

I'm not familiar with the space so my question might not be that relevant - where does OpenShift fit in all of this (I still struggle to differentiate it from Kubernetes) and is there any merit to IBM trying to sell it so hard?

> I'm well aware that you can learn programming, data science, etc... without being good at math

I don't think that this is accurate for data science. Data science is essentially software engineering + math.

Can you gives us some numbers that show that this is actually happening?

Maybe I'm biased but I much prefer the way the UK has handled this. Card payments are everywhere, contactless payments are everywhere (life changer in London's public transport where touching in and out with your phone/card automatically charges you the correct price meaning that you don't need to deal with tickets) and everyone still has the option to use cash.

What do your colleagues think? Or is every engineer in this big company also incompetent in addition to your management?

I guess it's the selective aspect of a question like this but I'm genuinely surprised that so many people in this thread are taking actual measures.

> That they may be. But that doesn't give them the authority to think "I know better than every one else in my country/world how this wealth should be spent."

Owning the wealth gives them authority on how it's spent.

I'm really not a fan of the rising trend to attack billionaires just because they're billionares. There are plenty of points that each of the mentioned individuals can be legitimately criticised on. Their level of wealth or the decision to donate it to one cause or another is not a valid point of criticism.

> Given that a person’s gender cannot be inferred by appearance, we have decided to remove these labels in order to align with the Artificial Intelligence Principles at Google, specifically Principle #2: Avoid creating or reinforcing unfair bias.

Isn't this just outright wrong? A person's gender can be inferred by appearance, and with extremely high accuracy at that.

Also, opening their front page at the same time from different browsers can show completely different discount levels. And those will be different still from the prices that you see when you log into your account.

Depends on his position relative to yours. If he's the reviewer, only leaving thumbs down on a PR means that he's not doing his job properly. If he isn't the reviewer, you can just ignore him. When he tells you that your decisions don't make sense - if it's something that you're discussing, consider that he might be right and get in more depth on why your decisions might not make sense, especially if this person is more senior. If it's just a peer who's throwing around negative one-liners - just ignore him. If it's someone that you're supposed to learn from / be managed by - then they suck at their job.

Either way, don't quit because of this. It's far from what I would label "toxic" and it's likely that you'll meet people like this in most places so you're better off learning how to handle them early on.

Missed pun opportunity at went viral?

> How many of the ML self-taught crowd can write framework-level code, or debug a ML algorithm bug?

This isn't specific to ML though - I don't see why the number should be different from the number of self-taught web developers who can write framework-level code.

> Machine learning

> revolutionizing and democratizing

> perception

> alarming rate

Well done. How can I send you money?

> but it is orders of magnitude harder than software development, mainly because of much longer learning feed-back

The order of magnitude point is just wrong. You might argue that it's harder because it's essentially software development and a lot of applied math. But that certainly doesn't account for orders of magnitude difference.

> Second, it's not -$10b if he's getting a tax break for some of this. It's $7.6b as someone else mentioned

No. It's $10 billion. 10 billion that he won't pay tax on. But he gives $10 billion and the cause receives $10 billion. The $2.4 billion is money that the government won't get in taxes.

Do we have any evidence that they lied? Like actual evidence, not the comments of a few outraged customers (one of them literally calling it "fake news").

You really don't need a guide. Enjoy using your new phone.

Similar experience. Switching from bash to zsh was probably the most disruptive part of it.

JupyterLab