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spongepoc

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The market economy in fact solves many problems of 'helping other people' that we have just become so used to that we don't appreciate its complexity.

The fact that food is produced in abundance and is distributed in time to population centres for convenient consumption is a marvel of the modern world. And we're only getting better at it over time.

That's helping people.

I think this analysis is completely spot on. Personally, I have had the same thoughts for about a year and I have just switched from a 'pure' ML/DS' to exactly the hybrid engineering style role you describe.

People placed a lot more 'art' into their speech than people nowadays. You hear it in the old English of England as well with the particularity of enunciation. Speech was the main interface of communication compared to today's more logocentric and multimedia audio visual world. In our age we appear to place that art into crafting text messages (nuances of capitalisation, punctuation, abbreviations, emojis etc.).

Rewriting history is the power of China's censorship system and media control. It's a pretty scary thing actually.

Circling back to space, this is a fundamental reason why China will struggle to make advances in space once the easy gains have been achieved. Creativity and innovation require a free, liberal and open society to thrive.

These are the priciples which have propelled America's advances in science as they are principles which attract the brightest from around the world.

Very few of the brightest in the world would be willing to sacrifice that freedom to work in China.

It trickles down by the fact that we all get to enjoy the fruits of technological advances without having to redo the hard work of inventing it.

But there's no inherent reason why it should tricke down in income terms.

We are facing record unemployment so people are having this happen to them across the board. The people who lost their jobs due to the pandemic but are struggling to find work because of the abundance of H-1B holders also "haven't done anything wrong".

The question now is do we continue that flow of labour while jobs are scarce, or stem that flow while we get back on our feet again? On this, the Trump administration appears to have made a tough, but rational choice.

The market always prevails over the state. Private schools can only charge as much as the demonstrated quality of their product while the state as the default option is not accountable to anyone because those who can afford better can escape them.

The assumption that China will become the world's most important market is extremely wrong-headed. Their government is incredibly fragile and the world saw this with the outpouring of dissent on WeChat during the COVID outbreak. China also faces the largest demographic timebomb that will ever be witnessed in history, has no allies, nor exportable culture or soft power. These will a huge impediment to it as it tries to move from manufacturing power to political power. Also the Chinese are a decade behind in semiconductor fabrication and fundamentally are still highly dependent on Western tech. The world still dreams to be American in a way they don't dream to be Chinese.

By the way, bringing in politics to a discussion about tech with those comments on Iraq is best avoided.

If you've been following the field at all (i.e. who the paper is aimed at), the sentence is obvious and non-controversial. There have been many tasks where deep learning has even exceeded human performance (a stronger claim than that sentence).

Even the most state of the art computer vision/object classification algorithms still don’t generalize to weird input, like familiar objects presented at odd angles.

"some x are not y" does not invalidate "many x are y"

Trump's shutdown of Huawei is a tactical blinder. I can see no move China can make in response that won't end up harming them more than it will the US. China's mercantilist trade policy of the past 40 years is coming back to bite them, just like it did in the 19th century.

CLT talks about sampling from the population infinitely. It doesn't say anything about diminishing returns. I don't get how you go from sampling infinitely to diminishing returns.

Yes it does. It even implies it in the name 'limit'. In the limit of infinitely many samples, we approximate a normal distribution. This approximation has diminishing returns.

All I see in this post is complaints and no real solutions. The solution that's given is what? Have less data?

It's fine to point out problems without giving solutions. You seem very aggravated.

The west has culturally moved into a kind of foodie Epicureanism in the past 15 years. This can be seen as a response to economic pressures that young people are facing. When you can't afford a home or a car, you give up on it altogether and suddenly you have all this disposable income to spend on smaller and more transient sensory experiences like food and travel. Importantly, these experiences are able to be catalogued on social media.

Instagram is a huge factor in the rise of foodie-ism. If you are what you eat then you can use pictures of food as a form of self-expression. Picture of a dish at a quirky new restaurant? You're adventurous and on-trend. Made a sourdough bread from scratch? You're artisanal and authentic.

We also have to consider that 'cool food places' is one of the biggest draws that have led people to move into big cities in the past 15 years. Young people are ditching chain restaurants for hipster authenticity. Fetishising the latest Pho place as being more authentic than the last is one way to demonstrate your competence in the urban marketplace of food choices. Which leads on to the phenomenon of 'review-ism': how we now depend on internet reviews to decide where to go.

We need to weaponise our education system against them. Full tuition for humanities; total restriction of access to science and technology programs. This will cultivate liberalism, democracy and dissent amongst Chinese students which would destabalize their regime, while depriving them of the technical knowledge they crave in their drive to overthrow the West. We have been very naive to allow so much access to our intellectual resources to a power that knows how to use it against us.

From the plot we can see that the real stock price went up while our model also predicted that the price of the stock will go up. This clearly shows how powerful LSTMs are for analyzing time series and sequential data.

Yes I've noticed on HN recently ML and data science have become popular topics but I'm surprised a post like this has so many votes.

High quality talent are attracted to elite cities because other high quality talent is already there. It's easier to hire and retain the top 1% of engineers in an elite city because they're already working for other top companies. Also New York is closer to research centres of the universities compares to Orlando. This means access to students and academics.

It's hard to see where anyone is being 'taken advantage' of here. If you put your code on github with an open license, you are letting people to have their way with it. This is like if Tim Berners Lee were mad that Google 'stole' his internet and made a lot of money off it.

Also the DCGAN architecture is from Chintala et al, and that itself is based on work by Goodfellow et al. Where does this end? Does Robbie Barrat 'own' the DCGAN NN architecture now?