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mjohn

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papers.ssrn.com 4y ago

Blue Screen of Death? Obsolescence and Structural Change in the Computer Age

mjohn
4pts0
www.ft.com 4y ago

San Francisco is scaring away the tech crowd

mjohn
9pts1
www.bloomberg.com 4y ago

For Tesla, Facebook and Others, AI’s Flaws Are Getting Harder to Ignore

mjohn
132pts182
www.bloomberg.com 4y ago

London House Prices Surge in Places Where More People Go Hungry

mjohn
2pts1
alanwinfield.blogspot.com 5y ago

The Grim Reality of Jobs in Robotics and AI

mjohn
3pts0
evonomics.com 5y ago

Why Immigration Drives Innovation

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2pts1
calpaterson.com 5y ago

Threat modelling case study: bicycles

mjohn
25pts12
www.theguardian.com 5y ago

In the months my husband and I were apart, the world changed completely

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1pts0
www.bloomberg.com 6y ago

Under Armour dumped an app

mjohn
68pts52
towardsdatascience.com 6y ago

Stop Hiring Data Scientists

mjohn
1pts0
evonomics.com 6y ago

Do Markets Make Us Fair, Trusting, and Cooperative, or Bring Out the Worst in Us

mjohn
1pts0
www.bloomberg.com 6y ago

We're Teaching Coding All Wrong

mjohn
4pts0
www.ft.com 7y ago

Police launch fraud investigation into Revolut

mjohn
1pts1
hipmunk.github.io 8y ago

The Zen of Chatbot State

mjohn
2pts0
www.ft.com 9y ago

Uber employees lose faith and explore exit

mjohn
31pts19
medium.com 9y ago

Things I’ve wasted money on in my startup this year and what I learned from it

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2pts0
www.telegraph.co.uk 9y ago

Three Mobile cyber hack: six million customers' private information at risk

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2pts0
www.bloomberg.com 9y ago

My Second Thoughts About Universal Basic Income

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3pts0
www.ft.com 9y ago

Renewables overtake coal as world’s largest source of power capacity

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2pts0
mobile.nytimes.com 9y ago

SoftBank and Saudi Arabia Partner to Form Giant Investment Fund

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2pts0
www.nytimes.com 9y ago

Relaxing Privacy Vow, WhatsApp to Share Some Data with Facebook

mjohn
1pts0
www.bloomberg.com 9y ago

So What If New York Is Unaffordable? That Helps the U.S

mjohn
2pts0
www.bloomberg.com 9y ago

All of a Sudden, Economists Are Getting Real Jobs

mjohn
1pts0
www.politico.eu 10y ago

Why Europe’s largest economy resists new industrial revolution

mjohn
5pts0
www.theguardian.com 10y ago

A viable shot at a better NHS has been killed off by privacy paranoia

mjohn
2pts2
www.bloomberg.com 10y ago

Doom, Gloom and Unease: London's Tech Scene Reacts to Brexit

mjohn
155pts384
ftalphaville.ft.com 10y ago

Decentralised courts and blockchains

mjohn
2pts0
blog.thecodewhisperer.com 10y ago

Integrated Tests Are a Scam (2010)

mjohn
1pts1
multithreaded.stitchfix.com 10y ago

Engineers Shouldn’t Write ETL

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291pts174
www.theguardian.com 10y ago

How much should we fear the rise of artificial intelligence?

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1pts0

Sure, why not, I'm just thinking out loud to be honest and am probably biased towards feeling quite comfortable using something like ChatGPT. I don't ask ChatGPT to write code for me but regularly use it to explore, a bit like a rubber duck that talks back.

Just curious - why would you not feel comfortable using it in an interview? Interesting to hear a different POV.

I've never tried it, but in the age of AI why not ask candidates to interact with ChatGPT to solve a problem?

In my (limited) interviewing experience the good candidates were the ones who had a good mental model for solving novel problems, were inquisitive and asked good questions. I think these attributes are also a reasonable indicator of general intelligence.

The people who I hired that were less successful were the ones who solved the coding exercises but had a poor mental model of how to solve novel problems and did not ask good questions.

Trying to use ChatGPT could take the pressure off from regurgiating coding minutae. The interviewer would be able to observe how the candidate approaches the problem and whether they can spot where ChatGPT goes wrong. It might also help introverted candidates since it feels less confrontational and there is likely to be less anxiety about unimportant details (after all any syntax mistakes would be ChatGPT's mistakes).

No, because it's often very hard to estimate until you're actually working on something. It's common to get a consensus estimate that something is "easy" only for some poor developer to be left with something that is "hard" and takes much longer than estimated.

Also, something might genuinely be easy for someone who has worked on that part of the codebase before. But it could take someone new a long time to get up to speed, again making that developer look bad (this is not to advocate that only devs familiar with the code should work on it - you want to spread the knowledge around).

In the UK there are regulations that require casinos and other gambling venues to block access if a problem gambler doesn't show restraint. It's much like how we would expect a barkeeper to tell a alcoholic who has had too much that they won't be served more and shouldn't drive home.

Similar addictive behaviour occurs with these apps and the games are designed to be as addictive as possible. While users should take personal responsibility, it would be trivial for these app producers to provide users with some protections from themselves.

That's a bit of a simplification.

From £9.5k to £50k you pay 12% national insurance in addition to income tax, so it's really 32% not 20% tax.

Over £50k you pay 2% national insurance.

Your employer will also be paying 13.8% national insurance.

Once your income exceeds £100k you start losing your personal allowance at a rate of £1 for every £2 over £100k, so you have no personal allowance after earning over £125k. This means that your effective marginal tax rate between £100k & £125k is about 60%

I pretty much agree with you, if the client doesn't have any in-house expertise and stays hands-off then you get the scenario I described but outsourcing can work if it's in addition to in-house expertise.

In this case the client didn't want .Net 3.0 experts to support a legacy app, that's what the consultants built it in and then let it turn into legacy by not performing regular maintenance.

The client didn't know that it was becoming legacy until it was too late because they never developed the in-house expertise to understand what was necessary and the consultants have no incentive to do it by themselves. In fact they can charge more by letting it rot and requiring development of a whole new project to replace the legacy.

I recently joined a company where my main task is to modernise a business critical application built and supported by Wipro over ten years ago. Everything is still on .Net 3.0 (first released in 2007), and despite hundreds of pages of documentation the developers seem to have little understanding of what the application actually does for the business.

The impression I have is that their business model is geared towards building one thing, learning one technology, and then exploiting it for as long as possible with minimal evolution. This is fine if you don't need the software to evolve, but most business applications do need to evolve even if slower than at a start-up or FAANG.

At least where I work there has been the recent realisation that outsourcing all your technology means you will struggle to iterate and improve that technology.

It's worth bearing in mind that this is not a study on educational outcomes, but is assessing how useful value-added models are for quantifying teacher performance. While the biggest correlative factor may well be socioeconomic status, that does not preclude teacher's having an impact on within-group differences.

From the introduction:

In this paper, we provide a stark illustration of the limitations to using value-added models to identify high-and low-performing teachers. We do this by applying commonly estimated models to an outcome that teachers cannot plausibly affect: student height. Aside from the implausibility of teacher effects on height, student height is an attractive measure for this exercise since it is symmetrically distributed, interval measured, and arguably less prone to measurement error than achievement. We find that the estimated teacher “effects”on height are nearly as large as the variation in teacher effects on math and reading achievement.

It's also an interesting approach: take a model that is apparently predictive and see if it's also predictive of something that we know is unrelated. By showing that value-added models are displaying spurious correlation maybe policymakers will take note.

Could maybe take a similar approach to validating our ML models?

Wool In The Gang, a supplier of knitting kits, was acquired for about the same price that investors put in; Crowdcube backers got a gift certificate in lieu of payment

This really surprised me, but it appears that investors had a choice between receiving cash or gift certificates worth more according to a Crowdcube blog post (http://blog.crowdcube.com/2016/08/30/over-5-million-has-been...):

Investors will receive their initial investment back plus a 5% return or a Wool and the Gang gift voucher, which would give them a 20% return on their investment.

Nonetheless 5% return on such a risky investment doesn't seem great.

Saying it's trivial that the developing world is improving could be interpreted as the developing world lacking importance in comparison to the developed world.

Did you mean it was easy to achieve (not that I would agree with that either).

Even within cities employers face competition that they need to respond to if they want to compete. There are plenty of employers in London trying to hire experienced software developers or PhD machine learning experts for less than I made 5 years ago as a junior developer, let alone compared to what banks in London are willing to pay.

There may well be a shortage, but that is all the more reason to increase salaries if you want to compete in the global market for software developers.

The point of the article is that objectively the world, as a whole, is getting better, and in some cases improving quite dramatically. Personally, I don't think the survey quoted in the opening paragraph is really that interesting - it's not the least bit surprising that people replied subjectively rather than objectively.

My point about the Chinese experience being more pertinent was regarding these objective measures not how people replied subjectively to a survey question. It's not that the Chinese experience is pertinent to someone in US or France, but that recent Chinese economic development has been more pertinent to whether or not the world has objectively gotten better.

In the future we are also going to see far more reductions in poverty and child mortality in countries like India and China than in the USA, because the USA is so much wealthier. Additionally, if we want to understand how to improve the world in the future, I believe it's more important to look at countries that have recently improved standards of living, like China, rather than countries like the USA that experienced their most significant improvements in standards of living before the 1960s.

Without knowing the future, I think the best we can do is look at historic trends to give us an idea of what is going to happen in the future. I agree 1800 is an interesting datapoint but probably not that relevant for the present day. Nonetheless, there appear to have been consistent improvements even in the past few decades, and there is still plenty of scope for improvement given almost 10% of the world population are in extreme poverty (about 700 million people).

I think a lot of people answering the survey question:

“All things considered, do you think the world is getting better or worse, or neither getting better nor worse?”

focus on whether their world is getting better or worse, and not the whole world. Most of the improvements in the past few decades have been in developing countries, which have experienced dramatic improvements in standards of living (and developing countries are also home to the majority of the global population). Meanwhile standards may well have been relatively stagnant or declining for many people in developed countries.

If we are talking about whether the world is getting better or worse, expectations based on experiences in India and China are far more pertinent than the recent history of the USA.

Most of the recent improvements have been in developing countries, because for a long time there have been a minuscule number of people in the US living on less that $1.9 a day.

For some sub-populations of the US things have gotten significantly worse in the past few decades and we should do something to help. Nonetheless, I think it's worth celebrating a reduction in the global rate of extreme poverty from 64% in 1960 to 9.6% in 2015.

It's also worth noting that the estimates are adjusted for inflation and price differences between countries, so changes in cost of living should not be a significant factor (even though adjusting historic data for inflation is imperfect).

It's sad how many comments dismiss the remarkable data, e.g. by commenting that the article "only" shows that average living conditions have improved, as if that is an argument against the conclusion that global living conditions have been continuously improving (and likely to continue if the trend continues).

The data shows that for all the selected metrics global living standards have improved, regardless of wealth distribution etc. For example, fewer children are dying today than in 1800 or 1960:

- a child born in 1800 had a 43.3% probability of dying before their fifth birthday

- in 1960 the probability was 18.5%

- in 2015 the probability was 4.25%

The 1800 estimate is astonishing. Almost half the children born in 1800 would probably have died by 1805. To me even the 1960 mortality rate is astonishing. Almost a fifth of all children born in 1960 would probably have died by 1965.

An even bigger improvement can be seen in extreme poverty (defined as living on $1.9 a day adjusted for inflation and price differences between countries):

- in 1820 94% of the global population lived in extreme poverty

- in 1960 64% lived in extreme poverty

- in 2015 only 9.6% lived in extreme poverty

I cannot see how such statistics can be interpreted as anything other than extraordinarily positive, and I just hope the trend continues.