nhaliday + error + security   4

Linus's Law - Wikipedia
Linus's Law is a claim about software development, named in honor of Linus Torvalds and formulated by Eric S. Raymond in his essay and book The Cathedral and the Bazaar (1999).[1][2] The law states that "given enough eyeballs, all bugs are shallow";


In Facts and Fallacies about Software Engineering, Robert Glass refers to the law as a "mantra" of the open source movement, but calls it a fallacy due to the lack of supporting evidence and because research has indicated that the rate at which additional bugs are uncovered does not scale linearly with the number of reviewers; rather, there is a small maximum number of useful reviewers, between two and four, and additional reviewers above this number uncover bugs at a much lower rate.[4] While closed-source practitioners also promote stringent, independent code analysis during a software project's development, they focus on in-depth review by a few and not primarily the number of "eyeballs".[5][6]

Although detection of even deliberately inserted flaws[7][8] can be attributed to Raymond's claim, the persistence of the Heartbleed security bug in a critical piece of code for two years has been considered as a refutation of Raymond's dictum.[9][10][11][12] Larry Seltzer suspects that the availability of source code may cause some developers and researchers to perform less extensive tests than they would with closed source software, making it easier for bugs to remain.[12] In 2015, the Linux Foundation's executive director Jim Zemlin argued that the complexity of modern software has increased to such levels that specific resource allocation is desirable to improve its security. Regarding some of 2014's largest global open source software vulnerabilities, he says, "In these cases, the eyeballs weren't really looking".[11] Large scale experiments or peer-reviewed surveys to test how well the mantra holds in practice have not been performed.

Given enough eyeballs, all bugs are shallow? Revisiting Eric Raymond with bug bounty programs: https://academic.oup.com/cybersecurity/article/3/2/81/4524054

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8 weeks ago by nhaliday
Information Processing: US Needs a National AI Strategy: A Sputnik Moment?
FT podcasts on US-China competition and AI: http://infoproc.blogspot.com/2018/05/ft-podcasts-on-us-china-competition-and.html

A new recommended career path for effective altruists: China specialist: https://80000hours.org/articles/china-careers/
Our rough guess is that it would be useful for there to be at least ten people in the community with good knowledge in this area within the next few years.

By “good knowledge” we mean they’ve spent at least 3 years studying these topics and/or living in China.

We chose ten because that would be enough for several people to cover each of the major areas listed (e.g. 4 within AI, 2 within biorisk, 2 within foreign relations, 1 in another area).

AI Policy and Governance Internship: https://www.fhi.ox.ac.uk/ai-policy-governance-internship/

Deciphering China’s AI Dream
The context, components, capabilities, and consequences of
China’s strategy to lead the world in AI

Europe’s AI delusion: https://www.politico.eu/article/opinion-europes-ai-delusion/
Brussels is failing to grasp threats and opportunities of artificial intelligence.

When the computer program AlphaGo beat the Chinese professional Go player Ke Jie in a three-part match, it didn’t take long for Beijing to realize the implications.

If algorithms can already surpass the abilities of a master Go player, it can’t be long before they will be similarly supreme in the activity to which the classic board game has always been compared: war.

As I’ve written before, the great conflict of our time is about who can control the next wave of technological development: the widespread application of artificial intelligence in the economic and military spheres.


If China’s ambitions sound plausible, that’s because the country’s achievements in deep learning are so impressive already. After Microsoft announced that its speech recognition software surpassed human-level language recognition in October 2016, Andrew Ng, then head of research at Baidu, tweeted: “We had surpassed human-level Chinese recognition in 2015; happy to see Microsoft also get there for English less than a year later.”


One obvious advantage China enjoys is access to almost unlimited pools of data. The machine-learning technologies boosting the current wave of AI expansion are as good as the amount of data they can use. That could be the number of people driving cars, photos labeled on the internet or voice samples for translation apps. With 700 or 800 million Chinese internet users and fewer data protection rules, China is as rich in data as the Gulf States are in oil.

How can Europe and the United States compete? They will have to be commensurately better in developing algorithms and computer power. Sadly, Europe is falling behind in these areas as well.


Chinese commentators have embraced the idea of a coming singularity: the moment when AI surpasses human ability. At that point a number of interesting things happen. First, future AI development will be conducted by AI itself, creating exponential feedback loops. Second, humans will become useless for waging war. At that point, the human mind will be unable to keep pace with robotized warfare. With advanced image recognition, data analytics, prediction systems, military brain science and unmanned systems, devastating wars might be waged and won in a matter of minutes.


The argument in the new strategy is fully defensive. It first considers how AI raises new threats and then goes on to discuss the opportunities. The EU and Chinese strategies follow opposite logics. Already on its second page, the text frets about the legal and ethical problems raised by AI and discusses the “legitimate concerns” the technology generates.

The EU’s strategy is organized around three concerns: the need to boost Europe’s AI capacity, ethical issues and social challenges. Unfortunately, even the first dimension quickly turns out to be about “European values” and the need to place “the human” at the center of AI — forgetting that the first word in AI is not “human” but “artificial.”

US military: "LOL, China thinks it's going to be a major player in AI, but we've got all the top AI researchers. You guys will help us develop weapons, right?"

US AI researchers: "No."

US military: "But... maybe just a computer vision app."

US AI researchers: "NO."

AI-risk was a mistake.
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february 2018 by nhaliday
Interview: Mostly Sealing Wax | West Hunter

- conformity and Google, defense and spying (China knows prob almost all our "secrets")
- in the past you could just find new things faster than people could reverse-engineer. part of the problem is that innovation is slowing down today (part of the reason for convergence by China/developing world).
- introgression from archaics of various kinds
- mutational load and IQ, wrath of khan neanderthal
- trade and antiquity (not that useful besides ideas tbh), Roman empire, disease, smallpox
- spices needed to be grown elsewhere, but besides that...
- analogy: caste system in India (why no Brahmin car repairmen?), slavery in Greco-Roman times, more water mills in medieval times (rivers better in north, but still could have done it), new elite not liking getting hands dirty, low status of engineers, rise of finance
- crookery in finance, hedge fund edge might be substantially insider trading
- long-term wisdom of moving all manufacturing to China...?
- economic myopia: British financialization before WW1 vis-a-vis Germany. North vs. South and cotton/industry, camels in Middle East vs. wagons in Europe
- Western medicine easier to convert to science than Eastern, pseudoscience and wrong theories better than bag of recipes
- Greeks definitely knew some things that were lost (eg, line in Pliny makes reference to combinatorics calculation rediscovered by German dude much later. think he's referring to Catalan numbers?), Lucio Russo book
- Indo-Europeans, Western Europe, Amerindians, India, British Isles, gender, disease, and conquest
- no farming (Dark Age), then why were people still farming on Shetland Islands north of Scotland?
- "symbolic" walls, bodies with arrows
- family stuff, children learning, talking dog, memory and aging
- Chinese/Japanese writing difficulty and children learning to read
- Hatfield-McCoy feud: the McCoy family was actually a case study in a neurological journal. they had anger management issues because of cancers of their adrenal gland (!!).

the Chinese know...: https://macropolo.org/casting-off-real-beijings-cryptic-warnings-finance-taking-economy/
Over the last couple of years, a cryptic idiom has crept into the way China’s top leaders talk about risks in the country’s financial system: tuo shi xiang xu (脱实向虚), which loosely translates as “casting off the real for the empty.” Premier Li Keqiang warned against it at his press conference at the end of the 2016 National People’s Congress (NPC). At this year’s NPC, Li inserted this very expression into his annual work report. And in April, while on an inspection tour of Guangxi, President Xi Jinping used the term, saying that China must “unceasingly promote industrial modernization, raise the level of manufacturing, and not allow the real to be cast off for the empty.”

Such an odd turn of phrase is easy to overlook, but it belies concerns about a significant shift in the way that China’s economy works. What Xi and Li were warning against is typically called financialization in developed economies. It’s when “real” companies—industrial firms, manufacturers, utility companies, property developers, and anyone else that produces a tangible product or service—take their money and, rather than put it back into their businesses, invest it in “empty”, or speculative, assets. It occurs when the returns on financial investments outstrip those in the real economy, leading to a disproportionate amount of money being routed into the financial system.

Bad day for Lehman Bros.
Good day for everyone else, then.
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may 2017 by nhaliday

bundles : abstractengframehackerinfointerwebparanoiatechiethinkingvague

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