kylebrown

According to the website, FindBugs was partially funded by a couple of NSF grants. So US taxpayers did indirectly pay for his services.

But if the startup gods aren’t smiling, and you can’t either figure out the cause and/or figure out how to correct it, it’s time to start working on a Plan B for the business. Plan B often includes kicking off a strategic process that ends up in the sale of the company before it becomes as obvious to others as it is to you that you’ve got a dying shark on your hands.

That sounds not entirely ethical / honest..

Is there a free/open-source download for RiakTS?

Or can anyone recommend something lighter-weight than full-blown Kafka etc.?

But something tells me that our society and economy derives zero benefit from nanosecond resolution trading vs. trading with say 1 minute resolution.

Not only does nanosecond resolution provide zero benefit, models indicate that it actually harms liquidity. To be specific, serial order processing in continuous-time is more efficient in "time-space", but less efficient in "volume-space". The better mechanism is batch order processing in discrete-time (i.e. process all arriving orders simultaneously in batch every 100 milliseconds, rather than one-by-one every nanosecond): http://faculty.chicagobooth.edu/eric.budish/research/HFT-Fre...

Otherwise a broker would just route mom n' pop's orders to the exchange that pays the biggest bribe to the broker (and screw mom n' pop).

A point of controversy is whether or not the 43 students were incinerated. The indedentent experts (GIEI) report insist that it was impossible:

Dr. José Luis Torero, an internationally recognized fire-investigation expert, was hired by the GIEI to conduct an independent examination into the incineration scenario. Torero, a Peruvian who participated in the forensic investigations of the World Trade Center attacks, has a Ph.D. from the University of California, Berkeley, and was previously a professor of fire security at the University of Edinburgh. He currently heads the School of Civil Engineering at the University of Queensland, Australia. The incineration of forty-three bodies in an open-air terrain like that of the Cocula dump, Torero concluded, would have required some thirty-three tons of wood or fourteen tons of pneumatic tires, along with the same amount of diesel fuel; the fire would have had to burn for sixty hours, not the twelve that the P.G.R. claimed it had, based on the confessions of captured Guerreros Unidos sicarios. The smoke from such a fire would have risen nearly a thousand feet into the sky and would have been visible for miles around; no such pillar of smoke was spotted, or even captured by satellite imagery.

The pro-government media is pushing back that its just one scientist's opinion, which is at odds with the opinion of scientists at UNAM (national university of mexico) who participated in the government investigation and concluded that the missing students _were_ incinerated.

Specifying a solution is easy; that's a purely technical exercise. The hard problem is figuring out how we get from where we are now (A) to where we want to go (B); that's a political problem.

The screenshot in the article is one I posted 9 months ago, and is being used without attribution: https://news.ycombinator.com/item?id=8593050

The other day, I ran across this in a Yudkowsky article[1]:

Suppose that earthquakes and burglars can both set off burglar alarms. If the burglar alarm in your house goes off, it might be because of an actual burglar, but it might also be because a minor earthquake rocked your house and triggered a few sensors. Early investigators in Artificial Intelligence, who were trying to represent all high-level events using primitive tokens in a first-order logic (for reasons of historical stupidity we won't go into) were stymied by the following apparent paradox: [.. snip ..] Which represents a logical contradiction, and for a while there were attempts to develop "non-monotonic logics" so that you could retract conclusions given additional data.

1. http://lesswrong.com/lw/ev3/causal_diagrams_and_causal_model...

In a hypothetical cyber-utopia or something, this could all just be a simple protocol (say, um, combining aspects of Direct Connect, BitTorrent, NNTP, Gopher, Bitcoin, GPG)

The article does mention p2p and decentralization, but the browser isn't whats holding that back. The client-server development paradigm is.

Currently, every dev making a p2p app has to roll their own platform because there's no standard (i.e. no LAMP, rails, or Heroku for deploying p2p apps). Some projects are working to change this, namely BitTorrent Maelstrom (which is a fork of Chromium with native support for magnet URLs, so it auto-renders an html/js package distributed via torrent); and http://ipfs.io (a sort of content-addressable p2p filesystem, or bittorrent on steroids).

Javascript package managers like npm tend to work much more seamlessly than the old unix ones. Wouldnt mind scrapping them all for https://node-os.com/

Also, the reason package managers suck is because.. entropy. See Joe Armstrong, The Mess We're In http://www.youtube.com/watch?v=lKXe3HUG2l4

Microsoft's first customer was IBM because an IBM VP sat on the board of Seattle National Bank with Bill Gates's mother (the bank was founded by Bill's grandfather).

Can we entirely rule out the possibility of AI researchers making advancements over time, and then eventually some research lab building one that's super intelligent compared to us? Why?

That's not the thing we should be worried about, or at least that's the point I got from the article. The thing we should be worried about is the way machine learning is applied in the here-and-now: the ethics of big data social networks, the robustness of complex (API-driven) systems, and so on. I fully agree that these issues are much more pressing and worrying than some emergent super-intelligence.

But I thought the article was weak in its discussion of dreams, creativity, and linear "flat data". It links to a June 2015 popular mechanics article about applying a genetic search optimization algorithm to discover gene regulatory networks, downplaying it as not-true-intelligence. But it does not mention deep neural networks and their higher-dimensional abstractions, particularly the psychedelic "inception" images.

The author also mentions "linear reasoning", and says he expects we'll learn more about intelligence from stem cell and Alzheimer's research, and the "tissues surrounding neurons, and the roles they play in contextual regulation." As if to set up some dichotomy between machine and biological intelligence. But what about deep neural networks?? I'm not sure how that would affect the author's arguments, but I'd like to see it discussed.

In the comments of a recent mathematics-without-apologies blog post[1], there was a back-and-forth between Jacob Lurie and Urs Schreiber (the author of the OP article on nLab). I've been trying to parse the material on nLab for years, good to know I'm not the only one who seems to have trouble with it. A refreshingly blunt discussion, not to be missed!

1. https://mathematicswithoutapologies.wordpress.com/2015/05/13...

I, for one, welcome our new corporate data center overlords.

Speaking of smalltalk, was project Oberon inspired by Alan Kay's STEPS project to implement a full OS + apps in under 20k LoC?

http://www.vpri.org/pdf/tr2008004_steps08.pdf

https://github.com/ejgallego/jscoq

Quoting from a comment on the linked article:

I’d only add that the corrupt elites were not only overspending, but they were involved in vendor finance scams. Hundreds of millions in bribes on some single deals. The credit came through to sign the contracts, and the bribes were rolled into the contracts. On one deal alone, Siemens, you had the Greek defense minister take hundreds of millions to approve a tens of billions deal. He is in jail, so are members of his family, but then there are 64 others being prosecuted as well for this one deal. Think about it, hundreds of millions spread to 64 people (who probably doled out more themselves).

You can't deny the fact that in the last decade, greeks have become accustomed to a certain life style that can no longer be maintained.

The point of the article is that the 'moral hazard' of lending and borrowing cuts both ways. What about the lifestyle of European bankers & elites? The lifestyle of elites was funded by their reckless lending, buying up "idiot paper" left and right (not just Greece). They believe themselves entitled to collect high-interest rents regardless of the risk which is priced into the interest rate!

To stretch an analogy, it'd be like Venture Capitalists blaming the startups for failing to earn returns on their investments.Rather than take responsibility for making risky investments, they demonize startup founders and employees, and threaten to break their legs until they pay back the firm.

Its "loan-shark theatre" between governments and central banks, with politicians stoking nationalist sentiment and stereotypes (as politicians do) in the service of elites (i.e. the creditors). Maybe you should read the article, instead of asserting "undeniable facts" (p.s. the greek economy has been in a worsening great depression for the last decade; and your handful of gamer acquaintances are a non-representative sample).

This is just begs the question of what the tax policy should be. If mainly income is taxed, then the rich get (proportionally) more votes. If mainly consumption is taxed, then everyone else (those who spend their income rather than save/invest it) gets more votes.

EDIT: disabled zoom?

Hah, the OP article does disable zoom. Disabled zoom is one of the frustrating things lately about iOS apps. Every time I try to show someone older than me something in a Skype chat, or (speaking of google) in a hangouts chat on the iPad... they cant read it - "Hang on... let me find my glasses."

Your reference [1] confused me because most of the books I saw were about code and design patterns, or books by Tufte. I also didn't realize what DoET meant, on first glance.

Thanks. These innocuous seeming algorithms may be even more influential than advertisements.

The Poisson process equation is actually in Satoshi's whitepaper. The 6-block confirmation rule-of-thumb comes from it.

That mammalian brains are motivated by optimization of energy expenditure. Like anything in biologically evolved systems, energy efficiency is key, since food is often scarce.

That doesn't square with empirical reality. Evolved biological systems appear to be optimized for robustness to perturbations, not efficiency (John Doyle argues that there is in fact a fundamental tradeoff between robustness and efficiency, for all types of complex systems not just biological).

how do mammalian brains problem solve using just thoughts.

They don't. Sensory input is required for brains to learn new classes of problems.

find a way to train RNNs that are able to adapt to new problems

Is this something different than multi-task learning?

The problem is simulations of the brain are not "machines", they are algorithms,

Simulations are executed on concrete machines that exist in the real world. Algorithms are abstract concepts.

e.g. they assume everything is happening at the information processing level.

Everything does happen at the information processing level. Any kind of physical process can be seen as a type of information processing. Information processing is not an abstract concept like an algorithm, for it to occur requires the time-evolution of concrete physical processes.

We can emulate the motions and powers in play in liquids, but not "wetness" in the sense of the physical property (moisture etc).

The physical property is experienced as sensory input. Machines can have sensory input.

An emulation can only water emulated flowers.

You are asserting that virtual reality is different from reality, which is true. That's not the GP's question. The question is whether there is a fundamental difference between machines in the real world (with sensors and arms and so on) and the human body and brain.

We recommend expanded research aimed at ensuring that increasingly capable AI systems are robust and beneficial: our AI systems must do what we want them to do.

The author points out that the meaning of this statement hinges on the word "we". Hasn't the world already arrived at a dystopian future where AI systems simply maximize revenue and ad clicks for their owners? Whereas "good" AI would be emloyed "for the people", i.e. to maximize social welfare while taking into account externalities (poverty and global warming).

The fear is of some future AI which acts only to further its own pathological interests... but how would that be different from present-day corporate bureacracies, with business processes increasingly driven by weak (but rapidly improving) AI? Seems to me that the owners of such systems are the only people who would fare differently under the two scenarios. But for the vast majority of the world, their experience would be the same in both cases: exploitation by autonomous AI, or exploitation by bureaucracy. Changing the parameters that control the way either one operates is equally difficult.

Smart contracts are pointless since you need trust anyway to deal with real-world assets.

jgarzik (bitcoin core dev) disagrees with you, he tweeted recently that he's excited about their potential (he calls them "active addresses"). Also, Nick Szabo disagrees with you.

Nobody would rather trade in a p2p system instead of "real" exchange either.

Lots of people would rather. There are many projects attempting to do decentralized/p2p exchange. For example, atomic cross-chain transactions have been on the horizon for a while now. And startups like tether.to, so that USD-tied assets can circulate in a decentralized manner (I won't mention ripple, but it is the same idea).

It is a natural evolution, the demand for an alternative to centralized exchanges comes from the same motivation to have an alternative to PayPal. Oh, and people also want a decentralized Silk Road (once they realize that its possible).

I see the FAQ says no callbacks. So as long as there aren't any callbacks, running app state should be preserved through code updates?

The video demos a React component, great. I hope amok will work with my current workflow, using jspm (rather than webpack or something).

Bo Xilai was deposed eight months before Xi Jinping took over. The corruption crackdown that ensued under Xi overwhelmingly targeted officials who were not "Second Generation Red." After Bo, other princelings made sure they got off scott-free by making a media spectacle of scapegoated fall guys: corrupt up-and-comers from "commoner families".