researcher

A skilled, knowledgeable researcher could audit the code closely, and report any bugs they find. Cryptocat could fix all of those bugs.

'"In tests it even used the word bullshit in an answer to a researcher's query." ' I'm not sure which is worse: the singularity with a bullshit detector or without.

And you're a "security researcher" but "curious if this is an automated process"? please.

Me: "Ah, well, my last job title was 'Computer Science researcher' and before that I had several years of experience as a programmer, so I think I'll fit" [apparently not! ] HR: "Yes, but do you know algorithms?"

A review of many of the case studies was done by a prominent cerebellum researcher [1]. Typically the individuals that survive past birth live relatively normal lives but with impaired motor skills which are slower to develop.

- If by some miracle a researcher produces code which is high-quality and general enough to be used by others, the competitive atmosphere may cause them to want to keep it to themselves. Not as bad a problem in some fields, but I hear biology can be especially bad here.

At work we had a researcher from Yahoo Mail come in and give a presentation on the machine learning techniques they use to try and stop spammers abusing their mail servers. It was eye-opening to learn just what kind of hourly battle they face to keep spam out of their systems and the ways they are trying to combat it.

My perspective is as a researcher in academia. From here Python is far from needing to be revived, it is gaining ground. Also, Python 2 is still king and I suspect will remain popular - researchers rarely have the luxury/incentive to go back and improve it to comply with a language update.

You aren't going to be the world's best human genome researcher and C++ programmer; the time spent learning C++ could have been used to do research. The idea is: if you use a tool that lets you describe your problem at a high level and let the computer worry about how to do the calculation efficiently, you'll beat your hand-rolled C++ every time.

You can not trust any research done where the career of the researcher depends on them finding results. Universities, by hiring based on research credentials that currently translate roughly in the amount of positive results a person has generated, completely render worthless the research going on in their departments.

This incentivizes people to fix things quickly and preserves the reputational value of breaking into things without researcher-vendor relations getting adversarial when you announce something like "I harvested a couple dozen of your customers' API keys" or "Here's an exploitation roadmap you can follow in your browser" in a public forum.

Thanks in part to the popularity of his books, movie, and speeches, Kurzweil now knows pretty much every AI researcher in the planet, and we can safely assume he's aware of even very obscure research projects in the field, both inside and outside academia. Joining Google gives him ready access to data sets of almost unimaginable size, as well as unparalleled infrastructure and skills for handling such large data sets, putting him in an ideal position to connect researchers in academic and corporate settings with the data, infrastructure, and data management skills they need to make their visions a reality.