Research Debt

Achieving a research-level understanding of most topics is like climbing a mountain. Aspiring researchers must struggle to understand vast bodies of work that came before them, to learn techniques, and to gain intuition. Upon reaching the top, the new researcher begins doing novel work, throwing new stones onto the top of the mountain and making it a little taller for whoever comes next.

Mathematics is a striking example of this. For centuries, countless minds have climbed the mountain range of mathematics and laid new boulders at the top. Over time, different peaks formed, built on top of particularly beautiful results. Now the peaks of mathematics are so numerous and steep that no person can climb them all. Even with a lifetime of dedicated effort, a mathematician may only enjoy some of their vistas.

People expect the climb to be hard. It reflects the tremendous progress and cumulative effort that’s gone into mathematics. The climb is seen as an intellectual pilgrimage, the labor a rite of passage. But the climb could be massively easier. It’s entirely possible to build paths and staircases into these mountains.1 The climb isn’t something to be proud of.

The climb isn’t progress: the climb is a mountain of debt.

Source: Research Debt

 

Google’s DeepMind made ‘inexcusable’ errors handling UK health data, says report – The Verge

A new academic report examining a deal between Google’s AI subsidiary DeepMind and the UK’s National Health Service (NHS) has said that the US tech giant made “inexcusable” errors in terms of transparency and oversight when handling sensitive medical information.

The data-sharing agreement — which was signed in 2015 and has since been superseded by a new contract — allows DeepMind access to medical records from 1.6 million patients attending London hospitals run by the NHS Royal Free Trust. Although at the time Google presented the deal as primarily about finding patients at risk from a condition known as acute kidney injury or AKI, the actual terms of the agreement, revealed in April 2016 by a New Scientist investigation, were more broad.

The report notes that DeepMind was given access not only to relevant blood tests and diagnostics, but historical medical records dating back five years, including information on HIV diagnoses, drug overdoses, and abortions. The report also says the wording of the 2015 deal did not constrain the company from using AI analytical techniques on the data (something DeepMind disputes).

Source: Google’s DeepMind made ‘inexcusable’ errors handling UK health data, says report – The Verge

 

Principles for C programming – Drew DeVault’s Blog

In the words of Doug Gwyn, “Unix was not designed to stop you from doing stupid things, because that would also stop you from doing clever things”. C is a very powerful tool, but it is to be used with care and discipline. Learning this discipline is well worth the effort, because C is one of the best programming languages ever made. A disciplined C programmer will…

Source: Principles for C programming – Drew DeVault’s Blog

 

Greg – Sam Altman

A lot of people ask me what the ideal cofounder looks like.  I now have an answer: Greg Brockman.

Every successful startup I know has at least one person who provides the force of will to make the startup happen.  I’d thought a lot about this in the abstract while advising YC startups, but until OpenAI I hadn’t observed up close someone else drive the formation of a startup.

OpenAI wouldn’t have happened without Greg.  He commits quickly and fully to things.  I organized a group dinner early on to talk about what such an organization might look like, and drove him home afterwards.  Greg asked me questions for the first half of the drive back to San Francisco, then declared he was in, and started planning logistics for the rest of the drive.

Source: Greg – Sam Altman