Jeff Dean

  • Student

Activity Feed

Prepare for comments about blockchain! This is a really interesting (and well written!) piece on voting machines. Open innovation traditionally relies on a public dataset or public collaboration on a product, and I am inspired by your summary of the field to think that this is an opportunity for both. As ES&S gradually accepts the inevitability of hacking attacks, their role becomes less ‘product manufacturer’ and more one of providing a trusted system – I could foresee a world 10 years from now where they have given up on making their margins on selling hardware, and instead have spend deep and meaningful time with a community of committed hackers building a robust and well-modeled software tool that focuses on issues of voter accessibility just as much as it does on cryptography. In my view, playing with the hardware is just the beginning – hopefully, this will open the door to talking about how America’s electoral system is structured, how to generate trust, and how to provide a reliable and accessible mechanism for civic engagement.

On November 13, 2018, Jeff Dean commented on ADIDAS – Additive Manufacturing for the Masses :

From a marketing perspective, this application of additive manufacturing is quite sexy! If I were to be optimistic and assume that the technology will be scalable and cheap enough to install in every Adidas retail shop, my follow-on question would be – what is the customer value? Customized orthotics in shoes are invaluable for correcting postural and gait issues, but their design requires complex tests by a podiatrist. If the customization, therefore, were purely aesthetic, why do this “on the spot” over the existing model of ordering customized shoes online that can be manufactured in factory for cheaper?

I would echo your last questions and worry even further – essentially, what will this really change? The idea that academia has access to little-surveyed oceanographic data has unclear benefits, and for private oil & gas companies, simply reading data (and even finding indicators of promising sites in overlooked areas) is not the barrier to starting a project – everything else is! Buying rights, construction & maintenance of extraction facilities, refinement … oil & gas companies are the only ones that could make use of this data in the first place, and now you’re just cutting out one of many large costs from them. From a cynic’s perspective, this effort really just sounds like it made the rich richer.

I’m glad that you ended your article on a skeptical note – as I can’t help but agree! The market for razors appears to be bifurcating between cheap replaceable razors and sophisticated electrics – I seriously doubt that this product is anything more than a flashy marketing effort. It has very little inherent consumer value beyond its novelty – why would a buyer even need the customization?

On November 13, 2018, Jeff Dean commented on Can ML replace Human Resources? :

What a great topic. I can’t help but wonder whether systems like this will ever work as standalone products, or whether they will be more successful if they are a feature of an existing communication platform (Slack, Email, etc.) I would think that the general principle of data mining is true here – the product will only be as good as its underlying data – and the companies that provide communication tools have that data in a silo. Why would a company like Humana have a right to win when Slack could make plugins that show you exactly how often and in what ways your organization’s sub-teams are interacting?

This is a fascinating topic! As sharing platforms begin to bear responsibility for the content they are used to disseminate, I wonder how this idea of fact checking and filtering might swing too far in the opposite direction – disincentivizing and burying less ‘factual’ media like editorials, opinion papers, and honest (yet uninformed) dialogue. Will there be an inevitable accidental cost to more opinion-based reportage while the filters are calibrated?