apu

scratch a liberal and a fascist bleeds

Incredible to see the bloodlust and warmongering here, cloaked in the language of technical interest.

I think it's the worst indictment of our entire industry that Victor doesn't have oodles of funding for life.

Context: this was a giant "subtweet" of the douchebag who (briefly) took over as co-host of At the Movies and violated every single one of these rules.

The big book of stuff that doesn't work.

lol. lmao.

the far right and far left are roughly equally wrong

Graham's sleights of hand used to be better hidden.

The "far left" and "far right" are not fixed points in ideological space (even within a single country).

Dropbox | Machine Learning Engineer | New York City, NY (SF and Seattle also possible) | Onsite, full-time

Dropbox is used by over half a billion people to share knowledge and coordinate work in organizations large and small. Our Machine Learning (ML) team is working on a variety of applications to make this process much easier and reduce the “work about work” that consumes a large part of many people’s days.

From images and videos to documents and audio (in every language!), we tackle it all. We leverage the full range of classic & modern ML techniques (whatever a problem calls for), including {semi,un,}supervised learning, deep learning of all flavors (from CNNs to LSTMs and beyond), and online/interactive learning.

Our current focus is on a set of features we’re calling DBXi (for intelligence); see this blog post for more details about our vision: https://blogs.dropbox.com/tech/2018/09/machine-intelligence-...

This involves investments into a number of different areas, including deep understanding of many different content types, extracting and representing knowledge to build connections between items, and analyzing file activity and hierarchies — at scale! — to help keep teams more organized and individuals more focused on the work that really matters.

We're looking for people with either academic or practical backgrounds in machine learning, ideally with experience in natural language understanding, information retrieval, or knowledge extraction. We’re growing an ML team within our NYC office and looking for both ML engineers and a NYC-based manager for this team. In addition, we also have openings in our existing ML teams in San Francisco/Bay Area and Seattle as well.

Responsibilities:

- Work within the Machine Learning Team to prototype, design, code, train, test, deploy, and iterate on large scale machine learning systems.

- Build delightful products and experiences for millions, while working alongside an excellent, cross-functional team across Engineering, Product and Design.

- Help shape the direction of machine learning and artificial intelligence at Dropbox.

Benefits and Perks:

- Having tremendous impact on products used by hundreds of millions of people around the world

- Working with a highly skilled and experienced ML team with backgrounds in industry & academia, across many different fields

- Market competitive total compensation package

- Comprehensive medical, dental, & vision insurance coverage

- 401k + company match

- Generous vacation & volunteer policy

- Free Dropbox space for your friends and family :-)

Please reach out to me to apply, or even just to chat/ask a question! (Contact info in my profile.)

Ah whoops! Sorry about that; I'll try to get an updated one. In the meantime, feel free to contact me (email address on my webpage at neerajkumar.org)

Dropbox does offer visa sponsorship in some cases.

Dropbox | Machine Learning Engineer | San Francisco, CA | Onsite, full-time

Dropbox’s Machine Learning team develops high-impact solutions that touch millions of people and a lot of data. From images and videos to documents and audio (in every language!), the Dropbox ML team tackles it all. We leverage the full range of classic & modern ML techniques (whatever a problem calls for!), including {semi,un,}supervised learning, deep learning of all flavors (from CNNs to LSTMs and beyond!), and online/interactive learning.

See this blog post for a deep-dive into a recent feature we developed (OCR on scanned documents): https://blogs.dropbox.com/tech/2017/04/creating-a-modern-ocr

We're looking for people with either academic or practical backgrounds in machine learning, ideally with experience in natural language understanding, information retrieval, knowledge extraction, and/or deep learning.

Responsibilities:

- Work within the Machine Learning Team to prototype, design, code, train, test, deploy, and iterate on large scale machine learning systems.

- Build delightful products and experiences for millions, while working alongside an excellent, cross-functional team across Engineering, Product and Design.

- Help shape the direction of machine learning and artificial intelligence at Dropbox.

Benefits and Perks:

- Getting to make a tremendous impact on our infrastructure & products, which are used by hundreds of millions of people around the world

- Working with a highly skilled and experienced team (small, but growing fast!) with backgrounds in industry & academia, across many different fields

- Market competitive total compensation package

- 100% company-paid individual medical, dental, & vision insurance coverage

- 401k + company match

- Generous vacation & volunteer policy

- Free Dropbox space for your friends and family :-)

Apply here: https://www.dropbox.com/jobs/listing/533100

Please don't hesitate to reach out to me, even if just to ask a question or clarify something! (Contact info in my profile)

Dropbox | Machine Learning Engineer | San Francisco, Seattle, New York | Onsite, full-time

Dropbox’s Machine Learning team develops high-impact solutions that touch millions of people and a lot of data. From images and videos to documents and audio (in every language!), the Dropbox ML team tackles it all. We leverage the full range of classic & modern ML techniques (whatever a problem calls for!), including {semi,un,}supervised learning, deep learning of all flavors (from CNNs to LSTMs and beyond!), and online/interactive learning.

See this blog post for a deep-dive into a recent feature we developed (OCR on scanned documents): https://blogs.dropbox.com/tech/2017/04/creating-a-modern-ocr

We're looking for people with either academic or practical backgrounds in machine learning, ideally with experience in natural language understanding, information retrieval, knowledge extraction, and/or deep learning.

Responsibilities:

- Work within the Machine Learning Team to prototype, design, code, train, test, deploy, and iterate on large scale machine learning systems.

- Build delightful products and experiences for millions, while working alongside an excellent, cross-functional team across Engineering, Product and Design.

- Help shape the direction of machine learning and artificial intelligence at Dropbox.

Benefits and Perks:

- Getting to make a tremendous impact on our infrastructure & products, which are used by hundreds of millions of people around the world

- Working with a highly skilled and experienced team with backgrounds in industry & academia, across many different fields

- Market competitive total compensation package

- 100% company-paid individual medical, dental, & vision insurance coverage

- 401k + company match

- Generous vacation & volunteer policy

- Free Dropbox space for your friends and family :-)

Apply here: https://www.dropbox.com/jobs/listing/533100 (the listing says San Francisco, but Seattle and NYC are also options)

Please don't hesitate to reach out to me, even if just to ask a question or clarify something! (Contact info in my profile)

Dropbox | Machine Learning Engineer | San Francisco, Seattle, New York | Onsite, full-time

Dropbox’s Machine Learning team develops high-impact solutions that touch millions of people and a lot of data. From images and videos to documents and audio (in every language!), the Dropbox ML team tackles it all! We leverage the full range of classic & modern ML techniques (whatever a problem calls for!), including {semi,un,}supervised learning, deep learning of all flavors (from CNNs to LSTMs and beyond!), and online/interactive learning.

See this blog post for a deep-dive into a recent feature we developed (OCR on scanned documents): https://blogs.dropbox.com/tech/2017/04/creating-a-modern-ocr

We're looking for people with either academic or practical backgrounds in machine learning, ideally with experience in natural language understanding, information retrieval, knowledge extraction, and/or deep learning.

Responsibilities:

- Work within the Machine Learning Team to prototype, design, code, train, test, deploy, and iterate on large scale machine learning systems.

- Build delightful products and experiences for millions, while working alongside an excellent, cross-functional team across Engineering, Product and Design.

- Help shape the direction of machine learning and artificial intelligence at Dropbox.

Benefits and Perks:

- Getting to make a tremendous impact on our infrastructure & products, which are used by hundreds of millions of people around the world

- Working with a highly skilled and experienced team with backgrounds in industry & academia, across many different fields

- Market competitive total compensation package

- 100% company-paid individual medical, dental, & vision insurance coverage

- 401k + company match

- Generous vacation & volunteer policy

- Free Dropbox space for your friends and family :-)

Apply here: https://www.dropbox.com/jobs/listing/533100

Please don't hesitate to reach out to me, even if just to ask a question or clarify something! (Contact info in my profile)

Dropbox | Machine Learning Engineer | San Francisco, Seattle, New York | Onsite, full-time

Dropbox’s Machine Learning team develops high impact solutions that touch millions of people and a lot of data. From images and videos to documents and audio (in every language!), the Dropbox ML team tackles it all! We leverage the full range of classic & modern ML techniques (whatever a problem calls for!), including {semi,un,}supervised learning, deep learning of all flavors (from CNNs to LSTMs and beyond!), and online/interactive learning.

See this blog post for a deep-dive into a recent feature we developed (OCR on scanned documents): https://blogs.dropbox.com/tech/2017/04/creating-a-modern-ocr

We're looking for people with either academic or practical backgrounds in machine learning, ideally with experience in natural language understanding, information retrieval, knowledge extraction, and/or deep learning.

Responsibilities:

- Work within the Machine Learning Team to prototype, design, code, train, test, deploy, and iterate on large scale machine learning systems.

- Build delightful products and experiences for millions, while working alongside an excellent, cross-functional team across Engineering, Product and Design.

- Help shape the direction of machine learning and artificial intelligence at Dropbox.

Benefits and Perks:

- Getting to make a tremendous impact on our infrastructure & products, which are used by hundreds of millions of people around the world

- Working with a highly skilled and experienced team with backgrounds in industry & academia, across many different fields

- Market competitive total compensation package

- 100% company-paid individual medical, dental, & vision insurance coverage

- 401k + company match

- Generous vacation & volunteer policy

- Free Dropbox space for your friends and family :-)

Apply here: https://www.dropbox.com/jobs/listing/533100

Please don't hesitate to reach out to me, even if just to ask a question or clarify something! (Contact info in my profile)

Dropbox | Machine Learning Engineer | San Francisco, Seattle, New York | Onsite, full-time

Dropbox’s Machine Learning group develops high impact solutions that touch millions of people and a lot of data. From images to documents in every language, the Dropbox ML team delivers solutions across a number of domains, from computer vision to natural language processing and more. We leverage the full range of classic & modern ML techniques (whatever a problem calls for!), including supervised/semi-supervised/unsupervised learning, deep learning of all flavors (from CNNs to LSTMs and even newer stuff as well), and online/interactive learning. While some of our algorithms run on mobile devices, others require large clusters on our infrastructure.

See this blog post for a deep-dive into a recent feature we developed (OCR on scanned documents): https://blogs.dropbox.com/tech/2017/04/creating-a-modern-ocr...

We're looking for people with either academic or practical backgrounds in machine learning, ideally with experience in natural language understanding, information retrieval, knowledge extraction, or deep learning.

Responsibilities:

- Work within the Machine Learning Team to design, code, train, test, deploy and iterate on large scale machine learning systems.

- Build delightful products and experiences for millions, while working alongside an excellent, cross-functional team across Engineering, Product and Design.

- Help shape the direction of machine learning and artificial intelligence at Dropbox.

Benefits and Perks:

- Getting to make a tremendous impact on our infrastructure & products, which are used by hundreds of millions of people around the world

- Working with a highly skilled and experienced team with backgrounds in industry & academia and many different fields

- Market competitive total compensation package

- 100% company paid individual medical, dental, & vision insurance coverage

- 401k + company match

- Wellness Reimbursement

- Generous vacation & volunteer policy

- Free Dropbox space for your friends and family :-)

Apply here: https://www.dropbox.com/jobs/listing/533100

Wilson was racist even by the standards of his time.

This is an important point. People are thinking about it, and a lot of it will have to do with how the input data is gathered and curated.

It took me a bit longer than 15 minutes (maybe a hour or so), but this guide really worked for me when I visited Korea for a week last year. I couldn't really believe it was that simple!

Please be civil.

BTW, the person you're replying to is a lawyer. Are you?

Funny to see that latter link on this message board, of all places.

That doesn't fit any of the best developers I've seen.

Perhaps the people you've seen are not, in fact, very good?

More than people realize... Google and apple, for example, use sfm heavily to compute their 3d maps (in Google earth and the apple equivalent). Google also uses it in various other products.

A lot of the underlying machinery is similar: they both rely on "structure from motion" (sfm) techniques to automatically estimate both camera locations and 3d geometry of the scene simultaneously. And both works come from the same lab: the GRAIL group at the University of Washington.

(I postdoced in that lab for 3 years and the authors of this paper are friends/former colleagues.)

I can't tell if you're continuing the joke or genuinely missed it...

(although given your prior comment history, I'm guessing the latter)

Also weird crashes with ultra json, lack of nice formatting in outputs, and high memory usage in some situations

https://www.google.com/search?q=%22*%20is%20about%20to%20*%2...

You might want to talk about the diversity benefits of this approach. In particular, it would be attractive to lots of companies if you can make a credible case for this attracting traditionally hard-to-reach demographics, and then of course assessing them more fairly.

And if you've not seen it yourself in 10 years, of course it must not exist.

I highly recommend this book [1] on Licklider's life, because it's also one of the best books on the computing movement from the creation of the early machines through the Xerox PARC years and slightly beyond. It's also the only one recommended by Alan Kay[2].

[1] http://www.amazon.com/The-Dream-Machine-Licklider-Revolution...

[2] http://www.mail-archive.com/fonc@vpri.org/msg04144.html

Crazy that it's been so long. Did any site used to have as in-depth reviews as AnandTech regularly does? My impression is that AT is what pushed other sites into having such detailed hardware reviews...

These are so great! I recognized a couple of them from hacker news as well -- so perhaps they might be usable here in a semi-automated way to detect bad conversations?

(I know there's already a flame-war detector. But other patterns might be useful as well.)