faustomorales
Joined 9 years ago
Joined 9 years ago
For example, a criticism an opponent of Al Gore might make is something like, “Would you still be an advocate for climate policy X if you didn’t stand to gain $Y due to its implementation?”
Of course, I’m not saying the criticism necessarily holds up to careful scrutiny. And, from what I can tell, neither does the author of this article.
As more context, I do remember thinking, "that X number seems higher than I would expect, but maybe we had a lot of folks who signed up for the event that didn't show." I worked at a small company so the size of the company was on the same order of magnitude as the number of invitees to the event (~100). I explained away the Y time zones because I knew some people traveled internationally. I was also operating on very little sleep, so that probably didn't help.
"Thank you everyone for contributing to our shared mission. When you are done with your work today, please delete all the data from your machines. Hope we see each other again soon!"
Slack gave me a dire warning that my message would send notifications to so many people across so many time zones. This didn't surprise me because attendees came from various countries for the event. So I dismissed it.
But I had accidentally sent it to my company's Slack organization instead of the hackathon-specific one. I didn't realize it until a co-worker sent me a private message asking why I had just tried to fire everyone at our company.
You do have to set up an account and sign in to use the service, which I know is not appreciated in a Show HN. But the main page has a pretty clear demo showing how it works to help you decide if it's worth a look, the privacy policy is straightforward, we only collect your email address, there are no trackers at all, and you can delete your account along with all your data with just one click.
Full disclosure: I'm the primary package developer. Shameless plug. :)
[1] https://github.com/faustomorales/keras-ocr#comparing-keras-o...
Some use cases for this package:
- You can use the pretrained (trained by others!) models for OCR (see the README for an example) on English text. [0]
- You can fine-tune a version of the detection and recognition models on a different alphabet / language (see the tutorial [1]).
- You can just use the data generator with backgrounds and fonts (I provide a packaged set of both) to create images with character-level annotations for some other model [2].
I'd really like to continue improving the image generator to render more realistic images while retaining the existing mix of simplicity / flexibility. Ideas welcome!
[0] https://keras-ocr.readthedocs.io/en/latest/examples/using_pr...
[1] https://keras-ocr.readthedocs.io/en/latest/examples/end_to_e...
[2] https://keras-ocr.readthedocs.io/en/latest/examples/end_to_e...
In a bit of a twist, worth noting that Exxon Research & Engineering was involved in the invention of the rechargeable lithium ion battery [2]. Quoting from [3], "Thus Stanley Whittingham invented the first rechargeable LIB, patented in 1977 and assigned to Exxon."
[1] https://ir.exxonmobil.com/static-files/37b7e1b7-620b-4248-a3...
[2] https://patents.justia.com/patent/4009052
[3] https://www.currentscience.ac.in/Volumes/117/09/1416.pdf
Disclosure: I worked for ExxonMobil from 2012-2017 but don't have any remaining ties.