thpalmear
Re:Ask HN: Who is hiring? (October 2016)
on Monday October 03, 2016 @02:39PM (#12630118)
Slack Bot Tester/QA | San Francisco CA | Remote OK | INTERNS OK
Slack Bot testers are needed for extending testing overall functionality of new slack bots and other messenger bots. Must be familiar with slack and at least the functionality of our current slack bot: http://sumve.com/slack/cc
Required: - Previous testing, curating or Quality Assurance work Optional: - Python and some scripting experience
Contact: [email protected]
Re:Sam Altman’s Manifest Destiny
on Monday October 03, 2016 @02:17AM (#12625730)
It's all about real AI today (not based on words and rules - lookup CTM - the real bots have this and its based on vector space). Get the companies and groups that are making very small breakthroughs in this area. The days of regurgitated cut-n-pasted text entry boxes and js (geocities, friendster, myspace, facebook) are over. Time for the new Googles of the world that will solve things bigger than SpaceX like extending human lifespan which is a requirement for space travel.
Re:The Berkeley Document Summarizer: Learning-Based, Single-Document S...
on Monday October 03, 2016 @12:24AM (#12625509)
That's not what was said. It's how the feature attributes in the vectors are constructed, scored and ranked in addition to the calculations used to score vectors for similarity.
Re:Our Part of the Milky Way Is Bigger Than Previously Thought
on Monday October 03, 2016 @12:21AM (#12625502)
When it comes to the Universe/Multiverse, everything is always bigger than we think.
Re:The Berkeley Document Summarizer: Learning-Based, Single-Document S...
on Sunday October 02, 2016 @03:48AM (#12621440)
Google has been to busy trying to lift methods from Berkeley Lab and passing it off as their own, in particular Tomas Mikolov https://www.kaggle.com/c/word2vec-nlp-tutorial/forums/t/1234...
Re:The Berkeley Document Summarizer: Learning-Based, Single-Document S...
on Sunday October 02, 2016 @03:14AM (#12621371)
In the end, language and libs don't matter as much as the actual relevancy of the algorithmic methods. This is where the real innovation and invention occurs, in the ability to mimic human cognition as closely as possible. This is also why side-by-side comparisons are the ultimate litmus and why there is now a separation happening between companies that regurgitate voyeuristic ideas (geocities, friendster, myspace, facebook-aol, snapchat, twitter-majordomo) verses companies that truly invent and innovate hard-to-duplicate initial algorithmic solutions (Google, SENS, Buck Inst., Human Longevity, SpaceX). It's like fake AI vs a path toward some semblance of real AI.
Re:The Berkeley Document Summarizer: Learning-Based, Single-Document S...
on Saturday October 01, 2016 @10:45PM (#12620836)
Here's some competition: http://sumve.com/slack/sumbot/sumbot11.html