predictable. It panders to a common denominator. We build buckets and templates to hold every kind of content, then move on to the next component of the system. Digital design is a human assembly line.” Travis Gertz, ‘Design Machines’ >> https://louderthanten.com/articles/story/design-machines
from one media player to another. It took the automated system 26 hours to complete the transplant, while VLC's manual addition of the code happened over a period of 20 days.” Automated system to take code from one base and move it to another. Currently C only, but could work in any language. http://www.wired.co.uk/news/archive/2015-07/30/code-organ-transplant-software-myscalpel
and fine- tunes code without ever needing the original source, in a matter of hours or even minutes.” Performance increases between 75% and 500% in tests. http://news.mit.edu/2015/computer-program-fixes-old-code-faster-than-expert-engineers-0609 The developers are probably feeling less smug now.
and perfecting our machine-like assembly techniques, others have been watching closely and assembling their own machines. We’ve designed ourselves right into an environment ripe for automation.” All of the workflow tools we’ve built make our jobs automatable. These quotes are from a fairly mandatory article, ‘Design Machines’ by Travis Gertz. But the best thing about the article is that he also suggests a solution to the problem:
humanlike intelligence. Lovelace Test: artificial agent must produce an original program (music, poem, etc) that it was not engineered to produce. Must be reproducible, and unexplainable. http://www.slate.com/articles/health_and_science/new_scientist/2014/12/lovelace_test_of_artificial_intelligence_creativity_better_than_the_turing.html
of people to do non- routine, non-repetitive tasks. Teaching innovation and creativity could be one way to get there.” Andrew Ng is a major player in Google and Baidu’s AI. He has major concerns about the effects of automation and AI on employment. http://www.huffingtonpost.com/2015/05/13/andrew-ng_n_7267682.html
Watson’s capabilities, using Node/Java and a range of RESTFUL APIs. They just brought a whole range into general availability. They want to be the ubiquitous platform of AI, as Windows was to the home PC and Android to mobile. http://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/
can i help you with today? Human: hi, i forgot my password. can you tell me how i can recover it? Machine: i’ll need to verify who it is at that machine. can we do a hangout? Human: yes Machine: <a hangout ensues> Human: cool, i am good now Google trained the system using old support calls. http://www.wired.com/2015/06/google-made-chatbot-debates-meaning-life/
where each utterance follows from what’s already been said and is relevant to the overall interaction. Dialog systems must maintain a context over several turns.” http://radar.oreilly.com/2015/09/talking-to-the-iot.html
virtual assistant. Siri in Apple TV, Apple Car, Apple Watch etc. Google Voice Search, also in Android, Chrome, Wear, Auto, TV, etc. … in your Windows 10 laptop.
from 26% to 8%. That’s from one word in 4 to one word in 12. This was a few months ago - a recent update is even better. Baidu, ‘China’s Google’, says theirs is 6% - one word in 17.
Not all options are available, but I can train it to use them. I used Chicago because an unfortunate drawback is that they don’t always recognise British English.