>I think it’s worth asking why anyone in their right mind should care about mid-century handwriting recognition algorithms in 2016.
Lots of people care, specially in Asia(Chinese and Japanese). It is just that the problem is incredible hard.
We put 5 very smart people working for a year on that, and it was totally impossible meeting people's expectations, specially people like doctors taking notes fast(and ugly).
We thought that the market was in creating mindmaps or something instead as people could write slower and better.
But people write a double u and expect the computer to see an "m". With deep learning is possible but extremely flimsy.
I have been doing that for years form me and for others(managing people) so they do not procrastinate with the team like they will do if alone. I do that without telling them I am doing that.
I will add some things I consider very important:
Use paper, write things down. Dividing a big task means nothing if you have no external memory you could trust to free the brain short term memory but you could recover it later. Paper today is the cheapest and more advanced external memory there is.
You could also use a tape recorder if you prefer audio memory.
After creating small sub task(tactics) from your general strategic thinking, put a checklist square near it. When you finish the task, check it.
Every hour of deep work, mark it on a calendar like a prisoner does with sticks. This provides visual feedback for your brain of your accomplishments, specially with hard tasks that takes months to complete.
The word for managing to do dread task is "reframing" into something that is important and positive for you.
Of course if you have money and power you could delegate most of the dreaded task, like googlers do with most of their domestic chores.
There are more things but the important thing is that you need practice, practice and practice until you get it. And like in anything else you will learn it much much faster if you personally know someone who "gets it" and learn from this person directly.
I have met some "naturals" of this processes in my life but I am not. I developed this skill over a long period of time, making me super productive compared to when I started.
I generally enjoy using paper for this reason as well, but I struggle with organizing the paper. Or, sticking to some form of organization.
I've tried setting up bullet journals, but paper discourages me for a few reasons.
- What if I need to edit or add extra content? I generally write in pen so that what I write down sticks around.
- I prefer to write in a stream of thoughts. To organize the paper, I try to think ahead and categorize my nebulous thoughts. This extra effort discourages me from writing and eventually, from using any organization system with paper.
I like Evernote because I can throw it in there and search will eventually help me find it.
In particular you could not compare injuries created by explosives in a war with advanced use on gunpowder with injuries made by stones, arrows and spears.
Gunpoder and canon shrapnel was extremely deadly because x-rays were not invented and doctors could not see were those fragments were in the body.
They were blind until Madame Curie started using X-rays in WWI and suddenly people started surviving. It took the Curies getting too much radiation though.
normal driving requires anticipating the behavior of other humans who may or may not entire your path of travel or anticipating unseen obstacles. it has less to do with "reaction times" than one would think. Humans routinely over-drive their vehicles capability to safely stop for an obstacle in front or adjacent to their path of travel.
> Humans routinely over-drive their vehicles capability to safely stop for an obstacle in front or adjacent to their path of travel.
Hence, the opportunity for an automated system that does not do that to be much safer, by relying on reaction times rather than strong AI.
Where a human driver would use subtle cues to anticipate a slowdown of the preceding vehicle before a turn, an automated system can get by by simply slamming the brakes in less than one millisecond when it detects braking from the other vehicle.
... and that self-driving car will make its passengers car sick and get rear ended by the human driver behind it.
those types of twitchy driving mechanics aren't normal and don't share the road well with normal humans. The physics of cars and reaction times would dictate that we program a self-driving car to drive like Grandma .... always maintain safe low speeds, very long following distances and braking hard for sketchy actions by other cars or random things near the road, but we know that actually makes the road more dangerous as humans drivers will aggressively cut-off and rear end this self-driving grandma. Secondly, that type of driving creates a bad public impression of self-driving cars hurting their chances of adoption. If you read some of the earlier impressions of Google/Waymo cars its clear they went down that path initially and had to change their approach.
If someone works for me 18 hours instead of 8 consistently I will fire him immediately.
We do not want overworked and burn out slaves, thank you very much.
Making more than 6 hours of real deep work every day is extremely challenging. Someone who tells me he is working 18...
We have some Indians that work for us, on similar terms than Europeans or Americans, living in Europe. Good workers and have earned their place, like the rest.
Remember that even the first serious cinematographers, like Lumiere brothers considered cinema just a "toy" with no practical applications.
From my perspective AR applications in the future will be huge in all areas as it means a new way to interface with 3d editing on real time.
But having said that, I do not believe Magic Leap will be the one who bring this to the table. I see magic Leap as the Altavista or pets.com of the Internet, burning investor money like crazy and trowing things to the wall expecting something to stick.
> the Altavista or pets.com of the Internet, burning investor money
I'm not sure it's fair to lump Altavista with pets.com.
The latter burned through something like 300 megabucks in just over 2 years.
The former was the first full-text search engine for the web and generated tens of megabucks of revenue, though they couldn't come up with a business model to keep it going (and eventualy lost out to Google on search quality [1], IIRC). I'm not sure we'll ever know how much it cost DEC to build and run it, but it seems credible that they at least came close to breaking even.
[1] Though I still miss their richer query language, incuding the NEAR keyword.
We will have to start migrating our software there into a more neutral platform.
I don't like the consolidation in Software in which there are only 5-6 huge players. It means politics and private interest of the conglomerate take precedence over everything else, like competence, and freedom.
Those oligopolies can just send their lawyers against competition or just buy them to stop the threat.
How can you tell that they lack nutrients? I have a basset hound and despite his supposedly excellent sense of smell he still enjoys "chocolate" snacks on a regular basis. He's an adult dog and getting Kirkland food. His weight is consistent and the vet is happy about what he weighs. I would love to be proven wrong (please!) but I doubt he's "snacking" because he lacks nutrients. I think he might be a little slow mentally and maybe he's _that_ hungry and doesn't have access to anything else to eat.
Lots of people care, specially in Asia(Chinese and Japanese). It is just that the problem is incredible hard.
We put 5 very smart people working for a year on that, and it was totally impossible meeting people's expectations, specially people like doctors taking notes fast(and ugly).
We thought that the market was in creating mindmaps or something instead as people could write slower and better.
But people write a double u and expect the computer to see an "m". With deep learning is possible but extremely flimsy.