If you wanted to do research on a specific joseki to see if AG0 found
weaknesses or explored alternatives, especially in games past day 3 (when
it began besting AGM), it would be quite interesting to see, through that
explicit filter, what kinds of things emerged around that specific joseki.
You might even discover that the joseki has weaknesses in several early
branches which haven't been found by humans in hundreds of years of using
the joseki.

Another angle is pretty much every game from AG0 day 4 forward would be
superior to the 100,000 games of the pro players upon which AGM was
trained. IOW, that is a huge number of games that exceed the very best
human-vs-human games quality and would be quite superior to seeding with
those human (biased) games for any other engine playing in the area.

Or, someone training a net, could walk up the 29 million games and explore
how their engine differs, make adjustments and explore climbing higher.
This data set enables "higher" in a totally different way than any prior
data set.

The number and variety of things that could be explored with the 29 million
games boggles the mind. I am deeply hopeful they do some form of simple
compressed dump of it somewhere. Then, it would be just a matter of getting
it loaded into a DB to create all sorts of indexes, queries, novel subsets,
etc.


Namaste,

Jim O'Flaherty
Founder/CEO
Precision Location Intelligence, Inc.
<http://www.precisionlocationintelligence.com/> • Irving, TX, USA
469-358-0633 <4693580633> • jim.oflaherty...@gmail.com •
www.linkedin.com/in/jimoflahertyjr

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On Mon, Oct 23, 2017 at 9:44 AM, Petri Pitkanen <petri.t.pitka...@gmail.com>
wrote:

> If the AG got better by playing against itself rather than training on
> previous good players then I do not thing training data is that important.
> Perhaps it is but google has shown that actually u dont need it. Just loads
> of processing will do the trick.
>
>
>
> 2017-10-23 15:05 GMT+03:00 Jim O'Flaherty <jim.oflaherty...@gmail.com>:
>
>> Couldn't they be useful as part of a set of training data for newly
>> trained engines and networks?
>>
>> On Oct 23, 2017 2:34 AM, "Petri Pitkanen" <petri.t.pitka...@gmail.com>
>> wrote:
>>
>>> They are free to use in any attribution. Game score is a reflection of
>>> historical fact and hence not copyrightable. Dunno what use them are to
>>> anyone though.
>>>
>>> Petri
>>>
>>> 2017-10-23 2:29 GMT+03:00 Lucas Baker <suuj...@gmail.com>:
>>>
>>>> Hi Robert,
>>>>
>>>> The AlphaGo Zero games are free to use with proper attribution, so
>>>> please use them as you like for commentaries as long as you credit 
>>>> DeepMind.
>>>>
>>>> Best,
>>>> Lucas Baker
>>>>
>>>> On Sun, Oct 22, 2017 at 3:59 PM Robert Jasiek <jas...@snafu.de> wrote:
>>>>
>>>>> AlphaGo Zero games are available as zipped SGF from Deepmind at
>>>>> http://www.alphago-games.com/ For earlier AlphaGo games, I have seen
>>>>> statements from Deepmind encouraging free use (presuming stating
>>>>> origin,
>>>>> of course) so that the games may be commented etc. I cannot find a
>>>>> similar statement from Deepmind for the published AlphaGo Zero games.
>>>>> Are they for free use or copyrighted? I hope the former so everybody
>>>>> including Deepmind can see more commentaries.
>>>>>
>>>>> --
>>>>> robert jasiek
>>>>> _______________________________________________
>>>>> Computer-go mailing list
>>>>> Computer-go@computer-go.org
>>>>> http://computer-go.org/mailman/listinfo/computer-go
>>>>
>>>>
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