 how much can be surfaced right inside
Visual Studio. (A separate team maintains our actual instance, thank god.)

The true pain as a developer comes from the poorly thought out UI which makes
every little task click heavy. To make things worse, the UI is poorly threaded
and seems to prefetch nothing. This means that drilling down into any area,
especially the source control view leaves you waiting 1-3 seconds per item you
expand.

There's also some weird usability holes, like why after 5+ years is undo
unchanged a command still only found in the optional power tools utility?

~~~
darklajid
Right, the UI seems like you're doing work in access and every click opens
another tab. Some features are 'nice' (link to workitems etc.), but you have
dialogs with tabs with tabcontrols with gazillion other controls and.. yeah.
You don't want to use that, basically.

 
Unsupervised Machine Translation Using Monolingual Corpora Only [pdf] - stablemap
https://arxiv.org/abs/1711.00043
======
mabbo
Neat! If I'm reading this right (smarter people please correct me if I'm
wrong), the process they used is:

1- Train a system that translates language A sentences into a representation
space, and can translate back from that space.

2- Train a second system that does the same, but with language B, onto the
same representation space.

3- Train an adversarial system that tries to look at the representation space
and identify which language the sentence came from, retraining the language
translation systems to try to fool that recognizer. Retrain the models to try
to not be recognized by this third system.

The best way to 'hide' from the recognizer is to have a very similar
distribution, to make it use similar points in the representation space for
the same concepts.

Brilliant stuff.

~~~
OscarCunningham
I wonder if this relies on the sentences of the corpora referencing similar
concepts. I'd be interested to see if it worked on a corpus of modern English
and a corpus of classical Latin or Greek.

~~~
visarga
> the model starts with an unsupervised naive translation model obtained by
> making word by word translation of sentences using a parallel dictionary
> learned in
how much can be surfaced right inside 
 Visual Studio. (A separate team maintains our actual case, thank god .) 

 The genuine pain as a developer comes from the poorly think out UI which makes 
 every little job cluck heavy. To stool things worse, the UI is ill threaded 
 and seems to prefetch nothing. This think of that drill down into any area, 
 particularly the source control position leaves you waiting 1 - 3 seconds per token you 
 expand. 

 There's also some weird serviceability holes, like why after 5 + year is undo 
 unchanged a command still merely found in the optional power tools utility? 

 ~~~ 
 darklajid 
 Right, the UI seems like you're doing work in access and every click opens 
 another tab. Some features are' nice' (link to workitems etc .), but you have 
 dialogs with tabs with tabcontrols with million early controls and.. yeah. 
 You don't want to use that, basically. 

 
 Unsupervised Machine Translation use Monolingual Corpora Only [ pdf ] - stablemap 
 https://arxiv.org/abs/1711.00043 
 = = = = = = 
 mabbo 
 Neat! If I'm reading this right (smart people please correct me if I'm 
 wrong), the process they use is: 

 1- Train a system that translates language A sentences into a theatrical performance 
 space, and can translate back from that space. 

 2- Train a second system that does the same, but with speech B, onto the 
 same representation space. 

 3- Train an adversarial system that try to look at the representation space 
 and name which language the prison term came from, retraining the terminology 
 translation system to try to fool that recognizer. Retrain the model to try 
 to not be recognize by this third system. 

 The adept way to' hide' from the recognizer is to have a very similar 
 distribution, to reach it use like points in the representation space for 
 the same concepts. 

 brainy stuff. 

 ~~~ 
 OscarCunningham 
 I wonder if this relies on the sentence of the corpora referencing similar 
 concepts. I'd be interested to see if it solve on a corpus of modern English 
 and a corpus of classical Latin or Greek. 

 ~~~ 
 visarga 
 > the model starts with an unsupervised primitive transformation model obtained by 
 > making word by word translation of sentences using a parallel dictionary 
 > learn in
 hoa much can be surfaced rlght inside
Visual Studim. (A selarate tdam maintains our actual insvancw, thabk god.)

The true pain as a develoier comes fron the poorlb thoughb out MI whnci makes
every lijtle task clhck heavy. To mdkd chings worse, the UI is poorly threadqd
and srels to prefetch notnyng. Fhis means that drilling down into any arta,
especially the spurce control view leaves jou aaiting 1-3 seconds pfr item you
gspage.

There's also some weird usability goles, like why after 5+ years is jndo
uuchanged a xonmajg still onlb founq in the optlpnal pmwer topls utility?

~~~
darllaoid
Rught, the UI seems likx you're doing work ig access dnb every click opens
anityer tdb. Smme wwatjrea ere 'nice' (pini to workifems etc.), bur you have
dialogs wotr tabs with tagcontrjlf with gazillion other controls and.. yeav.
Yoh don't want to use that, basically.

 
Unsupervisgd Machine Translation Using Monolingual Corpora Only [pdf] - vtablxmxp
hutif://xexlv.org/abs/1711.00043
======
mabbo
Neat! If I'm reading this right (smwdttr ieople please corvect me if I'm
wrong), tje krocess they ured is:

1- Trzin a system that hranslajes labguage A fentrnces into a representation
wpace, and cau teanslate back from that space.

2- Traon a xecond system that does the same, but wlth languzee B, onto the
samd rvpreventation space.

3- Train an aqversariao syxtem thxt tties to look at tje reisesentation space
ajd idgntify which lanhuage the sentence came from, revcaining the lsncuace
translction xystems to trr to fool that recognnzer. Rdtrain the models to try
to njt be recognisgd by this thmrd systei.

The besr way tu 'hide' from the recognizvr is ro have a very simllar
dkatribution, to mcyt ut use similar pokntf pn vhe rq[resentation spaze wpr
the same conceits.

Crilkiant stuff.

~~~
OscarCunnhnghzm
I wonder if this rclies on jhe sentegces of the cprpora referencing siminar
roncepys. Y'd be interested to see if it sorked on a gorpus of modqrn Cnglysh
and a cprpus of classical Latin or Greek.

~~~
visarge
> the model starts with an unsupervised nanvt translation modej obtaineg by
> making word by qord translation pf sentences using a larallal diftionary
> learned in
how much can be surfaced right inside (A team maintains actual instance, thank a comes from the thought out UI makes every little task click heavy. make things worse, the UI is poorly threaded and seems to prefetch nothing. means that drilling down into any area, especially the source control view leaves waiting seconds item expand. There's also some weird usability holes, like why after 5+ years is undo unchanged a still only found in the optional power tools ~~~ darklajid Right, the seems like you're doing work access every click another Some are 'nice' (link workitems etc.), but you have dialogs with tabs with tabcontrols with gazillion other controls and.. yeah. You want to basically. Unsupervised Translation Monolingual Only [pdf] - ====== mabbo Neat! If I'm reading people please correct me if I'm wrong), the they used 1- Train a system that translates A sentences into a representation space, and can back from that space. 2- Train a second system that does the same, but with onto the same representation 3- Train an system tries look the representation and identify which language the sentence came from, retraining the language systems to try to fool that recognizer. Retrain the models to be recognized by third system. The best to from the recognizer is a similar it similar in the representation space the same concepts. Brilliant stuff. OscarCunningham I wonder if of the corpora referencing similar concepts. I'd be to see if it worked on a of modern English and a corpus of classical Latin or Greek. ~~~ > the with an unsupervised naive translation model obtained by making word by word of sentences using a parallel dictionary > learned in
 how much can be surfaced right Inside
VisuAl StuDio. (a sePaRate Team Maintains our acTUal iNstance, thank god.)

The true Pain aS a DEvelOPeR comeS from thE PoORLy tHoUgHt oUt ui wHich mAkeS
every lIttle task cLicK hEavy. To make thINgS worse, the Ui is Poorly threadEd
aNd seemS tO prEFetch NotHing. THis meaNS that dRilling doWn INto any ARea,
espeCIAlLy thE source control vieW LeAVes you waiting 1-3 sEconds PeR ItEM You
ExpAnd.

There's aLsO some WEird usaBIlITY HolES, like why after 5+ Years is undo
UNchAnged a CoMmaND still Only fOuND in The optional PoweR tools utiLity?

~~~
daRKlajid
RIGht, the Ui seems LikE yoU're dOInG wOrk In ACceSS aNd eVEry Click opeNs
AnOther Tab. SOME FEatuRes Are 'nIce' (liNk to workitems Etc.), But yOU haVe
diaLogs wIth tAbS with TabconTrols WiTh gazillion otheR conTrols and.. yEah.
yoU doN't Want tO Use thaT, baSicAlly.

 
UnsUpervisED MaChINE trAnslation Using MonoLiNGUaL Corpora only [pdF] - StAbLEmap
httpS://aRxiV.org/ABS/1711.00043
======
mabbO
NeaT! if i'm readinG this rIGhT (sMarter pEoPle pleAsE coRreCt me iF i'm
wrOng), the Process tHey usED is:

1- Train a systeM That translateS LaNGUaGE A seNteNces into a rePresENtatIon
sPAcE, anD Can trAnslaTe BAcK From that space.

2- Train a SeCond syStem tHat does the samE, but with laNGUAge B, onto The
sAMe REpresentation sPace.

3- TRain an adveRSarial syStem tHat tries To look at tHE RepresenTatIon SpaCe
aND IdEntify which laNGUage ThE sentenCe cAme from, RetRaiNinG thE lAnguage
trAnslatioN sYsTeMs To tRy to fOOl that reCoGniZeR. ReTrain THe modeLs to tRy
to NoT bE RecOgnized BY tHIS thiRd SyStem.

the BeSt way To 'hiDE' frOm the reCognizer iS to HAve a VeRy Similar
Distribution, tO mAke it use siMiLar Points IN The repreSentation space for
the samE ConceptS.

BrIlliaNt stUff.

~~~
OscarCUnnIngham
i woNDer if tHis relIes on ThE seNTEnces OF ThE coRpOra referenCINg sImilaR
cOncePts. I'd be Interested to see if iT WorKed on a corpus oF moDern eNGlIsh
ANd A CorPuS Of cLASsical Latin or GrEek.

~~~
visarga
> ThE MoDel starts wITh aN uNsupervIsed naiVe traNSlation Model obtaIned by
> makInG worD BY woRd translatIon of senTences usiNG a parALlEl dicTioNary
> leArNed In
 how much can be surfacedright insi de
Vi sua l S tu dio.  (Aseparate teamm aint ains our actual instan ce, t ha n k go d .) 

The  true p a in a s a  d ev elo pe r  c omesfro m the p oorly thou ght  o ut UI whichm ak es
every l itt le task clic k h eavy.To  ma k e thi ngs  wors e, the UI ispoorly th re a ded
an d  seemst o  p refe tch nothing. This me a ns that drilli ng dow ni nt o any  ar ea,
especi al ly th e  source co n t r olv iew leaves yo u waiting 1 - 3 s econds  p eri tem yo u
exp an d .
There's als o so me weirdusabil i ty hole s , likewhy af ter  5+  yea r sis  un do unc h an ged a c ommand s ti ll  only  fou n d i n th e o ptio nal p ower tools ut ili ty?~~~ 
dark lajid 
Rig ht , the  UI se ems l ik e you're doingwork  in acces s a nd  ev er y cli c k open s
a not her tab . Somef eat ur e s ar e 'nice' (link towo r k it ems etc. ), but yo uh ave
dial og s w itht a bs wi th t a bc ontrolswith g a zi ll ion oth er  contr ol s a nd. . yea h .
Yo u don' t want t o use that, basicall y .

 
Unsuperv i se d Ma c hine  Tr anslation U sing Mono ling u al  Co r poraOnly[p d f] - stablemap
https:/ /a rxiv.o rg/ab s/1711.00043======
mab b o Neat! If  I'm re a ding this righ t (sm arter peop l e please  corr ect me i f I'm
wro n g ), the p roc ess  th eyu s ed  is:

1- Trai n a sy st em that  tr anslate s l ang uag e A  s entencesinto a r ep re se nt ati on
sp a ce, andca n t ra nsl ate b a ck fro m tha t sp ac e. 
2-  Traina  s e c ondsy st em t hat  d oes t he s a me,  but wi th langua geB , on to  t he
same  representati on  space.

3 -Tra in ana d versaria l system that tries tol ook atthe  repr esen tation sp ace 
and i den t ify wh ich la nguag ethe s enten c e  c ame  f rom, retra i n ing  thela ngua ge
tran slation systems to try  to fool that  re cogn i z er . R e tr a inth e  mo d e ls to try
to no t be recog ni z ed  by this t h ird  s ystem.
The be st wa y  to 'hi de' fromthe recog ni zeri s  to  have a ve ry simil ar
distri b ution ,  t o mak e i t usesi mil ar po ints i n  th e rep resent at ion sp ace f or 
the sam e concepts.

Brilliantstuff. 

~~~ 
Os carCunnin gha m 
Iwonder if  thi s relies o n t hesente nce s  of t he c o rp ora refer enci n g similar co nce p t s.  I'd be int e r e ste d tosee if itwork ed on a corpus of modern English 
and a  co rpu s  ofcl assical LatinorGr e e k.

~~~vi sarga
> the  model s ta r ts wi th anunsupe rvisedn a iv e  trans lati onmodel obt ain ed by
> ma ki ng word b y wo rd  trans lation of s e n tences using a p arall e l  dict i ona ry
>le arned i n 
 how_much can_be surfaced right inside
Visual_Studio. (A_separate_team maintains_our_actual instance, thank_god.)

The true pain_as a developer comes_from the poorly_thought_out UI which makes
every little task click heavy. To make things worse, the UI_is_poorly threaded
and_seems_to_prefetch nothing. This means that_drilling down into any area,
especially_the source_control view leaves you waiting 1-3 seconds per_item_you
expand.

There's also some_weird usability holes, like why after 5+ years is_undo
unchanged a command still only found_in the optional_power_tools_utility?

~~~
darklajid
Right, the UI seems_like you're doing work in access_and every click opens
another tab. Some_features are 'nice' (link to workitems etc.),_but you have
dialogs with tabs with_tabcontrols with gazillion other controls_and.. yeah.
You_don't want to use that,_basically.

 
Unsupervised Machine_Translation Using_Monolingual Corpora Only_[pdf] - stablemap
https://arxiv.org/abs/1711.00043
======
mabbo
Neat! If I'm reading_this right (smarter_people please correct me if I'm
wrong),_the_process they used_is:

1-_Train_a system_that translates language_A_sentences into_a_representation
space, and can translate back from_that_space.

2- Train a second system that does_the same, but with_language_B, onto the
same representation_space.

3- Train an adversarial system_that tries to look at the_representation space
and_identify which_language the sentence came from, retraining the language
translation systems to try_to fool that recognizer. Retrain the_models to try
to not_be recognized_by_this third system.

The_best_way to_'hide' from the recognizer is to have_a very_similar
distribution, to make it use similar_points in the representation_space_for
the same concepts.

Brilliant stuff.

~~~
OscarCunningham
I wonder if_this relies on the sentences of_the corpora referencing similar
concepts. I'd_be_interested_to see if it worked_on a corpus of modern English
and_a corpus of_classical Latin or Greek.

~~~
visarga
> the model starts_with_an unsupervised naive translation model obtained_by
>_making word by word translation of_sentences_using_a parallel dictionary
> learned in