Solution to 1D has been deliberately left unsolved and is to be answered only by a non-regular / novice commenter, with proper annotation. Those who have answered earlier in the week, please give others a chance.
ACROSS
9 Proves set’s variance exceeds limit (9) OVERSTEPS*
10 Former top scorer finishes with ten runs (5) PRIOR {toP}{s...eR}{10}{R}
12 Blue sea waves at your disposal (7) USEABLE*
13 Beat revolutionary up, lest she expose leaders! (5) PULSE {UP<=}{Lest}{She}{Ex...e}
14 Like softmax and relu functions connected in layers of neuron-like artificial receptors (3-6) NON-LINEAR {ONLINE} in {Ne...e}{Ar...l}{Re...s}
16 China, in general, is getting transformed after taking the lead in modern AI (7,8) MACHINE LEARNING {CHINA+IN+GENRAL+Mo...n}*
19 Lost again, kindling a sad feeling (9) NOSTALGIA*
22 Vibrator smuggled by retreating hurricane evacuee? (5) VEENA [T<=]
26 Surgical instrument cut tree, with some modifications (7) CURETTE*
28 Measurements obtained by transforming a tensor over networked stimuli, ultimately (9) ORDINATES {A+TENSOR}* over {n...eD}{s...lI}
DOWN
1 Every now and then, upset priests lodge report (6) ?O?S?P (Addendum - GOSSIP {PrIeStS+lOdGe}<= - See comments)
2 Souvenir embodying local form of government (8) REPUBLIC {RE{PUB}LIC}
4 Humble Gussalufz is passed over by head of department (6) DEMEAN {DE{ME}AN}
5 India mishandled a census release (8) ISSUANCE {I}{A+CENSUS}*
6 Peacekeeper holding raised sword (4) EPEE [T<=]
7 A few bits from new version of bible (6) NIBBLE {N}{BIBLE*}
8 Carelessly forget about protected forest-dweller (4,4) TREE FROG {FORGET}* over {RE}
16 Moreover, following the start of monsoon, rain destroyed fruit (8) MANDARIN {AND}<=>{Mo...n} with {RAIN}*
18 Name of agitated deity devouring books by Gussalufz? (8) IDENTITY {IDE{NT}{I}TY*}
21 With regular losses as a coach, he made me give in (6) ACCEDE {As+c+CoaCh+hE+maDe+mE}
23 In India, tea-sellers say this to make men relaxed (2,4) AT EASE [T]
25 Went back a long way (4) DEEP <=
Reference List
Runs = R, Husband = H, About = C, India = I, New = N, About = RE, On = RE, Books = NT(New Testament), Energy = E
1D GOSSIP is report ; reverse telescopic starting from G in lodge and alternate every two characters. I.e. G..O..S..S..I..P
ReplyDeleteRead as every Second character
DeleteYes, well spotted!
DeleteThere's a nina to be found, and a theme. The nina is a bit esoteric though (but thematic :-))
ReplyDeleteI think I got it. But not sure. Will wait
DeleteThere are two ninas: Gradient and Descent(?) and a few theme words linked to the Ninas. I think they are Non-Linear, Ordinates, Identity(?)
ReplyDeleteWhat is NINA- my ignorance?
DeleteNina is a hidden message in the grid. See Viresh's comment below.
Deletewow!!! Gr8 Vasanth. Promptly spotted
DeleteNot really Prassana. You can see Viresh's comments below. I have very little know how on AI.
DeletePulse,set out?
ReplyDeleteDelectable as ever. Thank you.
ReplyDeleteLovely grid. My favs are 10a PRIOR, 2d REPUBLIC and 25d IRREVERENT. Thank you Gussalufz. 🙂
ReplyDeleteThanks, folks! I tried to dial down the difficulty level of the clues in this crossword. But the nina and theme are, as I said earlier, esoteric :-). Here are my notes for this puzzle:
ReplyDelete----------------------------------------------------------
There is a nina running across the top row and the fifth-from-the-bottom row: GRADIENT DESCENT. Gradient descent is a key algorithm used in artificial intelligence (which is the theme in this crossword). Gradient descent is used for training computational neural networks to recognize patterns found in large data sets.
The following clues and solution entries are thematic:
- 10a. PRIOR is also a technical term, referring to the starting point of knowledge encoded in a system, before it is made to learn from training data.
- 11a. SHUFFLE is what you have to do to training data, to make sure that the network learns patterns inherent in the data rather than any patterns in the ordering of the data.
- 14a. NON-LINEAR functions are often used as computational "neurons" that make deep-learning networks powerful by being able to handle complex patterns in data.
- 14a. The surface itself describes a deep learning neural network.
- 15a. MACHINE LEARNING is the broad name for the key area of artificial intelligence that concerns training computer systems using data.
- 16a. The surface refers to AI.
- 25d. DEEP is the adjective that's part of "deep learning," that has revolutionized AI using deep stacks of computational neurons.
- 28a. The surface refers to the workings of a neural network.
In addition, 7d. (NIBBLE), 12a. (USEABLE), 13a. (PULSE), 18d. (IDENTITY), and 28a. (ORDINATES) also have technical interpretations that can be construed (at a stretch) to fit the theme.
Amazing!
DeleteExcellent Analytics Viresh. Glad to know more on AI. Thanks Vasanth.
Delete+1
+1. Thank you Ratnakar. We keep learning from your CW's.
ReplyDelete+2 I am like the fools who came to scoff remained to pray (Deserted Village)
Delete+3
Delete+2
DeleteGood quote from Goldsmith.
ReplyDeleteThanks!
ReplyDeleteGussalufz Nicely indicated the delicious south indian dish "Adai" in 3D....in fact the the answer also apt for that. Thanks for the wonderful Grid and esp. for 1D....GOSSIP.
ReplyDeleteSome very nice clues Viresh. Particularly liked 16A
ReplyDeleteEventhough i know nothing about AI - loved the grid. My fav - REPUBLIC, SHUFFLE, ACTED UP, IRREVERANT.
ReplyDelete👍
& yes. The difficulty level has been toned down. Thanx.
ReplyDelete