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Through the Looking-Glass by Lewis Carroll, is part of the HackerNoon Books Series. You can jump to any chapter in this book . The Garden of Live Flowers here CHAPTER II. The Garden of Live Flowers “I should see the garden far better,” said Alice to herself, “if I could get to the top of that hill: and here’s a path that leads straight to it—at least, no, it doesn’t do that—” (after going a few yards along the path, and turning several sharp corners), “but I suppose it will at last. But how curiously it twists! It’s more like a corkscrew than a path! Well, turn goes to the hill, I suppose—no, it doesn’t! This goes straight back to the house! Well then, I’ll try it the other way.” this And so she did: wandering up and down, and trying turn after turn, but always coming back to the house, do what she would. Indeed, once, when she turned a corner rather more quickly than usual, she ran against it before she could stop herself. “It’s no use talking about it,” Alice said, looking up at the house and pretending it was arguing with her. “I’m going in again yet. I know I should have to get through the Looking-glass again—back into the old room—and there’d be an end of all my adventures!” not So, resolutely turning her back upon the house, she set out once more down the path, determined to keep straight on till she got to the hill. For a few minutes all went on well, and she was just saying, “I really do it this time—” when the path gave a sudden twist and shook itself (as she described it afterwards), and the next moment she found herself actually walking in at the door. shall “Oh, it’s too bad!” she cried. “I never saw such a house for getting in the way! Never!” However, there was the hill full in sight, so there was nothing to be done but start again. This time she came upon a large flower-bed, with a border of daisies, and a willow-tree growing in the middle. “O Tiger-lily,” said Alice, addressing herself to one that was waving gracefully about in the wind, “I you could talk!” wish “We talk,” said the Tiger-lily: “when there’s anybody worth talking to.” can Alice was so astonished that she could not speak for a minute: it quite seemed to take her breath away. At length, as the Tiger-lily only went on waving about, she spoke again, in a timid voice—almost in a whisper. “And can the flowers talk?” all “As well as can,” said the Tiger-lily. “And a great deal louder.” you “It isn’t manners for us to begin, you know,” said the Rose, “and I really was wondering when you’d speak! Said I to myself, ‘Her face has got sense in it, though it’s not a clever one!’ Still, you’re the right colour, and that goes a long way.” some “I don’t care about the colour,” the Tiger-lily remarked. “If only her petals curled up a little more, she’d be all right.” Alice didn’t like being criticised, so she began asking questions. “Aren’t you sometimes frightened at being planted out here, with nobody to take care of you?” “There’s the tree in the middle,” said the Rose: “what else is it good for?” “But what could it do, if any danger came?” Alice asked. “It says ‘Bough-wough!’” cried a Daisy: “that’s why its branches are called boughs!” “Didn’t you know ?” cried another Daisy, and here they all began shouting together, till the air seemed quite full of little shrill voices. “Silence, every one of you!” cried the Tiger-lily, waving itself passionately from side to side, and trembling with excitement. “They know I can’t get at them!” it panted, bending its quivering head towards Alice, “or they wouldn’t dare to do it!” that “Never mind!” Alice said in a soothing tone, and stooping down to the daisies, who were just beginning again, she whispered, “If you don’t hold your tongues, I’ll pick you!” There was silence in a moment, and several of the pink daisies turned white. “That’s right!” said the Tiger-lily. “The daisies are worst of all. When one speaks, they all begin together, and it’s enough to make one wither to hear the way they go on!” “How is it you can all talk so nicely?” Alice said, hoping to get it into a better temper by a compliment. “I’ve been in many gardens before, but none of the flowers could talk.” “Put your hand down, and feel the ground,” said the Tiger-lily. “Then you’ll know why.” Alice did so. “It’s very hard,” she said, “but I don’t see what that has to do with it.” “In most gardens,” the Tiger-lily said, “they make the beds too soft—so that the flowers are always asleep.” This sounded a very good reason, and Alice was quite pleased to know it. “I never thought of that before!” she said. “It’s opinion that you never think ,” the Rose said in a rather severe tone. my at all “I never saw anybody that looked stupider,” a Violet said, so suddenly, that Alice quite jumped; for it hadn’t spoken before. “Hold tongue!” cried the Tiger-lily. “As if ever saw anybody! You keep your head under the leaves, and snore away there, till you know no more what’s going on in the world, than if you were a bud!” your you “Are there any more people in the garden besides me?” Alice said, not choosing to notice the Rose’s last remark. “There’s one other flower in the garden that can move about like you,” said the Rose. “I wonder how you do it—” (“You’re always wondering,” said the Tiger-lily), “but she’s more bushy than you are.” “Is she like me?” Alice asked eagerly, for the thought crossed her mind, “There’s another little girl in the garden, somewhere!” “Well, she has the same awkward shape as you,” the Rose said, “but she’s redder—and her petals are shorter, I think.” “Her petals are done up close, almost like a dahlia,” the Tiger-lily interrupted: “not tumbled about anyhow, like yours.” “But that’s not fault,” the Rose added kindly: “you’re beginning to fade, you know—and then one can’t help one’s petals getting a little untidy.” your Alice didn’t like this idea at all: so, to change the subject, she asked “Does she ever come out here?” “I daresay you’ll see her soon,” said the Rose. “She’s one of the thorny kind.” “Where does she wear the thorns?” Alice asked with some curiosity. “Why all round her head, of course,” the Rose replied. “I was wondering hadn’t got some too. I thought it was the regular rule.” you “She’s coming!” cried the Larkspur. “I hear her footstep, thump, thump, thump, along the gravel-walk!” Alice looked round eagerly, and found that it was the Red Queen. “She’s grown a good deal!” was her first remark. She had indeed: when Alice first found her in the ashes, she had been only three inches high—and here she was, half a head taller than Alice herself! “It’s the fresh air that does it,” said the Rose: “wonderfully fine air it is, out here.” “I think I’ll go and meet her,” said Alice, for, though the flowers were interesting enough, she felt that it would be far grander to have a talk with a real Queen. “You can’t possibly do that,” said the Rose: “ should advise you to walk the other way.” I This sounded nonsense to Alice, so she said nothing, but set off at once towards the Red Queen. To her surprise, she lost sight of her in a moment, and found herself walking in at the front-door again. A little provoked, she drew back, and after looking everywhere for the queen (whom she spied out at last, a long way off), she thought she would try the plan, this time, of walking in the opposite direction. It succeeded beautifully. She had not been walking a minute before she found herself face to face with the Red Queen, and full in sight of the hill she had been so long aiming at. “Where do you come from?” said the Red Queen. “And where are you going? Look up, speak nicely, and don’t twiddle your fingers all the time.” Alice attended to all these directions, and explained, as well as she could, that she had lost her way. “I don’t know what you mean by way,” said the Queen: “all the ways about here belong to —but why did you come out here at all?” she added in a kinder tone. “Curtsey while you’re thinking what to say, it saves time.” your me Alice wondered a little at this, but she was too much in awe of the Queen to disbelieve it. “I’ll try it when I go home,” she thought to herself, “the next time I’m a little late for dinner.” “It’s time for you to answer now,” the Queen said, looking at her watch: “open your mouth a wider when you speak, and always say ‘your Majesty.’” little “I only wanted to see what the garden was like, your Majesty—” “That’s right,” said the Queen, patting her on the head, which Alice didn’t like at all, “though, when you say ‘garden,’— seen gardens, compared with which this would be a wilderness.” I’ve Alice didn’t dare to argue the point, but went on: “—and I thought I’d try and find my way to the top of that hill—” “When you say ‘hill,’” the Queen interrupted, “ could show you hills, in comparison with which you’d call that a valley.” I “No, I shouldn’t,” said Alice, surprised into contradicting her at last: “a hill be a valley, you know. That would be nonsense—” can’t The Red Queen shook her head, “You may call it ‘nonsense’ if you like,” she said, “but heard nonsense, compared with which that would be as sensible as a dictionary!” I’ve Alice curtseyed again, as she was afraid from the Queen’s tone that she was a offended: and they walked on in silence till they got to the top of the little hill. little For some minutes Alice stood without speaking, looking out in all directions over the country—and a most curious country it was. There were a number of tiny little brooks running straight across it from side to side, and the ground between was divided up into squares by a number of little green hedges, that reached from brook to brook. “I declare it’s marked out just like a large chessboard!” Alice said at last. “There ought to be some men moving about somewhere—and so there are!” She added in a tone of delight, and her heart began to beat quick with excitement as she went on. “It’s a great huge game of chess that’s being played—all over the world—if this the world at all, you know. Oh, what fun it is! How I I was one of them! I wouldn’t mind being a Pawn, if only I might join—though of course I should to be a Queen, best.” is wish like She glanced rather shyly at the real Queen as she said this, but her companion only smiled pleasantly, and said, “That’s easily managed. You can be the White Queen’s Pawn, if you like, as Lily’s too young to play; and you’re in the Second Square to begin with: when you get to the Eighth Square you’ll be a Queen—” Just at this moment, somehow or other, they began to run. Alice never could quite make out, in thinking it over afterwards, how it was that they began: all she remembers is, that they were running hand in hand, and the Queen went so fast that it was all she could do to keep up with her: and still the Queen kept crying “Faster! Faster!” but Alice felt she go faster, though she had not breath left to say so. could not The most curious part of the thing was, that the trees and the other things round them never changed their places at all: however fast they went, they never seemed to pass anything. “I wonder if all the things move along with us?” thought poor puzzled Alice. And the Queen seemed to guess her thoughts, for she cried, “Faster! Don’t try to talk!” Not that Alice had any idea of doing . She felt as if she would never be able to talk again, she was getting so much out of breath: and still the Queen cried “Faster! Faster!” and dragged her along. “Are we nearly there?” Alice managed to pant out at last. that “Nearly there!” the Queen repeated. “Why, we passed it ten minutes ago! Faster!” And they ran on for a time in silence, with the wind whistling in Alice’s ears, and almost blowing her hair off her head, she fancied. “Now! Now!” cried the Queen. “Faster! Faster!” And they went so fast that at last they seemed to skim through the air, hardly touching the ground with their feet, till suddenly, just as Alice was getting quite exhausted, they stopped, and she found herself sitting on the ground, breathless and giddy. The Queen propped her up against a tree, and said kindly, “You may rest a little now.” Alice looked round her in great surprise. “Why, I do believe we’ve been under this tree the whole time! Everything’s just as it was!” “Of course it is,” said the Queen, “what would you have it?” “Well, in country,” said Alice, still panting a little, “you’d generally get to somewhere else—if you ran very fast for a long time, as we’ve been doing.” our “A slow sort of country!” said the Queen. “Now, , you see, it takes all the running can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!” here you “I’d rather not try, please!” said Alice. “I’m quite content to stay here—only I so hot and thirsty!” am “I know what like!” the Queen said good-naturedly, taking a little box out of her pocket. “Have a biscuit?” you’d Alice thought it would not be civil to say “No,” though it wasn’t at all what she wanted. So she took it, and ate it as well as she could: and it was dry; and she thought she had never been so nearly choked in all her life. very “While you’re refreshing yourself,” said the Queen, “I’ll just take the measurements.” And she took a ribbon out of her pocket, marked in inches, and began measuring the ground, and sticking little pegs in here and there. “At the end of two yards,” she said, putting in a peg to mark the distance, “I shall give you your directions—have another biscuit?” “No, thank you,” said Alice: “one’s enough!” quite “Thirst quenched, I hope?” said the Queen. Alice did not know what to say to this, but luckily the Queen did not wait for an answer, but went on. “At the end of yards I shall repeat them—for fear of your forgetting them. At the end of , I shall say good-bye. And at the end of , I shall go!” three four five She had got all the pegs put in by this time, and Alice looked on with great interest as she returned to the tree, and then began slowly walking down the row. At the two-yard peg she faced round, and said, “A pawn goes two squares in its first move, you know. So you’ll go quickly through the Third Square—by railway, I should think—and you’ll find yourself in the Fourth Square in no time. Well, square belongs to Tweedledum and Tweedledee—the Fifth is mostly water—the Sixth belongs to Humpty Dumpty—But you make no remark?” very that “I—I didn’t know I had to make one—just then,” Alice faltered out. “You have said, ‘It’s extremely kind of you to tell me all this’—however, we’ll suppose it said—the Seventh Square is all forest—however, one of the Knights will show you the way—and in the Eighth Square we shall be Queens together, and it’s all feasting and fun!” Alice got up and curtseyed, and sat down again. should At the next peg the Queen turned again, and this time she said, “Speak in French when you can’t think of the English for a thing—turn out your toes as you walk—and remember who you are!” She did not wait for Alice to curtsey this time, but walked on quickly to the next peg, where she turned for a moment to say “good-bye,” and then hurried on to the last. How it happened, Alice never knew, but exactly as she came to the last peg, she was gone. Whether she vanished into the air, or whether she ran quickly into the wood (“and she run very fast!” thought Alice), there was no way of guessing, but she was gone, and Alice began to remember that she was a Pawn, and that it would soon be time for her to move. can About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Lewis Carroll (2008). Through the Looking-Glass. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/files/18857/18857-h/18857-h.htm This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

The Garden of Live Flowers

The Golden Road by L. M. Montgomery, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . FLOWERS O’ MAY CHAPTER XII. FLOWERS O’ MAY Accordingly we went a-maying, following the lure of dancing winds to a certain westward sloping hill lying under the spirit-like blue of spring skies, feathered over with lisping young pines and firs, which cupped little hollows and corners where the sunshine got in and never got out again, but stayed there and grew mellow, coaxing dear things to bloom long before they would dream of waking up elsewhere. ‘Twas there we found our mayflowers, after faithful seeking. Mayflowers, you must know, never flaunt themselves; they must be sought as becomes them, and then they will yield up their treasures to the seeker—clusters of star-white and dawn-pink that have in them the very soul of all the springs that ever were, re-incarnated in something it seems gross to call perfume, so exquisite and spiritual is it. We wandered gaily over the hill, calling to each other with laughter and jest, getting parted and delightfully lost in that little pathless wilderness, and finding each other unexpectedly in nooks and dips and sunny silences, where the wind purred and gentled and went softly. When the sun began to hang low, sending great fan-like streamers of radiance up to the zenith, we foregathered in a tiny, sequestered valley, full of young green fern, lying in the shadow of a wooded hill. In it was a shallow pool—a glimmering green sheet of water on whose banks nymphs might dance as blithely as ever they did on Argive hill or in Cretan dale. There we sat and stripped the faded leaves and stems from our spoil, making up the blossoms into bouquets to fill our baskets with sweetness. The Story Girl twisted a spray of divinest pink in her brown curls, and told us an old legend of a beautiful Indian maiden who died of a broken heart when the first snows of winter were falling, because she believed her long-absent lover was false. But he came back in the spring time from his long captivity; and when he heard that she was dead he sought her grave to mourn her, and lo, under the dead leaves of the old year he found sweet sprays of a blossom never seen before, and knew that it was a message of love and remembrance from his dark-eyed sweet-heart. “Except in stories Indian girls are called squaws,” remarked practical Dan, tying his mayflowers together in one huge, solid, cabbage-like bunch. Not for Dan the bother of filling his basket with the loose sprays, mingled with feathery elephant’s-ears and trails of creeping spruce, as the rest of us, following the Story Girl’s example, did. Nor would he admit that ours looked any better than his. “I like things of one kind together. I don’t like them mixed,” he said. “You have no taste,” said Felicity. “Except in my mouth, best beloved,” responded Dan. “You do think you are so smart,” retorted Felicity, flushing with anger. “Don’t quarrel this lovely day,” implored Cecily. “Nobody’s quarrelling, Sis. I ain’t a bit mad. It’s Felicity. What on earth is that at the bottom of your basket, Cecily?” “It’s a History of the Reformation in France,” confessed poor Cecily, “by a man named D-a-u-b-i-g-n-y. I can’t pronounce it. I heard Mr. Marwood saying it was a book everyone ought to read, so I began it last Sunday. I brought it along today to read when I got tired picking flowers. I’d ever so much rather have brought Ester Reid. There’s so much in the history I can’t understand, and it is so dreadful to read of people being burned to death. But I felt I OUGHT to read it.” “Do you really think your mind has improved any?” asked Sara Ray seriously, wreathing the handle of her basket with creeping spruce. “No, I’m afraid it hasn’t one bit,” answered Cecily sadly. “I feel that I haven’t succeeded very well in keeping my resolutions.” “I’ve kept mine,” said Felicity complacently. “It’s easy to keep just one,” retorted Cecily, rather resentfully. “It’s not so easy to think beautiful thoughts,” answered Felicity. “It’s the easiest thing in the world,” said the Story Girl, tiptoeing to the edge of the pool to peep at her own arch reflection, as some nymph left over from the golden age might do. “Beautiful thoughts just crowd into your mind at times.” “Oh, yes, AT TIMES. But that’s different from thinking one REGULARLY at a given hour. And mother is always calling up the stairs for me to hurry up and get dressed, and it’s VERY hard sometimes.” “That’s so,” conceded the Story Girl. “There ARE times when I can’t think anything but gray thoughts. Then, other days, I think pink and blue and gold and purple and rainbow thoughts all the time.” “The idea! As if thoughts were coloured,” giggled Felicity. “Oh, they are!” cried the Story Girl. “Why, I can always SEE the colour of any thought I think. Can’t you?” “I never heard of such a thing,” declared Felicity, “and I don’t believe it. I believe you are just making that up.” “Indeed I’m not. Why, I always supposed everyone thought in colours. It must be very tiresome if you don’t.” “When you think of me what colour is it?” asked Peter curiously. “Yellow,” answered the Story Girl promptly. “And Cecily is a sweet pink, like those mayflowers, and Sara Ray is very pale blue, and Dan is red and Felix is yellow, like Peter, and Bev is striped.” “What colour am I?” asked Felicity, amid the laughter at my expense. “You’re—you’re like a rainbow,” answered the Story Girl rather reluctantly. She had to be honest, but she would rather not have complimented Felicity. “And you needn’t laugh at Bev. His stripes are beautiful. It isn’t HE that is striped. It’s just the THOUGHT of him. Peg Bowen is a queer sort of yellowish green and the Awkward Man is lilac. Aunt Olivia is pansy-purple mixed with gold, and Uncle Roger is navy blue.” “I never heard such nonsense,” declared Felicity. The rest of us were rather inclined to agree with her for once. We thought the Story Girl was making fun of us. But I believe she really had a strange gift of thinking in colours. In later years, when we were grown up, she told me of it again. She said that everything had colour in her thought; the months of the year ran through all the tints of the spectrum, the days of the week were arrayed as Solomon in his glory, morning was golden, noon orange, evening crystal blue, and night violet. Every idea came to her mind robed in its own especial hue. Perhaps that was why her voice and words had such a charm, conveying to the listeners’ perception such fine shadings of meaning and tint and music. “Well, let’s go and have something to eat,” suggested Dan. “What colour is eating, Sara?” “Golden brown, just the colour of a molasses cooky,” laughed the Story Girl. We sat on the ferny bank of the pool and ate of the generous basket Aunt Janet had provided, with appetites sharpened by the keen spring air and our wilderness rovings. Felicity had made some very nice sandwiches of ham which we all appreciated except Dan, who declared he didn’t like things minced up and dug out of the basket a chunk of boiled pork which he proceeded to saw up with a jack-knife and devour with gusto. “I told ma to put this in for me. There’s some CHEW to it,” he said. “You are not a bit refined,” commented Felicity. “Not a morsel, my love,” grinned Dan. “You make me think of a story I heard Uncle Roger telling about Cousin Annetta King,” said the Story Girl. “Great-uncle Jeremiah King used to live where Uncle Roger lives now, when Grandfather King was alive and Uncle Roger was a boy. In those days it was thought rather coarse for a young lady to have too hearty an appetite, and she was more admired if she was delicate about what she ate. Cousin Annetta set out to be very refined indeed. She pretended to have no appetite at all. One afternoon she was invited to tea at Grandfather King’s when they had some special company—people from Charlottetown. Cousin Annetta said she could hardly eat anything. ‘You know, Uncle Abraham,’ she said, in a very affected, fine-young-lady voice, ‘I really hardly eat enough to keep a bird alive. Mother says she wonders how I continue to exist.’ And she picked and pecked until Grandfather King declared he would like to throw something at her. After tea Cousin Annetta went home, and just about dark Grandfather King went over to Uncle Jeremiah’s on an errand. As he passed the open, lighted pantry window he happened to glance in, and what do you think he saw? Delicate Cousin Annetta standing at the dresser, with a big loaf of bread beside her and a big platterful of cold, boiled pork in front of her; and Annetta was hacking off great chunks, like Dan there, and gobbling them down as if she was starving. Grandfather King couldn’t resist the temptation. He stepped up to the window and said, ‘I’m glad your appetite has come back to you, Annetta. Your mother needn’t worry about your continuing to exist as long as you can tuck away fat, salt pork in that fashion.’ “Cousin Annetta never forgave him, but she never pretended to be delicate again.” “The Jews don’t believe in eating pork,” said Peter. “I’m glad I’m not a Jew and I guess Cousin Annetta was too,” said Dan. “I like bacon, but I can never look at a pig without wondering if they were ever intended to be eaten,” remarked Cecily naively. When we finished our lunch the barrens were already wrapping themselves in a dim, blue dusk and falling upon rest in dell and dingle. But out in the open there was still much light of a fine emerald-golden sort and the robins whistled us home in it. “Horns of Elfland” never sounded more sweetly around hoary castle and ruined fane than those vesper calls of the robins from the twilight spruce woods and across green pastures lying under the pale radiance of a young moon. When we reached home we found that Miss Reade had been up to the hill farm on an errand and was just leaving. The Story Girl went for a walk with her and came back with an important expression on her face. “You look as if you had a story to tell,” said Felix. “One is growing. It isn’t a whole story yet,” answered the Story Girl mysteriously. “What is it?” asked Cecily. “I can’t tell you till it’s fully grown,” said the Story Girl. “But I’ll tell you a pretty little story the Awkward Man told us—told me—tonight. He was walking in his garden as we went by, looking at his tulip beds. His tulips are up ever so much higher than ours, and I asked him how he managed to coax them along so early. And he said HE didn’t do it—it was all the work of the pixies who lived in the woods across the brook. There were more pixy babies than usual this spring, and the mothers were in a hurry for the cradles. The tulips are the pixy babies’ cradles, it seems. The mother pixies come out of the woods at twilight and rock their tiny little brown babies to sleep in the tulip cups. That is the reason why tulip blooms last so much longer than other blossoms. The pixy babies must have a cradle until they are grown up. They grow very fast, you see, and the Awkward Man says on a spring evening, when the tulips are out, you can hear the sweetest, softest, clearest, fairy music in his garden, and it is the pixy folk singing as they rock the pixy babies to sleep.” “Then the Awkward Man says what isn’t true,” said Felicity severely. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. L. M. Montgomery (2008). The Golden Road. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/316/pg316-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

FLOWERS O’ MAY

The Story-book of Science by Jean-Henri Fabre, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . HONEY CHAPTER LXXIX. HONEY “The bee is diligent: at sunrise it is at work, far from the hive, visiting the flowers one by one. You already know what it is in flowers that attracts insects: I have told you about the nectar, that sweet liquor that oozes out at the bottom of the corolla to entice the little winged people and make them shake the anthers on the stigma. This nectar is what the bee wants. It is its great feast, the great feast also of the little ones and the queen-mother; it is the prime ingredient of honey. How carry home a liquid so that others may enjoy it? The bee possesses neither pitcher, jar, pot, nor anything of the sort. I am wrong: like the ant that carries the plant-lice’s milk to the workers, it is provided with a natural can, stomach, paunch, or crop. “The bee enters a flower, plunges to the bottom of the corolla a long and flexible trunk, a kind of tongue that laps the sweet liquor. Droplet by droplet, drawn from this flower and that, the crop is filled. The bee at the same time nibbles a few grains of pollen. Moreover, it proposes to carry a good load of it to the hive. It has special utensils for this work: first, the down of its body, then the brushes and baskets that its legs supply. The down and the brushes are used for harvesting; the baskets for carrying. “First the bee rolls delightedly among the stamens to cover itself with pollen. Then it passes and re-passes over its velvety body the extremities of its hind legs, where is found a square piece bristling on the inside with short and rough hairs which serve as a brush. The grains of pollen scattered over the down of the insect are thus gathered together into a little pellet, which the intermediary legs seize in order to place it in one or other of the baskets. They call by this name a hollow edged with hair on the outside of the hind legs, a little above the brushes. It is there the pellets of pollen are piled up as fast as the brushes gather them on the powdery down. The load does not fall, because it is held by the hairs that edge the basket; it is also stuck against the bottom. The queen and the drones have not these working implements. Utensils are useless to those who do not work.” “The little yellow masses one sees on the hind legs of bees visiting the flowers are loads of pollen contained in the baskets?” asked Jules. “Exactly. The bee has lapped so much sweet from the corollas, has brushed its pollen-powdered sides so often, that finally the crop is full and the baskets are running over. It is time to go back to the hive, time for a flight made heavy with so much treasure. “Let us take advantage of the time used in the return journey to inform ourselves about the origin of honey. The bee carries with it a sugary liquor in its crop, two balls of pollen in its baskets; but all that is not yet honey. Real honey the bee prepares with the ingredients that we have just seen it gather; it cooks it, lets it simmer in its crop. Its little stomach is better than a real pot for carrying: it is an admirable alembic, in which the liquid that has been lapped up and the grains of pollen that have been nibbled are worked by digestion and converted into a delicious marmalade, which is honey. This skilful cooking finished, the content of the crop is honey. “The bee arrives at the hive. If by good fortune the queen-mother is encountered, the workman does reverence to her and offers her, from mouth to mouth, a sip of honey, the first from its crop. Then it seeks an empty cell, inserts its head into the storeroom, projects its tongue, and spits out the contents of its stomach; and there you have real honey disgorged by the bee.” “Is it all disgorged?” Emile asked. “Not all. The crop’s contents are usually divided into three parts: one for the nurses that remain in the hive to do the housework; a second for the little ones still in the nest; a third kept by the bee that has prepared the honey. Must it not have food in order to work well?” “Then bees feed on honey?” “Without a doubt. You imagined perhaps that bees made honey expressly for man. Undeceive yourself: bees make honey for themselves and not for us. We plunder their riches.” “What becomes of the little balls of pollen?” inquired Jules. “The pollen enters into the making of honey, and serves as nourishment for the bees. The working bee, on its return from harvesting, puts its hind legs into a cell where there is neither larva nor honey, and with the end of its middle legs it detaches the pellets and pushes them to the bottom. In repeating its trips it ends by filling both the cell in which the honey is disgorged and that in which the pollen is stored. The nurses draw on these provisions when they go from cell to cell, distributing small portions to the little ones; thence also they get their own food; in fact, the whole population finds its resources there when bad weather comes. “Flowers do not last all the year, and, moreover, there are days of rest, rainy days when the bees cannot go out. It is necessary, therefore, to have pollen and honey in reserve, and to have a good supply. So, when flowers are plenty and the harvest exceeds immediate requirements, the workers gather honey and pollen untiringly and store it in cells, which they close, as soon as full, with a cover of wax. “These are reserve supplies, safeguards for the future in case of scarcity. The wax cover is religiously respected; it would be a state crime to touch it prematurely. In time of want the seals are removed and each one draws from the open comb, but with restraint and sobriety. The comb exhausted, they break the seals of another.” “How are young bees fed?” was Jules’s next question. “When the cells destined to serve as nests are prepared in sufficient number by the wax-bees, the queen-mother goes from one to another, dragging with much effort her fruitful womb. The nurses form a respectful retinue. One egg, one only, is laid in each cell. In a few days—from three to six—there comes from this egg a larva, a little white worm, without legs, bent like a comma. Now begins the nurses’ delicate work. “They must every day, and several times a day, distribute nourishment to the little worms, not honey or pollen in its natural state, but a preparation of increasing strength such as delicate stomachs need at first. It is, in the beginning, a liquid paste, almost tasteless; then something sweeter; and finally pure honey, nourishment at its full strength. Do we offer a slice of beef to a crying baby? No, but milk first and then pap. Bees do the same: they have honey, strong food, for the strong; and weaker nourishment, tasteless pap, for the weak. How do they prepare these more or less substantial foods? It would be hard to say. Perhaps they mix pollen and honey in different proportions. “In six days the larvæ, called brood-comb, have attained their development. Then, like the larvæ of other insects, they retire from the world to undergo metamorphosis. In order to protect its suffering flesh at the critical moment of its transfiguration, each larva lines the inside of its cell with silk, and the working-bees close the cell with a cover of wax. In the silk-lined case the skin is cast off and the passage to the state of nymph accomplished. Twelve days later the nymph awakes from the deep sleep of the second birth; it shakes itself, tears its narrow swaddling-clothes, and comes forth a bee. The wax cover is gnawed by the inclosed insect as well as by the working-bees lending a ready hand to the resuscitated; and the hive counts one more citizen. The new-born bee makes its toilet a little, dries its wings, polishes its body, and is off to work. It knows its trade without having had to learn it: wax-bee in its youth, nurse in its old age.” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jean-Henri Fabre (2018). The Story-book of Science. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/56795/pg56795-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

The bee is diligent: at sunrise it is at work, far from the hive, visiting the flowers one by one

The Story-book of Science by Jean-Henri Fabre, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . FRUIT CHAPTER LX. FRUIT “IT would be knowing a person very little only to be aware of his wearing a garment of a certain material, a coat of such and such a cloth. One does not know a flower any better when one knows that it is clothed with a calyx and a corolla. What is under this covering? A flowering branch of the Gillyflower “Let us examine together this gillyflower. It has a calyx of four sepals and a corolla of four yellow petals. I take away these eight pieces. What is left now is the essential part; that is to say, the thing without which the flower could not fill its rôle and would be perfectly useless. Let us go carefully over this remaining part. You will find it well worth the trouble. “First, there are six little white rods, each one surmounted by a bag full of yellow powder. These six pieces are called stamens. They are found in all flowers in greater or less number. The gillyflower has six, four longer ones arranged in pairs, and two shorter. “The double bag that surmounts the stamen is called an anther. The dust contained in the anther is known as pollen. It is yellow in the gillyflower, lily, and most plants; ashy gray in the poppy.” “You have already told us,” Jules interposed, “how clouds of pollen, raised by the wind in the woods, are the cause of supposed showers of sulphur that frighten people so.” “I take away the six stamens. There remains a central body, swollen at the bottom, narrow at the top, and surmounted by a kind of head wet with a sticky moisture. In its entirety this central body takes the name of pistil; the swelling at the bottom is called an ovary, and the sticky head that terminates it is a stigma.” “What big names for such little things!” exclaimed Jules. “Little, yes; but of unparalleled importance. These little things, my dear friend, give us our daily bread; without the miraculous work of these little things we should die of hunger.” “I will take care to remember their names, then.” “I, too,” chimed in Emile; “but you must go over them again, they are so hard to learn.” Uncle Paul began again. Jules and Emile repeated after him: stamen, anther and pollen; pistil, stigma and ovary. “With a penknife I divide the flower in two. The split ovary shows us what is inside.” “I see little seeds in regular rows in two compartments,” observed Jules. “Do you know what those hardly visible seeds are?” “Not yet.” “They are the future seeds of the plant. The ovary, then, is the part of the plant where the seeds form. At a certain time the flower withers; the petals wilt and fall; the calyx does the same, or remains to play the part of protector a while longer; the dried stamens break off; only the ovary remains, growing larger, ripening, and finally becoming the fruit. “Every fruit—the pear, apple, apricot, peach, walnut, cherry, melon, strawberry, almond, chestnut—began by being a little swelling of the pistil; all these excellent things that the plant furnishes us for food were first ovaries.” “A pear began by being the ovary of a pear blossom?” “Yes, my child; pears, apples, cherries, apricots, begin by being the ovaries of their respective flowers. I will show you an apricot in its blossom.” Uncle Paul took an apricot blossom, opened it with his penknife, and showed the children what is here shown in the picture. “In the heart of the flower you see the pistil surrounded by numerous stamens. The head that terminates it at the top is the stigma; the swelling at the bottom is the ovary or future apricot.” “That little green thing would have been an apricot, full of sweet juice, that I like so much?” inquired Emile. “That little green thing would have become an apricot like those Emile is so fond of. Now would you like to see the ovary that gives us bread?” “Oh, yes! All these things are very curious,” replied Jules. “Better than that, very important.” Claire gave her uncle a needle at his request; then with the delicate patience necessary for this operation he isolated one of the numerous flowers of which the whole forms the ear of wheat. The delicate little flower displayed clearly, on the point of the needle, the different parts composing it. Wheat “The blessed plant that gives us bread has not time to think of its toilet. It has such weighty things to attend to: it must feed the world! So you see what quiet clothes it wears! Two poor scales serve it for calyx and corolla. You can easily recognize three hanging stamens with their double sachets for anthers. The principal body of the flower is the tun-bellied ovary, which, when ripe, will be a grain of wheat. It is surmounted by the stigma, fashioned like a double plume of exquisite delicacy. Salute it, my children: behold the modest little flower that gives life to us all!” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jean-Henri Fabre (2018). The Story-book of Science. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/56795/pg56795-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

A flowering branch of the Gillyflower

SELECTING THE FLOWER OF MANKIND

Data and Its Color

Authors:
(1) Jianzhu Yao, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology;
(2) Ziqi Liu, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology;
(3) Jian Guan, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology;
(4) Minlie Huang, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology. Table of Links Abstract and Intro Related Works DIALSTORY Dataset Proposed Tasks Methodology Experiments Discussion Future Work Conclusion Limitations and References Abstract Many classical fairy tales, fictions, and screenplays leverage dialogue to advance story plots and establish characters. We present the first study to explore whether machines can understand and generate dialogue in stories, which require capturing traits of different characters and the relationships between them. To this end, we propose two new tasks including Masked Dialogue Generation and Dialogue Speaker Recognition, i.e., generating missing dialogue turns and predicting speakers for specified dialogue turns, respectively. We build a new dataset DIALSTORY, which consists of 105k Chinese stories with a large amount of dialogue weaved into the plots to support the evaluation. We show the difficulty of the proposed tasks by testing existing models with automatic and manual evaluation on DIALSTORY. Furthermore, we propose to learn explicit character representations to improve performance on these tasks. Extensive experiments and case studies show that our approach can generate more coherent and informative dialogue, and achieve higher speaker recognition accuracy than strong baselines. 1 Introduction Dialogue plays an important role in various types of literary works such as short stories, novels, and screenplays by advancing plots, establishing characters, and providing expositions using natural and lifelike words (Kennedy et al., 1983). Compared to dialogue in conversational scenarios such as chitchat bots (Shang et al., 2015) or task-oriented dialogue systems (Deng et al., 2012), dialogue in stories is mainly used to exhibit emotions, motivations, or personalities of characters following the authors’ design, which further serve for the coherence, informativeness, engagingness, and plot development of whole stories. Dialogue is also revealed to be essential for user-agent interaction in many text adventure games (Xi et al., 2021;Li et al., 2022). It has not been widely explored for machines to understand and generate dialogue in stories despite the broad recognition of the importance of this ability. To spur research in this field, we present a new story dataset named DIALSTORY, which consists of 105k Chinese short stories with automatic annotations of dialogue turns and corresponding speakers. Furthermore, we formulate two new tasks including: (1) Masked Dialogue Generation (DialGen): completing a story with several dialogue turns masked with placeholders; and (2) Dialogue Speaker Recognition (DialSpk): choosing correct speakers from given candidates for several specified dialogue turns. We construct standardized datasets for these tasks through automatic or manual annotation based on DIALSTORY. As exemplified in Figure 1, these tasks comprehensively investigate the ability to capture characters’ emotions (e.g., the mother squirrel is worried about baby squirrel’s catching cold), motivations (e.g., the mother squirrel intends to call her baby to come back home or get medicine), and relationship between each other (e.g. mother rabbit knows the kind of flower as a friend of mother squirrel when they were kids). Furthermore, we found in massive stories that dialogue had a strong connection to different characters, reflected in their emotional states, speaking styles, and plot development. To provide more insights to tackle these tasks, we propose to learn character representations for modeling dependencies between characters and dialogue explicitly. Extensive experiments and case studies show that our approach can generate more coherent and informative dialogue, and achieve higher speaker recognition accuracy than strong baselines. This paper is available on arxiv under CC 4.0 DEED license. Authors: (1) Jianzhu Yao, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology; (2) Ziqi Liu, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology; (3) Jian Guan, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology; (4) Minlie Huang, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology. Authors: Authors: (1) Jianzhu Yao, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology; (2) Ziqi Liu, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology; (3) Jian Guan, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology; (4) Minlie Huang, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology. Table of Links Abstract and Intro Abstract and Intro Related Works Related Works DIALSTORY Dataset DIALSTORY Dataset Proposed Tasks Proposed Tasks Methodology Methodology Experiments Experiments Discussion Discussion Future Work Future Work Conclusion Conclusion Limitations and References Limitations and References Abstract Many classical fairy tales, fictions, and screenplays leverage dialogue to advance story plots and establish characters. We present the first study to explore whether machines can understand and generate dialogue in stories, which require capturing traits of different characters and the relationships between them. To this end, we propose two new tasks including Masked Dialogue Generation and Dialogue Speaker Recognition, i.e., generating missing dialogue turns and predicting speakers for specified dialogue turns, respectively. We build a new dataset DIALSTORY, which consists of 105k Chinese stories with a large amount of dialogue weaved into the plots to support the evaluation. We show the difficulty of the proposed tasks by testing existing models with automatic and manual evaluation on DIALSTORY. Furthermore, we propose to learn explicit character representations to improve performance on these tasks. Extensive experiments and case studies show that our approach can generate more coherent and informative dialogue, and achieve higher speaker recognition accuracy than strong baselines. 1 Introduction Dialogue plays an important role in various types of literary works such as short stories, novels, and screenplays by advancing plots, establishing characters, and providing expositions using natural and lifelike words (Kennedy et al., 1983). Compared to dialogue in conversational scenarios such as chitchat bots (Shang et al., 2015) or task-oriented dialogue systems (Deng et al., 2012), dialogue in stories is mainly used to exhibit emotions, motivations, or personalities of characters following the authors’ design, which further serve for the coherence, informativeness, engagingness, and plot development of whole stories. Dialogue is also revealed to be essential for user-agent interaction in many text adventure games (Xi et al., 2021;Li et al., 2022). It has not been widely explored for machines to understand and generate dialogue in stories despite the broad recognition of the importance of this ability. To spur research in this field, we present a new story dataset named DIALSTORY, which consists of 105k Chinese short stories with automatic annotations of dialogue turns and corresponding speakers. Furthermore, we formulate two new tasks including: (1) Masked Dialogue Generation (DialGen): completing a story with several dialogue turns masked with placeholders; and (2) Dialogue Speaker Recognition (DialSpk): choosing correct speakers from given candidates for several specified dialogue turns. We construct standardized datasets for these tasks through automatic or manual annotation based on DIALSTORY. As exemplified in Figure 1, these tasks comprehensively investigate the ability to capture characters’ emotions (e.g., the mother squirrel is worried about baby squirrel’s catching cold), motivations (e.g., the mother squirrel intends to call her baby to come back home or get medicine), and relationship between each other (e.g. mother rabbit knows the kind of flower as a friend of mother squirrel when they were kids). Furthermore, we found in massive stories that dialogue had a strong connection to different characters, reflected in their emotional states, speaking styles, and plot development. To provide more insights to tackle these tasks, we propose to learn character representations for modeling dependencies between characters and dialogue explicitly. Extensive experiments and case studies show that our approach can generate more coherent and informative dialogue, and achieve higher speaker recognition accuracy than strong baselines. This paper is available on arxiv under CC 4.0 DEED license. This paper is available on arxiv under CC 4.0 DEED license. available on arxiv

Understanding and Generating Dialogue between Characters in Stories: Abstract and Intro

Exciting news! Our monthly product update is here! Get ready for the latest mobile app update, Apple’s Memoji-inspired pixelated avatars, “April Shower Brings May Flowers” Color Theme, better story pages layout, fresh top writers ranking page, and more!🚀 This product update reflects changes to the platform fromMarch 1st until May 3rd, 2024. New for Writers New Mobile App Update: Version 2.0 Just Landed The 2.0 Version has brought HackerNoon’s original polling data, and active technology polls, into The HackerNoon App to help you stay on the pulse of the internet’s trends. Stay in the loop with the latest tech discussions, cast your vote, and contribute your insights to poll topics—all from your phone! Here's how: Navigate to the homepage, scroll down, and tap on "Poll of the Week"  - this will lead you to a collection of completed polls. Protip: When you see a topic you want to elaborate on, such as this one, simply click “✏️about the results” and it will direct you to a fully editable draft. You can also create a new draft on the web versions of HackerNoon polls as well! Simply search for any polls in our Poll database and click on “Write about the results” to get to a new draft with polls results in the feature image. This release also includes major improvements to the mobile writing experience. We added hundreds of story templates to make it easier to start writing and made the headline story function more like Apple Notes and Google Keep, editable in the story draft itself and within story settings. Breakthrough ideas can come from tiny keyboards! And that's not all. We improved and sped up authentication to save you a few precious moments upon opening the HackerNoon App, and changed the user tab so that once you tap it, you’ll get instantly directed to your user profile where you can easily update your information or navigate to settings. Check it out for yourself: Keep the feedback coming! We’ll keep improving! Emoji Credibility Indicators are Live on GitHub and Figma Emoji Credibility Indicators by HackerNoon are now live on  Figma and Github! Our open-source pixelated emoji pack was designed to communicate context about a story's content on HackerNoon and you can be amongst the first to try them! What will you get from this open-source package? Pixelated Emojis, designed on a 24px grid.
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Stay in the loop with the latest tech discussions, cast your vote, and contribute your insights to poll topics—all from your phone! Here's how: Navigate to the homepage, scroll down, and tap on "Poll of the Week"  - this will lead you to a collection of completed polls. 2.0 Version original polling data active technology polls Protip: When you see a topic you want to elaborate on, such as this one, simply click “✏️about the results” and it will direct you to a fully editable draft. You can also create a new draft on the web versions of HackerNoon polls as well! Simply search for any polls in our Poll database and click on “Write about the results” to get to a new draft with polls results in the feature image. Protip : When you see a topic you want to elaborate on, such as this one , simply click “✏️about the results” and it will direct you to a fully editable draft. You can also create a new draft on the web versions of HackerNoon polls as well! Simply search for any polls in our Poll database and click on “Write about the results” to get to a new draft with polls results in the feature image. Protip such as this one This release also includes major improvements to the mobile writing experience. We added hundreds of story templates to make it easier to start writing and made the headline story function more like Apple Notes and Google Keep, editable in the story draft itself and within story settings. Breakthrough ideas can come from tiny keyboards! story templates And that's not all. We improved and sped up authentication to save you a few precious moments upon opening the HackerNoon App, and changed the user tab so that once you tap it, you’ll get instantly directed to your user profile where you can easily update your information or navigate to settings. Check it out for yourself: Keep the feedback coming! We’ll keep improving! Keep the feedback coming! We’ll keep improving! the feedback Emoji Credibility Indicators are Live on GitHub and Figma Emoji Credibility Indicators are Live on GitHub and Figma Emoji Credibility Indicators are Live on GitHub and Figma Emoji Credibility Indicators are Live on GitHub and Figma Emoji Credibility Indicators by HackerNoon are now live on Figma and Github ! Figma Figma Github Our open-source pixelated emoji pack was designed to communicate context about a story's content on HackerNoon and you can be amongst the first to try them! What will you get from this open-source package? What will you get from this open-source package? Pixelated Emojis, designed on a 24px grid. Well crafted SVGs Fully customizable Ready to use for development via GitHub Repo and Figma! Pixelated Emojis, designed on a 24px grid. Well crafted SVGs Fully customizable Ready to use for development via GitHub Repo and Figma ! GitHub Repo GitHub Repo Figma Figma Sounds good? Try them out today and tell us about your experience here. Designing HackerNoon's Emoji Credibility Indicators: Get the developer’s perspective here. Learn more about Emoji Credibility Indicators here. Read about all our emoji credibility indicators, their meaning, and how to use them here. Sounds good? Try them out today and tell us about your experience here . here here Designing HackerNoon's Emoji Credibility Indicators : Get the developer’s perspective here . Designing HackerNoon's Emoji Credibility Indicators Designing HackerNoon's Emoji Credibility Indicators here here Learn more about Emoji Credibility Indicators here . here here Read about all our emoji credibility indicators, their meaning, and how to use them here . here here HackerNoon's Enhanced Top Writers Ranking: Explore the New Page for Tech Categories' Leaders HackerNoon's Enhanced Top Writers Ranking: Explore the New Page for Tech Categories' Leaders HackerNoon's Enhanced Top Writers Ranking: Explore the New Page for Tech Categories' Leaders The latest evolution of HackerNoon's Top Writers ranking now features a dedicated page for each of our Tech Categories . This feature aims to spotlight HackerNoon’s exceptional contributors and refine and enhance readers’ experience, making it easier to discover and engage with the tech’s leading voices. HackerNoon's Top Writers ranking HackerNoon's Top Writers ranking Tech Categories Tech Categories You can now navigate to all Tech Categories from the top nav. Check it out! You can now navigate to all Tech Categories from the top nav. Check it out! all Tech Categories What's New? What's New? Dedicated Pages: Each Tech Category now boasts its own dedicated Top Writers page, offering a comprehensive showcase of the most prolific writers. If you visit https://hackernoon.com/writers/programming you’ll see each top writer’s profile, including name, handle, bio and avatar, tags of expertise, and their placement on the ranking. Real-Time Updates: Our Top Writers ranking is updated daily, ensuring users remain up-to-date with the latest contributors in their favorite categories. Dedicated Pages: Each Tech Category now boasts its own dedicated Top Writers page, offering a comprehensive showcase of the most prolific writers. If you visit https://hackernoon.com/writers/programming you’ll see each top writer’s profile, including name, handle, bio and avatar, tags of expertise, and their placement on the ranking. https://hackernoon.com/writers/programming https://hackernoon.com/writers/programming Real-Time Updates: Our Top Writers ranking is updated daily, ensuring users remain up-to-date with the latest contributors in their favorite categories. How Does This Improve Your Experience? How Does This Improve Your Experience? If you’re a reader, this ranking is a great place to find new authors and subscribe to their work. And if you’re a writer… well, wouldn’t you like to land a top spot? Find out how here . Happy reading! here here New for Readers Create Your Own Pixelated Avatar With Hackernoon Create Your Own Pixelated Avatar With Hackernoon Create Your Own Pixelated Avatar With Hackernoon Create Your Own Pixelated Avatar With Hackernoon https://www.youtube.com/watch?v=WFc3ryAkCv4&embedable=true https://www.youtube.com/watch?v=WFc3ryAkCv4&embedable=true Pixelated avatars have just landed on HackerNoon , and now you have the power to create your own! just landed on HackerNoon Add some fun to your profile, and improve your experience at HackerNoon while ensuring your profile reflects your true essence. Get your customized avatar: Get your customized avatar: Go to your profile page settings. Click the “Create Avatar” button - you can’t miss it! Have fun creating your avatar! Hit “Save Avatar” and it’ll automatically replace your old placeholder image. Go to your profile page settings . profile page settings profile page settings Click the “Create Avatar” button - you can’t miss it! Have fun creating your avatar! Hit “Save Avatar” and it’ll automatically replace your old placeholder image. New Theme Alert 🌸 New Theme Alert "In a world of petals and pixels, let your content flourish." - GPT, Chat "In a world of petals and pixels, let your content flourish." - GPT, Chat Experience the all-new HackerNoon theme by clicking the paintbrush icon, choosing BlossomBytes , and hitting save. Watch as the design gets instantly transformed: BlossomBytes Protip: you can also customize HackerNoon in many other ways via HackerNoon’s Choose Your Color setting. Simply click on the paintbrush to the right of the yellow banner ad, and see for yourself! Protip: you can also customize HackerNoon in many other ways via HackerNoon’s Choose Your Color setting. Simply click on the paintbrush to the right of the yellow banner ad, and see for yourself! Choose Your Color One-Tap Google Signup and Login? Yup, HackerNoon Has It! One-Tap Google Signup and Login? Yup, HackerNoon Has It! One-Tap Google Signup and Login? Yup, HackerNoon Has It! HackerNoon continues to simplify the signup process, and if you have a Google account, then this one is for you - meet the One-Tap Google Signup and Login. This feature leverages the security and convenience of Google's authentication system, making it easy to access HackerNoon with a single tap, whether you're a seasoned writer or a new reader eager to explore our platform, ensuring a hassle-free experience. All you need is: All you need is: Google's Chrome browser on your computer; To be logged in to your Google account. Google's Chrome browser on your computer; To be logged in to your Google account. With these two requirements checked off, you’ll be able to visit hackernoon.com and with just one tap, sign up or log in. Here’s what it looks like: hackernoon.com hackernoon.com Remember: You must be logged in to Google for the one-tap login to work! If, after being logged in to your Google account, you still don’t see the one-tap option, check the permissions for HackerNoon on your browser. Remember: You must be logged in to Google for the one-tap login to work! Remember: If, after being logged in to your Google account, you still don’t see the one-tap option, check the permissions for HackerNoon on your browser. What if I don’t have a Google account? What if I don’t have a Google account? No problem! You can either follow our regular Signup flow ( learn more here and here ), just make sure you have an active email, a GitHub, or an X account, and you’re all set! Click here to create a HackerNoon account! learn more here learn more here here here here here Story Page Redesign Story Page Redesign Story Page Redesign Story pages have received a fresh makeover! Translations and TLDR summaries now share the spotlight with the story title, enhancing navigation. Easily identify stories with multiple authors in the "About the Author" section, along with various CTAs. Enjoy the playful pixelated icons for bookmarking, reacting, commenting, and sharing, adding a fun touch to interaction. Moreover, wider stories now occupy more screen space, ensuring better readability. New for Brands New for Brands Tech Press Release Page Tech Press Release Page Tech Press Release Page Tech Press Release Page For our beloved brands, a new package just landed: Tech Press Release ! Tech Press Release Tech Press Release Publish your announcements onto HackerNoon and join our trusted +4K brands worldwide. If you’re undecided about whether or not to partner with HackerNoon, look at our Reader Demographics section right here. If you’re undecided about whether or not to partner with HackerNoon, look at our Reader Demographics section right here . here here That's all folks!

It's Gonna Be May... a New Mobile App Update, Pixelated Avatars, Revamped Story Pages and More

এটি হতে চলেছে... একটি নতুন মোবাইল অ্যাপ আপডেট, পিক্সেলেড অবতার, সংস্কার করা গল্পের পৃষ্ঠা এবং আরও অনেক কিছু

Es wird Mai ... ein neues Update für die mobile App, pixelige Avatare, überarbeitete Story-Seiten und mehr

Será mayo... una nueva actualización de la aplicación móvil, avatares pixelados, páginas de historias renovadas y más

Ce sera en mai... une nouvelle mise à jour de l'application mobile, des avatars pixelisés, des pages d'histoire remaniées et bien plus encore

यह मई में होने वाला है... एक नया मोबाइल ऐप अपडेट, पिक्सेलयुक्त अवतार, नया स्टोरी पेज और बहुत कुछ

5月になります...新しいモバイルアプリのアップデート、ピクセル化されたアバター、改良されたストーリーページなど

5월이 됩니다... 새로운 모바일 앱 업데이트, 픽셀화된 아바타, 개편된 스토리 페이지 등

Vai ser maio... uma nova atualização de aplicativo móvel, avatares pixelados, páginas de histórias renovadas e muito mais

Это будет май... новое обновление мобильного приложения, пиксельные аватары, обновленные страницы историй и многое другое

Mayıs Olacak... Yeni Mobil Uygulama Güncellemesi, Pikselli Avatarlar, Yenilenen Hikaye Sayfaları ve Daha Fazlası

Sẽ có thể xảy ra... một bản cập nhật ứng dụng di động mới, Hình đại diện có pixel, Trang câu chuyện được cải tiến và hơn thế nữa

五月即将到来……新的移动应用程序更新、像素化头像、改版的故事页面等等

Mission Generation Using Classic Machine Learning and Recurrent Neural Networks in Zombie State

জম্বি রাজ্যে ক্লাসিক মেশিন লার্নিং এবং পুনরাবৃত্ত নিউরাল নেটওয়ার্ক ব্যবহার করে মিশন জেনারেশন

Missionsgenerierung mit klassischem maschinellem Lernen und rekurrierenden neuronalen Netzwerken im Zombie-Zustand

Generación de misiones utilizando aprendizaje automático clásico y redes neuronales recurrentes en estado zombie

Génération de mission à l'aide de l'apprentissage automatique classique et des réseaux de neurones récurrents dans un état zombie

ज़ोंबी स्टेट में क्लासिक मशीन लर्निंग और रीकरंट न्यूरल नेटवर्क का उपयोग करके मिशन जनरेशन

ゾンビ状態での古典的な機械学習とリカレントニューラルネットワークを使用したミッション生成

좀비 상태에서 고전적인 기계 학습과 순환 신경망을 사용한 미션 생성

Geração de missão usando aprendizado de máquina clássico e redes neurais recorrentes no estado zumbi

Генерация миссий с использованием классического машинного обучения и рекуррентных нейронных сетей в состоянии зомби

Zombie State'te Klasik Makine Öğrenimi ve Tekrarlayan Sinir Ağlarını Kullanarak Görev Oluşturma

Tạo nhiệm vụ bằng cách sử dụng mạng lưới thần kinh định kỳ và học máy cổ điển ở trạng thái Zombie

在僵尸状态下使用经典机器学习和循环神经网络生成任务

From Chat-Bots to Killer-Bots?

How Understanding CPU Caches Can Supercharge Your Code: 461% Faster MatMul Case Study

Chain Theory: A Proposed User-Friendly and Customizable Cryptographic Model

চেইন তত্ত্ব: একটি প্রস্তাবিত ব্যবহারকারী-বান্ধব এবং কাস্টমাইজযোগ্য ক্রিপ্টোগ্রাফিক মডেল

Kettentheorie: Ein Vorschlag für ein benutzerfreundliches und anpassbares kryptografisches Modell

Teoría de la cadena: una propuesta de modelo criptográfico personalizable y fácil de usar

Théorie des chaînes : une proposition de modèle cryptographique convivial et personnalisable

चेन थ्योरी: एक प्रस्तावित उपयोगकर्ता-अनुकूल और अनुकूलन योग्य क्रिप्टोग्राफ़िक मॉडल

チェーン理論: ユーザーフレンドリーでカスタマイズ可能な暗号モデルの提案

체인 이론: 제안된 사용자 친화적이고 사용자 정의 가능한 암호화 모델

Teoria da Cadeia: Uma Proposta de Modelo Criptográfico Fácil de Usar e Personalizável

Теория цепей: предлагаемая удобная и настраиваемая криптографическая модель

Zincir Teorisi: Önerilen Kullanıcı Dostu ve Özelleştirilebilir Bir Şifreleme Modeli

Lý thuyết chuỗi: Một mô hình mật mã thân thiện với người dùng và có thể tùy chỉnh được đề xuất

链式理论：一种用户友好且可定制的加密模型

So, let’s start! Tell us a bit about yourself. For example, name, profession, and personal interests. I’m João, and I have been a Software Engineer for more than 10 years now. I am technically a Software and Telecom engineer, but most part I have only been doing software engineering professionally. There are many things I love to do, and that, of course, includes making Tech videos and writing blog posts and articles, and maintaining my website. Outside work and outside Tech, I am someone very curious about biology, which is why I like to try to maintain a garden where I grow things like blueberry bushes, honeysuckles, and gooseberry bushes, and I also love photography. I mostly enjoy photographing nature, cities, and things with lights. Further, I also like to enjoy my time doing stuff related to art, for example, video, photo editing, and style editing. Outside of all of this, I also enjoy music, series, films, traveling, cooking, and, from time to time, the occasional electronics project. Interesting! What was your latest Hackernoon Top story about? My latest Hackernoon Top story was the one I did about Kuma, which is about a way to create Meshes using Kuma-Meshes, where we can have a much more granular control over the data flow within our own network, which, amongst other things, can protect an organization against internal bad actors. Do you usually write on similar topics? If not, what do you usually write about? A the moment I exclusively write about Tech, although I can form time to time relate those posts with other kind of topics like opinionated arguments or even politics when they have the potential to influence tech. It can also be that I can write about how some particular tech stacks may influence our approach to tech or even society and environment. But the main focus is always tech. Great! What is your usual writing routine like (if you have one?) I do not have a specific writing routine, although I am writing a lot more these days. Being a writer in tech can be a challenge. It’s not often our main role, but an addition to another one. What is the biggest challenge you have when it comes to writing? My biggest challenge in writing is creating a functional example as fast as possible. Creating a story, implementing needed elements, making them run, creating tests for it, creating databases or any other persistence mechanisms for it, and trying to guarantee as much as possible that people can use the examples without walking against errors or faults is usually a very energy-intensive work. Therefore, it can take longer than desired. What is the next thing you hope to achieve in your career? I want to be as successful as possible with my own effort and work, and I want to share my experiences and knowledge with other colleagues in the world of software engineering. I don’t know if it eventually can become a full-time job, but if it does, it will probably be the next thing that I would love to achieve. Wow, that’s admirable. Now, something more casual: What is your guilty pleasure of choice? Listening to Madonna’s Ray of Light album. Do you have a non-tech-related hobby? If yes, what is it? Yes! I love to take photos of wildlife. I especially love making macro photos of leaves, insects, and flowers, as well as minerals, rocks, glass, metals, and anything that looks outstanding in a macro photo. What can the Hacker Noon community expect to read from you next? I usually write more about topics related to the Kotlin programming language; however, having said that I am finding it more and more interesting to write about security and operations from the DevSecOps area as I did in my article about Kuma. I think we can expect to read more about the SecOps area in my next articles, but I will still write about Dev. What’s your opinion on HackerNoon as a platform for writers? I think HackerNoon is a unique platform for writers to share knowledge about Technology because it is very recognizable, and a lot is automatically done for us like, for example, in this last article when it comes to translating my Kuma article in multiple languages. That was a very nice surprise to see. All in all, I think HackerNoon really appeals to Software programmers, Engineers, Developers, and even Businesses and so I’m very happy to keep writing for HackerNoon. Thanks for taking time to join our “Meet the writer” series. It was a pleasure. Do you have any closing words? Yes, thank you for giving me this great interview. I really appreciate the boost given to my article. I hope to be able to keep writing for HackerNoon for as long as possible. It is a pleasure to do so. Thanks again for the incredible support and for being there. So, let’s start! Tell us a bit about yourself. For example, name, profession, and personal interests. I’m João, and I have been a Software Engineer for more than 10 years now. I am technically a Software and Telecom engineer, but most part I have only been doing software engineering professionally. There are many things I love to do, and that, of course, includes making Tech videos and writing blog posts and articles, and maintaining my website. Outside work and outside Tech, I am someone very curious about biology, which is why I like to try to maintain a garden where I grow things like blueberry bushes, honeysuckles, and gooseberry bushes, and I also love photography. I mostly enjoy photographing nature, cities, and things with lights. Further, I also like to enjoy my time doing stuff related to art, for example, video, photo editing, and style editing. Outside of all of this, I also enjoy music, series, films, traveling, cooking, and, from time to time, the occasional electronics project. Interesting! What was your latest Hackernoon Top story about? My latest Hackernoon Top story was the one I did about Kuma, which is about a way to create Meshes using Kuma-Meshes, where we can have a much more granular control over the data flow within our own network, which, amongst other things, can protect an organization against internal bad actors. Do you usually write on similar topics? If not, what do you usually write about? A the moment I exclusively write about Tech, although I can form time to time relate those posts with other kind of topics like opinionated arguments or even politics when they have the potential to influence tech. It can also be that I can write about how some particular tech stacks may influence our approach to tech or even society and environment. But the main focus is always tech. Great! What is your usual writing routine like (if you have one?) I do not have a specific writing routine, although I am writing a lot more these days. Being a writer in tech can be a challenge. It’s not often our main role, but an addition to another one. What is the biggest challenge you have when it comes to writing? My biggest challenge in writing is creating a functional example as fast as possible. Creating a story, implementing needed elements, making them run, creating tests for it, creating databases or any other persistence mechanisms for it, and trying to guarantee as much as possible that people can use the examples without walking against errors or faults is usually a very energy-intensive work. Therefore, it can take longer than desired. What is the next thing you hope to achieve in your career? I want to be as successful as possible with my own effort and work, and I want to share my experiences and knowledge with other colleagues in the world of software engineering. I don’t know if it eventually can become a full-time job, but if it does, it will probably be the next thing that I would love to achieve. Wow, that’s admirable. Now, something more casual: What is your guilty pleasure of choice? Listening to Madonna’s Ray of Light album. Do you have a non-tech-related hobby? If yes, what is it? Yes! I love to take photos of wildlife. I especially love making macro photos of leaves, insects, and flowers, as well as minerals, rocks, glass, metals, and anything that looks outstanding in a macro photo. What can the Hacker Noon community expect to read from you next? I usually write more about topics related to the Kotlin programming language; however, having said that I am finding it more and more interesting to write about security and operations from the DevSecOps area as I did in my article about Kuma. I think we can expect to read more about the SecOps area in my next articles, but I will still write about Dev. What’s your opinion on HackerNoon as a platform for writers? I think HackerNoon is a unique platform for writers to share knowledge about Technology because it is very recognizable, and a lot is automatically done for us like, for example, in this last article when it comes to translating my Kuma article in multiple languages. That was a very nice surprise to see. All in all, I think HackerNoon really appeals to Software programmers, Engineers, Developers, and even Businesses and so I’m very happy to keep writing for HackerNoon. Thanks for taking time to join our “ Meet the writer ” series. It was a pleasure. Do you have any closing words? Meet the writer Yes, thank you for giving me this great interview. I really appreciate the boost given to my article. I hope to be able to keep writing for HackerNoon for as long as possible. It is a pleasure to do so. Thanks again for the incredible support and for being there.

Meet the Writer: HackerNoon's Contributor João Esperancinha, Software Engineer

This paper is available on arxiv under CC 4.0 license. Authors: (1) Muzhaffar Hazman, University of Galway, Ireland; (2) Susan McKeever, Technological University Dublin, Ireland; (3) Josephine Griffith, University of Galway, Ireland. Table of Links Abstract and Introduction Related Works Methodology Results Limitations and Future Works Conclusion, Acknowledgments, and References A Hyperparameters and Settings B Metric: Weighted F1-Score C Architectural Details D Performance Benchmarking E Contingency Table: Baseline vs. Text-STILT 6 Conclusion In this work, we addressed the challenge of training multimodal meme sentiment classifiers on a limited number of labelled memes by incorporating unimodal sentiment analysis data. We did so by proposing the first instance of STILT that applies unimodal intermediate tasks to a multimodal target task. Specifically, we tested image-only and text-only sentiment classification as intermediate tasks in training a meme sentiment classifier. We showed that this approach worked – unimodal text improved meme classification performance to a statistically significant degree. This novel approach allowed us to train a meme classifier that outperforms meme-only finetuning with only 60% as many labelled meme samples. As possible explanations for our observations, we discuss apparent similarities and differences in the roles of image and text modalities between unimodal and multimodal sentiment analysis tasks. Acknowledgments This work was conducted with the financial support of the Science Foundation Ireland Centre for Research Training in Digitally-Enhanced Reality (d-real) under Grant No. 18/CRT/6224; and the provision of computational facilities and support from the Irish Centre for High-End Computing (ICHEC). References Christian Bauckhage. 2011. Insights into internet memes. Proceedings of the International AAAI Conference on Web and Social Media, 5(1):42–49. Efrat Blaier, Itzik Malkiel, and Lior Wolf. 2021. Caption enriched samples for improving hateful memes detection. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 9350–9358, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics. Ana-Maria Bucur, Adrian Cosma, and Ioana Iordache. 2022. BLUE at memotion 2.0 2022: You have my image, my text and my transformer. In De-Factify @ AAAI 2022. First Workshop on Multimodal FactChecking and Hate Speech Detection, CEUR Workshop Proceedings. AAAI. Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. 2019. BoolQ: Exploring the surprising difficulty of natural yes/no questions. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 2924–2936, Minneapolis, Minnesota. Association for Computational Linguistics. CrowdFlower. 2016. Image sentiment polarity - dataset. Available at https://data.world/ crowdflower/image-sentiment-polarity. Accessed: 2023-01-15. Baishan Duan and Yuesheng Zhu. 2022. Browallia at memotion 2.0 2022 : Multimodal memotion analysis with modified ogb strategies (short paper). In DeFactify @ AAAI 2022. First Workshop on Multimodal Fact-Checking and Hate Speech Detection, CEUR Workshop Proceedings. AAAI. Noam Gal, Limor Shifman, and Zohar Kampf. 2016. “it gets better”: Internet memes and the construction of collective identity. New Media & Society, 18(8):1698–1714. Yue Gu, Kangning Yang, Shiyu Fu, Shuhong Chen, Xinyu Li, and Ivan Marsic. 2018. Hybrid Attention based Multimodal Network for Spoken Language Classification. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2379–2390, Santa Fe, New Mexico, USA. Association for Computational Linguistics. Muzhaffar Hazman, Susan McKeever, and Josephine Griffith. 2023. Meme sentiment analysis enhanced with multimodal spatial encoding and face embedding. In Artificial Intelligence and Cognitive Science, pages 318–331, Cham. Springer Nature Switzerland. Junguang Jiang, Yang Shu, Jianmin Wang, and Mingsheng Long. 2022. Transferability in deep learning: A survey. arXiv preprint, arXiv:2201.05867. Vishal Keswani, Sakshi Singh, Suryansh Agarwal, and Ashutosh Modi. 2020. IITK at SemEval-2020 task 8: Unimodal and bimodal sentiment analysis of Internet memes. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1135–1140, Barcelona (online). International Committee for Computational Linguistics. Douwe Kiela, Hamed Firooz, Aravind Mohan, Vedanuj Goswami, Amanpreet Singh, Pratik Ringshia, et al. 2020. The hateful memes challenge: Detecting hate speech in multimodal memes. Advances in Neural Information Processing Systems, 33:2611–2624. Liisi Laineste and Piret Voolaid. 2017. Laughing across borders: Intertextuality of internet memes. The European Journal of Humour Research, 4(4):26–49. Gwang Gook Lee and Mingwei Shen. 2022. Amazon pars at memotion 2.0 2022: Multi-modal multi-task learning for memotion 2.0 challenge. In De-Factify @ AAAI 2022. First Workshop on Multimodal FactChecking and Hate Speech Detection, CEUR Workshop Proceedings. AAAI. Quinn McNemar. 1947. Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2):153–157. Shreyash Mishra, S Suryavardan, Parth Patwa, Megha Chakraborty, Anku Rani, Aishwarya Reganti, Aman Chadha, Amitava Das, Amit Sheth, Manoj Chinnakotla, Asif Ekbal, and Srijan Kumar. 2023. Memotion 3: Dataset on sentiment and emotion analysis of codemixed hindi-english memes. arXiv preprint, arXiv:2303.09892. Niklas Muennighoff. 2020. Vilio: state-of-the-art visiolinguistic models applied to hateful memes. arXiv preprint arXiv:2012.07788. Thanh Van Nguyen, Nhat Truong Pham, Ngoc Duy Nguyen, Hai Nguyen, Long H. Nguyen, and YongGuk Kim. 2022. Hcilab at memotion 2.0 2022: Analysis of sentiment, emotion and intensity of emotion classes from meme images using single and multi modalities (short paper). In De-Factify @ AAAI 2022. First Workshop on Multimodal Fact-Checking and Hate Speech Detection, CEUR Workshop Proceedings. AAAI. Asaf Nissenbaum and Limor Shifman. 2017. Internet memes as contested cultural capital: The case of 4chan’s /b/ board. New Media & Society, 19(4):483– 501. Parth Patwa, Sathyanarayanan Ramamoorthy, Nethra Gunti, Shreyash Mishra, S Suryavardan, Aishwarya Reganti, et al. 2022. Findings of memotion 2: Sentiment and emotion analysis of memes. In De-Factify @ AAAI 2022. First Workshop on Multimodal FactChecking and Hate Speech Detection, CEUR Workshop Proceedings. AAAI. Kim Ngan Phan, Gueesang Lee, Hyung-Jeong Yang, and Soo-Hyung Kim. 2022. Little flower at memotion 2.0 2022 : Ensemble of multi-modal model using attention mechanism in memotion analysis (short paper). In De-Factify @ AAAI 2022. First Workshop on Multimodal Fact-Checking and Hate Speech Detection, CEUR Workshop Proceedings. AAAI. Jason Phang, Thibault Fevry, and Samuel R. Bowman. ´ 2019. Sentence encoders on stilts: Supplementary training on intermediate labeled-data tasks. arXiv preprint, arXiv:1811.01088. Mohammad Taher Pilehvar and Jose Camacho-Collados. 2019. WiC: the word-in-context dataset for evaluating context-sensitive meaning representations. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 1267–1273, Minneapolis, Minnesota. Association for Computational Linguistics. Clifton Poth, Jonas Pfeiffer, Andreas Ruckl ¨ e, and Iryna ´ Gurevych. 2021. What to pre-train on? Efficient intermediate task selection. 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Innovative Strategies in Meme Sentiment Analysis: The Impact of Unimodal Training

This paper is available on arxiv under CC 4.0 license. Authors: (1) Terence Blésin, Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL) & Center of Quantum Science and Engineering (EPFL); (2) Wil Kao, Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL) & Center of Quantum Science and Engineering (EPFL); (3) Anat Siddharth, Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL) & Center of Quantum Science and Engineering (EPFL); (4) Alaina Attanasio, OxideMEMS lab, Purdue University; (5) Hao Tian, OxideMEMS lab, Purdue University; (6) Sunil A. Bhave, OxideMEMS lab, Purdue University; (7) Tobias J. Kippenberg, Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL) & Center of Quantum Science and Engineering (EPFL). Table of Links Introduction Results A. Physics and design B. Device characterization C. Bidirectional microwave-optical transduction D. Pulsed transduction Discussion Acknowledgments Appendix A: Theory Appendix B: Fabrication process flow Appendix C: Optical characterization Appendix D: Characterization of acoustic resonances Appendix E: Characterization of bidirectional transduction Appendix F: Optimization of optical extraction efficiency ACKNOWLEDGMENTS The authors would like to thank Amirali Arabmoheghi, Nils Johan Engelsen and Junyin Zhang for experimental assistance and fruitful discussions. This work was supported by the Air Force Office of Scientific Research under award no. FA8655-20-1-7009, Swiss National Science Foundation under grant agreement no. 204927, and European Research Council (ERC) under the EU H2020 research and innovation programme, grant agreement no. 835329 (ExCOM-cCEO). This work was further supported by United States Air Force Research Laboratory Award no. FA8750-21-2-0500, as well as United States National Science Foundation’s International Collaboration Supplements in Quantum Information Science and Engineering Research for RAISE-TAQS Award no. 18-39164. A.S. acknowledges support from the European Space Technology Centre with ESA Contract No. 4000135357/21/NL/GLC/my. Samples were fabricated in the Center of MicroNanoTechnology (CMi) at EPFL and Birck Nanotechnology Center at Purdue University. AUTHOR CONTRIBUTIONS T.B. designed the device. R.N.W, A.A. and H.T. fabricated the device. T.B., A.S. and W.K. conducted the experiments. T.B. and W.K. wrote the paper with input from all authors. T.J.K. and S.A.B. supervised the project. [1] K.-L. Lee, B. Sedighi, R. S. Tucker, H. Chow, and P. Vetter, J. Opt. Commun. Netw. 4, A59 (2012). [2] Q. Cheng, M. Bahadori, M. Glick, S. Rumley, and K. Bergman, Optica 5, 1354 (2018). [3] J. I. Cirac, P. Zoller, H. J. Kimble, and H. Mabuchi, Phys. Rev. Lett. 78, 3221 (1997). [4] L.-M. Duan, M. D. Lukin, J. 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Bidirectional Microwave-optical Transduction Based on Integration: Acknowledgments

So far, most of my playing with Generative AI has been on the prompt side, with no real look at the various settings you can tweak in your calls. As I'm still very new to this, I'm trying my best to take things slowly. But every time I open and see the settings on the right, I keep nagging myself to take a deeper look. Google AI Studio You can also see the various settings options in the default code Studio spits out: const generationConfig = {
	temperature: 0.9,
	topK: 1,
	topP: 1,
	maxOutputTokens: 2048,
};

const safetySettings = [
	{ category: HarmCategory.HARM_CATEGORY_HARASSMENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, },
	{ category: HarmCategory.HARM_CATEGORY_HATE_SPEECH,	threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, },
	{ category: HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, },
	{ category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, },
]; I thought today I'd take a look at , as I had a rough idea of what it implied. Temperature, at a high level, refers to how 'varied' a particular generated response can be. As an example, if I were to say, "I like ____", then you could make a list of what the next word would be, rated by how likely it is: temperature very Cats (VERY LIKELY) Star Wars (LIKELY) Books (LIKELY) Vegetables (UNLIKELY) At the highest temperature value, there will be a of variety. At the lowest level, no variety. Now, from what I know, that does mean that every response will be the same. Just very similar. This post, , does a great job explaining temperature (and other settings). lot not "Creatively Deterministic: What are Temperature and Top_P in Generative AI?" While it's relatively easy in AI Studio to adjust the temperature setting you see above, what I really wanted was a tool to help me see multiple results at once. So, I built one. :) Temperature Testing Tool My tool begins with a simple prompt: This is pretty vanilla HTML, so I won't share the code here (I've got a link to everything down below). Upon hitting the button, that's where the magic begins. Here's the JavaScript: // Testing ranges for temperature
const tempRanges = [0, 0.3, 0.6, 1];

// How many times to test per temp.
const perTemp = 2;

let $status, $results;

document.addEventListener('DOMContentLoaded', init, false);
async function init() {
	document.querySelector('#submitBtn').addEventListener('click', handleSubmit, false);
	$status = document.querySelector('#status i');
	$results = document.querySelector('#results');
} I begin with some variable declarations and a listener for . The first two variable sections are the crucial ones. Temperature values go from 0 (focus on only the highest probable response) to 1 (be more creative), and I decided to test four values in that range. DOMContentLoaded For each range in the array of temperatures, I do two tests. My thinking was that two results would be enough to see the variance in one particular temperature value. Carrying on... async function handleSubmit(e) {
	e.preventDefault();
	$results.innerHTML = '';

	let prompt = document.querySelector('#prompt').value.trim();
	if(prompt === '') return;

	/*
	We are going to loop perTemp times for each tempRange. In order to not
	get stopped by Gemini for too many requests, and to provide feedback to the user, 
	I'll report after each tempRange
	*/
	for(temp of tempRanges) {
		$status.innerText = `Getting results for temperature ${temp}.`;
		let promises = [];
		for(let i=0; i<perTemp; i++) {
			promises.push(getResult(prompt, temp));
		}

		let results = await Promise.all(promises);
		let html = `<h2>Temperature ${temp}</h2>`;
		for(let i=0; i < results.length; i++) {
			html += `
<p>
Result #${i+1}:<br/>
${results[i]}
</p>`;
		}
		$results.innerHTML += html;
		console.log(results);
	}

	$status.innerText = ``;
	
}

async function getResult(prompt, temperature) {
	console.log(`Calling getResult with prompt ${prompt} and ${temperature}`);
	let body = {
		prompt, 
		temperature
	};
	let req = await fetch('/api', { method: 'POST', body: JSON.stringify(body)});
	return await req.json();
} In this code, I loop over the range of temperatures and then make my two sample calls. When done, I render it out to the screen. The last function simply passes my prompt and temperature to the backend API. I'll share a screenshot, but it's a wall of text. This is only a small portion: long The backend is a lightweight Node.js server that basically handles outputting my HTML and responding to the request by the client-side JavaScript. Let's take a look at that, specifically the portion handling the Google Gemini call: POST import { GoogleGenerativeAI, HarmCategory, HarmBlockThreshold } from '@google/generative-ai';

const MODEL_NAME = "gemini-pro";
const API_KEY = process.env.GOOGLE_AI_KEY;

const genAI = new GoogleGenerativeAI(API_KEY);
const model = genAI.getGenerativeModel({ model: MODEL_NAME });

async function callGemini(text, temperature) {

	const generationConfig = {
		temperature,
		topK: 1,
		topP: 1,
		maxOutputTokens: 2048,
	};

	const safetySettings = [
		{ category: HarmCategory.HARM_CATEGORY_HARASSMENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, },
		{ category: HarmCategory.HARM_CATEGORY_HATE_SPEECH,	threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, },
		{ category: HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, },
		{ category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, },
	];

	const parts = [
    	{text},
  	];

	const result = await model.generateContent({
		contents: [{ role: "user", parts }],
		generationConfig,
		safetySettings,
	});

	const response = result.response.candidates[0].content.parts[0].text;
	
	return response;
} This is pretty much the exact code spit out by Studio but wrapped into a function where the prompt and temperature can be passed in. This function has error handling, and that absolutely bit me in the butt. I'm going to be taking a look at those errors, and how to handle them, in a future blog post. no So what did I find? Results Here are the results of using the prompt: "Tell me a story about cats." First, temperature 0. Result 1 Once upon a time, in a quaint little town nestled amidst rolling hills, there lived a mischievous cat named Mittens. Mittens was known throughout the neighborhood for her playful antics and her insatiable curiosity. One sunny afternoon, as Mittens was basking in the warmth of the sunbeam that streamed through the window, she noticed a peculiar sound coming from the kitchen. Intrigued, she hopped off the window sill and tiptoed towards the source of the noise. Upon entering the kitchen, Mittens discovered a group of kittens huddled around a bowl of milk. Their tiny paws were eagerly reaching for the sweet liquid, and their eyes sparkled with delight. Mittens, being the adventurous cat she was, couldn't resist joining in on the fun. With a playful leap, Mittens landed gracefully in the midst of the kittens. She purred loudly, her tail swishing back and forth as she rubbed against their soft fur. The kittens, initially startled by the sudden intrusion, soon warmed up to Mittens' friendly presence. Together, they formed a circle around the bowl of milk, their whiskers twitching as they lapped up the delicious treat. Mittens, being the eldest and most experienced cat, took it upon herself to teach the kittens proper table manners. She showed them how to take turns and how to avoid spilling the milk. As the kittens learned and grew, they developed a deep bond with Mittens. They looked up to her as their mentor and protector. Mittens, in turn, cherished her role as the leader of the pack. She spent her days playing with the kittens, teaching them valuable life lessons and keeping them safe from harm. Word of Mittens' extraordinary kindness and wisdom spread throughout the town. People would often bring their cats to her, seeking her advice and guidance. Mittens welcomed each and every cat with open paws, offering them comfort, support, and a sense of belonging. And so, Mittens became known as the "Guardian Cat" of the town. She was loved and respected by all, both humans and cats alike. Her legacy lived on for generations, inspiring countless cats to follow in her paw prints and spread joy and kindness wherever they went. Result 2 Once upon a time, in a quaint little town nestled amidst rolling hills, there lived a mischievous cat named Mittens. Mittens was known throughout the neighborhood for her playful antics and her insatiable curiosity. One sunny afternoon, as Mittens was basking in the warmth of the sunbeam that streamed through the window, she noticed a peculiar sound coming from the kitchen. Intrigued, she hopped off the window sill and tiptoed towards the source of the noise. Upon entering the kitchen, Mittens discovered a group of kittens huddled around a bowl of milk. Their tiny paws were eagerly lapping up the delicious liquid, their whiskers quivering with delight. Mittens, unable to resist the temptation, joined the kittens and began to partake in the feast. As they drank, Mittens couldn't help but notice that one of the kittens was smaller and weaker than the others. It struggled to keep up with its siblings, and its eyes held a look of longing. Mittens, being the compassionate cat that she was, decided to help the little kitten. With a gentle nudge, Mittens pushed the other kittens aside and made room for the weaker one. She then curled her tail around the kitten, providing it with warmth and comfort. The little kitten, grateful for Mittens' kindness, nuzzled against her fur and began to purr softly. As the kittens continued to drink their milk, Mittens couldn't help but feel a sense of fulfillment. She had not only satisfied her own hunger but had also brought joy and comfort to a fellow creature. From that day forward, Mittens became known as the neighborhood's guardian angel. She would often be seen playing with the kittens, teaching them how to climb trees and chase butterflies. She would also bring them food and shelter when they were in need. The kittens, in turn, adored Mittens and would follow her everywhere she went. They would purr and rub against her legs, showing their affection and gratitude. And so, Mittens lived a long and happy life, surrounded by the love and companionship of her feline friends. She taught the town's residents the importance of kindness and compassion, and her legacy lived on long after she was gone. Notice that both start off the same and then diverge. To save on space, I'll skip to temperature 1 next. Result 1 Once upon a time, in a bustling city called Willow Brook, there lived a calico cat named Mittens. Mittens had a reputation for being a fearless explorer, always curious and eager for adventure. One day, Mittens embarked on her biggest expedition yet. She had heard rumors of a secret garden hidden deep within the city park, and she was determined to find it. When nightfall came, Mittens began her adventure, carefully sneaking out of her home and into the park. The park was silent, illuminated only by the soft glow of the moon. As she tiptoed through the winding paths, a faint scent of flowers carried by the wind caught her attention. Mittens followed the scent until she stumbled upon a large tree. Its branches were laden with bountiful blooms, and a gentle breeze sent petals raining down on her. Suddenly, a soft voice whispered, "Welcome, little traveler." Mittens looked around, her eyes widening in astonishment. Sitting on a branch was a beautiful cat; its fur shimmered like the night sky. "I am Esmerelda," the cat said, "and you are Mittens, the brave calico." Mittens was amazed. She had heard stories about Esmerelda, a magical cat said to hold the secret to unlocking the hidden garden. "Yes, Mittens," Esmerelda continued, "you have found the Enchanted Garden. But to enter, you must pass three challenges." Without hesitation, Mittens agreed. Her first challenge was to find a golden key hidden within the roots of an oak tree. With her sharp claws and determined spirit, Mittens discovered the key, its surface glowing brightly. Next, Esmerelda asked Mittens to gather dewdrops from the heart of a moonflower blossom. As Mittens gracefully leaped and climbed the tall stems, she carefully collected the sparkling dew in a tiny seashell. Finally, Mittens' last challenge was to sing a song that would make the trees sway and the flowers bloom. As Mittens lifted her voice, her melodious' tune enchanted the garden, which sprang to life with vibrant colors and dazzling lights. Esmeralda smiled, "Well done, little traveler. You have passed the challenges." With a gentle paw, Esmerelda touched the large oak tree, causing it to slowly open like a door, revealing an awe-inspiring paradise. Inside the Enchanted Garden, Mittens found lush meadows, sparkling fountains, and exotic creatures playing among the trees. It was a place of wonder and joy as if every storybook she had ever heard had come true. Mittens spent the entire night exploring the magical realm, amazed by its beauty. As dawn broke, she turned to Esmerelda and said, " Thank you for sharing this incredible place with me. Esmerelda purred softly. "You are welcome, Mittens. As long as you believe in magic, the garden will always be here for you to explore." From that day forward, Mittens became the guardian of the Enchanted Garden, a place where she could always find solace, friendship, and a sense of belonging among the natural beauty of Willow Brook. And so, the legend of the brave calico and the Enchanting Garden lived on, brought to life of the belief in magic and the wonders that can be found when one dares to explore beyond the ordinary. Result 2 Once upon a time, in a small and charming town called Willow Creek, nestled amidst rolling hills and blooming meadows, there lived two extraordinary cats. One was a sleek and graceful Siamese named Luna, whose shimmering white fur and piercing blue eyes radiated elegance and mystique. Her every movement exuded nimbleness, gliding through the streets of Willow Creek with an air of regal composure. Meet the second cat, a tabby by the name of Max, a playful and mischievous soul adorned with a coat of orange and black stripes. His sparkling green eyes twinkled with a mischievous glint; ears always perked, ever alert to the adventures that awaited him. His playful antics had become a legend among the townspeople, who were often greeted by his friendly antics and joyful meows. The companionship between Luna and Max was a sight to behold. They were inseparable, roaming the cobblestone streets together, their playful pursuits leading them to alleyways and secret paths known only to them. Their friendship was a true testament to the unwavering spirit and unbreakable bond between cats. During the day, they would bask lazily in the warm sunlight that bathed the town square, absorbing the melody of children playing and the laughter of friends sharing stories. At night, under the velvet sky adorned with shimmering stars, they would chase elusive fireflies and embark on daring expeditions, exploring the town's hidden nooks and crannies, their soft paw steps barely disturbing the tranquil silence. Many a local came to rely on the presence of Luna and Max, knowing that their playful chases and affectionate purrs brought an unexplainable joy and warmth to the heart. The elderly, feeling isolated, found solace in their presence, witnessing a simple yet profound beauty in their interactions. Children were captivated by their antics, watching in delight as they climbed trees or chased each other through the flowerbeds. One day, a traveling circus arrived in Willow Creek, filled with fanfare and vibrant colors. Luna and Max, captivated by the excitement, couldn't resist exploring the wonders this circus held. As they ventured into the largest tent, they were greeted with the mesmerising spectacle of trained cats, performing incredible feats of agility and balance. Inspired by their newfound passion, Luna and Max made a daring decision - they ran away to join the circus! They honed their skills tirelessly, practicing their balancing acts and performing stunning leaps. Their dedication and unwavering friendship caught the attention of the ringmaster, who recognized their talent and potential. Finally, the moment arrived when Luna and Max took center stage, their hearts pounding with excitement and anticipation. The audience, holding their breath in anticipation, witnessed an extraordinary performance, a mesmerizing ballet of agility and grace. Luna's elegant poise and Max's playful energy combined to create a symphony of motion that left the spectators awe-inspired. News of Luna and Max's incredible talents spread like wildfire, and they became stars of the circus, sharing their joy and laughter with audiences of all ages. Their unwavering friendship remained the heart of their performances, a symbol of the magical bond between cats that touched the hearts of all who witnessed their amazing journey. And so, Luna and Max, once ordinary cats roaming the streets of Willow Creek, found their destined path in the spotlight of the circus ring, leaving behind a legacy of a friendship that defied the ordinary and inspired the extraordinary in others. As you can tell, even if you only skimmed it, these are much more varied. I found having all these variations on screen at once, from the same prompt, a easy way to help me understand the impact of temperature. If you want to try this yourself, you can grab the bits here: real https://github.com/cfjedimaster/ai-testingzone/tree/main/temp_tester Download the code, the required bits, and set an environment variable for your Google API key. Run the script ( ) and it will open up a web server on port 3000. Lastly, just open that up with your browser. npm i node script.js As always, let me know what you think. I've got some ideas for other tools like this as a way of learning generative AI! Also published . here

Testing Generative AI Temperature Settings with Some Cat Stories

This paper is under CC 4.0 license. available on arxiv Authors: (1) Shreyash Mishra has an equal contribution from IIIT Sri City, India; (2) S Suryavardan has an equal contribution from IIIT Sri City, India; (3) Megha Chakraborty, University of South Carolina, USA; (4) Parth Patwa, UCLA, USA; (5) Anku Rani, University of South Carolina, USA; (6) Aman Chadha, work does not relate to a position at Amazon from Stanford University, USA, or Amazon AI, USA; (7) Aishwarya Reganti, CMU, USA; (8) Amitava Das, University of South Carolina, USA; (9) Amit Sheth, University of South Carolina, USA; (10) Manoj Chinnakotla, Microsoft, USA; (11) Asif Ekbal, IIT Patna, India; (12) Srijan Kumar, Georgia Tech, USA. Table of Links Abstract & Introduction Related Work Task Details Participating systems Results Conclusion and Future Work and References 6. Conclusion and Future Work In this paper, we summarize the approaches used by the participants for the Memotion 3 task and analyze the results. Due to the multi-modal nature of the dataset, all teams use a pre-trained image and text embedding models. However, each team presents a novel model pipeline. The highest scores achieved in Task A, Task B and Task C of Memotion 3.0 are 34.41%, 79.77% and 59.82% respectively, which shows there is significant room for improvement. On analysis of the results and the mis-classified examples on the test set, we find that "Sarcasm" and "Humour" are difficult to identify, especially in code-mixed memes. While we address Hind-English code-mixed memes in this paper, future work could include exploring other languages/language pairs. A unified baseline model to analyze memes in multiple languages could also be an interesting possibility. References [1] R. Dawkins, The selfish gene, Granada Publishing Lim, 1979. [2] A. Marwick, Memes, Contexts 12 (2013) 12–13. [3] N. Akhther, Internet memes as form of cultural discourse: A rhetorical analysis on facebook, 2018. doi:10.31234/osf.io/sx6t7. [4] S. 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Overview of Memotion 3: Sentiment & Emotion
Analysis of Codemixed Hinglish - Conclusion

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