📜 [專欄新文章] Uniswap v3 Features Explained in Depth
✍️ 田少谷 Shao
📥 歡迎投稿: https://medium.com/taipei-ethereum-meetup #徵技術分享文 #使用心得 #教學文 #medium
Once again the game-changing DEX 🦄 👑
Image source: https://uniswap.org/blog/uniswap-v3/
Outline
0. Intro1. Uniswap & AMM recap2. Ticks 3. Concentrated liquidity4. Range orders: reversible limit orders5. Impacts of v36. Conclusion
0. Intro
The announcement of Uniswap v3 is no doubt one of the most exciting news in the DeFi place recently 🔥🔥🔥
While most have talked about the impact v3 can potentially bring on the market, seldom explain the delicate implementation techniques to realize all those amazing features, such as concentrated liquidity, limit-order-like range orders, etc.
Since I’ve covered Uniswap v1 & v2 (if you happen to know Mandarin, here are v1 & v2), there’s no reason for me to not cover v3 as well ✅
Thus, this article aims to guide readers through Uniswap v3, based on their official whitepaper and examples made on the announcement page. However, one needs not to be an engineer, as not many codes are involved, nor a math major, as the math involved is definitely taught in your high school, to fully understand the following content 😊😊😊
If you really make it through but still don’t get shxt, feedbacks are welcomed! 🙏
There should be another article focusing on the codebase, so stay tuned and let’s get started with some background noise!
1. Uniswap & AMM recap
Before diving in, we have to first recap the uniqueness of Uniswap and compare it to traditional order book exchanges.
Uniswap v1 & v2 are a kind of AMMs (automated market marker) that follow the constant product equation x * y = k, with x & y stand for the amount of two tokens X and Y in a pool and k as a constant.
Comparing to order book exchanges, AMMs, such as the previous versions of Uniswap, offer quite a distinct user experience:
AMMs have pricing functions that offer the price for the two tokens, which make their users always price takers, while users of order book exchanges can be both makers or takers.
Uniswap as well as most AMMs have infinite liquidity¹, while order book exchanges don’t. The liquidity of Uniswap v1 & v2 is provided throughout the price range [0,∞]².
Uniswap as well as most AMMs have price slippage³ and it’s due to the pricing function, while there isn’t always price slippage on order book exchanges as long as an order is fulfilled within one tick.
In an order book, each price (whether in green or red) is a tick. Image source: https://ftx.com/trade/BTC-PERP
¹ though the price gets worse over time; AMM of constant sum such as mStable does not have infinite liquidity
² the range is in fact [-∞,∞], while a price in most cases won’t be negative
³ AMM of constant sum does not have price slippage
2. Tick
The whole innovation of Uniswap v3 starts from ticks.
For those unfamiliar with what is a tick:
Source: https://www.investopedia.com/terms/t/tick.asp
By slicing the price range [0,∞] into numerous granular ticks, trading on v3 is highly similar to trading on order book exchanges, with only three differences:
The price range of each tick is predefined by the system instead of being proposed by users.
Trades that happen within a tick still follows the pricing function of the AMM, while the equation has to be updated once the price crosses the tick.
Orders can be executed with any price within the price range, instead of being fulfilled at the same one price on order book exchanges.
With the tick design, Uniswap v3 possesses most of the merits of both AMM and an order book exchange! 💯💯💯
So, how is the price range of a tick decided?
This question is actually somewhat related to the tick explanation above: the minimum tick size for stocks trading above 1$ is one cent.
The underlying meaning of a tick size traditionally being one cent is that one cent (1% of 1$) is the basis point of price changes between ticks, ex: 1.02 — 1.01 = 0.1.
Uniswap v3 employs a similar idea: compared to the previous/next price, the price change should always be 0.01% = 1 basis point.
However, notice the difference is that in the traditional basis point, the price change is defined with subtraction, while here in Uniswap it’s division.
This is how price ranges of ticks are decided⁴:
Image source: https://uniswap.org/whitepaper-v3.pdf
With the above equation, the tick/price range can be recorded in the index form [i, i+1], instead of some crazy numbers such as 1.0001¹⁰⁰ = 1.0100496621.
As each price is the multiplication of 1.0001 of the previous price, the price change is always 1.0001 — 1 = 0.0001 = 0.01%.
For example, when i=1, p(1) = 1.0001; when i=2, p(2) = 1.00020001.
p(2) / p(1) = 1.00020001 / 1.0001 = 1.0001
See the connection between the traditional basis point 1 cent (=1% of 1$) and Uniswap v3’s basis point 0.01%?
Image source: https://tenor.com/view/coin-master-cool-gif-19748052
But sir, are prices really granular enough? There are many shitcoins with prices less than 0.000001$. Will such prices be covered as well?
Price range: max & min
To know if an extremely small price is covered or not, we have to figure out the max & min price range of v3 by looking into the spec: there is a int24 tick state variable in UniswapV3Pool.sol.
Image source: https://uniswap.org/whitepaper-v3.pdf
The reason for a signed integer int instead of an uint is that negative power represents prices less than 1 but greater than 0.
24 bits can cover the range between 1.0001 ^ (2²³ — 1) and 1.0001 ^ -(2)²³. Even Google cannot calculate such numbers, so allow me to offer smaller values to have a rough idea of the whole price range:
1.0001 ^ (2¹⁸) = 242,214,459,604.341
1.0001 ^ -(2¹⁷) = 0.000002031888943
I think it’s safe to say that with a int24 the range can cover > 99.99% of the prices of all assets in the universe 👌
⁴ For implementation concern, however, a square root is added to both sides of the equation.
How about finding out which tick does a price belong to?
Tick index from price
The answer to this question is rather easy, as we know that p(i) = 1.0001^i, simply takes a log with base 1.0001 on both sides of the equation⁴:
Image source: https://www.codecogs.com/latex/eqneditor.php
Let’s try this out, say we wanna find out the tick index of 1000000.
Image source: https://ncalculators.com/number-conversion/log-logarithm-calculator.htm
Now, 1.0001¹³⁸¹⁶² = 999,998.678087146. Voila!
⁵ This formula is also slightly modified to fit the real implementation usage.
3. Concentrated liquidity
Now that we know how ticks and price ranges are decided, let’s talk about how orders are executed in a tick, what is concentrated liquidity and how it enables v3 to compete with stablecoin-specialized DEXs (decentralized exchange), such as Curve, by improving the capital efficiency.
Concentrated liquidity means LPs (liquidity providers) can provide liquidity to any price range/tick at their wish, which causes the liquidity to be imbalanced in ticks.
As each tick has a different liquidity depth, the corresponding pricing function x * y = k also won’t be the same!
Each tick has its own liquidity depth. Image source: https://uniswap.org/blog/uniswap-v3/
Mmm… examples are always helpful for abstract descriptions 😂
Say the original pricing function is 100(x) * 1000(y) = 100000(k), with the price of X token 1000 / 100 = 10 and we’re now in the price range [9.08, 11.08].
If the liquidity of the price range [11.08, 13.08] is the same as [9.08, 11.08], we don’t have to modify the pricing function if the price goes from 10 to 11.08, which is the boundary between two ticks.
The price of X is 1052.63 / 95 = 11.08 when the equation is 1052.63 * 95 = 100000.
However, if the liquidity of the price range [11.08, 13.08] is two times that of the current range [9.08, 11.08], balances of x and y should be doubled, which makes the equation become 2105.26 * 220 = 400000, which is (1052.63 * 2) * (110 * 2) = (100000 * 2 * 2).
We can observe the following two points from the above example:
Trades always follow the pricing function x * y = k, while once the price crosses the current price range/tick, the liquidity/equation has to be updated.
√(x * y) = √k = L is how we represent the liquidity, as I say the liquidity of x * y = 400000 is two times the liquidity of x * y = 100000, as √(400000 / 100000) = 2.
What’s more, compared to liquidity on v1 & v2 is always spread across [0,∞], liquidity on v3 can be concentrated within certain price ranges and thus results in higher capital efficiency from traders’ swapping fees!
Let’s say if I provide liquidity in the range [1200, 2800], the capital efficiency will then be 4.24x higher than v2 with the range [0,∞] 😮😮😮 There’s a capital efficiency comparison calculator, make sure to try it out!
Image source: https://uniswap.org/blog/uniswap-v3/
It’s worth noticing that the concept of concentrated liquidity was proposed and already implemented by Kyper, prior to Uniswap, which is called Automated Price Reserve in their case.⁵
⁶ Thanks to Yenwen Feng for the information.
4. Range orders: reversible limit orders
As explained in the above section, LPs of v3 can provide liquidity to any price range/tick at their wish. Depending on the current price and the targeted price range, there are three scenarios:
current price < the targeted price range
current price > the targeted price range
current price belongs to the targeted price range
The first two scenarios are called range orders. They have unique characteristics and are essentially fee-earning reversible limit orders, which will be explained later.
The last case is the exact same liquidity providing mechanism as the previous versions: LPs provide liquidity in both tokens of the same value (= amount * price).
There’s also an identical product to the case: grid trading, a very powerful investment tool for a time of consolidation. Dunno what’s grid trading? Check out Binance’s explanation on this, as this topic won’t be covered!
In fact, LPs of Uniswap v1 & v2 are grid trading with a range of [0,∞] and the entry price as the baseline.
Range orders
To understand range orders, we’d have to first revisit how price is discovered on Uniswap with the equation x * y = k, for x & y stand for the amount of two tokens X and Y and k as a constant.
The price of X compared to Y is y / x, which means how many Y one can get for 1 unit of X, and vice versa the price of Y compared to X is x / y.
For the price of X to go up, y has to increase and x decrease.
With this pricing mechanism in mind, it’s example time!
Say an LP plans to place liquidity in the price range [15.625, 17.313], higher than the current price of X 10, when 100(x) * 1000(y) = 100000(k).
The price of X is 1250 / 80 = 15.625 when the equation is 80 * 1250 = 100000.
The price of X is 1315.789 / 76 = 17.313 when the equation is 76 * 1315.789 = 100000.
If now the price of X reaches 15.625, the only way for the price of X to go even higher is to further increase y and decrease x, which means exchanging a certain amount of X for Y.
Thus, to provide liquidity in the range [15.625, 17.313], an LP needs only to prepare 80 — 76 = 4 of X. If the price exceeds 17.313, all 4 X of the LP is swapped into 1315.789 — 1250 = 65.798 Y, and then the LP has nothing more to do with the pool, as his/her liquidity is drained.
What if the price stays in the range? It’s exactly what LPs would love to see, as they can earn swapping fees for all transactions in the range! Also, the balance of X will swing between [76, 80] and the balance of Y between [1250, 1315.789].
This might not be obvious, but the example above shows an interesting insight: if the liquidity of one token is provided, only when the token becomes more valuable will it be exchanged for the less valuable one.
…wut? 🤔
Remember that if 4 X is provided within [15.625, 17.313], only when the price of X goes up from 15.625 to 17.313 is 4 X gradually swapped into Y, the less valuable one!
What if the price of X drops back immediately after reaching 17.313? As X becomes less valuable, others are going to exchange Y for X.
The below image illustrates the scenario of DAI/USDC pair with a price range of [1.001, 1.002] well: the pool is always composed entirely of one token on both sides of the tick, while in the middle 1.001499⁶ is of both tokens.
Image source: https://uniswap.org/blog/uniswap-v3/
Similarly, to provide liquidity in a price range < current price, an LP has to prepare a certain amount of Y for others to exchange Y for X within the range.
To wrap up such an interesting feature, we know that:
Only one token is required for range orders.
Only when the current price is within the range of the range order can LP earn trading fees. This is the main reason why most people believe LPs of v3 have to monitor the price more actively to maximize their income, which also means that LPs of v3 have become arbitrageurs 🤯
I will be discussing more the impacts of v3 in 5. Impacts of v3.
⁷ 1.001499988 = √(1.0001 * 1.0002) is the geometric mean of 1.0001 and 1.0002. The implication is that the geometric mean of two prices is the average execution price within the range of the two prices.
Reversible limit orders
As the example in the last section demonstrates, if there is 4 X in range [15.625, 17.313], the 4 X will be completely converted into 65.798 Y when the price goes over 17.313.
We all know that a price can stay in a wide range such as [10, 11] for quite some time, while it’s unlikely so in a narrow range such as [15.625, 15.626].
Thus, if an LP provides liquidity in [15.625, 15.626], we can expect that once the price of X goes over 15.625 and immediately also 15.626, and does not drop back, all X are then forever converted into Y.
The concept of having a targeted price and the order will be executed after the price is crossed is exactly the concept of limit orders! The only difference is that if the range of a range order is not narrow enough, it’s highly possible that the conversion of tokens will be reverted once the price falls back to the range.
As price ranges follow the equation p(i) = 1.0001 ^ i, the range can be quite narrow and a range order can thus effectively serve as a limit order:
When i = 27490, 1.0001²⁷⁴⁹⁰ = 15.6248.⁸
When i = 27491, 1.0001²⁷⁴⁹¹ = 15.6264.⁸
A range of 0.0016 is not THAT narrow but can certainly satisfy most limit order use cases!
⁸ As mentioned previously in note #4, there is a square root in the equation of the price and index, thus the numbers here are for explantion only.
5. Impacts of v3
Higher capital efficiency, LPs become arbitrageurs… as v3 has made tons of radical changes, I’d like to summarize my personal takes of the impacts of v3:
Higher capital efficiency makes one of the most frequently considered indices in DeFi: TVL, total value locked, becomes less meaningful, as 1$ on Uniswap v3 might have the same effect as 100$ or even 2000$ on v2.
The ease of spot exchanging between spot exchanges used to be a huge advantage of spot markets over derivative markets. As LPs will take up the role of arbitrageurs and arbitraging is more likely to happen on v3 itself other than between DEXs, this gap is narrowed … to what extent? No idea though.
LP strategies and the aggregation of NFT of Uniswap v3 liquidity token are becoming the blue ocean for new DeFi startups: see Visor and Lixir. In fact, this might be the turning point for both DeFi and NFT: the two main reasons of blockchain going mainstream now come to the alignment of interest: solving the $$ problem 😏😏😏
In the right venue, which means a place where transaction fees are low enough, such as Optimism, we might see Algo trading firms coming in to share the market of designing LP strategies on Uniswap v3, as I believe Algo trading is way stronger than on-chain strategies or DAO voting to add liquidity that sort of thing.
After reading this article by Parsec.finance: The Dex to Rule Them All, I cannot help but wonder: maybe there is going to be centralized crypto exchanges adopting v3’s approach. The reason is that since orders of LPs in the same tick are executed pro-rata, the endless front-running speeding-competition issue in the Algo trading world, to some degree, is… solved? 🤔
Anyway, personal opinions can be biased and seriously wrong 🙈 I’m merely throwing out a sprat to catch a whale. Having a different voice? Leave your comment down below!
6. Conclusion
That was kinda tough, isn’t it? Glad you make it through here 🥂🥂🥂
There are actually many more details and also a huge section of Oracle yet to be covered. However, since this article is more about features and targeting normal DeFi users, I’ll leave those to the next one; hope there is one 😅
If you have any doubt or find any mistake, please feel free to reach out to me and I’d try to reply AFAP!
Stay tuned and in the meantime let’s wait and see how Uniswap v3 is again pioneering the innovation of DeFi 🌟
Uniswap v3 Features Explained in Depth was originally published in Taipei Ethereum Meetup on Medium, where people are continuing the conversation by highlighting and responding to this story.
👏 歡迎轉載分享鼓掌
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[挑戰Excel Google Shit]得唔得架?人地萬億美金市值喎。
彭博原文:Spreadsheet Maker Airtable Taps Funds at $2.5 Billion Value(https://bityl.co/3YWw)
TLDR:介面幾靚,收費又好似唔貴。但,辦公室軟件,好難挑戰巨頭喎,仲要做埋同佢地差不多嘅嘢。
1. 呢檔新Startup(*),最成功係個名。AirTable,易記,又唔會諗起其他嘢,但又唔係唔啦更。正如Bloomgerg所講,Spread Sheet,「哦,即係挑戰Excel 同Google Shit」
2. 其實話新都唔係好新,2012年成立。另外,都玩到D輪融資,最新集資近2億美金,估值25億美金,唔係蚊型嘢了。創辦人話唔會賣盤呀下,至少而家唔會(never say never),1000億機會輕而易舉喎(計乜先?)
3. 得唔得架?之前都有啦,EditGrid嘛,香港嘢添,好似話仲早過Google,我有用過,還好.「但而家都係用返Excel同Google」.咁今次呢舊又乜家伙?
4. 利申:只係快望過,當然冇用過,亦冇好細心咁去睇。趕住訓。其實我之前聽都未聽過間公司。當然可能只係我問題,我見都有唔少教學,中文嘅都有(https://bityl.co/3YVr)
5. 呢篇中文簡介反而幾好,至少有個「Vision」.入面講咗句嘢,唔知係咪公司原本講,(甚至可能根本條友有份),總之就係:1985年,已經係Word Excel同Powerpoint,而家2020年啦喎。中途Google有搞下Google Shit Google Dog之類,但本質都係一樣。應該改變下,云云
6. (不過說實話,本人呢啲腦盲,應該去到1995年先接觸Word,之前同學屋企玩過WordPerfect,至於試算表嘛,反而90前已經IBM玩過,但唔記得叫乜名)
7. Bloomberg篇嘢,叫佢做Spread Sheet,唔知公司會唔會覺得唔恰當。篇報導將公司產品定位為「冇咁強大但易用嘅Excel」
8. 但我見公司網頁反而講自己係Spread Sheet+Database,我望落亦都覺得似係。
9. 第一印象,介面幾靚嘅。見佢啲template,亦唔似同Excel好相似,反而係integrate 更多其他嘢,特別係相同埋片。好似,幫到啲一大堆資料但好零散嘅友,例如會幫到我寫文?或者公司做product system呀,CRM呀乜鬼,其實可能都有用。我見過啲唔少系統,都係介面唔多靚仔,亦有點兒複雜嘅
10. 唔好睇少呢樣嘢,都未得閒寫,但早排我問過下人,點解Zoom跑出?講最早又唔係,早多錢又唔係。根據專家朋友講,似乎就係因為夠易用,介面簡單靚仔,廢老都識用。好重要的!
11. 唔知個比喻啱唔啱,但你睇真係去到智能電話大盛後,你老母甚至你阿爺嗰啲先會變埋「上網」。你畀部電腦佢,佢係唔會玩的。但拎部電話佢就識同你發長輩圖。當然可以拎住周圍用亦係原因,Network effect佢地其他朋友都用亦係原因
12. 講到Network effect,我諗又係呢類公司嘅死症。拿我唔係專家,但你見MS Office雄霸多年,當然亦因為人人用,你都要用。你整個file對家開唔到嘅,點玩?掉轉都係。就當你有兼容性(個個都會做啦),但你公司一用,又要啲員工全部識用喎。固然AirTable之類實會幫你培訓,而家有埋Zoom之類更好。但,你都知多數員工都係好似我呢類嘅腦盲,「學咗咁多年先識VLookup先識VBA寫Macro你而家又要我學第樣嘢」,好煩的
13. 我見佢AirTable都有啲大公司客,很重要。但個出路會唔會都係個人,或者中小企?見啲收費似乎唔貴,應該有競爭力。
14. 其他?唔知。但直覺好難玩,又係嗰個問題,大公司當道,抄你又得,搶你啲人又得。你話你做啲同佢完全唔同嘅嘢都話,但你同佢做差不多嘅嘢,扮公室軟件,得唔得架?
15. 呢,你見Slack,應該已經算係相當成功。但,「本人用都冇用過」「用MS Teams我都覺得麻撚煩」,「點解唔Whatsapp講或打電話講?」。固然唔好咁中二病,你冇用過唔等於冇人用,但,用家數字爭好遠下話。Zoom就真係殺出一條血路。
16. 拿,本人嘅tech 撚朋友評曰:「簡單來講,佢個媽劇係邊?就係只剩唔多願意科水俾錢既Startup或中小企,企業巿場實在難以同一條龍及深受IT高層信賴既Microsoft Teams搶。咁大個餅你淨係咬得幾啖,仲要啲豆沙餡係哂人地果邊。筆者想科水俾Slack時,公司IT、Finance都輪流質疑「點解唔用返Teams?」,而當你科水時,你就會發現科水跟本買唔到幾多,「好似有少少貴」,你最愛既功能跟本唔科水都夠用。然後⋯⋯Github而家Integrate埋Teams了,點搞?又,唔係你以為Microsoft而買Github?呢啲咪「仙甩治」。」
17. (而再講一次,本人連用Teams都覺得麻撚煩,「點解唔用Whatsapp」)
18. 另一tech 撚朋友評曰:「我個人經驗,工作溝通通常都只係文字對話,或者開會。呢類 app 除非提供到一啲其他 instant messenger 一定提供唔到嘅功能,否則啲人用用下就會自然地用返一般用開的 instant messenger嘅 group chat。因為方便,唔駛開多樣。」
19. 我不負責任咁講句:唔係咁易架葉師傅。技術背景嘅,當然係留意隻嘢有幾勁有幾多功能,但女人嘅嘢,絶世好Bra話頭,唔使你轉幾十個 pose架!你睇電飯煲(**),就一個大掣,你阿麻都識用,幾咁撚簡單!呢啲就Design thinking啦!你睇微波爐?其實你有用過乜功能?我用嘅功能就只係較時間,然後叮。「我好多時連大中小火都唔搞」「唔夠熱咪再叮耐啲」
20. 另外當然,就係大公司點都以本傷人,綑綁銷售又好,價格戰又好,利用現有嘅優勢去打你又好(Microsoft玩咗幾廿年啦),點會咁易畀你搶灘?
21. 咁但不過,潑冷水之類後,又要講,成件事係冇矛盾的。係呀,好撚難架。但正係難先有機會發嘛,如果個個做到,就唔會有得發啦。你做到一間Zoom突圍成功,你睇袁征副身家幾咁勁?
22. AirTable嘛,好在仲係唔係太大,雖則都話20萬個公司客了(嘩),但25億美金估值唔算係咩好誇張,「王維基咁上下」。相反,Slack嗰啲,已經都幾成熟,玩咗咁多年,市都上埋,140億美金市值,但依然冇錢賺,點玩落去?
23. 不過唔緊要,沒有最泡,只有更泡。Slack今年啲表現都還不錯的。早兩日上嗰隻Snowflake先CSL挑戰你三觀,啲估值令我懷疑人生。一度成900億美金市值,而家跌返啲都仲有600億美金。我就唔知點計數了,但900億美金市值,講緊在標普500指數都排70—但公司收入?得4億,低過任何一間標普500指數成份股公司。
24. 4億收入撐900億市值?亞馬遜1997年上市,玩到2011年先有800億市值—但當時收入係400億
25. 呀,又賣廣告了,Snowflake嘅嘢,其實Patreon有講,仲有大把其他嘢(https://bit.ly/31QmYj7)
26. 真的,有機會我都想試用下呢個AirTable—但你睇到問題了,「老人家邊有時間慢慢學」,但,後生有時間嘅,又唔肯科水喎。「所以你見手遊都係男兒當入樽,因為啲廢老有錢畀」
(*)有舊Startup?有的,Palantir成立咗17年,都仲扮係Start up,或者想人當佢係,或者有人當佢係
(**)唔係做愛姿勢嚟的,唔係講緊乞兒煲飯OK?雖則我到而家都唔知乞兒點煲飯,更加唔明外國嘅乞兒煲唔煲飯?煲Risotto?
———————————————————
Ivan Patreon 狼耳街華人,一星期至少三篇港美市場評點,一個月一舊水唔使,開張一個月已500人訂!仲有兩篇免費試睇:https://bit.ly/31QmYj7
——————————————————————————
[收費短片第九擊]美股科技股是否泡沫爆破?價值投資之選
課程資訊:https://homebloggerhk.com/course_detail/?code=CC009
內容:
*美股急跌點算好
*科技股係咪泡沫爆煲?
*有乜價值投資之選?
本星期內特惠售價: $80
課程編號:CC009
觀看期限:首次播放後一星期及限每影片4次
客服whatsapp: 63832145
另外想買返第八擊(美國總統大選股票部署)都仲可以:https://bityl.co/3NPn
system design教學 在 藍諾Eleanor Jiang Youtube 的精選貼文
一年一度的 9月 Apple 發表會就要來了,每年最令人期待的就是 iPhone 到底會變出什麼新功能來。那其實近幾年可以看到 Apple 放很多心思在強化 iPhone 上的錄影功能,從一顆鏡頭到三顆鏡頭,有超廣角模式,更有 4K 60FPS 的錄製格式等等。
那頻果對於攝影功能的強化應該是因為看上了社群媒體與影音時代的崛起,讓更多大大小小的創作者能夠在手機上得到強大的錄影畫質!
今年 iPhone 13 就流出了更強大的攝影規格,我們今天就來聊聊這些規格在一台小小的手機上的開發難度,以及這些規格能夠預期拍出怎樣的畫面,更重要的是它是不是真的能夠媲美,甚至是取代一些攝影器材。
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0:00 開頭
1:14 iPhone 13 外觀變化
3:38 iPhone 13 像素/畫素
4:56 iPhone 13 人像錄影功能
5:43 iPhone 13 Pro Res
7:04 結尾
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藍諾攝影課程 : https://bit.ly/3utQoQg
藍諾剪接課程: https://www.pressplay.cc/link/DE905742
《藍諾導演攝影實戰課:12 步拍出故事感》🎉
繼剪輯課程後,推出全新的 #動態攝影課程!
這堂課不僅教你穩扎穩打的攝影基本功
還會教學導演實戰祕技,從實作和案例剖析示範給你
課程內容包含:
🎬 前置作業|器材、參數設定、拍攝腳本、流程規劃等
🎬 拍攝當下|運鏡、收音、打光、實作等
🎬 拍攝當下|星宇航空紀錄片的案例剖析、接案注意事項等
初次拍攝最該在意的那些事,細細地教給你 https://bit.ly/3utQoQg
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音樂來源 Artlist (無版權問題):https://reurl.cc/j878om
素材庫Artgrid (無版權問題): https://reurl.cc/2r0reE
- - - - - - -
你可能對這部也有興趣 ?
🎬導演日常:
1. 星宇航空首航幕後花絮大公開|導演VLOG
https://reurl.cc/XWL8nj
2. 給台灣學生的一段話 | 藍諾演講
https://reurl.cc/83qamR
3. 跟著星宇去德國接飛機! 導演Vlog
https://reurl.cc/2rW9qX
🔧教學影片:
1. 我們如何幫保時捷拍廣告 - 5個實用撇步|How we filmed for Porsche - 5 TIPS
https://reurl.cc/W3Dm2x
2. 拿著相機亂晃就對了!超實用轉場教學
https://reurl.cc/83qagd
3. 6種必學空拍機運鏡方法|簡單上手技巧
https://reurl.cc/ZGXkmQ
📦開箱評測:
1. 搶先幫大家評測A7S3!
https://reurl.cc/gWZAd4
2. 星宇航空給了我一個神秘箱子
https://reurl.cc/Gme61D
3. 實力派精品降噪耳機 Bose 700 評測
https://reurl.cc/MARQem
👨👩👧👦關於專一團隊:
1. 專一不怕做大夢 | Too Focused is not afraid to dream BIG
https://reurl.cc/xGlmR5
2. 有夢最美 - 全新百坪工作室攝影棚開箱!
https://reurl.cc/MARQpm
3. 4K! 繫好安全帶 極限旅遊作品集 - 專一影音工作室
https://reurl.cc/5rMxjG
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🙌認識妳真好,藍諾幫你打折:
DJI 產品優惠:https://click.dji.com/ANAsFogbf2FCg5Q...
Peak Design 產品優惠:https://www.peakdesign.com/?acc=540
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📞想聯絡我/跟我合作嗎?
FB : https://www.facebook.com/eleanorjiang...
Instagram : https://www.instagram.com/eleanor.dir...
Email : Eleanor@toofocused.productions
郵政信箱:中壢郵政26-20號信箱 (藍諾收)
P.O Box:26-20 Chungli Post Office, Taoyuan City, Taiwan (R.O.C)
![post-title](https://i.ytimg.com/vi/h8n0DXgocaU/hqdefault.jpg)
system design教學 在 飛馬電腦 FLYHORSE HK Youtube 的最讚貼文
Sorry 今日遲左出片.......... QQ
今日黎同大家講下點樣可以提升細機箱既散熱表現
片尾仲有講到少少關於 Corsair SF750 Platinum 最近既災情
有觀眾提醒我地 Corsair SF750 Platinum 最近既災情,香港最近發售既批次應該都過左 19年第50週既, 所以新買唔洗擔心, 之前買落都唔洗太驚, 畢竟有保養而且果個Defect 唔會燒埋你電腦入面既其他零件
有興趣既記住睇到最尾啦
[和你砌 Build Guide] ITX 都可以好簡單 - 逐步逐步一齊砌 Fractal Design Node 202: https://youtu.be/Ir6GtXeihXs
新出AMD Ryzen 3 3100! 普通人都上到 4.5G !? ft. Samson @TechiCardia (CC中文字幕):
https://youtu.be/PGXoB2kM4Jw
Corsair ML120 評測: https://thermalbench.com/2016/07/12/corsair-ml120-pro-120-mm-fan
Reddit /r/sffpc: https://www.reddit.com/r/sffpc/
Node 202 膠袋 / 紙皮改造: https://post.smzdm.com/p/aexm4edk/
極客灣 Node 202 ITX: https://www.youtube.com/watch?v=wK0PEXoC4YE (4:45 - 5:15)
================
快D加入我地最新既討論區?https://www.facebook.com/groups/pegasushk.group/
▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄
- Whatsapp 砌機查詢: https://wa.me/85295408014
- Website / 網店 : https://shop.pegasus.hk
- Facebook: https://fb.com/HongKongPegasus/
- YouTube: https://youtube.com/c/PegasusComputer
- Instagram: @pegasus.hk
飛馬電腦 - 唔止砌機咁簡單
Pegasus Computer - More than just a System Builder.
![post-title](https://i.ytimg.com/vi/rOtw4idiBhE/hqdefault.jpg?sqp=-oaymwEbCKgBEF5IVfKriqkDDggBFQAAiEIYAXABwAEG&rs=AOn4CLDXybeu2TAwduMsqJIxxljrJYnP8Q)
system design教學 在 飛馬電腦 FLYHORSE HK Youtube 的最佳解答
[26-May-2020 Update]
有觀眾提醒我地 Corsair SF750 Platinum 最近既災情,香港最近發售既批次應該都過左 19年第50週既, 所以新買唔洗擔心, 之前買落都唔洗太驚, 畢竟有保養而且果個Defect 唔會燒埋你電腦入面既其他零件
拖左咁耐,終於有機會教大家砌 ITX 既時候有咩要留意既!
今日就同大家講下點樣 PICK 零件啦!
雖然每隻 ITX 機箱既限制都有唔同, 但我相信睇完條片既你都會略知一二, 知道點做自己既功課~
Windows 10 安裝教學: https://youtu.be/ilX9w0hAld0
Parts List:
Link 版: https://bit.ly/2SX9oa1
圖片版: https://i.imgur.com/DGmNpC0.png
中央處理器 ► AMD Ryzen 7 3700X 8核16線程 Box (含散熱風扇)
主機板 ► ASRock 華擎 Fatal1ty B450 Gaming-ITX/ac ITX 主機板
RAM (記憶體) ► Corsair VENGEANCE LPX DDR4 3600 MHz 16GB (8GB X 2) (CMK16GX4M2D3600C18)
SSD (固態硬碟) ► Samsung 三星 PM981a 256GB 3D TLC M.2 NVMe PCIe 3.0 x4 SSD
顯示卡
► MSI 微星 RTX 2070 VENTUS GP 顯示卡
電源 ► Corsair SF750 Platinum 750W 80Plus Platinum 鉑金牌 全模組 火牛 (7年保)
機箱 ► Fractal Design Node 202 - Black
風冷散熱器 ► CRYORIG C7 G LOW PROFILE 風冷散熱器
================
快D加入我地最新既討論區?https://www.facebook.com/groups/pegasushk.group/
▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄
- Whatsapp 砌機查詢: https://wa.me/85295408014
- Website / 網店 : https://shop.pegasus.hk
- Facebook: https://fb.com/HongKongPegasus/
- YouTube: https://youtube.com/c/PegasusComputer
- Instagram: @pegasus.hk
飛馬電腦 - 唔止砌機咁簡單
Pegasus Computer - More than just a System Builder.
特別感謝 Felton Distribution, ASRock, Corsair, Fractal Design 贊助! ❤️️❤️️❤️️
![post-title](https://i.ytimg.com/vi/Ir6GtXeihXs/hqdefault.jpg?sqp=-oaymwEbCKgBEF5IVfKriqkDDggBFQAAiEIYAXABwAEG&rs=AOn4CLB1n7i8nXLXnztfTV9Cn-a5CclcVw)
system design教學 在 全端開發人員天梯- 使用Adobe XD 建立design system 的影片 ... 的推薦與評價
如何建構好用的Design System,儼然已是企業UI/UX設計師、PM、App程式開發者都必須認識的基本功,這系列翻譯教學影片相信能讓台灣地區的UI/UX用戶在接觸Adobe XD之前, ... ... <看更多>
system design教學 在 Angular UI:Clarity Design System | Jonny Huang 的學習筆記 的推薦與評價
安裝教學可參閱https://vmware.github.io/clarity/get-started。 安裝圖示:Clarity Icons. 安裝指令如下: npm install clarity-icons --save 官方指南是 ... ... <看更多>
system design教學 在 donnemartin/system-design-primer · GitHub - 系統設計入門 的推薦與評價
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards. - system-design-primer/README-zh-TW.md at master ... ... <看更多>