分類
區塊鏈

博弈遊戲產業瞄準區塊鍊技術

區塊鏈的崛起吸引了各行業目光,除金融科技、物流以及醫療等產業外,博弈遊戲業也是這波區塊鏈熱潮
的擁護者。像是博弈重鎮馬爾他,已著手讓加密貨幣在線上賭場合法化,並研擬策略與配套措施。
根據市場數據分析師的預測,2020年時博弈遊戲產業的收益將會成長至600億美元。這也代表著符合博弈法規的高品質
博弈娛樂數量,將隨著線上博弈合法化普及與網路技術的進步不斷成長。而成長的關鍵要素之一,就是區塊鏈技術的應
用。玩家的資金存放的媒介,將獲得更安全、透明的保障。
目前,最受博弈遊戲產業關注與歡迎的,是利用區塊鏈技術衍生的虛擬貨幣作為解決方案,包括成為遊戲的主要支付系
統,甚至是法定貨幣的替代選項。博弈遊戲產業看中的是虛擬貨幣可讓用戶三名的優勢,且無須提交相關文件或者建立
帳戶,省略繁琐步驟流程及龐大手續費。虛擬貨幣也讓線上博弈更易於推震,降低新玩家進入門檻,同時規避只適用於
法定貨幣的博弈法律規範。
再者,導入區塊鏈
技術與智慧合約將加密虛擬技術提升至另一層次,可有助線上賭場平台透明化,公平性得到背書。線
上賭場可以獲得認證的公平、公正、公開遊戲環境,去吸引更多玩家前來參與遊戲。此外,利用區塊鏈技術的特性,讓
任何人都能成為線上賭場的一員。部分的比特幣賭場,更已讓使用者資助線上賭場並從莊家優勢中獲利。
區塊鏈技術應用於線上博弈產業,和過去傳統線上賭場的最大差別在於,所有流程都被攤在陽光下参與者都看得一清二
楚。換句話說,過去許多線上賭場的數據會被刻意隱藏或部分遮掩,包括:奖金、遊戲結果和支出等不受監督。但線上
賭場應用區塊鏈技術後,將會開啟線上賭場的全新境界,因為它無須中間人驗證交易。公開透明的系統,也更能被玩家
所信任。

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分類
區塊鏈

區塊鍊能為遊戲產業改變什麼?

隨著區塊鏈技術應用的興起,不少新創公司也紛紛以區塊鏈為根基,試圖開發新的商機。最早應用區塊鏈
的大部份為金融產業,近幾年,遊戲產業也開始投入此應用。
隨著區塊鏈技術應用的興起,不少新創公司也紛紛以區塊鏈為根基,試圖開發新的商機。最早應用區塊鏈的大部份為金
融產業,近幾年,遊戲產業也開始投入此應用。新創公司GAME PROTOCOLE有意透過區塊鏈平台來確保玩家的資訊
安全,並消除競爭者間的歧視與不公平的優勢。
由於過往的遊戲管理模式是采用集中式管理系統,玩家的遊戲帳號、密碼、銀行帳號及相關個資均由遊戲公司储存保
管,往往會導致商業詐欺或個資被竊等行為。集中式管理的缺點就是容易遭駭客攻擊,這也是遊戲產業長期頭痛的問
由於區塊鏈真有去中心化、不可篡改、加密保護的特性, GAME PROTOCOL意圖利用這項技術的優勢來為玩家創造一
個透明化、安全存取的資料平台,而該平台還可供遊戲開發者創造並推廣分散式自動化遊戲。
基於智慧合約的分散式自動化遊戲,其程式碼開放給所有遊戲玩家兼用,以確認遊戲中的程式錯誤或詐騙行為,具透明
化且非常可靠。此外,分散式自動化遊戲讓玩家的個資免於受到集中式機構的控制,也不會在未經授權的情況下使用。

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分類
區塊鏈

2018區塊鍊高峰會於在上海完美落幕

2018區塊鏈高峰會(BTS)於8月25日在上海圓滿結束,此次高峰會重點著重在全球區塊鏈技術的發展和
未來趨勢,同時致力於推動創新產業及高端產業的應用。

由Boolan.com策劃舉辦2018區塊鏈高峰會(Blockchain Technology Summit BTS),於8月25日在上海圓滿結束。
此次高峰會重點著重在全球區塊鏈技術的發展和未來趨勢,同時致力於推動創新產業及高端產業的應用。
此次峰會與會者包括技術專家、商業領袖、風險投資人及各界精英等都聚集於此,針對區塊鏈特徵和技術應用等發展,
此計到
進一步商討及交流未來發展的趨勢及影響。
2018年BTS的重點包括主題演講、小組討論、創新項目展覽及相關產業的文化展覽,吸引來自華為、騰訊、阿里巴巴、
中興、360、爱立信及惠普等500強企業,與金融相關的PayPal及渣打銀行也都參與此次峰會。
區塊鏈技術對未來的發展是一個全新的突破,主題演講中就有超過30位來自各國的主講者,針對區塊鏈生態系統發表演
說,包括基礎設施、產業升級、安全性問題、零售產業發展、人工智慧的結合及金融的
應用等領域分享研究成果和觀

此外,PPTV創始人和Bluerun Ventures 合顆彩人姚欣共同發表了一個專題演講,名為「價值回歸」,探討有關區塊鏈
的投資風險。

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分類
市場分析

2019博弈市場大餅 達5110億美元

博彩市場在全球合法化的腳步不曾停過,日漸成熟的博彩娛樂已成最受矚目的潛力產業之一。根據GBGC
(Global Betting and Gaming Consultants )研究指出,2015年至2019年博彩產業持續穩定成長,並預
估2019年整體市值將達5.110億美元規模。該如何把握博彩產業潛力並發揮實力,即是眾廠商的最大課
.
博弈產業近幾年在全球掀起了一波熱潮,形成了「賭博性娛樂事業」的產業型態,隨著產業逐漸成熟下也帶動產值逐年
成長,根據GBGC Global Gaming Forecast研究報告指出,2015年開始至2019年,博弈產業務穩定維持年複合成長
3%增長的速度,並預估2019年博弈產業整體市值將可達到5.110億美元。
亞洲占比逾43%
根據該份研究報告指出,2010年時全球博弈產業產值約3,860億美元,歐美國家約佔據了三分之二,然而到了2014年
全球博弈產業產值已經到了4,520億元,其中成長幅度最大的區域來自於亞洲,年均複合成長率高過7%,高於整體產業
的4%,同時亞洲市場佔整體博弈產業市佔率超過43%,正式取代美國成為全球博弈市場的霸主。
若以單一地區觀察,目前澳門新加坡整體博弈產業的營收規模旨超過美國賭城拉斯維加斯,該區儼然對於全球博弈產
業發展具有影響力,並預期未來幾年高度成長區域將由原先的亞洲區域國家,增加為新興國家與亞太地區,至2019年
年複合成長率分別為8%及4%。
ULT A Gant
澳門世界最大
澳門博弈產業目前仍是世界最大的博弈中心,博弈產業年收入是美國賭城拉斯維加斯的七倍,惟近幾年在中國經濟放
緩、反貪腐等政策驅使下,使得澳門博彩業大受打擊,衝擊國內經濟,隨著澳門被中央納入一帶一路戰略之內,推動經
濟轉型適度多元,降低博弈產業比重下,根據澳門博彩監察協調局
資料顯示,2016年博彩總收入為2,232億澳門元,較
2015年下降3.2%,創6年低點,同時澳門政府也開始降低對未來博弈收入的預期。
新加坡急追新秀
新加坡目前則有兩座大型賭場,包括馬來西亞財團投資聖淘沙名勝世界,美國拉斯維加斯的金沙集團投資營運的濱海灣
金沙,預期新加坡將可取代南韓及澳洲,成為亞太地區規模僅次於澳門的博弈市場。
菲律賓積極搶攻
近年亞太區域陸續新建賭場,其中以菲律賓博弈商機最受關注,近幾年隨著政府積極發展博弈事業,成立博弈特區
並且規畫相關交通設施與相關配套措施,吸引相關產業進駐與商業投資,根據PACGOR報告指出,2012年到2016年菲
律賓整體博弈收入由700億披索成長超過1,500億披索(約當30億美元),4~5年整體營收成長超過一倍,MAYBANK
預估菲律賓龐大的博弈事業到2020年收入将突破70億美元。

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分類
市場分析

線上博弈人才正夯 來看看在歐美你值多少錢

近年線上博弈遊戲產業快速發展,對相關專業技術人才需求也大幅增加。在博弈產業相關職位工作的你,
想知道你的一技之長若在歐美職場能獲得多少報酬嗎?不妨看看這篇報導吧!
根據調查顯示,線上博弈業務正如火如地發展,而此一趨勢和手機遊戲技術的進步不謀而合。所以對包括設計師、開發
人員、項目經理,甚至是有經驗的營銷專家和產品經理等不同職務人才,都有強大需求。以下就來看看線上博奕產業
不同職位的人才,在歐美職場價值多少呢?
|||
自動化和分析人才激增
對於業務分析師人才需求更勝以往,根據薪資調查數據指出,分析職位負責人目前在全球平均薪水為73,000英鎊;商業
分析師平均薪資則是46,000英鎊。和直布羅陀和英國一樣,馬爾他共和國是分析行業興起的主要受益者。
分析人才的崛起不僅如此,現在有此一專長的人才,是所有線上博弈公司中最不可或缺的職務。
自動化也改變體育交易
型態,對量化分析師也有很大需求,平均薪資接近57,000英鎊。
數以千計的薪資單都證明線上博弈產業的興起,此外,體育博弈產品對技術依賴性隨著市場所需交易速度增加,這也逐
漸改變線上體育博弈的性質。這種自動化交易的轉變,特別是在英國、愛爾蘭、直布羅陀和馬爾他等體育博弈中心最為
亞洲線上博弈產業的崛起是另一大趨勢,特別是馬尼拉的職缺也隨著整個行業蓬勃發展,越來越受到全球人才的瞩目。
揭密八大司法管轄區特定職位平均薪資
根據Bettinglobs在2015年6月一項薪資調查,考察了全球8個司法管轄區,包括:英國、愛爾蘭、歐洲大陸、東歐、馬
爾他、直布羅陀、曼島和亞洲等處,並檢視了行政、技術、商業、市場營銷、交易、財務、分析、營運、產品和法律等
10個專業技術領域的職位。
ULTS Garmin
以下則介紹幾個職稱平均薪資供參考,一探博弈產業的徵才標準。像是首席營銷長的平均薪資約在124,000英鎊;地區
經理平均薪資可獲得58.571英鎊;掌控一間公司技術領域的T總監,平均薪資約在99.438英鎊,而設計師的平均薪資
約在36.250英鎊之譜,而T產品經理平均薪資則落在47.813英鎊左右。
其他像是營運總監平均的94.125英鎊、產品總監的112.375英鎊、產品經理的51,063关鎊。透過bettingjobs的網站,
即可查詢各區域、各領域、各項職缺的薪資數據,為博弈行業提供一個参考基準,也有利於博弈公司在進行人才招募時
可以利用Bettinglobs的調查成果,進一步設定戰略定和趨勢。
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分類
市場分析

你知道為什麼iLottery是產業的未來嗎

彩票,是全球博弈業成長最重要的領域。但與其他博弈種類相比,它的技術和線上參與能力仍似黑暗時
代。然而,英國特許彩票遊戲LOTTO團隊在2018年ICE展中,為全球客戶展示iLottery的未來。

目前,彩票佔全球博弈產業的30%,預計2020年將更上一層樓,來到6.350億美元規模。但在網路提供機會方面,彩票
仍處於落後態勢。這也意味許多有利可圖的彩票營運商因為當地法律框架,面臨滅絕風險。因為大部分國家彩票皆由政
府控制,且因互聯網和警察等因素,彩票在網路銷售和推廣方面進展緩慢。而此情況在美國更為明顯,不信任的線上投
注意味著,包括百萬富翁和強力球等超高奖金彩票無法在線上玩。
***** GATING
當然,彩票轉型線上形式已出現一些變化。來自英國的Camelot 2003年起,便開始提供線上銷售,2010年以來要從
鮮為人知的小眾市場,轉變成數十億英鎊的商業帝國。iLottery為原本僅限在自己國家的彩票遊戲,開啟了全新的型
態。事實上,彩票的本質更適合線上遊戲,線上營運商可透過使用隨機亂數產生器(RNG)
進行官方或內部拍笑,提供每週、每日和即時遊戲的混合體。因為彩票遊戲傾向於以保險模式為基礎,所以在遊戲上
可以更靈活,如:提供累積獎金、多彩票組合遊戲,甚至是適合某個市場奖品等特色。

iLottery另一個優勢,在於它完美地適合線上遊戲。現在英國55%以上的玩家使用手持移動裝置進行遊戲投注,這個數
字在非洲等新興市場更成長到85%甚至更高,大多數的玩家使用Android手機作為上網接入單一來源。這也新,
iLottery需要完全適應所有平台,應用程式是好的但依賴下載者,若網速或手機處理速度過慢則無法正常遊戲。目前現
在一些领先的iLottery品牌,仍使用十年前的後端技術,即便目前仍能應付玩家需求,但隨著日新月異的科技創新,最
終將更新速度變慢、易受到安全威脅等而導致其過時。
在移動優先遊戲世界,速度和
靈活性是最重要的,更小和
更有活力的推動者將主宰iLottery發展,使用Sas雲端技術,
為國家操作彩票和私人營運商提供解决方案:ilottery的革命才正要開始,隨著非洲、亞洲和Latam市場正逐步開放海
外彩票,提供鉅額奖金和優惠賠,2018年將會是iLottery產業起飛的一年,不僅如此,看看美國賓夕法尼亞州正準備
提供州級彩票的線上銷售服務,全球成長率有望上看16%,隨著越來越多市場開放,成長空間只可能更高。

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分類
市場分析

展望全球博弈產業 未來五年趨勢分析

全球博弈產業崛起有目共睹,原因除了越來越多國家將其視為增加國家收入的財源外。線上和移動博弈技
術的進步,也讓更多人體驗到線上博弈的便利與娛樂性。以下是博弈娛樂在2023年前的產業展望。
H

博亞娛樂產業現下已成為美國、英國和許多西歐國家的主要商業活動,在澳大利亞也相當受到歡迎。在這些國家受歡迎
的博弈遊戲包括:不同類型的撲克、賭場遊戲、體育博弈和彩票等。然而,博弈產業成長最快速的部分,是線上遊戲和
移動應用程式。原因有二,一是工資增加,自由支配金錢變多,即有餘力参與博弈遊戲;二是許多國家將其合法化,玩
家可以在法律的保護下,透過互聯網隨時隨地體驗博弈娛樂。研究人員指出,未來5年全球博弈市場收入將突破5, 250億
美元,每年成長幅度超過4%。
值得注意的,還有壹擬處境和虛擬雪境的技術。上述兩項技術已成功應用於遊戲技術和電競市場,專家預計在2023年
時將會更為普遍流行。藉由這兩項技術的成熟發展,博弈玩家亦能獲得到更好的遊戲體驗。無論是線上賭場或體育博弈
方面,3D的賭場體驗將會出現於市場,讓玩家視覺和聽覺等感官體驗再次升級。
或許不少人認為,美國、歐洲和澳大利亞的博弈市場將漸超過度飽和的狀態。但有不少專家指出,這些市場仍會以每年
增加3%收入的幅度成長,像是線上賭場能即時為線上博弈玩家提供服務,讓玩家能在觀看體養手的同時進行投注。
另外,傳統的直博弈遊戲仍有大批粉絲擁護,無論是線上或在實體賭場。而體育博弈、養馬、賽狗的投注市場也還在
成長,這些投注項目都是博弈市場成長的動力。
除了傳統西方市場外,亞洲博弈市場的崛起也不容小鼠。除了澳門、香港和海南外,日本也已啟動合法博弈特區計畫。
另外在東南亞,包括束埔寨、韓國和越南等,都如火如荼推動博奕合法化。此外,南美市場也是博弈產業的另一大亮
點。雖然目前僅有巴西設有合法的賭場,但未來南美洲的博弈市場將出現爆炸性的成長。因為已有不少南美國家對體育
博弈和線上博奕合法化躍躍欲試,這也吸引了國際博弈營運商摩拳擦掌準備大幹一場。
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分類
人工智慧

撲克玩家的地獄 ? AI強勢來襲 !

人工智慧當道,已成為市場顯學。舉凡任何與網路相關的產業,無不積極投入與開發AI的技術,其中博奕
遊戲產業也深受影響。匹茲堡超級計算中心的研究團隊以AI與四位世界級職業撲克選手展開人腦與電腦的
對決,並在競賽中赢得了170萬美元!本文為您詳細解析,A是如何擊敗四位世界頂尖撲克選手!
slavina Trocco hands of heads-ub. no-lim
“That was anticlimactic,” Jason Les said with a smirk, getting up from his seat. Unlike nearly everyone else in
Pittsburgh’s Rivers Casino, Les had just played his last few hands against an artificially intelligent opponent on
a computer screen. After his fellow players – Daniel McAulay next to him and Jimmy Chou and Dong Kim in an
office upstairs — eventually did the same, they started to commiserate. The consensus: That AI was one hell of a
player.
The four of them had spent the last 20 days playing 120,000 hands of heads-up, no-limit Texas Hold’em
against an artificial intelligence called Libratus created by researchers at Carnegie Mellon University. At stake: a
total pot of $200,000 and, on some level, the pride of the human race. A similar scene had unfolded two years
prior when Les, Kim and two other players decisively laid the smackdown on another Al called Claudico. The
players hoped to put on a repeat performance, finish up the event January 30th, and ride the rush of
endorphins until they got home and resumed their usual games of online poker.
The fight wasn’t even close. All told, Libratus won by more than 1.7 million (virtual) dollars, and — just like that
— the second Brains vs. Al competition came to a close. To understand what these players were up against and
what makes Libratus work, let’s go back to a time before all hope of victory was lost.
Men vs. machine
For the four men playing against Libratus, victory didn’t always seem impossible. The AI was in the lead from
the get-go, building an impressive streak of wins for the first three days. Then came the counter-attack. Day
four saw the gap narrow $40,000, and a string of successes on day six brought the humans to within $50,000 of
the lead.
“In the start here, we lost the first day,” Les explained. “Whatever — not a big deal. And then we were losing,
but then we fought back up to nearly equal. We were feeling really confident! We know how to play, we’re
going to be able to win.”
On the night after the sixth day of competition, the humans did what they did every other night: sift through
the Libratus hand data provided to them by CMU in hopes of devising a winning strategy. With spirits high after
a big day, they decided on a seemingly crazy strategy: three-betting on every hand that came along.
Three-betting, for the uninitiated, is poker slang for reraising on a hand. When you decide to play a hand in a
situation like this, paying the blinds is the first bet. If you’re confident in your cards, you raise — that’s the
second bet. Generally, when you reraise — the third bet-you’re pretty sure you’ve got the exchange in the
bag. Based on their understanding of Libratus’ play style, the humans thought they could knock if off balance
by playing this aggressively for a while. It backfired.
“We applied this crazy strategy we would never do online,” Kim explained. “Basically, we reraised all of our
hands. All of us went in, like, ‘Let’ s just try this, let’ s go crazy.”
“We had a reason to believe that specific size-three-bet was going to work well against the AI,” Les added.
“We just fired off all day doing that.”
Les and Kim concede that they just got unlucky, too, but either way: Libratus was unfazed by their plan and
started demolishing them. “It just kept improving every single day, and we started going backwards and
backwards,” Les said. In fairness, the humans weren’t playing with their usual setups. The four competitors
are almost exclusively online poker pros, and when duking it out at virtual tables at home, they always have
their HUDs handy. These heads-up displays are filled with stats and probabilities that help online players make
the best moves. Their absence here in Pittsburgh was noticeable.
“Without the HUD, without the numbers, you don’t know if you’re being paranoid or not,” Daniel McAulay
said, leaning back in his chair after winning a hand. “Is it folding less? We were never sure. We would always
say the same thing to each other. Just play it out until we get home and we’d see the sample of hands and
then we’ll change the plan. But that cost us a lot of money. A lot of money.”
Those losses would only continue to mount.
Building the beast
One of the men responsible for the players’ anguish can usually be found in his ninth-floor office, overlooking
Carnegie Mellon University’s snow-flecked quad. Professor Tuomas Sandholm might live a second life as a
startup entrepreneur, but he has spent years trying to perfect the algorithms that make Libratus such a potent
player. It wasn’t out of any particular love for the game — Sandholm admits he’s no poker pro — but he was
fascinated by the thought of complex computer systems that make decisions better than we can. That fixation
led him to co-create Claudico (the earlier AI that the humans trounced) with PHD student Noam Brown, and it
led the two of them to try again with Libratus.
To think of Libratus as just a poker-playing champ is to sorely underestimate it. Instead, Sandholm says, it’ sa
more general set of algorithms meant to tackle any information-imperfect situation. Confused? Don’t be.
Broadly speaking, the term just describes any situation in which two or more parties don’t have the same
information. Something unlike, say, chess, where the entirety of the game’ s world is splayed out on the board
in front of players. Those players can figure out exactly what’s going on and, assuming they have decent
memories, draw on their understanding of the events that led them there. This is a perfect information game.
No-limit Texas Hold’em is different. You don’t know which cards your opponent has, your opponent
doesn’t know which cards you have, and those minutes playing a hand to its conclusion are spent trying to
make the smartest moves possible with a shortage of intel. And unlike the limit variant, where there’s a cap on
how big your bets can be, no-limit gives you the freedom to bet whatever you want. There’s so much
information a person — or an AI — can infer about an opponent’ s strategy based on their bets that it sno
wonder researchers have been trying to crack the game.
“Heads-up, no-limit Texas Hold’ em poker has emerged as the leading benchmark for measuring the quality
of these general purpose algorithms in the AI community,” Sandholm told me.
With that in mind, Sandholm and Brown jointly built Libratus from three major components. The first is an
algorithm that devises overall strategies based on Nash equilibria. In other words, Libratus spent a total of 15
million computing hours chewing on the rules of the game before the competition, finding rational ways to act
when both players are making the best possible moves with the information available. Thanks to a new logic
model developed by the two researchers to minimize Libratus’ “regret,” the AI could solve larger
abstractions of the game faster and with higher accuracy than before.
The second is what Sandholm calls the end-game solver. This is the part that players actually faced during their
20 days of combat. Unsurprisingly, too, this is where Sandholm says most innovative breakthroughs have
happened. Essentially, this allowed Libratus to cook up an approach based on the first two cards it was dealt,
and modify that approach based on its opponent’ s actions and the river and flop that are dealt. Sandholm
says Libratus was also designed to keep tabs on how safe its options are. Let’s say a human player screws up
and loses $372. That money is viewed as a gift of sorts, so the AI can freely lose up to $372 and still remain
ahead.
ULTTE Garming
“That gives us more flexibility for optimizing our strategies while still being safe,” Sandholm explained.
We’ II get to the last key component a little later. In any case, the sheer number of complex calculations meant
Libratus couldn’t run on the desktop in Sandholm’ s office. If nothing else, the human players can take solace
in the fact that it took a supercomputer and millions of computing hours to beat them. If you thought Gowas
tough to wrap your head around, consider the complexity of no-limit Texas Hold’em: When you’re dealt into
a game, the hands you’re dealt and the communal cards that appear are one possibility of 10^160.
“That’s one followed by 160 zeroes,” said Sandholm. “That’s more than the number of atoms in the
universe. You cannot just brute-force your way through it.” Still, it takes some degree of brute force to build as
close to optimal a strategy as possible. That’s where “Bridges” comes in.
If Libratus is the brain of the operation, Bridges — a supercomputer made of hundreds of nodes in the
basement of the Pittsburgh Supercomputing Center – is most definitely the brawn.
“Libratus is running on about 600 nodes at Bridges, out of 846 total compute nodes,” said Nick Nystrom,
senior director of research at the Pittsburgh Supercomputing Center. Most of those 800+ nodes have two
CPUs, each with 28 computing cores and 128GB of RAM. Forty-eight of those nodes have two state-of-the-art
GPUs, and still others were loaded with even more power: NVIDIA’ s Tesla-series K80 and P100 GPUs.
༧.༠༠
There’s more: 42 of those nodes have 3TB of RAM each, and a very special four nodes have a whopping 12TB
of RAM. That’s some serious firepower, but all those nodes were ingeniously woven together to maximize
data bandwidth and minimize latency. It’s just as well, considering the amount of data involved: Libratus was
using up to 2.6 petabytes of storage during the competition.
When not being used to best humans at card games, Bridges was being used for around 650 projects by more
than 2,500 people. Think of Bridges as a supercomputer for hire: Researchers from around the country are using
it to gain insight into arcane subjects like genomics, genome sequence assemblies and other kinds of machine-
learning.
The beauty of Bridges, according to Nystrom, is that those researchers don’t need to be supercomputer buffs.
“It’ sa very cloud-like model letting people who are not programmers, not computer scientists, not
supercomputer users make use of a supercomputer without necessarily even knowing it.” That’ s what
happened with Libratus, and everything seemed to be working perfectly.
ULTS 2 Garmin
GATING
Game theory
After the humans’ gutsy attack plan failed, Libratus spent the rest of the competition inflating its virtual
winnings. When the game lurched into its third week, the AI was up by a cool $750,000. Victory was assured, but
the humans were feeling worn out. When I chatted with Kim and Les in their hotel bar after the penultimate
day’s play, the mood was understandably somber.
“Yesterday, I think, I played really bad,” Kim said, rubbing his eyes. “I was pretty upset, and I made a lot of
big mistakes. I was pretty frustrated. Today, I cut that deficit in half, but it’s still probably unlike for me to
win.” At this point, with so little time left and such a large gap to close, their plan was to blitz through the
remaining hands and complete the task in front of them.
For these world-class players, beating Libratus had gone from being a real possibility to a pipe dream in just a
matter of days. It was obvious that the AI was getting better at the game over time, sometimes by leaps and
bounds that left Les, Kim, McAulay and Chou flummoxed. It wasn’t long before the pet theories began to
surface. Some thought Libratus might have been playing completely differently against each of them, and
others suspected the AI was adapting to their play styles while they were playing. They were wrong.
As it turned out, they weren’t the only ones looking back at the past day’ s events to concoct a game plan for
the days to come. Every night, after the players had retreated to their hotel rooms to strategize, the basement
of the Supercomputing Center continued to thrum. Libratus was busy. Many of us watching the events unfold
assumed the AI was spending its compute cycles figuring out ways to counter the players’ individual play
styles and fight back, but Professor Sandholm was quick to rebut that idea. Libratus isn’t designed to find
better ways to attack its opponents; it’ s designed to constantly fortify its defenses. Remember those major
Libratus components I mentioned? This is the last, and perhaps most important, one.
“All the time in the background, the algorithm looks at what holes the opponents have found in our strategy
and how often they have played those,” Sandholm told me. “It will prioritize the holes and then compute
better strategies for those parts, and we have a way of automatically gluing those fixes into the base strategy.”
If the humans leaned on a particular strategy — like their constant three-bets — Libratus could theoretically
take some big losses. The reason those attacks never ended in sustained victory is because Libratus was quietly
patching those holes by using the supercomputer in the background. The Great Wall of Libratus was only one
reason the AI managed to pull so far ahead. Sandholm refers to Libratus as a “balanced” player that uses
randomized actions to remain inscrutable to human competitors. More interesting, though, is how good
Libratus was at finding rare edge cases in which seemingly bad moves were actually excellent ones.
“It plays these weird bet sizes that are typically considered really bad moves,” Sandholm explained. These
include tiny underbets, like 10 percent of the pot, or huge overbets, like 20 times the pot. Donk betting, limping
— all sorts of strategies that are, according to the poker books and folk wisdom, bad strategies.” To the
players’ shock and dismay, those “bad strategies” worked all too well.
Poker and beyond
On the afternoon of January 30th, Libratus officially won the second Brains vs AI competition. The final margin
of victory: $1,766,250. Each of the players divvied up their $200,000 spoils (Dong kim lost the least amount of
money to Libratus, earning about $75,000 for his efforts), fielded questions from reporters and eventually left to
decompress. Not much had gone their way over the past 20 days, but they just might have contributed to a
more thoughtful, Al-driven future without even realizing it.
Through Libratus, Sandholm had proved algorithms could make better, more-nuanced decisions than humans
in one specific realm. But remember: Libratus and systems like it are general-purpose intelligences, and
Sandholm sees plenty of potential applications. As an entrepreneur and negotiation buff, he’ s enthusiastic
about algorithms like Libratus being used for bargaining and auctions.
“When the FCC auctions spectrum licenses, they sell tens of billions of dollars of spectrum per auction, yet
nobody knows even one rational way of bidding,” he said. “Wouldn’t it be nice if you had some AI
support?”
But there are bigger problems to tackle – ones that could affect all of us more directly. Sandholm pointed to
developments in cybersecurity, military settings and finance. And, of course, there’s medicine.
“In a new project, we’re steering evolution and biological adaptation to battle viral and bacterial infections,”
he said. “Think of the infection as the opponent and you’re taking sequential actions and measurements just
like in a game.” Sandholm also pointed out that such algorithms could even be used to more helpfully
manage diseases like cancer, both by optimizing the use of existing treatment methods and maybe even
developing new ones.
Jason, Dong, Daniel and Jimmy might have lost this prolonged poker showdown, but what Sandholm, Brown
and their contemporaries have learned in the process could lead to some big wins for humanity.

分類
歐美訊息篇

直至羅陀,靠線上博弈經濟拼上DOP全球第四 !

全球博彩產業線上化已成為市場顯學,而提到線上博奕發展最蓬勃的國家,不能不提到直布羅陀!據悉,
線上博彩產業對直布羅陀GDP貢獻超過整體的四分之一,且產值與人力需求持續攀升中。這個面積只有約
6平方公里的英屬領土,憑藉發達的海運及吸金力十足的博彩觀光產業,GDP高居世界第四!
直布羅陀,一個才7平方公里小小的英國海外屬地,GDP去年7.9%,人均國內生產總值達到280萬台幣,全球第四,
除了發達的海運以及觀光,靠的是發展區域經濟,其中線上博彩貢獻GDP高達四分之一,在全球市場占比超過六成,相
當龐大。
這裡靠近西班牙邊界,彙集許多線上遊戲以及博奕公司,在直布羅陀10個人當中,就有一個人從事相關產業,尤其是線
上博彩,占全球市場高達六成。
線上博彩產業每年對直布羅陀的GDP,貢獻超過四分之一,重要性持續計,約有3500人從事相關產業,占整體勞工
13%,超過一半以上,來自西班牙以及歐盟各國,但隨著脫歐風險增加,公司在招募人力上感到憂慮。
作為全球最大規模的彩券公司之-Lottoland,客戶遍及歐洲及亞洲,每年產值高達3億歐元,註冊地就在直布羅陀。
原文章來源:
線上博彩的天堂!這裡每年線上博彩貢獻GDP的四分之一!

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分類
歐美訊息篇

這幾款老虎機帶你重返古埃及

古埃及的神秘文明一直是娛樂產業的靈感來源,近幾年,線上博弈產業也跳上了樂隊花車跟上主流似乎基
於古埃神話與歷史的線上博弈遊戲將再次回歸。
古埃及的神秘文明一直是娛樂產業的靈感來源,近幾年,線上博弈產業也跳上了樂隊花車跟上主流。遊戲開發商多年來
創造許多以埃及為主題的老虎機,似乎基於古埃神話與歷史的線上博弈遊戲將再次回歸。對埃及神話和歷史充滿興趣的
玩家,以下幾款老虎機高定不能錯過。
Push Gaming拉神的烈焰(Blaze of Ra)
Push Gaming是一家起步稍晚的遊戲開發商,但很快就成為業界公認的品牌。日前才發表幾款熱門的老虎機,拉神的
烈焰就是其中之一。 Blaze of Ra是一款以埃及為主題的老虎機,讓玩家深入古埃及沙漠中神秘的金字塔。遊戲中可看見
熟悉的符號,如阿努比斯、芭絲特、荷鲁斯、聖甲多蟲和生命之符,此外在免費旋轉回合中,百搭全屏會固定鎖定在演
1、3及5上,因此保證會獲得不少派彩。
ULTI GENTE
Play nGO的埃及遺產(Legacy of Egypt)
Legacy of Egypt主打讓玩家在遊戲中體驗沿著尼羅河昇華的神聖魔法和神秘主義。玩家的目標就是透過30種賠付線組
合以獲得派彩:其符號包括埃及艷后、法老王、阿努比斯、芭絲特、貝克及荷鲁斯·聖甲蟲。
透過三個金字塔的符號可觸發免費旋轉回合,進入免費旋轉回合前,會先啟動神之轉盤以決定免費旋轉的次數,可
獲得20次,令人興奮的是,每旋轉一次,派彩的倍數都不一樣。
Microgaming的圖坦卡門(Temple of Tut)
Temple of Tut中,玩家将扮演冒險家在埃及尋找著名法老圖坦卡門的巨大財富。遊戲風格以卡通方式呈現,搭上充滿
埃及風情的音樂。玩法簡單易懂,共有10條賠付線,透過百搭符號的堆疊,提高玩家與古埃及花瓶、生命之符、男探家
與女探險家等這些符號配對的機會。
NetEnt的埃及硬幣(Coins of Egypt)
才剛在週一發表的Coins of Egypt,同樣也是以古埃及神話為主題,將帶領玩家前往古埃及,尋找一座美麗卻被遺忘的
寺廟,裡頭充滿財財富,等待玩家來探險。和前面幾款一樣,附有經典的符號,如聖甲蟲、埃及諸神,當然也少不了玩
家最愛的免費遊戲及百搭符號功能。
免費旋轉回合中,每次旋轉期間滾軸上最多可出現3枚硬幣,它們的價值被添加3個
不同的箱子,只要玩家選對了箱子,
就可骑著裝滿硬幣的駱駝離開埃及。

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