Beyond Algorithms: Delivering AI for Business
暫譯: 超越演算法：為商業交付人工智慧

Luke, James, Porter, David, Santhanam, Padmanabhan

Beyond Algorithms: Delivering AI for Business

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商品描述

With so much artificial intelligence (AI) in the headlines, it is no surprise that businesses are scrambling to exploit this exciting and transformative technology. Clearly, those who are the first to deliver business-relevant AI will gain significant advantage.

However, there is a problem! Our perception of AI success in society is primarily based on our experiences with consumer applications from the big web companies. The adoption of AI in the enterprise has been slow due to various challenges. Business applications address far more complex problems and the data needed to address them is less plentiful. There is also the critical need for alignment of AI with relevant business processes. In addition, the use of AI requires new engineering practices for application maintenance and trust.

So, how do you deliver working AI applications in the enterprise?

Beyond Algorithms: Delivering AI for Business answers this question. Written by three engineers with decades of experience in AI (and all the scars that come with that), this book explains what it takes to define, manage, engineer, and deliver end-to-end AI applications that work. This book presents

  • Core conceptual differences between AI and traditional business applications
  • A new methodology that helps to prioritise AI projects and manage risks
  • Practical case studies and examples with a focus on business impact and solution delivery
  • Technical Deep Dives and Thought Experiments designed to challenge your brain and destroy your weekends

商品描述(中文翻譯)

隨著人工智慧（AI）頻繁出現在新聞標題中，企業爭相利用這項令人興奮且具變革性的技術也就不足為奇了。顯然，首批提供與業務相關的 AI 的企業將獲得顯著的優勢。

然而，這裡有一個問題！我們對社會中 AI 成功的認知主要基於我們與大型網路公司消費者應用的經驗。由於各種挑戰，AI 在企業中的採用進展緩慢。商業應用面對的問題要複雜得多，而解決這些問題所需的數據也不那麼豐富。此外，AI 與相關業務流程的對齊也是至關重要的需求。此外，使用 AI 需要新的工程實踐來進行應用維護和建立信任。

那麼，如何在企業中交付可運作的 AI 應用呢？

超越演算法：為商業交付 AI 對這個問題給出了答案。這本書由三位擁有數十年 AI 經驗的工程師撰寫（以及隨之而來的所有傷痕），解釋了定義、管理、工程和交付可運作的端到端 AI 應用所需的條件。本書介紹了：


  • AI 與傳統商業應用之間的核心概念差異

  • 一種新的方法論，幫助優先考慮 AI 項目並管理風險

  • 以商業影響和解決方案交付為重點的實用案例研究和範例

  • 技術深入探討和思維實驗，旨在挑戰你的思維並摧毀你的週末

作者簡介

James Luke, is an Engineer with over 25 years' experience delivering real AI solutions that solve real world problems. James is the Innovation Director at Roke, a leading UK technology company, having previously worked as an IBM Distinguished Engineer and Master Inventor. James has multiple US patents in subjects relating to AI and, for his PhD, researched the application of AI in detecting previously unseen computer viruses. James is an experienced conference speaker and has given evidence on the development of AI to both the European Commission and the House of Lords Select Committee. In 2018, James delivered a TEDx talk entitled, "How To Survive An AI Winter" ( https: //www.youtube.com/watch?v=MWOkEVdITIg ). James started his career failing to deliver an AI solution for a leading Formula 1 team. This experience changed James's understanding and perspective on what it takes to actually deliver a working AI solution. James responded to his early failure by developing new methods for the definition, design and delivery of AI solutions. He has delivered projects in multiple industries from Public Sector to Insurance and Retail. Prior to joining Roke, James held a number of key positions in IBM including Chief Architect for Watson Tools, CTO of the Cognitive Practice in Europe and Leader of the Academy of Technology core team on AI.

Dr. Padmanabhan Santhanam is currently a Principal Research Staff Member at the IBM T. J. Watson Research Center in New York, working to enable AI systems in government and public sector. His personal research interest is both in the use of AI for engineering traditional software systems and the emerging field of AI Engineering (i.e. how to engineer trust-worthy AI systems). Prior to that, Dr. Santhanam worked on several aspects of AI strategy and execution in IBM Research. He holds a Ph.D. in Applied Physics from Yale University. Dr. Santhanam worked in software engineering research for two decades, having to do with the creation of tools and methodology to improve commercial software development. His interests included software quality metrics, automation of software test generation, realistic modeling of software development processes, etc. He has more than fifty published research papers in peer-reviewed journals and conferences in a variety of topics. He is a member of the ACM & AAAI and a Senior Member of the IEEE. He is also a Member of the IBM Academy of Technology.

David Porter is currently an Associate Partner at IBM Consulting. He graduated in 1995 from the University of Greenwich with a degree in Information Systems Engineering. He has worked in AI and Data Science ever since, with consultancy roles at SAS Software, Detica/BAE Systems and now IBM. Early on in his career he chose to focus on counter-fraud and law enforcement systems. This specialisation has allowed him to work with governments and organisations all over the world. Achievements in this field include the co-invention of the graph analytics software NetReveal and leading the design teams for both the UK's Insurance Fraud Bureau and the original Connect system at Her Majesty's Revenue and Customs (HMRC). He joined IBM in 2016, enticed by the Watson story; could AI be used to catch crooks? He has been putting Natural Language Processing to good use ever since.

作者簡介(中文翻譯)

詹姆斯·盧克（James Luke）是一位擁有超過25年經驗的工程師，專注於提供能解決現實世界問題的真正人工智慧（AI）解決方案。詹姆斯是英國領先科技公司Roke的創新總監，曾擔任IBM的傑出工程師和首席發明家。詹姆斯在人工智慧相關領域擁有多項美國專利，並在其博士研究中探討了人工智慧在檢測未曾見過的電腦病毒中的應用。詹姆斯是一位經驗豐富的會議演講者，曾向歐洲委員會和英國上議院選擇委員會提供有關人工智慧發展的證據。2018年，詹姆斯發表了一場名為「如何在人工智慧寒冬中生存」的TEDx演講（https://www.youtube.com/watch?v=MWOkEVdITIg）。詹姆斯的職業生涯始於未能為一家領先的F1車隊交付人工智慧解決方案。這段經歷改變了詹姆斯對於實際交付有效人工智慧解決方案所需條件的理解和看法。詹姆斯通過開發新的定義、設計和交付人工智慧解決方案的方法來回應他早期的失敗。他在公共部門、保險和零售等多個行業交付了項目。在加入Roke之前，詹姆斯在IBM擔任多個關鍵職位，包括Watson工具的首席架構師、歐洲認知實踐的首席技術官以及人工智慧核心團隊的技術學院領導者。

帕德馬納班·桑坦南（Dr. Padmanabhan Santhanam）目前是IBM T. J. Watson研究中心的首席研究成員，專注於在政府和公共部門推動人工智慧系統的應用。他的個人研究興趣包括使用人工智慧來工程化傳統軟體系統以及新興的人工智慧工程領域（即如何設計值得信賴的人工智慧系統）。在此之前，桑坦南博士在IBM研究部門負責多個人工智慧策略和執行方面的工作。他擁有耶魯大學的應用物理學博士學位。桑坦南博士在軟體工程研究領域工作了二十年，專注於創建工具和方法論以改善商業軟體開發。他的研究興趣包括軟體質量指標、軟體測試生成的自動化、軟體開發過程的現實建模等。他在各種主題上發表了超過五十篇的同行評審期刊和會議論文。他是ACM和AAAI的成員，也是IEEE的高級會員。他還是IBM技術學院的成員。

大衛·波特（David Porter）目前是IBM顧問公司的副合夥人。他於1995年畢業於格林威治大學，獲得資訊系統工程學位。自那時以來，他一直從事人工智慧和數據科學的工作，曾在SAS Software、Detica/BAE Systems和現在的IBM擔任顧問角色。在職業生涯的早期，他選擇專注於反詐騙和執法系統。這一專業化使他能夠與世界各地的政府和組織合作。在這一領域的成就包括共同發明圖形分析軟體NetReveal，以及領導英國保險詐騙局和英國稅務海關總署（HMRC）原始Connect系統的設計團隊。他於2016年加入IBM，受到Watson故事的吸引；人工智慧能否用來抓捕罪犯？自那時以來，他一直在有效利用自然語言處理技術。

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