Beyond Algorithms: Delivering AI for Business

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)

在人工智慧（AI）成為頭條新聞的同時，企業爭相利用這項令人興奮且具有轉型能力的技術。顯然，首先提供與業務相關的AI解決方案的企業將獲得重大優勢。

然而，問題來了！我們對於AI在社會上的成功觀念主要是基於我們對大型網絡公司的消費者應用的經驗。由於各種挑戰，企業中對於AI的採用進展緩慢。商業應用需要解決更複雜的問題，且用於解決這些問題的數據較少。此外，AI與相關業務流程的協調是至關重要的。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，如何在企業中提供可運行的AI應用？

《超越演算法：為企業提供AI解決方案》回答了這個問題。這本書由三位擁有數十年AI經驗（以及相應的傷痕）的工程師撰寫，解釋了定義、管理、工程和交付端到端AI應用所需的要素。本書提供了以下內容：

- AI與傳統商業應用之間的核心概念差異
- 一種新的方法論，有助於優先考慮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際案例和示例
- 旨在挑戰您思維並毀掉您周末的技術深入探討和思考實驗

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)

James Luke是一位工程師，擁有超過25年的經驗，提供解決真實世界問題的真正AI解決方案。James是英國領先的科技公司Roke的創新總監，曾任IBM杰出工程師和主要發明家。James在AI相關主題上擁有多項美國專利，並在他的博士研究中研究了AI在檢測以前未見過的電腦病毒方面的應用。James是一位經驗豐富的會議演講者，並向歐洲委員會和上議院選舉委員會提供了有關AI發展的證據。2018年，James發表了一場名為“如何在AI冬天中生存”的TEDx演講。James在職業生涯初期未能為一支領先的F1車隊提供AI解決方案。這次經歷改變了James對實際交付工作的AI解決方案所需的理解和觀點。James對早期的失敗做出回應，開發了定義、設計和交付AI解決方案的新方法。他在多個行業中交付了項目，從公共部門到保險和零售。在加入Roke之前，James在IBM擔任了多個重要職位，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AI技術學院核心團隊的負責人。

Padmanabhan Santhanam博士目前是IBM T. J. Watson研究中心的首席研究員，致力於在政府和公共部門中實現AI系統。他個人的研究興趣包括使用AI來工程傳統軟件系統以及新興的AI工程領域（即如何工程可信賴的AI系統）。在此之前，Santhanam博士在IBM研究中心從事AI戰略和執行的多個方面的工作。他擁有耶魯大學應用物理學的博士學位。Santhanam博士在軟件工程研究方面有二十年的經驗，涉及創建工具和方法論以改進商業軟件開發。他的興趣包括軟件質量指標、軟件測試生成的自動化、軟件開發過程的實際建模等。他在各種主題的同行評審期刊和會議上發表了五十多篇研究論文。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。

David Porter目前是IBM Consulting的副合夥人。他於1995年從格林威治大學獲得信息系統工程學位。他從事AI和數據科學工作至今，曾在SAS Software、Detica/BAE Systems和現在的IBM擔任顧問職位。在職業生涯初期，他選擇專注於反欺詐和執法系統。這種專業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件NetReveal，並領導英國保險欺詐局和英國海關及稅務局（HMRC）的原始Connect系統的設計團隊。他於2016年加入IBM，被Watson的故事所吸引；AI能用來抓捕罪犯嗎？從那時起，他一直在有效利用自然語言處理。

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