2017 was very much the year where every business sector woke up to the potential impact of advanced artificial intelligence (AI) technology, and now everyone is asking the question: if we’re not using AI, why not? As such, 2018 will see the biggest ever increase in demand for AI backed services.
2017年各行各业都意识到（woke up to）了先进的人工智能（以下简称AI）技术带来的潜在影响，如今大家都在问：如果我们没有使用AI，还等什么呢（why not?根据语义）？就此而言（As such 就本身而论），由AI支持的服务将在2018年迎来（see）迄今最为显著的需求增长。
Certain industries, such as big tech and finance, are already leading on AI adoption as they have the deep pockets to afford the limited expertise that exists in the world. Therefore, 2018 will be a year of catching-up for many companies as they try to understand how AI can help them and what they need to do to access the technology. What will be interesting is whether the AI industry will be able to supply and satisfy the massive increase in demand.
大型技术、金融（中英文顺序哦）等特定行业已经走在了AI应用（adoption采用）的前列，他们拥有雄厚的财力（ have the deep pockets ），汇聚全球有限的专业技术。因此，2018年很多企业将奋起直追（catching-up），弄清AI可以为他们提供怎样的帮助，以及如何获得这一技术。值得关注的（What will be interesting ）是AI产业能否满足激增（massive increase好吧，真滴要有些简练的语言呢）的需求。
In my mind, in order to power the AI rocket ship, you will need three crucial things: data, computing power and the right IT tooling infrastructure. But how will the technology be used to actually impact day-to-day business operations?
在我看来，想要驱动AI这艘火箭船，你需要三个关键要素（three crucial things根据后面列举的三个短语，可知不是事情，而是因素/条件）：数据、运算能力以及合适（right）的信息技术加工（tooling）基础构架。但如何应用这种技术才能在日常业务运转中（business operations 经营活动）产生实际作用（impact）简简单单翻译成影响是欠考虑的呢？
AI will, at the very least, be used in 2018 to transform known healthcare difficulties, such as important information being missed and long wait times delays. For example, predictive analytics can be used to reduce bottlenecks and improve patient flow.
在2018年AI至少可以用来解决已知的医疗难题，如重要信息被遗漏、长时间等待造成延误（delays词性）等。举例来说，预测性分析可用于减少瓶颈，有利于病患分流（improve patient flow.）。
Among leading healthcare systems, some form of AI will be adopted within their diagnostic groups as deep learning algorithms get more and more adept at recognising patterns — which is, in essence, what much of diagnostics is about. When it comes to analysing data, AI can aid humans in making this process smoother and more accurate.
从本质上讲（in essence），诊断学以识别病理模式为主（much of diagnostics is about）。随着深度学习算法越来越精通模式识别，某种形式的AI将在主要医疗系统的诊断小组内得到应用，还可以帮助人类更顺畅、更准确地进行数据分析。
AI and machine learning will begin to be used to help clinical trials to better identify potential patients through the use of large data sets, data analysis and data modelling.
通过大数据集、数据分析和数据建模，AI和机器学习将帮助临床试验更好地确定潜在病患。
With financial strains on health services, AI will be implemented to help reduce patient admittance. One way of doing this could be by using a chatbot-like system to ask individuals about their symptoms, convey that information to their doctor and ensure the right medications are being taken at the right time.
由于（With）医疗服务资金有限（strains on），AI将用于减少病患入院，其中一种方式是通过聊天机器人（chatbot）之类的系统询问症状，将这些信息传递给医生，确保病人适时使用正确的药物。
The growing disruption of the industry by fintech startups means that more traditional financial services organisations will need to leverage AI technology in order to advance their competitive position, strengthen customer engagement and improve performance.
金融科技初创公司（fintech startups）对金融业的日益颠覆（growing disruption翻译成颠覆哈哈）意味着，将有更多传统的金融服务机构需要利用 AI 技术提高其竞争力，加强客户参与度，提高效益（improve performance.）。
The Financial Conduct Authority (FCA) reports that the number of successful cyber attacks has risen from 5 to 49 annually between 2014 and 2017. Given the nearly endless proliferation of data breaches and cyber attacks over the past year alone, there will no doubt be a huge increase in the number of banks and financial services adopting innovative technology such as AI and machine learning in an attempt to minimise this threat.
据金融行为监管局称，2014年至2017年，网络攻击事件从每年5起上升至每年49起。鉴于单单在过去一年里发生的大规模（endless）数据泄露和网络攻击扩散事件（proliferation），采用人工智能、机器学习等创新技术的银行和金融服务公司的数量无疑将大幅增加，以尽量减少这种威胁。
The efficient levels of processing enabled through AI means that it will be used more and more by financial services to not only assess risk, but also to help detect early signs of market changes.
通过 AI 实现的有效处理水平意味着，AI将越来越多的被应用到金融服务中，不仅能够评估风险，还能帮助检测市场变化的初期迹象（early signs）。
Due to the success of personalised solutions in other industries, consumers will start to demand the same of their financial services and this is where AI comes in. By analysing data sets to find common patterns, the gap between what consumers want and what financial firms are able to deliver can be greatly reduced.
鉴于个性化解决方案（solutions）在其他行业所取得的成功，消费者也将对金融服务业有着同样的需求，AI随之进入金融业（this is where AI comes in. 进入金融业的契机）。通过分析数据集找出共同的模式，这样消费者的需求（what consumers want）和金融公司能够提供的服务之间的差距可以大大缩小。
In 2018, AI will be used in e-commerce on a more global scale to identify the purchase habits associated with particular products, for example to better understand shopping cart abandonment rates, resulting in smarter retargeting messages being sent to consumers.
2018 年，AI将在世界电子商务领域应用地更加广泛（more），例如根据特定商品确定购买习惯，以更好地了解购物车（shopping cart）产品放弃率，更加精准地向客户推送信息（retargeting）。
Chatbots will become an even greater way of bringing a personal element to the e-commerce realm and customer satisfaction will increase for retailers that have engaged with consumers through AI, offering guidance and advice that mirrors the in-store shopper experience.
聊天机器人将以更好的方式为电子商务领域（realm）引入个人元素，顾客对那些通过AI与顾客互动（engaged with ）的零售商的满意度将得到提高，AI可以根据（mirrors）店内购物者的经验，为顾客提供指导和建议。
The collection of accurate demographic data on any given shop’s footfall will allow retailers to understand exactly the type of shoppers engaging with their brand. These insights will allow for more tailored decisions to be made on everything - from buying decisions and marketing campaigns to store layout and customer loyalty programs.
对任何指定商店的客流量（footfall）进行精准的人口数据收集，可以使零售商准确地掌握其品牌的消费者类型——从购买决策和营销活动到店面布局和客户忠实计划。
Consumers will become less and less tolerant of generic offers and messages in 2018. Instead, they’ll expect to be offered something relevant and meaningful, sent to them in real-time, via a channel that works for them.
2018年，消费者将愈发不能容忍无差别化（generic通用的）的产品和信息。相反，消费者会希望得到一些与之相关的、有意义的东西，并通过专为他们运转的渠道，实时传递（sent to them in real-time）。
As AI technology becomes democratised and can help to automate many time-consuming and repetitive tasks, marketers will have more time to focus on higher value creative projects.
AI技术正在变得大众化，能够让许多耗时的、重复性的工作自动化，如此一来，营销人员就会有更多时间专注于更高价值的创造性工作。
Marketers will also begin using AI tools on a larger scale to scan data points and gauge consumer sentiment. This information will then go on to inform future campaigns and content.
营销人员也将开始在更大范围内使用AI工具处理大数据（scan data points 扫描数据项目），判断消费者的情绪。这些信息可以为未来的营销活动服务。
There is no doubt that AI can help us solve many of the world’s most challenging problems and that everyone should be able to enjoy the benefits of AI. As is true with so many things, it will be the companies that can afford AI that will implement it first. Therefore, the key question for 2018 will be: how can we ensure that the technology is usable and affordable for all companies and organisations, not only the big and powerful?
毫无疑问，AI能帮助我们解决世界上许多最具挑战的问题，每个人都应该享受AI带来的好处。就像很多事情一样（As is true with so many things），那些能够负担得起AI的公司将最先运用AI。因此，2018年的关键问题是：我们如何保证这项技术不仅可以在有实力的大公司应用，所有公司和组织都能够使用并负担得起。
At Peltarion, we have been working on the next step in our mission - to democratise and demystify artificial intelligence by making it easily accessible for everyone and, as we move into 2018, we hope to significantly lower the barriers of entry for AI.
在Peltarion（译者注：人工智能供应商），我们已经开始进行下一步工作——通过让每个人都能方便使用AI，使AI变得大众化和平民化。2018年，我们希望能显著降低（significantly lower）人工智能的门槛（barriers of entry ）。
