1、Technology Trend Report 2020 Tech Lab Innovation others might be greatly overes- timated and remain niche concepts. We dont know our future and we will never be able to predict it. That said, we can analyse trends, extrapolate findings and sketch a multitude of scenarios. Some pos- sibilities are le

2、ss likely, but others have a fair chance of coming to fruition and can give guidance on how to position Rabobank and/or her clients to reap the benefits of these developments. This report is brought to you by the Tech Lab team of the Rabobank Innovation often, our ten- dency can be to fear new techn

3、ologies. With this report we hope to build your confidence in new technologies and support the belief that they can help you, your cli- ents and organisation as a whole. This report is initially targeting Rabobank employees and our clients, and consequently lays its focus mostly on our customers and

4、 our banking environment. As we think these insights are applicable to other industries, compa- nies and individuals as well, we are eager to share our les- sons learned. We want to encourage you to extend these technical developments to your own situation. Please get in touch with us if you have qu

5、estions, feedback or interesting opportunities We hope you enjoy reading this report as much as we enjoyed facilitating its development. Preface Roel Steenbergen Chris Huls Contact us: Technical Innovator Lead Tech Lab 3 Preface techlabrabobank.nl A few decades ago the world welcomed a new era: the

6、digital age. Extremely rapid digitisation meant we said goodbye to the world as we knew it. Most companies and organisations have already under- gone a major digital transformation. We now find ourselves in a whole new chapter of the digital era, but that by no means implies that the most signif- ic

7、ant changes are behind us not in the slightest. Rather, the world, again, finds itself at a tipping point. This report explores the abundance of opportuni- ties that digital technologies present the world, the banking and Food Next Gener- ation Communication Networks; Extended Reality; Blockchain; S

8、ecure Multi-Party Computation; Voice Technology; Quantum Computing and Artificial Intelligence. This report digs a little deeper to un- pack the definition, developmental context, future growth and practical application of each of these technologies. In the coming years, we will continue to focus on

9、 how to leverage these technologies to do what we do even more effectively serve our clients and their interests, while simultaneously working to make the world a better, smarter and more sus- tainable place. Because for us at Rabobank, this is one of our key priorities. We can only achieve true sus

10、tainability if people and businesses collaborate to contribute to a better, cleaner world. And a better world is precisely what Rabobank hopes to create by providing financial services that improve clients access to information, knowledge and networks. Leveraging technological trends to build new bu

11、si- ness models and drive economic development has its merits, but should never take priority over our responsibility to care for our people and our planet. 5 Introduction Artificial Intelligence Chapter 01 Unpacking Artificial Intelligence Artificial Intelligence (AI) refers to a collection of tech

12、nol- ogies that, when brought together, enables machines to act with human-like levels of intelligence. AI can be described as applications that leverage machine learn- ing, natural language processing (NLP) and computer vision to learn new information, draw conclusions and comprehend content. By do

13、ing so, machines are able to automate certain tasks and replace the role of humans in carrying out predominantly routine, repetitive activi- ties. Like in the case of Quantum Computing (QC) and Secure Multi-Party Computation (SMPC), the technology and maths behind AI has been around for ages; its on

14、ly flourished of late with the enormous increase in compu- tational power, the explosion of available data and the increasing number of data professionals in the workforce. Theres no doubt that AI, which combines and powers a wide range of developments, will change the way we work and live more so t

15、han any other technology alone. Self-automated learning is a key aspect of AI. Machines are able to learn through: Supervised learning the algorithm learns on a la- belled dataset and has access to the correct answer that it can use to evaluate its accuracy on training data; Unsupervised learning th

16、e algorithm tries to make sense of unlabelled data by extracting features and patterns on its own; Reinforcement learning the algorithm learns by interacting with its environment, through a system of reward and punishment (trial and error). Definition 7 Artificial Intelligence Evolution of Artificia

17、l Intelligence Context Today, approximately 80 percent of large companies have adopted examples of machine learning and other forms of AI to enhance their core business operations. Five years ago, this figure was less than 10 percent. Nev- ertheless, most companies still only use AI tools as point s

18、olutions for fraud prevention, for instance discrete applications that are isolated from the enterprises wider IT architecture. Every day, AI is getting closer and closer to human-like in- telligence, and at some point we may no longer be able to tell the difference between machines capabilities and

19、 those of people. That said, since AI currently still isnt able to grasp the full meaning of concepts, its scope of appli- cation is slightly limited. That might change, though. Af- ter all, when AI was first pioneered, it could only perform tasks that were easy and repetitive. It has since evolved

20、and can now tackle far more multifaceted and complex activities accurately predicting travel times in naviga- tion apps, for instance. So, who knows what it will be ca- pable of in the future? Narrow AI versus Broad AI At present, most AI applications fall under the Narrow AI category meaning, theyr

21、e built for a specific task. In the future, we expect the rise of Broad AI solutions systems that can work on a broad range of problems. Even though its relatively early days as far as AI goes, busi- nesses worldwide are already using AI and deep learn- ing in several unique ways as invaluable tools

22、. Thanks to developments in computer hardware, performance improvements, the advent of cloud computing and ad- vancements in AI technology itself, AI has become acces- sible to enterprises of all sizes. That said, bigger technol- ogy companies are still the biggest investors in this field. The movem

23、ents in this arena bode well for the future: today, AI is already capable of making highly accurate predictions, and going forward, it will take over more and more activities that humans are currently responsible for. The other side of the Artificial Intelligence coin As is the case with various oth

24、er technologies, data qual- ity and privacy are both still challenging issues when it comes to AI. Perhaps more than any other innovation, though, AI instills much fear in people. There are the more widely expressed concerns Will we lose our jobs to robots? and then theres also anxiety about losing

25、control over AI, its outcomes and impacts. As AI models become increasingly advanced, intelligent and complex, we as humans tend to understand them less we need to be wary of possible biases that we dont immediate- ly recognise and cant explain or even interpret. Its even been found that AI-driven m

26、odels can make choices that us humans arent capable of understanding the “Com- puter says no” scenario is an example. Naturally, for many people, thats a scary thought. 8 Artificial Intelligence What tomorrow holds for Artificial Intelligence While human intelligence is still indispensable, well alm

27、ost certainly see a drop in our dependence on the living brain in the coming years. One day, for instance, AI will be able to fully run the autopilot function in an aircraft. The reality is, though, were not at this point yet. AI algorithms are still far from perfect in fact, the idea of 100 percent

28、 accurate algorithms that can operate entirely on their own without the need for hu- man intervention or decision-making is still a far-off ideal. Furthermore, many organi- sations today battle with the amount of data, and the level of data quality, needed for solid AI applications. AI will complete

29、ly change the way we work and live While it will still be many decades before we see Quantum Computing (QC) take off on a large scale, its predicted that when this happens, it will have a significant impact on the field of AI leading to enhanced judgement, improved interaction, greater degrees of tr

30、ust and products that are far more intelligent. In general, AI is going to change almost every aspect of daily life and the nature of work as we know it. To manage AI and harness its power within organisations, new jobs, roles and skills will be required. As AI tackles less complex, more mundane dut

31、ies, employees can start taking on higher-value, more rewarding tasks. Future 9 Artificial Intelligence Implications and applications for Rabobank and its clients Context AI is bringing about a massive transformation in the banking industry. It yields many new data-driven in- sights, while increasin

32、g productivity and presenting new cost-saving opportunities. AI allows banks to enhance the customer experience, accelerate business growth, mitigate risks and increase operational efficiency. This trend offered endless opportunities for Rabobank, too. AI can be applied to all of the banks internal

33、and available external sources of data. It has already been lev- eraged for multiple different purposes for fraud preven- tion, personalised financial advice, real-time transaction monitoring, risk assessment, cybersecurity, enhanced human-machine interaction and even for marketing. Ra- bobank creat

34、ed an AI model to identify operational de- posits, enabling the bank to conduct better risk assess- ments. The model was built in only six weeks, and saves the bank millions of euros per year - of course by using customer data only in accepted ways. A proactive player in the market Rabobank strives

35、to promote a data-driven society and aims to improve confidence in AI. One way the bank con- tributes is by being an active player in the market. Ra- bobank is one of the investors behind ProducePay, a Los Angeles-based company that aims to overcome the lack of proper short-term access to financing

36、and transparen- cy within the farming industry supply chain by providing fresh produce farmers with financial resources, tech tools and data insights. Another AI-driven initiative Rabobank is proud to sup- port is JoinData, an authorisation data platform for the Dutch agricultural sector that enable

37、s companies, knowl- edge institutions and agricultural entrepreneurs to work together to stimulate sustainable entrepreneurship and innovation in the industry. 10 Artificial Intelligence Artificial Intelligence in practice Agricultural companies around the world are looking to technology to help the

38、m access data-driven insights, run operations more efficiently and reduce waste in food pro- duction. AI technology, in particular, is transforming the agricultural sector, as farmers can now rely on data from satellites like drones to assess their farms state they no longer have to walk the full le

39、ngth of their property. Machine learning models are being developed to track and predict the impact of environmental conditions, like weather changes, on crop yield. Finally, companies are also developing and programming autonomous robots to handle essential agricultural tasks, like crop harvesting,

40、 and to do so at a significantly higher volume and faster pace than human labourers could. John Deere, American manufacturer of farming and in- dustrial machinery, is a shining example of a company thats used AI to radically transform the farming industry. The companys pesticide and herbicide distri

41、bution sys- tems use smart cameras, powered by computer vision, to distinguish between healthy and unhealthy plants as the equipment passes through the field these smart machines then use this information to decide, then and there, which individual crops to dose with chemicals. PEAT is a Berlin-base

42、d agricultural tech startup that has developed a deep-learning application called Plantix. Plantix can identify potential defects and nutrient defi- ciencies in soil using a software algorithm that correlates certain foliage patterns with soil problems, plant pests and diseases. Financial institutio

43、ns everywhere have also eagerly jumped on the AI bandwagon. JPMorgan Chase, for in- stance, has implemented a proprietary algorithm to de- tect fraud patterns. Every time a credit card transaction is processed, complete details of the event are sent to central computers in J.P. Morgan Chases data ce

44、ntres, and these then decide if the transaction is fraudulent. Another example is US Bank, which has been using deep learning for anti-money laundering purposes for the past three years. By doing so, the bank has managed to double the output it could achieve using the previous systems capabilities.

45、Lastly, its also worth noting the example of Ceba, from the Commonwealth Bank of Australia. Ceba is a chatbot thats been trained to provide customers with in-the-moment digital support. The application is capa- ble of answering a broad range of customers day-to-day banking-related questions. Example

46、s 11 Artificial Intelligence Blockchain Chapter 02 Unpacking Blockchain What exactly is blockchain? Its an IT solution that enable multiple parties to work on a shared set of data this data could be, for example, all the information that flows through the mortgage chain, and is used by banks, notari

47、es and financial advisors. It allows digital information to be distributed, while participating parties keep full own- ership of their own individual pieces of data. Imagine a shared spreadsheet that exists in the IT systems of all participants. Each individual cell is owned by one party, and if cha

48、nges are made, they are executed across all copies of the shared spreadsheet. As a result, this “spreadsheet” (or block- chain solution) serves as mutual place to store data and a single version of the truth for involved parties. Blockchain technology enables Bitcoin and other cryptocurrencies, but

49、can actually be used to facilitate the transaction of any type of digital asset. It does so by creating and maintaining a distributed ledger that functions as a registry of transaction re- cords. Blockchain helps to improve the way businesses, governments and individuals work together by ensuring that all digital agreements are secure and trustworthy, so that the involved parti