Daily Tech Digest - January 17, 2021

‘Augmented creativity’: How AI can accelerate human invention

What we’re witnessing is the emergence of something called “augmented creativity,” in which humans use AI to help them understand the deluge of data. Early prototypes highlight the important role humans can, and should, play in making sense of the suggestions proposed by the AI. OpenAI attempted to replicate this approach with the release of a music-making tool called Jukebox. While the achievement is significant from a technological perspective, the results are unlikely to threaten the livelihoods of human musicians. Various projects have also attempted to produce new and enticing recipes by using AI to mine food composition databases and concoct interesting combinations. For instance, Google researcher Sara Robinson recently showcased her system that produced a cake-cookie hybrid. Accenture researchers prototyped a similar recipe creation tool at their Dock facility in Dublin, but with stomach-churning results. Most of these approaches utilize huge datasets that AI mines to look for well-established yet previously untapped connections. By using general adversarial networks (GANs), the next-generation models are capable of coming up with ideas without requiring access to the underlying logic.

Enterprise Architecture and Risk Management for banks: Aligned?

What does enterprise architecture mean for RMiT? Chief Architect of of ATD Solution, Aaron Tan Dani, opined that enterprise architecture is important to respond fast and to understand the impact of any action taken. One of the outcomes of enterprise architecture is a digital enterprise map, a visual of all the applications in the organisation’s IT environment and how they map back to hardware, network, data, and ultimately to the objectives of the business. There is proper and thorough traceability between each architecture domains (Business, Data, Application and Technology), and troubleshooting of the entire enterprise can be made, allowing strategic business decisions to be made in an agile way. This Digital Enterprise Map is constructed collaboratively with effort from every department and business unit across the enterprise, enabling a single view of the connected organisation.  In a way, this map can also help organisations to address these questions: Are you able to define your technology initiatives from a business perspective? Are you able to model the strategy and provide the traceability on its execution? Are you able to map the business strategies, objectives and goals to the different capabilities/elements in the enterprise?

UK government needs a digital reboot

Over the last six months, the Commission on Smart Government has undertaken extensive work in this domain to identify the major barriers to better digital government. We have identified a number of areas in which action should be taken to reduce barriers and build capability in this area. Many of the 60 recommendations the Commission makes in this area focus on reforms around governance and leadership, without which we will never see digital and technology matters viewed consistently alongside other top-tier issues. Creating more effective, cross-departmental digital oversight, while allowing for greater autonomy outside of Whitehall, forms the basis of many of our recommendations – and that is why the latest organisational announcements are so welcome. It will be vital, however, that the CDO role is empowered so far as is possible – and should serve as the prime minister’s chief technology adviser – and that chief digital roles exist in every department to ensure no policy area is left behind and that each has a vision for a digitally enabled future. This will see a requirement both for more dedicated technologists in government as well as better digital skills among those responsible for overseeing larger digital projects or local services.

Banks need to strike the right balance for digital transformation

Banks have increasingly understood they need outside help to execute their digital transformation agenda. “Banks usually have very rigid systems and procedures,” says Fei. “For instance, if you want to launch a new product you have to follow the process, and it takes at least six months. In the age of digitalization, this doesn’t work, as customers want things immediately. This has put huge pressure on these financial institutions to build agile operations and systems to be able to respond to the needs of their customers.” But the number of tech companies pushing into financial services can be overwhelming and not all of them have domain expertise, which can lead to misguided attempts to apply new technologies everywhere. Without experience of financial services, tech companies may also underestimate the trade-offs involved in deploying certain digital tools. OneConnect combines expertise in digital technology with deep knowledge of banking. Fei, who has past experience working at HSBC China and Bank of Langfang, a Chinese commercial bank, describes one partnership with a Chinese national bank to reimagine its customer service center as an illustration of why banking experience matters in digital reform.

Deep learning sharpens near-infrared images for cancer diagnostics

Fluorescence imaging is a valuable method for examining biological systems. To achieve the maximum tissue penetration depth and minimum light scattering, detecting near-infrared (NIR) fluorescence in the long-wavelength end of the second NIR window (1500–1700 nm), known as NIR-IIb, provides the best results. Unfortunately, NIR-IIb imaging relies on nanoparticle fluorescent probes that often contain toxic elements, hindering its clinical translation. Biocompatible small-molecule NIR fluorescent probes do exist. Indocyanine green (ICG), for example, is approved by the US Food and Drug Administration and has already been used for clinical applications. Such small-molecule fluorophores, however, emit in the shorter-wavelength NIR-I and NIR-IIa windows (700–1000 and 1000–1300 nm). And light scattering at these wavelengths limits the imaging depth and causes low contrast images. To achieve high image contrast and clarity while using biocompatible probes, Zhuoran Ma, his PhD adviser Hongjie Dai, and colleagues at Stanford University turned to deep learning. Using roughly 2800 in vivo images of mice taken in the NIR-IIa and NIR-IIb windows, they trained artificial neural networks to transform blurred NIR-IIa fluorescence images into higher-resolution images previously only achievable using NIR-IIb.

Deep learning doesn’t need to be a black box

Deep learning models are usually trained on a single data set of annotated examples. Concept whitening introduces a second data set that contains examples of the concepts. These concepts are related to the AI model’s main task. For instance, if your deep learning model detects bedrooms, relevant concepts would include bed, fridge, lamp, window, door, etc. “The representative samples can be chosen manually, as they might constitute our definition of interpretability,” Chen says. “Machine learning practitioners may collect these samples by any means to create their own concept datasets suitable for their application. For example, one can ask doctors to select representative X-ray images to define medical concepts.” With concept whitening, the deep learning model goes through two parallel training cycles. While the neural network tunes its overall parameters to represent the classes in the main task, concept whitening adjusts specific neurons in each layer to align them with the classes included in the concept data set. The result is a disentangled latent space, where concepts are neatly separated in each layer and the activation of neurons correspond with their respective concepts.

Blockchain Beyond Bitcoin: Transforming FinTech, Healthcare, And More

One would be hard-pressed to find a use case in financial services that wouldn’t benefit from blockchain, save for in-person payments given the single-digit TPS (transactions per second) vs the modern payment rails that operate in the tens of thousands of TPS. Trade finance, asset management, capital markets, banking and lending, insurance, etc. all would realize increased privacy, accuracy, and security from the distributed, immutable ledger technology. On cross-border settlement transactions alone, a report by Jupiter Research shows that blockchain deployments will enable banks to save up to $27 billion by the end of 2030, reducing costs by more than 11%. Financial institutions acknowledge that Blockchain technology will save billions of dollars for banks and major financial institutions over the next decade. Payments is a category on which blockchain efforts are concentrated. This is an obvious conclusion, being that on the blockchain, AP/AR is easily tracked and verified, duplications are virtually impossible, and smart contracts can automate the process based on agreed-upon terms. However, cryptocurrencies have proven too volatile and slow to be an adequate payment solution in most cases.

Answers to the Most Common Questions about Enterprise Architecture

The importance of enterprise architecture will depend a lot on what the organization does with their EA. Orbus have found as many as 28 different use cases for iServer across our customer base, and even that figure is not likely to encompass every activity. Some enterprises may simply use their enterprise architecture to reduce IT costs, but for others it can have transformative impacts. In fact, the prime use of enterprise architecture is to drive digital transformation. Planning changes over short and long periods, predicting the impacts of changes, gathering stakeholder views, and executing change are all possible through the correct application of EA. In general, EA will make firms more agile, able to react quickly to external events and deal with shocks. Indeed, perhaps the best reason to have enterprise architecture has been revealed through the coronavirus, which has forced huge changes in the ways that organizations do business in rapid time. Those firms that could very quickly pivot to working from home and e-commerce were left in much better shape than others. Within the field of Enterprise Architecture are a host of sub architectures that represent different parts of the organization.

Tech partnership to drive Finland’s quantum computing project

Micronova, a national research and development infrastructure resource operated jointly by VTT and Aalto University, will provide the clean room environment to build the quantum computer and associated components at a dedicated facility at Espoo, southwest of Helsinki. The build will use Micronova’s specialised input and micro- and nanotechnology expertise to guide the project. The project marks the latest phase in cooperation between VTT and Aalto University. The two partners are also involved in a joint venture to develop a new detector for measuring energy quana. As measuring the energy of qubits lies at the core of how quantum computers operate, the detector project has the potential to become a game-changer in quantum technology. IQM’s collaborative role with VTT emerged following an international public tender process. All partners expect to see robust advances in the quantum computing project in 2021, said Jan Goetz, CEO of IQM. “This project is extremely prestigious for us,” said Goetz. “We will be collaborating with leading experts from VTT, so this brings a great opportunity to work together in ways that help build the future of quantum technologies.”

Data Governance for the Multi-Public Cloud: Top 10 AWS Best Practices

Start with building policies and write them into code, or scripts that can be executed. This requires compliance and cloud security experts working together to build a framework for your complex business. You cannot start from scratch as it will be error-prone and will take too long. Try to invest in some Cloud security tools then build your process and policies to run at scale to meet and exceed compliance and governance. ... Visibility means not only understand your inventory of assets which changes by the minute but at the same time understand the risk ratings for each asset and prioritize the remediation accordingly. Again, you will need to invest in some commercial tools that can provide the above. Risk analysis and constantly monitoring security policies to see if they are being enforced is not a simple task with home built scripts. ... Now, either you build all the integrations into all these tools or invest in some third-party tools. At some point, you need to comprehend the “Holistic” view of security or context around specific alert so that you can prioritize things, or else it will be lots of noise. Note none of the cloud vendors offer any holistic risk management tools.

Quote for the day:

"Integrity is the soul of leadership! Trust is the engine of leadership!" -- Amine A. Ayad

No comments:

Post a Comment