The characteristics of third generation DLTs are shifting markedly, and the blockchain vernacular is losing some of its mystique. Decentralisation distinguished the first generation blockchain, and some still say it’s essential. But let’s remember that the public blockchains don’t actually produce decentralisation; they are designed with decentralization as a starting point. Nakamoto rejected financial institutions, and the Bitcoin blockchain was designed to handle e-cash with no central authority. Yet nothing in the original design indicated that decentralisation could fit all types of business, nor that the blockchain could decentralise anything other than e-cash. Immutability is another word that’s becoming a bit stale. In my nearly twenty years experience in cybersecurity prior to blockchain, I don’t recall “immutability” ever being expressed as a requirement.
Market-based access to data and algorithms will lower entry barriers and lead to an explosion in new applications of AI. As recently as 2015, only large companies like Google, Amazon and Apple had access to the massive data and computing resources needed to train and launch sophisticated AI algorithms. Small startups and individuals simply didn’t have access and were effectively blocked out of the market. That changes now. The democratization of ML gives individuals and startups a chance to get their ideas off the ground and prove their concepts before raising the funds needed to scale. ... There is an effort underway to standardize and improve access across all layers of the machine learning stack, including specialized chipsets, scalable computing platforms, software frameworks, tools and ML algorithms.
Most banks’ customer strategies, fueled by customer analytics, will need to change to really take advantage of customers’ new channel preferences, for many different researches show that consumers who have grown up immersed in digital technologies, are two to three times more likely to want more digital interactions than what banks currently support, yet older customers are becoming surprisingly open to adding other channels to their portfolio and are increasingly experimenting with online interactions, using a wider variety of contact channels and apps. As a result, customers from all ages find it easier to compare a bank’s or financial institution’s promise with its delivery and how the overall experience meets their own expectations and, subsequently, make changes if they consider their bank isn’t as digitally ready as they would want it to be.
"The repository enables lawmakers to draw upon the database of legislation when drafting laws on cybercrime or electronic evidence," said Loide Lungameni, chief of the UNODC (UN Office on Drugs and Crime) Organized Crime Branch. " ... Established in conjunction with the 2013 Comprehensive Study on Cybercrime, the database is a response to the explosion of global connectivity at "a time of economic and demographic transformations, with rising income disparities, tightened private sector spending, and reduced financial liquidity." "Upwards of 80 percent of cybercrime acts are estimated to originate in some form of organized activity," the study determined, "with cybercrime black markets established on a cycle of malware creation, computer infection, botnet management, harvesting of personal and financial data, data sale, and 'cashing out' of financial information."
Where has Deep Learning helped NLP? The gains so far have not so much been from true Deep Learning as from the use of distributed word representations—through the use of real-valued vector representations of words and concepts. Having a dense, multidimensional representation of similarity between all words is incredibly useful in NLP, but not only in NLP. Indeed, the importance of distributed representations evokes the “Parallel Distributed Processing” mantra of the earlier surge of neural network methods, which had a much more cognitive-science directed focus (Rumelhart and McClelland 1986). It can better explain human-like generalization, but also, from an engineering perspective, the use of small dimensionality and dense vectors for words allows us to model large contexts, leading to greatly improved language models.
Innovation is the only sustainable way to make society wealthier and better off. In terms of real GDP, Americans are on average more than eight times wealthier today than they were in 1917 2. In the 16th century, Queen Elizabeth was practically the only person wearing silk stockings. In the 21st century, any American woman can. A similar point holds true for cars, plumbing, electricity, and a variety of other modern wonders that began as luxury goods. When technological unemployment occurs, laid-off workers seek retraining and private sector leaders create transitional infrastructure to reabsorb them into the economy. Innovative technologies create more wealth and better jobs in the end by eliminating unpleasant rote work and increasing overall productivity. In the past 30 years, we have experienced a complicated period of globalisation.
Today already 40 million people use app-enabled carpooling services, and the usage of ridehailing apps has grown rapidly to over 70 million users. Frost & Sullivan’s mobility research has highlighted the continued trend of the automotive industry investing in dedicated collaborations. “As information services, in particular, become more sophisticated, the potential to integrate and aggregate mobility services is increasing,” explains Shwetha Surender, Program Manager Mobility. This allows users to plan, book and pay for their journeys on the smartphone in real time. To make this effective, partnerships between both private and public transport providers are essential. The revenue potential of such digital mobility services is expected to rise to ~$2 trillion by 2025 globally, explaining the continued interest from the private sector.
Startups have the advantage of being free of legacy technology systems and tough regulation, both of which limit the digital developments of established financial services firms. As a result, start-up companies can more efficiently create mobile-focused services or products that threaten existing financial companies. For example, a number of mobile-based banks such as Atom, Tandem, Starling and Monzo have emerged in the past year with the aim of offering current accounts that help customers to manage their money and lifestyle. Some fintech start-ups pose a direct threat by capitalising on weaknesses and gaps left by established companies. Nutmeg in the UK, for example, provides low-cost online wealth management, which makes investment expertise accessible to millions of people who cannot afford advice but do not have the confidence to go it alone.
The dump of Windows exploits -- arguably affecting the most people and organizations and likely to cause the most damage and embarrassment to the intelligence agency -- has been expected since the hacking group first emerged on the scene last year. In case you missed it, hacking tools that were confirmed to belong to the NSA's so-called Equation Group were stolen last year in one of the biggest breaches of classified files since the Edward Snowden revelations. These tools, allowed NSA analysts to break into a range of systems, network equipment, and firewalls, and most recently tools to target the Linux operating system -- many of which were old and outdated. The group attempted to auction off the files but failed, and have been releasing portions of the stolen files in stages.
Ever since the UK shocked the world (and, maybe, itself) by voting to exit the European Union, pundits have prognosticated on what effects this will have on the economy and society. While many think it’s too early to say, UK skills sourcing company Arrows Group broke cover and came out with a notable statement, suggesting that Brexit is already leading to a 10 per cent reduction in skilled tech workers from within the EU relocating to the UK. Conversely, the company says there is an increase in UK digital skills heading elsewhere, notably Switzerland. The Arrows database used for this research only covers about 2,000 contractors but as an early indicator of what is going on its insights might have some value. With that caveat, I followed up with Arrows founder and CEO James Parsons and the following is a lightly edited version of our email exchange.
Quote for the day:
"A computer will do what you tell it to do, but that may be much different from what you had in mind." -- Joseph Weizenbaum