The global investment banking industry is worth a few hundred billion dollars annually, as are both the audit and legal professions. And since the last decade or so, increased regulation has forced banks to devote around 10% of their salary costs to employing an army of compliance controllers to ensure that their transactions and processes meet the standards required by the law. And the stakes are high. Rogue traders, breaches of confidentiality, and reckless financial positions can expose financial institutions to fines, cripplingly negative publicity, and even prison sentences, not to mention huge financial losses. These stakes are what make banks the earliest adopters of many technological innovations.
A couple of weeks ago a friend of mine asked me about my opinion on IOTA, it's usability and future prospects. I would like to share my thoughts about IOTA on Seekingalpha, I am always open for feedback and willing to discuss about the things I say in my article. To understand the benefits of IOTAs "tangle" against the blockchain, we have to get some facts about the blockchain, as an example we will use Bitcoins blockchain and its classical proof-of-work system. In the Bitcoin-Blockchain we can and now have to distinguish between miners and issuer of transactions. These are roughly the steps a transaction on the bitcoin network has to go through to be part of the blockchain and therefore accepted, but even after these steps it is recommended (or was since the 6-block-rule is from the very beginning) to wait until 6 block are added to the block where the transaction has been issued.
There's only one constant in business – and that's that things change. And that change has been accelerating in recent years. Businesses have had to adjust to new ways of doing things, most of them related to the digital transformation that business, and the world, has experienced in recent years. From artificial intelligence (AI), to blockchain and the Internet of Things (IoT), new digital technologies are having a major impact on business – and that impact will only grow in 2018. And companies can't afford to ignore the trend.
This was the case with the advent of ERP (allowing greater oversight of a company's finances), Big Data (most notably in the context of risk management), and recently Blockchain tech (enabling a raft of new online financial transactions hitherto impossible). The burgeoning potential of Artificial Intelligence (AI) looks set to continue this trend. The reason for this is that the nature of finance is quantitative, and advances in computing readily lend themselves to number crunching and data analysis, more so than in other business domains. As such, any time there is a leap in the capabilities of what computers can handle, the practical use-cases in finance are never far behind this expanding frontier. Raw data is the fundamental resource of both finance and computer science – while the more eye-catching applications in AI (like autonomous military agents) are a long way from being practical, AI applications in finance will have a substantial impact in the next 1-3 years.
Due to the exponential growth and development of technology in the last couple decades, the computing world can be broken up into three core technologies: cognitive (AI), connected (IoT), and distributed (Blockchain/Digital-Currency) computing. The'trinity' works together because each type of computing tackles the others' weaknesses and drawbacks. For instance, the main problems of cognitive and connected computing regarding ethics, security, and privacy can be addressed by distributed computing. The main problems of limited hardware and detailed data for distributed and cognitive computing, respectively, can be addressed by connected computing. The main problems of customer protection and automation limitations for distributed and connected computing, respectively, can be addressed by cognitive computing.
The Future of AI: Blockchain and Deep Learning First point: considering blockchain and deep learning together suggests the emergence of a new class of global network computing system. These systems are self-operating computation graphs that make probabilistic guesses about reality states of the world. Second point: blockchain and deep learning are facilitating each other's development. This includes using deep learning algorithms for setting fees and detecting fraudulent activity, and using blockchains for secure registry, tracking, and remuneration of deep learning nets as they go onto the open Internet (in autonomous driving applications for example). Blockchain peer-to-peer nodes might provide deep learning services as they already provide transaction hosting and confirmation, news hosting, and banking (payment, credit flow-through) services.
The Data Science Trends for 2018 are largely a continuation of some of the biggest trends of 2017 including Big Data, Artificial Intelligence (AI), Machine Learning (ML), along with some newer technologies like Blockchain, Edge Computing, Serverless Computing, Digital Twins, and others that employ various practices and techniques within the Data Science industry. The Dataconomy article titled The Future of Big Data Is Open Source aptly captures the industry buzz that dominated the last part of 2016 and the entire 2017. Then, Big Data and Data Science were the biggest industry buzzwords, but a lot has changed since then. In 2016, and 2017, Big Data was a market differentiator for businesses, and continues to be. Now, as we enter 2018, there are numerous new technologies that will coordinate within the greater foundations of Data Science and Big Data, and expand such industries into new spaces that are only beginning to be understood and appreciated.
In their excellent laymans explanation A Framework for Identity, Dan Elitzer of the IDEO coLAB summarizes their recent work with Boston universities like MIT and Harvard, focused on exploring the key dynamics of the emergent blockchain, especially it's generalized role as a new Identity infrastructure. The fusion of the Blockchain and Digital Identity, will play a keystone role in enabling advanced Digital Government features like a unique Blockchain Identity, as is described in this video, where they propose they're implementing the first Blockchain ID. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA. Join Cloud Expo / @ThingsExpo conference chair Roger Strukhoff (@IoT2040), June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA for three days of intense Enterprise Cloud and'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets.
Just when many companies are finally beginning to move toward cloud computing, edge computing -- driven by the sheer volume and speed of information produced by the IoT--is jumping to the forefront of the business scene. As smart drones, autonomous vehicles, and other AI-powered smart devices seek to connect and communicate instantly via the IoT, the matter of sending data "all the way" to the cloud will become highly impractical. Many of these devices will need real-time response and processing, making edge computing the only viable option. Companies will continue to use AI to surprise, connect, and communicate with their customers in ways they may not even appreciate or realize.
From a business perspective, the use of AI (AKA cognitive computing) can transform the consumer landscape. However, there is another type of product that integrates AI systems into their already existing business models (the technology is secondary to the business). This statement comes at a time when the country pledges a multibillion dollar investment initiative for AI startups and research. While the technology behind such weapons are likely to kept close secret, it begs the question as to how much governments like China will keep cutting edge research for consumer products within their borders.