The booming growth of machine learning and artificial intelligence (AI), like most transformational technologies, is both exciting and scary. It’s exciting to consider all the ways our lives may improve, from managing our calendars to making medical diagnoses, but it’s scary to consider the social and personal implications.
Spark can handle pretty much any data store you throw at it and data scientists can use a common way of thinking about data (SQL) for handling it. You don’t have to use the SQL-like interface, but it’s there, and many take advantage of it. Don’t care for the SQL/HQL aproach? That’s fine, you can use Spark like many use bash for data wrangling. Spark spans many skill levels.
Your business needs should dictate what your IoT platform is. Not vendor definitions. They come in all shapes and sizes. Hoards of them. They are called IoT Platforms. They are hard to differentiate. They combine two words that we wax eloquent trying to describe. IoT and Platform.
The complexity of building out an IoT solution from scratch can be daunting, indeed. Devices must be designed and built, or suitable COTS devices identified, networks created, security — both physical and cyber — put into place, databases and software architected, connectivity purchased. That kind of a complex build-out is costly.
Today, there is a new gold rush, sparked by the Internet of Things (IoT). The news is filled with stories of self driving cars, smart solutions, and smart cities. Everyone has a disruptive idea that is going to change the world. Thousands of companies, new and established, are planning “smart” solutions. Marketing, hype and confusion are one and the same. And we’re just getting started.
In the burgeoning IoT space, a number of company’s are creating and acquiring their way to a full stack offering – lets call them the ‘Full Stacks.’ The other end of the spectrum represents best of breed integrations that we’ll call the ‘Custom Stacks.’ Clients, such as OEM’s, seeking to develop an IoT solution are faced with a strategic decision of either buying a ‘Full Stack’ or assembling a ‘Custom Stack.’ Both approaches, and in between, require integration, a separate topic, but are viable options and all come with pros and cons.
What we needed was a protocol and network, on which data marketplaces can be built. This is Ocean. Its network (running the Ocean protocol) handles storing of the metadata (i.e. who owns what), links to the data itself, and more. On top of Ocean there can be thousands of data marketplaces and exchanges, all accessing the same data. Each marketplace acts as the last mile in connecting buyers and sellers.
We are now in the era of the customer. The control around product development, customer access to information and customer engagement has gone from the brands to the hands of the customers. This means that the customers share their product reviews with the world, have access to competitive pricing information with a simple click, and drive product innovation and development at a demanding and breathtaking pace.
AI is more than a “tool” that improves, for instance, manufacturing processes. It is more than the next step in compliance. It is more than a system to make predictions that facilitate action. It is probably even more than a disruptor of “knowledge work”, more generally.
The emergence of “digital twin” technology will revolutionize how industrial enterprises approach manufacturing operations. Digital twins unite physical entities with virtually-modeled “twins” based on technologies like AI and Big Data derived from IoT sensors, ultimately improving the design and execution of manufacturing and maintenance life cycles as well as creating new revenue streams and services. Vince is a platform and product executive spanning cloud, mobile, big data, analytics, and artificial intelligence offerings. He is a leader of global product management, design, and GTM teams that consistently delivered outstanding business results.
Like their conventional counterparts, smart contracts define an agreement between parties that is binding. Payments from one party to another can be scheduled to process on a particular date, or triggered by a set of predetermined conditions. But while paper contracts are bound by law and subject to interpretation by legal professionals, smart contracts are secured by the blockchain.
Global insurance industry is entering a distinct phase of disruptive change driven by the Internet of Things (IoT). While the insurance industry has undergone significant technology-driven change in the last fifteen years, the basic insurance modus operandi has remained the same. However, as the industry enters this new phase, emerging IoT-based insurance propositions threaten to undermine today’s long established insurance offerings particularly in some of the largest mainstream sectors.
Now, big data technology is quietly transforming every enterprise backend on the planet. For example, in many places “data warehouses” of relational databases are getting replaced by “data lakes” running big data software. More than $100B annually is going towards big iron compute clusters, the software on top, and the services to keep it all running smoothly.
Success depends on not just great data but also on how well the enterprise coordinates its efforts to realize benefits that are greater than the sum of individual contributions. Here are a few key lessons and guidance on how to bridge the chasm that too often separates big data and wise decisions.
In today’s big data world, AI and machine learning applications already analyze massive amounts of structured and unstructured data and produce insights in a fraction of the time and at a fraction of the cost of consultants in the financial markets. Moreover, machine learning algorithms are capable of building computer models that make sense of complex phenomena by detecting patterns and inferring rules from data — a process that is very difficult for even the largest and smartest consulting teams. Perhaps sooner than we think, CEOs could be asking, “Alexa, what is my product line profitability?” or “Which customers should I target, and how?” rather than calling on elite consultants.
In financial services, the dangers associated with monetizing big data are nearly as great as the rewards. The promises of machine learning, data science and Hadoop are tempered by the realities of regulatory penalties, operational efficiency and profit margins that must quickly justify any such expenditure.
Blockchain technology could transform AI too, in its own particular ways. Some applications of blockchains to AI are mundane, like audit trails on AI models. Some appear almost unreasonable, like AI that can own itself — AI DAOs. All of them are opportunities. This article will explore these applications.
In this article, we discuss five different ways blockchain will fit into your company in less than ten years from now. So let’s start with the basics: what is blockchain exactly? Put simply, a blockchain is a database. It’s an ever-growing database of different kinds of data and it has quite remarkable properties:
The proliferation and ‘smartening’ of IoT-driven devices is projected to reach a market cap exceeding $195 billion in 2023, according to analysts at ReportsnReports. From a market of $16 billion in 2016, this growth is mainly fueled by the increasingly ubiquitous manufacturing of smarter in-home, mobile, and transportation devices — and the need to capture that data and enhance communication infrastructure.
Ethereum is the subject of a lot of hype lately. It is praised by some as the new internet or the world’s computer and criticised by others as a platform that enables widespread scams and ponzi schemes to thrive. I see badly informed articles about Ethereum, smart contracts, DApps, DAO’s, ICO’s and tokens on the daily so it is time to analyse the subject. I will present the argument that Ethereum might form the main protocol enabling the ‘internet of value’.
The future of insurance could flourish through an intelligent adoption of Blockchain, with applications in digital currencies, fraud solutions and smart contracts. Large insurers have the potential to benefit immensely. However, its implementation will mean that insurance companies will have to change their underwriting process, the structure of the policy, as well as risk underwriting.
A growing cadre of people are recognizing that blockchain is in fact the “killer app” of the digital currency era, going as far as likening it to a foundational technology. A growing number of entrepreneurs and investors are crowding in to the blockchain space all seeking to answer the core question: “If blockchain could not exist without the internet, what could not exist without blockchain?”
The IIoT offers the potential for significant improvements in manufacturing productivity and quality by providing information on every aspect of productive assets while enabling people and programs to make the necessary adjustments to optimize their performance.
This article will help you get a better grasp of the future of cryptocurrency. After you finish it, you’ll clearly see how these technologies are poised to join the mainstream. So, when will this dizzying race come to an end? Is there real value in the blockchain craze? Can it possibly live up to the expectations created by so many rivers of newsprint?