WHY IT MATTERS: Digital Transformation

Organizations should first consider how the behind-the-scenes logistics of their “Full Service 2.0” offering will be best facilitated by advances in technology. Ride-sharing services could provide a chauffeur-like experience by modifying their algorithms to allow a user to request trips with the same driver instead of the first available car. Hotels may accelerate the introduction of robots to handle room deliveries or other in-room services in a socially distant manner. Technology gives organizations new options to address the previously high costs of high-touch, full-service models or the uncertainties around service and delivery times that turned away consumers from these services.

In our experience, technical due diligence is the single biggest differentiator of deals done well—or poorly. What’s more, technical due-diligence failures can usually be avoided. Almost always, the disappointed acquirer insufficiently vets the technology and discovers too late that it fails to work as advertised. Or the technology does work, but only in constrained environments, and won’t scale. In other cases, crucial parts of the IP turn out not to be owned by the seller.

Every Western institution was unprepared for the coronavirus pandemic, despite many prior warnings. This monumental failure of institutional effectiveness will reverberate for the rest of the decade, but it's not too early to ask why, and what we need to do about it... Our nation and our civilization were built on production, on building. We built roads and trains, farms and factories, then the computer, the microchip, the smartphone, and uncounted thousands of other things that we now take for granted, that are all around us, that define our lives and provide for our well-being. There is only one way to create the future we want for our own children and grandchildren, and that's to build.

Which technology trends are most likely to impact your business in the coming years? Trends are waypoints to help anticipate future states in a world where uncertainty looms. The Future Today Institute's annual Tech Trends Report asks you to examine your assumptions, cherished beliefs and expectations for the future using a bolder, more holistic perspective. In the 13th edition of our Tech Trends Report, we forecast the key technology trends that will redefine businesses in the coming years. More importantly, we offer strategic analysis and guidance on those trends and further explore them in future scenarios to help you understand their implications on your organization and industry.

The Fourth Industrial Revolution represents a fundamental change in the way we live, work, and relate to one another. It is a new chapter in human development, enabled by technology advances that are commensurate with those of the first, second and third industrial revolutions, and which are merging the physical, digital, and biological worlds in ways that create both promise and peril. The speed, breadth, and depth of this revolution is forcing us to rethink how countries should develop, how organizations create value, and even what it means to be human. Now, as the world grapples with COVID-19, there is an opportunity to further harness the power of the revolution in ways that create a more inclusive, human-centred global economy.

When Google researchers presented a deep bidirectional Transformer model that addresses 11 NLP tasks and surpassed even human performance in the challenging area of question answering, it was seen as a game-changer in NLP/NLU.

Le livre blanc, une initiative de l’industrie des technologies du Québec portée et mobilisée par TechnoMontréal vise à rassembler les nombreuses visées des acteurs de notre industrie sous une seule vision. C’est une démarche de consultation publique auprès de plus de 450 entreprises et organismes en technologies afin de les accompagner à mieux définir les besoins de l’industrie et à proposer des solutions concrètes pour influencer le développement proactif de stratégies numériques d’envergure!

The MarTech marketplaces that RSG covers continue to evolve rapidly and have become more complex (with more overlaps!) this year. The Customer Data Platform (CDP) market is no different - with new vendors, more investment, emerging niches, and evolving use cases.

On earth and in space, there are almost no unexplored regions. But a new atlas of blank spaces is emerging, which will enable an age of astonishing discovery.

The WSE (pronounced “wise”) is the largest commercial chip ever manufactured, built to solve the problem of deep learning compute. The WSE is 1.2 trillion transistors, packed onto a single 215mm x 215mm chip with 400,000 AI-optimized cores, connected by a 100Pbit/s interconnect. The cores are fed by 18 GB of super-fast, on-chip memory, with an unprecedented 9 PB/s of memory bandwidth.

Superlatives abound at Cerebras, the until-today stealthy next-generation silicon chip company looking to make training a deep learning model as quick as buying toothpaste from Amazon. Launching after almost three years of quiet development, Cerebras introduced its new chip today — and it is a doozy.

Succeeding is no longer just about who’s able to build the technology, or who’s first to market. It’s about who’s got the best experience.

Machine learning continues to gain traction in digital businesses, and technical professionals must embrace it as a tool for creating operational efficiencies. This updated primer discusses the benefits and pitfalls of machine learning, architecture updates, and new roles and responsibilities.

Focusing on business processes can lead companies to end up with multiple systems that perform similar functions, such as customer-relationship management. Concentrating too much on technology can cause EA teams to organize their work around building applications rather than enabling the business.

The retail industry is rewriting the laws of physics. Change is coming at an ever faster rate each year and 2030 will be upon us before we know it. Explore the world in 2030 and the future of retail 2030.  

This report presents LibraBFT, a robust and efficient state machine replication system designed for the Libra Blockchain. LibraBFT is based on HotStuff, a recent protocol that leverages several decades of scientific advances in Byzantine fault tolerance (BFT) and achieves the strong scalability and security properties required by internet settings. LibraBFT further refines the HotStuff protocol to introduce explicit liveness mechanisms and provides a concrete latency analysis. To drive the integration with the Libra Blockchain, this document provides specifications extracted from a fully-functional simulator. These specifications include state replication interfaces and a communication framework for data transfer and state synchronization among participants. Finally, this report provides a formal safety proof that induces criteria to detect misbehavior of BFT nodes, coupled with a simple reward and punishment mechanism.

We present Move, a safe and flexible programming language for the Libra Blockchain. Move is an executable bytecode language used to implement custom transactions and smart contracts. The key feature of Move is the ability to define custom resource types with semantics inspired by linear logic: a resource can never be copied or implicitly discarded, only moved between program storage locations. These safety guarantees are enforced statically by Move’s type system. Despite these special protections, resources are ordinary program values — they can be stored in data structures, passed as arguments to procedures, and so on. First-class resources are a very general concept that programmers can use not only to implement safe digital assets but also to write correct business logic for wrapping assets and enforcing access control policies. The safety and expressivity of Move have enabled us to implement significant parts of the Libra protocol in Move, including Libra coin, transaction processing, and validator management.

The Libra Blockchain is a decentralized, programmable database designed to support a low-volatility cryptocurrency that will have the ability to serve as an efficient medium of exchange for billions of people around the world. We present a proposal for the Libra protocol, which implements the Libra Blockchain and aims to create a financial infrastructure that can foster innovation, lower barriers to entry, and improve access to financial services. To validate the design of the Libra protocol, we have built an open-source prototype implementation — Libra Core — in anticipation of a global collaborative effort to advance this new ecosystem.

To get a deeper understanding of the lifecycle of a Libra transaction, we will follow a transaction on its journey from being submitted to a Libra validator to being committed to the Libra Blockchain. We will then “zoom-in” on each logical component of a validator and take a look at its interactions with other components.

The Libra Blockchain is a cryptographically authenticated distributed database, and it is based on the Libra protocol. This document briefly describes the key concepts of the Libra protocol. For a detailed description of all the elements of the Libra protocol, refer to the Libra Blockchain technical paper

Here are all the slides, plus analysis from Recode.

Fortune summary: tech firms are focusing on privacy; more people are using images to communicate; Twitter and Amazon are making small in-roads into the Facebook-Google ad duopoly; 51% of the world's population is now online.

LUMA is the leading investment bank focused on digital media and marketing. We provide strategic advice, proven M&A expertise, and extensive industry knowledge to optimize outcomes for our clients.

In Tetlock’s 20-year study, both the broad foxes and the narrow hedgehogs were quick to let a successful prediction reinforce their beliefs. But when an outcome took them by surprise, foxes were much more likely to adjust their ideas. Hedgehogs barely budged. Some made authoritative predictions that turned out to be wildly wrong—then updated their theories in the wrong direction. They became even more convinced of the original beliefs that had led them astray. The best forecasters, by contrast, view their own ideas as hypotheses in need of testing. If they make a bet and lose, they embrace the logic of a loss just as they would the reinforcement of a win. This is called, in a word, learning.