WHY IT MATTERS: Digital Transformation

A detailed study of machine intelligence in industrial and manufacturing operations reveals the surprisingly different paths companies can take. But a group of leaders shares similar characteristics.

Artificial intelligence today plays a massive role in strengthening and transforming industries around the world. In this article, we’ll go over all of the newest artificial intelligence statistics to help you determine if AI is right for your business’s future.

Sometimes the centre of gravity in tech is very clear, but as we enter 2022 there are lots of areas where trillion dollar questions are wide open. These are the questions I wonder about today, from crypto to cars to fast fashion - there are others.

The human brain is pretty tricky: While we think we know things, there’s a whole list of cognitive biases that can be gumming up the works.

Boards can add value to their business’s digital transformation in five specific areas.

We surveyed more than 3,000 CEOs around the world to learn how they are positioning their organizations for success after COVID-19. Five key factors set outperforming CEOs apart.

Covid brought shock and a lot of broken habits to tech, but mostly, it accelerates everything that was already changing. 20 trillion dollars of retail, brands, TV and advertising is being overturned, and software is remaking everything from cars to pharma. Meanwhile, China has more smartphone users than Europe and the USA combined, and India is close behind - technology and innovation will be much more widely spread. For that and lots of other reason, tech is becoming a regulated industry, but if we step over the slogans, what does that actually mean? Tech is entering its second 50 years.

cette édition du Québec économique montre comment les innovations numériques au sein de nos organisations publiques et privées touchent actuellement tous les secteurs de notre économie, faisant de la transformation en cours une véritable révolution numérique sur le marché de l’emploi, mais également dans le monde de l’éducation et de la formation. L’écosystème d’innovation et de collaboration qui se met en place au Québec et au Canada, principalement autour de l’IA, fait l’objet d’analyses poussées dans cet ouvrage.

There’s an old saying that the first fifty years of the car industry were about creating car companies and working out what cars should look like, and the second fifty years were about what happened once everyone had a car - they were about McDonalds and Walmart, suburbs and the remaking of the world around the car, for good and of course bad. The innovation in cars became everything around the car. One could suggest the same today about smartphones - now the innovation comes from everything else that happens around them.

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 hype about artificial intelligence is unavoidable. From Beijing to Seattle, companies are investing vast sums into these data-hungry systems in the belief that they will profoundly transform the business landscape. The stories in this special report will deepen your understanding of a technology that may reshape our world.

Technological change driving ‘creative destruction’ in jobs market, says OECD

Global research highlights how AI is changing the relationship between people and technology at work.

Get a copy of the playbook Leading Upskilling Initiatives in Data Science & Machine Learning, compliments of Dataiku.

The A.I. Age | This 12-month series of stories explores the social and economic questions arising from the fast-spreading uses of artificial intelligence. The series is funded with the help of the Harvard-MIT Ethics and Governance of AI Initiative. Seattle Times editors and reporters operate independently of our funders and maintain editorial control over the coverage.

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.

Bien que l'intelligence artificielle est sur toutes les lèvres, très peu de gestionnaires sont familiers avec les différentes applications qu'offrent l'IA et surtout, comment concrètement l'implanter au sein de leur organisation. C'est ce que nous tenterons de démystifier dans ce webinaire qui portera sur les différentes étapes d'une transformation digitale. Joignez-vous à nous pour savoir;

• Par où commencer ?
• Les questions à se poser
• Comment faire l'état des lieux
• Quels acteurs impliquer
• Comment éviter le ''trip'' technologique

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.

It’s where forward-thinking managers should be focusing.

1. First, catalogue your business processes. 
2. Second, focus on simple problems. 
3. Third, don’t use machine learning where standard business logic will suffice.
4. Fourth, if a process is complicated, use machine learning to create decision support systems.

Digital business is accelerating interest in artificial intelligence (AI) at a pace that has left many CIOs hurrying to build an AI strategy and investment plan appropriate for their enterprise.  
CIOs are in the perfect position to educate their company’s CEO and board about recent developments in artificial intelligence and show how AI might influence their business and competitive landscape. 
Gartner’s e-book provides actionable insights and advice to create and implement a plan for artificial intelligence in the enterprise, make the business case to the c-suite and the board, and build the right AI data. 

By now you understand that AI is mainstream. We carry it around in our phones, it’s installed in our automobiles and household appliances. But how should you be thinking about using AI in your business? Start by considering the data managed by your company. What can your data teach you about your business? What can you automate or streamline using your data? If there are repetitive processes in your business, AI can be used to automate those processes.
For example, if you have large customer data sets, it is likely you can use machine learning to let the data tell you more about those customers, give you intelligent insights that will help you to create a more customer focused offering. Examples: Retail banks use AI to offer appropriate banking products tailored for individual customers. Insurance companies use AI to verify identity, assess risk profiles and recommend coverage. Companies are using ML to sort though massive resumes to find the best matches for new employees.

One former employee claims it’s one of the most expensive research and development projects in the company’s history, though Kumar disputes that, saying the stores use off-the-shelf hardware and Amazon’s existing cloud computing infrastructure. Still, considering the dense placement of cameras and sensors, and the tech-support crews that are on call at all hours of the week, it’s much more expensive than running, say, a 7-Eleven, which could be staffed by a single cashier and—with the possible exception of the Slurpee machine—have little in the way of bespoke technology.

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.