Recent advancements in AI foundation models have made it possible for them to be utilized off-the-shelf for creative tasks, including ideating design concepts or generating visual prototypes. However, integrating these models into the creative process can be challenging as they often exist as standalone applications tailored to specific tasks. To address this challenge, we introduce Jigsaw, a prototype system that employs puzzle pieces as metaphors to represent foundation models. Jigsaw allows designers to combine different foundation model capabilities across various modalities by assembling compatible puzzle pieces. To inform the design of Jigsaw, we interviewed ten designers and distilled design goals. In a user study, we showed that Jigsaw enhanced designers' understanding of available foundation model capabilities, provided guidance on combining capabilities across different modalities and tasks, and served as a canvas to support design exploration, prototyping, and documentation.

When you apply for a career in tech, it often means having to decide: Am I a product manager? These roles are all clearly defined with their own sets of mostly nonoverlapping skills to help companies hire the right talent. But that's not the way we define ourselves. Most of us have a variety of skills that don't all neatly fall into one box. We collect skills across multiple dimensions over a lifetime of different experiences.

In this special issue we are reprinting our top stories of the past year. This article first appeared online in our "Mind" issue in March, 2021. The 21st century is a time of great scientific discovery. Vaccines against deadly new viruses are created in less than a year. The latest Mars Rover is hunting for signs of alien life.

Imagine you have a jigsaw puzzle with 10,000 pieces but no picture on a box. In fact, you don't even have the box--it was destroyed nearly 2,000 years ago. These puzzle pieces are fragments of frescoes in the ancient Roman city of Pompeii that were leveled or buried by the eruption of Mount Vesuvius in A.D. 79. Some pieces are missing, others are broken. And instead of being precisely-cut shapes designed to neatly interlock, they're damaged, irregular fragments.

The 21st century is a time of great scientific discovery. Vaccines against deadly new viruses are created in less than a year. The latest Mars Rover is hunting for signs of alien life. But we're also surrounded with scientific myths: outdated beliefs that make their way regularly into news stories. Being wrong is a normal and inevitable part of the scientific process.

Before you start building an Artificial Intelligence solution it is important to define clear ... [ ] business objectives and success metrics. Business managers these days are challenged by the sheer scale of the learning curve presented by the artificial intelligence domain and many concepts such as machine learning, big data, cloud, data infrastructure and engineering that form part of the ecosystem and journey towards AI. The field of Artificial Intelligence is vast, the subject matter a fusion of multiple disciplines - from philosophy and behavioural economics to neuroscience and computer science - and is rapidly changing. What is more, it comes with a reputation and promise that few technologies other than perhaps the internet and blockchain could lay claim to: the promise to completely revolutionise society, industry and our lives. So how something so revolutionary be so poorly understood to the public?

Artificial Intelligence is like Lego; to build something nice, you need to combine the right pieces in the right way. Most of us have played with Lego when we were small. I did at least and I absolutely loved it. I can remember the days when my friends and I were playing with Lego for hours on end, constantly creating new structures and building complete cities. We loved it and I am sure it stimulated my creativity. Even adults still play with Lego, often in group exercises to get some creativity flowing.

New mobile machine learning capabilities are coming to Apple devices, thanks to IBM Watson and Apple Core ML. Under CEO Tim Cook's leadership, Apple has been angling for an ever-bigger slice of the enterprise pie. Last year we saw the technology giant partner with GE to bring the industrial predictive and analytics capabilities of the Predix IIoT platform to Apple's iOS. But for the past few years Apple has been deepening and extending its ties with IBM too. When the two companies announced their strategic partnership in 2014, Tim Cook and IBM CEO Virginia Rometty claimed that "Apple and IBM are like puzzle pieces that fit perfectly together."

Artificial Intelligence is like Lego; to build something nice, you need to combine the right pieces in the right way. Most of us have played with Lego when we were small. I did at least and I absolutely loved it. I can remember the days when my friends and I were playing with Lego for hours on end, constantly creating new structures and building complete cities. We loved it and I am sure it stimulated my creativity. Even adults still play with Lego, often in group exercises to get some creativity flowing.

You should probably be thrilled to be alive these days. Every week brilliant researchers present new breakthroughs in scientific papers that extend our understanding of who we are (groundbreaking accuracy of CRISPR/Cas9 genome editing), how the universe began (the recent discovery of gravitational waves), and what computers can learn (phenomenal advances in deep-learning techniques). Yet, as a regular consumer of scientific research, I'm frustrated that the current knowledge comes in puzzle pieces: a research paper presented in a conference here and another recommended by a friend there. Existing tools aren't particularly helpful when it comes to solving this problem. Finding relevant academic studies can take days, sometimes even weeks as Google Scholar, Microsoft Academic, and other existing tools give millions of results, the vast majority of which are not valuable to your search.