In 1896, the Lumiere brothers released a 50-second-long film, The Arrival of a Train at La Ciotat, and a myth was born. The audiences, it was reported, were so entranced by the new illusion that they jumped out of the way as the flickering image steamed towards them. The urban legend of film-induced mass panic, established well before 1900, illustrated a valid contention if the story was, in fact, untrue: The technology had produced a new emotional reaction. That reaction was hugely powerful but inchoate and inarticulate. Nobody knew what it was doing or where it would go. Nobody had any idea that it would turn into what we call film. Today, the world is in a similar state of bountiful confusion over the creative use of artificial intelligence. Already the power of the new technology is evident to everyone who has managed to use it.

'These bits of data shape a driver and can make him either a very good driver, a good driver, or a bad driver--it's just how you use it.'

Instagram is testing new ways to verify age, including asking followers to verify their age and even using artificial intelligence (AI) that can …

A GOOGLE engineer who says the tech giant has created a'sentient AI child' is now claiming it could escape and do "bad things". Engineer Blake Lemoine has been suspended by Google, which says he violated its confidentiality policies. News of Lemoine's claims broke earlier in June but the 41-year-old software expert has since suggested to Fox News that the AI could escape. In a recent interview, he described the AI as a "child" and a "person". He said: "Any child has the potential to grow up and be a bad person and do bad things."

The large majority of human activities require collaborations within and across formal or informal teams. Our understanding of how the collaborative efforts spent by teams relate to their performance is still a matter of debate. Teamwork results in a highly interconnected ecosystem of potentially overlapping components where tasks are performed in interaction with team members and across other teams. To tackle this problem, we propose a graph neural network model designed to predict a team's performance while identifying the drivers that determine such an outcome. In particular, the model is based on three architectural channels: topological, centrality, and contextual which capture different factors potentially shaping teams' success. We endow the model with two attention mechanisms to boost model performance and allow interpretability. A first mechanism allows pinpointing key members inside the team. A second mechanism allows us to quantify the contributions of the three driver effects in determining the outcome performance. We test model performance on a wide range of domains outperforming most of the classical and neural baselines considered. Moreover, we include synthetic datasets specifically designed to validate how the model disentangles the intended properties on which our model vastly outperforms baselines.

The Oscar-winning studio has produced visual effects for movies like "Titantic," "The Curious Case of Benjamin Button" and several Marvel films. To create the photorealistic characters seen in "The Quarry," it used the AI facial capture system Masquerade, which was developed to replicate Josh Brolin's likeness for his character Thanos in "Avengers: Infinity War." Masquerade was originally designed to do one thing: to take the performance from a head-mounted camera and translate it into a digital mesh that could then be rendered in a movie. For "The Quarry," the VFX team needed something that could track the movement and facial expressions of actors and create digital characters that could be edited in real time. So they built Masquerade 2.0.

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Welcome to our June 2022 monthly digest, where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we find out about meta-learning, explore the importance of images in communicating about AI, and ponder over who to vote for in the AI Song Contest. In the latest episode of New voices in AI, Oumaima Hajri shares her work and journey in ethical AI. Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, and Satinder Singh won an ICLR 2022 outstanding paper award for their work Bootstrapped meta-learning. We spoke to Sebastian about how the team approached the problem of meta-learning, how their algorithm performs, and plans for future work.

Now that consumers expect speed and hyper-personalization in all things, marketers have to find innovative ways to meet demands and maximize their budgets. To do this, marketers are turning to artificial intelligence and machine learning. In fact, there is a new term just for this – "AI Marketing." Customer expectations have never been higher. Amazon, Netflix and Google have set the standard for what customers have come to expect from technology and marketing.

Combining the biological data generated from Body-on-a-Chip with the computational power of machine learning and Artificial Intelligence should …