Go, Team Robot…

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Slack GPT and Einstein GPT for Salesforce users currently under development…

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The new updates to Google Cloud’s machine learning service will help the company square up against rivals such as Microsoft, AWS and IBM.

Read the full article at: www.infoworld.com

A futuristic demonstration of emerging renewable energy material – printed solar cells, is being trialled in a public setting for the first time as it nears commercial readiness.

 

Creator of the organic printed solar material, Physicist Professor Paul Dastoor from the Faculty of Science said his team were excited to take their ‘science to the streets’ in what represented significant progress toward commercial availability of the material. “Globally, there’s been so few of these installations, we know very little about how they perform in a public setting. This installation is the next critical step in accelerating the development and commercialization of this technology. It presents a new scenario for us to test performance and durability against a range of new challenges,” said Professor Dastoor.

 

Read the full article at: www.newcastle.edu.au

Apple is working on a paid AI-powered health coach that’s codenamed “Quartz,” according to Bloomberg. The company is also reportedly developing a Health app for iPad as part of iPadOS 17.

Read the full article at: www.theverge.com

Read the full article at: www.theverge.com

Stanford University researchers have developed a generative AI model that can choreograph human dance animation to match any piece of music. It’s called Editable Dance GEneration (EDGE).

 

“EDGE shows that AI-enabled characters can bring a level of musicality and artistry to dance animation that was not possible before,” says Karen Liu, a professor of computer science who led a team that included two student collaborators, Jonathan Tseng and Rodrigo Castellon, in her lab. The researchers believe that the tool will help choreographers design sequences and communicate their ideas to live dancers by visualizing 3D dance sequences. Key to the program’s advanced capabilities is editability. Liu imagines that EDGE could be used to create computer-animated dance sequences by allowing animators to intuitively edit any parts of dance motion.

 

For example, the animator can design specific leg movements of the character, and EDGE will “auto-complete” the entire body from that positioning in a way that is realistic, seamless, and physically plausible as well — a human could complete the moves. Above all, the moves are consistent with the animator’s choice of music. Like other generative models for images and text — ChatGPT and DALL-E, for instance — EDGE represents a new tool for choreographic idea generation and movement planning.

 

The editability means that dance artists and choreographers can iteratively refine their sequences move by move, position by position, adding specific poses at precise moments. EDGE then incorporates the additional details into the sequence automatically. In the near future, EDGE will allow users to input their own music and even demonstrate the moves themselves in front of a camera. “We think it’s a really a fun and engaging way for everyone, not just dancers, to express themselves through movement and tap into their own creativity,” Liu says.

Read the full article at: hai.stanford.edu

From writing dish descriptions to updating handbooks — make it work for you.

Read the full article at: www.hospitalitymagazine.com.au

• 17 April 2023

Several search tools claim to help researchers do science.

• Katharine Sanderson

 

As large language models (LLMs) gallop ever onwards — including GPT-4, OpenAI’s latest incarnation of the technology behind ChatGPT — scientists are beginning to make use of their power. The explosion of tools powered by artificial intelligence (AI) includes several search engines that aim to make it easier for researchers to grasp seminal scientific papers or summarize a field’s major findings. Their developers claim the apps will democratize and streamline access to research.

But some tools need more refinement before researchers can use them to help their studies, say scientists who have experimented with them. Clémentine Fourrier is a Paris-based researcher who evaluates LLMs at Hugging Face, a company in New York City that develops open-source AI platforms. She used an AI search engine called Elicit, which uses an LLM to craft its answers, to help find papers for her PhD thesis. Elicit searches papers in the Semantic Scholar database ad identifies the top studies by comparing the papers’ titles and abstracts with the search question.

Read the full article at: www.nature.com