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Category: robotics/AI – Page 708

More than 10 Chinese companies this year have revealed innovations related to humanoid robots, he noted, adding that China already has some supporting facilities from developing industrial robots.

Beijing has set aside about 10 billion yuan (about $1.4 billion) to fund the robotic development. On Nov. 6, China opened the first provincial-level innovation center on humanoid robots in the country’s capital to work on solving pressing “key common problems,” including an operation control system, open source software, and robot prototypes.

At least one Chinese company, Jiangsu Miracle Logistics System Engineering Co., has promised to introduce its first humanoid robot by the end of the year. Chinese securities brokerage firm Zheshang Securities estimates that the humanoid robot market will have a demand for 1.77 million machines by 2030.

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In particular, many have griped over their original work being used to train these AI models — a use they never opted into, and for which they’re not compensated.

But what if artists could “poison” their work with a tool that alters it so subtly that the human eye can’t tell, while wreaking havoc on AI systems that try to digest it?

That’s the idea behind a new tool called “Nightshade,” which its creators say does exactly that. As laid out in a yet-to-be-peer-reviewed paper spotted by MIT Technology Review, a team of researchers led by University of Chicago professor Ben Zhao built the system to generate prompt-specific “poison samples” that scramble the digital brains of image generators like Stable Diffusion, screwing up their outputs.

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Researchers at the University of Barcelona have made a sweet discovery: Honeybees make great subjects when studying the dynamic of group behavior and decision-making.

In a recently released study, Professor M. Carmen Miguel, who has previously studied leadership activity among schooling fish and social interactions among flocks of birds, said a group of mini robots were trained to reach a consensus on tasks by mimicking processes displayed by .

The intricate behavior of bees has long been a subject of great interest among researchers. There are more than 4,000 species of the insect, and they have been around for more than 100 million years.

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VentureBeat presents: AI Unleashed — An exclusive executive event for enterprise data leaders. Hear from top industry leaders on Nov 15. Reserve your free pass

MIT scientists have developed a deep learning system, Air-Guardian, designed to work in tandem with airplane pilots to enhance flight safety. This artificial intelligence (AI) copilot can detect when a human pilot overlooks a critical situation and intervene to prevent potential incidents.

The backbone of Air-Guardian is a novel deep learning system known as Liquid Neural Networks (LNN), developed by the MIT Computer Science and Artificial Intelligence Lab (CSAIL). LNNs have already demonstrated their effectiveness in various fields. Their potential impact is significant, particularly in areas that require compute-efficient and explainable AI systems, where they might be a viable alternative to current popular deep learning models.

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AI startup Hugging Face offers a wide range of data science hosting and development tools, including a GitHub-like portal for AI code repositories, models and datasets, as well as web dashboards to demo AI-powered applications.

But some of Hugging Face’s most impressive — and capable — tools these days come from a two-person team that was formed just in January.

H4, as it’s called — “H4” being short for “helpful, honest, harmless and huggy” — aims to develop tools and “recipes” to enable the AI community to build AI-powered chatbots along the lines of ChatGPT. ChatGPT’s release was the catalyst for H4’s formation, in fact, according to Lewis Tunstall, a machine learning engineer at Hugging Face and one of H4’s two members.

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Meta has joined forces with Hugging Face, an open source community-driven platform that hosts machine learning models and tools, and Scaleway, European cloud leader for AI infrastructures, to launch the “AI Startup Program”, an initiative aimed to accelerate the adoption of open-source artificial intelligence solutions within the French entrepreneurial ecosystem. With the proliferation of foundation models and generative artificial intelligence models, the aim is to bring the economic and technological benefits of open, state-of-the-art models to the French ecosystem.

Located at STATION F in Paris, the world’s largest startup campus, and with the support of the HEC incubator, the programme will support 5 startups in the acceleration phase, from January to June 2024. A panel of experts from Meta, Hugging Face and Scaleway will select projects based on open foundation models and/or demonstrating their willingness to integrate these models into their products and services.

The startups selected will benefit from technical mentoring by researchers, engineers and PhD students from FAIR, Meta’s artificial intelligence research laboratory, access to Hugging Face’s platform and tools, and Scaleway’s computing power in order to develop their services based on open source AI technology bricks. In addition to LLMs – large language models – startups will also be able to draw on foundation and research models in the field of image and sound processing. Applications are open until 1 December 2023.

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Agi, if you can see or hear this. WE Eagerly Await and Welcome Your Arrival!!!

Update from November 9, 2023:

During a Q&A session at OpenAI’s developer conference, Altman reiterated that GPT-5 is not yet concrete. OpenAI still has “a lot” of things to figure out before it can train a model it calls GPT-5, Altman said.

There is no guarantee that it will work, and OpenAI still needs to solve difficult scientific problems and needs more computing power, he said.

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