Disney and Adobe have announced a multiyear partnership to develop generative AI tools customized for Disney’s creative and operational work. Through Adobe Firefly Foundry, the companies will build proprietary models trained on Disney-specific knowledge, including characters, settings, and visual styles. They say the tools will be artist-led and human-centered, with outputs designed to be commercially safe and ready for production while helping teams work faster and take on more creative projects. Disney will also get early access to Adobe’s developing technologies.
The collaboration is intended to reach beyond film production. Disney’s Imagineering research and development team already uses Firefly in theme-park development, and the companies plan to expand creative workflows at Walt Disney Studios. They will also explore uses in ESPN content and ways to increase sports-fan engagement, as well as applications across Disney’s resorts and cruise line. The deal extends an existing relationship and follows Disney’s other moves into generative AI, including a partnership with OpenAI. It comes as Disney reportedly prepares to cut thousands of jobs and pursue substantial annual cost savings, placing the expansion of AI tools alongside a broader effort to reduce costs.
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Researchers tested 16 LLMs on all 55 TIS-100 puzzles, giving each one attempt and time to refine its code. The models found 133 new performance tradeoffs across 18 puzzles and set three outright cycle records, though human players improved on most solutions within days. (tis-100.wincon.dev)
Australia is considering a new criminal offence for AI companies that fail to take reasonable steps to prevent harm caused by their models. The government is also weighing an AI safety watchdog with power to impose significant fines, following a hack of a Medicare statistics portal involving OpenAI. (abc.net.au)
AI is increasingly becoming a gateway through which people find information. Audiences still resist having AI produce their news. (niemanlab.org)
Nvidia holds a central position in the AI industry, making disruption to the company potentially catastrophic for the wider ecosystem. The race for advanced AI is also intensifying economic and geopolitical conflict, while concentrated corporate power and infrastructure face growing political resistance. (france24.com)
LLM inference can require reading about 26 GB of model weights to generate each token from a 13-billion-parameter model. The explanation shows how model size drives memory bandwidth demands during text generation. (youtube.com)
Deletion Tuning matches full fine-tuning across three LLM post-training methods by zeroing fewer than 0.05% of model weights. Its compact masks also preserve prior-task accuracy better than full fine-tuning, LoRA, and random sparse tuning. (arxiv.org)
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