Conversastional Computing is allowing for personalized digital assistants managing daily tasks — but we must also consider privacy, bias and other ethical concerns.
Apple today released several open source large language models (LLMs) that are designed to run on-device rather than through cloud servers. Called OpenELM (Open-source Efficient Language Models), the LLMs are available on the Hugging Face Hub, a community for sharing AI code.
As outlined in a white paper [PDF], there are eight total OpenELM models, four of which were pre-trained using the CoreNet library, and four instruction tuned models. Apple uses a layer-wise scaling strategy that is aimed at improving accuracy and efficiency.
Adobe researchers have developed a new generative AI model called VideoGigaGAN that can upscale blurry videos at up to eight times their original resolution. Introduced in a paper published on April 18th, Adobe claims VideoGigaGAN is superior to other Video Super Resolution (VSR) methods as it can provide more fine-grained details without introducing any “AI weirdness” to the footage.
In a nutshell, Generative Adversarial Networks (GANs) are effective for upscaling still images to a higher resolution, but struggle to do the same for video without introducing flickering and other unwanted artifacts. Other upscaling methods can avoid this, but the results aren’t as sharp or detailed. VideoGigaGAN aims to provide the best of both worlds — the higher image/video quality of GAN models, with fewer flickering or distortion issues across output frames. The company has provided several examples here that show its work in full resolution.
Some of the finer details in the demo clips Adobe provided appear to be entirely artificial, such as the skin texture and creases in the below example, but the results appear impressively natural. It would be difficult to tell that generative AI was used to improve the resolution, which could extend the “what is a photo” debate to include video.
1/ OpenAI researchers have proposed a new instruction hierarchy approach to reduce the vulnerability of large language models (LLMs) to prompt injection attacks and jailbreaks.
OpenAI researchers propose an instruction hierarchy for AI language models. It is intended to reduce vulnerability to prompt injection attacks and jailbreaks. Initial results are promising.
Language models (LLMs) are vulnerable to prompt injection attacks and jailbreaks, where attackers replace the model’s original instructions with their own malicious prompts.
Continue reading “OpenAI’s new ‘instruction hierarchy’ could make AI models harder to fool” »
Xaira has recruited a group of researchers who developed the leading models for protein and antibody design while in Baker’s lab. The company aims advance these models and develop new methods that can “connect the world of biological targets and engineered molecules to the human experience of disease.”
“Driven by growing data sets and new methods, there has been accelerating progress in artificial intelligence and its applications to medicine, biology and chemistry, including seminal work from David Baker’s lab at the Institute for Protein Design,” said Foresight’s Dr Vikram Bajaj. “In starting Xaira, we have brought together incredible multidisciplinary talent and capabilities at the right time to reimagine our entire approach, from drug discovery to clinical development.”
Boasting proficiency in handling vast and multidimensional datasets, Xaira claims it will enable comprehensive characterization of disease biology at various levels, from molecular to clinical. Drawing from Illumina’s functional genomics R&D effort and integrating a key proteomics group from Interline Therapeutics, the company aims to gain new insights into disease mechanisms.
The Meta CEO is spending massively on AI. In a call with analysts, he explained how these huge investments can pay off in the future.
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