Uncovering new opportunities with edge AI
With technology ever-advancing, edge AI is within reach. How to build, validate and push new edge AI software into production.Read More
To Hold Tech Accountable, Look to Public Health
The field of public health has transformed medicine, yet failed the most vulnerable. This trajectory can be avoided.
I’m the creator of LoRA. How can I make it better?
I wrote this paper two years ago: https://arxiv.org/abs/2106.09685 Super happy that people find it useful for diffusion models. I had text in mind when I wrote the paper, so there are probably things we can tweak to make LoRA more suited for image generation. I want to better understand how exactly LoRA is used in …
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Skills mapping: Turning skills to workforce gold
Skills mapping allows for more complex and personalized work journeys, ultimately allowing organizations to thrive.Read More
It’s Never Been Easier to Make an Adventure Game
New tools like Adventure Game Studio are responsible for a thriving indie scene for the genre.
I didn’t realize how powerful inpainting was till today!
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Embrace a Cookieless Future With Generative AI and First-Party Data
Cookies had a good run. The third-party data trackers beloved by marketers have been a part of the consumer web experience since the launch of Netscape in 1994. But, in an effort to position themselves as guardians of consumer privacy—and to comply with increasing regulations—tech giants Apple, Mozilla, and Google have rendered cookies virtually obsolete. …
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Continuous Pseudo-Labeling from the Start
Self-training (ST), or pseudo-labeling has sparked significant interest in the automatic speech recognition (ASR) community recently because of its success in harnessing unlabeled data. Unlike prior semi-supervised learning approaches that relied on iteratively regenerating pseudo-labels (PLs) from a trained model and using them to train a new model, recent state-of-the-art methods perform ‘continuous training’ where …
March 20 ChatGPT outage: Here’s what happened
An update on our findings, the actions we’ve taken, and technical details of the bug.
Detecting novel systemic biomarkers in external eye photos
Posted by Boris Babenko, Software Engineer, and Akib Uddin, Product Manager, Google Research Last year we presented results demonstrating that a deep learning system (DLS) can be trained to analyze external eye photos and predict a person’s diabetic retinal disease status and elevated glycated hemoglobin (or HbA1c, a biomarker that indicates the three-month average level …
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