In our new blog series, “Meet our Data Champions,” we showcase the exciting work Google Cloud customers are doing with data and AI/ML. In this edition, we talk to Bob Summers, CEO and founder of Goodcall, a company whose phone AI service leverages Google Cloud Speech AI technologies to bring the power of AI to …
Databricks on Tuesday launched Lakehouse for Manufacturing, a new platform to unify data and AI for various analytics use cases.Read More
A multidisciplinary team has created a new fabrication technique for fully foldable robots that can perform a variety of complex tasks without relying on semiconductors.
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In this post, we introduce Koala, a chatbot trained by fine-tuning Meta’s LLaMA on dialogue data gathered from the web. We describe the dataset curation and training process of our model, and also present the results of a user study that compares our model to ChatGPT and Stanford’s Alpaca. Our results show that Koala can …
Denoising Diffusion models have demonstrated their proficiency for generative sampling. However, generating good samples often requires many iterations. Consequently, techniques such as binary time-distillation (BTD) have been proposed to reduce the number of network calls for a fixed architecture. In this paper, we introduce TRAnsitive Closure Time-distillation (TRACT), a new method that extends BTD. For …
Read more “TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation”
In his book The Book of Why, Judea Pearl advocates for teaching cause and effect principles to machines in order to enhance their intelligence. The accomplishments of deep learning are essentially just a type of curve fitting, whereas causality could be used to uncover interactions between the systems of the world under various constraints without …
Practical machine learning (ML) is a trial and error process. ML practitioners compare different performance metrics by running ML experiments till you find the best model with a given set of parameters. Because of the experimental nature of ML, there are many reasons for tracking ML experiments and making them reproducible including debugging and compliance. …
Read more “How you can automate ML experiment tracking with Vertex AI Experiments autologging”
Yes, it has looks only a mother could love—but shut your eyes and wait till you hear how mind-blowingly good this new speaker is.
Anthropic, one of the chief rivals to OpenAI, quietly rolled out broader access to the “Private Alpha” version of the highly anticipated chat service, Claude, at a bustling Open Source AI meetup.Read More