Curated for content, computing, and digital experience professionals

Day: May 10, 2023

Adobe and Google integrating Firefly and Bard

Adobe and Google are partnering to bring Firefly to Bard, Google’s experimental conversational AI service, with the ability to continue the creative journey further in Adobe Express. With the new Bard by Google integration, users at all skill levels will be able to describe their vision to Bard in their own words to create Firefly generated images directly in Bard and then modify and use them to create designs via Express.

Because Firefly has the CAI’s Content Credentials on by default, every image created in Bard using Firefly will have transparency built in. The CAI’s Content Credentials are a free, open-source tool that serve as a digital “nutrition label.” Content Credentials can show information such as name, date, the tools used to create an image and any edits made to that image. They remain associated with content wherever it is used, published or stored, enabling proper attribution and helping consumers make informed decisions about digital content.

Firefly’s first model is trained on Adobe Stock images, openly licensed content and public domain content where copyright has expired. Enterprise businesses will be able to train Firefly with their own creative collateral in order to generate content in the company’s brand language.

MindsDB and Nixtla enhance time-series forecasting

MindsDB, an open-source applied machine learning platform, announced full integration with Nixtla, an open-source ecosystem that offers time-series forecasting.

Time-series forecasting refers to making scientific predictions based on historical, time-stamped data. It allows data scientists to employ models to predict a future value or classification at a particular point in time, such as forecasting power demand, call volumes, inventory requirements, or supply and demand.

Nixtla offers libraries specifically for time-series forecasting. One of the libraries, StatsForecast, which provides statistical and econometric models, will now function seamlessly within the MindsDB ecosystem. This integration will allow developers using MindsDB to build AI-powered forecasting capabilities and anomaly detection solutions in the database without writing extensive code. MindsDB turns a team of 1,000 developers into 1,000 AI developers with little to no training.

The Nixtla integration includes accurate model implementations, probabilistic forecasting and confidence intervals, support for exogenous variables and static covariates, anomaly detection and time series forecasting. Nixtla’s StatsForecast is optimized for high performance and scalability and uses classical methods, such as ARIMA, rather than deep learning models. This platform means models can be trained quickly and generalized well, making short-time series forecasting easier for developers. ■‍

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