It provides free CPUs and it’s similar to the Streamlit Cloud. Hugging Face Spaces is a service where you can deploy your Streamlit or Gradio applications so that you can easily share them.I suggest having a look at Gradio as well, which is another popular Python library with similar goals. Moreover, you can deploy your Streamlit application to the Streamlit Cloud, which makes it easy to share your applications with other people and you get free CPUs to run your applications. Check out the Streamlit Gallery to learn what can be done with the library. Streamlit is a Python library that allows data scientists to easily create small interactive demos, so that other people can test their machine learning models or see their data analyses. I am delighted that Generate is creating opportunities for testing programs that were not possible only a few months ago.” Saad Khan, PhD.I’ve been wanting to experiment with Streamlit and Hugging Face Spaces for a while now. Our users have also been delighted at how Generate has expanded their thinking by creating fresh content and new items and distractors that they had never even thought of. This is the underlying philosophy we embedded in creating Generate. “Computer scientists know that the best AI tools are those that can be used in a hybrid human-AI fashion by domain professionals. Ongoing research is centered on optimizing the client experience and new insights will be shared over the coming months. Generate’s proof of effectiveness has been robustly established both theoretically (presentations at Association of Test Publishers 2021 national conference and at the 2021 Educator’s Data Mining conference) and in practice with current partners. Based on our pilot partners’ feedback, they are too.” Steve Shapiro. As we continue that work we are thrilled at the advances our AI Center has made. “Over the past six years Finetune has developed a deep partnership with The College Board in building the AP Classroom platform serving millions of students and their teachers. Generate’s NLP algorithms develop high quality items at scale by mastering content domains based on a small, safe, and secure sample of existing items. Generate was developed in Finetune’s AI Center of Excellence, led by Saad Khan, PhD, a computer scientist and globally recognized expert in the application of Machine Learning to education and assessment. In addition, blind comparisons between samples of existing and Generate-developed items have resulted in Generate items receiving higher quality ratings on average. Generate’s power is applicable to any content (K-12 to advanced technical specialties like medicine or law) and to any program (education, certification and licensure, training, prep) for multiple purposes (formative to high stakes).Įarly adopters of Generate have reported impressive gains of 3x to 10x in productivity. Users point out that Generate excels where other approaches are weakest, particularly around coming up with novel and creative ways to sample domains and developing highly effective ways of measuring higher-order thinking skills. Importantly, Generate functions without templates therefore avoiding the cost, time, and psychometric disadvantages of automated item generation (AIG) tools. Generate employs state-of-the-art artificial intelligence (AI) and natural language processing (NLP) to recommend novel, creative and conceptually-accurate assessment passages, stems, and distractors. Finetune, a global educational technology company, announces the release of Finetune Generate ®, a groundbreaking AI product that was shown to increase subject matter experts’ (SME) authoring speed up to 10x while concurrently improving item quality and creativity.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |