If you suffered losses exceeding $50,000 investing in Dada stock or options between May 11, 2023 and January 8, 2024 and would like to discuss your legal rights, call Faruqi & Faruqi partner Josh Wilson directly at 877-247-4292 or 212-983-9330 (Ext. 1310). You may also click here for…

If you suffered losses exceeding $100,000 investing in EHang stock or options between January 20, 2022 and November 6, 2023 and would like to discuss your legal rights, call Faruqi & Faruqi partner Josh Wilson directly at 877-247-4292 or 212-983-9330 (Ext. 1310). You may also click here…

If you suffered losses exceeding $25,000 investing in Maison Solutions (a) Class A common stock pursuant and/or traceable to the registration statement and prospectus (collectively, the “Registration Statement”) issued in connection with the Company’s October 2023 initial public offering…

If you suffered losses exceeding $100,000 investing in Mobileye stock or options between January 26, 2023 and January 3, 2024 and would like to discuss your legal rights, call Faruqi & Faruqi partner Josh Wilson directly at 877-247-4292 or 212-983-9330 (Ext. 1310). You may also click here…

If you suffered losses exceeding $50,000 investing in Expensify common stock pursuant and/or traceable to the Offering Documents issued in connection with the Company’s initial public offering conducted on or about November 11, 2021 (the “IPO” or “Offering”) and would like to discuss your…

If you suffered losses exceeding $50,000 investing in Fisker securities between August 4, 2023 and November 20, 2023 and would like to discuss your legal rights, call Faruqi & Faruqi partner Josh Wilson directly at 877-247-4292 or 212-983-9330 (Ext. 1310). You may also click here for…

Originally published by TriplePundit

The tech company IBM is among those bringing AI into the sphere of mitigating the impact of weather-related disasters, and together with NASA, it’s hard at work on revolutionary foundational models. These models learn from a broad dataset to make using them for many different tasks quicker and easier, as opposed to task-specific models that are trained with data designed to teach them to do one job. This way, a dataset doesn’t need to be painstakingly created for each new task, because the AI can apply the information it’s learned from other situations to teach itself.

Among the projects its working on, IBM partnered with the University of Illinois to develop a foundational model capable of anticipating heavy rainfall and flash floods in the Appalachian Mountains.

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