AI Newsletter #011 (2023/07/31 – 2023/08/06)

1. Amazon Creates New Group to Work on Its ‘Most Ambitious’ AI Models
Amazon CEO Andy Jassy has created a new group focused on developing the company’s “most ambitious” large language models (LLMs), according to a leaked internal email. The group will be led by Rohit Prasad, SVP and head scientist for Alexa. Amazon is aiming to keep up with competitors such as OpenAI, Google, and Microsoft in the AI race.

2. IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
IBM and Hugging Face have announced that IBM’s geospatial foundation model, built from NASA’s satellite data, will be openly available on Hugging Face. This will be the largest geospatial foundation model on Hugging Face and the first-ever open-source AI foundation model built in collaboration with NASA. The model aims to democratize access and application of AI in climate and Earth science.

3. AI chip firm Tenstorrent raises $100 million from Hyundai, Samsung
Canadian AI chip startup Tenstorrent has raised $100 million in funding from Hyundai Motor Group, Samsung’s Catalyst Fund, and other investors. Tenstorrent, led by chip industry veteran Jim Keller, is developing AI chips to challenge market leader Nvidia. The funding will be used to further develop their AI chip technology for various applications, including smart televisions and future Hyundai, Kia, and Genesis vehicles.

4. AI Startup Inworld Raises $50M to Create Better Video Game Characters
Inworld AI, an AI startup focused on creating more interactive non-player characters (NPCs) in video games, has raised over $50 million in its latest funding round. The funding, led by Lightspeed Venture Partners and including contributions from Stanford University, Samsung Next, and others, brings Inworld AI’s total valuation to $500 million. The funds will be used for research and development, hiring, and infrastructure. Inworld AI’s technology has already been used in popular games like Skyrim and Grand Theft Auto V.

5. Salesforce launches Einstein Studio for training AI models with Data Cloud
Salesforce has introduced Einstein Studio, a new feature that allows enterprises to connect and train their own AI models on proprietary data within Salesforce. The offering aims to streamline the AI project lifecycle, enabling data science and engineering teams to manage and deploy models more efficiently and at a lower cost. Once trained, these models can be used across various applications within Salesforce. The feature has already been tested by multiple enterprises and is now available for all users of Salesforce’s Data Cloud.

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