Reddit Stock Jumps after OpenAI Partnership

Reddit app is seen on a smartphone in this illustration taken, July 13, 2021. (Reuters)
Reddit app is seen on a smartphone in this illustration taken, July 13, 2021. (Reuters)
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Reddit Stock Jumps after OpenAI Partnership

Reddit app is seen on a smartphone in this illustration taken, July 13, 2021. (Reuters)
Reddit app is seen on a smartphone in this illustration taken, July 13, 2021. (Reuters)

Shares of Reddit rose nearly 15% on Friday, following a partnership with artificial intelligence firm OpenAI that is expected to boost advertising income for the social media platform.

The jump pushed the stock up at $64.80, within striking distance of the record closing price of $65.11 hit in late-March, and added $1.38 billion to the company's market value.

The partnership, announced on Thursday, allows Reddit to leverage OpenAI's technology to build tools and features, and OpenAI's ChatGPT platform to integrate Reddit's content in a "real-time, structured" manner. OpenAI will also become an advertising partner for Reddit.

The deal could yield more than $50 million to $60 million annually for Reddit, Piper Sandler lead analyst Thomas Champion said in a note on Friday.

More than half the analysts covering the stock have a "buy" or higher rating, with a median price of $63.

The deal delivers on Reddit's "IPO promise of seizing opportunities to make more of AI," said Russ Mould, investment director at AJ Bell.

The company's shares have gained more than 90% since their debut in March at $34 a piece.

In a February filing, the company indicated its intentions to explore new monetization channels beyond advertising revenue, including offering creator tools and licensing its data to third parties.

Reddit already has data licensing agreements with undisclosed firms that are projected to contribute at least $66.4 million in revenue this year. The license allows third parties to access, search, and analyze data on the platform.

The deal comes amidst a growing number of lawsuits against OpenAI, with firms alleging unauthorized use of their content for training large language models.

In recent months, OpenAI has also secured content licensing deals with several publishers, including the Associated Press and the Financial Times.



SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI
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SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

The Center of Excellence for Data Science and Artificial Intelligence at the Saudi Data and Artificial Intelligence Authority (SDAIA) and King Abdullah University of Science and Technology (KAUST) have introduced the MiniGPT-Med model.

The large multi-modal language model is designed to help doctors quickly and accurately diagnose medical radiology using artificial intelligence techniques.

Dr. Ahmed Alsinan, the Artificial Intelligence Advisor at the National Center for Artificial Intelligence and head of the scientific team at SDAIA, explained that the MiniGPT-Med model is capable of performing various tasks such as generating medical reports, answering medical visual questions, describing diseases, locating diseases, identifying diseases, and documenting medical descriptions based on entered medical images.

The model was trained on different medical images, including X-rays, CT scans, and MRIs.

The MiniGPT-Med model, derived from large-scale language models, is specifically tailored for medical applications and demonstrates significant versatility across different imaging methods, including X-rays, CT scans, and MRI. This enhances its utility in medical diagnosis.

Dr. Alsinan highlighted that the MiniGPT-Med model was developed collaboratively by artificial intelligence specialists from SDAIA and KAUST.

The model exhibits advanced performance in generating medical reports, achieving 19% higher efficiency than previous models. It serves as a general interface for radiology diagnosis, enhancing diagnostic efficiency across various medical imaging applications.