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THE DAILY INDEX

Technology, AI, software, security, crypto and business

Across today’s newsletters

Today’s Index

MUSK'S $97.4 BILLION OPENAI BID PILES PRESSURE ON SAM ALTMAN

Elon Musk's offer to buy OpenAI for $97.4 billion, backed by a consortium of investors, could force OpenAI's board of directors to reassess how it is valuing the nonprofit. OpenAI is currently negotiating how much equity Microsoft should get in its for-profit company - satisfying all those parties was already complicated. The company must get approval for its conversion from attorneys general in California and Delaware - these officials will oversee the valuation of the nonprofit's assets during a sale to ensure it is properly compensated. Sam Altman has stated that he thinks Musk's offer is just a tactic to slow OpenAI down.

LEAKED PIXEL 9A RENDERS SHOW ALMOST NO CAMERA BUMP

Google appears to be ditching the camera bump this year for the Pixel 9A - it's still there, but just barely. A new set of renders has leaked showing the phone in black, white, pink, and purple. The back cameras will include a 48-megapixel main shooter and a 13-megapixel ultrawide. The phone will have a 13-megapixel selfie camera in the front and a 5,100mAh battery. The base model of the phone, which will have 128GB storage, will cost $499. The Pixel 9A will be released on March 26.

ARGENTINA'S GENE-EDITED HORSES

Scientists in Argentina have created genetically edited horses with increased explosive speed. The five foals have been tweaked to one day be able to outrun the champion mare they received genes from. Gene editing is banned by the International Federation for Equestrian Sports and the British Horseracing Authority, but the biotech firm that created the foals argues that the new horses' genes could have theoretically occurred naturally through selective breeding or genetic mutations.

EMERGING PATTERNS IN BUILDING GENAI PRODUCTS

A range of common patterns is emerging as software products that use generative AI are moving from proof-of-concept to production systems. This article looks at some of the regular patterns used to deal with issues in moving to production. It covers direct prompting, embeddings, evals, hybrid receivers, query rewriting, and retrieval augmented generation. The article provides an example and instructions for when to use the pattern for each pattern described.

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