Intel's new programmable chip unit began as a standalone business last year. On Thursday, the company laid out plans for the future and finally gave us its official name, Altera.
Intel plans, according to Reuters, to hold a stock offering for Altera within the next two or three years. Intel acquired the business when it bought Altera for $16.7 billion in 2015. The chips can be used for everything from encrypting data to 5G wireless telecommunications equipment.
The programmable chips designed by Altera are useful for AI applications and computing tasks that range between purpose-built customer processors designed by cloud computing companies, such as Amazon, and general-use AI chips made by Nvidia.
The hardware needed to run AI is fluctuating, according to a statement from Intel. However, the company believes its programmable chips will fill a void in a growing market.
"(Programmable chips are) always at the forefront of that innovation cycle and that's our job to stay at the forefront," CEO Sandra Rivera said. "To make it easy to drive these transitions."
The market estimate for programmable chips was roughly $8-$10 billion for 2023, but it's not clear how large the opportunity for programmable chips is because no good third-party data exists, Rivera said.
"I think it's larger than people realize," she said, and added that's because there are many programmable chips helping at various stages of the "AI workflow." Intel's current line of programmable chips, Agilex, is produced by Intel Foundry, the company's contract manufacturing wing.
Intel's CEO declined to say if Intel Foundry will manufacture the Agilex 3 chips but expects Intel will be "treated like customers" and get a "friends and family discount on top."
The Continued Effect Of A.I.
Artifical Intelligence continues to be at the forefront of discussion in the culture. Late last year, HNGN reported that the drug-resistant Staphylococcus aureus (MRSA) bacteria had been a cause for concern to the international medical community for at least 30 years. However, a new class of antibiotics was discovered by using deep learning AI models.
The use of artificial intelligence helped scientists to create the first new antibiotics in 60 years. A deep-learning model was used to predict the mechanisms and potentially toxic nature of each new compound. Deep learning methodology uses artificial neural networks to learn and present information gleaned from data without needing to be programmed to do so. The severity of MRSA infections ranges from skin infections to life-threatening conditions such as pneumonia and bloodstream infections.
