🤖 OpenAI’s Officially Worth $300 Billion?!

💵OpenAI’s Officially Worth $300 Billion?!

🧠AI Decodes Brain Signals Into Spoken Words

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OpenAI’s core focus remains on pursuing Artificial General Intelligence (AGI), which is achieved when AI Systems display human-level learning, perception, and cognitive ability.

“We’re now confident we know how to build AGI,” explained OpenAI CEO Sam Altman. “We’re beginning to turn our aim beyond that to Superintelligence.”

$18 billion will go toward The Stargate Project, a new company that’ll spend $500 billion over the next four years building new AI infrastructure for OpenAI in America.

The money is contingent on OpenAI successfully restructuring into a Delaware Public Benefit Corporation (PBC) that’s no longer controlled by a Non-Profit Board of Directors (BofD).

OpenAI was founded as a non-profit organization before it added a “capped profit” framework called OpenAI LP in 2019. In other words, OpenAI created a money-making company within the original non-profit organization. Investors are requiring OpenAI to restructure OpenAI LP because it puts a ceiling on how much money they can earn from OpenAI’s success.

This $300 billion valuation puts OpenAI as one of the world’s most richly valued private companies.

Despite achieving $3.7 billion in revenue for 2024, OpenAI burned through $5 billion in the same year to acquire AI talent, build AI infrastructure, and train advanced AI models.

“AIBVN” decodes brain activity from the left frontal lobe of the Motor Cortex, which coordinates mouth, tongue, and throat movements to articulate words.

Then, it amplifies, filters, and digitizes this brain activity to prepare it for a Text-to-Speech (TTS) Framework, which synthesizes everything into spoken words.

To train the TTS Framework, patients look at phrases like: “Hey, how are you?” Then, they attempt to speak the phrases, which provides a mapping between the chunked windows of brain activity and the words they’re trying to articulate.

“AIBVN” can also use a patient’s pre-injury voice, so when it decodes brain activity and the TTS Framework synthesizes everything into spoken words, it sounds like them.

“We’re essentially intercepting brain signals where a thought is translated into articulation,” explained Co-Lead Researcher and Ph.D. Student Jun Cho. “So, we’re decoding everything after the thought, after we’ve decided what to say with what words to use.”

“AIBVN” represents a significant leap in restoring natural, personalized speech for patients who’ve lost the ability to communicate because of accidents or medical conditions.

It also showcases how AI developments enable the creation of more advanced Brain-Computer Interfaces (BCIs) that connect a patient’s brain signals to external devices like speech speakers or robotic limbs.

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