When we speak of artificial intelligence (AI), everything is about a smart working ecosystem along with a lot of money. This indeed is a booming segment which has been driving almost all the leading industries of the world as everyone is racing towards being faster in the segment. Recently, it was reported that Google, along with Microsoft and OpenAI, running in the race to develop advanced AI technologies.
As per Googles AI boss, the company is set to invest more than USD 100 billion in AI development and further aim at maintaining its edge over competitors.
Multiple quests related to AI dominance have turned into a financial arm for race, with tech behemoths which are pouring massive sums into AI research and development. Several rumours have surfaced about Microsoft and OpenAI collaborating on a USD 100 billion supercomputer project which will be called Stargate,.
Stargate will be aiming at propelling OpenAIs AI advancements and it will be responding to the inquiries about this competition. Demis Hassabis, head of DeepMind- Googles AI research lab has disclosed that Googles investment will surpass its rivals- but specific figures are yet to be disclosed.
The skyrocketing investment in artificial intelligence has reflected the surge in the AI ecosystem development across industries. AI startups are said to alone grown to around USD 50 billion in 2023, which has signalled the growing need and requirement for AI innovation.
However, the pursuit of Artificial General Intelligence (AGI) AI capable of human-like reasoning will come at a steep price and will be developing advanced AI models like Googles LLM and OpenAIs GPT series that demand substantial financial resources, and will cost which will escalate over time.
A significant portion of Googles investment is expected to be directed towards chip development, which has been designed to specialize chips which will enable the companies to optimize computing power for training AI models.
However, Google and other tech leaders are currently relying on third-party chip manufacturers like Nvidia. However, they are reportedly increasingly shifting towards in-house chip design to enhance control and efficiency.
Escalating training costsThe costs which are associated with training the AI models have also surged.
Stanford Universitys AI index report has revealed that OpenAIs GPT-4 required around USD 78 million worth of computing power for training, a significant jump from the USD 4.3 million spent on GPT-3 in 2020.
Similarly, Googles Gemini Ultra incurred USD 191 million in training costs. This will exponentially increase the underscores of the growing complexity and resource requirements of AI development.
Looking ahead, the AI industry is poised for further expansion, with investments expected to continue rising. OpenAI and Microsofts ambitious plan to build the Stargate supercomputer signifies the industrys commitment to pushing the boundaries of AI capabilities.
As the race for AI supremacy intensifies, the tech giant will spare no expense in their quest for innovation and dominance in the AI landscape.
