Hardware crisis threatens to throw a spanner in the works for AI development

Behind the scenes of the booming artificial intelligence (AI) market, a crisis is lurking: there is a huge shortage of hardware. This could put the ambitions of countless developers and innovations on hold. Interestingly, decentralized cloud computing could save the day, which could also be positive for crypto.

The salvation of AI

The concentration of computing power among tech giants not only brings high prices, but also risks in terms of AI security, a monopoly on “innovation” and possible unethical use.

To break this scarcity and centralization, decentralized cloud computing platforms are emerging as saviors. These platforms address the challenges of underutilized GPU resources and the inefficiencies of current models, making AI development accessible to everyone.

At least, that is of course the idea.

But decentralized platforms must consider the reality that most high-performance enterprise GPUs are already occupied, leaving limited capacity available. However, almost 90% of the potential of consumer GPUs remains untapped. Since these GPUs are designed primarily for gaming, it is essential to optimize them for AI calculations as traditional aggregation methods are inadequate.

Decentralized cloud for AI calculations

Exabits, a decentralized cloud computing platform, exceeds the limitations of standard decentralized platforms as a base layer of AI computing and full-stack solution, by aggregating, accelerating and stabilizing consumer-grade GPUs to nearly the same performance as enterprise-grade GPUs.

Very simply put: they use a lot of computers from normal people to develop computers that compete with those of the tech giants.

This taps into a vast but largely untapped reserve of consumer GPUs, potentially providing a solution to the GPU shortage crisis.

Projects such as io.net, Render Network, Akash, Aethir, EMC and Solana collaborate with Exabits to create a large, interconnected decentralized computing network.

Additionally, thanks to its decades of experience in the data center industry, Exabits has unique access to the sought-after enterprise-class H100 and A100 GPUs (and soon the new B200s), further democratizing AI development.

With access to more than 350,000 GPUs, Exabits takes untapped consumer GPUs and turns them into AI computing solutions. For optimal performance, the platform accelerates, connects and balances hardware with advanced technologies developed by their team of PhD researchers.

Clusters of enterprise-class GPUs

The Exabits team is led by PhDs from Harvard and Princeton with experience at organizations such as BitMain, Ericsson, QuickNode, The White House, Plug and Play, TikTok and Meta. Their combined expertise includes more than $2 billion in deals in the construction, management and operation of data centers worldwide.

The platform ensures customers have the computing power they need to efficiently train advanced machine learning models at scale. It enables developers to build complex AI projects without facing traditional barriers to entry, providing a cost-effective alternative to limited high-end enterprise GPUs.

After partnering with Nebula Block, a Web3 infrastructure platform, Exabits reports a 71% cost savings and a 30% performance improvement over traditional Amazon Web Services (AWS) platforms.

As we envision the future, the need to create a more inclusive AI infrastructure is undeniable. By fostering a community-driven approach and implementing scalable and efficient solutions, the technology sector can overcome current limitations. Solutions like Exabits can pave the way to a future where AI development is accessible to everyone.

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