IBM to launch $500M AI Venture Fund while blockchain tackles AI’s energy consumption

IBM has announced that its $500 million AI venture fund will be invested in a diverse range of AI companies, accelerating the growth of generative AI within the business sector. This fund is a gateway for emerging AI startups to tap into IBM’s deep expertise and strategic resources, according to the press release.

The announcement comes amid forecasts that AI could contribute up to $16 trillion to the global economy by 2030, with IBM positioning itself as a significant contributor in prominent AI players like Hugging Face and HiddenLayer.

However, the rapid advancement of AI has brought a pressing concern: the immense energy consumption required to power this technology. This is where blockchain emerges as an innovative solution to AI’s energy dilemma.

While AI’s computational demand continues to surge, blockchain initiatives present the potentiality to curb the environmental impact. By distributing the computational load across a decentralized network, blockchain can reduce energy consumption as well as enhance security and reliability.

IBM’s venture into AI funding is parallel to the broader developer community’s efforts to address the energy consumption of powerful AI algorithms.

Blockchain’s role in AI’s energy challenge

Blockchain’s reputation for high energy consumption, primarily through cryptocurrencies like Bitcoin, is undergoing a transformation. With over half of Bitcoin’s energy now sourced from renewables, blockchain’s potential to support sustainable growth in AI is becoming increasingly evident.

Platforms like CUDOS are creating decentralized cloud infrastructures that leverage renewable energy and idle computing power, thus facilitating an environmentally sustainable expansion for AI startups. This approach reduces carbon footprints and democratizes access to AI by lowering operational costs. It spreads computational tasks across numerous locations to minimize energy use and enhance system resilience.

This method also indicates that disruptions in one node won’t compromise the entire network while also sourcing the most cost-effective and cleanest energy to fuel AI processes. Through decentralized cloud computing, AI can grow more intelligently, safeguarding the planet while expanding its capabilities.

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