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As we strategy the tip of 2024 and mirror on the technological developments it introduced, the excitement surrounding synthetic intelligence and high-performance computing continues to overshadow all different web3 developments. As such, this 12 months noticed an overwhelming buyer demand for AI merchandise and even higher strain on knowledge facilities to ship AI infrastructure to spice up effectivity.
With corporations racing to undertake these applied sciences, many have thought of investing in compute assets like graphic processing unit chips, generally used for coaching AI fashions, blockchains, autonomous automobiles, and different rising purposes. However earlier than organizations totally embrace the thrilling potential of this {hardware}, we have to fastidiously think about the complexities and challenges that include them.
It’s true that the promise of AI is certainly attractive. Simply have a look at the stats from OpenAI’s ChatGPT, which garners over 200 million lively weekly customers. From automating mundane duties to driving refined analytics, the potential of AI and enormous language fashions is huge, and these applied sciences are right here to remain.
The expansion has simply began
Unsurprisingly, organizations are keen to achieve a aggressive edge by AI, main main gamers like Meta and Apple to put money into the software program that helps this know-how.
A current report from Bain & Firm—a administration consulting firm—revealed that AI workloads are anticipated to develop 25 to 35 p.c yearly over the subsequent a number of years, pushing the AI-related {hardware} and software program market to between $780 billion and $990 billion by 2027.
Nonetheless, investing in compute assets includes extra than simply buying {hardware} or subscribing to a cloud service. If we’re assessing among the obstacles to investing on this software program, one of many largest hurdles buyers face is the preliminary value.
The prices of superior GPUs like NVIDIA’s A100 or H100 could be upwards of hundreds of thousands of {dollars}, with extra prices for servers, cooling methods, or the electrical energy wanted to energy the units. This presents a problem for retail buyers wanting so as to add this know-how to their portfolios, typically limiting funding alternatives to highly effective firms.
Past the hefty price ticket, the {hardware} itself isn’t for the faint of coronary heart. It requires a radical understanding of optimizing and managing these assets successfully. Buyers ought to have specialised data within the {hardware} and software program, making technical experience a prerequisite.
Even when affordability and technical challenges weren’t obstacles to investing, a major impediment stays: Provide or lack thereof. The Bain & Firm report reveals that demand for AI elements may develop by 30 p.c or extra, outpacing provide capabilities.
Whereas investing in compute could seem out of attain, there are new fashions making it extra accessible to on a regular basis buyers, permitting them to faucet into the potential of superior computing regardless of present obstacles.
Tokenization as an answer
By the tokenization of high-compute GPU assets, Exabits gives customers a chance to develop into stakeholders within the AI compute economic system, permitting them to earn rewards and income without having to handle the complexities of {hardware} possession. With reasonably priced entry factors and reward methods, Exabits permits people to take part within the demand for GPU assets whereas avoiding the dangers related to direct funding, making investing in AI compute extra accessible.
Exabits has coined its enterprise mannequin, “The Four Seasons of GPU,” emphasizing high quality assurance and consistency throughout its GPU choices. Simply because the 4 Seasons is world famend for its excessive service requirements, “The Four Seasons of GPU” gives quality-guaranteed {hardware} that buyers can belief. Buyers can depend on Exabits for personalised help, much like the lodge’s dedication to buyer satisfaction. As a platform and a enterprise, Exabits goals to offer equal alternatives for buyers to take part on this rising AI compute economic system.
As demand for computation rises, so does the urge for food for funding alternatives inside this quickly rising area. With the continued progress of AI, blockchain, and different tech developments, the way forward for GPU improvement will depend upon the business’s capacity to satisfy these calls for and create alternatives that proceed to broaden entry to this esteemed know-how.
