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The AI compute craze for retail investors in web3

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Disclosure: The views and opinions expressed here belong solely to the author and do not represent the views and opinions of crypto.news’ editorial.

As we approach the end of 2024 and reflect on the technological advancements it brought, the buzz surrounding artificial intelligence and high-performance computing continues to overshadow all other web3 developments. As such, this year saw an overwhelming customer demand for AI products and even greater pressure on data centers to deliver AI infrastructure to boost efficiency. 

With companies racing to adopt these technologies, many have considered investing in compute resources like graphic processing unit chips, commonly used for training AI models, blockchains, autonomous vehicles, and other emerging applications. But before organizations fully embrace the exciting potential of this hardware, we need to carefully consider the complexities and challenges that come with them.

It’s true that the promise of AI is indeed enticing. Just look at the stats from OpenAI’s ChatGPT, which garners over 200 million active weekly users. From automating mundane tasks to driving sophisticated analytics, the potential of AI and large language models is vast, and these technologies are here to stay. 

The growth has just started 

Unsurprisingly, organizations are eager to gain a competitive edge through AI, leading major players like Meta and Apple to invest in the software that supports this technology. 

A recent report from Bain & Company—a management consulting company—revealed that AI workloads are expected to grow 25 to 35 percent annually over the next several years, pushing the AI-related hardware and software market to between $780 billion and $990 billion by 2027. 

However, investing in compute resources involves more than just purchasing hardware or subscribing to a cloud service. If we’re assessing some of the barriers to investing in this software, one of the biggest hurdles investors face is the initial cost.

The costs of advanced GPUs like NVIDIA’s A100 or H100 can be upwards of millions of dollars, with additional costs for servers, cooling systems, or the electricity needed to power the devices. This presents a challenge for retail investors looking to add this technology to their portfolios, often limiting investment opportunities to powerful corporations.  

Beyond the hefty price tag, the hardware itself isn’t for the faint of heart. It requires a thorough understanding of optimizing and managing these resources effectively. Investors should have specialized knowledge in the hardware and software, making technical expertise a prerequisite. 

Even if affordability and technical challenges weren’t barriers to investing, a significant obstacle remains: Supply or lack thereof. The Bain & Company report reveals that demand for AI components could grow by 30 percent or more, outpacing supply capabilities. 

While investing in compute may seem out of reach, there are new models making it more accessible to everyday investors, allowing them to tap into the potential of advanced computing despite existing barriers.  

Tokenization as a solution

Through the tokenization of high-compute GPU resources, Exabits offers users an opportunity to become stakeholders in the AI compute economy, allowing them to earn rewards and revenue without needing to manage the complexities of hardware ownership. With affordable entry points and reward systems, Exabits allows individuals to participate in the demand for GPU resources while avoiding the risks associated with direct investment, making investing in AI compute more accessible. 

Exabits has coined its business model, “The Four Seasons of GPU,” emphasizing quality assurance and consistency across its GPU offerings. Just as the Four Seasons is world renowned for its high service standards, “The Four Seasons of GPU” provides quality-guaranteed hardware that investors can trust. Investors can rely on Exabits for personalized assistance, similar to the hotel’s commitment to customer satisfaction. As a platform and a business, Exabits aims to provide equal opportunities for investors to participate in this growing AI compute economy.

As demand for computation rises, so does the appetite for investment opportunities within this rapidly emerging space. With the ongoing growth of AI, blockchain, and other tech trends, the future of GPU development will depend on the industry’s ability to meet these demands and create opportunities that continue to broaden access to this esteemed technology. 



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Io.net and Phala Network partner to improve decentralized AI

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As part of a new agreement, Phala Network will enhance its AI capabilities using io.net’s GPU cloud infrastructure, making advanced computation more accessible.

GPU cloud network io.net (IO) has partnered with Phala Network to improve secure computation and decentralized AI capabilities, according to a press release shared with crypto.news. 

The IO Cloud service provided by io.net allows users to access high-performance GPUs on demand, reducing costs compared to traditional cloud services by up to 90%. Machine learning engineers and developers can access the computational power needed to train and deploy AI models without investing in expensive hardware.

The collaboration will allow Phala Network to tap into io.net’s cloud network, IO Cloud, for powerful GPU hardware, expanding the reach of Phala’s decentralized AI ecosystem.

This partnership strengthens Phala’s ability to run complex AI applications securely by leveraging Nvidia H100 and H200 GPUs, known for their advanced cryptographic protections. In other words, this collaboration will make it easier and more cost-effective for developers to run complex AI tasks while ensuring data security.

Phala Network will use io.net’s GPU resources to support its Trusted Execution Environment CPU nodes. TEEs are isolated sections of a computer’s hardware designed to securely handle sensitive data.

AI workloads 

According to the press release, Phala introduced the first benchmark for TEE-enabled GPUs in August. Through io.net’s network, Phala ensures that AI workloads are processed securely with Nvidia’s confidential computing features, such as encrypted memory and secure boot.

Phala Network is known for offering a decentralized platform where developers can execute complex tasks outside of traditional blockchain networks while maintaining privacy. Its infrastructure of over 40,000 TEE CPU nodes enables Web3 applications to handle computationally intensive tasks while safeguarding data privacy.

Io.net and Phala Network will conduct research and benchmarking, starting with Nvidia’s H100 and H200 GPUs. 

They plan to integrate Phala’s AI agents and hardware into the IO Network, enhancing both parties’ ability to support secure and decentralized AI operations, according to the release. This could lead to more accessible and efficient AI-driven Web3 applications.



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Render price recovers amid whale accumulation

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Render, a decentralized graphics processing unit-based rendering solutions provider, is seeing a notable price recovery as large wallet addresses aggressively accumulate the native token.

The Render (RENDER) token ranks as one of the top artificial intelligence and decentralized finance cryptocurrencies by market cap. After its native token plummeted to $4.50 on Sept. 7, Render has shown significant resilience, reclaiming support above $6.00.

RENDER price ‘bottomed’

According to market intelligence and on-chain insights provider Santiment, Render is showing recovery buoyed by large address accumulation. This comes after the artificial intelligence token bottomed out near $4.60 on Sept. 18, with bears rejecting bulls’ attempt to push higher around $5.35 a week earlier.

Most altcoins experienced significant volatility during this time, with related tokens such as Bittensor (TAO) soaring.

Gains for Render have largely been muted, but the bullish shift amid whale accumulation has seen its price rise by more than 33% over the past week. This upside has coincided with a fresh spike in artificial intelligence-related tokens.

Whales bought the Render dip

Whales and sharks took advantage of recent pullbacks to buy low. For Render, this was a notable occurrence, as pointed out by Santiment analysts in an post on X.

On-chain data shows that these large holders possess at least 100,000 Render tokens. About 902 addresses hold 100,000 or more tokens, with large holders controlling 91% of the total supply.

In the past eleven weeks, these large wallets have accumulated over 20.5 million Render tokens, valued at more than $126.3 million. During this aggressive accumulation, whales and sharks added 3.7% of Render’s total supply to their holdings.

While the whales adopted a bullish stance on the altcoin, investor wallets appear to have sold off sharply. In the past month, investors dumped 21% of their holdings, which whales absorbed. Retail investors also purchased more tokens, adding 3.6% to their portfolios.



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Bittensor tops crypto charts as AI tokens ride Nvidia wave

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Decentralized AI project Bittensor skyrocketed to the top of the weekly gainers’ list, riding the wave of Nvidia’s stock surge.

Bittensor (TAO) topped the charts this week as the biggest gainer among the top 100 cryptocurrencies with a solid 31% price jump. At the time of writing, TAO ranked 41st by market cap which stood at over $2.51 billion, with its price up 8.87% in the last 24 hours, trading at $313.59.

TAO’s recent climb can be credited to Nvidia Corp’s stock rallying 13.5%, closing at $119.08 on Sept. 13. This surge pushed Nvidia’s market cap to a whopping $2.92 trillion, according to MarketWatch.

With Nvidia stocks up 140.5% so far this year, the momentum has lifted TAO and other AI-focused cryptocurrencies along with it, pushing the AI-crypto market cap up by 0.8% in the last 24 hours. According to CoinGecko, the total market cap for AI tokens now stands at $23.9 billion.

AI tokens typically move in tandem with Nvidia’s stock. On Sept. 4, tokens like Artificial Superintelligence Alliance (FET) and Render (RNDR) fronted double-digit losses after a 9.5% dip in Nvidia’s stock. Back in February, these tokens rallied after Nvidia’s strong Q4 2023 earnings, and a similar buzz also built up ahead of its Q2 2024 report.

TAO primed for liftoff

Bittensor tops crypto charts as AI tokens ride Nvidia wave - 1
TAO 1D price, MACD, and RSI chart – Sep. 14 | Source: crypto.news

The 1D TAO/USD price chart from Sep. 14, signals a strong bullish trend, suggesting a potential for upward movement. 

The Moving Average Convergence Divergence has crossed above its signal line, and displaying longer green bars on the histogram, both positive signs for upward momentum.

Moreover, the Relative Strength Index currently stands at 59, indicating the asset is in a healthy trading zone, still far away from overbought levels. 

This provides room for potential growth without immediate concerns of a pullback due to overvaluation, painting a bullish outlook for the token’s short-term price trajectory, with further gains expected in the short term.

Market observers on X are echoing a similar bullish sentiment. According to analyst Marco Polo, TAO is currently ranging between $268 and $357. He expects a powerful upward move once TAO breaks above the $357 mark.

Meanwhile, analyst Ramon shares a similarly bullish outlook but identifies a slightly higher key resistance around the $400 mark. 

Ramon predicts that TAO could reach the $3,000 to $5,000 range of this bull run, depending on liquidity moving out of Bitcoin and the strength of the overall AI narrative, which has been further fueled by recent developments like Apple’s announcement of its generative AI at the iPhone 16 event.



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