Summary:
Marathon Digital is shifting focus towards AI amid declining Bitcoin production.
The company appointed AI experts Janet George and Barbara Humpton to its board.
Bitcoin production dropped by 3% in August, mining 673 BTC.
Marathon increased its hash rate by 11% to 35.2 EH/s.
The firm aims to reach 50 EH/s by the end of 2024.
Marathon Digital is making strategic moves towards artificial intelligence (AI) as its Bitcoin production faced a downturn in August. On September 5, the Bitcoin miner announced the addition of AI experts, Janet George and Barbara Humpton, to its board. This change comes after the resignation of Kevin DeNuccio and Said Ouissal as part of a planned transition.
AI Experts Joining the Board
Marathon's new board members bring a wealth of experience in AI, data centers, and energy. Barbara Humpton, currently the President and CEO of Siemens USA, has been a leader in integrating AI and industrial data to enhance operations. Janet George, previously the Corporate Vice President and General Manager of Data Center & AI at Intel, has an impressive background with major corporations such as Oracle, Yahoo, and Apple.
Fred Thiel, Marathon’s chairman and CEO, emphasized the growing importance of AI strategies in data centers and the need for expertise to support the company’s infrastructure expansion focused on AI.
Bitcoin Production Decline
In August, Marathon experienced a 3% drop in Bitcoin production, mining 673 BTC, while block wins decreased by 2% compared to July. Nonetheless, the company successfully mined its 4,000th block and increased its hash rate by 11% to 35.2 EH/s. Thiel noted improvements in site operations and reaffirmed the goal of reaching 50 EH/s by the end of 2024. Significant developments include energizing nearly 18 immersion containers in Granbury, Texas, transitioning a large part of the data center from air-cooled systems to immersion cooling.
These strategic shifts reflect a broader trend among Bitcoin miners exploring the vast potential revenue that an AI pivot could bring, with projections suggesting an average yearly profit of $14 billion if 20% of energy capacity is dedicated to AI computations by 2027.
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