Jake Brukhman

2 months ago | fortune.com | Jake Brukhman

Stopping the recent regulatory assault against tech founders is a good start—but more is needed.

Jun 26, 2024 | fortune.com | Jake Brukhman

On May 23, the SEC approved exchange-traded funds (ETFs) for the spot market for a type of cryptocurrency known as Ethereum. It was the second type of ETF after Bitcoin bringing crypto exposure to traditional investors and authorized by the SEC, crypto’s most incredulous regulator. The same week, the House passed FIT21, a bill meant to provide regulatory clarity for the digital currency industry, which has begged for a decade for clear guidance on how to operate within U.S. law.

Jul 11, 2023 | blog.coinfund.io | Isaiah Washington |Rishin Sharma |Jake Brukhman |Einar Braathen

We are excited to announce that CoinFund has led a $3 million dollar round in Giza, a company working toward enabling AI models for blockchain smart contracts. Large tech companies have historically dominated the production of cutting edge machine learning models due to the significant resources required. These resources include vast amounts of data for training, high-performance computing infrastructure, and specialized expertise in machine learning.

Jul 11, 2023 | zephyrnet.com | Isaiah Washington |Rishin Sharma |Jake Brukhman

We are excited to announce that CoinFund has led a $3 million dollar round in Giza, a company working toward enabling AI models for blockchain smart contracts. Large tech companies have historically dominated the production of cutting edge machine learning models due to the significant resources required. These resources include vast amounts of data for training, high-performance computing infrastructure, and specialized expertise in machine learning.

Jul 11, 2023 | zephyrnet.com | Rishin Sharma |Jake Brukhman

We are excited to announce that CoinFund has led a $3 million dollar round in Giza, a company working toward enabling AI models for blockchain smart contracts. Large tech companies have historically dominated the production of cutting edge machine learning models due to the significant resources required. These resources include vast amounts of data for training, high-performance computing infrastructure, and specialized expertise in machine learning.