MERGE: The second biggest cryptocurrency just changed forever

9/15/22 8:00PM

MERGE

‍For those with crypto-loving colleagues or friends, you may be sick of hearing about "the merge". For the uninitiated however, there was some big news in the crypto corner of the internet this week as Ethereum underwent a transformation in a bid to reduce the complexity and energy consumption of the world's second-largest cryptocurrency.

Developers successfully executed on the plan, known as the "Ethereum merge", which fundamentally changes how the cryptocurrency validates transactions on the Ethereum chain. The move, away from a type of blockchain that uses "proof-of-work" towards an architecture using "proof-of-stake", is set to reduce the need for power-hungry computers. According to crypto researchers, the change is set to reduce Ethereum's energy consumption by some 99.95%.

That's a big deal because, like Bitcoin, Ethereum has historically used an enormous amount of energy to validate its transactions. Digiconomist estimates that the energy consumption of the two combined would rank 27th on a list of the world's most energy-intensive countries.

‍Ethereum > Bitcoin?

‍After skyrocketing in the last 2 years, cryptocurrencies have fallen back to Earth in 2022, losing a combined $2 trillion in market value — and Ethereum has been no exception. The total market value of all Ethereum is currently somewhere around half of Bitcoin's. Time will tell whether this major infrastructure change will see Ethereum finally unseat its rival.

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Apple is on its way to becoming the biggest smartphone seller in China

The memory crunch has made iPhones a more popular alternative as competitors’ prices rise.

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Microsoft loses exclusive access to OpenAI’s models and tools while ending revenue-sharing deal with ChatGPT maker

Microsoft shares dropped as it announced a revised agreement with OpenAI.

The amended agreement ends revenue-sharing payments from Microsoft to OpenAI, and also ends Microsoft’s exclusive access to OpenAI’s intellectual property (i.e. models and products).

OpenAI’s revenue sharing with Microsoft will end in 2030, is subject to a total cap, and is no longer dependent on its achieving artificial general intelligence.

Amazon, a likely beneficiary of this lack of exclusivity, initially popped on the news but erased those gains.

This is a developing story.

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China just blew up one of Meta’s key AI bets

China has ordered Meta to unwind its $2 billion acquisition of Manus, a Chinese startup (since relocated to Singapore) that makes AI agents and was central to Meta’s push to turn its massive AI investments into a real business. The move is part of the Chinese government’s effort to stop US firms from gaining access to Chinese talent and intellectual property, as Washington continues to restrict sales of advanced AI chips to Chinese companies.

Unlike its tech peers, which can sell AI through cloud services, Meta mainly uses AI to improve its existing ad business rather than as a stand-alone revenue driver. The decision strips away one of Meta’s clearest paths to monetizing AI — leaving it spending like a hyperscaler, without a hyperscaler business model.

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DeepSeek releases new V4 series models highlighting efficiency and long context

Chinese AI lab DeepSeek has released a major new version of its eponymous open-source AI models that are nipping at the heels of leading frontier models in some areas.

The most significant DeepSeek-V4 Pro and DeepSeek-V4 Flash both have a 1 million-token context — the amount of information the model can actively work with in a single session — which is a crucial feature for complex, long-running coding tasks.

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

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