Crypto struggles

Faded hopes for crypto-friendly policies

Cryptocurrency prices remained largely stagnant on Thursday, following a recent surge that pushed Bitcoin to its highest level in eight months. Despite the lackluster movement, analysts at ING observed that the crypto market was displaying resilience in the face of macroeconomic challenges.

Earlier this week, Bitcoin experienced a rapid rally of 15 percent, reaching its peak since last November. However, the gains were partially reversed on Thursday, with Bitcoin dropping by 0.6 percent to $40,088. Meanwhile, ether slid 0.3 percent to $3,192.06.

According to ING strategists, the crypto market was demonstrating surprising strength, considering the ongoing turbulence in the global economy. Rising interest rates and the potential for a U.S. recession have put pressure on riskier assets, including cryptocurrencies.

“The crypto market seems to be holding up remarkably well, all things considered. We’ve had a lot of macroeconomic uncertainty this year, with the war in Ukraine, rapidly rising interest rates, and the threat of a U.S. recession. In such an environment, you might expect risky assets like crypto to struggle,” stated strategists at the Dutch bank.

However, the strategists noted that the crypto market had remained resilient, attributing it to a shift in investor focus toward Web3 and artificial intelligence (AI).

“But instead, we’ve seen a strong performance in the first half of the year, fueled by interest in Web3 and AI, both of which are closely linked to the crypto ecosystem.”

Moreover, the strategists pointed out that the outlook for cryptocurrencies was becoming increasingly dependent on the narrative surrounding AI.

“The narrative around AI will be crucial for crypto in the second half of the year. If the enthusiasm for AI continues, it could bode well for further gains in crypto.”

In the realm of AI, researchers at DeepMind, a subsidiary of Google's parent company Alphabet, announced that they had developed an AI system capable of performing scientific discoveries. This breakthrough could revolutionize the way scientists approach research.

The AI system, known as Graph Neural Networks (GNNs), was trained on a vast dataset of scientific papers and data. It learned to identify patterns and make connections that would be difficult for humans to spot.

In their paper, published in the journal Nature, the researchers described how the GNN system was able to solve a 20-year-old problem in biology. Scientists had been trying to understand how different types of proteins fold into three-dimensional structures.

Using a simulation of a molecule with 100 amino acids, the researchers set the GNN system the task of predicting the molecule’s structure. Despite the complexity of the task, the AI system was able to quickly converge on the correct solution.

According to the researchers, this breakthrough could lead to the development of new drugs and materials. It could also be used to study climate change and other pressing global issues.

The development of an AI system capable of scientific discovery is a major milestone. It highlights the rapid progress that is being made in the field of artificial intelligence. As AI systems become increasingly sophisticated, they will be able to contribute even more to scientific knowledge and technological innovation.