2026-07-29 11:03:36

No, there are no resources for that.

Research by experts points to serious bottlenecks in the development of neural networks, including physical and economic constraints such as the availability of advanced chips and enormous power consumption.

AI advertising today is an interesting example of how marketing shapes expectations. Companies compete for attention and investment, so they often emphasize the most impressive use cases.

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2023-01-19 08:30:36

In 2042

Although China allocates 3 times more funds to microelectronics than its main competitors. China is currently dependent on US technology, and to overtake the US, it needs to create a new conductor technology. Such technology will be invented by 2040

The U.S. is already creating some tensions with its partners and will not be able to block the supply of key components to China in the future

Accuracy 10

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2025-12-14 07:43:49

In 2031.

Why is everyone talking about a bubble? 1) Huge investments with uncertain returns for many startups. 2) Thousands of AI startups that are essentially just a shell for other people's models. 3) High expectations: AI will replace everyone tomorrow. 4) Limitations of the models: hallucinations, high cost, dependence on data and computing power. OpenAI alone has attracted $300 billion in investments. Such investments will not pay off under any circumstances. By 2030, the company will need to show record profits, which it does not have.

Many AI startups will shut down or be acquired. Investors will become stricter: they want a real business case, not just 'we have AI'.

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