Big Tech faces financial reckoning if human-level AI doesn’t happen soon

Cointelegraph · 2024-07-05T20:17:50.000Z

Artificial intelligence (AI) companies may need to make good on promises to develop artificial general intelligence (AGI) in the near-term in order to make up for the disparity between investments and profits in the industry. Unfortunately, there’s still no scientific evidence that AGI — machines capable of human-level or greater reasoning — is even possible. A growth market According to analysts, the current AI market is largely anticipatory. OpenAI is one of the few highly profitable generative AI enterprises and the difference between its revenue (about $3.4 billion, according to the Information) and the next closest competitors is massive. What this amounts to is a capital dearth, or a negative flow in the amount of somewhere in the area of $600 billion, at least according to recent analysis from Sequoia Capital. Source: Sequoia Capital. It bears mention that Sequoia’s figures are based on estimates of Nvidia GPU usage. With this in mind, it’s probable that the figures above are slightly deflated where global industry expenditures are concerned. Essentially, the analysis indicates that AI companies need to make up more than half a trillion in revenue to justify current expenditures — a figure expected to grow year over year. Where’s the product? While the current surge in investor and corporate interest in generative AI technology may have driven the market to all-time highs, including Nvidia’s brief tenure as the world’s most valuable company by market cap, many analysts are asking when the actual AI products or services that are going to sustain this level of growth are going to arrive. As of yet, it’s hard to argue that generative AI has found a legitimate use case that will lead to exponentially expanding profits for those invested. ChatGPT might be the sector’s flagship product, but there’s little reason to believe it’s going to suddenly explode into the mainstream. Simply put, that $600 billion revenue mark will take decades to reach if OpenAI’s 10-digit profit margin is carrying the bulk of the market. Generative AI has yet to find the same kind of value proposition that machine learning has, yet investments continue to ramp up at the VC, government, and corporate levels. This could very well indicate that the AI market will soon enter an “AGI or bust” era where the viability of companies such as OpenAI and Anthropic will depend on whether they’ve made the right bets when it comes to delivering machines that can reason as well as humans. On the negative side of things, those companies at the heart of the generative AI sector may be coming up on crunch time for revenues. If the market can’t justify Nvidia’s position at or near $3 trillion soon enough to avoid a potential drawback, then that $600 billion dearth for the industry could widen to the point of no return. However, on the positive side of things, the point of no return won’t exist if the industry actually invents AGI. And Nvidia is also the key to this scenario. As Sequoia Capital also pointed out, Nvidia is gearing up to launch its new Blackwell-based chipset (called the “B100”) for training generative AI. The B100 is purported to outperform the current industry standard for training models (Nvidia’s H100) by as much as 2.5X and will reportedly only cost 25% more. If the experts believe it was possible to realize AGI before Nvidia’s latest and greatest chip was released, it should follow that it’ll be even easier with hardware featuring a 150% increase in power and efficiency. Related: Softbank lost 99% when the dotcom bubble burst, now it’s all-in on AI

人工智能（AI）公司可能需要兌現近期開發通用人工智能（AGI）的承諾，以彌補行業投資和利潤之間的差距。
不幸的是，仍然沒有科學證據表明 AGI（具有人類水平或更高推理能力的機器）是可能實現的。
增長型市場
分析師認爲，目前的人工智能市場很大程度上是預期性的。OpenAI 是少數幾家利潤豐厚的生成式人工智能企業之一，其收入（據 Information 報道約爲 34 億美元）與緊隨其後的競爭對手之間的差距巨大。
根據紅杉資本最近的分析，這相當於資本短缺，或者說是約 6000 億美元的負流動。
值得一提的是，Sequoia 的數據是基於對 Nvidia GPU 使用情況的估計。考慮到這一點，上述數字可能在全球行業支出方面略有縮水。
從本質上講，分析表明，人工智能公司需要賺取超過 5000 億美元的收入才能證明當前支出的合理性，而且這一數字預計還會逐年增長。
產品在哪裏？
雖然目前投資者和企業對生成式人工智能技術的興趣激增，可能推動市場達到歷史最高水平，包括英偉達短暫成爲全球市值最高的公司，但許多分析師都在問，何時纔會出現能夠維持這一增長水平的實際人工智能產品或服務。
到目前爲止，很難說生成式人工智能已經找到了合法的用例，並將爲投資者帶來成倍增長的利潤。
ChatGPT 可能是該領域的旗艦產品，但沒有理由相信它會突然成爲主流。
簡而言之，如果 OpenAI 的十位數利潤率佔據了大部分市場，那麼要達到 6000 億美元的收入目標將需要幾十年的時間。生成式人工智能尚未找到與機器學習相同的價值主張，但風險投資、政府和企業層面的投資仍在不斷增加。
這很可能表明人工智能市場將很快進入“AGI 或破產”時代，OpenAI 和 Anthropic 等公司的生存能力將取決於他們在提供能夠像人類一樣推理的機器方面是否做出了正確的選擇。
而負面的一面是，那些處於生成式人工智能領域核心地位的公司可能正面臨收入的關鍵時刻。如果市場不能儘快證明 Nvidia 市值接近或達到 3 萬億美元以避免潛在的不利因素，那麼該行業 6000 億美元的缺口可能會擴大到無法挽回的地步。
然而，從積極的一面來看，如果業界真的發明了 AGI，就不會出現無法挽回的局面。而 Nvidia 也是這一場景的關鍵。
紅杉資本還指出，Nvidia 正準備推出基於 Blackwell 的新型芯片組（稱爲“B100”），用於訓練生成式 AI。據稱，B100 的性能比當前行業訓練模型標準（Nvidia 的 H100）高出 2.5 倍，而價格僅高出 25%。
如果專家們相信在 Nvidia 最新最好的芯片發佈之前就有可能實現 AGI，那麼隨着硬件的功率和效率提高 150%，實現 AGI 會變得更加容易。
相關：互聯網泡沫破裂時軟銀損失了 99%，現在它全力投入人工智能

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