Alphabet Unveils Gemini 3.8 Flash and Fairwind Program

Temasek, Singapore's state investment company, has warned that if the investment momentum in artificial intelligence, or AI, begins to fade, it could become the single biggest risk to financial markets right now, even though there is no sign of that happening soon. Rohit Sipahimalani, Temasek's chief investment officer, said at the Milken Institute Asia Summit in Singapore that while there is still no clear signal that AI investment is slowing, markets could face volatility in 2027. AI has been a key driver keeping the S&P 500 near a record high, even as US Treasury yields have risen. However, the overall market is not strong across the board, because roughly half of the stocks in the Russell 3000 index have fallen at least 20% from their June peak, reflecting that most of the market's gains have been driven by just a handful of stocks. Temasek believes the AI investment momentum could stall for several reasons, such as safety concerns leading governments to impose stricter regulations, or customers beginning to see AI technology investments as not delivering returns worth the money spent. At the same time, Temasek remains positive on AI over the long term and is continuing to increase its investments in the sector. Currently, about half of its AI investments are in publicly traded assets, and the company wants to raise that share to around 70-75% so it can adjust its portfolio more quickly as the AI industry changes, since unlisted assets can take longer to sell or reduce. Temasek has invested in private AI model developers such as OpenAI and Anthropic, but Sipahimalani said Temasek will limit the proportion of its investments in these companies because they are assets that are harder to adjust than publicly traded ones.

Two widely accepted narratives about global artificial intelligence are unraveling as market data show U.S. models are often cheaper per completed task than Chinese competitors, while enterprise AI spending is stabilizing despite surging usage. Martin Chorzempa, a senior fellow at the Peterson Institute, wrote in a social media post Tuesday that benchmarking data from Artificial Analysis indicates top U.S. models from developers like OpenAI, Anthropic, and Google tend to be more efficient with tokens when accomplishing equivalent tasks, even though Chinese models may offer lower upfront pricing per token. Chorzempa noted that industry observers routinely focus on technical papers from Chinese labs highlighting architectural improvements while overlooking what U.S. firms have behind the scenes that would cut down on their number one cost, alongside access to more efficient hardware chips. He also pointed out that while open-weight models can be downloaded for free, most commercial enterprises rely on cloud infrastructure, where Chinese labs are reportedly asking for a 30% cut from cloud providers, passing additional expenses on to enterprise users. Separately, Chorzempa cited analysis from Ara Kharazian, lead economist at AI finance platform Ramp, showing that corporate AI spend actually fell 5.2% in recent tracking even as token consumption volumes reached all-time highs, with businesses becoming increasingly adept at picking the right cost and capabilities tradeoffs and leveraging fierce price competition between major U.S. labs.