I’m watching $NBIS closely because I believe AI infrastructure could become one of the biggest opportunities as AI agents drive demand for inference. With approximately 3.5 GW of contracted power and only a fraction currently active, Nebius has significant room to scale. Its growing serverless inference business could also improve revenue potential per MW. After the recent drawdown, the valuation looks interesting to me, but execution and capacity deployment will be key to watch.

Nvidia, $NVDA, is using AI to transform how chips get made. The company unveiled new CUDA-X AI tools to speed up semiconductor design, manufacturing and factory automation. Synopsys, Cadence, Applied Materials, Lam Research and KLA are among the companies adopting them. Nvidia says the tools can speed up some workflows by up to 50x.

At this stage is clear that most AI models are aiming to get cheaper and not better. Companies burning billions by undercutting each other on proces and selling tokens way below their value. They realized they either keep burning investor money to operate and be ahead of others, or they focus on bringing the price/value to a profitable level. As usually @grok went hard on the budget models with 4.7 which dirt-cheap while got a lot of heat for not beating the top models. I expect a slight deaccelaration with model capabilities and a lot more progress on sustainability.

This Week in AI, brought to you by Holoworld @OpenAI released 722 math manuscripts from an internal frontier model, while @Microsoft unveiled Maia 300 as it pushes deeper into custom AI silicon. @AnthropicAI, @GoogleCloud and @Meta all shipped new models or agents this week, and TypeSafe raised $870M just weeks after launching its non-text decision model Jev. AI is spreading beyond chat into research, infrastructure, agents and decision-making.

HUGE: @nvidia CEO @JensenHuang says AI has become essential to designing the company's chips and software. “We can’t design a chip anymore without AI.” Huang revealed that NVIDIA uses AI to explore new chip designs, boost performance, reduce energy consumption, write software and detect bugs. “Our chips are so much better because of AI.”

Nvidia agreed on September 3 to acquire Hugging Face, one of the most widely used hubs for open models. Nvidia says the aim is to protect open-source AI developers. The dominant GPU vendor will now also own one of the main places open models are published. For the person using those models, little changes. With every inference-as-a-service player today, you still cannot check the proof for: → Which model answered a request → Who could read your prompt → What happens to your data You trust whoever sits in the middle. Open models only stay open if anyone can verify how they run, whoever owns the hub. That takes an execution layer with no owner, where the network checks which model ran and keeps the data private.

AI needs more than chips. It needs POWER. ⚡ McKinsey projects global data-center demand could reach 219 GW by 2030, up from 82 GW in 2025. Big opportunity. But announced capacity ain’t cash flow. Watch debt, execution and profits—not just the AI headline. #AI #DataCenters #AIInfrastructure #StockMarket #GrowthStocks #LongTermInvesting #TradingSyndicates $ETN $VRT $GEV $NVDA $AVGO $ANET

AI BOOM DRIVES UP COMPUTER PRICES: U.S. TECHNOLOGY INFLATION HITS A 20-YEAR HIGH Massive investments in AI infrastructure have coincided with a notable increase in consumer technology prices in the United States. September inflation data revealed one of the sharpest annual increases in computer and hardware prices in the past two decades, bringing the impact of AI demand on prices into the economic spotlight. Annual Increase in Computer Prices Reaches 9.7% In September, prices for computers, peripherals, and smart home assistants rose 9.7% year over year. This marked the highest annual increase recorded since at least 2006. Annual price increases for computer software and accessories reached 28.4%. The data show that cost pressures on technology products are not limited to hardware but are also spreading across different product categories. AI Investments Are Driving Up Costs Technology companies are increasing spending on data centers, advanced processors, and high-performance servers, strengthening demand across the hardware supply chain. Intense demand for advanced processors from manufacturers such as Nvidia is making capacity constraints and supply costs increasingly important. The expansion of investment in AI infrastructure can create upward price pressure in areas where production capacity and component supplies cannot keep pace with demand. The extent to which these effects are passed on to consumer technology products will be closely monitored in the coming months. A New Inflation Risk for the Fed Rising technology prices are among the factors that could complicate the Federal Reserve’s efforts to bring inflation back to its 2% target. In particular, if AI investments continue to push up costs in sectors beyond energy and housing, the risk of inflationary pressures spreading more broadly could increase. The rise in U.S. consumer inflation to 3.7% year over year in September also indicates that price pressures persist. If increases in technology prices become entrenched alongside energy costs, the Fed may need to take a more cautious approach to monetary policy. AI Growth Could Fuel Inflation AI is expected to improve productivity and reduce production costs over the long term. However, before these gains fully materialize, infrastructure spending, chip demand, and energy requirements can generate inflationary effects in the short term. The critical question for markets is whether these cost increases will prove to be a temporary consequence of an investment cycle or spread to consumer prices and develop into more persistent inflationary pressure. If AI investment continues to support economic growth while also pushing prices higher, the Fed may face an increasingly difficult balancing act between sustaining economic expansion and keeping inflation under control. bitcoin:native ripple:native