Core Insights - The article highlights the impressive performance of Google's Gemini 3, which has received positive evaluations across various benchmarks, outperforming competitors like Claude Sonnet 4.5 and GPT-5.1 in multiple dimensions [1][3] Benchmark Performance - Gemini 3 Pro achieved significant scores in various benchmarks, such as: - 91.9% in scientific knowledge without tools [1] - 95.0% in mathematics without tools [1] - 100% in mathematics with code execution [1] - 87.6% in knowledge acquisition from videos [1] - 72.7% in screen understanding [1] - The model's performance in complex reasoning tasks showcases its superiority in high-difficulty scenarios, indicating a breakthrough in AI capabilities [4][3] Technological Advancements - The advancements in Gemini 3 are attributed to improvements in pre-training and post-training methodologies [3] - The model was trained using Google's own TPU, which is a strategic advantage over NVIDIA's GPUs, potentially impacting NVIDIA's market position negatively [7][8] Cost Efficiency - Training costs using TPU V7 are reported to be only half of that of NVIDIA's B200, highlighting a significant cost advantage for Google [8][12] - The article emphasizes that the performance improvements are based on substantial computational power, suggesting that scaling laws still have room for growth [15] NVIDIA's Market Outlook - NVIDIA has consistently exceeded market expectations, with forecasts for Q3 revenue ranging from $555.56 billion to $567 billion, driven by sustained AI demand [17][19] - The company is expected to maintain high gross margins, with estimates around 73.5% to 74% for Q3, despite rising component costs [22][24] Competitive Landscape - NVIDIA faces competition from AMD's MI300 and in-house chip developments by major cloud providers like Google and Amazon, which could impact its market share [26] - The article notes that while NVIDIA's software ecosystem remains a stronghold, the emergence of alternative solutions may challenge its pricing power [26] AI Capital Expenditure Trends - Global AI capital expenditure is projected to reach $204.6 billion by 2026, with a significant increase in enterprise adoption of generative AI expected [27][28] - The demand for AI infrastructure is anticipated to support NVIDIA's growth, even if some startups reduce their GPU purchases [28]

Bitcoin, it briefly dipped below 90K, but it's back around $93,000. It's down about 10% in just one week. It's now negative for the year.Is this the bottom or are we headed lower from here. Joining me now is Cosmo Jang, general partner at Panta Capital. Cosmo, it's great to have you on.>> Hi, Morgan. Thanks for having me. >> Is this crypto winter coming early here.>> Look, we just had a long six-month rally, so some consolidation I think is very reasonable. Crypto tends to have these characteristics of risk ...

Market Overview - The market has shifted focus from trade tensions to earnings performance, with earnings continuing to reach new 12-month forward highs driven by AI capital expenditures [3][4] - Despite concerns about potential impacts from tariffs, overall earnings have not been significantly affected, allowing the market to maintain upward momentum [2][3] Valuation and Historical Context - Current valuations for major tech companies (excluding Tesla) average between 35 to 38 times forward earnings, which is significantly lower than the over 200 times seen in 1999 for companies like Cisco and Intel [5][6] - The market is not in a euphoric state similar to the late 1990s, suggesting that the current AI-driven growth may continue to support performance [6] Federal Reserve and Interest Rates - The probability of a rate cut in December is currently at 71%, down from 84%, indicating a cautious market sentiment despite some expectations for cuts [8][9] - Analysts suggest that while the market is pricing in rate cuts, there is a risk that the Fed may not deliver as expected, especially if labor market data does not indicate significant weakness [9][10][14] Economic Implications - The market's reliance on further rate cuts implies a belief that the labor market is weaker than suggested by current data, which could lead to aggressive valuations if growth estimates are too high [14][15] - A balanced approach to rate cuts is preferred, as excessive cuts could signal deeper economic issues, impacting market stability [14][15]

Core Viewpoint - The discussion centers around the growth of AI-related stocks and whether this growth indicates a bubble, with a focus on the sustainability of capital expenditure (capex) in the AI sector [2][4][10]. Group 1: AI Market Dynamics - AI-related stocks are experiencing supernormal growth due to a significant phase of capex buildout, but current earnings growth does not reflect the extreme valuations seen in past bubbles like 1999 [2][4]. - There is a concern that companies may be over-earning, and the pace of capex growth will be crucial to monitor through 2026 [3][4]. - The US equity market is being driven higher by AI capex, which in turn boosts consumer spending, creating a circular economic effect [9][10]. Group 2: Investment Strategies - The investment strategy suggests a balanced approach, incorporating optimism about technological advancements, caution regarding market corrections, and exploration of alternative investments [12][16]. - The optimistic view emphasizes the importance of investing in high-quality companies that benefit from AI capex rather than speculative names [17]. - The pessimistic perspective highlights the need for diversification in fixed income portfolios, particularly through municipal bonds, to mitigate risks associated with inflation [19]. Group 3: Alternative Investments - The nihilistic approach encourages looking beyond traditional asset allocations, with a focus on alternatives like crypto, which can provide lower correlation to public markets [21][22]. - Crypto is viewed as a psychological commodity sensitive to liquidity, making it a potential part of a risk asset allocation for investors with high risk tolerance [22].

Market Overview - There is evidence of bubble-like behavior in the AI sector, characterized by speculative actions and aggressive pricing [1][2] - The US market is experiencing a two-speed economy, heavily reliant on AI capital expenditures, which could lead to vulnerability if there is a slowdown [6][12] Investment Opportunities - Europe and Japan are seen as attractive investment areas due to their cheap valuations and resilience against recession fears [3][4] - Value stocks in Europe, particularly in financials, industrials, and pharmaceuticals, are trading at significant discounts compared to US counterparts, presenting good return potential [5] AI Sector Dynamics - The AI ecosystem is increasingly dependent on debt financing rather than cash flow, raising concerns about sustainability [9][12] - Companies like Nvidia are investing heavily in non-profitable firms, which may indicate a shift in the capital structure of the tech industry [8][11] Capital Investment Trends - The tech industry is becoming more capital-intensive, which could challenge the historically high returns on capital that were previously maintained [15][16] - Innovative financing structures, such as special purpose vehicles for debt management, are emerging but may signal underlying risks [14]

Economic Outlook & Investment Strategy - KKR认为美国正在经历类似于1990年代的生产力繁荣，这能够支持更高的工资、承受关税对利润率的影响，并最终推动收入增长 [8][9] - KKR的基本观点是，美国经济将继续以1.5%到2%的速度增长，并且可能略有上升 [14] - KKR预计美联储今年将降息两次，明年将降息三次，以支持市场 [15][28] - KKR认为企业正在继续增加资本支出，消费者状况良好，因此当前市场水平相对安全 [16] Sector & Regional Analysis - AI资本支出增长超过了个人消费的所有增长，这是一个巨大的变化 [3] - 亚洲市场（尤其是韩国和日本）存在投资机会，这些市场的估值较低，且企业正在进行改革 [17][18][19] - 亚洲内部贸易正在增长，预计将从目前的48%-50%增长到70%，类似于欧洲和美洲的水平，这将推动物流基础设施的发展 [22][23] Risks & Concerns - 如果AI领域的回报率下降过快，可能会对GDP产生影响 [26] - 如果失业率大幅上升至5.5%，将对经济体系造成冲击 [26] - 低收入消费者正在感受到更高通胀的影响，一些杠杆实体因利率上升而面临压力 [15] Labor Market Dynamics - 政府部门就业岗位的减少和医疗保健及教育行业的窄幅关注可能会导致政府数据表现不佳 [10] - KKR观察到企业招聘速度放缓，但没有出现大规模裁员 [11] - 如果不是因为特朗普政府限制了劳动力供应，失业率可能会接近5% [12]

Joining us right now for his take on the markets is Mike Wilson. He's chief investment officer and chief US equity strategist for Morgan Stanley. And Mike, it's great to see you. Morning. Before we talk more broadly, can you just comment on on Nvidia, what that means maybe for tech for tech companies at large? Yeah, I think this is back to the the issue we've been dealing with is like what's going to be sanctioned, what's not going to be sanctioned. I mean the 232 like what's going to be carved out. So this ...

Joining me now, Goldman's co-head of public tech investing, Sun Cho. It's good to see you. Welcome back.You as well. What a day to have you. Um, no China, no problem.I mean, is that's is that what the market is saying here. Look, I think it's you have to take a little bit of a broader picture of what's been going on with the AI trade, right. And it singularly has to do with the perception around AI capex, right.Just a couple of months ago when all of these stocks were under lows, there was this perception t ...