Core Viewpoint - Alphabet is positioned as a leading AI stock for the next decade, potentially surpassing competitors like Nvidia, Tesla, and Meta due to its comprehensive involvement in various AI sectors [2][7][14] AI Ecosystem - AI encompasses a wide range of technologies, with large language models (LLMs) being a significant focus since the launch of ChatGPT [4] - Cloud platforms play a crucial role in AI development, with Nvidia's GPUs being the standard for AI model deployment [5] Alphabet's Strengths - Alphabet's Google Gemini 3.0 is recognized as a powerful LLM, enhancing its position in AI model development [8] - Google Cloud is experiencing rapid growth in AI applications, outpacing larger competitors like AWS and Azure [9] - Alphabet's Waymo unit is leading in the robotaxi market, providing services in five cities and planning to expand to twelve more, including London [10] - The company is also developing humanoid robots through its Gemini Robotics models in collaboration with Apptronik [10] Future Innovations - Alphabet is integrating AI into smart glasses through a partnership with Warby Parker, and aims to develop artificial general intelligence (AGI) by 2030 [11] - Google Workspace tools are being enhanced with agentic AI, and the company is working on a universal AI assistant [12] Investment Proposition - While smaller companies may outperform Alphabet in stock performance over the next decade, Alphabet is viewed as offering the best overall risk-reward proposition in the AI sector [14]

With Alphabet's record-breaking rally taking a pause and Nvidia bouncing, the two going head-to-head for AI chip partnerships with Nvidia customer Meta reportedly looking to strike a deal with Google. Joining me with his take on the entire AI space, CQG partners portfolio manager Brian Kershman. And Brian, it's great to to have you uh to check in on this take of yours where, you know, I think you've you've guys have believed that pe the market was over excited about the AI opportunity for a while.Now, the m ...

Joining us now Xia CEO of AI consulting firm Malo Santo also a former global strategy lead for responsible innovation at Google. X first of all just let me get your take on on Gemini 3 which seems to have certainly uh captured the imagination of many investors and performed quite well on all those benchmarks that all you AI people do to sort of you know get a sense for that latest model. What are your thoughts.>> Yeah 100%. So, I will say first of all that Gemini was state-of-the-art up until last night. Uh ...

An AI pioneer is convinced that most in his field have been led astray by the siren song of large language models https://t.co/AFcCW3ItGI ...

Yann LeCun invented many fundamental components of modern AI. Now he’s convinced most in his field have been led astray by the siren song of large language models. https://t.co/MwW3pcCIji ...

AI Technology & Trends - Yann LeCun, a key figure in modern AI, believes the field is misguided by large language models [1]

AI and the Federal Reserve - The Fed is dedicating significant attention to AI, with approximately 25% to 33% of Fed communications addressing the topic [2] - A Fed governor suggests policymakers should allow AI disruption, trusting long-term benefits will outweigh costs, similar to historical technology trends [2] - History indicates new technology fosters growth and employment, with capital and labor acting as complements [3] - The challenge for policymakers is to facilitate worker and firm adaptation, ensuring efficiency gains translate to higher wages and growth [3] AI's Impact on Labor and Productivity - AI-related job losses are currently managed through attrition and retraining, but layoffs are expected to increase, particularly for college-educated workers [5] - AI presents potential threats including fraud, disinformation, bias, and cybersecurity [6] - The Fed anticipates AI could deliver greater productivity, potentially allowing the Fed to operate at a lower rate [6] Regulatory Approaches and Investment - A Fed governor suggests the US approach of allowing technology to develop before regulating is superior to Europe's preemptive regulation [7] - The US approach is credited for the US leading Europe in the 1990s technological boom [7] - A report indicates AI investment may have peaked in the first half of the year [8] Monetary Policy Implications - One Fed governor suggests the neutral rate could be higher due to capital investment from AI [8] - The potential influence of AI on monetary policy, particularly regarding long-run rate outlook changes due to investment and productivity booms, remains a key consideration [9][10]

Core Insights - Micron Technology, Inc. is set to report its fourth-quarter fiscal 2025 results on September 23, 2025, with projected revenues of $10.7 billion, indicating a year-over-year growth of 43.3% [1][8] - The company estimates adjusted earnings of $2.50 per share, while the consensus estimate has been revised to $2.87 per share, reflecting a year-over-year improvement of 143.2% [2][8] Revenue and Earnings Estimates - The Zacks Consensus Estimate for Micron's fourth-quarter revenues is $11.1 billion, which is higher than the company's projection [1][8] - The earnings per share (EPS) consensus has increased from $2.85 to $2.87 over the past week, indicating positive sentiment [3][5] Market Dynamics - The demand for memory chips is expected to rise significantly due to the increasing adoption of GPU-enabled AI servers, which is likely to enhance Micron's revenue [6][8] - Improved supply-demand dynamics in the memory chip market have led to better pricing for DRAM chips, with fourth-quarter DRAM revenues expected to reach $7.1 billion, a 50.7% year-over-year growth [7][8] Competitive Positioning - Micron has achieved industry-first advancements in memory technology, positioning itself well for future demand [9] - The company is benefiting from a favorable pricing environment for DRAM and NAND chips, driven by the scarcity of advanced DRAM supplies due to AI server demand [15] Valuation Metrics - Micron's shares are currently trading at a price/sales ratio of 3.79, which is lower than the industry average of 3.87, indicating a potential undervaluation [12] Investment Considerations - The company is experiencing growth due to improved market dynamics and effective sales strategies, particularly in data centers and other sectors [14] - Collaboration with NVIDIA for AI technologies is expected to strengthen Micron's market position [16][21]

Technology & Knowledge - Large language models like ChatGPT are increasingly used for information retrieval [1] - These models do not contribute to the overall stock of knowledge [1]

Company Focus & Strategy - Cohere is uniquely focused on bringing large language model (LLM) technology to enterprise, training models for enterprise tool use and API integration within businesses [1] - Cohere trains efficient models that can fit on two GPUs, aiming for a balance between performance, cost, and accessibility for enterprise deployment [1] - Cohere prioritizes Return on Investment (ROI) over Artificial General Intelligence (AGI), focusing on helping enterprises achieve practical AI deployments [14] Model Training & Data - While the transformer architecture remains largely unchanged, Cohere focuses on refining training methods, including the use of synthetic data to augment real-world data [1] - Data quality remains a bottleneck, requiring a combination of real-world and synthetic data, with in-house annotators creating real data [1] - Cohere releases model weights for non-commercial usage, aiming to build credibility within the research community while maintaining a commercial business model [10] Competition & Market - Cohere differentiates itself from consumer-focused companies like OpenAI and Anthropic by concentrating on enterprise solutions and knowledge worker augmentation [14] - The company views being Canadian as an asset, attracting companies interested in working with non-American tech companies due to geopolitical considerations [18] - Cohere believes that benchmarks are not always an accurate reflection of the utility value of models, as they can be gamified and may not align with enterprise use cases [4] Talent & Workforce - Cohere acknowledges the war for AI talent but emphasizes the importance of stability, purpose, and value alignment in attracting and retaining employees [5] - The company believes that LLMs will augment human work, automating boring tasks and allowing people to focus on creativity, communication, and strategic thinking [8] - Cohere foresees changes to the workforce similar to those brought about by previous technological revolutions, emphasizing the need for policies to ensure a smooth transition and address income inequality [8][9] Future Predictions - By 2026, Cohere predicts that users will be able to use language to interact with computers to automate tasks like filing expenses [21] - The company believes that the skill of prompting will become less relevant as language models are trained to better fit how people expect them to work [12] - Cohere anticipates that language will become a more important part of how people interact with computers, though graphic user interfaces will still be valuable [18]