General Overview - The author encourages readers to reshare the content if they found it insightful [1] - The author shares tutorials and insights on Data Science (DS), Machine Learning (ML), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAGs) daily [1] Author Information - The author can be found on Twitter/X with the handle @_avichawla [1]

Core Insights - Nvidia's investment in OpenAI is projected to reach up to $100 billion, primarily for AI supercomputing facilities, with the first facility expected to be operational in the second half of 2026 [2][6] - OpenAI plans to lease Nvidia's GPUs rather than purchase them upfront, allowing for cost distribution over the GPUs' useful life, which could be up to five years [3][4] - The initial $10 billion from Nvidia will support OpenAI in deploying its first gigawatt of capacity [6] Investment Details - Nvidia's CEO described the deal as "monumental in size," estimating that an AI data center with a gigawatt of capacity costs around $50 billion, with $35 billion allocated for Nvidia's GPUs [4] - The lease arrangement allows OpenAI to manage costs more effectively and potentially secure better terms for future debt financing [9] - OpenAI executives have indicated that equity financing is the most expensive way to fund data centers, and the company is preparing to take on debt for further expansion [8] Operational Implications - The investment will primarily enhance OpenAI's compute capabilities, which are essential for building and training large language models [7] - OpenAI's CFO highlighted the role of partners like Oracle in financing, with Oracle leasing the Abilene facility [10][11] - OpenAI is focused on increasing compute capacity to meet growing demand, emphasizing the need for more resources to support its business model [12][15] Market Context - Nvidia's market cap has surged to $4.3 trillion, driven by GPU sales to OpenAI and other tech giants [13] - OpenAI's valuation is projected at $500 billion, supported by significant investments from Microsoft and others, allowing the company to sustain cash burn while developing AI models [13] - Concerns have been raised about the sustainability of the AI boom, with analysts noting the circular nature of funding arrangements [14]

The recent AI explosion has been largely based on large language models. But small ones are starting to steal a march, @HenryTricks tells “The Intelligence” https://t.co/6gpwRU7kRy https://t.co/zAViunD26D ...

That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.AAvi Chawla (@_avichawla):Researchers from AssemblyAI built a state-of-the-art model that:- transcribes speech across 99 languages.- works even if the audio has many speakers.- outperforms Deepgram and OpenAI models.And much more.(2-step setup below) https://t.co/7eg0zpE4pM ...

Core Insights - A recent study indicates that leading large language models (LLMs) can now pass the CFA Level III exam, including its challenging essay portion, which was previously a struggle for AI models [2][4]. Group 1: Study Overview - The research was conducted by NYU Stern School of Business and Goodfin, focusing on the capabilities of LLMs in specialized finance domains [3]. - The study benchmarked 23 leading AI models, including OpenAI's GPT-4 and Google's Gemini 2.5, against the CFA Level III mock exam [4]. Group 2: Performance Metrics - OpenAI's o4-mini model achieved a composite score of 79.1%, while Gemini's 2.5 Flash model scored 77.3% [5]. - Most models performed well on multiple-choice questions, but only a few excelled in the essay prompts that require analysis and strategic thinking [5]. Group 3: Reasoning and Grading - NYU Stern Professor Srikanth Jagabathula noted that recent LLMs have shown significant capabilities in quantitative and critical thinking tasks, particularly in essay responses [6]. - An LLM was used to grade the essay portion, and it was found to be stricter than human graders, assigning fewer points overall [7]. Group 4: Impact of Prompting Techniques - The study highlighted that using chain-of-thought prompting improved the performance of AI models on the essay portion, increasing accuracy by 15 percentage points [8].

We want to get into your tech investments. We want to get into your views. But we got to put this question to you around H-1B visas and this new application fee.What do you make of it. What's the impact. Well, again, this is part of President Trump's negotiating process, and I think he's negotiating quite intensively right now with India.I think India would be have the biggest impact here in terms of, you know, workers in the United States. So I think this is a little bit like tariffs and it's going to capt ...

Delphi-2M’s creators reasoned that an AI tool fed on large amounts of human-health data could have similar predictive power for diseases as large language models do for text https://t.co/smz3xJZ2bG ...

Core Viewpoint - Palantir Technologies has experienced a significant stock increase of nearly 400% over the past year, raising concerns about the sustainability of this growth and potential risks ahead [1]. Group 1: Enterprise AI Market Performance - The enterprise AI sector may be underperforming, with a study from MIT indicating that 95% of enterprise AI pilots fail to deliver meaningful results [2]. - This raises questions about the sustainability of the substantial capital investments in both hardware and software within the industry [3]. Group 2: Palantir's Business Performance - Palantir's second-quarter revenue surged by 48% year over year to $1 billion, with U.S. enterprise clients driving a 93% increase in sales to $306 million [4]. - Despite the challenges in the enterprise AI market, Palantir's growth is primarily fueled by private sector adoption of its AI-driven data analytics tools, which contrasts with the MIT report [5]. Group 3: Competitive Landscape - Palantir faces competition from other enterprise software companies like Snowflake and Microsoft, which also offer AI-powered data analytics solutions [6]. - This competition may impact Palantir's market share, growth potential, and profit margins in the long run [6]. Group 4: Valuation Concerns - Palantir's forward price-to-earnings (P/E) ratio is approximately 200, significantly higher than the S&P 500 average of 22 and other AI stocks like Nvidia and Microsoft, which have forward P/Es of 40 and 33, respectively [9]. - The high valuation is difficult to justify based on fundamentals, and the company's popularity may be influenced by the political connections of its co-founder, Peter Thiel [10]. Group 5: Political Exposure Risks - Palantir's political connections could pose risks, as a politically charged brand might deter enterprise clients [11]. - Overall, the risks associated with Palantir's stock currently appear to outweigh the potential rewards, suggesting a need for a valuation correction before investment consideration [11].

General Information - The author encourages readers to reshare the content if they found it insightful [1] - The author shares tutorials and insights on DS (Data Science), ML (Machine Learning), LLMs (Large Language Models), and RAGs (Retrieval-Augmented Generation) daily [1] Author Information - The author can be found on Twitter (now X) with the handle @_avichawla [1]

Iron Mountain Conference Call Summary Company Overview - **Company**: Iron Mountain (NYSE: IRM) - **Date of Conference**: September 16, 2025 Key Industry Insights Records and Information Management (RIM) - RIM constitutes over 70% of Iron Mountain's business, maintaining strong pricing and volume growth despite being a slower-growing segment [4][5] - The company has achieved mid to upper single-digit revenue management or pricing action in RIM, with volume growth between 20 to 100 basis points per quarter [6] Growth Portfolio - The growth portfolio, including Asset Lifecycle Management, Data Centers, and Digital Solutions, has driven approximately 6% consolidated growth in top-line and bottom-line [5] - The growth portfolio is collectively growing in excess of 20% and is expected to continue [9] Data Centers - Iron Mountain has secured significant power capacity for future data center expansions, with plans to bring online 450 megawatts over the next 12 to 36 months [14] - The data center business is projected to approach $800 million in revenue for 2025, with expectations to exceed $1 billion in 2026 [19] - The company has seen a shift in customer focus back to their core data center offerings, moving away from large language model campuses [12][15] Asset Lifecycle Management (ALM) - ALM is primarily project-based, with significant growth potential as data center decommissioning increases due to the lifecycle of equipment [20] - There is a strong cross-sell opportunity between the core enterprise storage business and ALM, with only single-digit percentage crossover currently [21] Financial Performance Margins and Growth - The global RIM business has high incremental margins of 70% to 80%, while the Data Centers business has recently achieved EBITDA margins of over 50% [8] - Renewal spreads in the Data Centers business have been favorable, with increases of 10% to 20% [26] Capital Expenditure and Funding Strategy - Iron Mountain's capital-light core business generates substantial cash flow, allowing for funding of growth initiatives without excessive leverage [29] - The company has utilized sale-leasebacks and asset-level financing to support capital needs [29] Government Contracts - Iron Mountain has secured a five-year contract with the U.S. Department of Treasury for digitization of tax returns, valued at approximately $140 million [31][32] - The contract is expected to ramp up in volume, particularly during tax season, although no guidance has been provided for this year [33] Additional Considerations - The company emphasizes the importance of securing power for data centers, noting that it has become a significant constraint in recent years [28] - The decision cycle for data center leases remains stable, although there is a trend away from long-term commitments [16][18] This summary encapsulates the key points discussed during the Iron Mountain conference call, highlighting the company's strategic focus, financial performance, and growth opportunities within the industry.