RFK and the growing MAHA movement have only added fuel to the fire. But with disruption comes opportunity, and we believe this chaotic backdrop has created some of the most compelling setups in years.

Healthcare policy is uniquely susceptible to headline distortion, where perception often outruns reality. But this isn’t a bug… it’s a feature for active investors.

“Politics introduces bias, bias creates dislocation, and dislocation is where alpha is born.”

- BSR

Policy chatter has been loud, but mostly off-key. Washington’s latest rule changes landed with the usual fireworks, yet national health-spending is still projected to grow 5 %+ into 2025, hardly the apocalypse the headlines suggest.

So instead of trading on tweets, we follow the cash flows. Each supposedly “toxic” narrative (drug-pricing reform, election-year brinkmanship, even the AI-doctor hype cycle) contains a seam of opportunity once you strip away the fear-premium. Several of our top performers were born precisely where consensus shouted “avoid.”

And to sum it all up, we take a look at a mispriced sub-sector that looks, to me, like biotech circa 2012…

Volatile on the surface, but compounding for those willing to stomach the drama.

Read more

Read more

In an increasingly fragmented energy landscape, there’s no single bet that captures the full story. That’s why our new basket is built around a two-speed thesis: on one side, reliable exposure to the cash-generating core of today’s energy markets—producers, pipelines, and liquefied natural gas exporters. On the other, a calculated lean into the next frontier—nuclear technologies, infrastructure enablers, and national security tailwinds.

The first component focuses on the now: upstream names riding the wave of tight supply, geopolitical risk, and favorable pricing dynamics; midstream assets delivering yield, stability, and throughput optionality. It’s the classic energy trade—battle-tested and cash-flow positive.

But energy is no longer just hydrocarbons. The second component recognizes the slow but undeniable pivot toward durable energy infrastructure, clean baseload generation, and geopolitically sensitive supply chains. This is where names like LEU, BWXT, and FLS come into play—each representing a niche, underappreciated angle on the broader transition.

Together, this basket is designed to capture both the immediate opportunity and the longer-duration structural shifts—a balanced, high-conviction view of where global energy is today and where it’s going tomorrow.

Initiating Coverage: New Energy Infrastructure

Read more

This week, the AI world lit up when DeepSeek, a Chinese AI developer, released two new open-source models—DeepSeek-V3 and DeepSeek-R1, plus a set of instructions called R1 Zero. These models deliver performance on par with top-tier offerings from OpenAI and Anthropic, but with a shockingly lower price tag.

Naturally, everyone is buzzing about two things:

1. The performance: DeepSeek’s models seem to match or exceed the capabilities of more famous systems.

2. The cost: They’re offering API access at a fraction of the usual rate.

This prompted excitement—plus a healthy dose of skepticism—online. Some wonder if DeepSeek quietly amassed restricted GPUs or if the Chinese government is behind some grand “psyop.” Either way, they’re proving that cutting-edge AI can be trained and run more cheaply than ever before.

I’m not surprised. For nearly a year, I’ve thought of the second order effects that China’s “hardware handicap” would drive innovation in new architecture.

Sure enough, the cost-efficiency of DeepSeek’s models has rattled many investors, with some proclaiming the “death of the AI trade.” Others remain bullish on big hardware suppliers like NVIDIA (NVDA).

In my view, both sides are missing the point: efficiency is a good thing, and NVIDIA isn’t AI—they’re a critical hardware enabler. Meanwhile, cheaper and more efficient models could unlock an even larger universe of AI applications.

Phase 1 vs. Phase 2: The Ongoing AI Thesis

Read more

In this Investment Primer I will go in depth on the following:

• AI Growth Drives Data Center Expansion

• Importance of Spans

• Investment Opportunity

• Market Cycle Timing

• Telecom Sector's Potential

• Growth Drivers

• Current Industry Downturn

• Infrastructure Focus - Future technological integration

  • Fog Computing

  • Fiber Optics

  • Wireless Networks

  • Software

• Government Initiatives Programs

• Which Stocks to invest in

• Basket Composition

Read more

• Navigating the healthcare investment cycle

• Exploring how the sector has evolved post-COVID

• Identifying key areas of opportunity.

• Analyzing the current state of healthcare investing (highlighting how the cycle bust from COVID-19 affected the industry and what variables have shifted since then.)

• Introduction of companies driving innovation in 2 key sectors

• Strategy for portfolio construction (i.e. which stocks I’m including and % comp.)

• Further analysis on specific components within these baskets

• Potential for returns

I hope you enjoy the read.

Lets Dive In….

Read more

The traditional drivers of GDP growth—population growth, productivity growth, and debt growth—are undergoing significant shifts. In recent decades, reliance on debt growth has led to borrowing against future potential, a trend that culminated in the 2008 financial crisis. Today, much of the debt growth is merely servicing existing debt, leaving little room for new investments to drive economic expansion.

Challenges with Population and Productivity Growth

In the Western world, population growth has stagnated and, in some cases, is declining. This demographic shift, coupled with an aging population, poses a challenge to productivity growth. As the workforce ages, overall productivity tends to decline, compounding the issue. The confluence of these factors, within the broader context of the debt and debasement cycle, paints a concerning picture for traditional economic growth models.

The Role of Technology: A New Catalyst for Growth

However, technology presents a potential solution to these challenges. The integration of artificial intelligence (AI) and robotics is rapidly transforming industries, offering a new source of productivity and, indirectly, population growth. For instance, Amazon has expanded its use of robots from 250,000 to 750,000 in just three years, significantly boosting its operational efficiency. This trend suggests that the company's autonomous workforce could soon surpass its human workforce, as robots are often 3-10 times more productive than humans.

This shift challenges the traditional GDP formula, as AI and robotics can theoretically provide unlimited productivity growth. The question then becomes: what is required to support an infinite use of robots and AI? The answer lies in the availability of infinite electricity and computational power.

The Intersection of Technology and Green Energy

This need for vast energy resources brings the green energy narrative into focus. While some view the forced investment in Environmental, Social, and Governance (ESG) initiatives as unfounded or wasteful, it could play a critical role in enabling the technological future. By driving down the cost of capital for innovative energy solutions—such as nuclear, wind, solar, and geothermal energy—society can achieve significant reductions in the cost of electricity.

The potential multiplier effect of a 75% reduction in energy costs, combined with the exponential growth in productivity from an "infinite" workforce of robots and AI, is staggering. Just as the post-World War II baby boom led to a 30% increase in the population, we are on the cusp of a similar transformative period, this time driven by technological advances rather than human births.

Conclusion: Embracing the Technological Future

The future of GDP growth in an aging world hinges on embracing technology as the new engine of growth. AI and robotics, supported by advancements in energy technology, offer a path to sustained economic expansion even in the face of demographic challenges. As we move forward, the integration of these technologies will redefine the concept of productivity and growth, paving the way for a new era of economic development.

This technological future requires thoughtful planning and investment, particularly in the energy sector, to ensure that the necessary infrastructure is in place to support these advancements. As we transition to this new paradigm, it will be crucial to balance innovation with sustainability, ensuring that the benefits of technological progress are widely shared and contribute to a prosperous and equitable society.

Read more

Read more

Read more

Read more

Read more

Notably, when…

Read more

Read more

The burgeoning datasphere owes its expansion to a confluence of diverse trends, ranging from the surge in remote work arrangements and the proliferation of IoT devices to advancements in machine learning and the widespread integration of AI technologies. This growth is further fueled by the increasing accessibility of high-speed Internet connections across the globe. Consequently, the global Big Data market—comprising companies specializing in assisting enterprises in the management and utilization of colossal data volumes—is poised for significant expansion, with anticipated annual growth rates ranging between 11% and 13.5% until 2030.

The continuous influx of data serves immediate and apparent purposes, whether it's a social media selfie, a point-of-sale record from a local store, or a research annotation. However, the true power and versatility of data emerge when these individual pieces are aggregated into massive datasets. Large-scale datasets play a pivotal role in driving cutting-edge research endeavors, particularly in the realms of generative artificial intelligence, facilitating development, training, and rigorous testing processes, among other crucial applications.

Large datasets serve as more than just a glamorous tool; they play a pivotal role across diverse sectors, spanning finance, agriculture, insurance, retail, transportation, healthcare, education, and law enforcement. These extensive data pools are instrumental in enhancing:

1. Risk Management: By harnessing large datasets, entities across the business spectrum and governmental bodies gain a panoramic perspective on potential risks. They uncover concealed patterns and trends that serve as early indicators of risk events. These encompass operational setbacks like cyberattacks and fraud, as well as various financial risks and those stemming from natural disasters.

2. Operational Efficiency: Businesses leverage large datasets to fine-tune their operations, from optimizing supply chains and refining production processes to resource allocation and streamlining transportation and delivery logistics. In healthcare, these datasets empower hospitals and other providers to anticipate public health demands and elevate patient care standards.

3. Research and Product Development: The richness of big data enhances the efficacy of machine-learning models, facilitating breakthroughs in medical treatments, innovative materials, and detailed insights into consumer behaviors and preferences. Whether refining financial models, optimizing agricultural practices, or enhancing retail recommendations, large datasets are indispensable in driving research and product innovation.

Read more