June 2025
As we move through 2025, we’re excited to share perspectives on the trends and shifts in U.S. Early-Stage, Net New Enterprise Technology. We encourage you to explore our key insights below, along with notable updates from our portfolio companies.
View from the Top: Key Trends and Insights
Global GDP Statistics (2024)
The United States stands out as the clear leader in gross domestic product (GDP) among selected countries in 2024, accounting for 26% of global GDP, significantly outpacing all other economies represented. This substantial economic footprint underscores the influence of the U.S. in global trade, financial markets, and geopolitical affairs, reinforcing its ability to shape international economic policy.
Although China is not depicted in the chart, it remains a critical force in the global economy. In 2024, China’s GDP reached $18 trillion, supported by an annual growth rate of approximately 5%—more than double the United States’ growth rate of 2.5%. This accelerating expansion signals China’s rising economic influence and its potential to narrow the gap with the U.S. over time. The pressing question now is how the United States will adapt its economic strategies to bolster growth and sustain its global leadership in the face of intensifying competition.
Private vs Public Companies
There is a substantial disparity between the number of private and publicly listed companies in the United States, with approximately 58,000 private companies compared to just 4,300 public ones. This stark contrast underscores the depth and diversity of the U.S. economy, driven by a thriving private sector that plays a critical role in both economic growth and domestic consumption. Private enterprises contribute meaningfully to GDP by fueling innovation, creating jobs, and stimulating demand across industries, reinforcing the overall robustness of the U.S. economic system.
The relatively small number of publicly listed companies suggests a saturated and increasingly crowded public market, where investment opportunities are more constrained. The vast and growing private sector presents significant untapped potential for investors seeking exposure to earlier-stage growth. As more value creation occurs before companies reach the public markets, participating in the private sector has become essential for capturing a broader share of economic expansion. This trend reflects a shift in how and where economic growth is occurring, one that rewards diversified engagement across both public and private domains.
The World has 11,800 Datacenters: Where are they Located?
The United States is home to 46% of the world’s total datacenters, a commanding share that underscores the country’s early investment and leadership in digital infrastructure. Advanced economies like the U.S. demand significant data center capabilities to support innovation, productivity, and digital services. The dominance of the U.S. in data center infrastructure is further amplified by the global reach of companies such as Google, Microsoft, and Amazon. These companies not only operate expansive domestic facilities but also deploy data centers internationally that are built on U.S.-developed technologies and standards.
Without the capabilities that data centers provide, nations are limited in their ability to scale technology, enable artificial intelligence, and drive economic progress. In essence, robust data infrastructure is now a prerequisite for national competitiveness and sustained economic growth.
AI Continues to Beat Humans in Tasks
AI systems are increasingly surpassing human performance across a variety of tasks. Several AI models have consistently exceeded the human baseline threshold in key domains, such as language understanding, image recognition, and problem-solving. This trend signals that AI capabilities are not only evolving rapidly but also doing so with a trajectory that shows no signs of slowing. As these systems continue to improve, it’s clear that AI is becoming not just a complementary tool, but a fundamental enabler of progress.
Unlike humans, who are constrained by biological limitations—finite memory, limited processing speed, and a need for rest, AI possesses virtually unlimited capacity to store, compute, and correlate massive amounts of information at scale. By accepting that AI exists and will continue to evolve, the real opportunity lies in how we choose to integrate it into our lives. Humans can leverage AI to free up cognitive space, accelerate innovation, build new skills, and solve complex global challenges.
Portfolio Company Milestones
Several Cota portfolio companies have achieved notable milestones that we’re excited to share. We encourage you to explore these updates further:
CAST AI secured a $108 Million Series C round to propel the future of Application Performance Automation. LEARN MORE
Capella Space – IonQ announced that it has signed a definitive agreement to acquire Capella Space Corporation, a signals platform leader for top-secret government and commercial applications, to facilitate a global space-to-space and space-to-ground satellite quantum key distribution (QKD) network, highlighting its ambitions to be the first company to have both a quantum network and quantum computer in space. LEARN MORE
Auradine secured $153 Million in Series C financing to expand its product portfolio and accelerate its mission to deliver scalable, sustainable and innovative infrastructure for the AI and blockchain era. LEAR MORE
Amplifier Security raised $5.6 Million to power autonomous user security and announced its User Security Graph and AI Automation Studio to scale its platform for real-time user risk reduction. LEARN MORE
At Cota, we are constantly exploring the intersection of technology and its broader impact on industries. Here are some of our latest research articles:
The Solution to Hallucinations in LLMs Will Likely Not Be Found Within
Despite the widespread adoption and impressive capabilities of Generative AI chatbots like ChatGPT and Claude, a critical challenge persists: “hallucinations,” where Large Language Models (LLMs) produce factually incorrect yet grammatically sound outputs. This article delves into the underlying reasons for these inaccuracies, explores current mitigation strategies like Retrieval-Augmented Generation (RAG) and Large Reasoning Models (LRMs)—and their inherent limitations—ultimately arguing that a new architectural approach, such as Neuro-Symbolic AI, is essential to achieve the unwavering reliability required for high-stakes enterprise applications. Read the full article here
Redefining Connectivity and Edge Intelligence with AI-Designed Smart Networks
AI and edge intelligence are transforming connectivity, enabling adaptive networks that are not only efficient and scalable but also resilient in the face of growing complexities. From logistics to manufacturing, this piece delves into real-world applications that highlight the profound impact of this technological evolution.
Avoiding LLM Hallucinations: Neuro-symbolic AI and other Hybrid AI approaches
Critical LLM “hallucinations”—factually incorrect outputs—are addressed by examining Neuro-Symbolic AI. This hybrid approach, combining neural networks with symbolic logic, is presented as a potential solution for achieving 100% reliability in high-stakes applications. The article delves into the technical aspects, challenges, and future prospects of this and other related hybrid AI methods.
Part 1: The Many Ways LLMs Leak Data—and How to Solve It
Enterprises embracing AI face escalating cybersecurity risks, particularly data leakage from LLM vulnerabilities. This first article in a two-part series highlights the growing threat of AI-driven breaches and the critical attack vectors exploiting LLMs, urging immediate attention from security teams. Read the full article here
Part 2: The Many Ways LLMs Leak Data—and How to Solve It
Traditional cybersecurity isn’t equipped to handle LLM attack vectors. The second article in a two-part series dives deeper into the emerging threats of prompt injection, jailbreaking, and flowbreaking, and the need for AI-native security solutions. Read the full article here
Winning the Adoption Battle at the Edge
Edge computing offers real-time insights by processing data locally, yet deploying it in 2025 remains challenging due to fragmented hardware, shifting standards, and immature software. This article explores this evolving edge landscape, identifying key gaps in the stack and pinpointing where early, durable returns will likely emerge as the ecosystem moves towards more interoperable, plug-and-play solutions.
Small but Mighty: Enterprises should take note of small language models
The AI paradigm is rapidly shifting: while larger models once dominated, smaller language models (SLMs) are now proving equally powerful. This article explores the remarkable efficiency, effectiveness, and underlying innovations driving SLMs’ impressive performance, particularly within enterprise applications, demonstrating that in AI, less can indeed be more.
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