While it’s almost always a good time to be an early-stage technology investor, the opportunities today are particularly breathtaking. I’ve been a tech executive and investor for more than 40 years and can’t remember a time when exciting new technology applications were exploding all around us like they are right now.
3 Reasons Deep Tech Is So Hot
- The acceleration of AI applications, global chip wars, gene editing advancements and more have driven VC interest in deep tech.
- The rise of AI is pushing beyond chatbots to drive rapid growth in meaningful sub sectors such as AI semiconductors and enterprise AI applications in defense and financial services.
- The decline in IPOs is further fueling deep tech’s growth with large tech companies exploring startup acquisitions to expand their leading edge product offerings in lieu of in-house development.
As a venture capital investor, my firm is active in many different categories of tech, including semiconductors, artificial intelligence and converging areas of high tech and biosciences. The bulk of our investments flows toward deep tech — companies with technologies built upon meaningful scientific or engineering innovations that help them create strong competitive advantages and IP portfolios.
Interest in various areas of deep tech has grown substantially over the past few years with the stunning acceleration of AI applications, semiconductor supply chain issues and CRISPR breakthroughs, just to name a few. Deep tech now accounts for 20 percent of annual venture capital funding, double what it was 10 years ago, according to Boston Consulting Group data.
As advancements continue to accelerate, these leading-edge tech sectors are playing a pivotal role in shaping the future of myriad industries in 2024 and beyond. Here are just a few of the areas that will drive growth in the early-stage tech startup landscape in the months and years ahead.
Evolving AI Applications
With the astonishing acceleration of generative AI, we are seeing a rapid evolution away from simple consumer uses, such as chatbots, and toward proprietary enterprise applications. These require AI solutions that can better handle the higher privacy and data security needs of more critical applications and industries.
We are currently invested in Normal Computing, an exciting early-stage company founded by former members of Google Brain, Palantir and X. Normal is developing a complex reasoning AI framework for use in semiconductor manufacturing, insurance and finance applications, with a focus on making AI models that are more transparent, easily auditable and less prone to hallucinations.
Healthcare solutions are similarly experiencing transformation through the widespread adoption of AI-powered diagnostics, predictive analytics and personalized treatment recommendations. Deep learning algorithms enable the detection of diseases earlier, predict patient outcomes more accurately and tailor interventions to individual needs, leading to improved patient outcomes and cost savings. Whiterabbit, for example, is using AI to improve breast-cancer screening through earlier and more accurate detection.
Next-Generation Chip Technologies
In the semiconductor space, as applications that require advanced chip technologies continue to expand, new issues and bottlenecks are arising around factors such as energy consumption, processing efficiency and demand for instant calculations.
Arguably the most significant among these trends is the increasing demand for data-intensive applications. The amount of data being generated and consumed is growing exponentially, driving the need for new devices and technologies that can process and analyze data quickly and efficiently.
In response to this, semiconductor startups are developing new architectures that can improve the performance and efficiency of semiconductors. Eliyan is one example of an emerging company in this space; the company is developing chiplet systems that enable greater chip-to-chip bandwidth and speed. Eliyan’s technology helps to solve the need to process more data at high speeds by enabling movement of large bi-directional data feeds, helping networks and chips run more efficiently.
The rise of AI in particular is creating a significant shift in the hardware market. There is a massive overhaul of the hardware infrastructure necessary to power AI, with purpose-built chips that can better handle the much higher demands of AI training, memory, storage and data processing speed coming from both Big Tech and startups.
The current costs of running generative AI systems are simply unsustainable and must be more efficient to scale. Recogni is one example of a rapidly rising company in this space developing chips optimized for autonomous driving and generative AI use cases.
Continued Rise of Alternative Exits
Further fueling deep tech’s growth is the shift by large tech companies towards M&A for expertise and technologies that can help expand their product offerings, in lieu of in-house development. Increased regulatory intervention will reduce large-scale M&A deals, prompting a strategic shift of buyers toward smaller acquisitions that can still fortify competitive differentiation, enable rapid market penetration and drive top line growth, according to Gartner data.
The deceleration in IPOs has also created a stronger market for alternative means to access capital, especially through private equity and acquisitions. According to PwC, Q1 2024 saw 14 companies going public and collectively raising more than $6.5 billion, an improvement over 2023 yet still a fraction of IPO activity in previous years.
Coupled with the poor aftermarket performance of many companies the past few years, the question remains whether the IPO market is poised for a full-scale revival in 2024, even as market conditions appear to improve and long-held companies like Reddit have seen early success. Transactions are instead turning to the private M&A and secondary markets, given the ample capital available at large private equity funds, big tech companies like Google or Microsoft and within bullish sectors.
The growth of early-stage tech will continue as we witness unprecedented levels of innovation and aggregate investment.
Some deep tech sectors, such as semiconductors and gene editing, will see significant M&A activity. Over the past decade, for example, the market capitalization of major chip companies has skyrocketed from $10 billion to staggering figures exceeding $300 billion, $800 billion, and even $1 trillion. Empowered by this substantial growth and further emboldened by the more difficult startup fundraising environment and valuation reset, many of these public companies are using their excess dry powder to aggressively pursue M&A opportunities.
Companies such as Broadcom, Intel, NVIDIA and AMD are deploying their R&D budgets not by developing new products, but by acquiring already developed companies for billions of dollars.
The growth of early-stage tech will continue as we witness unprecedented levels of innovation and aggregate investment. From breakthroughs in biotechnology to the increasing adoption of AI-powered solutions by businesses, consumers and government, the possibilities are far-reaching across sectors and society.
