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“木头姐”押注技术革命,预计未来7年股价复合增速超40%!163页重磅年度报告来了

“Sister Mu Tou” is betting on a technological revolution, and the compound stock price growth rate is expected to exceed 40% in the next 7 years! The 163-page heavy annual report is here

wallstreetcn ·  02/12 18:32

Can Sister Mu successfully bet on the next skyrocketing miracle?

The brilliance of technology stocks also brought “Sister Mu” Cathie Wood (Cathie Wood), a Wall Street star fund manager and CEO of Ark Investment Management Company, to reinvigorate in 2023. The company's flagship fund, ARK Innovation ETF (ARKK), rose 68% throughout the year, ranking in the top 1% of similar funds.

After coming out of the “Lost Two Years,” “Sister Mu” recently led her ARK research team to release a report called “Big Ideas 2024” as scheduled.

In this 163-page report, “Sister Mu Tou” continues to focus on the field of “disruptive innovative technology”. It is expected that technology integration, AI, digital wallets, precision therapy, and 3D printing will change all aspects of the world. By 2030, technology will accelerate the world economy to 7%:

Key highlights include:

1. The five major technology platforms of artificial intelligence, public blockchain, multi-group sequencing, energy storage, and robotics are integrating with each other to form a synergy, which may accelerate the global economic growth rate from an average of 3% in the past 125 years to more than 7% in the next 7 years.

2. The market value of stocks associated with disruptive innovation will grow at a rate of 40% per year, surging from 16% of the total global stock market to over 60% in 2030, and growing from about $19 trillion today to about $220 trillion in 2030.

3. By 2030, the integration of hardware and software could reduce AI training costs by 75% per year. The global software market is likely to grow tenfold by 2030.

4. It is estimated that by 2040, the scale of hardware investment in the AI field will reach 1.3 trillion US dollars. This huge investment will drive AI software sales to 13 trillion US dollars, keeping the gross margin of the software industry at 75%.

5. The robot taxi platform will redefine personal travel and create a corporate value of 28 trillion US dollars over the next 5-10 years. The number of robot taxis sold each year is about 74 million, accounting for most of the automobile market.

6. With the consolidation of manufacturing, battery costs are falling, depressing the price of automobiles. Batteries account for 20% of the value of electric vehicles, and battery manufacturers generate $30 billion in annual revenue for electric vehicle OEMs.

7. Thanks to 3D printing technology, automobile production has entered an unprecedented field, which is expected to reduce automobile development time by 50% and mold design verification costs by 97%.

8. Precision therapies account for 25% of newly launched drugs. By 2030, drug revenue will increase by 15%, or about 300 billion US dollars.

9. With the full penetration of artificial intelligence-enhanced multiomics technology, R&D efficiency related to drug development will double. The actual return on R&D increased 10% by 2035.

10. Blood tests to detect various types of cancer at an early stage have become the standard of treatment, reducing cancer mortality by 25% in certain age groups. In developed markets, 30% of patients benefit from the new diagnostic system.

11. Digital leisure spending should gain a larger market share from the real economy and grow at a compound annual growth rate of 19% over the next seven years, from $7 trillion in 2023 to $23 trillion in 2030.

12. By 2030, revenue from smart devices, entertainment and social platforms reached $5.4 trillion, of which advertising and commerce revenue accounted for 80%.

Disruptive technology innovation platform

According to ARK's research, the convergence of disruptive technologies will define the development of the next decade. Five major technology platforms — AI, public blockchain, multiomic sequencing (multiomic sequencing), energy storage, and robotics — are integrating with each other to transform global economic activity. The economic growth rate may accelerate from an average of 3% in the past 125 years to 7% over the next 7 years:

We believe that technological convergence may bring about macroeconomic structural changes that are more impactful than the first and second industrial revolutions. Globally, the advent of robots will revive manufacturing, robot taxis will transform transportation, AI will increase the productivity of knowledge workers, and actual economic growth will accelerate.

Driven by breakthroughs in AI technology, the global stock market value associated with disruptive innovation is likely to increase from 16% to more than 60% of total market capitalization by 2030. As a result, the annualized return on stocks associated with disruptive innovation is likely to exceed 40% by 2030. Over the next seven years, its market capitalization will increase from about $19 trillion today to around $220 trillion in 2030.

According to the report, the picture below shows the impact of technologies such as steam engines, railways and telegraph, and general technology such as electricity, telephones, and radio stations on the economy. Today, the impact of the integration of disruptive technologies such as AI and robotics on the economy will surpass that of previous general-purpose technologies:

These disruptive technologies also have varying degrees of integration and influence with each other. Some have a very high degree of technology integration (such as AI), while others are relatively low (such as precision therapy). The degree of integration of AI can show the position and role of a core technology catalyst.

According to the report, AI is also developing faster than market expectations. In 2019, the market generally expects to wait 80 years for the advent of general AI, and 2020 will decrease from 80 to 50, and 2021 to 34. With the advent of GPT-4, the expected time was even reduced to 8 years. Ark expects general AI to appear as early as 2026, and later by 2030:

Ark believes that advances in individual disruptive technologies can bring huge new market opportunities if integrated with each other, such as the general robot market and the autonomous taxi market:

Neural network+battery technology can enable autonomous mobile devices (such as autonomous taxis) to scale up. In addition to batteries and AI support, general-purpose robots also require components such as motors and sensors. As autonomous taxis are scaled up, the cost of these technologies will also decrease, and the general robot market will also usher in rapid development.

Compared to technologies such as industrial robots, Internet information technology, and steam engines, disruptive technology (AI in particular) will have a huge impact on the economy.

We expect disruptive technological innovation to dominate global stock market capitalization. In 2023, non-disruptive innovative technology (the grey circle section) is still dominating global stock market capitalization. By 2030, disruptive technology will not only triple the total market value, but will also be the dominant force in market capitalization (color part).

According to the report, the investment scale of AI hardware will reach 1.3 trillion US dollars, driving AI software sales to 13 trillion US dollars, and maintaining gross margin at 75%.

Artificial Intelligence: Redefining Work

In 2023, the AI wave set off by ChatGPT was “higher than one wave”, and AI was rapidly integrated into every aspect of people's lives. ARK pointed out in the report that thanks to the rapid decline in AI training costs and open source from major technology companies, AI brought not only an increase in efficiency, but would also drive the rapid development of the global economy.

ARK pointed out that the advent of ChatGPT has amazed companies, satisfied users, and greatly improved productivity:

Programming assistants such as GitHub, Copilot, and Replit AI have achieved certain results, and their emergence has improved the productivity and working status of software developers.

The rapid development of Wenshengtu's large models has also reshaped graphic design, and the output effect of image models is already comparable to that of professional graphic designers.

The cost of writing text is also falling dramatically. Over the past century, the cost of writing written content has remained relatively stable in real terms. But over the past two years, as the quality of writing big language models has improved, so have costs.

Compared to high-performing employees, previously underperforming employees have benefited more from the advent of AI.

ARK points out that with the expansion of AI applications, researchers are innovating in AI training and inference, hardware and model design to improve performance and reduce costs, and inference costs seem to drop at a rate of about 86% per year. The convergence of hardware and software is expected to reduce AI training costs by 75% per year by 2030:

Based on enterprise-size use cases, inference costs seem to drop at a rate of about 86% per year, even faster than training costs. Today, the reasoning costs associated with the GPT-4 Turbo are lower than the GPT-3 a year ago.

As stated by Wright Law, improvements in accelerated computing hardware should reduce the production cost of artificial intelligence-related computing units (RCUs) by 53% each year, while improvements in the algorithm model further reduce training costs by 47% each year. In other words, the convergence of hardware and software could reduce AI training costs by 75% each year through 2030.

(Note: The core of Wright's law is that every time the cumulative production of a product doubles, the cost falls by a constant percentage. (If production in the automotive sector doubles cumulatively, the cost price will drop 15%.)

The report points out that the open source model is competing with the closed source model. Overall, the performance of the open source model is improving faster than the closed source model:

The open source model field is gradually challenging OpenAI and Google's closed source model, led by leading company Meta.

In 2023, the open source model rapidly progressed in performance benchmarking, winning continued support from developers in large enterprises, startups, and academic institutions. We're also excited to see what the open source community has achieved in 2024.

In response to current investors' concerns, will training data run out of data, thereby limiting its performance? Ark stated in the report that the optimization of the model requires more training data, and Epoch AI estimates that high-quality language/data sources such as books and scientific papers may be exhausted by 2024, but at the same time, there is still a large amount of undeveloped visual data.

Microsoft CEO Nadella first mentioned Microsoft's preparations for AI monetization in Microsoft's earnings report. Ark mentioned in this year's report that customized AI products should enjoy more pricing power:

With the advent of open source alternatives and falling costs, suppliers that develop and customize AI software for enterprises should be easier to monetize. Conversely, AI applications with simple functions will be quickly commercialized, and profitability will decrease in the face of fierce competition.

Therefore, in the report, Ark believes that in terms of continuously improving the productivity of knowledge workers, the potential opportunities for AI software vendors reach a trillion dollars, and the global software market is likely to grow tenfold:

We believe AI has the potential to automate most tasks in knowledge-driven occupations by 2030, thereby dramatically increasing employee productivity.

Software solution vendors that automate and accelerate knowledge work tasks should be the primary beneficiaries. If a new wave of AI application innovators has similar pricing capabilities to today, and the increase in AI productivity is as meaningful as we think, then the global software market could grow tenfold by 2030.

Digital consumers move further towards digital entertainment

According to ARK's research, digital leisure spending should gain more market share from the real economy and grow at a compound annual growth rate of 19% over the next seven years, from $7 trillion in 2023 to $23 trillion in 2030. The report says five trends will drive its growth:

1. The compound annual growth rate of advertising amount in smart TVs (CTV) reached 17%, from US$25 billion in 2023 to US$73 billion in 2030.

2. E-commerce revenue from social platforms is expected to grow at a compound annual rate of 32%, from $730 billion in 2023 to over $5 trillion in 2030.

3. Consumer demand for sports betting remains strong and will continue to grow rapidly.

4. AI-assisted game creation will become a new wave in the gaming industry. For example, game creation on user-generated content (UGC) platforms such as Roblox may cause game content to explode. Roblox has provided more than 480 million experiences worldwide, 52 times the total number of games on PC, game consoles, and mobile apps.

5. The beginning of the AI+ hardware era may redefine wearable devices in the future. If virtual reality (VR) devices continue to face adjustments, new AI hardware devices will surely appear.

Ark notes in the report that the advent of AI will further reduce average working hours and stimulate digital entertainment consumption:

Generative AI can reduce per capita working hours by an average of 1.3%, from 5.0 hours per day in 2022 to 4.5 hours in 2030. As a result, consumers are likely to spend more time on online entertainment, and the share of online time in their daily lives will increase from 40% in 2023 to 49% in 2030.

robotics

Ark believes that the integration of AI and hardware may drive the application of robots in a wider range of fields. It is expected that general robots will usher in new market opportunities, and the annual revenue scale will exceed 24 trillion US dollars.

Ark points out that rapid advances in robot performance and drastic cost reductions are spurring factories to increase the adoption of robots:

Increased robot performance is further stimulating the demand for industrial robots in factories. Advances in computer vision and deep learning have increased robot performance by 33 times in seven years. Robots have more than doubled the performance of humans, and it's still unclear where the upper limit is.

With AI and computer vision, robots should be able to operate cost-effectively in unstructured environments. Lower prices stimulate demand for industrial robots, and as robot production doubles, industrial robot costs will drop by 50%.

Ark emphasized that robots that work collaboratively with humans are reaching a critical stage of development called the “S curve tipping point” and are about to enter a stage of rapid development:

The S curve is a graph commonly used to describe the increase in the market adoption rate of a new technology or product over time. It starts growing slowly, then increases rapidly, and then slows down again, forming an S pattern. When a new technology's market share approaches 10% to 20%, this usually indicates that it is about to enter a phase of rapid growth.

Taking the number of robots deployed by Amazon as an example, it can be seen that Amazon drastically increased the use of robots in 2023, reaching an all-time high, similar to the number of human employees.

The robot also had a huge impact on production capacity after use. Judging from the efficiency of the Amazon warehouse, the time from customer clicking to placing an order to shipping the product was reduced by 78% in minutes.

Therefore, Ark believes that in the future, in addition to household robots, general robots will also include manufacturing robots, and the global manufacturing GDP is expected to benefit from the use of robots to soar to 28.5 trillion US dollars in 2030.

Digital Wallets: Bilateral Markets Build a Closed Loop Consumption System

Ark pointed out in the report that leading vertical software platforms create a closed-loop consumption system through bilateral markets to promote closed-loop transactions from consumers to merchants, merchants to employees, and employees to merchants. Digital wallets on these platforms will enable a completely closed payment ecosystem, and total C2B digital wallet payments will grow at a rate of 20% per year, to around $7 trillion by 2030:

In addition to supporting core business operations, vertical software providers such as Block, Shopify, and Toast are also integrating financial services for merchants. With digital wallets as the core, we work with banks and fintech companies (or have their own banking license) to eliminate inefficient interactions between merchants and traditional financial institutions.

Over the next seven years, total C2B digital wallet payments will grow at a rate of 20% per year, from around $2 trillion in 2023 to around $7 trillion in 2030. The share of closed-loop payments will increase from 4% to 25%, and Block's Square, Shopify, and Toast's payment revenue forecast to increase from $3.5 billion to $21 billion, with an annualized growth rate of 29%.

Ark believes that bilateral markets can close the financial cycle between consumers and merchants, and the closed-loop payment ecosystem is achieved through three methods of internal transfers:

From the consumer to the merchant, from the merchant to the employee, and from the employee (who is also a consumer) to the merchant. To build these payment ecosystems, platforms must have: 1) large and highly engaged bilateral networks, 2) end-to-end visibility into merchant operations and finances, and 3) vertical industry expertise.

Digital wallets have the potential to replace the consumer-to-business (C2B) payment ecosystem. Using digital wallets for transactions can bypass banks and bank card networks, saving payment institutions, merchants, and consumers exchange fees. We believe that vertical software platforms with large-scale consumer and merchant ecosystems will use digital wallets to facilitate closed-loop transactions.

Vertical software platforms can provide financial services to merchants. Through digital wallets, these platforms not only improved convenience, but also monetized deposits, reducing the number of steps from payment authorization to merchant settlement from 16 to 5, and more than doubling the platform's yield.

Precision treatment & multi-group sequencing development

Ark pointed out that in the past 20 years, new models of precision therapy, CRISPR gene editing, RNA therapy, and targeted protein degradation have surged. Driven by artificial intelligence (AI), CRISPR gene editing, and new sequencing technologies, innovative therapies have increased the rewards of research and development. Some diseases that were originally thought to be untreatable with targeted drugs can now be treated with newly developed drugs, providing new possibilities for certain diseases:

Companies in the precision therapy sector are expected to experience significant growth. Precision therapy is a medical method that customizes treatment plans based on patients' specific genetic information. It involves in-depth research and application at the level of various biomolecules such as DNA, RNA, and protein.

According to ARK Investment Research's forecasts, the corporate value of companies focusing on precision treatment will grow at a rate of 28% per year from 2023 to 2030, and the corporate value will increase from about $820 billion to about $4.5 trillion:

Over the past 30 years, treatments with novel mechanisms of action have emerged endlessly. They not only expand the number of treatable diseases, but also improve efficacy and safety. In 2023, more than 25% of clinical trials are using new treatment models.

According to our research, the trend of declining return on investment in the pharmaceutical industry will be reversed in the future with new treatment models and R&D methods, and regulatory approval of “precision” treatments.

More and more precise treatments are becoming multiomic and curative, with mechanisms of action spanning DNA, RNA, proteins, etc. According to ARK's research, the corporate value of companies focusing on precision treatment will grow at a rate of 28% per year over the next 7 years, from US$820 billion in 2023 to US$4.5 trillion in 2030.

Precision treatments, including RNA-based drugs and “targeted proteolytics” (TPDs), have not only expanded the amount of drug-treatable proteins in the human genome, but also increased the number of treatable tissue types.

Multiomics Tools and Techniques: Transforming Biological Insights into Healthcare and Economic Value

Ark pointed out that in the past ten years, biological tools and technology have continued to develop and improve. Among them, advances in high-throughput proteomics, artificial intelligence (AI), and single-cell sequencing have become key forces driving the development of biological research and medical technology. It is estimated that drug R&D spending is expected to decrease by more than 25%. The value of enterprises in the field of precision therapy will increase by 26% over the next seven years, from about US$820 billion in 2023 to about US$4.5 trillion in 2030:

The combined use of these technologies has improved the productivity and efficiency of research and development work, as well as the accuracy of medical applications, such as disease diagnosis, treatment personalization, and new drug development.

According to ARK's research, artificial intelligence and automation are providing stronger support for drug development, and technological advancements should significantly reduce the development costs of each drug:

Over the past decade, advances in mass spectrometry and bioinformatics have greatly improved proteome analysis, increasing resolution, accuracy, and the ability to analyze multiple samples simultaneously.

Wright's law predicts a decline in the cost of proteomics, not only enabling detailed exploration of proteomics in health and disease, but also accelerating the discovery of cancer biomarkers and the development of targeted therapies. We believe single-cell RNA sequencing is revolutionizing our understanding of cancer.

We believe that the development of artificial intelligence and automation will reduce drug costs and reduce approval processes. At the same time, advances in basic biology, artificial intelligence, automation, and trial design should significantly reduce the cost of preclinical drug development. Eliminate unpromising drugs early in the drug development process, prevent improper allocation of downstream R&D funds, and create more space early in the discovery phase.

Over the next decade, companies that take full advantage of these technologies can reduce the cost per approval by nearly 50%, in part because drug candidates entering clinical trials have more than doubled their chances of success.

Electric vehicles are becoming more popular due to lower battery costs

The report points out that after battery costs have risen due to supply chain disruptions, battery costs are now falling in line with Wright's law and will drive electric vehicle (EV) prices down. Electric vehicles are expected to account for 95-100% of the total number of vehicles in 2030, and electric vehicle sales will grow at a rate of 33% every year over the next 7 years, from 10 million units in 2023 to 74 million units in 2030

We believe electric vehicles continue to take market share from internal combustion engine vehicles. If electric vehicles continue to seize the share of fuel vehicles, then fuel vehicle manufacturers may be forced to restructure and integrate.

According to Wright's law, for every doubling of kilowatt-hours production, battery costs will drop by 28%. Lithium iron phosphate batteries are seizing the market share of nickel-rich batteries, which shows that it is very difficult to predict commodity prices as the chemical composition of batteries continues to change.

Wright's law also points to faster charging speeds for electric vehicles, and the charging speed of an electric vehicle seems to be a good representative of overall performance, including efficiency, range, and power.

Over the past five years, the 200-mile range has nearly tripled its charging speed, from 40 minutes to 12 minutes, and is likely to triple to 4 minutes in the next five years. As electric vehicles charge at acceptable levels, manufacturers may optimize other features, including autonomous driving, safety, and entertainment.

Autonomous taxis: Transforming urban mobility

Breakthroughs in artificial intelligence will drive autonomous taxis to completely transform urban travel, and will greatly change or reduce the demand for individuals to buy cars, affecting the car loan market that relies on personal car sales. According to ARK's research, the robo-taxi platform will redefine personal mobility and create $28 trillion in corporate value over the next five to ten years:

According to our estimates, large-scale autonomous taxis can cost as little as $0.25 per mile, and this low cost may drive widespread adoption of autonomous taxis.

The report points out that autonomous vehicles are safer than human-driven cars, and the application of big language models and generative AI can accelerate the development of autonomous driving technology:

We believe that the accident rate of autonomous vehicles will be 80% lower than that of human drivers, thereby reducing about 40,000 car-related fatalities in the US and about 1.35 million car-related fatalities worldwide each year.

In fully automated driving (FSD) mode, Tesla is 5 times safer on the ground than in manual mode and 16 times the national average. Waymo's autonomous vehicles are about 2-3 times safer than the national average.

Neural networks trained by GPT-4 to perform robot tasks outperformed expert human programmers on 83% of tasks, with an improvement of 52%. Large language models support text-based training, validation, and self-interpretation, which should help facilitate regulatory approval.

Multimodal models can train autonomous vehicles through images and text, which may improve system performance. Generative artificial intelligence can train and verify the safety of autonomous vehicles through simulation.

“Sister Mu Tou” emphasized in the report that the increase in the market share of autonomous taxis will disrupt the US auto loan industry. By 2030, the corporate value of autonomous driving platform providers can reach 28 trillion US dollars, equivalent to 9 times the market value of all automobile manufacturers in 2023:

Over the past three years, interest rate hikes have increased monthly auto loan expenses for new cars by about 27%, from $581 to $739. This has also recently brought the number of car loan arrears for more than 60 days to a record high.

As the price of electric vehicles continues to fall, more users are using autonomous taxi technology and reducing the value of fuel vehicles.

Editor/Somer

The translation is provided by third-party software.


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