Translator: Bai Hua Blockchain

TL;DR:

AI investment hits new highs: The global AI market is expected to reach $13 trillion by 2030. With venture capital firms betting on startups that are reshaping industries, AI investment is experiencing explosive growth.

One of the key investment areas in 2024 is AI infrastructure: As the demand for computing power by AI models continues to increase, venture capital firms are increasing their investments in AI infrastructure, including specialized chips and data centers.

Notable funding trends: Late-stage financing and AI infrastructure investments are dominant, while AI applications in healthcare, finance, and defense attract significant investment as investors seek projects with tangible impact.

The next billion-dollar startup: The future of AI investment will focus on areas like automated Bots, energy, and entertainment, where human-AI collaboration has paved the way for pioneering startups to emerge.

Overview: This article will discuss:

• The introduction of AI in the venture capital ecosystem

• Part 1: Navigating the noise in a competitive market

• Part 2: Top AI financing rounds in 2024

• Part 3: Five key opportunities driving the next billion-dollar AI startup

• Challenges and ethical considerations

1. The introduction of AI in the venture capital ecosystem

With billions of dollars pouring into the AI space, it's safe to say the "AI hype" is far from over - in fact, it's only getting bigger.

AI has become one of the most heavily invested sectors in the venture capital world.

According to Pitchbook data, global AI investment has reached $290 billion over the past five years, with private investment firms completing over 15,400 deals since 2022. This frenetic activity reflects a high degree of confidence in the future of AI. There are varying opinions on how big the AI market will become by 2023.

According to McKinsey:

"AI has the potential to contribute $13 trillion to global economic growth by 2030, which is 16% higher than the current cumulative GDP. This translates to an additional 1.2% of GDP growth per year."

Statista and Bloomberg Intelligence both predict that the AI market could grow to $2 trillion by 2030, covering the entire spectrum from AI software to hardware and services. PwC estimates that AI will contribute $15.7 trillion to the global economy by 2030, primarily through productivity gains and increased consumer demand for AI-enhanced products.

It's safe to say that AI has become a part of our daily lives, and the hype has passed. However, with the excitement comes noise - investors now face thousands of AI companies, each claiming to be the next "big star". Data privacy issues, talent shortages, ethical AI, and concentration risks add more challenges to this already competitive landscape.

2. Part 1: Navigating the noise in a competitive market

Today, over 100 venture capital funds are actively investing in the AI market, covering both horizontal applications (like infrastructure) and vertical applications in industries like healthcare, finance, and agriculture.

To understand the current state of AI venture capital, I'll introduce two types of investors:

Pioneers: Aggressive investors who are willing to take big bets across multiple AI domains. Pragmatists: More conservative funds that see the potential in AI but are more selective or cautious in their investments.

1) Pioneers: The most active venture capital firms

Pioneers are known for their willingness to take risks and lead the charge, playing a crucial role in shaping the future of AI investment. Here are some notable players:

• Andreessen Horowitz (a16z) has made 29 investments since 2023, spanning multiple domains, including a $100 million investment in Character.AI and a $224 million investment in Genesis Therapeutics. a16z is making big bets at the intersection of AI and biotech and consumer tech.

• Sequoia Capital has taken a particularly aggressive approach, leading multiple financing rounds for well-known startups like Cohere (language models) and Viz.ai (medical imaging). In 2023, Sequoia allocated around 60% of its new investments to the AI space, up significantly from 16% the previous year.

• General Catalyst has committed $750 million to the medical AI space, including investments in companies like Commure, Sword Health, and Overjet. They have made 19 AI investments, with just under half focused on generative AI (GenAI) projects.

• Alumni Ventures has made multiple AI and machine learning investments, covering both consumer and enterprise applications, including SenseTime, Dataminr, and Iterative Health.

As Sequoia Capital partner Stephanie Zhan said, focusing on seed and early-stage investments:

"The past year has injected new life into the investment ecosystem with AI."

2) Pragmatists: More conservative venture capital firms

While the Pioneers are rushing in, the Pragmatists are choosing to observe for now.

These funds see the potential in AI but prefer a more selective approach, focusing on sustainable returns and more stable market conditions. Here are some typical examples:

• Kleiner Perkins leans towards relatively safe AI investments, such as Together AI ($102.5 million Series A), whose underlying technology supports the widespread adoption of AI.

• Benchmark Capital: Benchmark is known for its anti-hype philosophy, leading a $24 million Series A round in September 2024 for a startup aiming to create automated digital employees to simplify go-to-market (GTM) operations. Benchmark is more inclined to focus on practical solutions rather than speculative technologies.

• Bessemer Venture Partners: Bessemer has invested around $250 million in AI, focusing on applications that solve real-world problems rather than chasing hype. Their support for EvenUp ($50.5 million Series B), an AI startup automating medical documentation for personal injury lawyers, reflects their cautious investment strategy.

• Union Square Ventures (USV): USV's AI investments, totaling around $150 million, are primarily concentrated in network-effect-driven applications. Their investment in Recursion Pharmaceuticals aligns with their belief in network effects over high-risk technologies, as the company uses AI for drug discovery.

• GGV Capital: GGV's AI investments are around $180 million, with a preference for more mature areas like SaaS and enterprise software, using AI as an additive technology rather than a core one. Their strategy supports growth, avoiding experimental technologies.

Here is the English translation of the text, with the terms in <> retained as is: What has caused these funds to hesitate? Pragmatic investors remain cautious about the challenges posed by artificial intelligence: - : Developing AI is costly - from data to computing power - and these venture capital firms are cautious about large upfront investments. - : As regulations lag behind the rapid development of AI, pragmatic funds are more willing to wait for the rules to become clearer, especially in areas like autonomous driving and healthcare. - : The soaring valuations of AI startups have led some investors to worry about a potential "AI bubble" bursting. Pragmatic funds avoid over-investing when the market is overheated, until the hype subsides. - : With tightening global data regulations, the ethical issues surrounding AI have increased the risks. Pragmatic funds remain cautious and avoid investing in areas where privacy concerns may overshadow returns. 3) Conservative funds like , , , , and may be seen as having missed out on AI investment opportunities due to their cautious approach. However, this conservative stance is not necessarily a disadvantage. While their selective investment strategies provide stability and allow them to capture AI's rapid growth, they may also miss out on some transformative opportunities in the long run. Pioneers like and (Andreessen Horowitz) have made significant investments in foundational AI and generative technologies, ultimately paving the way for the next era of technological revolution. If AI continues to grow at its current pace, the pragmatists' cautious stance may leave them on the sidelines of an industry that could shape the next decade. 2. Now that we understand which large venture capital funds are dominating the AI space, let's take a look at the startups that received the biggest funding support in 2024. <2024 Q4 Significant Deals in Europe and the US:> - (Series E, $260 million): An AI-powered enterprise search engine, valued at $4.34 billion. - (Series C, $150 million): An AI programming platform to boost developer productivity, valued at $1.1 billion. - (Series B, $47 million): An AI test automation platform for finance, HR, and enterprise planning. - (Series B, $38 million): Focused on using physical AI to provide anonymous people sensing and occupancy solutions. These deals showcase the broad range of AI applications, from logistics to automation, that have attracted investor attention. 1) Despite the cost and scalability challenges, generative AI remains a focus area for investment. Over the past five years, generative AI startups have raised $26 billion, particularly in content creation, healthcare, and enterprise solutions, including companies like QuizGecko, Writesonic, and Tome. 2) As generative AI models demand increasing computing power, venture capital firms are betting on the "pillars" of AI - AI infrastructure. Companies focused on developing specialized chips, data centers, and platforms are receiving more financing: - , an AI semiconductor and software startup, raised a $640 million Series D led by Blackrock, valuing the company at $2.8 billion. Groq's success reflects the growing attention on companies supporting the "engines" of AI (from chip design to large-scale computing). - and have launched a $30 billion AI infrastructure investment fund to build AI infrastructure, including data centers and energy projects, to meet the demands of AI. This trend reflects a fundamental shift: as AI advances, venture capitalists recognize that supporting the infrastructure (chips, servers, data platforms) underlying AI is as important as the algorithms themselves. 3) Venture capital firms are pouring significant capital into mature, revenue-generating AI companies, pushing some financing rounds into the billions of dollars. While early-stage investments are still ongoing, late-stage financing rounds are now dominating. In Q3 2024 alone, we saw: - (Alphabet's self-driving unit) raised $5 billion. - , an AI research lab founded by OpenAI co-founder Ilya Sutskever, received a $1 billion investment from Andreessen Horowitz and Sequoia Capital. - completed a $500 million Series D, valuing the company at $5.5 billion. - If you think those are not big enough, raised $6.6 billion in an October 2024 financing round, led by Thrive Capital, Microsoft, and Nvidia, reaching a valuation of $157 billion. 4) Venture capital firms are increasingly investing in startups applying AI to healthcare, finance, and defense: - : AI is transforming drug discovery and diagnostics, and investors have taken notice, such as (drug development) and (drug discovery). - : AI is reshaping decision-making processes, with using machine learning to help banks create customized credit scoring workflows (recently raised $20 million), and applying AI to digital asset security, showcasing how machine learning is permeating lending practices to financial security. - : Europe's completed a $488.2 million Series C, focused on AI-driven military intelligence and defense systems, while the US's focuses on military drones. These startups demonstrate the expanding role of AI in defense technology, as real-time insights and automation become increasingly crucial. 5) Due to venture capital firms' stricter screening of startups, seed-stage deals have slowed down. For early-stage AI startups, securing funding has become increasingly challenging, especially without clear potential. Venture capital firms are more inclined to invest in later-stage companies with established revenue paths, potentially including those with strong historical growth, stable customer bases, and large market opportunities, like (Series C, $100 million).

4. Part Three: 5 Key Opportunities That Will Lead to the Next Billion-Dollar AI Startup

Generative AI and foundation models are the biggest hype in 2024. So what's next in the world of AI, and what might give rise to the next billion-dollar AI startup?

My key predictions

The next AI revolution is not about making technology smarter, but about fundamentally changing the way we live - the way we live, work, and even age.

Here are my three big predictions for the future:

1) The internet as we know it will disappear.

Goodbye to Google search, Bing, and Yahoo. The next evolution of the internet will no longer be a simple search box, but a dynamic realm of digital agents that will handle our browsing tasks for us. Imagine billions of personal AI agents handling everything from research to filtering out spam and bots.

2) We will get closer to human immortality.

From breakthroughs in anti-aging to AI-driven health diagnostics, we are moving towards a future where living to 100 may become the norm. Advances in AI in molecular biology and regenerative medicine may turn aging into a solvable problem.

3) Human-AI collaboration will become the norm.

Forget the idea of "AI replacing jobs" - we are entering a new era where human intuition, creativity, and moral judgment combined with AI's data processing and analysis capabilities will help solve problems that neither humans nor AI can solve alone. This collaboration will be a defining trend of the next decade.

These changes lay the foundation for the rise of the next wave of billion-dollar startups.

Here are the five key opportunities that will create the next billion-dollar startup:

1) Automated Bots: The Rise of Home and Industrial Assistants

Human-AI collaboration may fundamentally change robotics, creating automated systems that support rather than replace us. Automated Bots are already entering our homes and workplaces, providing hands-free assistance in areas where humans are present but constrained.

• Consumer Applications: Figure and Tesla's Optimus are leading this shift, introducing affordable humanoid Bots for household use. Imagine a future where middle-class homes have a Kin assistant, just like they have a washing machine or dishwasher, to help with childcare and chores.

• Industrial Applications: Companies like Agility Robotics, Sanctuary AI, and Co.bot are advancing collaborative Bots in industrial environments. Co.bot recently raised $100 million in a Series B, demonstrating the growing demand for "cobots" that can safely work alongside humans, handling labor-intensive or repetitive tasks. As Bots take on the labor-intensive work, humans can focus on strategic tasks, improving productivity and safety.

2) Energy Grid: Building Sustainable, Efficient Energy Systems

The energy industry remains an underexplored area for AI, with huge potential to optimize and autonomously manage energy use. The future vision is for every home and business to have a smart energy management system, creating a resilient and efficient grid.

Autogrid (now part of Schneider Electric) uses AI to optimize energy distribution in real-time, minimizing waste and improving the reliability of renewable energy. Grid AI and Stem Inc. have also made progress in demand forecasting and energy storage solutions, supporting the smart grid and potentially reducing carbon footprints at scale.

3) Quantum Molecular Modeling in Drug Discovery

In healthcare, quantum molecular modeling offers unprecedented potential for drug discovery and materials science. By combining quantum computing and AI, we can accelerate the screening of promising drug candidates, saving time, cost, and potentially saving lives.

Insil1C0 Medicine uses AI to predict molecular behavior, significantly reducing the time to find new drug candidates. Schrodinger uses quantum modeling for precise drug interaction simulations, while Atomwise employs deep learning to design compounds targeting diseases.

4) AI in Entertainment: The Rise of Synthetic Media and Hyper-Personalized Content

The entertainment industry is seeing an AI-driven creative transformation, with synthetic media and personalized content redefining storytelling. AI can now not only generate media content, but also collaborate with creators to produce innovative and high-quality experiences.

In a conversation with Farid Haque, Venture Partner at AlphaQ Capital and an AI and deep tech investor, he shared a vision of AI creating movies and TV shows, with human actors becoming a "high art" experience. As AI-driven production processes handle routine content creation, human performances will become scarce and highly sought-after, adding a unique layer to live-action media.

Actors can license their voice and facial expressions to AI-generated films, creating new revenue streams while preserving the "high art" of human-led performances. As AI technology evolves, the business model shifts, with studios able to use actors' digital archives, while traditional live performances become a premium experience.

DeepBrain AI allows actors to authorize the use of their digital "clones," opening up new revenue models. Flawless AI enables seamless cross-language speech and lip-sync, driving transformations in global media distribution.

5) Gaming and Advanced NPCs (Non-Player Characters)

Gaming is one of the most natural domains for human-AI collaboration, as AI can enable deeper interactions, more realistic NPCs, and highly personalized gaming experiences. Here, AI is not just a tool, but a co-creative partner that can adapt and evolve based on player behavior.

Inworld AI is developing NPCs that can remember past interactions with players, creating more immersive and responsive game worlds. This collaboration between players and AI characters opens up new dimensions of interactivity.

5. Challenges and Ethical Considerations

As AI systems continue to advance, ensuring their ethical and responsible use becomes crucial. Building systems that avoid discriminating against specific groups or exacerbating inherent biases in human data is necessary. AI is fundamentally a social equity issue.

Currently, over 3 billion people globally remain unconnected to the internet, with women disproportionately represented - this means AI has the potential to exacerbate the digital divide. To make AI a true force for good, reliable internet access and digital literacy are needed. Today, nearly 40% of the global population is offline, and many more have limited experience with digital tools. This imbalance could lead AI systems to be biased towards privileged groups, further perpetuating biases and exclusion.

Therefore, investing in inclusive AI, covering underserved communities, is crucial. From AI-driven remote education to accessible healthcare, to digital tools that promote rural development, venture capitalists, tech leaders, and policymakers need to address the digital divide and advocate for equitable AI models that benefit everyone.

6. Conclusion

As AI permeates our search engines and every corner of our home lives, it is clear that this technology has become deeply embedded in human society and is here to stay. The "hype" around AI is over, and we are tired of companies and marketing gimmicks that tout "AI." It is no longer a fad of the 90s, but a reality of our daily lives. Venture capital is fueling a new wave of startups that will change the way we live and work, from Bots to energy, to media.

For investors and innovators, the challenge is to go beyond hype and focus on real impact. Artificial intelligence is not just a trend - it is a transformation that is destined to last. This is just the beginning, and more changes await us in the future.

Link to the article: https://www.hellobtc.com/kp/du/12/5588.html

Source: https://medium.com/included-vc/the-hype-is-over-ai-landscape-in-venture-capital-2024-4eedd7f352ff