We recently compiled a list of the 10 Best AI Stocks to Buy According to Reddit. In this article, we are going to take a look at where C3.ai Inc. (NYSE:AI) stands against the other AI stocks.
As artificial intelligence becomes more prevalent in current world affairs, new patterns concerning its research and development strategies are also emerging. Traditionally, academia has focused on basic research and education, while industry concentrated on applied research and commercialization. However, in recent years, the commercial sector’s dominance in AI investment and research has raised concerns about the balance of power. The shift of researchers from academia to industry has also raised questions.
Advanced AI systems increasingly require large amounts of data, compute power, and funding resources that industry actors possess in greater quantities than academia and nonprofits. Hence, AI research, which was originally the domain of academia in the early 2000s is now being taken over by industry.
We recently talked about this division in another article we published, 7 Most Popular AI Penny Stocks Undis $5here’s an excerpt from it:
“A recent study from Stanford University found that businesses train AI models faster than academic institutions. In 2023, the industry-trained AI neared 51 significant machine learning models, while academia managed only 15. This trend persisted in 2024 despite rising training costs. ChatGPT 4, the latest model of ChatGPT, cost about $80 million to train. Google’s Gemini Ultra cost around $191 million.”
A 2021 Stanford report says that the reason behind the blurring roles of academia and industry is that businesses come with affordable cloud computing, open-source libraries, and pre-trained models that incentivize university researchers to pursue commercial applications of their work. More and more industry papers are now appearing at conferences, raising concerns about applied research stifling long-term innovation or being biased toward corporate interests, all while also accelerating solutions for real-world problems.
A 2023 paper in the journal Science states that businesses attract 70% of the top talent with PhDs in AI today, as compared to just 20% 2 decades ago. The number of AI research faculty in academia has stagnated, while industry hiring has surged 8 times since 2006. Industry models being substantially larger (about 29 times), indicating superior computing power, is a huge reason behind this.
In 2021, US government agencies allocated a total of $1.5 billion for academic AI research, while Google spent the same amount on a single project in just one year.
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The largest AI models are now developed in industry 96% of the time. Leading benchmarks are also primarily industry-driven, accounting for 91% of the total. Furthermore, the number of published papers with industry co-authors has nearly doubled since 2000.
Yet, there’s another anticipated shift as academic researchers are increasingly able to deploy their inventions in real-world settings. Duolingo, a language learning app developed by academics, is a successful example.
A distinguished MIT professor, Frédo Durand, believes academia can still be a driving force for innovation. He says that 25 years ago, the field of computer graphics in academia faced a similar resource imbalance where the industry created stunning visuals that academia couldn’t match. However, instead of trying to mimic industry, academia took a different path and focused on ideas like advanced lighting simulations, fluid dynamics, and machine learning for animation. These seemingly outlandish ideas eventually became the foundation of modern rendering and graphics hardware.
Durand believes this approach holds valuable lessons for AI research. He emphasizes the importance of academia pursuing unconventional approaches, openly sharing their work, and maintaining a sense of excitement about the field.
However, he recognizes the challenges for academia and suggests potential solutions including increased government funding for academic research, shared research infrastructure, and strategies to keep top AI talent within academia. While industry seems to be taking over AI in general, collaborative partnerships with academia could yield better results. In one way or the other, AI will remain a hot topic in the coming times.
Methodology
To compile our list, we sifted through several active subreddits to compile a list of 15 AI stocks to buy. We then selected the 10 stocks that were the most popular among elite hedge funds and that analysts were bullish on. The stocks are ranked in ascending order of the number of hedge funds that have stakes in them, as of Q2 2024.
Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points (see more details here).
A computer engineer debugging a complex AI application on a powerful workstation.
C3.ai Inc. (NYSE:AI)
Number of Hedge Fund Holders: 18
C3.ai Inc. (NYSE:AI) helps businesses use AI to solve real-world problems by building tools for challenges in areas like supply chain management. These challenges look like fraud detection in finance and predictive maintenance in manufacturing. Its GenAI products are deployed across 15 industries and had 50,000+ inquiries in FQ4.
The company closed 47 agreements, including 34 new pilots, and continued to diversify across industries in this quarter. It entered into new agreements with ExxonMobil, A.P. Moller-Maersk, General Mills, Quest Diagnostics, Flextronics, BASF Petronas, Worley Limited, Thales Group, the U.S. Navy, the U.S. Intelligence Community, the U.S. National Science Foundation, The Secil Group, Cargill, Nucor Corporation, and Dow, among others.
The company recorded a 20% year-over-year growth in FQ4 2024 and was held by 18 hedge funds by the end of this quarter. The largest shareholder was Citadel Investment Groupwith a position of $85,964,864.
C3.ai Inc. (NYSE:AI) was recognized by Constellation Research as a leader in AI and ML platforms. Its platform was included in the ShortList for both Best-of-Breed and Cloud categories, acknowledging its capability for building and running large-scale Enterprise AI applications.
C3.ai Inc. (NYSE:AI) is a leading player in enterprise AI with a head start in the market (90+ applications). It sees AI value transitioning from hardware to software, positioning the company well for long-term growth. Analysts and hedge funds view it as a top AI stock due to its strong market position and successful execution.
Bireme Capital stated the following regarding C3.ai, Inc. (NYSE:AI) in its fourth quarter 2023 investor letter:
“Our final new short position is in a company called C3.ai, Inc. (NYSE:AI). Originally named “C3 Energy,” C3.ai has changed its name multiple times based on whatever hot new trend they were supposedly capitalizing on. The “energy” theme was about smart grid and cap-and-trade. Then the firm changed its name to “C3 IoT” to attempt to capitalize on the Internet of Things buzz. After that trend fizzled out, the moniker was altered once more, with the company capturing the “AI” ticker in December 2020 – a savvy move if it wants to sell stock to credulous investors, but irrelevant to its business prospects. As Kerrisdale put it, the company is a “minor, cash burning consulting and services business masquerading as a software company.”
Overall AI ranks 9th on our list of the best AI stocks to buy. While we acknowledge the potential of AI as an investment, our conviction lies in the belief that AI stocks hold great promise for delivering high returns and doing so within a shorter timeframe. If you are looking for an AI stock that is more promising than AI but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock.
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Disclosure: None. This article is originally published at Insider Monkey.
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