Venture-capital investment in artificial intelligence seems to have slowed a bit in 2022 from the historic highs of last year.
But top VCs at firms like Sequoia Capital, Coatue, Bessemer Venture Partners, Foundation Capital, and others told Insider they’re serious about investing in AI and machine-learning technology, especially as it relates to managing and optimizing vast and unwieldy datasets.
Investment journeys have validated some long-term AI VCs over the past decade. For instance, Ashu Garg of Foundation Capital was an early investor in the analytics decacorn Databricks, which raised a $1.6 billion round last August. The evolution of software technology has helped expand the applications of AI at lower costs, he said.
“If you look at what’s happened in AI, a lot of the core theory has been around for 20 years,” Garg told Insider. “What changed 15 years ago was the cost of computing — people were able to use larger models for the same costs, allowing them to find many more use cases for AI.”
In 2022, VC investments in AI and machine learning amounted to $48.2 billion as of June 30, according to a recent PitchBook report. Last year, VC deals in AI and machine learning amounted to $118 billion, a roughly 80% increase from 2020, according to the report.
Here are 19 venture capitalists to know who specialize in AI and machine learning:
Key investments: Anyscale, Ponder, Opaque, and Verta.
His interest and experience in this space: Araki, an investment manager at Intel Capital who has an engineering background, previously worked at Intel Corporation’s AI team leading machine-learning projects.
Araki said that he’s focused on investing in AI innovations geared toward data management — a reflection of the broader demand for innovations in data optimization and management. He also focuses on the cloud domain, investing in data, analytics, and machine-learning platforms, he said.
“After 14 years on the Intel engineering team, I’d grown passionate about the data community’s innovative culture, and was itching to be part of the startups leading our industry’s evolution, which led me to join Intel Capital as an investment director,” Araki said.
Relationship-building with founders: “I’m part of the data, analytics, and AI communities, and am accessible to entrepreneurs via social media,” he said.
“I do my best to respond quickly to founders around the globe in the data, analytics, and machine-learning domains,” he added. “I like to start the discussion as early as possible, hopefully in the idea stage, and build the relationship from there, even if it is too early for investment.”
Key investments: Hugging Face, Weights & Biases, Runway, Gantry ML, Abacus.AI, Scale AI, Replit, Edge Impulse, and Infinitus Systems.
His interest and experience in this space: Cahn, previously an investment banker at Morgan Stanley focused on tech M&A, has led Coatue’s software-investing practice, and invested in startups using AI to level up coding and databases, he said.
Relationship-building with founders: Cahn said that he typically develops stronger connections with founders who have been introduced through the Coatue network, but that Coatue investors are receptive to hearing from any AI founders.
“We invest in founders who are passionate, courageous, and driven, with the technical credentials to turn ideas into action,” he said.
Key investments: Tecton, Imply, dbt, and Fivetran.
His interest and experience in this space: “I love software,” he said. “And it’s been very clear over the last decade that AI/ML has become a fundamental component for how software is built and how software businesses are run.”
Casado previously cofounded the software company Nicira, which VMware bought for $1.3 billion in 2012, where he stayed on to help lead its networking-and-security business unit. Casado also has expertise in cybersecurity, having worked on what he described as “large-scale simulations” for the Department of Defense. He’s also worked at his alma mater Stanford University, where he has a master’s degree and a Ph.D. in computer science.
Relationship-building with founders: Casado said he welcomes conversations with founders, noting that slides are optional.
Key investments: Hyperscience, Enveda, Galileo, and LatticeFlow.
His interest and experience in this space: Chan, who helped start Google Ventures — now known as GV — and was previously at Felicis Ventures, founded the venture fund FPV this year with Pegah Ebrahimi, who is also on this list.
“As Google was a really big innovator in AI, it’s a natural area we knew well and hence I did a lot of AI companies,” he said.
Chan said that FPV invests in AI used in a range of applications including drug discovery and platform development. Through Felicis, he’s also invested in Hyperscience, an AI-automation company that raised a $100 million round in December.
Relationship-building with founders: Chan said that he usually receives pitches from founders who have been referred from within his AI network.
“Most of our investments are sourced through our referral network of founders and advisors and colleagues from Google, Amazon, and other places of AI excellence where we spend time,” Chan said.
Key investments: Bodo.ai, Snyk, Galileo, and LatticeFlow.
Her interest and experience in this space: Ebrahimi was the youngest CIO at Morgan Stanley, as well as the COO of Morgan Stanley’s Global Tech Banking, and COO of Cisco Collaboration, where she worked with a number of AI startups.
She advises companies like Synk and Canva on go-to-market strategy, helping them better understand the target market and advising them on the right product-messaging and distribution channels, among other things, according to FPV.
She’s also an independent director for companies she hasn’t invested in, like the 3D lithium-ion-battery startup Enovix and ApplyBoard, an edtech startup.
Relationship-building with founders: Similar to Wesley Chan, founders can pitch to her through referrals from the company’s networks in the field, she said.
Key investments: Tubi.tv, Databricks, Anyscale, Regie.ai, and Coefficient.
His interest and experience in this space: Garg joined Foundation in 2008 after running the ads business for Microsoft in the mid-2000s. He worked with AI even at that time, since behavioral targeting on ads was an early, large-scale commercial use case for machine learning, Garg said.
His initial foray into AI and machine-learning investing also focused on marketing-related technology, with what he described as the first wave of funding in content platforms, ad software, and online-video companies like Tubi.tv, TubeMogul, and Conviva. Garg was an early investor in Databricks, which whet his appetite for investing in data-infrastructure companies, he said. He now also invests in a range of applied-AI startups.
Relationship-building with founders: Garg said he looks for “technical founders solving harder technical problems” for which there is a large market. As an early-stage investor, Garg said he also looks to be with a startup for the long-haul. “We’re most in the business of trying to build generational companies,” he said.
Though he does look at cold emails, the best way to reach him would be through a founder he works with, he said.
Key investments: Glean, Streamlit, Hugging Face, Tecton, dbt, and Amplitude.
Her interest and experience in this space: Huang describes herself as a thematic investor who looks for top founders and companies behind technology “mega trends.”
After graduating from Princeton in 2014 with a minor in computer science, statistics, and machine learning, Huang worked as an analyst at Goldman Sachs. Her work at Sequoia has involved advising a number of early-stage companies, where she said she has leveraged her finance expertise.
“Even taking machine-learning classes back in college, it was clear that we were about to enter an inflection point in AI: More and more data, compute, and better algorithms,” she said. “So it felt natural that data and AI were the themes I wanted to go all-in on as an investor.”
She has invested in a range of software and machine-learning startups, and said she’s particularly interested in the field of generative AI, a category of tech that uses algorithms to create visual imagery and other types of media.
Relationship-building with founders: Huang said she hopes founders see her as a reliable partner who cares about them, as one who understands the data-and-artificial-intelligence market.
“Somebody they enjoy being around, their first call when anything goes right or wrong,” she said.
Key investments: Cohere, Covariant, Unlearn, Untether, Twelve Labs, and Waabi.
His interest and experience in this space: Jacobs was once a tech attorney at a Canadian firm before embarking on his own artificial-intelligence ventures. One of them was Layer 6 AI, which he ended up selling to TD Bank. He also cofounded the Vector Institute for Artificial Intelligence in Toronto, an organization that’s encouraged investments in AI technology.
Having expertise in AI technology has not only given him a sense for the real-world applications and uses of AI algorithms, but also helped him understand how to sell those products to wary users, he said.
“Often, the recipient is a data scientist who might be threatened by the existence of the AI, thinking it’s going to do their job better than them,” he said. “So how do you turn those people from skeptics to your evangelists?”
Relationship-building with founders: “We tend to have strong relationships throughout the research community — all the top universities in the world doing AI, and many, many founders,” he said. “So if you are like a true AI founder, it shouldn’t be that hard to reach us through a warm lead.”
But founders can also attempt outreach through the firm’s website or social media, he said.
Key investments: Prefect, Coiled, Arcion, and Okera.
His interest and experience in this space: “I’ve been investing in developer platforms since the early days of cloud software, where the developer is the one who chooses their own tools to build, run, or manage the infrastructure,” Kurzweil said.
“After that trend has been running for a decade, we are now witnessing the same trends happening with data and applied AI — the specialists who conceptualize, build, and run the data tooling for the enterprise are now being empowered to create their own tool chain and as a student of this type of trend in the past, I got extremely excited to partner with the next generation of entrepreneurs who are bringing this shift to the enterprise, allowing these benefits to take advantage of the benefits of building data-aware applications,” he said.
Relationship-building with founders: “Founders should pitch me however it is best for them!” he said.
Key investments: Weights & Biases, Metabase, Astronomer, Pecan.ai, and Honeycomb.
His interest and experience in this space: Mathew focused on building data, analytics, artificial-intelligence, and machine-learning products for over 15 years before joining Insight Partners as an early-stage growth investor. He’s previously worked at companies including Salesforce, SAP, and Alteryx. He was also the CEO of the drone-analytics company Kespry.
Relationship-building with founders: “I love founders who come well-referenced with a compelling approach to changing the status quo in the data space,” Mathew said. “Just as the cloud-native data lakes are expanding the on-prem data-warehousing market, we believe there is a massive opportunity to invest in both the tools and applications built on top of these seminal platforms.”
Key investments: Tecton, Materialize, and Labelbox.
His interest and experience in this space: “As an investor, I focus on infrastructure,” Moore said. “Through this lens, the opportunity to provide foundational capabilities for developers and data scientists to bring AI to the world is massive and accelerating — I was drawn to the space by this realization.”
Relationship-building with founders: “Reach out any time, anywhere, and share as much relevant background context up-front as possible,” he said.
Key Investments: Abnormal Security, Adept AI, Apiiro, Cresta, Snorkel, and Predibase.
His interest and experience in this space: Motamedi’s early experience in AI includes his time in product management at the startup RelateIQ, which Salesforce later acquired.
“At RelateIQ, we built an intelligent CRM leveraging natural-language processing and other machine-learning techniques on top of email and sales data to enable sales reps to more efficiently and effectively engage and close accounts,” he said.
“Since seeing the power of AI/ML applied to business workflows first-hand, I’ve been highly focused on partnering with intelligent-application companies and the infrastructure companies that enable large enterprises to better utilize AI/ML,” he said.
Relationship-building with founders: “The best way to pitch me is on email (firstname.lastname@example.org) with a clear articulation of the North Star you’re building toward and why you’re the right team to do it,” he said.
Key Investments: SambaNova Systems, Modular, Pixie Labs, and Snorkel.
His interest and experience in this space: Dave Munichiello leads GV’s digital-investing team, which focuses on companies dealing with data, AI, and machine learning. He has a degree in mathematics and computer science and served in the US Air Force, leading technology teams there, he said.
He also led the tech and product teams at Kiva Systems, which, after its acquisition by Amazon in 2012, became known as Amazon Robotics.
“Since joining GV nearly a decade ago, I have tried to spend dedicated time each quarter with data practitioners across Google’s research teams to stay close to the cutting edge of AI and ML — both its infrastructure and the many applications those technologies power,” he said.
Relationship-building with founders: Munichiello said he looks for founders focused on big data, AI, and machine-learning innovations and those emphasizing “product evolution and its potential for significant impact in the future.”
He also said that he prefers direct, warm introductions from other founders he’s worked with and tech networks.
“I prioritize partnering with technologists who value building long-term relationships grounded in curiosity, drive, vision, and humility amidst a constant pursuit of excellence,” he said. “With markets constantly changing, I value teaming with founders who display grit and resilience with deep care for their company.”
Key investments: Hugging Face, Tecton, Fiddler AI, and Anduril.
His interest and experience in this space: Reeves told Insider he’s been following the field of AI since his undergraduate research in natural-language processing — the technology around machines being able to understand and respond to human commands — and expert systems.
Relationship-building with founders: “We look at everything from infrastructure to the application layer,” he said, referring to new ideas. “Obviously, there’s lots of excitement right now in the field, but the important questions are ‘why now,’ ‘founder-market fit,’ and how to think about long-term business durability,” he said.
Key investments: ChaosSearch, FeatureByte, and Verusen.
Her interest and experience in this space: Seseri spent her early career at Credit Suisse and Microsoft, where she was a senior manager in corporate development. She then left the tech giant in 2007 to take on a full-time role in venture at Fairhaven Capital, a boutique firm based in Boston, Massachusetts. Seseri then moved on to cofound Glasswing Ventures in 2016.
Relationship-building with founders: Seseri said she can be reached directly via email at email@example.com and responds to online messages. “I look at every single email that comes in, every text message, Twitter DM,” she said. “As much as founders are looking for capital, I am looking for them.”
Key investments: Dataiku, Ada Support, Synthesia, Hyperscience, Cockroach Labs, and ClickHouse.
His interest and experience in this space: Turck, an AI veteran, described investors’ lackluster reception of the tech during his early years in the field more than two decades ago. He previously cofounded the startup TripleHop Technologies, an enterprise search-software company that used AI techniques, which Oracle acquired in the mid-2000s. He described how, at the time, they would have to downplay their AI work to VCs.
“Because they would just look at us like, ‘Kid, don’t you know, AI is dead?'” he said.
“Regardless, that was a great head start for me to get deeply immersed in the field,” he added. “It was a very natural area for me to focus on when I became a VC.”
Relationship-building with founders: “If you’re building an AI application, I’m interested in understanding how using AI makes a 10-time difference to the problem you’re trying to solve,” Turck said.
“If you’re building data or AI infrastructure, I’m interested in how you’re differentiating in an increasingly crowded market,” he added. “Also, I tend to get excited by founding teams that have deep technical expertise, but also a natural commercial inclination.”
Key investments: Lightning.AI, Magical, Xembly, and Jiffy.AI.
His interest and experience in this space: Viswanath, who has a degree in computer science and was previously the chief technology officer at the software company Atlassian, joined Coatue this year as a general partner investing in AI-driven consumer-and-enterprise technology, according to the firm.
“As an investor and an advisor, I have been able to leverage my business expertise to help founders home in on their technology edge and solve for large-scale issues,” he said.
Relationship-building with founders: “We want to hear from founders who are looking beyond the immediate applications of AI and are finding opportunities to leverage AI for the broader good,” he said.
Key investments: Anyscale, Amenity Analytics, Augtera Networks, and OtterTune.
His interest and experience in this space: Washburn said he often invests in early-stage enterprise-software tech, and focuses on startups involving cloud infrastructure, applications, developer tools, and data platforms. He sits on the boards of a number of startups he’s invested in, including the cloud-network-AI company Augtera Networks, and OtterTune, a database-optimization platform that uses machine learning.
Now a senior managing director at Intel Capital, Washburn described his path to becoming a VC as serendipitous. He studied political science at the College of the Holy Cross, aiming for a Wall Street job, then wound up going to law school and working on the deals teams at big law firms including Simpson Thacher & Bartlett LLP.
Despite his success at the firm, he said the fit wasn’t ideal — he ended up turning down a partner role there and joined Intel Capital instead.
Relationship-building with founders: Washburn said he’s especially receptive to founders involved with developer tools, cloud infrastructure, data platforms, or the AI/ML workflow. Founders can email him at firstname.lastname@example.org, and he may also respond on social media including Twitter and LinkedIn, he said.
“Given I predominantly focus on Series A investing — it is naturally a very early stage, and will be a long journey working together,” Washburn said. “So I very much try and approach things as non-transactional, getting to know teams, and working to collaborate and show value on my end well before any actual fundraising process.”
Key investments: Databricks, Dataiku, Collibra, MX, and Armis.
His interest and experience in this space: Previously at the investment firms TPG, Hellman & Friedman, and GIC, Zanutto had invested in the likes of Uber and Airbnb. At CapitalG, which he joined in 2018, he has invested in growth companies and AI-startup unicorns including Databricks.
Relationship-building with founders: Investors from CapitalG often reach out to some of the companies the firm is interested in, but founders can also directly contact Zanutto and other investors at the firm, according to CapitalG.
“At CapitalG we partner with growth-stage companies in their transition from startup to scale up,” Zanutto said. He pointed to Florian Douetteau, the CEO of Dataiku, and Ali Ghodsi, the CEO of Databricks, as examples of AI leaders he’s teamed up with, saying they’re “changing the way enterprises capture, store, analyze, and leverage data.”
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19 Top VCs to Know Investing in AI and Machine-Learning Startups – Business Insider
Venture-capital investment in artificial intelligence seems to have slowed a bit in 2022 from the historic highs of last year.