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The once relatively vibrant M&A market has come to a screeching halt, with basically no BIG tech acquisitions of startups. Instead, tech giants are now testing out a new strategy to skirt regulators; hiring away the founders and key teams from startups, while licensing their some of their tech/IP. This approach allows companies like Microsoft, Google and Amazon to basically buy the top people without the complexities of full acquisitions - almost like outsourced R&D.

Once an outlier, twice a coincidence, three times a trend.

Why is BIG Tech Scared to Acquire Startups?

1. Regulatory Scrutiny: Increased government scrutiny on large acquisitions has made it basically impossible for tech giants to pursue traditional M&A. Antitrust concerns and lengthy approval processes have pushed companies to find alternative ways to bring innovation in-house - basically outsourcing it via investments. Really bad for investors.

2. Financial Prudence: Acquiring startups can be costly, and with market volatility, big tech companies are opting for less capital-intensive methods. Hiring key talent and licensing technology can be more cost-effective, reducing financial risk. And sadly investors dont make a lot of money this way.

3. Focus on Talent: The value of human capital in tech cannot be overstated. By hiring top talent from startups, big tech firms gain access to expertise and innovative thinking that can be immediately leveraged within their organizations. They leave an empty shell company behind.

Impact on Startups and Investors

This new trend has mixed implications for startups and their investors:

• For Startups: Founders and core teams might find lucrative opportunities within big tech companies, but the shell of a company will probably struggle without key personnel. Basically a year and a half into the Ai hype bubble, this will give pause possibly to some founders of new Ai startups / investors investing in them.

• For Investors: The exit opportunities via acquisition, which traditionally provided substantial like 95%+ of all returns, are dwindling. Licensing deals and talent poaching do not offer the same financial upside, leading to lower returns on investment. Aka less capital being invested into Ai startups if there is no BIG liquidity returns possible.

Examples of Recent Hire&License (H&L)

Google and Character.AI

• Founders: Noam Shazeer and Daniel De Freitas

• Funding Raised: Character.AI raised $150 million in March 2023, led by Andreessen Horowitz, at a $1 billion valuation. Google was rumored to be in discussions to invest hundreds of millions of dollars into Character.AI but that obviously never happened

• Investors: Andreessen Horowitz lead

• Deal Details: Google licensed Character.AI's technology and reintegrated the founders into their AI unit. The General Counsel took over as interim CEO because they have no idea what else to do

• Founders' Background:

  • Noam Shazeer: A former Google engineer, Shazeer is known for his work on Google Brain and as a co-creator of the Transformer architecture, which is the foundation of many modern AI models, including GPT-3.

  • Daniel De Freitas: Previously at Google, De Freitas worked on various AI and machine learning projects. His expertise in building conversational agents and AI systems played a crucial role in the development of Character.AI.

Microsoft and Inflection AI

• Founders: Mustafa Suleyman (co-founder of DeepMind) and Karén Simonyan

• Funding Raised: Inflection AI was valued at $4 billion in 2023 after raising $1.3 billion, with Microsoft as a lead investor.

• Investors: Greylock, Dragoneer Investment Group, and Microsoft.

• Deal Details: Microsoft paid $650 million to Inflection AI for licensing their AI technology and hired most of its staff. This strategy allows Microsoft to leverage Inflection AI's models while integrating the talent into its own AI projects. The transaction has attracted regulatory scrutiny already, highlighting some new complexities of such arrangements but will definitely take years to figure out.

• Founders' Background:

  • Mustafa Suleyman: A co-founder of DeepMind, Suleyman played a key role in its development before it was acquired by Google. At DeepMind, he focused on the application of AI to real-world problems, contributing significantly to its advancements in AI research.

  • Karén Simonyan: Another co-founder of Inflection AI, Simonyan has a background in AI research and development, particularly in neural networks and machine learning. His work at DeepMind and later at Inflection AI has been pivotal in advancing AI technologies.

Amazon and Adept AI

• Founders: David Luan, Augustus Odena, Maxwell Nye, Erich Elsen, and Kelsey Szot

• Funding Raised: $350M March 2023, which came less than a year after it raised $65 million Series A in April 2022

• Investors: Series B led by General Catalyst and co-led by Spark Capital

• Deal Details: Amazon hired the founders and key employees from Adept AI and licensed their technology, including AI models and datasets. The remaining team at Adept AI continues to operate independently, focusing on agent AI solutions and is completely screwed.

• Founders' Background:

  • David Luan: Formerly a director of engineering at OpenAI and a VP of engineering at Google, Luan has extensive experience in AI development. His leadership at Adept AI focused on creating AI agents to automate complex tasks.

  • Augustus Odena: Known for his research in generative models and adversarial training, Odena has contributed significantly to the field of AI. His work has been widely recognized and cited in AI research communities.

  • Maxwell Nye: Nye's expertise lies in natural language processing and machine learning. His work at Adept AI and previous roles has centered on developing advanced AI models.

  • Erich Elsen: With a background in machine learning and AI, Elsen has worked on various projects that push the boundaries of AI capabilities. His technical skills have been crucial in developing Adept AI's technology.

  • Kelsey Szot: Szot has a strong background in AI research and product development. Her work at Adept AI involved creating AI-driven solutions for enterprise applications.

Failed M&A Example: Adobe and Figma

Adobe and Figma

• Deal Overview: Adobe announced its intention to acquire Figma for approximately $20 billion in 2022. However, this acquisition faced significant regulatory hurdles from the start but was very welcomed after a rough year and a half in the VC world post ZIRP

• Outcome: After over a year of speculation and regulator scrutiny, they called off the deal, Adobe had to pay Figma $1B in a breakup fee, then Figma raised a down round around a $10B valuation. So now they can only hopefully IPO in the coming years.

Recent Tech Startup M&A Data (2022-2023)

• In 2023, the number of M&A deals targeting startups on Carta was 574, down 11% from the previous year. Despite the decline, M&A activity targeting startups remains significantly higher than in 2019 and 2020.

• Worldwide M&A deal value reached $3 trillion in 2023, making it the second-weakest year in a decade. However, the total estimated M&A deal count was 40,200—the third highest on record.

• The Americas accounted for 51% of global M&A activity in the first quarter of 2023, with the technology, media, and telecommunications (TMT) sector being the most active.

1. Do you think we’re in an Ai bubble? What’s your favorite Ai product?

2. I’m looking to meet with some pre/seed Israeli startups and investors if you know any.

3. Your trusted guide for health www.roon.com

FIND ME: 𝕏 @Trace_Cohen / in LinkedIn / [email protected]