While you’re busy Ghibli-fying your images with ChatGPT’s new image-generation capabilities, OpenAI is out raising a ton more cash. The company is close to finalizing a new $40 billion funding round led by SoftBank, according to a report from Bloomberg. The report noted that other funds, including the hedge fund Magnetar Capital, Coatue Management, Founders […]
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Microsoft adds AI-powered deep research tools to Copilot
Microsoft is introducing a “deep research” AI-powered tool in Microsoft 365 Copilot, its AI chatbot app. There’s been a raft of deep research agents launched recently across chatbots, including OpenAI’s ChatGPT, Google’s Gemini, and xAI’s Grok. Powering them are so-called reasoning AI models, which posses the ability to think through problems and fact-check themselves — […]
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Daphni secures $215M for its third fund
French VC firm Daphni is announcing the first closing of its new fund, Daphni Blue. The firm has raised €200 million (around $215 million at current exchange rates). It expects to raise as much as €250 million ($270 million) by the end of the year. Some of Daphni’s most remarkable past investments include Back Market, […]
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Future of the AI Age
Embracing the Future: Navigating the Age of Artificial Intelligence
As we stand on the brink of a new era, the Age of Artificial Intelligence (AI), we find ourselves at a unique crossroads in history. The advancements in AI technology have already begun reshaping our lives, workplaces, and global systems. But what does the future hold in this fast-evolving landscape? Let’s explore the potential developments, challenges, and opportunities on the horizon.
The Rapid Evolution of AI
AI has evolved rapidly over the past decade, driven by breakthroughs in machine learning, natural language processing, and neural networks. From self-driving cars6 to virtual personal assistants, AI is already embedded in many facets of our daily lives. As we move forward, we can expect even more sophisticated applications:
Enhanced Personalization: Businesses will leverage AI to offer hyper-personalized experiences. From tailored marketing to individualized healthcare plans, the ability to analyze vast amounts of data will revolutionize customer engagement.
Autonomous Systems: The development of autonomous vehicles, drones, and robots will transform transportation and logistics. Imagine a world where traffic congestion and accidents are significantly reduced, and delivery systems become faster and more efficient.
AI in Healthcare: AI’s role in healthcare will expand dramatically. From predictive analytics that improve patient outcomes to AI-powered diagnostic tools that enhance accuracy, the potential to save lives and improve overall health is immense.
The Workforce Transformation
As AI continues to advance, it will undoubtedly impact the job market. Some may view AI as a threat to employment, while others recognize its potential to create new opportunities. The key will lie in adaptation:
Automation vs. Augmentation: Certain jobs may become obsolete due to automation, but AI will also augment human capabilities. Professionals will need to reskill and upskill to work alongside AI, focusing on tasks that require creativity, emotional intelligence, and critical thinking.
New Job Categories: The rise of AI will give birth to entirely new job categories that we can’t yet imagine. Roles such as AI ethics consultants, data curators, and machine learning trainers will emerge, highlighting the need for a workforce that is adaptable and ready for change.
Ethical Considerations and Challenges
As we embrace the Age of AI, we must also confront the ethical implications that come with it. Questions regarding data privacy, bias in algorithms, and the accountability of AI systems are paramount. The following considerations will be crucial:
Regulating AI: Governments and organizations must develop robust regulatory frameworks to ensure that AI is used responsibly. Striking a balance between innovation and regulation will be essential to foster trust and protect public interests.
Addressing Bias: AI systems are only as good as the data they’re trained on. If not addressed, issues surrounding bias can lead to discriminatory outcomes. Ongoing efforts to diversify data sources and establish fairness protocols will be vital.
AI Ethics and Governance: Establishing ethical guidelines for AI development and implementation is a pressing need. Industry leaders, policymakers, and technologists must collaborate to create a framework that prioritizes humanity’s well-being.
The Promise of Collaboration
The future of the AI Age is not a solitary journey; it will require collaboration across borders and disciplines. The most successful innovations will emerge from partnerships that bring together diverse perspectives and expertise. Collaboration can lead to:
Global Solutions: Tackling the world’s most pressing challenges—such as climate change, public health crises, and economic inequality—will rely on AI’s power, coupled with collective human ingenuity.
Public Engagement: Fostering a dialogue between technologists and the public is essential. Educating individuals about AI, its implications, and empowering them to participate in discussions will create a more informed society ready to embrace the future.
Conclusion
The Age of AI promises to be transformative, offering unprecedented opportunities alongside significant challenges. As we navigate this new landscape, a proactive approach will be essential. By prioritizing education, ethical considerations, and collaboration, we can harness the potential of AI to enrich our lives, drive innovation, and create a better future for all.
As we look ahead, let us embrace the possibilities of AI with optimism and responsibility. The future is here, and it’s up to us to shape it.mited plan. -
On Funding — Shots on Goal
On Funding — Shots on Goal
Being great as a startup technology investor of course requires a lot of things to come together:
- You need to have strong insights into where technology markets are heading and where value in the future will be created and sustained
- You need be perfect with your market timing. Being too early is the same as being wrong. Being too late and you back an “also ran”
- You also need to be right about the team. If you know the right market and enter at this exact right time you can still miss WhatsApp, Instagram, Facebook, Stripe, etc.
I’ve definitely been wrong on market value. I’ve sometimes been right about the market value but too early. And I’ve been spot on with both but backed the 2nd, 3rd or 4th best player in a market.
In short: Access to great deals, ability to be invited to invest in these deals, ability to see where value in a market will be created and the luck to back the right team with the right market at the right time all matter.
When you first start your career as an investor (or when you first start writing angel checks) your main obsession is “getting into great deals.” You’re thinking about one bullet at a time. When you’ve been playing the game a bit longer or when you have responsibilities at the fund level you start thinking more about “portfolio construction.”
At Upfront we often talk about these as “shots on goal” (a fitting soccer analogy given the EURO 2020 tournament is on right now). What we discuss internally and what I discuss with my LPs is outlined as follows:
- We back 36–38 Series Seed / Series A companies per fund (we have a separate Growth Fund)
- Our median first check is $3.5 million, and we can write as little as $250k or as much as $15 million in our first check (we can follow on with $50 million + in follow-on rounds)
- We build a portfolio that is diversified given the focus areas of our partners. We try to balance deals across (amongst other things): cyber-security, FinTech, computer vision, marketplaces, video games & gaming infrastructure, marketing automation, applied biology & healthcare systems, sustainability and eCommerce. We do other things, too. But these have been the major themes of our partners
- We try to have a few “wild, ambitious plans” in every portfolio and a few more businesses that are a new model emerging in an existing sector (video-based online shopping, for example).
We tell our LPs the truth, which is that when we write the first check we think each one is going to be an amazing company but 10–15 years later it has been much hard to have predicted which would be the major fund drivers.
Consider:
- When GOAT started it was a restaurant reservation booking app called GrubWithUs … it’s now worth $3.7 billion
- When Ring started, even the folks at Shark Tank wouldn’t fund it. It sold to Amazon for > $1 billion.
- We’ve had two companies where we had to bridge finance them several times before they eventually IPO’d
- We had a portfolio company turn-down a $350 million acquisition because they wanted at least $400 million. They sold 2 years later for $16 million
- In the financial crisis of 2008 we had a company that had jointly hired lawyers to consider a bankruptcy and also pursued (and achieved!) the sale of the company for $1 billion. It was ~30 days from bankruptcy.
Almost every successful company is a mixture of very hard work by the founders mixed with a pinch of luck, good fortune and perseverance.
So if you truly want to be great at investing you need all the right skills and access AND a diversified portfolio. You need shots on goal as not every one will go in the back of the net.
The right number of deals will depend on your strategy. If you’re a seed fund that takes 5–10% ownership and doesn’t take board seats you might have 50, 100 or even 200 investments. If you’re a later-stage fund that comes in when there’s less upside but a lower “loss ratio” you might have only 8–12 investments in a fund.
If you’re an angel investor you should figure out how much money you can afford to lose and then figure out how to pace your money over a set period of time (say 2–3 years) and come up with how many companies you think is diversified for you and then back into how many $ to write / company. Hint: don’t do only 2–3 deals!! Many angels I know have signed over more than their comfort level in just 12 months and then feel stuck. It can be years before you start seeing returns.
At Upfront Ventures, we defined our “shots on goal” strategy based on 25 years of experience (we were founded in 1996):
- We take board seats and consider ourselves company-builders > stock pickers. So we have to limit the number of deals we do
- This drives us to have a more concentrated portfolio, which is why we seek larger ownership where we invest. It means we’re more aligned with the outcomes and successes of the more limited number of deals we do
- Across many funds we have enough data to show that 6 or 7 deals will drive 80+% of the returns and a priori we never know which of the 36–38 will perform best.
- The outcome of this is that each partner does about 2 new deals per year or 5.5 per fund. We know this going into a new fund.
So each fund we’re really looking for 1–2 deals that return $300 million+ on just one deal. That’s return, not exit price of the company. Since our funds are around $300 million each this returns 2–4x the fund if we do it right. Another 3–5 could return in aggregate $300–500 million. The remaining 31 deals will likely return less than 20% of all returns. Early-stage venture capital is about extreme winners. To find the right 2 deals you certainly need a lot of shots on goal.
We have been fortunate enough to have a few of these mega outcomes in every fund we’ve ever done.
In a follow-up post I’ll talk about how we define how many dollars to put into deals and how we know when it’s time to switch from one fund to the next. In venture this is called “reserve planning.”
** Photo credit: Chaos Soccer Gear on Unsplash
On Funding — Shots on Goal was originally published in Both Sides of the Table on Medium, where people are continuing the conversation by highlighting and responding to this story.