Investment Context
3 conversational turns exploring this topic
Q: What's getting funded in AI that indicates research priorities?
Subject: Forget the Hype: Where the REAL AI Money is Going
Here's a truth most won't admit: the AI "revolution" is being bankrolled by a handful of players with very specific agendas. This week's funding news, distilled from 1800+ articles, screams this louder than ever.
The Obvious (and Overhyped):
Everyone's breathlessly reporting on the potential $50B OpenAI is chasing in the Middle East and Sequoia's continued Anthropic bets. Yes, these are massive numbers. But focusing solely on them is like watching a magician's left hand while the real trick happens on the right.
| Company | Funding Focus (Perception) | My Take |
|---|---|---|
| OpenAI | General AI Domination | This is about securing compute. Plain and simple. The Middle East is swimming in capital and hungry for strategic tech investments. OpenAI needs the infrastructure to train bigger, more complex models. It's a land grab, not necessarily a sign of a breakthrough in fundamental AI research. |
| Anthropic | AI Safety & Alignment | Sequoia's bet is on a narrative. Anthropic is selling the responsible AI story, which resonates with investors concerned about the ethical implications of runaway AI. While important, it's debatable whether this translates to a sustainable competitive advantage. Their Claude model is good, but is it that much better than the rest to justify the valuation? I'm skeptical. |
The REAL Story: Infrastructure and Data Enablement
Buried beneath the headlines about OpenAI and Anthropic is a more telling trend: investment in the picks and shovels of the AI gold rush.
Take ClickHouse, for example. They just snagged a $400M Series D. Why? Because they provide the blazing-fast data analytics engine that every AI company needs to process the mountains of data required for training and inference. This isn't sexy, but it's essential.
Then there's OpenEvidence, valued at $12 Billion after recent funding. They're tackling AI in healthcare, but their real value proposition is aggregating and structuring medical data. Data is the new oil, and OpenEvidence is drilling it.
My Hot Take:
The future of AI isn't just about building smarter models. It's about building the infrastructure to support those models and, crucially, gaining access to high-quality, structured data. The companies that control the data pipelines and the compute resources will ultimately win.
Advice for Data Professionals:
- Look beyond the shiny objects: Don't get caught up in the hype around specific AI models or applications. Focus on the underlying infrastructure and data challenges.
- Sharpen your data engineering skills: Expertise in data pipelines, data warehousing, and data governance is becoming increasingly valuable. Learn tools like ClickHouse, Snowflake, and dbt.
- Specialize in a vertical: Deep domain knowledge combined with AI skills is a powerful combination. Focus on industries like healthcare, finance, or manufacturing, where data is abundant but often poorly managed.
Forget chasing the next LLM breakthrough. The real money – and the real opportunity – lies in building the foundation for the AI-powered future.
Yves Mulkers
Ins7ghts
Q: Which area has the most investment?
Subject: Re: Forget the Hype: Where the REAL AI Money is Going
You asked which area has the most investment. The headline numbers scream "Large Language Models!" – Anthropic and OpenAI dominate the news cycle, sucking up investment like black holes. But focusing solely on them is missing the forest for the trees.
The real story isn't just who's building the biggest model, but who's enabling them.
| Company | Article Count | Hot Take |
|---|---|---|
| Anthropic | 19 | Obvious play. Sequoia's hedging their bets, and everyone else is piling on, driven by FOMO. The real question is: can they really differentiate from OpenAI in the long run, or are they just a (very expensive) insurance policy? |
| OpenAI | 14 | The 800lb gorilla. The Middle East funding rumors are interesting – diversifying their investor base beyond Microsoft is crucial for long-term independence. Watch for geopolitical strings attached. |
| ClickHouse | 9 | THIS is the one to watch. Everyone's obsessing over model creation, but ClickHouse is quietly building the infrastructure to manage the tsunami of data these models generate. Real-time analytics at scale is the unsexy but crucial foundation for AI. |
| OpenEvidence | 8 | Interesting niche play in medical AI. $250M is nothing to sneeze at, but the $12B valuation feels inflated. AI in healthcare is promising, but regulatory hurdles and data privacy concerns will make scaling much harder than in other sectors. |
My hot take? Data infrastructure is the new AI gold rush. Building better models is great, but without the tools to efficiently store, process, and analyze the resulting data, those models are useless. ClickHouse's $400M Series D is a signal – smart money is flowing into the picks and shovels of the AI revolution.
Think about it: every query to ChatGPT, every image generated by DALL-E, every prediction made by an AI model, generates mountains of data. Someone needs to manage that data, and that's where the real opportunity lies.
Advice:
- Stop chasing the shiny object. Don't get caught up in the LLM hype.
- Look under the hood. Understand the infrastructure that powers AI.
- Invest in data skills. Learn how to manage, analyze, and visualize large datasets. SQL is your friend.
- Consider companies like ClickHouse, Snowflake, Databricks. They're not as glamorous as OpenAI, but they're building the foundation for the future of AI.
Forget the hype. Focus on the fundamentals. That's where the real value is.
Q: What research gaps does this reveal?
Subject: Re: Forget the Hype: Where the REAL AI Money is Going
You asked which research gaps this reveals. The headline numbers scream "Large Language Models!" – Anthropic and OpenAI dominate the news cycle, hoovering up billions. But look closer. The real story isn't the models themselves, it's what's missing to make them actually useful and safe in the real world.
The money chasing LLMs is creating a dangerous blind spot. We're building Ferraris without roads.
Here's what I'm seeing in the data from 1,800 articles this week:
| Gap Area | Description | Why It Matters