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What’s Ahead for AI investments?

As artificial intelligence evolves, the investment landscape shifts alongside it. We spoke with Austin Yu, an expert in AI strategy, to gain perspective on the future of large language models (LLMs), the role of GPUs, and where meaningful investments are headed. Below, he offers insights into why LLMs have reached their peak, what infrastructure developments could lead to the next phase, and the untapped potential in applied AI.

Q: It seems like the wave of investments in LLMs and GPUs has reached a peak. Where do you see AI investments moving from here?

Austin: “LLMs are largely becoming commoditized – I don't think there's a huge differentiation from one model to another. That’s probably why OpenAI is pushing hard toward AGI. The diversity of training data is limited, and while alternative training techniques or potential disruptors to the transformer model are interesting, they might not catch on quickly due to the entrenched momentum of transformer-based models. Going forward, it’s quality-of-life features and services that will distinguish one provider from another. Pricing will also be a key factor; bigger players have the advantage of subsidizing the core LLM services in ways that newcomers can’t.”

Q: With Nvidia dominating the GPU market, how much market share do you think a new chip company could realistically capture?

Austin: “On the inference side, AMD is fighting hard to secure the #2 spot, but Nvidia’s CUDA ecosystem is a massive barrier to overcome. Building a faster or more efficient chip than Nvidia isn’t trivial – and there are several well-funded companies attempting it – but what’s even harder is creating a chip that’s more usable than Nvidia’s. I believe startups working on custom accelerators will likely shift toward selling compute services and become more service-focused in order to stay competitive.”

Q: You mentioned two main categories for AI investments: infrastructure and applied AI. Where do you see the biggest opportunities in these areas?

Austin: “Over time, I think there may be some applied AI – such as AI or generative AI-enabled applications – that could deliver exponentially higher returns than the ‘picks and shovels’ model. That said, the infrastructure side, with new developments in the data layer, security layer, and serving layer, remains a highly compelling space due to the innovations driven by generative AI workloads across all layers of infrastructure.

"However, I’m concerned that many customers may lack the sophistication to make the most of these tools. For instance, I don’t believe most enterprises have the talent density needed to handle advanced fine-tuning effectively.”

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Bay Area Startups Secured Over $719M

The first full week of November was subdued in funding activity, recording just $719M in fundings -$400M of that in a single deal to Physical Intelligence. Exit activity was likewise subdued – no significant acquisitions and no IPOs (or even IPO filings). With the uncertainty of elections behind us and the Federal Reserve taking interest rates down another quarter of a percentage point, there may be light on the horizon for more robust funding in the startup ecosystem, but it's likely we're not going to find out until the new year.

Follow LinkSV on LinkedIn to stay on top of Bay Area startup fundings and exits.

Early Stage:

• Cynch AI closed a $18.7M Series A, combining reasoning, machine learning, and generative AI to change the way people make financial decisions.

• Fractional closed a $15M Series A, helps users co-invest in properties together.

• Endeavor AI closed a $7M Seed, helps industrial enterprises solve their critical problems by transforming their processes with AI.

• Algorized closed a $4.3M Seed, enables groundbreaking sensing and positioning applications through a software-only upgrade to existing commodity sensors.

• Corgea closed a $2.5M Seed,leverages AI to reduce development effort by 80%, enabling security teams to issue pull requests for source code fixes for engineering approval.

Growth Stage:

• Physical Intelligence closed a $400M Series A, bringing general-purpose AI into the physical world.

• ZAP Surgical Systems closed a $78M Series E, the industry’s first dedicated, non-invasive cranial radiosurgery solution to incorporate advanced gyroscopic technology.

• Inquis Medical closed a $40M Series B, a clinical stage medical device company focused on peripheral vascular innovations.

• PrognomiQ closed a $34M Series D, a healthcare company pursuing the development and commercialization of multi-omics human tests for cancer and other complex diseases.

• OptraSCAN closed a $30M Series B, providing cutting-edge digital pathology solutions, including state-of-the-art digital pathology scanners and whole slide imaging scanners.

  
  

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Head of Content // Team Ignite

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