What’s hot in AI?

I blogged the other day about what’s hot and what’s not in fintech, but what about what’s hot and what’s not in AI? Equally, as I also blogged, AI is not one thing. It’s a million use cases which are all different. So, what are hot use cases for AI?

Well, luckily, Allie Garfinle on Forbes, has surveyed nine VCs about where we’re at in the AI boom, and what they’re keeping an eagle-eye out for. Here are the nine AI startup ideas that VCs wish someone would pitch them on.

1: Reinventing recruiting

Recruiting is in desperate need of an AI glow-up, says NFX founding partner James Currier. “Recruiting has always been a mess,” Currier adds. “But I think with AI, you could just reinvent the experience. It’s been over a year-and-a-half, and no one’s done it. Let’s just throw out everything we know about it. It’s such an amorphous problem, it’s perfect for AI.”

2: Materials Discovery

For Tom Biegala and Ben Hemani, founding partners at Bison Ventures, they want to see more companies at the intersection of AI and materials discovery––using artificial intelligence and other advanced computational approaches to develop new materials with novel properties and applications. Think new more biodegradable and reusable plastics, new alloys that are lighter weight and cheaper to make, and new materials for batteries.

“AI has been talked about for a very long time as a way to accelerate materials discovery,” says Biegala, Founding Partner at Bison Ventures. “It’s just a very hard nut to crack, and you need a very unique kind of combination of AI expertise, plus material slash chemical expertise, plus high throughput experimentation, plus amazing engineers that understand the ins and outs of these various use cases and how to bring materials to markets.”

3: An AI speed reader

For this one, instead of using the Forbes text, here’s what JPMorgan Chase has to say (from 2017): At JPMorgan, a learning machine is parsing financial deals that once kept legal teams busy for thousands of hours. The program, called COIN, for Contract Intelligence, does the mind-numbing job of interpreting commercial-loan agreements that, until the project went online in June, consumed 360,000 hours of lawyers’ time annually. The software reviews documents in seconds, is less error-prone and never asks for vacation.

4: An open-source Nvidia CUDA alternative

Nagraj Kashyap, General Partner at Touring Capital, has a really specific idea: Build an open-source alternative to NVIDIA’s CUDA software that would allow AI developers to work on diverse hardware platforms and reduce costs for startups. “Solving this upstream problem could unlock AI discoveries worth billions,” says Kashyap.

5: An AI-native app with an AI-native interface

To Tomasz Tunguz, General Partner at Theory Ventures, one of the missing pieces in AI right now is fundamentally aesthetic. “I don’t think we’ve really seen a native app yet,” he says. “I don’t know if we know what that looks like yet. Aside from ChatGPT, which looks like a text message from a mobile phone, we haven’t really seen an app where the UX is completely different. We’re in a phase of ‘let’s add AI here,’ let’s slap on a chatbot.”

6: AI to make invoicing less terrible

Most B2B goods companies are still doing payments via check*, says Headline partner King Goh. “B2B business owners spend a lot of time sending manual invoices, chasing payments, reconciling the checks, and then dealing with late payments,” he says. “In fact, 55% of payments are late.”

Only in America!

7: AI to help mom-and-pop business better understand customers

Another B2B idea from Goh: Most B2B businesses outside professional services, especially small businesses, don’t have a CRM, so they “don’t know anything about their customers beyond hearsay/word-of-mouth, let alone grow their business using technology … imagine a world where a mom-and-pop manufacturing company uses AI software that knows all the safe but relevant information about their customer … so the mom-and-pop business can finally grow?”

8: Data is everything

If it’s got lots of data –– important data dispersed across a number of different systems –– Ken Elefant, Sorenson Capital partner, might be interested. He’s been looking for startups in industries like “security, especially in the data centre”.

9: AI for AI

AI also needs AI. It seems like a joke but in the right application, for example, AI could help make other AI cheaper. “The type of startup within the AI space that I think is going to be really important for the future of AI is the kind that makes AI way more efficient,” says Biegala, of Bison Ventures. “That means computationally efficient, that means power efficient, that means lower greenhouse gas emissions, and this could be on both the software side and the hardware side.”

Finally, according to Allie, there’s one thing they heard loud and clear, and it was this: no one wanted to see another LLM.

Read the full article over here (if you’re a subscriber).

 

* in America

 

Postscript: The respected American Brookings Institute just produced an interesting report about the responsible use of AI in finance. The report concludes with five detailed recommendations to the regulator (the CFTC). The proposals urge the Commission to leverage its convening power around a roundtable discussion of registered entities who might consider the adoption and use of the AI risk management framework advanced by the National Institute of Standards and Technology (NIST). The report also proposes that the Commission perform legal gap analysis for autonomous AI systems, align AI policies with other agencies like the U.S. Securities and Exchange Commission (SEC), and engage staff in domestic and international dialogues around appropriate use of AI models in autonomous financial systems.