Technology

The unsexy future of generative AI is corporate apps

However, this amount includes massive funding from corporate backers, such as Microsoft’s capital injection into OpenAI and Amazon’s funding of Anthropic. Reduced to traditional VC investments, funding for AI startups in 2023 was much lower and slow to reach the total amount raised in 2021.

PitchBook senior analyst Brendan Burke noted in a report that venture capital funding is increasingly being directed toward “the underlying core AI technologies and their ultimate vertical applications rather than general-purpose middleware for audio, voice, images and video.”

In other words, a GenAI app that helps a company generate e-commerce sales, analyze legal documents, or maintain SOC2 compliance is likely a safer choice than one that sends a clever video or photo every now and then drummed together.

Clay Bavor, co-founder of Sierra, believes it’s not necessarily the cost of computing or cloud APIs that’s driving AI startups to B2B models, but rather the benefits of targeting and targeting a specific customer Develop a product based on his feedback. “I think everyone, myself included, is pretty optimistic that the capabilities of these AI models will increase and at the same time the costs will decrease,” says Bavor.

“There’s just something really powerful about solving a clear problem for a specific customer,” he says. “And then you can get feedback: ‘Is this working?’ Is this the solution to a problem?’ And if you build a business with it, it’s very powerful.”

Although ChatGPT sparked an AI boom in part because it can quickly generate code one second and sonnets the next, Arvind Jain, CEO of AI startup Glean, says the nature of the technology still favors narrow tools. On average, a large company uses more than a thousand different technical systems to store corporate data and information, he says, which creates an opportunity for many smaller companies to sell their technology to these corporations.

“We’re in a world where there’s essentially a set of functional tools, each one meeting a very specific need. This is the way of the future,” says Jain, who has worked on search at Google for more than a decade. Glean operates a search engine in the workplace by integrating with various corporate apps. The company was founded in 2019 and has raised over $200 million in venture capital funding from Kleiner Perkins, Sequoia Capital, Coatue and others.

Error checking

Optimizing a generative AI product for business customers comes with challenges. The errors and “hallucinations” of systems like ChatGPT can have more serious consequences in a corporate, legal or medical environment. Selling genetic AI tools to other companies also means meeting their privacy and security standards, and potentially the legal and regulatory requirements of their industry.

“It’s one thing for ChatGPT or Midjourney to get creative for an end user,” says Bavor. “It’s a whole different thing for AI to get creative in the context of business applications.”

Bavor said Sierra has put “tremendous effort” into establishing safeguards and parameters so the company can meet security and compliance standards. This includes using…more AI to optimize Sierra’s AI. If you use an AI model that generates correct answers 90 percent of the time, but then build in additional technology that can detect and correct some of the errors, you can achieve a much higher level of accuracy, he explains.

“You really need to prepare your AI systems for enterprise use cases,” says Jain, the CEO of Glean. “Imagine a nurse in a hospital system using AI to make decisions about patient care – you just can’t be wrong.”

A less foreseeable threat to smaller AI companies selling their wares to enterprise customers: What if a giant generational AI unicorn like OpenAI, with its growing sales team, decides to launch the very tool that a single startup developed?

Many of the AI ​​startups WIRED spoke to are trying to move away from dependence on OpenAI’s technology by using alternatives like Anthropic’s Claude or open source models for large languages Meta’s Llama 3. Some startups even plan to build their own AI technology at some point. But many AI entrepreneurs will have to pay for access to OpenAI’s technology while potentially competing with it in the future.

Tome’s Peiris thought about the question and then said that he now focuses exclusively on sales and marketing use cases and is “amazing at generating high-quality products for these people.”

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