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To solve the problem, the company turned to gen AI and decided to use both commercial and opensource models. Both types of gen AI have their benefits, says Ken Ringdahl, the companys CTO. So we augment with opensource, he says. Right now, the company is using the French-built Mistral opensource model.
While organizations continue to discover the powerful applications of generativeAI , adoption is often slowed down by team silos and bespoke workflows. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generativeAI lifecycle.
2023 has been a break-out year for generativeAI technology, as tools such as ChatGPT graduated from lab curiosity to household name. But CIOs are cautiously evaluating how to safely deploy generativeAI in the enterprise, and what guard-rails to put around it.
GenerativeAI has seen faster and more widespread adoption than any other technology today, with many companies already seeing ROI and scaling up use cases into wide adoption. Vendors are adding gen AI across the board to enterprise software products, and AI developers havent been idle this year either.
Other respondents said they aren’t using any generativeAI models, are building their own, or are using an open-source alternative. Synthetic media, which includes AI-generated text, images, audio, and video, grew by 222% compared to the previous year. And the AI writing assistant category grew by 177%.
The overhype of generativeAI was unavoidable last year, yet despite all the distraction, unproven benefits, and potential pitfalls, Dana-Farber Cancer Institute CIO Naomi Lenane didn’t want to ban the technology outright. But allowing free, unfettered use of the public gen AI platforms was not an option.
GenerativeAI touches every aspect of the enterprise, and every aspect of society,” says Bret Greenstein, partner and leader of the gen AI go-to-market strategy at PricewaterhouseCoopers. In a recent report, he estimated that gen AI software revenues will grow from $3.7 billion this year to $36 billion by 2028.
Even though large companies have been working with machine learning for quite some time now, their models aren’t as sophisticated as the larger open-source models, says Sundberg. “You need something that’s smaller and trained on more domain-specific data, which is more accurate at answering questions in your domain than using GPT-4.”
Result: Though the full scope remains unclear, the breach affected almost all Okta customers and highlighted the potential risks associated with third-party vendorsmanaging sensitive data. Only 11% of opensource projects are actively maintained. 300+ AI-powered GitHub Actions in the marketplace.
Even with opensource models, not all of them make this information public. So far, there isn’t a good automated way to do this, or an open-source LLM designed specifically to test the alignment of other models, but there’s definitely a crucial need for it.
The AI agent will download it, try to build it, and if it doesnt run, itll fix the build scripts and code if necessary, check the code back into the repository, and flag it was done by an AI agent, he says. According to the KPMG report, administrative duties were the main use case for AI agents, cited by 60% of respondents.
But even as CIOs familiarize themselves with initiatives such as generativeAI pilots , moving to cloud-first , DevOps, and product and services development, there is still much for them to learn, and tech vendor CTOs steeped in these projects and modes of operation are happy to impart a wealth of knowledge. “It
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