Tech executives looking to get the most value from generative AI for their organizations need to understand the fundamentals of the technology, according to a Forrester Research report released Tuesday.
“While the tech world has been disappointed by several recent bubbles that promise a lot but haven’t delivered real value, generative AI is already making a difference in enterprise content creation, software development, and knowledge management. are improving,” the report notes.
“But hype breeds bad information and misunderstandings,” he continued. “Technical executives need to know some basics, such as what generative AI is, how it can be used, what the future holds for generative AI, and what to do in the short term.”
To understand what generative AI is, tech executives need to dispel some misconceptions about the technology.
“It may sound mundane, but the biggest misconception I run into over and over is that generative AI and ChatGPT are not the same thing,” said Forrester analyst and one of the report’s authors. Rowan Karan says.
“When executives look at these things, it’s important to see them as broader technologies that have captured our imagination through chatbot interfaces,” he told TechNewsWorld.
“ChatGPT is an application wrapped in the GPT-4 or GPT 3.5 turbo model,” he said. “Technical executives need to look at models in addition to applications.”
not as smart as i thought
Generative AI is a language model at scale, meaning it has all the capabilities associated with language, explained the Palo Alto, Calif.-based maker of the Process Experience Platform, which includes AI-enabled capabilities. Sagi Eliyahu, co-founder and CEO of Tonkean. .
“We humans communicate and think in words, so LLM now seems like it can do anything,” he told TechNewsWorld.
“But even though they appear to be able to ‘think,’ language models are ultimately constrained by the data they are trained on,” he said. “Like any technology, its usefulness is only determined by how you apply it to the existing culture.”
Daniel Castro, director of the Center for Data Innovation, an international think tank that studies the intersection of data, technology and public policy, adds:
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“People shouldn’t rely on it as a substitute for facts and human expertise,” he told TechNewsWorld. “Instead, it should be used as a tool for generating ideas and augmenting human skills. Generative AI has many important use cases, but it is still far from artificial general intelligence.”
Misinterpreting generative AI as artificial general intelligence — a type of AI that can perform any intelligent task that a human could — is another misconception, said the president and president of the Enderle Group, an advisory services firm in Bend, Oregon. Principal analyst Rob Enderle argues.
“AGI is still a few years away,” he told TechNewsWorld.
“Generative AI is a big language model that can talk to you,” he said. “This is the beginning of a new user interface based on voice and appearance that is more human-like by design.”
Wide range of use cases
The use of “chat” in generative AI like ChatGPT can also confuse AI-savvy executives. Mark N. Vena, president and principal his analyst at SmartTech Research in San Jose, California, said:
“These chatbots are not generational AI-based, as they generally derive responses from a finite universe of topic-specific general questions,” he told TechNewsWorld. “Gen AI is, in theory, curating material for all content on the internet, so it is much more real-time in terms of relevant content and can respond to a huge number of queries.”
While acknowledging that generative AI is still relatively immature, Forrester noted that tech executives can take advantage of a variety of use cases, including:
- Improved developer productivity with text-to-code generation tools.
- Empower visual designers to quickly iterate and ideate with a text-to-image generator.
- Empower marketers to create product descriptions that match their preferred brand language and tone.and
- Expand your executive presence by allowing a synthetic avatar of yourself to appear on video without having to record yourself.
“One of the most underrated aspects of generative AI is its ability to enable more people to create software than ever before,” said founder of Technalysis Research, a technology market research and consulting firm in Foster City. said Bob O’Donnell, Investor and Chief Analyst. , California.
“There have been no-code, low-code development tools available for years, but they still have to be very technical to make them work,” he told TechNewsWorld.
“One of the interesting applications of generative AI is the ability to create code from description,” he continued. “What this means is that if you have an idea, you can do a lot of interesting things without programming expertise.
From excitement to magic
Forrester says that generative AI is exciting today, but tomorrow’s applications will seem magical.
For example, future analytics platforms with built-in generative AI capabilities might allow users to submit queries such as: quarterly report”.
“AI is now enabling end users to make the leap from research to something much more useful: solutions,” said Eliyahu.
“And not any kind of solution, but a differentiated, agile, personalized, context-aware solution,” he continued. “At the end of the day, that’s what people really want and need from technology: tools that understand their needs, their questions, their problems, and solve them quickly.”
Forrester acknowledges that problems have plagued generative AI. Text generators can not only produce consistent nonsense, but can recreate harmful biases baked into the data. Questions about copyright and intellectual property are also unanswered.
Will Duffield, a policy analyst at the Cato Institute, a Washington, DC think tank, said: .
“There is always the risk of trying to overfit new technology to solve a problem that is not yet ready to be solved,” he told TechNewsWorld.
Seek Gen AI Vendor Input
Nonetheless, Forrester encourages tech executives to try generative AI in the next six to nine months.
“It’s very important that organizations start experimenting in this area and work with their vendor partners to understand what they’re doing,” Curran advised. “Most vendors have something on their roadmap for how they deliver generative AI capabilities.”
He also recommended that tech executives look broadly at the vendor landscape. “It’s a lot bigger than some of the players who have been in the spotlight in the last few months,” he said.
