Small and medium-sized businesses will struggle to keep up with tech giants like OpenAI in developing their own artificial intelligence (AI) models, according to a new report from Stanford University.
In the interview, Nestor MasleyThe editor-in-chief of Stanford University's new 2024 AI Index report highlighted findings about the growing AI gap between large and small companies. While a huge technology company, Pour billions into AI research and developmentsmall businesses lack the resources and talent to compete head-on.
“You can't train a frontier foundation model that can compete with the likes of GPT-4, Gemini, Claude, etc. for a small or medium-sized company,” Masley said. “But there are also some pretty capable open source models that are freely accessible, such as Llama 2 and Mistral. A lot can be done with these kinds of open source models, and they are likely to continue to improve over time. Yes, in a few years we may see an open, relatively low-parameter model that works the same way GPT-4 does today.
a Learn from PYMNTS We highlighted last year that generative AI technologies such as OpenAI's ChatGPT have the potential to significantly improve productivity, but also risk disrupting employment patterns.
Rising costs of AI
The main takeaway from this report is that there can be a disconnect between AI benchmarks and actual real-world business requirements.
“For me, the point is not to improve the models for these tasks, but to ask whether the benchmarks we have are good enough to assess the business utility of these systems. Yes,” Masley said. “Current benchmarks may not be well-aligned with a company's real-world needs.”
Although private investment in AI declined overall last year, funding for generative AI increased dramatically, increasing almost eightfold to $25.2 billion from 2022, according to the report. Major companies in the generative AI industry, including OpenAI, Anthropic, Hugging Face, and Inflection, reported significant increases in fundraising activity.
Maslej emphasized that while AI implementation costs a lot of money, it is overshadowed by the costs associated with training the systems.
“Deployment is not a cost issue because the real cost is in training the system. Most companies do not have to worry about training their own models and instead rely on open source or relatively inexpensively accessible APIs. You can adopt an existing model that is freely available through ,” he explained.
Driving standards for AI
The report also calls for standardized benchmarks in responsible AI development. Masrezi envisions a future where common benchmarks allow companies to easily compare and select AI models that meet ethical standards. “Standardization makes it easier for companies to see with more confidence how different AI models compare to each other,” he said.
Balancing profits and ethical concerns has emerged as a key challenge. The report shows that while many companies are concerned about issues such as privacy and data governance, fewer are taking concrete steps to mitigate these risks. “The more pressing question is whether companies are actually taking steps to address some of these concerns,” Masley said.
Measuring the impact of AI on worker productivity across industries remains complex. “It's possible to measure productivity in different industries. But it's more difficult to compare productivity gains across industries,” Masley said.
Looking to the future, this report highlights the need for businesses to navigate an increasingly complex regulatory environment.On Tuesday, Utah Sen. Mitt Romney and several other senators announced the plan To protect against the potential dangers of AI. These include threats in the biological, chemical, cyber, and nuclear fields due to increased federal regulation of advanced technology development.
Mr. Masrei stressed the importance of remaining vigilant. “This problem will be difficult to resolve. Regulatory standards for AI are not yet clear.”
As public awareness of AI increases, Masrej believes companies will need to address concerns about turnover and data privacy. “As people become more aware of AI, how can companies proactively address concerns, especially around turnover and data privacy?” he posed as an important question for the industry to consider.
The 2024 AI Index Report aims to guide businesses and society to navigate the rapid advances in artificial intelligence. Masrezi concluded, “The AI landscape is evolving at an unprecedented pace, presenting both immense opportunities and daunting challenges.”
