Baidu releases new AI offerings on the way to broader commercialization of the technology
Baidu has introduced a text-to-image generator dubbed I-RAG and a no-code developer platform called Miaoda as part of its growing portfolio of artificial intelligence (AI) products that, like US-based AI companies, it eventually aims to offer its user base as part of a wide array of commercial AI offerings.
CEO Robin Li introduced the new technology in a presentation at the company’s Baidu World Conference Tuesday. I-RAG uses Baidu’s search capabilities to generate images from speech and has been designed to address the “hallucinations” issue, according to a report on Reuters. The hallucinations referred to are images generated via large language model (LLM)-based AI that deviate from what was specified in the input prompt or contain non-existent elements.
Baidu also launched Miaoda, a developer platform that uses the capabilities of LLMs to generate code, and is aimed at allowing users without extensive coding expertise to develop applications. AI companies in the US also are providing similar tools to develop applications through a visual interface, with reusable components and advanced developer assistance, noted Manukrishnan SR, practice director for Everest Group.
Indeed, like those of leading US companies such as OpenAI, Google, and Microsoft, Baidu’s AI moves demonstrate its march toward the commercialization phase of the technology. The company, like others before it, has been adding AI to existing products or creating new ones that enterprise and other business users can integrate into their applications.
Follow the leader
Google, OpenAI, and Microsoft already have products similar to the ones Baidu revealed Tuesday, and the Chinese company has some catching up to do, analysts noted. The release of an AI-enhanced no-code platform in particular demonstrates Baidu’s aim to keep up with a software development trend that may one day leverage AI to replace traditional coding with software configuration.
“The pace of innovation and research in generative AI technologies and software is moving at a breakneck pace in the US,” Dave Schubmehl, research VP, AI & automation at IDC, observed. “To compete effectively on the world stage, other countries will need to adopt this same pace of innovation and research.”
He added, “many vendors are offering low code/no code/code generation capabilities in their products. Baidu’s product Miaoda is doing what other vendors like Microsoft and OpenAI have already done, which is using LLM capabilities to generate code.”
So far, however, Baidu’s AI tools do not seem to be as advanced as the ones released by OpenAI, Microsoft, and Google, Everest Group’s SR told CIO, “since these players have large existing datasets on which they can train their AI models.”
However, with “all major cloud platform players now offering some form of genAI-based programming augmentation facility,” AI-based software development may be the way forward for the enterprise, noted Bradley Shimmin, chief analyst, AI and data analytics, at Omdia.
“This is a very important area of research in that it points to an eventual state where both domain experts inside an organization and professional ISV practitioners can both use the same tooling to create full-stack apps and/or workflow automations in a declarative, no-code, conversational manner,” Shimmin said.
Still, this evolution is not without its challenges, and may not be something CIOs need to worry about quite yet, Everest Group’s SR noted.
“These tools are facing a host of challenges, including maintaining code quality, adherence to regulatory standards, and questions on ROI,” he told CIO. “Thus, while AI is set to revolutionize software development in the medium to long term, there are a lot of challenges that need to be ironed out before its potential can be fully realized.”
Don’t underestimate China
Though Baidu is still playing catch-up to US-based companies, China as a major global AI player should not be underestimated, Shimmins noted. In fact, “China and the US are really not that far apart from one another in terms of expertise and investment [in AI],” he observed.
“Already, China has produced some very strong models, particularly open source models such as Qwen2.5-Coder, which rivals some of the larger frontier models from Anthropic and OpenAI (at least in terms of published benchmarks),” he said.
The US has been doing everything it can to stymie overall technological development in China in various ways, and AI is no exception. A mere two weeks ago, the US government announced new rules restricting investments in China’s AI and other tech sectors deemed threats to national security, expanding existing technology restrictions that were so far limited to exports. China, for its part, has banned the use of OpenAI in the country.
However, despite the current friction between the US and China in terms of their technological arms race, the two countries have similar goals when it comes to AI, and may end up collaborating in some areas, Shimmin noted.
“In terms of academic research, the two nations are starting to work more closely with one another in seeking out a common ground concerning the existential threat posed by AI itself,” he said.
Source:: Computer World
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