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Ruholamin Haqshanas
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Ruholamin Haqshanas
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IBM has unveiled its new “Lightweight Engine” for the WatsonX.ai platform, marking a major step in the evolution of artificial intelligence (AI) deployment for businesses.
While IBM primarily targets large enterprises, the innovation could prove to be a game-changer for small to mid-sized companies, particularly in rapidly growing sectors like fintech.
Rise of Generative AI Drives Tech’s Expansion
The rise of generative AI has been a driving force in the tech industry’s expansion, with the first half of 2024 seeing substantial revenue growth attributed to this sector.
A decade ago, few could have anticipated the impact that large language models (LLMs) like OpenAI’s ChatGPT and Anthropic’s Claude would have on the market.
These models have not only revolutionized AI but also created a burgeoning industry centered around their capabilities.
However, the journey of AI in financial services has been complex.
Before the release of ChatGPT, the consensus among AI and finance experts was that models like GPT-3 were too unreliable for use in fields where precision is critical.
Despite significant advancements since then, the challenge remains: AI models designed for general use, based on public data, often lack the accuracy needed in industries like finance, where there is little room for error.
The solution lies in specialization.
For instance, JPMorgan Chase’s recent acquisition of enterprise access to OpenAI’s ChatGPT highlights the growing adoption of AI in financial services.
By fine-tuning the model on internal data and incorporating custom safeguards, JPMorgan is able to harness the power of generative AI while mitigating the risks associated with general-use models.
The move underscores the financial sector’s confidence in generative AI, provided the technology is tailored to their specific needs.
But generative AI’s potential goes far beyond chatbots. Most popular AI platforms, including ChatGPT, offer enterprise-level solutions, yet they remain predominantly cloud-based.
Cloud-Based AI Solutions Pose Challenges
For industries like fintech, where data security is paramount, cloud-based AI solutions can pose challenges.
Regulatory and fiduciary requirements often necessitate that sensitive data be protected from external threats, making purely cloud-based solutions less viable.
IBM’s WatsonX.ai addresses this concern by offering both cloud-based and on-premises solutions.
The introduction of the Lightweight Engine further enhances this flexibility, allowing businesses to deploy and run AI models on-site with minimal resource usage.
This is particularly appealing to industries like fintech, blockchain, and crypto-lending, where off-site AI solutions may not fully meet security requirements.
“As businesses add on-premises, they want the lightest weight platform for the enterprise to deploy and run their generative AI use cases, so they are not wasting CPUs or GPUs,” Savio Rodrigues, IBM’s vice president of ecosystem engineering and developer advocacy, said.
“This is where watsonx.ai lightweight engine comes in, enabling ISVs and developers to scale enterprise GenAI solutions while optimizing costs.”
While IBM’s Lightweight Engine presents a compelling solution, it faces stiff competition from tech giants like Microsoft, Google, and Amazon, as well as specialized startups offering similar services.
Although a detailed comparison of these services is beyond this discussion, IBM’s new engine stands out for its reduced footprint and enhanced efficiency, even if it does sacrifice some features available in its more robust counterparts.
