AI and data management solutions were at the forefront of GITEX 2024, as companies like Yash Technologies and Cloudera showcased their latest advancements. With AI adoption growing across industries, concerns about scalability, security, and workforce implications were key talking points at this year’s event.
AI Adoption Offers Cautious Optimism Amid Advancements
Yash Technologies, a global player in system integration, highlighted its role in helping companies navigate AI’s expanding footprint. Speaking at GITEX, Nitin Gupta, Global Head of Digital & Infrastructure Management Services at Yash Technologies, pointed out that while AI is gaining traction, some firms remain cautious.
“There is still apprehension in terms of how accurate AI will be,” Gupta said, referencing ongoing concerns about the reliability of AI models. However, Gupta noted that AI, particularly in conversational systems and computer vision analytics, is starting to show more promising results. “You will see a lot of use cases around customer behavior, sales analysis, and defect detection, where predictivity will become more accurate,” he added.
Despite concerns about AI making certain jobs redundant, Gupta suggested that AI could ultimately drive workforce upskilling rather than job losses. “It’s the same fear people had when computers first entered the market, but as they learned new skills, productivity improved. AI will likely follow a similar path,” he said.
Data Security at the Forefront
With the rise of generative AI, concerns around data security have also emerged, especially for enterprises using large language models (LLMs) in sensitive industries like finance and retail. Gupta stressed Yash Technologies’ focus on secure implementations, noting the importance of “private GPT” setups that keep enterprise data isolated. “We always ensure the security of data,” Gupta said, explaining that Yash follows strict GDPR and PCI DSS guidelines to protect sensitive information.
Cloudera Pushes AI Accelerators for Rapid Adoption
Meanwhile, Tariq Salameh, Manager Solution Engineer at Cloudera, underscored the importance of data platforms in AI integration. Cloudera’s primary focus is on enabling businesses to scale their AI capabilities without starting from scratch.
“Cloudera has invested over $1 billion in the AI and data architecture space in the last two years,” Salameh said, emphasizing the need for flexible, hybrid platforms that cater to both cloud and on-premise data management. He explained that Cloudera’s AI accelerators—pre-built machine learning prototypes—are designed to fast-track AI adoption across sectors like telecom, financial services, and government.
Cloudera continues to define a future where data drives business excellence. In its latest Industry 4.0 series, @CBS features our pivotal role in the data and AI sectors and shines a light on our commitment to driving enterprise success for customers: https://t.co/uWIGfIC5g9
— Cloudera (@cloudera) August 28, 2024
Salameh described use cases that range from predictive maintenance in engineering to AI-powered hiring systems for HR departments. “We’ve seen companies in oil and gas, financial services, and other industries using AI hiring models to match CVs with specific project needs,” he said.
However, he warned that AI models must be continuously monitored and retrained to maintain performance over time. “Model performance can degrade, so you need to watch for any drift and retrain models accordingly. We offer continuous integration solutions to automate that process,” he said.
Balancing AI Innovation with Sustainability Concerns
As the deployment of AI models expands, so too does the infrastructure needed to support them, raising sustainability issues. Data centers, which power AI models, are known for their high energy consumption. Azar addressed this, highlighting Cloudera’s innovations in data storage and processing efficiency.
“We’ve managed to store 400 terabytes per unit, up from 100 terabytes, while cutting the need for energy-intensive infrastructure,” he explained. Partnering with Nvidia, Cloudera has also optimized computation power, reducing processing times by up to 20 times, which helps mitigate the environmental impact.
