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Gen AI And LLMs Will Transform The Enterprise

Snowflake's Mona Attariyan, Director of Engineering, leads this conversation with Snowflake's Sunny Bedi, CIO and CDO, and Jennifer Belissent, Principal Data Strategist, about the impact Gen AI and LLMs will have on enterprises. Topics covered range from the impact on employee productivity, the personalization of the customer experience, the opportunities for data monetization. and more.

Gen AI And LLMs Will Change Our Lives Profoundly

How will Gen AI and LLMs impact the nature of people's jobs and worker productivity? "Data Cloud Now" anchor Ryan Green kicked off the Data and AI Predictions 2024 event in January by discussing that topic with Snowflake's CEO Sridhar Ramaswamy and Mona Attariyan, Director of Engineering. The conversation also covers the potential for AI to generate misinformation and the need to establish ethical guardrails for the technology.

Enhancing Software Testing with Large Language Models: Navigating the Challenge of Hallucinations

Software testing is an indispensable stage in the software development lifecycle, tasked with verifying application reliability, security, and performance before deployment. This process evaluates software components to ensure they adhere to specified requirements and perform reliably under varied conditions.

Emerging Tech Trends: Navigating the Most In-Demand Technical Careers for 2024

As we step into 2024, the tech industry continues to be a whirlwind of innovation and growth. With every passing year, technology reshapes not just how we live our daily lives but also the very fabric of our career landscapes. This year, certain tech roles are standing out, fueled by advancements in AI, cybersecurity, and cloud computing.

How to Automate Data Extraction from Patient Registration Forms in Healthcare

Automating data extraction from patient registration forms in healthcare is crucial to enhancing patient care efficiency, accuracy, and overall quality. Over 71% of surveyed clinicians in the USA agreed that the volume of patient data available to them is overwhelming. This abundance of data highlights the importance of streamlining the extraction process. Manual extraction is time-consuming and prone to errors, hindering patient safety.