A Brief Overview of the Strengths and Weaknesses Artificial Intelligence 

In this contributed article, editorial consultant Jelani Harper suggests that since there are strengths and challenges for each form of AI, prudent organizations will combine these approaches for the most effective results. Certain solutions in this space combine vector databases and applications of LLMs alongside knowledge graph environs, which are ideal for employing Graph Neural Networks and other forms of advanced machine learning.

Harnessing the Capabilities of Gen AI for Unprecedented Impact and Effortless Integration

In this contributed article, Ajay Kumar, CEO at SLK Software, discusses how generative AI provides unprecedented impact and effortless integration for the banking, insurance, and manufacturing industries. Ajay elaborates on why you need an adoption framework to successfully implement generative AI, how different categories of generative AI fit into an enterprise adoption framework, and navigating stakeholder challenges of adopting generative AI

Veritas Survey Finds Workers are Putting Businesses at Risk by Oversharing with GenAI Tools

Our friends over at Veritas just released a new survey revealing that workers are oversharing with generative AI tools, putting businesses at risk. Nearly a third (31%) of global office workers admitted to inputting potentially sensitive information into generative AI tools, such as customer details or employee financials.

Survey: 1 in 3 People are Using AI to Save their Love Lives

To find out exactly how people feel about AI influencing their dating journey, our friends over at Top10.com recently surveyed over one thousand adults about the idea. The results might surprise you!

Scaling Data Quality with Computer Vision on Spatial Data

In this contributed article, editorial consultant Jelani Harper discusses a number of hot topics today: computer vision, data quality, and spatial data. Computer vision is an extremely viable facet of advanced machine learning for the enterprise. Its utility for data quality is evinced from some high profile use cases. This technology can produce similar boons for other facets of the ever-shifting data ecosystem.

Navigating the AI Landscape in 2024: Prioritizing Ground-Truth Data, Developer Enablement, and Consumer Privacy

In this contributed article, Jason Hudak, SVP of Engineering at Foursquare, explores four pivotal aspects shaping the AI landscape: the imperative role of quality ground-truth data, the proliferation of developer enablement, the renewed focus on consumer privacy in the midst of an election year, and the role LLM’s and NLP’s will play in data democratization.

Sony AI Big Data Industry Predictions for 2024

Our friends over at Sony AI have prepared a special set of compelling technology predictions for the year ahead. The Sony AI team is comprised of researchers and leaders with backgrounds in deep reinforcement learning, data science, law, privacy and security, and more. They each offer different perspectives on topics related to AI ethics and policy, the use of AI to augment creativity and scientific research, emerging AI training methods, and more. From the company’s point of view 2024 should be quite a year! Enjoy these special perspectives from one of our industry’s best known movers and shakers.

AI Companies and Applications have a lot to Prove in 2024

In this contributed article, Saad Siddiqui, General Partner at Telstra Ventures, indicates that while there are plenty of risks for VCs in AI right now, they’re overwhelmingly outweighed by the potential benefits. As AI adoption continues to gain momentum, the task in 2024 will be making strategic investments in companies and applications capable of maximizing the value of the most revolutionary technology in the world.

Generative AI Report – 1/30/2024

Welcome to the Generative AI Report round-up feature here on insideBIGDATA with a special focus on all the new applications and integrations tied to generative AI technologies. We’ve been receiving so many cool news items relating to applications and deployments centered on large language models (LLMs), we thought it would be a timely service for readers to start a new channel along these lines. The combination of a LLM, fine tuned on proprietary data equals an AI application, and this is what these innovative companies are creating. The field of AI is accelerating at such fast rate, we want to help our loyal global audience keep pace.

Optimizing Performance and Cost Savings for Elastic on Pure Storage

[SPONSORED POST] Organizations can now confidently embrace Elastic, enhance their hot tier storage, and seamlessly manage historical data with cost-efficient capacity-optimized storage. Pure Storage not only meets the demands of the modern data landscape but also empowers organizations to simplify their Elastic architecture, reflecting the industry trend towards a more streamlined and efficient approach.