Could AI-generated ‘synthetic data’ be about to take off in the security space?https://totalsecuritysummit.co.uk/wp-content/uploads/2023/07/crowd-pedestrians-400811_1280.jpg 960 640 Stuart O'Brien Stuart O'Brien https://secure.gravatar.com/avatar/9defd7b64b55280442ad2d7fb546a9db?s=96&d=mm&r=g
Synthetic data startups are spearheading a revolution in artificial intelligence (AI) by redefining the landscape of data generation that will have implications for myriad industries, including security.
That’s according to GlobalData, which says substantial venture capital investments and a clear sense of direction, these startups are transforming industries, overcoming data limitations, and propelling AI innovation to new heights,
Kiran Raj, Practice Head of Disruptive Tech at GlobalData, said: “Synthetic data startups are breaking through the shackles of data quality and regulation, becoming the trusty substitutes for AI training. As the demand for reliable, cost-effective, time-efficient, and privacy-preserving data continues to accelerate, startups envision a future powered by synthetic data, ushering a new era of machine learning progress. The continuous exploration and innovation in this space promise exciting opportunities and transformative impact on AI development in the years to come.”
Shagun Sachdeva, Project Manager of Disruptive Tech at GlobalData, added: “The bullish investment landscape, expanding use cases across industries, and the ongoing AI advancements flowing to downstream tasks signify that we are merely scratching the surface of what synthetic data can truly achieve. Ranging from financial services and healthcare to automotive and retail sectors, GlobalData expects more remarkable innovations and transformative impacts across industries in the realms of synthetic data, which bodes well for the startups working in the space.”
GlobalData’s Innovation Radar report, Startup Series – Synthetic Data – The Master Key to AI’s Future, highlights the dynamic application landscape of synthetic data by startups across sectors.
Synthetic data in healthcare enables privacy-preserving research, improves AI model training by augmenting real patient data, and supports simulation and training for medical professionals. It also aids in drug discovery, clinical trials, and optimizing healthcare systems for enhanced patient care. Aindo, Betterdata, and Gretel are some of the synthetic data startups addressing the needs of healthcare sector.
Synthetic data offers significant advantages in financial services, including fraud detection, customer analytics, regulatory compliance, portfolio management, cybersecurity, and chatbot training. By harnessing the power of synthetic data, financial institutions can enhance operational efficiency, mitigate risks, personalize services, and drive innovation in a privacy-conscious manner. Clearbox, Hazy, and Diveplane are some of the synthetic data startups that offer solutions for financial service sector.
Synthetic data plays a vital role in the automotive sector, particularly in autonomous vehicle development, virtual testing, driver assistance systems, design optimization, HMI development, and traffic simulation. By leveraging synthetic data, automotive companies can accelerate innovation, improve safety, optimize manufacturing processes, and enhance the overall driving experience. Rendered AI, Anyverse, and Sky Engine AI are some of the synthetic data startups catering the needs of automotive sector.
Synthetic data in the retail sector enables accurate demand forecasting, personalized marketing, optimized pricing, improved store layouts, fraud detection, and enhanced customer service. By leveraging synthetic data, retailers can make data-driven decisions, enhance customer experiences, and optimize operations for business growth. Betterdata, Zumo Labs, and Synthesis AI are some of the synthetic data startups that offer solutions for retail sector.
It’s not difficult to see how applications of the above in the security space could have a significant impact, not just in terms of data security, but also in planning crowd control scenarios or training.
Sachdeva concluded: “Despite the considerable attention and substantial investment in synthetic data, user skepticism, dependency on real data, and lack of standards, trust and awareness can hinder the acceptance. As we closely monitor this evolving landscape, it will be interesting to watch startups within synthetic data space addressing these challenges and offering solutions that will mold the future trajectory of AI.”