Artificial Intelligence (AI) is being applied to more and more applications across industries, in everything from multiphysics product simulation to medical diagnosis tools. With the increase in edge computing and the exponential growth of IoT engineers, researchers, academics, and consumers are asking what is next for AI?
In this article, we look at the current trends and challenges in the sector and give an overview of the Future.Industry event sponsored by Altair coming up from the 4-6 of October.
The intersection of AI edge computing will have a massive impact on the way we perceive, access, learn from, and employ data across a wide range of industries. Edge computing shifts data processing and storage closer to where the data is created. This narrowing of the gap enables much faster access to insights - critical for applications where low latency, privacy, and cost-effective movement of data is essential such as autonomous vehicles and critical medical care.
Despite the massive advances, scaling AI at the edge remains a challenge, with many deployments stuck in the pilot phase. Creating effective ways to scale edge projects will be the key to moving closer to true industry 4.0, level 5 autonomy, and highly secure IoT.
Digital twins had been a buzzword for some time but are now fast becoming an essential part of companies, cities, industries, and more’s efforts to address sustainability. A digital twin is a virtual copy of a product or system that enables user to test and monitor. A digital twin might be used when testing a complex physical object such as a satellite or monitoring air quality inside a multi-level structure. Digital twins require a mix of physical simulation methods, data analytics, and machine learning techniques to create models that provide clear value.
Well-thought-out digital twins not only capture, organize and display data to give a realistic model of the physical world which can inform and quantify current events as well as combine multiple data sources to see the impact of decisions we’ve made. Digital twins can also be used as a predictive guide to the future. Using digital twins to compare possible scenarios and forecast the outcome of different decisions before they’re taken, we can test and model to ensure the most sustainable outcome.
Artificial intelligence provides many proven benefits but along with those benefits comes its own set of challenges as well. Datasets and algorithms can reflect or reinforce gender, racial or ideological biases. When the datasets (fed by humans) that AI rely on are incomplete or biased, they may lead to biased AI conclusions. While many independent foundations and watchdogs are bringing AI bias to attention. More must be done within the industry to ensure diversity is centered from the beginning of projects and not a hasty afterthought.
While AI has proven irreplaceable in some legal settings, such as fighting parking fines. It is also being used as a tool for judges in the US to predict whether a person will commit a crime. The software known as risk assessment instruments (RAIs) are used by judges when deciding if a person should be detained or released during their bail period. Research has shown that the risk score produced by the software appeared to favor white defendants over Black defendants by under-predicting recidivism for white and over-predicting recidivism for Black defendants.
The future development and application of Artificial Intelligence will require a comprehensive ecosystem of hardware, software development, ethicists, and researchers. AI is already demonstrating its ability to assist in reducing the carbon footprint of the design cycle and provide valuable data insights. Its future, particularly making the technology fair, open and accessible, is everyone’s responsibility.
Technology company Altair will host the event, Future.Industry on from October 4th through the 6th bringing together the engineering community to think together about the future of AI.
Over three days, industry leaders and Altair experts will present keynotes, panel discussions, and workshops centered on the convergence of simulation, high-performance computing, and AI.
On day one of the event, Amy Webb, founder and CEO of the Future Today Institute will present a talk titled, ''Why Do We Keep Getting the Future Wrong?''. This presentation will help all engineers think like a futurist, reimagine the way they understand risk, and inspire them to act.
On day two of the event, Intel will host a breakout session focused on scaling AI at the edge. Dr. Rita H Wouhaybi, a Senior AI Principal Engineer at Intel will discuss how we can tackle the challenge of scaling Edge AI and provide a clear vision for reaching scale deployment goals.
On the final day of Future.Industry Altair experts will discuss how simulation software can be used in the development and application of digital twins. The session will focus on the Altair digital twin integration platform and how it offers a unique blend of physical simulation methods, data analytics, and machine learning techniques to create digital twins for use in predictive maintenance, asset management, product design and more.
The Future.Industry Event is completely virtual, allowing companies of all sizes to attend without the required travel of traditional conferences. The global event spans October 4th through the 6th, with parallel learning tracks to ensure you have access to the information and experts that are most aligned with your current projects. Presentations will also have live audio translations in French, Spanish, German, Italian, Portuguese, Japanese, and Korean.
To learn more about the agenda and register your spot to attend, visit the Altair Future.Industry website.
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