Welcome to the fifth annual article “Neural Artificial Intelligence Predictions”! That makes this series one of the longest running series in Neuron history. And this year our goal is to raise the bar higher than ever with our best information round to date.
Meet up, have some hot chocolate and let’s see what the experts think will happen in the world of AI:
Natalie Monbiot, Head of Strategy at Hour One:
2022 will see the growth of a new hybrid workforce in which human employees share their workload with digital employees. They will offload repetitive or routine tasks to machines that can perform them just as well, and in some cases better.
What’s more, employees will have their own digital avatars, with superhuman skills – such as the ability to speak any language. This will serve to break down geographical and cultural barriers and enable a whole new era of frictionless communications.
The new augmented, hybrid workforce will become pervasive thanks to advances in AI video production, and the sheer portability of video. This will play well with asynchronous communication, which is proven to be the most effective medium for the remote working environment.
Max Versace, CEO and co-founder of Neurala:
AI will migrate from digital to physical applications: In 2020 and continuing into 2021, the world has been awakened to real, physical problems. As a result, the focus of AI applications will shift from digital domains to physical ones, where AI can play a pivotal role in helping us solve real-world challenges. For example, AI applications that shape our physical world, e.g., the ones that remove key vulnerabilities in manufacturing, supply chain, and logistics, will take the spotlight. AI will come of age and enter adulthood. One example of a physical function demanding AI is quality inspections, a task traditionally performed by human workers. AI’s physical impact could be huge for the 35 million workers – roughly the population of Canada – devoted to performing this basic function on the manufacturing floor. The year 2022 will be a pivotal moment for AI: the urgency many manufacturers face needs innovative technology to help cope with pandemic disruptions to our physical economic infrastructure.
Let the clouds be in the sky: AI will accelerate its migration from servers to edges. Where data lives needs to be interpreted (often in real-time) and should not leave the walls of the company. Today, a plethora of AI-ready processors, cameras, and other hardware makes this possible. Increasingly, companies are realizing that the way to build a truly efficient AI algorithm is to train it on their own unique data, which might vary substantially over time. To do that effectively, the intelligence needs to directly interface with the sensors producing the data. From there, AI should run at a compute edge, and interface with cloud infrastructure only occasionally for backups and/or increased functionality. No critical process – e.g., in a manufacturing plant – would and should exclusively rely on cloud AI, exposing the manufacturing floor to connectivity/latency issues that could disrupt production. 2022 will see edge learning technologies on the rise, enabling AI to ‘reprogram’ from scratch in a few seconds, whenever and wherever needed. This paradigm-shifting technology will empower AI to truly serve its purpose at speeds, latency, and costs that make it affordable for every user.
Andy Hock, Head of Product at Cerebras Systems:
In 2022, AI will continue to grow as a valuable and critical workload for enterprise organizations across industries. We will see a larger number of teams investing in world-class AI computing to accelerate their research and business. With this, the need for faster, more power efficient, and purpose-built AI compute will continue to grow rapidly along with applications, models, and datasets. Companies leveraging AI as a key strategy for their business growth will need faster time-to-solution from their AI computing infrastructure, more scalability, and broader accessibility through diverse consumption models.
In terms of AI models and use cases, we anticipate a continued expansion and use of large language models for text and other sequence data modeling problems, with increased attention being paid to more parameter- and data-efficient models and methods. In computer vision, we will see increased use of high-resolution 2D and 3D image datasets and video, which will lead to greater demand for purpose-built AI compute platforms with greater performance and efficiency at scale. We also expect to see continued development and greater adoption of graph neural networks for industry applications ranging from drug discovery to finance to social network analysis.
Yashar Behzadi, CEO and founder of Synthesis AI:
The Conversation Around Data for AI Will Be Prioritized: The discussions around data for AI have started, but they haven’t nearly received enough attention. Data is the most critical aspect for building AI systems, and we are just now starting to talk and think about the systems to acquire, prepare, and monitor data to ensure performance and lack of bias. Organizations will have to prioritize a data-first approach within an enterprise architecture in 2022 to enable AI and analytics to solve problems and facilitate new revenue streams.
Synthetic Data Will Be a Requirement to Build the Metaverse: The metaverse cannot be built without the use of synthetic data. To recreate reality as a digital twin, it’s necessary to deeply understand humans, objects, 3D environments, and their interactions with one another. Creating these AI capabilities requires tremendous amounts of high-quality labeled 3D data––data that is impossible for humans to label. We are incapable of labeling distance in 3D space, inferring material properties or labeling light sources needed to recreate spaces in high-fidelity. Synthetic data built using a combination of generative AI models and visual effects (VFX) technologies will be a key enabler of the AI models required to power new metaverse applications.
Michael Krause, Senior Manager of AI Solutions at Beyond Limits:
GPT-4, Neural Networks, and the Revolutionization of Artificial Intelligence in 2022: In general, major breakthroughs in AI technologies are hard to time. However, 2022 will be an exciting year, a potential new language model, GPT-4, brings with it hopes to dramatically improve natural language AI. Auto-generated articles that are indistinguishable from human writing, improved real-time language translation, and meta-learning capabilities are just a few ideas of what may come next. Taking this kind of human-like processing power and applying this to existing technologies such as the cloud will elevate the advancement of tech not just in one sector, but within every single industry
Kim Duffy, Senior Life Science Product Manager at Vicon:
The adoption of machine learning (ML) and artificial intelligence (AI) methods in clinical gait analysis remains in its infancy. It will take several years to utilize these methodologies and see true benefits and advancements for clinical gait. However, while the pandemic has caused clinical practice delays, there has been a rise in practical applications of facial blurring using ML in the background to detect head positions in video capture, for instance. Although this application is not yet replacing traditional methods, there is a notable increase in clinical research involving these approaches. In another example, ML algorithms are currently being developed for automated gait data interpretation and patient classification. These developments and trends will only continue to evolve in 2022, and with an increase in automation of gait analysis, the clinical community can continue to take stride in new diagnostic and treatment methods.
We hope your vacation turns out to be excellent and 2022 will be the best year of your life. We will be here to provide you with all the news, analysis and opinions that you have come to expect from the Neural team.
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