2023 Predictions: AI That Bends Reality, Unwinds the Golden Screw and Self-Replicates

After three years of uncertainty caused by the pandemic and its post-lockdown hangover, enterprises in 2023 - even with recession looming and uncertainty abounding - face the same imperatives as before: lead, innovate and problem solve.

AI is becoming the common thread in accomplishing these goals. On average, 54% of enterprise AI projects made it from pilot to production, according to a recent Gartner survey of nearly 700 enterprises in the U.S., U.K. and Germany. A whopping 80% of executives in the survey said automation can be applied to any business decision, and that they're shifting away from tactical to strategic uses of AI.

The mantra for 2023? Do more with less. Some of NVIDIA's experts in AI predict businesses will prioritize scaling their AI projects amid layoffs and skilled worker shortages by using cloud-based integrated software and hardware offerings that can be purchased and customized to any enterprise, application or budget.

Cost-effective AI development also is a recurring theme among our expert predictions for 2023. With Moore's law running up against the laws of physics, installing on-premises compute power is getting more expensive and less energy efficient. And the Golden Screw search for critical components is speeding the shift to the cloud for developing AI applications as well as for finding data-driven solutions to supply chain issues.

Here's what our experts have to say about the year ahead in AI:

ANIMA ANANDKUMAR

Director of ML Research, and Bren Professor at Caltech

Digital Twins Get Physical: We will see large-scale digital twins of physical processes that are complex and multi-scale, such as weather and climate models, seismic phenomena and material properties. This will accelerate current scientific simulations as much as a million-x, and enable new scientific insights and discoveries.

Generalist AI Agents: AI agents will solve open-ended tasks with natural language instructions and large-scale reinforcement learning, while harnessing foundation models - those large AI models trained on a vast quantity of unlabeled data at scale - to enable agents that can parse any type of request and adapt to new types of questions over time.

MANUVIR DAS

Senior Vice President, Enterprise Computing

Software Advances End AI Silos: Enterprises have long had to choose between cloud computing and hybrid architectures for AI research and development - a practice that can stifle developer productivity and slow innovation. In 2023, software will enable businesses to unify AI pipelines across all infrastructure types and deliver a single, connected experience for AI practitioners. This will allow enterprises to balance costs against strategic objectives, regardless of project size or complexity, and provide access to virtually unlimited capacity for flexible development.

Generative AI Transforms Enterprise Applications: The hype about generative AI becomes reality in 2023. That's because the foundations for true generative AI are finally in place, with software that can transform large language models and recommender systems into production applications that go beyond images to intelligently answer questions, create content and even spark discoveries. This new creative era will fuel massive advances in personalized customer service, drive new business models and pave the way for breakthroughs in healthcare.

KIMBERLY POWELL

Vice President, Healthcare

Biology Becomes Information Science: Breakthroughs in large language models and the fortunate ability to describe biology in a sequence of characters are giving researchers the ability to train a new class of AI models for chemistry and biology. The capabilities of these new AI models give drug discovery teams the ability to generate, represent and predict the properties and interactions of molecules and proteins - all in silicon. This will accelerate our ability to explore the essentially infinite space of potential therapies.

Surgery 4.0 Is Here: Flight simulators serve to train pilots and research new aircraft control. The same is now true for surgeons and robotic surgery device makers. Digital twins that can simulate at every scale, from the operating room environment to the medical robot and patient anatomy, are breaking new ground in personalized surgical rehearsals and designing AI-driven human and machine interactions. Long residencies won't be the only way to produce an experienced surgeon. Many will become expert operators when they perform their first robot-assisted surgery on a real patient.

DANNY SHAPIRO

Vice President, Automotive

Training Autonomous Vehicles in the Metaverse: The more than 250 auto and truck makers, startups, transportation and mobility-as-a-service providers developing autonomous vehicles are tackling one of the most complex AI challenges of our time. It's simply not possible to encounter every scenario they must be able to handle by testing on the road, so much of the industry in 2023 will turn to the virtual world to help.

On-road data collection will be supplemented by virtual fleets that generate data for training and testing new features before deployment. High-fidelity simulation will run autonomous vehicles through a virtually infinite range of scenarios and environments. We'll also see the continued deployment of digital twins for vehicle production to improve manufacturing efficiencies, streamline operations and improve worker ergonomics and safety.

Moving to the Cloud: 2023 will bring more software-as-a-service (SaaS) and infrastructure-as-a-service offerings to the transportation industry. Developers will be able to access a comprehensive suite of cloud services to design, deploy and experience metaverse applications anywhere. Teams will design and collaborate on 3D workflows - such as AV development simulation, in-vehicle experiences, clou

LINK:	https://blogs.nvidia.com/blog/2022/12/13/2023-ai-predictions/...
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