Digital Lifescapes

Embodied AI is shifting industrial robotics from precise to perceptive — from rigid automation to adaptive execution in messy, variable production environments. For manufacturers and logistics providers, this isn't just a technology upgrade; it's a structural change in how work gets organized and business value gets created. Industrial robots have long excelled in static workflows: automotive assembly, fixed production lines, repetitive tasks. Where variability or human interaction arose, they stalled or required prohibitive engineering. Embodied AI Market Development Embodied AI changes this by closing the "sim-to-real" gap. According to the latest worldwide market study by ABI Research, AI-augmented robots have reached genuine adaptive automation with tangible ROI for early adopters. The shift rests on robust algorithms — particularly Dynamic Policy Adjustment and robotics foundation models — that learn and adapt in real time rather than following hard-coded rules. ...

We're now witnessing a seismic shift, driven by the maturity and ubiquitous adoption of Artificial Intelligence (AI). For years, AI was an application-layer phenomenon; a software challenge. Today, however, the focus has pivoted to the foundational, physical layer that powers it. The latest data from International Data Corporation (IDC) confirms what many in the business technology sector have observed firsthand: we are in the midst of an unprecedented infrastructure build-out, one that will redefine corporate IT investment strategy. The Applied-AI Initiative race is no longer merely to build an industry-leading AI model, but to possess the computational engine robust enough to train and deploy it at an exponential scale. AI Infrastructure Market Development The latest market study forecast is significant, painting a picture of an infrastructure gold rush defined by massive capital expenditure and rapid transformation. Firstly, the projected market spending on AI infrastructure wi...

Two years after ChatGPT captured the world's imagination, there's a dichotomy in the enterprise artificial intelligence (AI) market. On one side, technology vendors are making unprecedented investments in AI infrastructure and new feature capabilities. On the other, there's measured adoption from customers who carefully weigh the AI costs and proven use case benefits. Artificial Intelligence Market Development The scale of new investment is significant. Cloud vendors alone were expected to invest over $150 billion in capital expenditures in 2024, with AI infrastructure being the primary driver. This massive bet on AI's future is reflected in the rapid growth of AI server revenue. Looking at just two major players - Dell Technologies and HPE - their combined AI server revenue surged from $1.2 billion in Q4 2023 to $4.4 billion in Q3 2024, highlighting the dramatic expansion. Yet despite these investments, the revenue returns remain relatively modest. The latest TBR resea...

The semiconductor and smartphone industry stands on the brink of a transformative era, driven by the rapid integration of Generative AI (GenAI) technology into mobile devices. According to the latest global market study by International Data Corporation (IDC), GenAI smartphone shipments are forecast to grow by 363.6 percent in 2024 alone, reaching 234.2 million units. This surge represents 19 percent of the overall smartphone market. As we look toward the future, the adoption of GenAI is anticipated to redefine mobile device user interaction. GenAI Smartphone Market Development GenAI smartphones are defined by their ability to run on-device generative AI models efficiently, thanks to a system-on-a-chip (SoC) featuring a neural processing unit (NPU) with a performance capability of 30 tera operations per second (TOPS) or more, using the int-8 data type. This technological advancement promises to enhance the mobile user experience by enabling more personalized and proactive GenAI tool f...

Soon you will start to experience Artificial Intelligence (AI) benefits everywhere -- in the public cloud, at the edge of mobile networks, and on many personal digital devices. Generative AI (GenAI) workloads have moved beyond the bounds of cloud environments and can now run on-device supported by implementing heterogeneous AI chipsets. Combined with an abstraction layer that can efficiently distribute AI workloads between processing architectures and compressed LLMs with under 15 billion parameters, these advanced chipsets can enable us to run generative AI inferencing locally. On-Device AI Market Development ABI Research estimates worldwide shipments of heterogeneous AI chipsets will reach over 1.8 billion by 2030 as personal computers, smartphones, and other form factors will increasingly ship with on-device AI capabilities. "Cloud deployment will act as a bottleneck for generative AI to scale due to data privacy, latency, and networking cost concerns. Solving these challenges...

The exponential growth of Artificial Intelligence (AI) applications will create demand for new devices that are purposely enabled and enhanced to deliver superior end-user experiences. Worldwide shipments of AI PCs and Generative AI (GenAI) smartphones are projected to total 295 million units by the end of 2024 -- that's up from 29 million units in 2023, according to the latest global market study by Gartner. Gartner defines AI PCs as devices equipped with dedicated AI accelerators or cores, neural processing units (NPUs), accelerated processing units (APUs), or tensor processing units (TPUs), designed to optimize and accelerate AI tasks on the device. GenAI-Enabled Device Market Development This new device platform provides improved performance and efficiency in handling AI and GenAI workloads without relying on external on-prem servers or public cloud services. GenAI smartphones are designed and equipped with hardware and software capabilities that enable integration and efficie...