TIRIAS Research analysts discuss the recent CES announcements from AMD and Nvidia, focusing on their implications for AI and the broader tech landscape in 2026. The analysis highlights the competitive dynamics between these two semiconductor giants in the context of physical AI advancements.
The IEEE Computer Society's guide emphasizes that a successful career in artificial intelligence relies on a blend of technical skills and human-centered capabilities rather than solely on mastering specific tools. This approach is crucial as AI continues to rapidly evolve and reshape the job market.
The article introduces AIE4ML, a framework designed to optimize AI model execution on AMD's Versal AI Engine, enhancing performance and memory management. It aims to facilitate efficient neural network execution across the AIE-ML architecture, including future compatibility with AIE-MLv2.
The article discusses the transition of advanced AI models from cloud environments to local supercomputers, drawing parallels to the evolution of computing from minicomputers to mainframes. This shift highlights the growing capabilities and relevance of local computing power in handling complex AI tasks.
Major semiconductor companies like Intel, Nvidia, and AMD showcased their latest processors at CES, indicating a competitive push in AI technology. These advancements are expected to significantly influence AI PCs, data centers, and embedded AI applications.
AMD has unveiled its new Ryzen AI 400 and PRO 400 Series processors, which offer up to 60 NPU TOPS for enhanced AI capabilities in PCs. Additionally, the introduction of Ryzen AI Max+ SKUs aims to elevate performance in ultra-thin notebooks and workstations for various applications including gaming and AI.
AMD has launched its new Ryzen AI Embedded P100 and X100 Series processors, which integrate high-performance CPU, GPU, and NPU technologies for efficient AI processing. These processors are designed to enhance immersive experiences in automotive, industrial automation, and autonomous systems.
AMD, under CEO Lisa Su, has transformed from a struggling company to a strong competitor against Intel in the datacenter market, largely due to innovations in its Zen microarchitecture and Epyc server chips. The article discusses AMD's ongoing efforts to develop Yottascale AI compute capabilities.
Ed envisions using AI-created characters to significantly lower movie production costs, potentially democratizing the film industry. This innovation could change the landscape of content creation in 2026.
The article lists the top ten semiconductor CEOs for 2025, highlighting industry leaders such as C C Wei, Jensen Huang, and Lisa Su. This recognition reflects their influence and contributions to the semiconductor landscape.
Q3 datacentre capital expenditures rose by 59% year-over-year, marking the eighth consecutive quarter of double-digit growth driven by ongoing investments in AI. This trend underscores the increasing demand for cloud services among major providers like Amazon and Google.
The article discusses key players in GPU networking, including NVIDIA, Broadcom, and AMD, while comparing various technologies like NVLink, UALink, and ESUN. It also touches on the competition in the AEC space and the debate between optical and electrical solutions.
The article discusses the impact of memory swizzling on AI compute performance and highlights how register-centric architecture can transform AI design. It suggests that these architectural changes are crucial for optimizing AI workloads.
The article discusses the optimization of GEMM algorithms for AMD's Ryzen AI XDNA and XDNA2 NPUs to enhance performance in deep learning workloads. It highlights the impressive throughput achieved for both 8-bit integer and brain floating-point precision across different NPU generations.
The article introduces Chopper, a new profiling and analysis framework designed to enhance the understanding of GPU performance during large language model training. It highlights the framework's ability to identify bottlenecks in multi-GPU environments, specifically during the training of Llama 3 8B using AMD's MI300X GPUs.
The article discusses the longevity and replacement cycles of XPUs versus GPUs, highlighting Arista's AI opportunities and mentioning Broadcom's role. It also touches on Amkor's developments in Arizona and TSMC's involvement.
The article discusses the competitive landscape of hybrid bonding technology in semiconductor packaging, highlighting the advantages of direct Cu-Cu and oxide-to-oxide connections. It also mentions Samsung's strategic move to secure a source for glass interposers, which are crucial for advanced packaging solutions.
The article discusses the insights of Melanie Mitchell, a prominent computer scientist, on the current state of artificial intelligence and its implications. Her work has significantly shaped the understanding of AI's capabilities and limitations in recent years.
The article discusses the prevalence of toxic work environments in the engineering field, particularly among semiconductor professionals. It highlights the negative impact of toxic managers and teammates on career development and workplace morale.
The article discusses the increasing demand for low-latency 4K UHD video encoding, highlighting the integration of dedicated hardware encoders in modern GPUs. It evaluates the performance of low-latency encoding modes on GPUs from NVIDIA, Intel, and AMD, comparing them to normal-latency settings.