Semiconductor News & Analysis Feed
94 articles
2026-06-17
cryptobriefing.com
2026-06-17
Crypto Briefing
Nvidia’s AI inference chip market share rises to 74%, cementing dominance in fastest-growing AI sector
The chipmaker expanded its lead from 66% as the AI inference market races toward $100 billion, wi
2026-06-16
aibusiness.com
2026-06-16
AI Business
The South Korean startup sees itself as capable of competing with the biggest AI infrastructure providers.
The origin story of this young AI chipmaker’s name captures its ambitious goals.
“Everybody's looking for an alternative to the big incumbent in every industry. And here we are to lead one of the rebellions against the big incumbent in this AI industry -- Nvidia,” said Marshall Choy, chief
2026-06-16
www.moomoo.com
2026-06-16
Moomoo
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2026-06-16
news.futunn.com
2026-06-16
富途牛牛
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2026-06-16
www.digitimes.com
2026-06-16
digitimes
Nvidia's dominance in AI is extending beyond model training and deeper into inference—the fast-growing segment of the AI market responsible for running deployed models and generating revenue.
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2026-06-16
digitimes.com
2026-06-16
Nvidia's dominance in AI is extending beyond model training and deeper into inference—the fast-growing segment of the AI market responsible for running deployed models and generating revenue.
2026-06-15
www.theinformation.com
2026-06-15
The Information
Amazon’s Jassy Raised Concerns About Anthropic Model Before Trump Crackdown
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2026-06-14
en.sedaily.com
2026-06-14
Seoul Economic Daily
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2026-06-12
digitimes.com
2026-06-12
Breaking the inference barrier requires a rethink of the whole system architecture, not just faster compute. This was the key takeaway from a recent panel discussion at SuperAI Singapore, which brought chip makers and an AI model accelerator together to address how to overcome inference bottlenecks at a time when compute workloads are hitting up against physical limits.
2026-06-10
digitimes.com
2026-06-10
WD is preparing for a global wave of AI data growth by prioritizing hard drives with higher capacity, faster performance, and lower power consumption. The company says the shift reflects how AI training and inference are generating more data than traditional systems can handle, making storage efficiency and affordability increasingly important worldwide.
2026-06-10
developer.nvidia.com
2026-06-10
NVIDIA Developer
Converting a quantized checkpoint into an NVIDIA TensorRT engine bridges the gap between model optimization and production deployment, enabling faster inference, higher throughput, and more efficient GPU utilization at scale.
In a previous post, we produced a high-quality FP8-quantized Contrastive Language-Image Pretraining (CLIP) checkpoint with NVIDIA TensorRT Model Optimizer.
This post picks
2026-06-09
digitimes.com
2026-06-09
Computex 2026 closed last week with physical AI among its central themes, and robots emerging as one of the clearest ways to demonstrate it. Yet, unlike CES, where robot makers competed to showcase their hardware, Computex presented a different picture: AI computing platforms, edge inference, physical AI architectures, and the ecosystems behind robots took center stage.
2026-06-08
seekingalpha.com
2026-06-08
Seeking Alpha
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Google TPU V8 Vs. Nvidia: How Inference Is Rewriting The AI Market
Jun 08, 2026, 3:49 AM ETAlphabet Inc. (GOOGL) Stock, NVDA Stock, GOOG:CA Stock, GOOG Stock, NVDA:CA Stock
Beth Kindig
Investing Group Leader
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Summary
Google announced that it will begin selling TPUs to select third-party data center operators, marking the company'
2026-06-05
news.google.com
2026-06-05
Seeking Alpha
2026-06-04
www.cloudmagazin.com
2026-06-04
Cloudmagazin
RATGEBER
**Reducing GPU Costs for AI Inference: FP8, FP4, and vLLM**
3 Juni 2026
8 min read
Training costs for a model are one-time, but inference costs accrue every day. That’s where the math is shifting: with native FP4 Tensor Cores on NVIDIA Blackwell and a serving layer like vLLM that leverages these formats, GPU hours and latency can be significantly reduced-without retraining the model. Fo
2026-06-03
www.forbes.com
2026-06-03
Forbes
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2026-06-02
www.techtimes.com
2026-06-02
Tech Times
By Adrian Parham
Published: Jun 02 2026, 10:00 AM EDT
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Intel CEO Lip-Bu Tan delivers the Intel keynote at Computex 2026 in Taipei, Taiwan INTEL CORPORATION
Intel CEO Lip-Bu Tan used Tuesday's Computex 2026 keynote in Taipei to deliver the most detailed public accounting yet of Crescent Island,
2026-06-01
www.digitaltoday.co.kr
2026-06-01
디지털투데이
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2026-06-01
gagadget.com
2026-06-01
Gagadget.com
Intel has unveiled Crescent Island, a data center GPU built specifically for AI inference — the stage where a trained model answers real user queries. It uses LPDDR5X memory instead of the expensive, supply-constrained HBM found in Nvidia's Blackwell chips. At 350W, it runs on standard air cooling, which matters directly to any operator who has been priced out of liquid-cooled infrastructure.
Aft
2026-06-01
www.theglobeandmail.com
2026-06-01
The Globe and Mail
Key Points
Cerebras and Nvidia are both using SRAM in their inference chips.
However, Cerebras is making massive-sized chips, while Nvidia has incorporated normal-sized LPUs into its chip ecosystem.
10 stocks we like better than Cerebras Systems ›
While large language model (LLM) training dominated the first phase of artificial intelligence (AI), inference is eventually expected to become the