DanielRomero

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$AMD says hybrid-bonded 3D DRAM is 17× more energy-efficient than HBM using microbumps
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$SKHY claims up to 5.15x LLM inference improvement with Custom HBM
Looking further ahead, the company is exploring a new type of memory:
- Compute-using DRAM
This would allow DRAM to perform certain computations directly inside the memory itself, reducing the need to move data back and forth between memory and the processor
SKHY2.17%
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I'd say the themes capturing the most attention at SEMICON this year are:
1. Advanced packaging
2. Memory
3. Photonics
Glass substrates are getting a lot of attention as well. I didn't expect that, but people were really pumped for Unimicron
Big vibe shift with $AMD too. People were really interested in them
AMD0.94%
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RAFI_098_77T:
give some dollars

ui: 17291626

ber -20 address: 0x1a9c6D8e36335E80296037a2C0c862E73835E137
$AAPL being the second-largest company in the world by market cap in 2026, despite having barely any direct AI exposure, is genuinely impressive
No data centers, no frontier AI models, just good ol’ smartphones and laptops
AAPL-0.73%
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Unimicron says TGV yields are still poor and is targeting 2029/2030 for mass production of glass-core substrates
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Glass will be used alongside ABF build-up layers and PID, an insulating polymer layer
This substrate material transition is crucial for FOPLP
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$LITE likes VCSELs for AI scale-up interconnects
Their main limitation is reach
LITE2.24%
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GateUser-ab9d682c:
So cool, bro.
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Samsung’s zNAND-O looks amazing
10× DRAM bit density, with 7× higher read bandwidth and 7× better read power efficiency than conventional flash
3D NAND could offload a lot memory capacity from HBM, particularly for inference workloads where not all data needs HBM-class latency
First samples targeted for 2028
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$GOOG:
“Software optimizations aren’t enough. We need more memory.”
GOOG-2.15%
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$GOOG showcases its two TPU 8 variants:
TPU 8t: optimized for training and massive scale, with 9,600 TPUs per pod and 2 PB of shared HBM
TPU 8i: optimized for inference and reinforcement learning, with 50% more HBM, up to 288 GB, to reduce latency and avoid expensive off-chip data movement
GOOG-2.15%
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Ihasif:
So, it will be bullish over the upcoming times. thanks for the important update. Need to heed back to CFD trading.
$CDNS laid out the three phases of AI adoption:
1–3 years: AI infrastructure
2–7 years: Physical AI
5–10+ years: Sciences AI
There seems to be a growing trend toward AI-powered biotech and scientific discovery
CDNS-0.45%
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$CDNS was the only presenter who decided to speak in Chinese at an event that was supposed to be 100% in English 😭
CDNS-0.45%
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$SKHY presenter is so nervous
He started by saying, “I prepared a script, and I’m going to start reading it…”
🥱
He even read the disclaimer
SKHY2.17%
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The US manufactured around 450 humanoid robots in 2025
China manufactured 20,000
If US humanoid production increases 1,000x from here,
Which stocks stand to capture the most value from that growth?
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$AMD mentions bottlenecks and everyone takes out their phone to take a picture
The favorite word of every investor in 2026
AMD0.94%
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Powertech stealing all the attention at the SEMICON forum
People woke up after the $LRCX and $AMAT presentations
First automated FOPLP mass production line for HPC, using massive 515 × 510 mm panels
LRCX-0.05%
AMAT-0.67%
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GateUser-55ba60f1:
To The Moon 🌕
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MediaTek says PLP yield is now as good as wafer-level
However, only at smaller package sizes
At larger sizes, you get warpage and thermal issues
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High-tech analogies at SEMICON by MediaTek
What happens when pizzas get too large?
You make them rectangular
Same with advanced packaging. As AI packages get larger, round wafers become too small and inefficient, and rectangular panels make a lot more sense
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kowser:
Ape In 🚀
Nice and ready
First day of SEMICON
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Powertech ( is now calling FOPLP a revolution
Makes me feel better about not being sensationalist
It truly is a revolution in semis that’s still going under the radar for the masses
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