$GOOGL Gemini 4 Argon benchmarks got released.
Against GPT-6 Astra + Anthropic Fable 5.1 / Opus 5.5.
Still coughing nonstop, so will comment on $MU / $JBL earnings later.
I've always thought Google's internal models were stellar, but anecdotally, they seem to get hard nerfed shortly after public release... Maybe because of compute constraints?
But yeah, looks like Google is back.
@DavidJang0620 I actually thought $JBL earnings were great.
But usually if you disagree with how markets reacted, that just means there's a buying opportunity.
Bro, $AMZN semi ETF portfolio is probably going to end up more compelling than what $NVDA owns...
Today Amazon signed a $49.8M private placement into PCB maker Gold Circuit Electronics (2368). So now Amazon has ownership/warrants in:
- $AAOI
- Alchip
- $MRVL (Celestial)
- $ALAB
- $CRDO
- $JBL
- $FLEX
- $STM
- $CBRS
- $GNRC
- $FN
- TD SYNNEX
- $QCOM
- Gold Circuit Electronics
And others..
If we look at the private placement amount for GCE in speciifc, it's like .36% of the company... Kinda small financially, meaningful strategically. Esp. since there were claims that GCE supplies ASIC-server PCBs to the four major hyperscaler CSPs...
Regardless it's pretty funny to see Amazon to Nvidia start to own all the worlds leading companies.
Since Amazon has exposure to the entire supply chain like PCBs now, optical fabric with Celestial, lasers with $AAOI, assembly from $FN to $JBL, ASIC partners like $QCOM / ALchip.
@llm_kv It’s a long way for it to serve production load at scale IMO.
Supply chain, reliability, unit economics are something hard to close vs NVIDIA GPUs
It took almost 18 months for AMD GPUs to mature enough to serve model inference. Not to mention CBRs
@LeoHsu4A Nextron (8147) — September 30, 2026 Investor Briefing: 10 Key Takeaways
Based on same-day media coverage. Forward-looking figures represent management targets.
AI revenue could double in 2027. Management expects AI’s revenue share to rise from approximately 15% in 2026 to around 30% next year.
AI rack shipments accelerated in Q3. Management described capacity as tight and expects Q4 revenue to sustain Q3’s elevated level.
Connectors remain the largest business. January–August revenue comprised 69% connectors, 26% electronic assemblies and 5% other products.
1.6T products are undergoing customer qualification. Working with a Japanese partner, Nextron targets production in Thailand in late 2026 or 2027.
12.8T remains at the specification and sample stage. Management targets commercial production in 2027–2028.
Humanoid robot components have started shipping. North American customers have outlined 2027 production targets, but volumes remain undisclosed.
Guangzhou is running at full utilization. The plant has increased capacity by 33%.
Thailand is entering production.
Medical products began production in Q3 following Q2 customer approval; certain optical communications products are scheduled for Q4. Expansion will focus on existing facilities.
Management plans additional automation, equipment and staffing, with no immediate plans to build new factories.
Revenue growth has already accelerated. January–August sales reached NT$1.402 billion, up 29% year over year. August revenue rose 95.98% to NT$229.8 million.
@3lHyl246m How can it go even lower despite such great news from $NVDA? Even though the narrative has shifted so much, nothing can revive it. Something is completely off here.
Liwei has never been a fan of $LPK, but I thought the NVDA news would at least give it a boost. Turns out it still sucks haha. What is wrong with this company 🤣🤣 https://t.co/l6Xt36jeYn
That’s why Liwei rarely do 'zero-to-one' plays in the stock market. Sure, uncovering obscure small caps feels rewarding, but life is too short—I'd rather spend my time on battle-tested winners. You'll get it once you've been in the game long enough.
Like I told @pequityresearch few days ago, I heard that glass core substrate adoption was being accelerated.
My Taiwan TGV equipment play, https://t.co/IxrBEkP8Fh, suddenly went limit-up two days in a row, and now the news is officially out 🤣 Liwei front-ran the news again.
$NVDA Is Pushing Glass Substrates Toward a 2028 Deadline
$NVDA has reportedly asked substrate makers in Taiwan, Japan and South Korea to accelerate glass-substrate development, with adoption potentially arriving before 2028. The technology targets a growing packaging problem: larger AI packages need better dimensional stability as more compute and HBM are integrated.
$LPK $TSM
Sources
https://t.co/ysQFba4kUX
@BenBajarin MediaTek enjoys priority access to TSMC's advanced node capacity, trailing just slightly behind Nvidia and where Apple historically ranked.
@AnthropicAI‘s report shows what bad actors could potentially do with powerful technology, but we’d like to highlight what good actors are already doing with the same technology.
We hope this balances the narrative and mitigates the association that “open models == dangerous.” (3/3)
https://t.co/UdXBzHVuBO
We present our full analysis of GLM-5.3, including cyber capabilities, inference performance, model architecture, and post-training pipeline in our newsletter (2/3) https://t.co/Bg0lg746Sq
We assessed GLM-5.3 cyber capabilities on ExploitGym and analyzed the traces. GLM-5.3 spent much of its execution budget testing whether hidden runtime conditions changed its conclusion. In problem arvo5665, GLM-5.3 explored more of the surrounding program through sanitizer builds, corpus tests, and target fuzzing. (1/3)🧵
https://t.co/YAcLMweMqo
AMD Helios (partial co-design): AMD revealed the TH6 scale up switch design publicly for the first time. If you look close enough, you can spot all the Broadcom ethernet retimers next to the flyover cables coming from the backplane into the switch ASIC. This design demonstrates AMD's lack of complete silicon product portfolio, particularly a scale up switch, which is necessary for a scale up rack. In the case of Helios, AMD relies on Broadcom for the scale up switch and retimers alone the scale up path. In the future, AMD are also working with UALink switch vendors in their pursuit of a true UALink scale up system. https://t.co/pWC888azm6.
In our advancing AI 2026 article, we talked about the challenges with these retimers and flyover cables towards manufacturing and signal performance. The retimers also add extra latency alone the scale up path. https://t.co/4Myxl9Uukb
If AI helps write and review papers, what is a top conference acceptance worth? As more papers get in, that acceptance carries less weight. What matters more is a paper’s real impact and the attention it gets from people in academia and industry. (6/6)
Academia is responding. ICLR warns of too few qualified reviewers. NeurIPS 2026 is testing AI assisted review; ICLR 2027 allows limited, disclosed AI help. However, as AI makes papers cheaper, review overload risks eroding the credibility these venues spent years building. (5/6)
NeurIPS main-track acceptances: 3,218 (2023), 4,037 (2024), 5,290 (2025), and 7,900 reported (2026). That's +49% in one year. More papers got in with similar acceptance rate: 24.5% to 25.7%. A stable acceptance rate says little about review depth. Did expert scrutiny scale with paper output? (4/6)
For example Jev launched Sep 15. By Sep 20, a preprint benchmarked it. More Jev papers followed on Sep 21, 22 and 24. The Sep 24 PDF says it is under review at ICLR 2027. Five days to a public paper, nine to a claimed conference submission. Research is moving on product time. (3/6)
Why the surge? AI tools make drafting, coding and revision cheaper. The effort of producing a polished paper can speed up; checking whether its claim is new and true still needs scarce expert time. (2/6)
AI is making papers cheaper to produce. ICLR submissions: 4,938 (2023), 7,262 (2024), 11,603 (2025), 19,525 (2026). Reported 2027 IDs exceed 62K, above roughly 56K paper submissions in all previous years COMBINED. Can reviewers keep up? (1/6)🧵 https://t.co/Om08umirx3
ALERT 🚨🚨OpenAI's latest GPT6.1 Sol Ultrafast is NOT running on Cerebras but is instead running at a low batch size on NVIDIA GPUs.
What does this say about Cerebras? Will Cerebras be serving GPT6.1 Sol Ultrafast in the future? https://t.co/FNkO6qOmP8