We’re proud to be a sponsor and partner of the Tomorrow X Summit, taking place in Austin on November 17–18, 2026. Since launching in November 2024, FUNDA has been committed to producing and supporting the best independent research on Substack. We share Gavin’s view that independent creators and analysts have been important voices in the AI infrastructure buildout, and we welcome this initiative from Gavin, Ron, and Antonio to foster broader and deeper engagement with the technology companies we cover and invest in. FUNDA will also take the stage to discuss how companies can build their own context layers to support AI-powered workflows. With more than 10 members of our team heading to Austin, we’re excited to meet our readers, exchange ideas, and connect in person. @TomorrowXSummit @GavinSBaker @Atreidesmgmt @AntonioGracias @rbiscardi @iconnections_io See you in Austin, The FUNDA Team

@FundaAI is one of three that passed a recent audit of newsletters. The author says Funda's strongest signal comes with the fourth bullish mention of a stock - conviction building across successive research notes is a reason to follow the research over time. quantdata.uk/research/financ…

On our weekly @FundaAI client call, we discussed what the microLED and microVCSEL demonstrations at ECOC mean for optical links moving into applications currently served by copper. We also covered their potential role in scale-in architectures and the industry’s shift toward “wide and slow,” using more lanes at lower speeds. This was a recurring topic in major plenary sessions at ECOC. Avicena’s successful microLED demo and ams OSRAM’s microVCSEL demo showed progress on both technologies. For Credo, we are watching its expected ALC demo at OCP, which it has renamed “active light cable.” When we spoke with the team at ECOC, they did not confirm whether the demonstration would use microLEDs or microVCSELs. Seeing it in action should give us a better sense of Credo’s progress and where the product could fit into customers’ systems. Client questions focused heavily on Lumentum versus Coherent, specifically the linewidth and phase-noise debate over Coherent’s 400 mW UHP CW laser. We still see Lumentum ahead, with customer feedback on Coherent’s UHP laser remaining limited. We have not heard confirmation of successful qualification nor reports of specific problems with its laser. We also do not yet have enough visibility to assess whether Coherent can meet its target for December-quarter volume shipments. fundaai.substack.com/p/resea…

Recommended reading for the weekend: 1. @a16z — State of Markets II 2. @GoldmanSachs — AI Is Becoming a Stock Picker’s Market 3. @FundaAI — Optics: FCC Transceiver Rules Might Be Better Than Feared, and Better for Top Chinese Players Than You'd Think 4. @abcampbell — There Are Bonds in the Singularity 5. @federalreserve — An Update on AI and the Economy Have a great weekend everyone!

Thank you @ParadisLabs for ranking us above the Federal Reserve. 🙏🙏

Column|Optics: FCC Transceiver Rules Might Be Better Than Feared, and Better for Top Chinese Players Than You'd Think Investors have been discussing yesterday’s strength in optics stocks, particularly Lumentum and Coherent. The gains have been attributed to a widely discussed note reporting a senior legal team’s view of how the FCC may frame restrictions on Chinese-built optical transceivers. We examine the context for that note and the potential effects on suppliers. $LITE $COHR $TSEM $Innolight $Eoptolink $MRVL $MTSI $SMTC $MXL Detailed Report fundaai.substack.com/p/colum…

A joint deep dive with Ozeco of Crack The Market is out, and the whole piece is free. We set out to map who can actually fabricate the PIC, the silicon photonics chip that sits inside every AI optical link. When we finished counting, the list of fabs shipping datacom PICs in volume had six names on it. Underneath them, one company supplies nearly all of the 300mm photonics substrate they build on. What the piece covers: - Each of the six, by platform, wafer size and the customers designing into it - Why customers are already handing the merchant fabs cash, or being asked to, before the new capacity is built - The 300mm expansions that all land around 2028, and what that could do to wafer pricing - Why we see Nvidia's TSMC-based CPO and Tower/NewPhotonics NPO as complements today and rivals once lanes reach 400G My side was the foundries and the packaging. Seen from packaging, CPO moves at the speed of what comes after the fab. In TSMC's flow that means a hybrid bond nobody can redo, with the driver chip fused onto the photonic chip. Then every engine needs an optical check before it goes anywhere. If the base-case arithmetic holds and the 2028 risk is surplus rather than shortage, who keeps the pricing power: the foundry, the substrate, or the bonding line?

Research|LLM: Gemini 4 Brings Google Back into Frontier Competition as Investment Accelerates Google announced Gemini 4 Argon on September 30, roughly ten months after Gemini 3. On Google’s evaluations, Argon leads or ties GPT-6 Astra and Claude Opus 5.5 on 14 of 19 benchmarks. Artificial Analysis scores it at 53, level with Astra and below Opus 5.5 at 58 and Sonnet 5.5 at 56. Google is back in frontier competition, though it still trails OpenAI and Anthropic overall. Introductory pricing is $2 per million input tokens and $10 per million output tokens, rising to $4/$20 at the standard rate. We use this input/output convention throughout. Access is initially limited to trusted testers, with paid API customers and Google AI Ultra subscribers next in line. Two months ago, many investors thought Google was stepping back from frontier models. Gemini 3.5 Pro had missed its launch window and been shelved, leaving Google reliant on Flash-tier models. On August 5, Demis Hassabis stepped down as DeepMind CEO to become its chairman and Alphabet’s chief scientist. Jeff Dean left to found Discovery Loop with Oriol Vinyals, Quoc Le and others. Koray Kavukcuoglu took over DeepMind’s day-to-day operations, reporting to Sundar Pichai. Alphabet fell about 5% that day. Much of the commentary saw a shift toward selling compute and distributing AI applications. Tim O’Reilly drew a parallel with Westinghouse, suggesting Google might focus on infrastructure and wider AI adoption. Our view was different: Google would keep investing in frontier models, and a tighter focus would give it room to catch up. Argon’s results support that view. The training run began before the reorganization, however, so the effect of the management changes on R&D will only become clear over the next few model generations. Early this year, some in the market considered a scenario in which Anthropic kept extending its lead in coding and the enterprise, the other labs gradually fell away, and the frontier ended up with a single player. Today, OpenAI and Anthropic still lead, Google is back in contention, and Meta and xAI continue to invest. Several labs remain in the race. Detailed Report fundaai.substack.com/p/resea…

Review| $MU FY26Q4: Visibility Extends to 2028, Supply Tighter Than in 2026 Micron expects memory supply-demand conditions in CY27 and CY28 to be tighter than in 2026. Customer orders and AI compute demand continue to rise. Even after accounting for planned cleanroom expansions across the industry, Micron sees no clear timeline for supply and demand to return to balance. Management expects prices to keep rising through FY27, though at a more moderate quarter-over-quarter pace. This is consistent with our prior view: memory prices will continue to rise, with the pace constrained by LTAs and customer affordability. Micron’s FY27Q1 gross margin guidance was 75 bps below the buy-side expectations shown below, reflecting additional costs such as incentive compensation and new fab startup expenses. Revenue and EPS results and guidance exceeded those expectations, while FY26Q4 gross margin was in line. Based on our adjustment for the additional costs, gross margin guidance was approximately 80 bps above buy-side expectations. We reiterate our view that this memory cycle will sustain a longer plateau, and we look forward to Micron’s planned increase in shareholder returns from December 9, 2026. Detailed Report fundaai.substack.com/p/revie…

I asked Claude yesterday on @FundaAI post about models not exposing full chain of thoughts as plaintext. CPU + GPU up today too.

I invite you all to read the whole paragraph and the full article for a complete overview. Credo will adopt both uLEDs and uVCSELs and have re-named their cables to Active Light Cables (ALC) which is more of an AOC now. Avicena showed at ECOC a successful uLED demo.

Deep| $FTAI : Aviation Aftermarket Meets AI Power We initiate coverage of FTAI, an independent aviation aftermarket platform focused on the CFM56-5B/-7B and V2500 engine families. It is expanding into power generation by converting CFM56 engines into aeroderivative turbines. FTAI is the second BTM solution provider we have covered, after Bloom Energy. We remain bullish on off-grid power providers. As estimated in our AIDC Deep Dive, North America could face a ~15GW power shortfall in 2027. Securing grid power could take ~5 years, while traditional gas turbine OEMs such as GEV are booked out to 2032 with cash commitments. We are therefore looking for alternative BTM providers with reliable technology and confirmed orders. FTAI trades at ~10.5x forward EV/EBITDA and has yet to receive the re-rating seen at other BTM providers, despite the $1.465b Power order announced in late July. We see two reasons. Its traditional Leasing and MRE businesses face pressure on margins and industry demand. Its Power business has yet to deliver Mod-1 units to customers, making future earnings harder to assess. Bears still view Mod-1 as a prototype rather than a mature commercial product. In short, we believe that margin compression in its MRE business does not prevent it from maintaining earnings growth, supported by expanding market share from ~15% to ~26% based on our proprietary supply-demand industry model; and Power could deliver ~10 Mod-1 products in 26Q4 vs LSD consensus; ~80 in 2027 vs ~70 consensus and ~100 company maximum target. Management were guiding $450-750mn Adj. EBITDA in Power, suggesting a range of ~60 to 100 Mod-1 deliveries as guidance in 2027. We see the first batch of Mod-1 delivery in Q4 as the next rerating catalyst, and do not think the execution bar for Power is that high in the near term. Successful delivery and acceptance from customers should be enough for the street to catch up as it clears ambiguity at current valuation. Our reverse SOTP suggests that the market is paying nothing for Power, and we estimate it should be worth $82/share in our base case of 80 Mod-1 delivery in 2027. Detailed Report fundaai.substack.com/p/deepf…

Research|Optics: ECOC 2026 Takeaways, NPO Gains Momentum as Slow and Wide Takes Shape We attended ECOC 2026 in Málaga last week. The debate between slow and wide and fast and narrow was a recurring topic in presentations and plenary sessions. Companies presented microLED and micro-VCSEL designs and discussed their performance, manufacturing challenges and production timelines. NPO was also in focus, with live NPO demos on the show floor and more discussion of how and when it ramps. This note covers our takeaways from the presentations, demos and conversations with companies, including developments in NPO, scale-in, external lasers, retimers, DSPs, coherent-lite and test and measurement. Detailed Report fundaai.substack.com/p/resea…

From @FundaAI latest. Credit to Credo for admitting to reality and pivoting quickly. uVCSEL >> uLED in every way. uLED has fundamental, unfixable issues. Blowing up fiber attach count for ultra slow lanes only to need to burn power on FEC anyway.

Deep|LLM: Open-Weight Models’ Low-Cost Catch-Up Is Unlikely to Last Top labs are going to widen their lead again A succession of strong open-weight models were released this summer. Zhipu launched GLM-5.2 on June 22, followed by GLM-5.3 on August 14, a release focused solely on scaling post-training. On Zhipu’s own evaluations, GLM-5.3 matched or outperformed Fable 5 and GPT-5.6 Sol on several agentic coding tasks. Moonshot AI launched Kimi K3 on July 17. It scored 57 on the Artificial Analysis Intelligence Index, behind only Fable 5 and GPT-5.6 Sol. DeepSeek’s August 13 update to V4 Pro scored 87.9 on Terminal-Bench 2.1, nearly matching Fable 5’s 88 at roughly one-fiftieth of its cost per task. DeepSeek followed with V4.1 Flash in September. Xiaomi released MiMo-V2.6 with open weights on September 22; its Pro variant now leads the open-weight rankings on the Artificial Analysis Intelligence Index. Many in the industry now put the gap between open-weight and top proprietary models at just a few months. Some argue that distillation is not the main reason open-weight models have kept pace. We agree it is not the only reason, but it has been one of the key ones. What worries investors is whether open-weight developers can keep matching top proprietary models at a fraction of the R&D cost, and if so, how long the proprietary labs’ lead can last. That worry is feeding into AI and compute stocks, as it did after DeepSeek R1 in January 2025. We do not think open-weight developers can keep catching up this cheaply, and we expect the recent narrowing of the gap to prove temporary, as it did after R1. Distilling capabilities from top proprietary models is getting harder. The latest models from Anthropic, OpenAI and Google no longer expose their full chain of thought as plaintext, and answers and summaries alone provide weaker training signals. Open-weight developers will need to invest more in their own reinforcement learning, synthetic data generation and training environments. All require compute. Over the next few model generations, we expect the leading open-weight models to fall roughly six to twelve months behind top proprietary models again. The same thing happened in 2025: R1 briefly approached o1, then o3, Claude 4 and GPT-5 pulled ahead. Detailed Report fundaai.substack.com/p/deepl…

Deep|$META Muse: The Software Companies Behind Its Actions (Part 1: Public Companies) We went under the hood of Muse to see which software services it calls as it carries out a user’s request. We followed the steps from finding information and accessing accounts to making calls, managing bookings and returning a result, then linked those steps to the companies behind the software. This first part covers 25 products from 24 listed companies. It shows where Muse could bring more activity to existing communication, productivity, travel, commerce and connected-device services—and where we can currently confirm only that a connection exists. Detailed Report fundaai.substack.com/p/deepm…