After Meta's (META.US) "Muse moment," who will be the next to see a "explosive rally"?

Meta Platforms (META.US)'s Muse AI agent had been live for less than two weeks when the stock responded to market enthusiasm with a single-day gain of over 11%. Evercore ISI analyst Mark Mahaney called it "a very intuitive manifestation of successful product innovation," and said outright that the company's roughly $200 billion in AI investment "did not go down the drain." This frenzy, which added about $190 billion in market value, also led Deepwater Asset Management managing partner Gene Munster to see a replicable patternwhen consumers actually use a product and find that it genuinely works well, the capital markets will reprice it in an almost violent manner. Munster said on social platform X: "We knew Muse was coming six months ago. The reason this stock surged is that the broader market has now used the product and finally understands how good it is." According to his reasoning, the same scenario will take shape in products from Apple Inc. (AAPL.US), Tesla, Inc. (TSLA.US), and SpaceX (SPCX.US). The catalysts differ, but the underlying logic is the same: product experience replaces narrative expectations and becomes the trigger for valuation re-rating. Muse's "usability moment" To understand Munster's logic, one must first see clearly what Muse actually got right. Muse can send emails, book travel, complete shopping, fill out forms, and even continue executing tasks after the app is closed. Within six days of launch, iOS downloads exceeded 902,000, higher than the 773,000 recorded by the previous-generation Meta AI app over the same period. As of September 18, daily active users had reached 448,000, with total downloads of about 730,000 in the first five days. And as of Monday, downloads for the service had surpassed 2.5 million, and it briefly became the most-downloaded free iPhone app in the United States. But what is truly interesting is not the numbers themselves. Muse runs on Meta's Muse Spark 1.3 modelthis is not the strongest model on the market. Its appeal comes from the execution layer: custom agents built around Facebook Marketplace, Instagram, Gmail, Google Calendar, and OpenTable can plan, execute, and track multi-step tasks across apps. In other words, Muse's victory is not a victory of the model, but a victory of the "shell." When model capabilities exceed the speed at which the product side and user side can absorb them, the competitive advantage shifts to the layer that organizes, orchestrates, and packages model output into reliable work. This explains why Meta's market value increase was accompanied by Arm (ARM.US) rising 17.16%, Intel Corporation (INTC.US) rising 12.14%, and AMD (AMD.US) rising nearly 10%while NVIDIA Corporation (NVDA.US) rose only 2.30%. When the operating unit of an agent changes from a single inference call to a continuously running sandbox environment, the value distribution landscape for CPUs is being rewritten. Wells Fargo raised its Meta target price from $640 to $796, saying the company "now has an AI story to tell." Apple Inc.'s two opportunities, but the second is the real test However, Munster's attention has already turned elsewhere. Munster first set his sights on Apple Inc., dividing Apple Inc.'s potential catalysts into two stages. The near-term one is iPhone DuoApple Inc.'s first foldable phone. This device, priced at $1,999 and featuring a 7.6-inch display when unfolded, will ship on October 23. Counterpoint expects sales of about 6 million units this year, while IDC expects Apple Inc. to hold 40% of the foldable market by the end of 2027. TrendForce estimates that shipments of this model in 2026 will be about 5 million units, which will help Apple Inc. secure about 24.8% share of the foldable market, second only to Samsung (SSNLF.US)'s 35.1%. This means that with just one product, Apple Inc. will enter the second tier of the foldable track. But foldables are essentially an iteration of hardware form factor; they can attract replacement demand, but it is difficult for them alone to support an AI narrative rally like the one triggered by Muse. The real test falls on personalized Siri. At WWDC 2026, Apple Inc. officially released Siri AI rebuilt on a custom Alphabet Inc. Class C (GOOGL.US) Gemini model. The assistant can call on personal context information from text messages, emails, and photos, understand what is currently being displayed on the screen, and complete multi-step operations across multiple apps. In terms of technical architecture, Apple Inc. adopted a three-layer privacy system: on-device models handle low-latency privacy tasks, private cloud computing handles medium-complexity requests, and the most complex reasoning is completed by a custom 1.2-trillion-parameter Gemini model running on NVIDIA Corporation Blackwell GPUs in Alphabet Inc. Class C cloud. The problem is timing. More than two years have passed since this feature was first promised, during which there were repeated delays and even consumer lawsuits. Munster's framework requires users not only to feel that Siri is "finally usable," but to feel that they "truly cannot do without it"by Muse's standard, this requires Siri to evolve from a passive voice assistant that answers questions into an agent that proactively completes tasks. Whether Apple Inc.'s balanced architecture between privacy and capability is sufficient to support this leap in experience currently lacks sufficient user data for judgment. Tesla, Inc.: first FSD, then Cybercab, then Optimus Munster arranged Tesla, Inc.'s catalysts in a clear sequence: FSD first, Cybercab second, Optimus third. This order itself conveys a judgmentthe further along, the greater the uncertainty. FSD v15 is described by Tesla, Inc. as a "step change," with about 40% of its seven-track parallel software architecture already deployed in the Austin Robotaxi fleet. The parameter scale of this architecture is about ten times that of earlier versions. Tesla, Inc. AI head Ashok Elluswamy said in early September that 24-hour Robotaxi service would arrive "in about the next month," provided that the next planned technical module of v15 completes merging. Currently, the paid Robotaxi network covers six citiesAustin, Dallas, Houston, Miami, Orlando, and Tampawith operating hours from 6 a.m. to 10 p.m. By July, the unsupervised fleet had accumulated more than 380,000 miles driven, and Tesla, Inc. claimed it maintained a "perfect safety record." The company's Robotaxi cost target is $0.30 per mile. As for Cybercab, limited paid rides began in Austin on September 4, but the Robotaxi network still relies mainly on Model Y rather than scaled deployment of purpose-built vehicles without steering wheels or pedals. Musk warned in January that the initial production ramp of Cybercab and Optimus would be "extremely slow." And in July, it was reported that Tesla, Inc. no longer planned to achieve "mass production" of its three newest productsCybercab, Semi, and Megapack 3in 2026. The situation with Optimus is more complex. The Gen 3 design was finalized at the end of June 2026 after an executive review chaired by Musk, ending more than three years of iteration across the internal Alpha, Beta, and C versions. Tesla, Inc. has issued parts procurement guidance to suppliers, aiming to reach a capacity of 1,000 units per week in September and sprint toward 2,500 units per week by year-end. But while Oppenheimer acknowledged that the Cybercab factory is "impressive," it warned that Optimus's production ramp "very likely" faces further delays. Tesla, Inc.'s stock has fallen about 17% year to date, the worst performer among the three names Munster favors. Munster's ordering essentially says: FSD is the only near-term catalyst, Cybercab needs FSD to prove itself first, and Optimus can only be discussed after the first two are running smoothly. SpaceX: the grandest and most distant bet SpaceX's orbital data center plan, Starmind, has the longest timeline and the highest uncertainty among the catalysts Munster listed. SpaceX has partnered with NVIDIA Corporation, and the first Starmind AI1 satellite will use NVIDIA Corporation's Vera Rubin NVL72 rack-scale system. Musk said on an earnings call that SpaceX will "exclusively use NVIDIA Corporation's AI architecture." The CECEP Solar Energy array on the first satellite has an output of up to 210 kilowatts. On the timeline, the target window for the first orbital computing launch is the fourth quarter of 2027, with scaled deployment expected in 2028. SpaceX President Gwynne Shotwell revealed that Anthropic and Alphabet Inc. Class C have already leased orbital capacity. In a filing with the FCC, SpaceX sought authorization to deploy as many as 1 million Starmind satellites, each weighing up to 4,000 kilograms. The primary challenge facing a constellation of this scale is not technology, but launch capacity. Related reports, citing analyst calculations, pointed out that to maintain a constellation of 1 million satellites, SpaceX would need to launch more than nine Starship rockets per day. Yet as of September 2026, Starship had completed only a dozen or so test flights, and the FAA-approved annual launch cap for Florida is 44. Musk once said it would take four years for Starship to achieve a frequency of "more than one launch per hour." The regulatory framework for orbital data centers is likewise in a vacuum. There is currently no license category specifically for "space data centers," and the regulatory authority over large-scale commercial data center satellites in the launch process remains unclear. More importantly, when data is processed in orbit, which country's laws apply and how data sovereignty is definedthere is still no international consensus on these questions. JPMorgan outlined a potential path to 75 gigawatts of orbital computing power by 2031. But if placed in the context of the global data center market, this figure would still require substantial infrastructure investment and international regulatory coordination to materialize.