What top creators are saying about Meta(META)— Page 6

Was reported as a destination for 10% of an investor’s portfolio. Its open-source model development and potential use of its own models were discussed, but no direct buy recommendation or price target was given.

Its 3.6 billion daily users and investment in Scale AI may strengthen its AI position, but the profitability of Muse remains uncertain amid concerns about model efficiency, monetization, and privacy.

Meta could use its large user base to distribute personalized AI products, but views on its models were mixed and concerns include uncertain consumer AI revenue, high costs, privacy, and user control.

Shares rose after news of a partnership with Apple involving Meta's MuseSpark model on Mac Studios. Further collaboration was speculative, although Altimeter reportedly held Meta and increased its portfolio allocation.

Meta was cited as an example of a narrative-driven large-cap trading opportunity around the 'Muse' story, but the guest gave no specific trade, price target, or directional view.

The bullish view rests on Meta's AI capabilities, its large user base as a distribution advantage, and positive developments in AI leadership.

Brad Gerstner said Altimeter moved 10% of its book into Meta, indicating increased allocation.

The speaker doubts Meta will spend $100 billion or $200 billion per year indefinitely and expects its spending to moderate eventually.

Mentioned in connection with discussions about digital identity standards and as an example of a company that can experience drawdowns while compounding over time; Pal gives no specific buy or sell view.

Meta's Muse models were described as competitive with OpenAI; the discussion suggested stronger AI models could benefit semiconductor demand, while acknowledging that efficiency gains might reduce hardware needs.

Its 2022 sell-off to about three standard deviations below trend was viewed as an opportunity because the business model was considered intact; the example is historical, not a current recommendation.

Mentioned mainly in market updates without specific company-level investment commentary.

The host described its business as relatively strong, but shares fell during the selloff and its stake in Anthropic and private AI investments add uncertainty.

Meta’s AI models were mentioned among sources of AI compute demand, with broader demand also attributed to startups and non-AI cloud workloads.

Its advertising business can help fund AI investment and could contain the damage from a failed buildout, though AI spending may divert cash from dividends or buybacks. The speaker considered the remaining former Mag 7 holdings fairly valued or somewhat overvalued.

Cautiously bullish on Meta’s AI potential, with possible benefits to its products; near-term commercial impact remains uncertain because access is limited and broader usefulness is unproven.

Discussed in the context of ad targeting and data pathways involving LiveRamp; no valuation view or stock recommendation was provided.

Meta is grouped among major AI infrastructure spenders. Its established business supports investment, but the broader risk is that AI-related spending may not earn adequate returns.

The discussion raised privacy and data-provenance issues but did not establish that Meta secretly uses ambient phone audio for ad targeting.

An upcoming model referred to as “Watermelon” was mentioned as a possible change in AI capabilities, not as a stock recommendation.

The speaker described Meta as one of the weakest Magnificent 7 stocks during the selloff despite viewing it as relatively inexpensive; the decline was presented as part of broad, indiscriminate selling.

Cited as a major planned investor in AI data centers; no individual stock recommendation is given.

The broader trend was considered positive, though the speaker expected possible consolidation or a pullback before another attempt higher.

The speaker expects Meta may eventually moderate its heavy AI spending and questioned whether such spending can continue indefinitely.

The speaker is bullish on Meta's potential AI comeback, citing its Muse personal agents, early user adoption, and distribution advantage across its platforms. The stock is described as potentially asymmetric, though risks include costly AI spending, compute constraints, product execution, and privacy concerns.

Meta was described as being on a positive trajectory after a major reset. Open-weight models may complement its broader business, though a rumored model release was unconfirmed and no financial-return forecast was offered.

Shares had risen about 40% since earnings, and the Muse rollout was presented as evidence that product quality and distribution matter in AI. Consumer adoption and usefulness remain important uncertainties.

Personalized AI companions could create engagement and monetization opportunities, but incentives to maximize engagement may raise safety, reputational, and regulatory risks.

Described as breaking out of a large symmetrical triangle, potentially creating an entry for a larger move.

Cautiously bullish on Meta’s AI momentum and Muse Wonder, while noting uncertainty about frontier-level capability, user retention, returns on substantial AI spending, and potential scrutiny.

Substantial AI investment could support future products and strengthen Meta’s competitive position, but durable Muse Wonder adoption, monetization, margins, and returns on data-center spending remain unproven.

Meta's Muse Wonderful model reportedly outscored named competitors on general, legal, and finance benchmarks, presenting Meta as a stronger AI competitor while benchmark rankings and commercial outcomes remain uncertain.

Muse Wonder and Muse Wonderful have brought Meta back into the frontier AI competition, and its consumer-app distribution could support adoption of personal and small-business agents. Shares rose 4% after the launch, though inconsistent results, usage limits, and high task costs leave execution and monetization uncertain.

Shares rose after a new AI model release, and the discussion was positive about Meta's AI ambitions and resources. The chart looked strong, though the guest warned against chasing a sharp move and noted uncertainty about AI returns.

Listed at $760 in both August 2025 and October 2026; no specific directional view on the company is stated.

Viewed positively for its distribution and AI product capabilities, including Muse, and its willingness to push back against excessive AI pessimism.

Meta was called the strongest large-cap stock of the day as its Muse model launch and improving investor sentiment drew positive attention; it was approaching its prior high.

The discussion was constructive on Meta's cash flow, distribution, data, and AI capabilities, while emphasizing uncertainty about whether AI products will justify substantial data-center spending.

Its stock rallied about 40% in a month after the Muse personal-agent launch. The discussion emphasized that sustaining investor enthusiasm depends on monetizing AI products.

Announced new AI models.

Shkreli was bullish on Meta's ability to turn AI into products, citing its distribution, product capabilities, and Muse work. No price target or specific buy recommendation was given.

The speaker is increasingly bullish, viewing Meta's AI developments, growth, competitive moat, and valuation as attractive, while emphasizing user trust and safety.

Its Muse Wonder models appeared competitive with leading models, and its AI-agent strategy could support user adoption, business opportunities, and continued infrastructure spending; commercial success remains unproven.

Shkreli favors Meta for its distribution and product capabilities, citing its Muse work and its willingness to pursue AI products.

Meta’s Muse AI model was discussed in relation to agent safety. The discussion noted Meta’s efforts to build safer architecture, while emphasizing that its safeguards need to be judged over time; no clear stock outlook was given.

Shkreli was bullish, citing Meta's distribution, product capabilities, and work on Muse as potential advantages in delivering AI to users.

Investor interest in AI products such as Muse complements an established advertising business that does not depend entirely on AI. Economic weakness and slower advertising demand remain risks.

Mentioned as a competitor in advanced AI; the discussion provides no company-specific assessment or stock recommendation.

Discussed in the context of AI-agent competition, but the speaker said Meta was not his preferred way to invest in the agent theme.

Meta is included in the hyperscalers’ approximately $730 billion combined 2026 capital expenditure guidance. Its Muse AI agent reportedly topped U.S. Apple app charts for a period, though it is unclear whether consumer interest will translate into meaningful revenue.