Bring investment ideas, sentiment and mention trends from X, Reddit, YouTube and newsletters into your AI. Connect the conversation to earnings calls, 13F filings and each author’s track record — including how their calls performed.
Wang and Park Ji-hoon connect the battery thesis to energy-storage demand, shipment growth and LFP competitiveness. Wang cites improving margins and earnings as support; these figures are attributed source claims. His valuation reference does not align with the stored call price, so it is not presented as a verified upside target.
Average call price: 82.02 USD → 81.66 USD · −0.44%
Bullish authors emphasize higher starting yields, potential rate declines and the role of duration in a diversified portfolio. Some also cite Treasury buybacks as support for supply and demand. Those arguments depend on inflation and yields stabilizing; their time horizons differ.
Average call price: 81.93 USD → 81.66 USD · −0.33%
The opposing case focuses on energy-driven inflation, fiscal borrowing and pressure on long-term yields. Earl Davis favors shorter duration over the 30-year sector, while other authors warn that buybacks may disappoint. These concerns can coexist with an attractive long-term yield: the disagreement is about entry timing and duration risk.
Asset mismatch in the returned evidence: these theses discuss the LAPTOP memecoin, not Toncoin. The server’s ranking row is retained, but these arguments cannot be used as a TON investment thesis.
Average call price: 1,856,500 KRW → 1,856,000 KRW · −0.03%
The bullish side points to HBM demand, tight memory supply and visibility into AI infrastructure orders. Authors connect pricing and earnings upside to constrained supply, while a minority prefers other exposures. The thesis depends on demand and margins holding as capacity expands; price targets cited on inconsistent reference levels are omitted.
Average call price: 1,856,000 KRW → 1,856,000 KRW · +0.00%
Shin Hyeok-seung is constructive on the company’s earnings but avoids direct exposure. He uses Samsung and SK hynix as market indicators and expects stronger opportunities in other sectors if the large semiconductor names remain stable. This is an allocation preference, not a forecast of collapsing fundamentals.
Average call price: 223.09 USD → 234.48 USD · +5.11%
mkfilko’s first tracked MRVL call is a technical setup: price above key moving averages and a bullish 10/20/50 EMA alignment. The source provides a momentum rationale, not a fundamental valuation model.
Average call price: 17.25 USD → 16.78 USD · −2.72%
Northwise Project’s short thesis focuses on financing: weaker project financing could require more parent-company equity, leading to further share issuance. A lower share price would make each raise more dilutive. The −2.72% figure is the raw share-price move since the call, not a direction-adjusted portfolio return.
Give me a portfolio update for NVDA, MSFT and TSLA.
L/S/A/N = LONG / SHORT / AVOID / NEUTRAL. N: authors without LONG/SHORT/AVOID. Mentions counts distinct authors in 24h, once each. Average is authors per day over the previous 30 days.
Average call price: 225.03 USD → 223.55 USD · −0.66%
The bullish case centers on pricing power and a longer AI infrastructure cycle. Mandeep Singh says customers still buy on Nvidia’s terms, while Gil Luria argues power and permitting constraints could extend the buildout rather than end it. Dominic Rizzo frames the valuation as attractive relative to his growth expectations. Other authors point to larger GPU clusters, hardware upgrades and demand for compute; these are their investment theses, not confirmed future outcomes. Several calls continue an existing bullish stance, rather than represent a first recommendation.
Average call price: 223.75 USD → 223.55 USD · −0.09%
Jared Dillian argues the AI investment boom could eventually create excess data-center capacity and a chip glut, drawing a parallel with the telecom buildout around 2000. He treats the Economist’s Jensen Huang cover as a contrarian sentiment signal. His concern is the next phase of the investment cycle, despite strong current fundamentals.
Average call price: 493.04 USD → 492.19 USD · −0.17%
Brad Smith describes an enforceable agreement with the American Federation of Teachers covering student data, teacher control and AI safeguards in schools. He frames it as a way for Microsoft to become a trusted education-AI partner. Smith is a Microsoft executive, a confirmed affiliation checked on 5 Sep 2026. The Reddit discussion separately treats Microsoft as an OpenAI proxy, while acknowledging that enthusiasm may already be reflected in the price; its breakthrough claims are unverified community commentary.
Average call price: 365.83 USD → 366.5 USD · +0.18%
The Reddit discussion highlights relative strength while the broader market weakens, but warns that this could reverse. Lee Ju-hyeon connects the rebound with reported Slovenia FSD approval and expectations around an October vote, alongside a rising trend channel. So Hyeon-cheol sees Cybercab as a competitive challenge for established automakers. These are momentum, regulatory and product scenarios; the returned calls do not establish that future milestones will be delivered.
No new portfolio-update, earnings-call or 13F events were returned for these tickers in this 24-hour window.
What does Gavin Baker focus on? Show me his track record.
Adjusted return is a shrunk, direction-adjusted average across 22 priceable positions; it is not benchmark alpha. 87 tracked mentions. Performance as of 9 Sep 2026.
First-call returns and average position returns use different samples. Missing prices or currencies are shown as —.
About the author
Gavin Baker founded Atreides Management in 2019 and serves as managing partner and CIO, investing in public and private consumer and technology companies. He worked at Fidelity from 1999 to 2017, managed the Fidelity OTC Portfolio from 2009 to 2017 and previously managed its Wireless, Telecommunications and Pharmaceuticals portfolios. He also helped build Fidelity’s venture investing effort from 2013 to 2017. He studied economics and history at Dartmouth and discusses semiconductors and AI infrastructure on X and investing podcasts.
247,481 X followers · 107 followers among Buzzberg-ranked authors. Follower counts: 10 Aug 2026.
Plot SIVE’s daily mentions and sentiment against its share price over the last 180 complete days. Highlight the biggest attention spike.
Captured 10 Sep 2026 · Complete days through 9 Sep
Mentions count ticker idea rows by publication date, including WATCH and NEUTRAL; they are not unique authors. Period sentiment is weighted by mention count. Price and mentions use separate axes. Lines connect available observations across dates without data, including weekends; missing-day readouts stay unavailable. Price change compares the first and last available closes in the selected period.
Deep dive NVDA. What is the bull case, and who disagrees?
Nvidia’s debate is about how long exceptional AI demand can last. Bulls expect spending to keep flowing through its chips and software; bears think today’s buildout could lead to excess capacity, tougher competition and weaker margins.
2,220 mentions · last 30 days306 mentions · last 7 days (−52% vs. previous week)
Mention counts through 9 Sep · Author views from 9–10 Sep
Why bulls see upside
5 authors in these selected arguments
AI spending keeps flowing to the infrastructure layer
Keith Rabois argues that Nvidia benefits as AI companies grow. Daniel Koss favors the owners and suppliers of AI computing capacity. Their upside case: more AI usage translates into more infrastructure spending and revenue for Nvidia.
Mandeep Singh says customers still buy on Nvidia’s terms. Choi Chang-gyu prefers Nvidia’s position across the AI computing supply chain. Their argument is that this position can support pricing and profits even as rivals compete.
Gil Luria sees power, land and permitting constraints delaying the buildout while demand remains strong. In his view, that spreads investment over a longer period and reduces the risk of an immediate supply glut.
Overbuilding could turn today’s shortage into a glut
Jared Dillian compares the AI boom with the telecom buildout around 2000. He expects investment to overshoot demand, leaving excess data-center capacity and chips. That would threaten future orders even while current results remain strong.
Reddit contributor u/alphajumbo argues that competition and alternatives to CUDA will make Nvidia’s margins harder to sustain. His concern is that rivals gradually weaken Nvidia’s pricing power and reduce profits on each sale.
Financing the ecosystem raises questions about demand
In r/SecurityAnalysis, u/JoeInOR questions why Nvidia invests in AI startups and compute leasing if chip demand is already so strong. He reads those moves as a hedge against a maturing cycle. This interpretation puts customer economics at the center of the bear case.
NVIDIA’s Q2 FY2027 release, published 26 Aug. Reported results and company guidance:
Demand is visible in revenue
Revenue reached $96.2bn, up 106% year on year. The company guides to $108bn next quarter, plus or minus 2%. NVIDIA Q2 FY2027 ↗
Margins are high; the next quarter tests their durability
Gross margin was 75%. Management guides to 74%, plus or minus 0.5 percentage points, next quarter. NVIDIA Q2 FY2027 ↗
The buildout comes with larger commitments
Supply and capacity commitments rose to $279bn from $119bn in the prior quarter, mainly for memory procurement. NVIDIA CFO commentary ↗
What would strengthen either case?
The bull case strengthens if revenue keeps growing while margins hold. The bear case strengthens if orders slow, competition forces lower prices, or customers struggle to fund capacity already planned.
Sources & coverage
Selected author theses were read through Buzzberg MCP; company facts were checked separately against NVIDIA’s release and CFO commentary. Statements above are paraphrases, with links to the source posts and videos.
30-day mentions: 11 Aug–9 Sep. Weekly comparison: 306 on 3–9 Sep versus 632 on 27 Aug–2 Sep. Both weeks contain seven complete UTC days. Captured on 10 Sep; mention totals can change as coverage grows.
Investment ideas, with a track record
We record the price when an author shares an investment idea, then track how it performs. Their entry prices and subsequent returns become part of their track record.
Discover investment ideas
Find fresh calls across X, Reddit, YouTube and newsletters. Compare the bull and bear cases with links to the original research.
Check the track record
See how an author’s recommendations have performed. Compare win rate and returns, and explore individual ideas from entry price to outcome.
Go deeper on a company
Bring together investor views, management commentary from earnings calls and fund positions disclosed in 13F filings when researching a ticker.
Connect in about a minute
Choose your client, add Buzzberg and finish the browser sign-in. Your account connects through OAuth.
In Claude web or Desktop, open Customize → Connectors → + → Add custom connector, name it Buzzberg, and paste this URL.
https://mcp.buzzberg.ai/mcp
Leave OAuth client ID, client secret, and other advanced fields empty.
On ChatGPT web, open Settings → Security and login and turn on Developer mode. Then open Plugins → +, create a developer-mode app named Buzzberg, and paste this URL.
https://mcp.buzzberg.ai/mcp
Choose OAuth when ChatGPT asks for the authentication method.
Add the Streamable HTTP server, then open /mcp in Claude Code and follow the browser sign-in.
claude mcp add --transport http buzzberg https://mcp.buzzberg.ai/mcp
Claude Code stores and refreshes the OAuth connection for you.
Already installed Buzzberg in ChatGPT? Open /apps in Codex to reuse that app authorization. Use direct MCP only when you intentionally want a separate local CLI or IDE connection.
/apps
# Separate local connection only
codex mcp add buzzberg --url https://mcp.buzzberg.ai/mcp
codex mcp login buzzberg
OAuth completes the connection without a personal API key. ChatGPT custom MCP apps currently run on the web; Claude's remote connector follows the same account across web, Desktop, and mobile.
Add Buzzberg to your Cursor MCP configuration, then connect and complete the browser sign-in.
Read the social conversation alongside newsletters, management commentary and institutional filings.
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X / Twitter
Investor posts and emerging theses
r/
Reddit
Community debates and retail sentiment
▶
YouTube
Interviews, podcasts and extracted ideas
≡
Newsletters
Long-form analysis and investment theses
↗
Earnings calls
Management commentary, results and guidance
13F filings
Quarterly holdings disclosed by tracked funds
Frequently asked questions
What can I ask Buzzberg through MCP?+
Ask for recent ideas, a portfolio update, company research or an author’s track record. Your AI uses Buzzberg tools to retrieve the relevant data and build an answer with sources.
What is a call, and how do you track its performance?+
A call is an author’s clear directional view on a ticker — for example, “I’m long SIVE” or “I’m strongly bullish on SIVE.” The first such mention we capture for that author, ticker and direction sets the entry point. We use the price recorded for that date to track subsequent returns. Repeated mentions in the same direction don’t reset the entry. Long and short calls are tracked separately. This measures public calls, not the author’s actual brokerage trades.
Which sources does Buzzberg cover?+
X, Reddit, YouTube, newsletters, earnings calls and stored 13F disclosures from tracked funds. Coverage varies by company, source and available history. Answers retain links to the available originals.
Do I need an API key?+
Connect a supported client to the server URL, then sign in with your Buzzberg account through OAuth. No personal API key is needed. Existing legacy keys continue to work and can be revoked in Profile.
Put the market in the conversation
The sources you follow. The context you need. Inside the AI you already use.
