The Verge⁠56%

Midjourney bought the astrology app Co-Star ⁠2%

By Emma Roth⁠39%

7/24/2026, 7:06:58 PM

BS Summary: This article contains 2 faulty reasoning types, including Framing Effect, with Appeal to Authority as the most egregious example at 13.8% saturation with 24 hits. Analysis detected 44 faulty-reasoning hits from 174 analyzed words, generating a BS Score of 12.6% and a BS Rank of ⁠2% (21,450 of 21,886 articles). This article is better (less manipulative) than 98.00% of the article peer group.

Midjourney, which has gone from generating AI cat images to full-body ultrasound scans, is getting into a new field: astrology. 
The AI startup announced on Thursday that it has acquired the personalized astrology app Co-Star, as reported earlier by Bloomberg. 
Co-Star is a free app that offers daily horoscopes and allows you to check your compatibility with friends. 
As noted on the app’s FAQ page, it combines human insight, data from NASA, and AI to deliver personalized advice for users each day. 
The terms of Midjourney’s deal, which reportedly closed in spring, haven’t been disclosed. 
Midjourney founder David Holz says Co-Star founder Banu Guler will stay in charge of the app following the acquisition. 
At the same time, Guler will also take on the role of Midjourney’s chief design officer, according to Bloomberg. 
Holz told the outlet that Guler and her team will help Midjourney build the company’s first apps, including one dedicated to image generation. 
Midjourney currently houses its AI models on the web and through Discord. 
Article reasoning-pattern comparisonThis article: 0.0%Emma Roth: 4.5%The Verge: 3.6%Confirmation Bias0.0%This article: 0.0%Emma Roth: 2.1%The Verge: 1.3%Anchoring Bias0.0%This article: 0.0%Emma Roth: 3.8%The Verge: 3.8%Availability Heuristic0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 1.3%Representativeness Heuristic0.0%This article: 0.0%Emma Roth: 0.3%The Verge: 0.7%Hindsight Bias0.0%This article: 0.0%Emma Roth: 1.4%The Verge: 1.7%Overconfidence Bias0.0%This article: 11.5%Emma Roth: 11.1%The Verge: 6.2%Framing Effect11.5%This article: 0.0%Emma Roth: 1.3%The Verge: 0.9%Loss Aversion0.0%This article: 0.0%Emma Roth: 1.4%The Verge: 0.5%Status Quo Bias0.0%This article: 0.0%Emma Roth: 0.4%The Verge: 0.4%Sunk Cost Effect0.0%This article: 0.0%Emma Roth: 7.0%The Verge: 4.0%Optimism Bias0.0%This article: 0.0%Emma Roth: 0.9%The Verge: 2.4%Pessimism Bias0.0%This article: 0.0%Emma Roth: 7.6%The Verge: 9.7%Negativity Bias0.0%This article: 0.0%Emma Roth: 3.6%The Verge: 1.5%Self-Serving Bias0.0%This article: 0.0%Emma Roth: 0.9%The Verge: 0.8%Fundamental Attribution Error0.0%This article: 0.0%Emma Roth: 0.4%The Verge: 0.2%Actor-Observer Bias0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.6%In-Group Bias0.0%This article: 0.0%Emma Roth: 0.5%The Verge: 0.4%Out-Group Homogeneity Bias0.0%This article: 0.0%Emma Roth: 2.8%The Verge: 2.8%Halo Effect0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.2%Horn Effect0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Emma Roth: 2.5%The Verge: 1.8%Recency Bias0.0%This article: 0.0%Emma Roth: 1.1%The Verge: 0.4%Primacy Effect0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.1%Blind-Spot Bias0.0%This article: 0.0%Emma Roth: 0.5%The Verge: 1.1%Ad Hominem0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.3%Straw Man0.0%This article: 13.8%Emma Roth: 8.4%The Verge: 4.0%Appeal to Authority13.8%This article: 0.0%Emma Roth: 0.6%The Verge: 1.6%False Dilemma0.0%This article: 0.0%Emma Roth: 0.4%The Verge: 1.2%Slippery Slope0.0%This article: 0.0%Emma Roth: 0.3%The Verge: 0.2%Circular Reasoning0.0%This article: 0.0%Emma Roth: 3.2%The Verge: 6.8%Hasty Generalization0.0%This article: 0.0%Emma Roth: 0.9%The Verge: 0.2%Red Herring0.0%This article: 0.0%Emma Roth: 0.3%The Verge: 0.7%Bandwagon0.0%This article: 0.0%Emma Roth: 1.4%The Verge: 4.2%Appeal to Emotion0.0%This article: 0.0%Emma Roth: 0.5%The Verge: 1.1%Begging the Question0.0%This article: 0.0%Emma Roth: 4.3%The Verge: 2.3%Post Hoc (False Cause)0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.2%Tu Quoque0.0%This article: 0.0%Emma Roth: 3.2%The Verge: 0.8%Burden of Proof0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.3%Appeal to Nature0.0%This article: 0.0%Emma Roth: 0.3%The Verge: 0.3%Composition/Division0.0%This article: 0.0%Emma Roth: 1.9%The Verge: 3.6%Anecdotal0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.1%No True Scotsman0.0%This article: 0.0%Emma Roth: 4.1%The Verge: 2.2%Ambiguity (Equivocation)0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.1%Middle Ground0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.1%Personal Incredulity0.0%This article: 0.0%Emma Roth: 0.8%The Verge: 0.2%Special Pleading0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.2%Genetic Fallacy0.0%This article: 0.0%Emma Roth: 5.3%The Verge: 2.6%Unattributed Quote0.0%This article: 0.0%Emma Roth: 2.1%The Verge: 1.4%Quote-first Misdirection0.0%This article: 0.0%Emma Roth: 8.9%The Verge: 10.8%Biased Writer Voice0.0%This article: 0.0%Emma Roth: 0.3%The Verge: 1.1%Indoctrination0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 1.6%Politically Left Leaning Bias0.0%This article: 0.0%Emma Roth: 0.0%The Verge: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Emma Roth: 4.2%The Verge: 4.2%Attempt to Sell a Product or S…0.0%

174 words analyzed.

Speakers

1speaker24%attributed speech132writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 6 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageDavid Holz • 19 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageDavid Holz • 23 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverage
Selected voice

David Holz

0%flagged-word coverage
42 attributed words100% of attributed speech33% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

Loading…
Loading…
Loading…

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.