AASHI TAYLOR ✓

@Aashi5_ · joined 24 May 2021

AI Enthusiast | Investor | Web3 Explorer | AI Insights Researcher l DM to Collaborate 📥 aashilabs8@gmail.com

24 836Followers

24 913Following

125 865Posts total

3.6MViews on collected posts

Against accounts of the same size

9 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views27 910this account2 751median for 10K–100K

Reach, %112.38%this account9.00%median for 10K–100K

Engagement, %0.26%this account1.65%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	27 910	2 751	10.2×
Reach (views ÷ followers)	112.38%	9.00%	12.5×
Engagement rate	0.26%	1.65%	0.16×

Others in this range → Compare with another account → How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

2.1M21 Aug

12.9K

433.9K28 Aug

18.9K

269.3K1 Sep

27.9K

14.2K2 Sep

687.4K

6.4K3 Sep

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.05%21 Aug

0.26%

0.13%28 Aug

0.55%

0.24%1 Sep

0.62%

0.35%2 Sep

0.20%

2.62%3 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.65%.

What the audience does

Likes48.5%2 317 in total

Reposts16.4%783 in total

Replies11.3%539 in total

Quotes10.7%513 in total

Bookmarks13.1%628 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Latest posts

TTS-2 now supports a verbatim tag for precise speech. No more voice agents misreading order numbers or critical details. Sometimes, one simple line is all it takes to fix the problem. Try it now: https://t.co/yapAZynbuX 6.4K views · 84 likes · 83 reposts · 0 replies 03 Sep 2026 Realtime TTS-2 is GA today, now the #1 model on Artificial Analysis and fastest TTS in the world of its class. The research preview got far more usage than expected. That experience went back into research and today's GA model represents the biggest leap in Inworld's history. ht 687.4K views · 838 likes · 218 reposts · 157 replies 02 Sep 2026 AI API costs rarely hurt on day one. The bill explodes once you start scaling—adding agent loops, SaaS background jobs, retries, and multiple vendors, all while stuck paying fixed official rates across separate dashboards. https://t.co/ZuOjCqrOq0 provides one OpenAI-compatible 14.2K views · 29 likes · 4 reposts · 17 replies 02 Sep 2026 A new era of filmmaking is starting. Not because machines create stories, but because more humans now have the ability to tell theirs. https://t.co/JIcVVbb9fR 27.9K views · 87 likes · 85 reposts · 0 replies 01 Sep 2026 17 filmmakers. 17 originals. No crews. No big budgets. Today, they premiere. Meet the filmmakers behind them. Watch now: https://t.co/xMwyo6UGsZ https://t.co/bOUbj7eIbt 269.3K views · 319 likes · 86 reposts · 116 replies 01 Sep 2026 This is basically the behind-the-scenes version of a 10M+ view video. The FlovaAI tutorial is the part I was looking for. 18.9K views · 52 likes · 53 reposts · 0 replies 28 Aug 2026 I built this animation using my own Flova Skill + Seedance 2.5 @Flovaai, allowing me to keep a consistent visual style and workflow throughout the project. AI Video Is Moving Beyond Prompts: Flova Brings “All-in-One” to Agent-Native Video Creation Create your own version with htt 433.9K views · 224 likes · 116 reposts · 121 replies 28 Aug 2026 Sometimes the most useful benchmarks are the ones that show us exactly what isn’t working yet. There’s still a huge gap, but AI4AI-Bench helps make the challenges around recursive self-improvement much easier to see. 12.9K views · 18 likes · 4 reposts · 12 replies 21 Aug 2026 1/ Recursive self-improvement (RSI) depends on agents improving how AI systems are trained —not just tuning hyperparameters, but improving the training algorithm itself. We tested this directly with AI4AI-Bench: 10 real research repositories spanning 10 distinct algorithm https 2.1M views · 666 likes · 134 reposts · 116 replies 21 Aug 2026