ipfconline engagement report
@ipfconline1 - 140K followers on X
Measured over 26 original posts from a 30-day window, last computed on September 28, 2026.
Engagement
A typical post picks up 66 interactions against 140K followers, an engagement rate of 0.047%. Measured over 26 original posts, its engagement rate beats 39% of 14,930 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 1.1K times each, and 5.97% of those impressions turn into an interaction. That is about 0.785% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.6 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 07:00 UTC, and Tuesday is the busiest day of the week. Of the 26 posts sampled, 100% carry an image or video and 81% link out. The account's strongest tracked post pulled 4.7K interactions, about 71x its own typical post. Recurring topics include #ai, #agenticai, #responsibleai.
Measured over 26 original posts from a 30-day window, last computed on September 28, 2026. Recurring tags: #ai, #agenticai, #responsibleai.
Compared with accounts its own size
ipfconline's engagement rate beats 39% of the tracked X accounts closest to it in follower count (14,930 accounts, accounts of similar size (decile 7 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 90% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.047%, ipfconline sits above the 25th percentile of the 151,319 accounts in this comparison. That places it in the below the median band, which runs 0.021% to 0.126%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.003% |
| 25th percentile | 0.021% |
| 50th percentile | 0.126% |
| 75th percentile | 0.6% |
| 90th percentile | 2.30% |
| 99th percentile | 84.3% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 07:00 UTC, and Tuesday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 100% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 81% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 100% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 81% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
- Its average post runs 283 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Sep 9, 202671x their median
new deepseek v4.1 flash pricing is absurd... https://t.co/sKZcYZ1P0W
- Sep 21, 202614x their median
acceleration news OpenAI has reportedly automated much of the process of training experimental AI models. Its internal models can write and optimize GPU kernels, run optimization work for weeks from a single example, and even collaborate with other AI agents without human involvement. Employees say this level of automation only became possible in the last few months. 👀 The loop is starting to close.
- Sep 15, 202611x their median
Solar panels now sell for around $0.12 per watt, down from $5–$6 at the turn of the millennium, according to the FT. Ember’s Dave Jones calls them “offensively cheap.” From 2030 onward, energy could become the most significant bottleneck in data center expansion. Solar power is one of the best and most cost-effective energy sources. As long as fusion energy is not yet a viable option, solar power should be expanded on a massive scale. This is because the prices for energy storage are also falling rapidly.
- Sep 19, 20269.1x their median
Banger paper from MIT and Sakana AI. They show that self-improving coding agents work. The best part is that their approach, Self-Improvement via Fast Tree-search (SIFT), runs at a tenth of the CPU hours of DGM. They reach 35.1 percent on Polyglot with o3-mini after 30 expansions. DGM reaches 30.7 percent after 80 nodes of tree search. SIFT does it in under 50 CPU hours and under 5 hours of wall clock. The Qwen3-30B configuration runs its full search at 224 CPU hours and $34 of API spend, a tenth of the DGM baseline. The saving comes from where the money goes. Benchmark evaluation is the runtime bottleneck, so an LLM judge ranks candidate self-modifications first and only promising candidates get evaluated. Judge quality decides the run. On TerminalBench, gpt-5.4-high as the pairwise judge finds a 36.7 percent agent against a 29.2 percent starting point. gpt-5 finds 34.5 percent, and its top-ranked candidate is not the best agent its search produced. Paper: https://t.co/DsTpejqgKF
- Jan 11, 20263.3x their median
50 Top Digital Experts & AI Content Creators / Influencers to Follow in 2026 - 10th Annual Edition 👇 https://t.co/9wK11DWt2f v/ @ipfconline1 --- including, in #AI – #MachineLearning 👇 @geoffreyhinton | @Yoshua_Bengio | @ylecun | @fchollet | @drfeifei | @AndrewYNg | | @karpathy | @DeepLearn007 | @random_walker | @Whats_AI in #HealthTech 👇 @EricTopol | @johnnosta | @EvanKirstel | @ahier | @irmaraste | @enilev | for #DigitalTransformation, let's connect to👇 @jblefevre60 | @antgrasso | @LindaGrass0 | @drsharwood | @dinisguarda | @TamaraMcCleary | @Khulood_Almani | @MarshaCollier | @HaroldSinnott | @FrRonconi | @IanLJones98 | @Nicochan33 | @stratorob | (... and why not us too ;)) concerning #AIEthics - #ResponsibleAI - #Sustainability - #Diversity & #Inclusion 👇 Theodora (Theo) Lau [https://t.co/3xofxPOWVp] | Mia Dand [https://t.co/ToPMkPwcos] | @pierrepinna | @AkwyZ | Women in AI Ethics [https://t.co/7NRX5wqphM] | @BroadenView | Hessie Jones [https://t.co/N07bHmnJZJ] in #Fintech: @SpirosMargaris | Theodora (Theo) Lau | @efipm | @SabineVdL in one of the most important topic, #CyberSecurity & #Privacy 👇 @roxananasoi | @mer__edith & finally in #DataScience, the core of #DeepLearning: @Datasciencectrl | Bob Hayes, PhD [https://t.co/gDXyloJf3Y] | @data_nerd | Bill Schmarzo [https://t.co/Wd4NGkR3gA] | @kdnuggets | @KirkDBorne | Tom Davenport [https://t.co/ATbACAnmXu] | Finally, for French speakers, and art lovers! :)) , we suggest you to follow the great @Ym78200! That's all folks!
- Sep 20, 20262.6x their median
AI is slowly escaping the datacenter. & Compression breakthroughs like this are part of how it gets into everything else.👀 Intel researchers just found a way to push ternary LLMs below the conventional 1.58-bit barrier, without changing a single weight. Their new BITCOS method exploits the unusually high number of zero weights in ternary models. Across 29 ternary LLM checkpoints, zero weights reached up to 51.48%. That allowed BITCOS to reach just 1.485 bits per weight, while preserving the exact ternary weights. In testing, it delivered up to 18% higher CPU decode throughput and up to 27% higher GPU decode throughput. Smaller models. Less memory movement. Faster inference. This could become increasingly important for running powerful AI on PCs, smartphones, robots and edge devices.
- Sep 23, 20261.6x their median
Two big questions, explained simply: 🤔 what is BrainChip 🧠 what is neuromorphic AI https://t.co/sr9LIJ1jQT
- Sep 22, 2026
What Is #AI Agent Memory? Short-Term, Long-Term, Episodic & Semantic Memory Explained https://t.co/PfpPVHja00 @UniteAi Cc @jblefevre60 @sallyeaves @AkwyZ @ahier @rvp @gvalan @HaroldSinnott https://t.co/jxub0bzOxq
- Sep 21, 2026
The #AI #coding security gap: Why faster development demands stronger guardrails https://t.co/vk5X5Wl1rE @BlackDuck_SW #cybersecurity Cc @DeepLearn007 @SpirosMargaris @YvesMulkers @floriansemle @timo_vi @bzarkout @crimson_crypto @rvp @domingonarvaez1 @jblefevre60 @EvanKirstel https://t.co/dwe5RxSKIT
- Sep 16, 2026
LLM Observability: Your Dashboard Is Green. Your Agent Is Wrong https://t.co/7J40UGxC1n v/ @_odsc #AI Cc @CurieuxExplorer @jblefevre60 @gvalan @XavierAncelin @RLDI_Lamy @DeepLearn007 https://t.co/72MJDMYCEs
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 66 interactions against 140K followers, an engagement rate of 0.047%. Measured over 26 original posts, its engagement rate beats 39% of 14,930 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 1.1K times each, and 5.97% of those impressions turn into an interaction. That is about 0.785% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.6 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 07:00 UTC, and Tuesday is the busiest day of the week. Of the 26 posts sampled, 100% carry an image or video and 81% link out. The account's strongest tracked post pulled 4.7K interactions, about 71x its own typical post. Recurring topics include #ai, #agenticai, #responsibleai.
- What is ipfconline's engagement rate on X?
- ipfconline (@ipfconline1) has an engagement rate of 0.047%, based on the median interactions across 26 original posts from the last 30 days against 139,952 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.047%, ipfconline sits above the 25th percentile of the 151,319 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @ipfconline1 have real engagement?
- Its engagement rate beats 39% of the tracked X accounts closest to it in follower count (14,930 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @ipfconline1 post?
- Most posts go out around 07:00 UTC, and Tuesday is its busiest day, at roughly 1.6 posts per day across the measured window.